code stringlengths 2k 1.04M | repo_path stringlengths 5 517 | parsed_code stringlengths 0 1.04M | quality_prob float64 0.02 0.95 | learning_prob float64 0.02 0.93 |
|---|---|---|---|---|
from work_materials.globals import *
import time, datetime
class Trigger:
def __init__(self, trigger_type, text):
self.type = trigger_type
self.text = text
#Типы триггеров - 0 - текст, 1 - видео, 2 - аудио, 3 - фото, 4 - документ, 5 - стикер, 6 - войс
def add_trigger(self, incoming, ... | libs/trigger.py | from work_materials.globals import *
import time, datetime
class Trigger:
def __init__(self, trigger_type, text):
self.type = trigger_type
self.text = text
#Типы триггеров - 0 - текст, 1 - видео, 2 - аудио, 3 - фото, 4 - документ, 5 - стикер, 6 - войс
def add_trigger(self, incoming, ... | 0.143893 | 0.102619 |
__all__ = [
'make_bdist_zipapp',
]
import distutils.core
import distutils.errors
import distutils.log
import stat
import tempfile
import zipfile
from pathlib import Path
def make_bdist_zipapp(
*, python='/usr/bin/env python3', main_optional=False, main=None
):
# pylint: disable=too-many-statements
c... | py/g1/devtools/buildtools/g1/devtools/buildtools/zipapps.py | __all__ = [
'make_bdist_zipapp',
]
import distutils.core
import distutils.errors
import distutils.log
import stat
import tempfile
import zipfile
from pathlib import Path
def make_bdist_zipapp(
*, python='/usr/bin/env python3', main_optional=False, main=None
):
# pylint: disable=too-many-statements
c... | 0.226955 | 0.053477 |
import math
import torch
from catalyst.utils.metrics import mean_average_precision
def test_mean_average_precision_weighted():
"""
Tests for catalyst.utils.metrics.mean_average_precision metric.
"""
target = torch.Tensor([0, 1, 0, 1])
output = torch.Tensor([0.1, 0.2, 0.3, 4])
weight = torch.... | catalyst/utils/metrics/tests/test_mean_average_precision.py | import math
import torch
from catalyst.utils.metrics import mean_average_precision
def test_mean_average_precision_weighted():
"""
Tests for catalyst.utils.metrics.mean_average_precision metric.
"""
target = torch.Tensor([0, 1, 0, 1])
output = torch.Tensor([0.1, 0.2, 0.3, 4])
weight = torch.... | 0.862858 | 0.659446 |
import json
from io import StringIO
import click
from .. import rsf, xsv, Register, Blob, validator
from ..exceptions import RegistersException
from . import utils
@click.group(name="blob")
def blob_group():
"""
Blob operations.
For example, you can validate that a blob '{"country": "ZZ", "name": "Zeta"}... | registers/commands/blob.py | import json
from io import StringIO
import click
from .. import rsf, xsv, Register, Blob, validator
from ..exceptions import RegistersException
from . import utils
@click.group(name="blob")
def blob_group():
"""
Blob operations.
For example, you can validate that a blob '{"country": "ZZ", "name": "Zeta"}... | 0.478773 | 0.298964 |
import six
from tempest import config
from tempest.lib.common.utils import data_utils
from tempest.lib import exceptions as lib_exc
from tempest import test
import testtools
from manila_tempest_tests.tests.api import base
CONF = config.CONF
class ManageNFSSnapshotTest(base.BaseSharesAdminTest):
protocol = 'nfs... | manila_tempest_tests/tests/api/admin/test_snapshot_manage.py |
import six
from tempest import config
from tempest.lib.common.utils import data_utils
from tempest.lib import exceptions as lib_exc
from tempest import test
import testtools
from manila_tempest_tests.tests.api import base
CONF = config.CONF
class ManageNFSSnapshotTest(base.BaseSharesAdminTest):
protocol = 'nfs... | 0.40157 | 0.11422 |
from typing import Callable
from wf_airtable_api_schema.models.educators_schools import *
from wf_airtable_api_schema.models import educators_schools
from . import response as response_models
from . import educators as educators_models
from . import schools as schools_models
from ..airtable.base_school_db import (
... | app/models/educators_schools.py | from typing import Callable
from wf_airtable_api_schema.models.educators_schools import *
from wf_airtable_api_schema.models import educators_schools
from . import response as response_models
from . import educators as educators_models
from . import schools as schools_models
from ..airtable.base_school_db import (
... | 0.665193 | 0.250363 |
import logging
import os
import click
import shutil
from deepfigures import settings
from scripts import build, execute, detectfigures
# Same module as in detectfigures.py in deepfigures_open
# However, this proved to be easiest and least error prone way to use function
def detectfigures(
output_directory,
... | scripts/bulk_detectfigures.py | import logging
import os
import click
import shutil
from deepfigures import settings
from scripts import build, execute, detectfigures
# Same module as in detectfigures.py in deepfigures_open
# However, this proved to be easiest and least error prone way to use function
def detectfigures(
output_directory,
... | 0.47171 | 0.206414 |
import random
"""
none = 0
fruit = 1
head = 2
body = 3
"""
def get_point(size, board):
"""Returns x,y in board which is empty,else None"""
i = 0
# A max try of 20 chances
for _ in range(20):
x = random.randint(0, size - 1)
y = random.randint(0, size - 1)
if board[x][y] == 0:
... | snake/game.py | import random
"""
none = 0
fruit = 1
head = 2
body = 3
"""
def get_point(size, board):
"""Returns x,y in board which is empty,else None"""
i = 0
# A max try of 20 chances
for _ in range(20):
x = random.randint(0, size - 1)
y = random.randint(0, size - 1)
if board[x][y] == 0:
... | 0.380759 | 0.302713 |
import pandas as pd
from .core import BarPLot, HeatMap, ScatterPlot, TablePlot, BoxPlot
from .finegrained import get_fine_grained_figure
from .utils import recursive_update
@pd.api.extensions.register_dataframe_accessor("iplot")
class FrameIplotMethods():
"""DataFrame interactive plotting accessor and method
... | plotlyink/register_pandas_accessors.py | import pandas as pd
from .core import BarPLot, HeatMap, ScatterPlot, TablePlot, BoxPlot
from .finegrained import get_fine_grained_figure
from .utils import recursive_update
@pd.api.extensions.register_dataframe_accessor("iplot")
class FrameIplotMethods():
"""DataFrame interactive plotting accessor and method
... | 0.92406 | 0.375621 |
import types
import operator
import six
class Field(object):
getter_takes_serializer = False
def __init__(self, attr=None, call=False, label=None, required=True):
self.attr = attr
self.call = call
self.label = label
self.required = required
def to_value(self, value):
... | Back-End/Python/External Libraries/Serpy/Serpy-Mini/serpy_.py | import types
import operator
import six
class Field(object):
getter_takes_serializer = False
def __init__(self, attr=None, call=False, label=None, required=True):
self.attr = attr
self.call = call
self.label = label
self.required = required
def to_value(self, value):
... | 0.654564 | 0.156523 |
from __future__ import print_function
import datetime
import dateutil.parser # available on PyPi as `python-dateutil`
import mysql.connector # available on PyPi as `mysql-connector` import nba_py.league
import nba_py.player
from nba_py.constants import CURRENT_SEASON
import os
import sys
from collections import named... | nba_update_censor.py | from __future__ import print_function
import datetime
import dateutil.parser # available on PyPi as `python-dateutil`
import mysql.connector # available on PyPi as `mysql-connector` import nba_py.league
import nba_py.player
from nba_py.constants import CURRENT_SEASON
import os
import sys
from collections import named... | 0.409929 | 0.380299 |
from unittest.mock import call, patch
import pytest
from second_qualification import forms
@pytest.fixture
def form_data():
return {
'emt_id': 42,
'phone_number': '0000000000',
'arrange_callback': forms.ARRANGE_CALLBACK_CHOICES[0][0],
}
def test_second_qualification_form_required()... | second_qualification/tests/test_form.py | from unittest.mock import call, patch
import pytest
from second_qualification import forms
@pytest.fixture
def form_data():
return {
'emt_id': 42,
'phone_number': '0000000000',
'arrange_callback': forms.ARRANGE_CALLBACK_CHOICES[0][0],
}
def test_second_qualification_form_required()... | 0.670177 | 0.362292 |
from objc import *
from Foundation import *
import cmd
import os
import logging
import time
from pprint import pformat
try:
from queue import Queue, Empty
except:
from Queue import Queue, Empty
from pyble.patterns import LoggerObject
class OSXCmd(cmd.Cmd, LoggerObject):
def __init__(self, history_size=... | pyble/osx/console.py | from objc import *
from Foundation import *
import cmd
import os
import logging
import time
from pprint import pformat
try:
from queue import Queue, Empty
except:
from Queue import Queue, Empty
from pyble.patterns import LoggerObject
class OSXCmd(cmd.Cmd, LoggerObject):
def __init__(self, history_size=... | 0.233532 | 0.061848 |
import innertube
import innertube.utils
import innertube.enums
import innertube.errors
import requests
import furl
import json
import re
import urllib.parse
from typing import \
(
Union,
Optional,
)
def watch \
(
*,
video_id: Optional[str] = None,
playlist_id: ... | youtube/operations.py | import innertube
import innertube.utils
import innertube.enums
import innertube.errors
import requests
import furl
import json
import re
import urllib.parse
from typing import \
(
Union,
Optional,
)
def watch \
(
*,
video_id: Optional[str] = None,
playlist_id: ... | 0.483405 | 0.147924 |
import sys
import numpy as np
np.random.seed(int(sys.argv[2]))
import tensorflow as tf
tf.set_random_seed(int(sys.argv[3]))
import utils
import models
from keras.callbacks import EarlyStopping
from keras.preprocessing.image import ImageDataGenerator
from sklearn.model_selection import ShuffleSplit
import matplotlib.pyp... | loyo_testing.py | import sys
import numpy as np
np.random.seed(int(sys.argv[2]))
import tensorflow as tf
tf.set_random_seed(int(sys.argv[3]))
import utils
import models
from keras.callbacks import EarlyStopping
from keras.preprocessing.image import ImageDataGenerator
from sklearn.model_selection import ShuffleSplit
import matplotlib.pyp... | 0.379493 | 0.286543 |
import os
import subprocess
from unittest import mock
from . import *
from .... import *
from mopack.builders.bfg9000 import Bfg9000Builder
from mopack.config import Config
from mopack.path import Path
from mopack.sources import Package
from mopack.sources.apt import AptPackage
from mopack.sources.sdist import Tarbal... | test/unit/sources/sdist/test_tarball.py | import os
import subprocess
from unittest import mock
from . import *
from .... import *
from mopack.builders.bfg9000 import Bfg9000Builder
from mopack.config import Config
from mopack.path import Path
from mopack.sources import Package
from mopack.sources.apt import AptPackage
from mopack.sources.sdist import Tarbal... | 0.467332 | 0.234144 |
from __future__ import division
import time
import numpy as np
import trainer
from params import params as P
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from functools import partial
import logging
import scipy.misc
from parallel import ParallelBatchIterator
from tqdm import tqdm
import os.p... | src/deep/unet/unet_trainer.py | from __future__ import division
import time
import numpy as np
import trainer
from params import params as P
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from functools import partial
import logging
import scipy.misc
from parallel import ParallelBatchIterator
from tqdm import tqdm
import os.p... | 0.609989 | 0.147402 |
from mock import patch, Mock, call
import unittest
from pitmTemperature import pitmTemperature
class TestStringMethods(unittest.TestCase):
def setUp(self):
self.subject = pitmTemperature()
self.subject._log = Mock()
@patch('time.sleep')
@patch('pitmTemperature.pitmTemperature._read_tempe... | brewerslab-orig-slave/test/test_pitmTemperature.py | from mock import patch, Mock, call
import unittest
from pitmTemperature import pitmTemperature
class TestStringMethods(unittest.TestCase):
def setUp(self):
self.subject = pitmTemperature()
self.subject._log = Mock()
@patch('time.sleep')
@patch('pitmTemperature.pitmTemperature._read_tempe... | 0.662251 | 0.283059 |
import os
import pdb # noqa
import shutil
from typing import Any, List, Optional, Tuple
import OpenGL.GL as GL
import OpenGL.GLU as GLU
import glfw
import imageio
import numpy as np
import pygame.time
from torch import Tensor
from contactnets.interaction import PolyGeometry3D
from contactnets.system import SimResult... | contactnets/vis/visualizer_3d.py | import os
import pdb # noqa
import shutil
from typing import Any, List, Optional, Tuple
import OpenGL.GL as GL
import OpenGL.GLU as GLU
import glfw
import imageio
import numpy as np
import pygame.time
from torch import Tensor
from contactnets.interaction import PolyGeometry3D
from contactnets.system import SimResult... | 0.869202 | 0.533519 |
import re
import numpy as np
import copy
import matplotlib.pyplot as plt
from matplotlib.widgets import CheckButtons
from matplotlib.lines import Line2D
from matplotlib.cm import get_cmap
LINE_STYLES = ['--', '-.', '--', ':']
COLORS = [i for i in get_cmap('tab20').colors]
LEAPMOTION = 'Leap Motion'
INTERPOLATION = '... | app/AnybodyResults.py | import re
import numpy as np
import copy
import matplotlib.pyplot as plt
from matplotlib.widgets import CheckButtons
from matplotlib.lines import Line2D
from matplotlib.cm import get_cmap
LINE_STYLES = ['--', '-.', '--', ':']
COLORS = [i for i in get_cmap('tab20').colors]
LEAPMOTION = 'Leap Motion'
INTERPOLATION = '... | 0.49585 | 0.435661 |
from django.contrib import admin
from django.utils.html import format_html
from reversion.admin import VersionAdmin
from elections.models import Election, ElectionResult, PresidentCandidate, PresidentCandidateBiography, \
PresidentCandidatePoliticalExperience, PresidentCandidateWorkExperience, PresidentCandidateAr... | elections/admin.py | from django.contrib import admin
from django.utils.html import format_html
from reversion.admin import VersionAdmin
from elections.models import Election, ElectionResult, PresidentCandidate, PresidentCandidateBiography, \
PresidentCandidatePoliticalExperience, PresidentCandidateWorkExperience, PresidentCandidateAr... | 0.344333 | 0.125306 |
from functools import wraps
from .inspect import TrueSight, shape_shift, WHITELISTED
# If I'm raised, I probably didn't use a TrueSight obj where I needed to
def ensure_truesight(_accessed, *args, **kwargs):
if not _accessed == "__getattr__":
return
arg = args[0]
if arg in WHITELISTED:
ra... | mimics/record.py | from functools import wraps
from .inspect import TrueSight, shape_shift, WHITELISTED
# If I'm raised, I probably didn't use a TrueSight obj where I needed to
def ensure_truesight(_accessed, *args, **kwargs):
if not _accessed == "__getattr__":
return
arg = args[0]
if arg in WHITELISTED:
ra... | 0.627951 | 0.098123 |
from django.test import TestCase
from geokey.contributions.templatetags import kml_tags
from geokey.categories.tests.model_factories import CategoryFactory
class TemplateTagsTest(TestCase):
def test_kml_name(self):
name = kml_tags.kml_name({'display_field': {'value': 'Awesome pub'}})
self.asser... | geokey/contributions/tests/observations/test_templatetags.py |
from django.test import TestCase
from geokey.contributions.templatetags import kml_tags
from geokey.categories.tests.model_factories import CategoryFactory
class TemplateTagsTest(TestCase):
def test_kml_name(self):
name = kml_tags.kml_name({'display_field': {'value': 'Awesome pub'}})
self.asser... | 0.475362 | 0.355439 |
import arcpy
import os
import sys
import datetime
import logging
def copy_sotd_features(feat_list, stamp, log):
for feat in feat_list:
try:
if arcpy.Exists(feat+'_'+stamp):
pass
else:
arcpy.CopyFeatures_management(feat, feat+'_'+stamp)
... | state-of-the-data-for-production/src/backup_sotd_results.py | import arcpy
import os
import sys
import datetime
import logging
def copy_sotd_features(feat_list, stamp, log):
for feat in feat_list:
try:
if arcpy.Exists(feat+'_'+stamp):
pass
else:
arcpy.CopyFeatures_management(feat, feat+'_'+stamp)
... | 0.199776 | 0.144119 |
from abc import ABCMeta, abstractmethod
import six
@six.add_metaclass(ABCMeta)
class Metric(object):
REGISTRY_NAME = "metric"
def __init__(self, *args, **kwargs):
self._flag = self.__class__.__name__
@property
def flag(self):
return self._flag
@flag.setter
def flag(self, fl... | neurst/metrics/metric.py | from abc import ABCMeta, abstractmethod
import six
@six.add_metaclass(ABCMeta)
class Metric(object):
REGISTRY_NAME = "metric"
def __init__(self, *args, **kwargs):
self._flag = self.__class__.__name__
@property
def flag(self):
return self._flag
@flag.setter
def flag(self, fl... | 0.914094 | 0.266068 |
import os
import json
from ast import literal_eval
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
# Load the configuration file (config.json, not config.py)
config_file = os.path.join(BASE_DIR, "config.json")
with open(c... | metadataset/settings.py | import os
import json
from ast import literal_eval
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
# Load the configuration file (config.json, not config.py)
config_file = os.path.join(BASE_DIR, "config.json")
with open(c... | 0.385606 | 0.05848 |
import yaml
import os
from appium import webdriver
global data
class AppiumInit(object):
"""appium server"""
def appium_init(self):
"""读取配置文件的数据"""
global driver
file = open('D:\AutoTest\config\config.yaml', 'r',encoding='utf-8')
data = yaml.load(file)
desired_caps = {}
... | comm/common.py | import yaml
import os
from appium import webdriver
global data
class AppiumInit(object):
"""appium server"""
def appium_init(self):
"""读取配置文件的数据"""
global driver
file = open('D:\AutoTest\config\config.yaml', 'r',encoding='utf-8')
data = yaml.load(file)
desired_caps = {}
... | 0.146911 | 0.102934 |
import torch
import torch.nn as nn
class Baselayer:
def __init__(self, layername: str, id: int, input: int, output: int, statedict: list):
self.layername = layername
self.inputlayer = input
self.outputlayer = output
self.layerid = id
self.inputchannel = 0
self.outpu... | model/prune/Block.py | import torch
import torch.nn as nn
class Baselayer:
def __init__(self, layername: str, id: int, input: int, output: int, statedict: list):
self.layername = layername
self.inputlayer = input
self.outputlayer = output
self.layerid = id
self.inputchannel = 0
self.outpu... | 0.732496 | 0.388676 |
import random
from typing import Any, Callable, Dict, List, Optional, Tuple, Set
import storable
import copy
class FeatureFilter(storable.Storable):
"""
FeatureFilters accept a list of feature dictionaries.
"""
args: tuple
kwargs: dict
filter_name: str
subfilters: list
_filter_prefix... | src/feature_filter.py | import random
from typing import Any, Callable, Dict, List, Optional, Tuple, Set
import storable
import copy
class FeatureFilter(storable.Storable):
"""
FeatureFilters accept a list of feature dictionaries.
"""
args: tuple
kwargs: dict
filter_name: str
subfilters: list
_filter_prefix... | 0.832169 | 0.195902 |
# =============================================================================
__version__ = '$Revision$'
__author__ = '<NAME> <EMAIL>'
__date__ = '2016-02-23'
__all__ = (
'Task' , ## the base class for task
'TaskManager' , ## task manager
)
# ===============================================... | ostap/parallel/mp_pathos.py | # =============================================================================
__version__ = '$Revision$'
__author__ = '<NAME> <EMAIL>'
__date__ = '2016-02-23'
__all__ = (
'Task' , ## the base class for task
'TaskManager' , ## task manager
)
# ===============================================... | 0.276886 | 0.067087 |
# This file was generated by running `python -m dagster.grpc.compile`
# Do not edit this file directly, and do not attempt to recompile it using
# grpc_tools.protoc directly, as several changes must be made to the raw output
# pylint: disable=protected-access
# -*- coding: utf-8 -*-
# Generated by the protocol buffe... | python_modules/dagster/dagster/grpc/__generated__/api_pb2.py |
# This file was generated by running `python -m dagster.grpc.compile`
# Do not edit this file directly, and do not attempt to recompile it using
# grpc_tools.protoc directly, as several changes must be made to the raw output
# pylint: disable=protected-access
# -*- coding: utf-8 -*-
# Generated by the protocol buffe... | 0.365796 | 0.060585 |
import json
import os
import sched
import threading
import time
from hashlib import sha256
import traceback
import arrow
import requests
from ics import Calendar
from tatsu.exceptions import FailedParse
from tools.tools import horodate, process
def cache(entry: dict, scheduler: sched.scheduler = None) -> None:
"... | app/tools/caching.py | import json
import os
import sched
import threading
import time
from hashlib import sha256
import traceback
import arrow
import requests
from ics import Calendar
from tatsu.exceptions import FailedParse
from tools.tools import horodate, process
def cache(entry: dict, scheduler: sched.scheduler = None) -> None:
"... | 0.451568 | 0.174059 |
from django import forms
from portfolios.models import (
Skill,
ProfessionalExperience, ProfessionalExperienceMedia,
Education, EducationMedia,
Certification, CertificationMedia,
Project, ProjectMedia,
Interest,
Testimonial
)
from portfolios.forms import (
SkillForm,
ProfessionalExpe... | backend/portfolios/views.py | from django import forms
from portfolios.models import (
Skill,
ProfessionalExperience, ProfessionalExperienceMedia,
Education, EducationMedia,
Certification, CertificationMedia,
Project, ProjectMedia,
Interest,
Testimonial
)
from portfolios.forms import (
SkillForm,
ProfessionalExpe... | 0.530723 | 0.087876 |
from part1 import (
gamma_board,
gamma_busy_fields,
gamma_delete,
gamma_free_fields,
gamma_golden_move,
gamma_golden_possible,
gamma_move,
gamma_new,
)
"""
scenario: test_random_actions
uuid: 482769947
"""
"""
random actions, total chaos
"""
board = gamma_new(4, 5, 4, 4)
assert board is... | z2/part3/updated_part2_batch/jm/parser_errors_2/482769947.py | from part1 import (
gamma_board,
gamma_busy_fields,
gamma_delete,
gamma_free_fields,
gamma_golden_move,
gamma_golden_possible,
gamma_move,
gamma_new,
)
"""
scenario: test_random_actions
uuid: 482769947
"""
"""
random actions, total chaos
"""
board = gamma_new(4, 5, 4, 4)
assert board is... | 0.828696 | 0.785761 |
import sys
import io
PY2 = (sys.version_info[0] == 2)
if PY2:
import unicodecsv
unicodecsv.field_size_limit(sys.maxsize)
def csvreader(file, encoding=None, **kwargs):
''' Pass encoding to unicodecsv
'''
if encoding is not None:
kwargs['encoding'] = encoding
... | openaddr/compat.py | import sys
import io
PY2 = (sys.version_info[0] == 2)
if PY2:
import unicodecsv
unicodecsv.field_size_limit(sys.maxsize)
def csvreader(file, encoding=None, **kwargs):
''' Pass encoding to unicodecsv
'''
if encoding is not None:
kwargs['encoding'] = encoding
... | 0.266453 | 0.058346 |
from keras.models import Sequential,Model
from keras.layers import LSTM, Dense, Dropout,Input,InputLayer,SpatialDropout1D,Conv1D,MaxPool1D,Flatten,concatenate
from keras.layers.embeddings import Embedding
def lstm(max_len,input_dim,output_dim=None,weight_matrix=None,input_type='wordindex',class_num=1):
model = Seq... | fxy/model.py | from keras.models import Sequential,Model
from keras.layers import LSTM, Dense, Dropout,Input,InputLayer,SpatialDropout1D,Conv1D,MaxPool1D,Flatten,concatenate
from keras.layers.embeddings import Embedding
def lstm(max_len,input_dim,output_dim=None,weight_matrix=None,input_type='wordindex',class_num=1):
model = Seq... | 0.7181 | 0.276825 |
from typing import List, Tuple
import pytest
from target_extraction.pos_taggers import stanford, spacy_tagger
class TestPOSTaggers:
def _en_emoji_sentence(self) -> Tuple[List[str], str]:
return (['Hello', 'how', 'are', 'you', ',', 'with', 'other', "'s", ':)'],
" Hello how are you, with... | tests/pos_taggers_test.py | from typing import List, Tuple
import pytest
from target_extraction.pos_taggers import stanford, spacy_tagger
class TestPOSTaggers:
def _en_emoji_sentence(self) -> Tuple[List[str], str]:
return (['Hello', 'how', 'are', 'you', ',', 'with', 'other', "'s", ':)'],
" Hello how are you, with... | 0.662796 | 0.510192 |
from collections import namedtuple
Customer = namedtuple('Customer', 'name is_88vip')
Product = namedtuple('Product', 'name price')
class Order:
def __init__(self, customer, cart, promotion=None):
"""订单类
Args:
customer (Customer): 该订单的顾客
cart (list): 购物车列表
pr... | src/python/practice/Discount.py |
from collections import namedtuple
Customer = namedtuple('Customer', 'name is_88vip')
Product = namedtuple('Product', 'name price')
class Order:
def __init__(self, customer, cart, promotion=None):
"""订单类
Args:
customer (Customer): 该订单的顾客
cart (list): 购物车列表
pr... | 0.593374 | 0.162446 |
from py_dss_interface.models.Example.ExampleBase import ExampleBase
dss = ExampleBase("13").dss
# Integer methods
print(45 * '=' + ' Integer Methods' + 45 * '=')
print(f'dss.linecodes_count(): {dss.linecodes_count()}')
print(f'dss.linecodes_first(): {dss.linecodes_first()}')
print(f'dss.linecodes_next(): {dss.linecod... | examples/16_Example_LineCodes.py | from py_dss_interface.models.Example.ExampleBase import ExampleBase
dss = ExampleBase("13").dss
# Integer methods
print(45 * '=' + ' Integer Methods' + 45 * '=')
print(f'dss.linecodes_count(): {dss.linecodes_count()}')
print(f'dss.linecodes_first(): {dss.linecodes_first()}')
print(f'dss.linecodes_next(): {dss.linecod... | 0.492188 | 0.211051 |
import logging
from typing import Any, Dict
from flask import Blueprint, request
from bling.helpscout.mailboxes import MAILBOXES_BY_ID, MAILBOXES_BY_TWILIO_PHONE
from bling.clients import (
twilio_transport,
incoming_message_handler,
outgoing_reply_handler,
transport_for_type,
)
from bling.transport... | bling/api.py | import logging
from typing import Any, Dict
from flask import Blueprint, request
from bling.helpscout.mailboxes import MAILBOXES_BY_ID, MAILBOXES_BY_TWILIO_PHONE
from bling.clients import (
twilio_transport,
incoming_message_handler,
outgoing_reply_handler,
transport_for_type,
)
from bling.transport... | 0.564699 | 0.107063 |
import asyncio
import ssl
from typing import Iterator, Optional
from checklisting.result import BaseTaskResult, TaskResult
from checklisting.result.builder import MultiTaskResultBuilder
from checklisting.result.status import TaskResultStatus
from checklisting.task import BaseTask
from checklisting.tasks.socket import ... | src/checklisting/tasks/services/zookeeper.py | import asyncio
import ssl
from typing import Iterator, Optional
from checklisting.result import BaseTaskResult, TaskResult
from checklisting.result.builder import MultiTaskResultBuilder
from checklisting.result.status import TaskResultStatus
from checklisting.task import BaseTask
from checklisting.tasks.socket import ... | 0.619817 | 0.11353 |
import os
import torch
import glob
class Config(object):
def __init__(self):
self.target_task = ['qmsum-latent', # 0: qmsum-latent
'arxiv-latent', # 1: arxiv-latent
'govreport-latent', # 2: govreport-latent
][2]
... | config.py | import os
import torch
import glob
class Config(object):
def __init__(self):
self.target_task = ['qmsum-latent', # 0: qmsum-latent
'arxiv-latent', # 1: arxiv-latent
'govreport-latent', # 2: govreport-latent
][2]
... | 0.512205 | 0.343562 |
import requests
import os
from shutil import rmtree
import tempfile
from config import ensureConfig
from subprocess import call
from cryptography.hazmat.primitives import serialization
from cryptography.hazmat.primitives.asymmetric import rsa
from cryptography.hazmat.backends import default_backend
# print(os.env... | back-end/service.py |
import requests
import os
from shutil import rmtree
import tempfile
from config import ensureConfig
from subprocess import call
from cryptography.hazmat.primitives import serialization
from cryptography.hazmat.primitives.asymmetric import rsa
from cryptography.hazmat.backends import default_backend
# print(os.env... | 0.282889 | 0.086709 |
import warnings
from extra.lists.queue import Queue
class Deque(Queue):
"""
A deque, which is usually pronounced "deck", is a queue-like data structure
that supports insertion and deletion at both the front and the back of the
queue. Deque is a short for "double-ended queue". The deque is more general... | extra/lists/deque.py | import warnings
from extra.lists.queue import Queue
class Deque(Queue):
"""
A deque, which is usually pronounced "deck", is a queue-like data structure
that supports insertion and deletion at both the front and the back of the
queue. Deque is a short for "double-ended queue". The deque is more general... | 0.933741 | 0.678919 |
import os
import shutil
from types import ModuleType
from typing import List
import sys
import pytest
from stubdoc import stubdoc
from stubdoc.stubdoc import _get_callable_names_from_module
def setup() -> None:
_delete_test_modules_and_stubs()
def teardown() -> None:
_delete_test_modules_... | tests/test_stubdoc.py | import os
import shutil
from types import ModuleType
from typing import List
import sys
import pytest
from stubdoc import stubdoc
from stubdoc.stubdoc import _get_callable_names_from_module
def setup() -> None:
_delete_test_modules_and_stubs()
def teardown() -> None:
_delete_test_modules_... | 0.439747 | 0.372049 |
import geopandas
class TileInfo:
""" A class for working with tiling information """
def __init__(self, tile_file: str, catchment_polygon: geopandas.geodataframe.GeoDataFrame):
self._tile_info = geopandas.read_file(tile_file)
self.catchment_polygon = catchment_polygon
self.file_name ... | src/geoapis/geometry.py | import geopandas
class TileInfo:
""" A class for working with tiling information """
def __init__(self, tile_file: str, catchment_polygon: geopandas.geodataframe.GeoDataFrame):
self._tile_info = geopandas.read_file(tile_file)
self.catchment_polygon = catchment_polygon
self.file_name ... | 0.711331 | 0.553988 |
from mics.segment.models.unet_parts import *
import torch.nn as nn
import torch.nn.functional as F
class UNET(nn.Module):
""" Implementation of UNET model as per the paper of Ronneberg when using default values. In case of skip being True
the feature maps are passed through a convolutional layer before being ... | segment/models/models.py | from mics.segment.models.unet_parts import *
import torch.nn as nn
import torch.nn.functional as F
class UNET(nn.Module):
""" Implementation of UNET model as per the paper of Ronneberg when using default values. In case of skip being True
the feature maps are passed through a convolutional layer before being ... | 0.973544 | 0.819677 |
import json
import logging
import platform
import types
import os
import signal
import sys
from time import sleep
from logging.config import fileConfig
from .constants import DEFAULT_LOGGING_PATH
from typing import Optional, List
from diagnostic.broker import Broker
from inbm_lib.windows_service import WindowsService
... | inbm/diagnostic-agent/diagnostic/main.py | import json
import logging
import platform
import types
import os
import signal
import sys
from time import sleep
from logging.config import fileConfig
from .constants import DEFAULT_LOGGING_PATH
from typing import Optional, List
from diagnostic.broker import Broker
from inbm_lib.windows_service import WindowsService
... | 0.554712 | 0.124107 |
import json
import copy
import urllib
from django.shortcuts import get_object_or_404, render, redirect, reverse
from django.http import HttpResponse, HttpResponseRedirect, JsonResponse, Http404
from city_guide.models import Attraction, Category, Ticket, TicketType, Tour, Profile, Order, User, UserBreak
from django.temp... | CityGuide/city_guide/views.py | import json
import copy
import urllib
from django.shortcuts import get_object_or_404, render, redirect, reverse
from django.http import HttpResponse, HttpResponseRedirect, JsonResponse, Http404
from city_guide.models import Attraction, Category, Ticket, TicketType, Tour, Profile, Order, User, UserBreak
from django.temp... | 0.385028 | 0.061848 |
from __clrclasses__.System import Enum as _n_0_t_0
from __clrclasses__.System import IComparable as _n_0_t_1
from __clrclasses__.System import IFormattable as _n_0_t_2
from __clrclasses__.System import IConvertible as _n_0_t_3
from __clrclasses__.System import Array as _n_0_t_4
from __clrclasses__.System import Attribu... | extensions/.stubs/clrclasses/__clrclasses__/System/Security/Permissions/__init__.py | from __clrclasses__.System import Enum as _n_0_t_0
from __clrclasses__.System import IComparable as _n_0_t_1
from __clrclasses__.System import IFormattable as _n_0_t_2
from __clrclasses__.System import IConvertible as _n_0_t_3
from __clrclasses__.System import Array as _n_0_t_4
from __clrclasses__.System import Attribu... | 0.685423 | 0.075858 |
import re, csv, string
from pyspark import SparkConf, SparkContext
from pyspark.sql import Row, SparkSession
from pyspark.sql.functions import rand
from pyspark.ml import Pipeline
from pyspark.ml.feature import Tokenizer, StopWordsRemover, HashingTF
from pyspark.ml.classification import LogisticRegression
from p... | consumerTrump.py | import re, csv, string
from pyspark import SparkConf, SparkContext
from pyspark.sql import Row, SparkSession
from pyspark.sql.functions import rand
from pyspark.ml import Pipeline
from pyspark.ml.feature import Tokenizer, StopWordsRemover, HashingTF
from pyspark.ml.classification import LogisticRegression
from p... | 0.369884 | 0.190988 |
import requests
import urllib3
import os
from helper import bytes32
import time
from config import debug
urllib3.disable_warnings()
class FullNodeClient():
def __init__(self, ssl_directory, host, port, logfile=None):
self.cert_path = os.path.join(ssl_directory, 'full_node/private_full_node.crt')
self.key_path = ... | full_node_client.py | import requests
import urllib3
import os
from helper import bytes32
import time
from config import debug
urllib3.disable_warnings()
class FullNodeClient():
def __init__(self, ssl_directory, host, port, logfile=None):
self.cert_path = os.path.join(ssl_directory, 'full_node/private_full_node.crt')
self.key_path = ... | 0.168139 | 0.1532 |
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from .. import _utilities
from . import outputs
from ._inputs import *
__all__ = [
'GetLogAnalyticsObjectCollectionRulesResult',
'AwaitableGetLogAnalyticsObjectCollectionRulesResult',
'... | sdk/python/pulumi_oci/loganalytics/get_log_analytics_object_collection_rules.py |
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from .. import _utilities
from . import outputs
from ._inputs import *
__all__ = [
'GetLogAnalyticsObjectCollectionRulesResult',
'AwaitableGetLogAnalyticsObjectCollectionRulesResult',
'... | 0.801819 | 0.155015 |
from operator import itemgetter
from collections import Counter
from pygments import highlight
from pygments.lexers import BashLexer
from pygments.formatters import TerminalFormatter
LEXER = BashLexer()
FORMATTER = TerminalFormatter()
class Command(object):
def __init__(self, cmd, line, idx, doc):
self... | searchcmd/commands.py | from operator import itemgetter
from collections import Counter
from pygments import highlight
from pygments.lexers import BashLexer
from pygments.formatters import TerminalFormatter
LEXER = BashLexer()
FORMATTER = TerminalFormatter()
class Command(object):
def __init__(self, cmd, line, idx, doc):
self... | 0.457864 | 0.160102 |
import pymysql
from dbutils.pooled_db import PooledDB
from pymysql.connections import Connection
from pymysql.cursors import DictCursor
class MySQL(object):
def __init__(self, **kwargs):
self._pool = None
self._connection = None
self.options = kwargs
def pool(self) -> ... | ZtjMySQL.py |
import pymysql
from dbutils.pooled_db import PooledDB
from pymysql.connections import Connection
from pymysql.cursors import DictCursor
class MySQL(object):
def __init__(self, **kwargs):
self._pool = None
self._connection = None
self.options = kwargs
def pool(self) -> ... | 0.391406 | 0.112942 |
import importlib
import os
import tensorflow as tf
import random as rn
import matplotlib.pyplot as plt
import hickle as hkl
import numpy as np
import pdb
import argparse
import math
import datetime
import pytz
from keras import backend as K
from keras.models import Model, model_from_json
from keras.layers import In... | CODES_prediction/double_prong_model/train_t_1.py | import importlib
import os
import tensorflow as tf
import random as rn
import matplotlib.pyplot as plt
import hickle as hkl
import numpy as np
import pdb
import argparse
import math
import datetime
import pytz
from keras import backend as K
from keras.models import Model, model_from_json
from keras.layers import In... | 0.752286 | 0.290978 |
import argparse
def default(docstring: str,
interactions: bool = False,
areas: bool = False,
places: bool = False,
add_places_id: bool = True,
add_interaction_strength: bool = True,
):
"""Create a default argument parser with docstring as mai... | mobilib/argparser.py |
import argparse
def default(docstring: str,
interactions: bool = False,
areas: bool = False,
places: bool = False,
add_places_id: bool = True,
add_interaction_strength: bool = True,
):
"""Create a default argument parser with docstring as mai... | 0.614394 | 0.151969 |
from lib.solutions.CHK.services.calculate_total_checkout_value_service import CalculateTotalCheckoutValueService
from lib.solutions.CHK.models.stock_keeping_unit import StockKeepUnit
from lib.solutions.CHK.models.special_offer import SpecialOffer
from lib.solutions.CHK.models.supermarket import SuperMarket
class Test... | test/solution_tests/CHK/services/test_calculate_total_checkout_value_service.py | from lib.solutions.CHK.services.calculate_total_checkout_value_service import CalculateTotalCheckoutValueService
from lib.solutions.CHK.models.stock_keeping_unit import StockKeepUnit
from lib.solutions.CHK.models.special_offer import SpecialOffer
from lib.solutions.CHK.models.supermarket import SuperMarket
class Test... | 0.823293 | 0.531453 |
from django.test import TestCase ,Client
from django.http import HttpRequest
from django.urls import reverse
from django.contrib.auth.models import User
from practise.models import Info,feed
import datetime
from basicapp.models import UserProfileInfo
class ListView_Testing(TestCase):
@classmethod
def setUpTest... | searchBar/practise/tests.py | from django.test import TestCase ,Client
from django.http import HttpRequest
from django.urls import reverse
from django.contrib.auth.models import User
from practise.models import Info,feed
import datetime
from basicapp.models import UserProfileInfo
class ListView_Testing(TestCase):
@classmethod
def setUpTest... | 0.390243 | 0.147248 |
import weakref
import pickle
import functools
_cached_funcs = []
def process_invalidate_cache():
for f in _cached_funcs:
f.cache_clear()
Flyweight._cache.clear()
def invalidate_cache():
from soap import logger
from soap.common.parallel import pool
process_invalidate_cache()
pool.in... | soap/common/cache.py | import weakref
import pickle
import functools
_cached_funcs = []
def process_invalidate_cache():
for f in _cached_funcs:
f.cache_clear()
Flyweight._cache.clear()
def invalidate_cache():
from soap import logger
from soap.common.parallel import pool
process_invalidate_cache()
pool.in... | 0.439988 | 0.164852 |
import time
import json
import math
class pyfeval:
'''
pyeval stands for python fast evaluator
This is an engine to evaluate a mathematical expression fast. The expression is a string in a certain format.
For example the expression ((1+2)-(6x7)>-20) | (3==4) should be translated to 'OR(GT(SUB(ADD(1,2)... | main.py | import time
import json
import math
class pyfeval:
'''
pyeval stands for python fast evaluator
This is an engine to evaluate a mathematical expression fast. The expression is a string in a certain format.
For example the expression ((1+2)-(6x7)>-20) | (3==4) should be translated to 'OR(GT(SUB(ADD(1,2)... | 0.395718 | 0.468243 |
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this
# list of conditions and the following disclaimer.
# * Redistributions in binary form mu... | universal_analytics/tracker.py |
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this
# list of conditions and the following disclaimer.
# * Redistributions in binary form mu... | 0.719285 | 0.097864 |
import argparse
import curses
import time
import sys
sys.path.append("../Dependencies/PythonSharedBuffers/src")
sys.path.append("../../../DistributedSharedMemory")
from Navigation import *
from Serialization import *
import pydsm
SERVERID = 254
CLIENTID = 100
outputs = Outputs()
for i in range(8):
outputs.motor... | src/Visualization/NavigationViewer.py | import argparse
import curses
import time
import sys
sys.path.append("../Dependencies/PythonSharedBuffers/src")
sys.path.append("../../../DistributedSharedMemory")
from Navigation import *
from Serialization import *
import pydsm
SERVERID = 254
CLIENTID = 100
outputs = Outputs()
for i in range(8):
outputs.motor... | 0.257018 | 0.12408 |
from uniback.dictionary.uniback_exceptions import JobQueueFullException
from uniback.dictionary.uniback_constants import JobStatus, JobStatusMap
from threading import Lock
from collections import deque
from uniback import process_manager
class JobQueue:
_job_list = deque()
# we implement thread locking so th... | uniback/tools/job_tools.py | from uniback.dictionary.uniback_exceptions import JobQueueFullException
from uniback.dictionary.uniback_constants import JobStatus, JobStatusMap
from threading import Lock
from collections import deque
from uniback import process_manager
class JobQueue:
_job_list = deque()
# we implement thread locking so th... | 0.670716 | 0.253948 |
# pylint: disable=no-self-use
from typing import Any, Dict, Literal, Optional
from optimade.models import Response
from oteapi.models import ResourceConfig, SessionUpdate
from pydantic import Field
from oteapi_optimade.models.config import OPTIMADEConfig
from oteapi_optimade.models.custom_types import OPTIMADEUrl
c... | oteapi_optimade/models/strategies/parse.py | # pylint: disable=no-self-use
from typing import Any, Dict, Literal, Optional
from optimade.models import Response
from oteapi.models import ResourceConfig, SessionUpdate
from pydantic import Field
from oteapi_optimade.models.config import OPTIMADEConfig
from oteapi_optimade.models.custom_types import OPTIMADEUrl
c... | 0.77768 | 0.059894 |
from django.db import migrations, models
import django.db.models.deletion
import django.utils.timezone
class Migration(migrations.Migration):
initial = True
dependencies = [
('contact', '0004_auto_20201102_1951'),
('product', '0022_auto_20210424_0940'),
('invoice', '0001_initial'),
... | purchase/migrations/0001_initial.py |
from django.db import migrations, models
import django.db.models.deletion
import django.utils.timezone
class Migration(migrations.Migration):
initial = True
dependencies = [
('contact', '0004_auto_20201102_1951'),
('product', '0022_auto_20210424_0940'),
('invoice', '0001_initial'),
... | 0.548432 | 0.145722 |
import numpy as np
def numpy_solution(Xdata, ydata):
# half examples for training
Xtrain, ytrain = Xdata[::2], ydata[::2]
# half examples for validation
Xvalid, yvalid = Xdata[1::2], ydata[1::2]
# closed-form solution to minimize cost (loss) function
# min(cost) = inverse(XT*X) * (XT*y)
... | LinearRegression.py |
import numpy as np
def numpy_solution(Xdata, ydata):
# half examples for training
Xtrain, ytrain = Xdata[::2], ydata[::2]
# half examples for validation
Xvalid, yvalid = Xdata[1::2], ydata[1::2]
# closed-form solution to minimize cost (loss) function
# min(cost) = inverse(XT*X) * (XT*y)
... | 0.67662 | 0.718125 |
from __future__ import annotations
import argparse
import json
import os
import sys
import awkward as ak
import numpy as np
import uproot
import shml
def initial(writeout_dir: str, filepath: str, cut_type: str) -> ak.Array:
print(f"running preprocessing with {cut_type} preselection")
filenames = list(filte... | examples/run_preprocessing.py | from __future__ import annotations
import argparse
import json
import os
import sys
import awkward as ak
import numpy as np
import uproot
import shml
def initial(writeout_dir: str, filepath: str, cut_type: str) -> ak.Array:
print(f"running preprocessing with {cut_type} preselection")
filenames = list(filte... | 0.38549 | 0.173884 |
import pickle
import numpy as np
def load_pickle(pickle_file):
try:
with open(pickle_file, 'rb') as f:
pickle_data = pickle.load(f)
except UnicodeDecodeError as e:
with open(pickle_file, 'rb') as f:
pickle_data = pickle.load(f, encoding='latin1')
except Exception as... | utils.py | import pickle
import numpy as np
def load_pickle(pickle_file):
try:
with open(pickle_file, 'rb') as f:
pickle_data = pickle.load(f)
except UnicodeDecodeError as e:
with open(pickle_file, 'rb') as f:
pickle_data = pickle.load(f, encoding='latin1')
except Exception as... | 0.342791 | 0.226741 |
import psycopg2, psycopg2.extras
import os
import configparser
import random
def ceiling_fox_post():
data = []
with open((os.path.join(os.path.dirname(__file__), 'blobfox')), 'r', encoding='utf-8') as emojilist:
data = emojilist.read().splitlines()
random.seed()
zahl = random.randint(0, len(da... | ceilingfox.py | import psycopg2, psycopg2.extras
import os
import configparser
import random
def ceiling_fox_post():
data = []
with open((os.path.join(os.path.dirname(__file__), 'blobfox')), 'r', encoding='utf-8') as emojilist:
data = emojilist.read().splitlines()
random.seed()
zahl = random.randint(0, len(da... | 0.21917 | 0.119126 |
from .Handlers import handlemsg, handlemsg_all, clientid_to_myself
import ba, _ba
Commands = ['kill', 'heal', 'curse', 'sleep', 'superpunch', 'gloves', 'shield', 'freeze', 'unfreeze', 'godmode']
CommandAliases = ['die', 'heath', 'cur', 'sp', 'punch', 'protect', 'ice', 'thaw', 'gm']
def ExcelCommand(command, arg... | dist/ba_root/mods/chatHandle/ChatCommands/commands/Cheats.py | from .Handlers import handlemsg, handlemsg_all, clientid_to_myself
import ba, _ba
Commands = ['kill', 'heal', 'curse', 'sleep', 'superpunch', 'gloves', 'shield', 'freeze', 'unfreeze', 'godmode']
CommandAliases = ['die', 'heath', 'cur', 'sp', 'punch', 'protect', 'ice', 'thaw', 'gm']
def ExcelCommand(command, arg... | 0.107379 | 0.181046 |
import matplotlib.pyplot as plt
def single_loc_plot():
"""Plot results for single location model."""
mfdgps = [0.600, 0.537, 0.371, 0.322]
ml_benchs = [0.118, 0.117, -0.051, -0.118]
env_benchs = [0.586, 0.439, -0.076]
x_mfdgp = [0., 0.2, 0.4, 0.6]
x_ml = [1., 1.2, 1.4, 1.6]
x_env = [2., 2... | analysis/barplot.py | import matplotlib.pyplot as plt
def single_loc_plot():
"""Plot results for single location model."""
mfdgps = [0.600, 0.537, 0.371, 0.322]
ml_benchs = [0.118, 0.117, -0.051, -0.118]
env_benchs = [0.586, 0.439, -0.076]
x_mfdgp = [0., 0.2, 0.4, 0.6]
x_ml = [1., 1.2, 1.4, 1.6]
x_env = [2., 2... | 0.704262 | 0.693038 |
import numpy as np
from optparse import OptionParser
# get the command line arguments
parser = OptionParser(description="python script to create pvalue and log2(foldchange) filtered ")
parser.add_option('-i', '--input_file',
type=str,
default="results/plotSelection.txt... | scripts/filterForPlots.py | import numpy as np
from optparse import OptionParser
# get the command line arguments
parser = OptionParser(description="python script to create pvalue and log2(foldchange) filtered ")
parser.add_option('-i', '--input_file',
type=str,
default="results/plotSelection.txt... | 0.244093 | 0.211112 |
import numbers
import os
import warnings
import numpy as np
import cv2
import random
import math
from train_config import config as cfg
######May wrong, when use it check it
def Rotate_aug(src,angle,label=None,center=None,scale=1.0):
'''
:param src: src image
:param label: label should be nu... | lib/dataset/augmentor/augmentation.py | import numbers
import os
import warnings
import numpy as np
import cv2
import random
import math
from train_config import config as cfg
######May wrong, when use it check it
def Rotate_aug(src,angle,label=None,center=None,scale=1.0):
'''
:param src: src image
:param label: label should be nu... | 0.337422 | 0.314379 |
import datetime
import math
import matplotlib.pyplot as plt
class Reporter(object):
def __init__(self, name):
self.name = name
self.plots = []
def flushes_per_txg(self, x_txgs, y):
fig, ax = plt.subplots()
ax.set_ylabel('# of flushes', color='r')
ax.set_ylim(0, max(y) +... | Reporter.py | import datetime
import math
import matplotlib.pyplot as plt
class Reporter(object):
def __init__(self, name):
self.name = name
self.plots = []
def flushes_per_txg(self, x_txgs, y):
fig, ax = plt.subplots()
ax.set_ylabel('# of flushes', color='r')
ax.set_ylim(0, max(y) +... | 0.39222 | 0.306138 |
from sys_simulator.channels import BANChannel
from sys_simulator import general as gen
from sys_simulator.q_learning.environments.completeEnvironment5 \
import CompleteEnvironment5
from sys_simulator.dqn.agents.dqnAgent import ExternalDQNAgent
from sys_simulator.dqn.externalDQNFramework import ExternalDQNFramework
... | scripts_dql/script31.py | from sys_simulator.channels import BANChannel
from sys_simulator import general as gen
from sys_simulator.q_learning.environments.completeEnvironment5 \
import CompleteEnvironment5
from sys_simulator.dqn.agents.dqnAgent import ExternalDQNAgent
from sys_simulator.dqn.externalDQNFramework import ExternalDQNFramework
... | 0.374791 | 0.406037 |
import mock
from novaclient.v2 import client as nova_client
from oslotest import mockpatch
from cloudferry.lib.os.compute import nova_compute
from cloudferry.lib.utils import utils
from tests import test
FAKE_CONFIG = {
'src': {'user': 'fake_user',
'password': '<PASSWORD>',
'tenant': '... | tests/lib/os/compute/test_nova.py |
import mock
from novaclient.v2 import client as nova_client
from oslotest import mockpatch
from cloudferry.lib.os.compute import nova_compute
from cloudferry.lib.utils import utils
from tests import test
FAKE_CONFIG = {
'src': {'user': 'fake_user',
'password': '<PASSWORD>',
'tenant': '... | 0.548915 | 0.087759 |
class YouTubeRequest:
""" YouTubeRequest is a data class for making YouTube API calls. """
def __init__(self):
""" Initializes all members (except safe_search) as None.
safe_search is initialized to strict because otherwise
you get some 'interesting' results by default... ""... | videolocale/youtube_request.py | class YouTubeRequest:
""" YouTubeRequest is a data class for making YouTube API calls. """
def __init__(self):
""" Initializes all members (except safe_search) as None.
safe_search is initialized to strict because otherwise
you get some 'interesting' results by default... ""... | 0.666605 | 0.376852 |
import vibrance
PALETTE = (
"000000", # black
"FFFFFF", # white
"FF0000", # red
"00FF00", # green
"0000FF", # blue
"FFFF00", # yellow
"00FFFF", # cyan
"FF00FF", # magenta
"FF8000", # orange
"8000FF", # purple
"0080FF", # light blue
"FF0080", # pink
)
color =... | examples/everything/scripts/keypad_simple.py | import vibrance
PALETTE = (
"000000", # black
"FFFFFF", # white
"FF0000", # red
"00FF00", # green
"0000FF", # blue
"FFFF00", # yellow
"00FFFF", # cyan
"FF00FF", # magenta
"FF8000", # orange
"8000FF", # purple
"0080FF", # light blue
"FF0080", # pink
)
color =... | 0.310276 | 0.314024 |
from typing import List, Optional, Set
from numpy import ndarray
from livia.process.analyzer.object_detection.DetectedObject import DetectedObject
class FrameObjectDetection:
def __init__(self, frame: ndarray, objects: List[DetectedObject], class_names: Optional[Set[str]] = None):
self.__frame: ndarray ... | livia/process/analyzer/object_detection/FrameObjectDetection.py | from typing import List, Optional, Set
from numpy import ndarray
from livia.process.analyzer.object_detection.DetectedObject import DetectedObject
class FrameObjectDetection:
def __init__(self, frame: ndarray, objects: List[DetectedObject], class_names: Optional[Set[str]] = None):
self.__frame: ndarray ... | 0.901415 | 0.400222 |
import datetime
import logging
from typing import List, Tuple
from climsoft_api.api.form_agro1 import schema as form_agro1_schema
from climsoft_api.utils.query import get_count
from fastapi.exceptions import HTTPException
from opencdms.models.climsoft import v4_1_1_core as models
from sqlalchemy.orm.session import Sess... | src/climsoft_api/services/form_agro1_service.py | import datetime
import logging
from typing import List, Tuple
from climsoft_api.api.form_agro1 import schema as form_agro1_schema
from climsoft_api.utils.query import get_count
from fastapi.exceptions import HTTPException
from opencdms.models.climsoft import v4_1_1_core as models
from sqlalchemy.orm.session import Sess... | 0.588416 | 0.082143 |
import unittest
from whoosh import analysis, fields
from whoosh.filedb.filestore import RamStorage
from whoosh.filedb.filewriting import NO_MERGE
class TestReading(unittest.TestCase):
def _create_index(self):
s = fields.Schema(f1 = fields.KEYWORD(stored = True),
f2 = fields.KEYWO... | tests/test_reading.py | import unittest
from whoosh import analysis, fields
from whoosh.filedb.filestore import RamStorage
from whoosh.filedb.filewriting import NO_MERGE
class TestReading(unittest.TestCase):
def _create_index(self):
s = fields.Schema(f1 = fields.KEYWORD(stored = True),
f2 = fields.KEYWO... | 0.439266 | 0.299912 |
from abc import ABC, abstractmethod
from typing import Callable, Dict, Generic, List, Iterable, TypeVar
from .connection import Connection
from ..errors import NotFound
from ..models.user import User
from ..models.guild import Guild
from ..typings import Snowflake
from ..typings.payloads import PartialUserPayload, ... | wumpus/core/manager.py | from abc import ABC, abstractmethod
from typing import Callable, Dict, Generic, List, Iterable, TypeVar
from .connection import Connection
from ..errors import NotFound
from ..models.user import User
from ..models.guild import Guild
from ..typings import Snowflake
from ..typings.payloads import PartialUserPayload, ... | 0.914927 | 0.247407 |
import tensorflow.keras.backend as K
import tensorflow as tf
import numpy as np
# alpha = 1, beta = 0.03, margin = {0.5, 1, 2, 4, 8}
class modals(tf.keras.Model):
def make_feature_extractor(self, layers, input_dim, hidden_size):
inputs = tf.keras.Input(shape=(None, input_dim))
x = inputs
f... | source/modals.py | import tensorflow.keras.backend as K
import tensorflow as tf
import numpy as np
# alpha = 1, beta = 0.03, margin = {0.5, 1, 2, 4, 8}
class modals(tf.keras.Model):
def make_feature_extractor(self, layers, input_dim, hidden_size):
inputs = tf.keras.Input(shape=(None, input_dim))
x = inputs
f... | 0.542621 | 0.504028 |
from datetime import date
from functools import partial
from os import remove
from os.path import exists
import matplotlib.pyplot as plt
from kivy.app import App
from kivy.core.window import Window
from kivy.uix.behaviors import ToggleButtonBehavior
from kivy.uix.boxlayout import BoxLayout
from kivy.uix.button import ... | main.py | from datetime import date
from functools import partial
from os import remove
from os.path import exists
import matplotlib.pyplot as plt
from kivy.app import App
from kivy.core.window import Window
from kivy.uix.behaviors import ToggleButtonBehavior
from kivy.uix.boxlayout import BoxLayout
from kivy.uix.button import ... | 0.50293 | 0.09709 |
import logging
import numpy as np
from mlagents.trainers import UnityException
from mlagents.trainers.models import LearningModel
logger = logging.getLogger("mlagents.trainers")
class UnityPolicyException(UnityException):
"""
Related to errors with the Trainer.
"""
pass
class Policy(object):
"... | ml-agents/mlagents/trainers/policy.py | import logging
import numpy as np
from mlagents.trainers import UnityException
from mlagents.trainers.models import LearningModel
logger = logging.getLogger("mlagents.trainers")
class UnityPolicyException(UnityException):
"""
Related to errors with the Trainer.
"""
pass
class Policy(object):
"... | 0.8709 | 0.408778 |
import smbus
import time
MCP23017_IODIRA = 0x00
MCP23017_IPOLA = 0x02
MCP23017_GPINTENA = 0x04
MCP23017_DEFVALA = 0x06
MCP23017_INTCONA = 0x08
MCP23017_IOCONA = 0x0A
MCP23017_GPPUA = 0x0C
MCP23017_INTFA = 0x0E
MCP23017_INTCAPA = 0x10
MCP23017_GPIOA = 0x12
MCP23017_OLATA = 0x14
MCP23017_IODIRB = 0x01
MCP23017_IPOLB =... | PiPyRelayProp/waveshare-expander/MCP23017-Raspberry-PI-Python-Library/mcp23017 input ouput demo.py | import smbus
import time
MCP23017_IODIRA = 0x00
MCP23017_IPOLA = 0x02
MCP23017_GPINTENA = 0x04
MCP23017_DEFVALA = 0x06
MCP23017_INTCONA = 0x08
MCP23017_IOCONA = 0x0A
MCP23017_GPPUA = 0x0C
MCP23017_INTFA = 0x0E
MCP23017_INTCAPA = 0x10
MCP23017_GPIOA = 0x12
MCP23017_OLATA = 0x14
MCP23017_IODIRB = 0x01
MCP23017_IPOLB =... | 0.088936 | 0.234977 |
from django.db import migrations, models
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='FrontPage',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize... | frontpage/migrations/0001_initial.py |
from django.db import migrations, models
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='FrontPage',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize... | 0.433382 | 0.187542 |
import pytest
from subnet import ip_network, IPv4Network, IPv4Address
from wireguard import (
INTERFACE,
PORT,
Config,
ServerConfig,
Peer,
Server,
)
from wireguard.utils import generate_key, public_key
def test_basic_server():
subnet = '192.168.0.0/24'
address = '192.168.0.1'
se... | tests/test_server.py | import pytest
from subnet import ip_network, IPv4Network, IPv4Address
from wireguard import (
INTERFACE,
PORT,
Config,
ServerConfig,
Peer,
Server,
)
from wireguard.utils import generate_key, public_key
def test_basic_server():
subnet = '192.168.0.0/24'
address = '192.168.0.1'
se... | 0.696165 | 0.387864 |
import boto3
import os
from botocore.exceptions import ClientError
def get_stack_outputs():
"""
Gets asetuapi stack outputs if it exists
"""
cfn = boto3.client("cloudformation")
try:
asetuapi_stack = cfn.describe_stacks(StackName="asetuapi")
except ClientError:
print(
... | generate_exports_and_bundle.py | import boto3
import os
from botocore.exceptions import ClientError
def get_stack_outputs():
"""
Gets asetuapi stack outputs if it exists
"""
cfn = boto3.client("cloudformation")
try:
asetuapi_stack = cfn.describe_stacks(StackName="asetuapi")
except ClientError:
print(
... | 0.34798 | 0.16398 |
import maya.cmds as mc
# globel attributes
srcObjSel=[]
trgObjSel=[]
srcCmpList=[]
trgCmpList=[]
srcTrList=[]
trgTrList=[]
srcGrp=[]
trgGrp=[]
actLayerList = []
currentLayer = []
sourceObj = []
targetObjs = []
sourceShape = []
targetShapes = []
srcPreText=[""]
srcSufText=[""]
trgPreText=[""]
trgSufText=[""]
allLaye... | matchRenderLayers.py | import maya.cmds as mc
# globel attributes
srcObjSel=[]
trgObjSel=[]
srcCmpList=[]
trgCmpList=[]
srcTrList=[]
trgTrList=[]
srcGrp=[]
trgGrp=[]
actLayerList = []
currentLayer = []
sourceObj = []
targetObjs = []
sourceShape = []
targetShapes = []
srcPreText=[""]
srcSufText=[""]
trgPreText=[""]
trgSufText=[""]
allLaye... | 0.177063 | 0.133981 |
from itertools import chain
import numpy as np
from openmdao.core.implicitcomponent import ImplicitComponent
from openmdao.core.constants import INT_DTYPE
import openmdao.func_api as omf
from openmdao.components.func_comp_common import _check_var_name, _copy_with_ignore, _add_options, \
jac_forward, jac_reverse, _... | openmdao/components/implicit_func_comp.py |
from itertools import chain
import numpy as np
from openmdao.core.implicitcomponent import ImplicitComponent
from openmdao.core.constants import INT_DTYPE
import openmdao.func_api as omf
from openmdao.components.func_comp_common import _check_var_name, _copy_with_ignore, _add_options, \
jac_forward, jac_reverse, _... | 0.80213 | 0.454714 |
import os, shutil
from classes.asar import Asar
class BaseUtils:
def prompt_for(self, message, valid_responses=None, default_response='', response_case_sensitive=False):
if valid_responses is None:
valid_responses = []
message = self.process_input_message(message, valid_respons... | classes/utils.py | import os, shutil
from classes.asar import Asar
class BaseUtils:
def prompt_for(self, message, valid_responses=None, default_response='', response_case_sensitive=False):
if valid_responses is None:
valid_responses = []
message = self.process_input_message(message, valid_respons... | 0.240329 | 0.078819 |
import logging
import math
import os
from abc import abstractmethod, ABC
from typing import Sequence, Tuple, List, Union
import numpy as np
import pandas as pd
from .util import cache
from .util.cache import DelayedUpdateHook
from .util.string import objectRepr
from .util.typing import PandasNamedTuple
log = loggin... | src/sensai/distance_metric.py | import logging
import math
import os
from abc import abstractmethod, ABC
from typing import Sequence, Tuple, List, Union
import numpy as np
import pandas as pd
from .util import cache
from .util.cache import DelayedUpdateHook
from .util.string import objectRepr
from .util.typing import PandasNamedTuple
log = loggin... | 0.887302 | 0.367327 |
import logging
import voluptuous as vol
import traceback
from homeassistant import config_entries
from homeassistant.core import callback
from homeassistant.helpers.aiohttp_client import async_create_clientsession
from .api import BWTPerlaApi
from .const import (
CONF_CODE,
CONF_HOST,
CONF_SYNC_INTERVAL,... | custom_components/bwt_perla/config_flow.py | import logging
import voluptuous as vol
import traceback
from homeassistant import config_entries
from homeassistant.core import callback
from homeassistant.helpers.aiohttp_client import async_create_clientsession
from .api import BWTPerlaApi
from .const import (
CONF_CODE,
CONF_HOST,
CONF_SYNC_INTERVAL,... | 0.395484 | 0.079639 |
import os
import cv2
import numpy as np
import pandas as pd
import skimage.io
import torch
from torch.utils.data import Dataset
class SpacenetLocDataset(Dataset):
def __init__(self, data_path, mode, fold=0, folds_csv='folds.csv', transforms=None, normalize=None, multiplier=1,
fix_orientation=Tru... | 5-selim_sef/spacenet_dataset.py | import os
import cv2
import numpy as np
import pandas as pd
import skimage.io
import torch
from torch.utils.data import Dataset
class SpacenetLocDataset(Dataset):
def __init__(self, data_path, mode, fold=0, folds_csv='folds.csv', transforms=None, normalize=None, multiplier=1,
fix_orientation=Tru... | 0.627951 | 0.200577 |
import numpy as np
from magenpy.simulation import GWASSimulator
class AnnotatedGWASSimulator(GWASSimulator):
def __init__(self, bed_files, **kwargs):
super().__init__(bed_files, **kwargs)
# For now, we will restrict to 2 mixture components.
assert self.n_mixtures == 2
self.w_h2 ... | magenpy/simulation/AnnotatedGWASSimulator.py | import numpy as np
from magenpy.simulation import GWASSimulator
class AnnotatedGWASSimulator(GWASSimulator):
def __init__(self, bed_files, **kwargs):
super().__init__(bed_files, **kwargs)
# For now, we will restrict to 2 mixture components.
assert self.n_mixtures == 2
self.w_h2 ... | 0.586404 | 0.572783 |
import os
import datetime
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/2.0/howto/deployment/checklist/
# SECURITY W... | rss_temple/rss_temple/settings.py | import os
import datetime
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/2.0/howto/deployment/checklist/
# SECURITY W... | 0.307462 | 0.098339 |
from symbol import parameters
__author__ = "<NAME>"
import re
import logging
logging.basicConfig(level=logging.INFO)
LOG = logging.getLogger(__name__)
class ParameterCollector:
def __init__(self, config):
self.config = config
def _translate_parameters_to_oversim(self, parameters):
transl... | configurator/configurator/ParamCollector.py | from symbol import parameters
__author__ = "<NAME>"
import re
import logging
logging.basicConfig(level=logging.INFO)
LOG = logging.getLogger(__name__)
class ParameterCollector:
def __init__(self, config):
self.config = config
def _translate_parameters_to_oversim(self, parameters):
transl... | 0.298185 | 0.269308 |
from django.test import TestCase
from ..models import (
Project,
ProjectGroup,
)
class ProjectTest(TestCase):
def setUp(self):
self.project_group = ProjectGroup.objects.create(
name='Pronto World',
slug='pronto-world',
description='Pronto World Group'
)... | rocket/projects/tests/test_models.py | from django.test import TestCase
from ..models import (
Project,
ProjectGroup,
)
class ProjectTest(TestCase):
def setUp(self):
self.project_group = ProjectGroup.objects.create(
name='Pronto World',
slug='pronto-world',
description='Pronto World Group'
)... | 0.521715 | 0.405331 |