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 __future__ import unicode_literals
import os
import re
import getpass
import posixpath
import logging
from subprocess import Popen, PIPE
from dvc.config import Config
from dvc.scheme import Schemes
from dvc.remote.base import RemoteBASE, RemoteCmdError
from dvc.utils import fix_env, tmp_fname
logger = logging... | dvc/remote/hdfs.py | from __future__ import unicode_literals
import os
import re
import getpass
import posixpath
import logging
from subprocess import Popen, PIPE
from dvc.config import Config
from dvc.scheme import Schemes
from dvc.remote.base import RemoteBASE, RemoteCmdError
from dvc.utils import fix_env, tmp_fname
logger = logging... | 0.391639 | 0.09426 |
import adsk.core, adsk.fusion, adsk.cam, traceback
import xml.etree.ElementTree as ET
import glob
import shutil, datetime
def serchTargetFile():
# logicoolのプロファイルのファイルパスをリストで取得
logicoolProfileList = glob.glob(r"C:\Users\*\AppData\Local\Logitech\Logitech Gaming Software\profiles\*.xml")
targetFile = 0
... | UpdateFusionPathForLogicool.py |
import adsk.core, adsk.fusion, adsk.cam, traceback
import xml.etree.ElementTree as ET
import glob
import shutil, datetime
def serchTargetFile():
# logicoolのプロファイルのファイルパスをリストで取得
logicoolProfileList = glob.glob(r"C:\Users\*\AppData\Local\Logitech\Logitech Gaming Software\profiles\*.xml")
targetFile = 0
... | 0.107367 | 0.118054 |
import sublime
import sublime_plugin
import json
import locale
import os
import re
import subprocess
import sys
PY3K = sys.version_info >= (3, 0, 0)
if PY3K:
from .ScalaFormatLib.MergeUtils import merge_code
from .ScalaFormatLib import log
else:
from ScalaFormatLib.MergeUtils import merge_code
from ... | ScalaFormat.py |
import sublime
import sublime_plugin
import json
import locale
import os
import re
import subprocess
import sys
PY3K = sys.version_info >= (3, 0, 0)
if PY3K:
from .ScalaFormatLib.MergeUtils import merge_code
from .ScalaFormatLib import log
else:
from ScalaFormatLib.MergeUtils import merge_code
from ... | 0.299105 | 0.053874 |
from collections import OrderedDict
import pymel.core as pm
import meta.core
attr_rig_components = 'rigComponents'
attr_rig = 'rig'
attr_rig_group = 'rigGroup'
attr_built = 'isBuild'
attr_socket = 'socket'
attr_component_group = 'componentGroup'
attr_controls = 'controls'
attr_bind = 'bindJoints'
attr_start_joint = ... | meta/examples/rig.py | from collections import OrderedDict
import pymel.core as pm
import meta.core
attr_rig_components = 'rigComponents'
attr_rig = 'rig'
attr_rig_group = 'rigGroup'
attr_built = 'isBuild'
attr_socket = 'socket'
attr_component_group = 'componentGroup'
attr_controls = 'controls'
attr_bind = 'bindJoints'
attr_start_joint = ... | 0.742702 | 0.291233 |
from __future__ import print_function
from __future__ import unicode_literals
from __future__ import division
import argparse, nltk
from collections import Counter
from nltk.tokenize import RegexpTokenizer
from nltk.corpus import stopwords
from nltk.stem.wordnet import WordNetLemmatizer
"""
Author: <NAME>, U... | bag_of_words/bow/bag_of_words_final.py |
from __future__ import print_function
from __future__ import unicode_literals
from __future__ import division
import argparse, nltk
from collections import Counter
from nltk.tokenize import RegexpTokenizer
from nltk.corpus import stopwords
from nltk.stem.wordnet import WordNetLemmatizer
"""
Author: <NAME>, U... | 0.577376 | 0.269449 |
import csv
import logging
import os
import re
import sys
from urllib2 import urlopen
from envparse import env
import sql_utils
from lisa_parser import config
logger = logging.getLogger(__file__.split('/')[-1])
def add_get_function(regex, content):
def inner():
try:
aux = re.search(regex, co... | HyperV/WS2012R2/lisa/Infrastructure/lisa-parser/lisa_parser/parse_build.py | import csv
import logging
import os
import re
import sys
from urllib2 import urlopen
from envparse import env
import sql_utils
from lisa_parser import config
logger = logging.getLogger(__file__.split('/')[-1])
def add_get_function(regex, content):
def inner():
try:
aux = re.search(regex, co... | 0.189371 | 0.125065 |
import os
import urllib.request
import tarfile
import numpy as np
import torch
import torch.nn
import torch.nn.functional
import pytorch_lightning as pl
from pytorch_lightning import loggers as pl_loggers
from math import pi
from typing import Sequence, Tuple, Union, Optional, List
from torch.utils.data import DataLo... | instance_segmentation.py | import os
import urllib.request
import tarfile
import numpy as np
import torch
import torch.nn
import torch.nn.functional
import pytorch_lightning as pl
from pytorch_lightning import loggers as pl_loggers
from math import pi
from typing import Sequence, Tuple, Union, Optional, List
from torch.utils.data import DataLo... | 0.886724 | 0.700325 |
from app import app
import json
import os
from flask import jsonify, request
from app.services import user_services, auth_service, faq_services, exame_services
from app.util.decorator import requires_authn, requires_authz
from app.util.exceptions import AbroadException
@app.route('/', methods=['GET'])
def home():
... | app/controllers/default.py | from app import app
import json
import os
from flask import jsonify, request
from app.services import user_services, auth_service, faq_services, exame_services
from app.util.decorator import requires_authn, requires_authz
from app.util.exceptions import AbroadException
@app.route('/', methods=['GET'])
def home():
... | 0.217421 | 0.045522 |
from scriptcore.testing.testcase import TestCase
from scriptcore.console.output.output import Output
class TestOutput(TestCase):
def test_title(self):
"""
Test title-function
:return: void
"""
text = self.rand_str()
text2 = self.rand_str()
output = Out... | tests/console/output/testoutput.py | from scriptcore.testing.testcase import TestCase
from scriptcore.console.output.output import Output
class TestOutput(TestCase):
def test_title(self):
"""
Test title-function
:return: void
"""
text = self.rand_str()
text2 = self.rand_str()
output = Out... | 0.683631 | 0.5144 |
from logging import getLogger
from datetime import datetime
from contextlib import contextmanager
import csv
import os
import io
import threading
import multiprocessing
import warnings
import pandas as pd
import sqlalchemy
logger = getLogger(__name__)
class Connector:
"""
Init Args:
connector: an ob... | sqljob/sqljob.py |
from logging import getLogger
from datetime import datetime
from contextlib import contextmanager
import csv
import os
import io
import threading
import multiprocessing
import warnings
import pandas as pd
import sqlalchemy
logger = getLogger(__name__)
class Connector:
"""
Init Args:
connector: an ob... | 0.526343 | 0.151686 |
import hashlib
from datetime import datetime, timedelta
from typing import Iterable, List, Optional
from flask_sqlalchemy import SQLAlchemy
from sqlalchemy import func, ForeignKey, DateTime
from sqlalchemy.orm.exc import NoResultFound
from servicex.mailgun_adaptor import MailgunAdaptor
db = SQLAlchemy()
max_string_s... | servicex/models.py | import hashlib
from datetime import datetime, timedelta
from typing import Iterable, List, Optional
from flask_sqlalchemy import SQLAlchemy
from sqlalchemy import func, ForeignKey, DateTime
from sqlalchemy.orm.exc import NoResultFound
from servicex.mailgun_adaptor import MailgunAdaptor
db = SQLAlchemy()
max_string_s... | 0.783658 | 0.107813 |
from heapq import nlargest
from collections import deque
try:
from accel import longest_common_substring
except ImportError:
raise RuntimeError("Unable to import the extension")
class PyyMatcher(object):
"""
Class for calculating the similarity of two string objects.
Usage:
>>> obj = PyyMat... | pyymatcher/matcher.py | from heapq import nlargest
from collections import deque
try:
from accel import longest_common_substring
except ImportError:
raise RuntimeError("Unable to import the extension")
class PyyMatcher(object):
"""
Class for calculating the similarity of two string objects.
Usage:
>>> obj = PyyMat... | 0.783119 | 0.268222 |
# 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... | tests/templates/test_subroutines/test_grover.py |
# 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... | 0.953405 | 0.655047 |
from unittest.mock import Mock, call
import pickle
from rnnr.callbacks import checkpoint
def test_ok(tmp_path):
max_epoch, max_saved = 5, 2
objs_values = {
"model": [f"MODEL_{i}" for i in range(max_epoch)],
"opt": [f"OPT_{i}" for i in range(max_epoch)],
}
ckpt_name = "ckpt"
callb... | tests/test_checkpointing.py | from unittest.mock import Mock, call
import pickle
from rnnr.callbacks import checkpoint
def test_ok(tmp_path):
max_epoch, max_saved = 5, 2
objs_values = {
"model": [f"MODEL_{i}" for i in range(max_epoch)],
"opt": [f"OPT_{i}" for i in range(max_epoch)],
}
ckpt_name = "ckpt"
callb... | 0.593963 | 0.449211 |
import librace
class RaceRawParam:
def __init__(self, data, count):
self.data = data
self.count = count
class RaceParam:
def __init__(self, type, delay_time_usec, last_chunk_size):
self.type = type
self.delay_time_usec = delay_time_usec
self.last_chunk_size = last_chu... | bindings/python/race.py | import librace
class RaceRawParam:
def __init__(self, data, count):
self.data = data
self.count = count
class RaceParam:
def __init__(self, type, delay_time_usec, last_chunk_size):
self.type = type
self.delay_time_usec = delay_time_usec
self.last_chunk_size = last_chu... | 0.319015 | 0.226805 |
from collections import OrderedDict
import torch
import torch.nn as nn
from .base import TorchModel
from .utils import get_shape
from .layers import ConvBlock, Upsample, Combine
from .blocks import DefaultBlock
from ..utils import unpack_args
class EncoderModule(nn.ModuleDict):
""" Encoder: create compressed r... | batchflow/models/torch/encoder_decoder.py | from collections import OrderedDict
import torch
import torch.nn as nn
from .base import TorchModel
from .utils import get_shape
from .layers import ConvBlock, Upsample, Combine
from .blocks import DefaultBlock
from ..utils import unpack_args
class EncoderModule(nn.ModuleDict):
""" Encoder: create compressed r... | 0.919367 | 0.274239 |
import rospy
import actionlib
from hanoying_back.msg import GameState, GameMoveAction, GameMoveGoal
from hanoying_back.srv import GameSolveList
rospy.init_node("ctrl")
def on_feedback(feedback):
print(str(feedback.percent*100) + "%")
def on_result(status, result):
# may want to update that if changing game:... | hanoying_front/src/ctrl/ctrl.py | import rospy
import actionlib
from hanoying_back.msg import GameState, GameMoveAction, GameMoveGoal
from hanoying_back.srv import GameSolveList
rospy.init_node("ctrl")
def on_feedback(feedback):
print(str(feedback.percent*100) + "%")
def on_result(status, result):
# may want to update that if changing game:... | 0.227641 | 0.125253 |
import os
import sys
import importlib
from collections import deque
from werkzeug.utils import cached_property, import_string
from jinja2 import Markup
from flask import json
# Find the stack on which we want to store the database connection.
# Starting with Flask 0.9, the _app_ctx_stack is the correct one,
# before th... | spotipo_plugins/__init__.py | import os
import sys
import importlib
from collections import deque
from werkzeug.utils import cached_property, import_string
from jinja2 import Markup
from flask import json
# Find the stack on which we want to store the database connection.
# Starting with Flask 0.9, the _app_ctx_stack is the correct one,
# before th... | 0.544559 | 0.134151 |
import unittest
import numpy
from cqcpy import test_utils
import cqcpy.spin_utils as spin_utils
import cqcpy.cc_equations as cc_equations
class CCRDMTest(unittest.TestCase):
def setUp(self):
pass
def test_1rdm_opt(self):
no = 4
nv = 8
thresh = 1e-12
T1, T2 = test_util... | cqcpy/tests/test_cc_rdm.py | import unittest
import numpy
from cqcpy import test_utils
import cqcpy.spin_utils as spin_utils
import cqcpy.cc_equations as cc_equations
class CCRDMTest(unittest.TestCase):
def setUp(self):
pass
def test_1rdm_opt(self):
no = 4
nv = 8
thresh = 1e-12
T1, T2 = test_util... | 0.411347 | 0.618608 |
import os
import zipfile
from datetime import date, timedelta
from io import BytesIO, StringIO
import httpx
import pandas as pd
import app
from CONSTANTS import *
ISO_2_TO_ISO_3_URL = "https://raw.githubusercontent.com/ilyabo/aiddata/master/data/static/data/countries-iso2-iso3.csv"
POPULATION_URL = (
"http://api... | data_loader.py | import os
import zipfile
from datetime import date, timedelta
from io import BytesIO, StringIO
import httpx
import pandas as pd
import app
from CONSTANTS import *
ISO_2_TO_ISO_3_URL = "https://raw.githubusercontent.com/ilyabo/aiddata/master/data/static/data/countries-iso2-iso3.csv"
POPULATION_URL = (
"http://api... | 0.293101 | 0.271134 |
from fastapi import APIRouter, Depends
from apps.climsoft.services import obsscheduleclass_service
from apps.climsoft.schemas import obsscheduleclass_schema
from utils.response import get_success_response, get_error_response
from sqlalchemy.orm.session import Session
from apps.climsoft.db.engine import SessionLocal
fro... | src/apps/climsoft/controllers/obsscheduleclass_controller.py | from fastapi import APIRouter, Depends
from apps.climsoft.services import obsscheduleclass_service
from apps.climsoft.schemas import obsscheduleclass_schema
from utils.response import get_success_response, get_error_response
from sqlalchemy.orm.session import Session
from apps.climsoft.db.engine import SessionLocal
fro... | 0.328422 | 0.096919 |
from datetime import datetime
from course_lib.Base.Evaluation.Evaluator import *
from src.data_management.New_DataSplitter_leave_k_out import *
from src.data_management.RecSys2019Reader import RecSys2019Reader
from src.data_management.data_reader import get_UCM_train_new
from src.model import new_best_models
from src.... | scripts/hp_tuning/run_tuning_weight_UCM.py | from datetime import datetime
from course_lib.Base.Evaluation.Evaluator import *
from src.data_management.New_DataSplitter_leave_k_out import *
from src.data_management.RecSys2019Reader import RecSys2019Reader
from src.data_management.data_reader import get_UCM_train_new
from src.model import new_best_models
from src.... | 0.404978 | 0.142918 |
import gc
import glob
import json
import nltk
import os
import re
import string
import sys
from collections import OrderedDict
from math import log10
from nltk.corpus import stopwords
from nltk import word_tokenize
from nltk.stem.porter import PorterStemmer
from string import translate
#Global Constants
PATH = sys.a... | ir_project/tokenizer.py | import gc
import glob
import json
import nltk
import os
import re
import string
import sys
from collections import OrderedDict
from math import log10
from nltk.corpus import stopwords
from nltk import word_tokenize
from nltk.stem.porter import PorterStemmer
from string import translate
#Global Constants
PATH = sys.a... | 0.062581 | 0.145874 |
from config import Config
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.common.exceptions import NoSuchElementException
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from dataset import connect
from pla... | crawlers/src/crawler.py | from config import Config
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.common.exceptions import NoSuchElementException
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from dataset import connect
from pla... | 0.13788 | 0.057019 |
"""Optimizing stack usage (pushes and pops)."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import collections
from tensorflow_probability.python.experimental.auto_batching import instructions as inst
def fuse_pop_push(program):
"""Fuses pop+push s... | tensorflow_probability/python/experimental/auto_batching/stack_optimization.py | """Optimizing stack usage (pushes and pops)."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import collections
from tensorflow_probability.python.experimental.auto_batching import instructions as inst
def fuse_pop_push(program):
"""Fuses pop+push s... | 0.794385 | 0.467393 |
import json
import os
import re
import ssl
from urllib.request import Request, urlopen
import pandas as pd
import requests
import usaddress
from bs4 import BeautifulSoup
from . import df_to_tempfile
class Scriptor:
def __init__(self, **kwargs):
self.__dict__.update(kwargs)
def get_hnum(self, addres... | library/script/nycdoc_corrections.py | import json
import os
import re
import ssl
from urllib.request import Request, urlopen
import pandas as pd
import requests
import usaddress
from bs4 import BeautifulSoup
from . import df_to_tempfile
class Scriptor:
def __init__(self, **kwargs):
self.__dict__.update(kwargs)
def get_hnum(self, addres... | 0.379148 | 0.106551 |
from __future__ import absolute_import, division, print_function
import numpy as np
import time
import glob
import sys
from os import makedirs, remove
from os.path import exists, join as pjoin, isfile, isdir
import nibabel
import pickle
import amico.scheme
from amico.preproc import debiasRician
import amico.lut
impor... | amico/core.py | from __future__ import absolute_import, division, print_function
import numpy as np
import time
import glob
import sys
from os import makedirs, remove
from os.path import exists, join as pjoin, isfile, isdir
import nibabel
import pickle
import amico.scheme
from amico.preproc import debiasRician
import amico.lut
impor... | 0.545286 | 0.130562 |
import argparse
from io import StringIO
import os
import shutil
import subprocess
import sys
import tempfile
from unittest import mock
from unittest.mock import patch
from oslo_serialization import jsonutils as json
from tempest.cmd import subunit_describe_calls
from tempest.tests import base
class TestArgumentPar... | tempest/tests/cmd/test_subunit_describe_calls.py |
import argparse
from io import StringIO
import os
import shutil
import subprocess
import sys
import tempfile
from unittest import mock
from unittest.mock import patch
from oslo_serialization import jsonutils as json
from tempest.cmd import subunit_describe_calls
from tempest.tests import base
class TestArgumentPar... | 0.413477 | 0.302365 |
import pandas as pd
import numpy as np
def get_stock_daily_fundamental(dates: np.array, date_position_dic: dict, code_order_dic: dict,
data_path: str) -> dict:
"""
:param data_path:
:param dates: 所以日期的array
:param date_position_dic: 日期到位置的字典
:param code_order_dic: 股... | QBG/DataLoader/data_processors/get_stock_daily_fundamental.py | import pandas as pd
import numpy as np
def get_stock_daily_fundamental(dates: np.array, date_position_dic: dict, code_order_dic: dict,
data_path: str) -> dict:
"""
:param data_path:
:param dates: 所以日期的array
:param date_position_dic: 日期到位置的字典
:param code_order_dic: 股... | 0.24599 | 0.450359 |
class QueryOperatorException(Exception): pass
class BaseQueryOperator(object):
# The symbol that identifies this operator in kwargs
# ie: colname__<symbol>
symbol = None
# The comparator symbol this operator uses in cql
cql_symbol = None
def __unicode__(self):
if self.cql_symbol is N... | cqlengine/operators.py | class QueryOperatorException(Exception): pass
class BaseQueryOperator(object):
# The symbol that identifies this operator in kwargs
# ie: colname__<symbol>
symbol = None
# The comparator symbol this operator uses in cql
cql_symbol = None
def __unicode__(self):
if self.cql_symbol is N... | 0.73431 | 0.282227 |
from json import JSONDecodeError
from django.db import models
from django.utils import timezone
from django.core import serializers
import uuid, logging, json
logger = logging.getLogger(__name__)
# Create your models here.
class ARSModel(models.Model):
class Meta:
abstract = True
def to_dict(self):
... | tr_sys/tr_ars/models.py | from json import JSONDecodeError
from django.db import models
from django.utils import timezone
from django.core import serializers
import uuid, logging, json
logger = logging.getLogger(__name__)
# Create your models here.
class ARSModel(models.Model):
class Meta:
abstract = True
def to_dict(self):
... | 0.393618 | 0.065905 |
import networkx as nx
__author__ = """\n""".join(['<NAME> <<EMAIL>>',
'<NAME> (<EMAIL>)',
'<NAME> (<EMAIL>)'])
__all__ = ['convert_node_labels_to_integers', 'relabel_nodes']
def relabel_nodes(G, mapping, copy=True):
"""Relabel the nodes of the graph G.
Par... | networkx-1.8.1/networkx/relabel.py | import networkx as nx
__author__ = """\n""".join(['<NAME> <<EMAIL>>',
'<NAME> (<EMAIL>)',
'<NAME> (<EMAIL>)'])
__all__ = ['convert_node_labels_to_integers', 'relabel_nodes']
def relabel_nodes(G, mapping, copy=True):
"""Relabel the nodes of the graph G.
Par... | 0.670608 | 0.493592 |
import os
import sys
import getopt
import scipy.stats as stats
import pandas as pd
import numpy as np
import sqlite3
DATA_DIR = os.path.join("..","data")
def connect_db(file_path):
"""
function to connection to aavail database
"""
try:
conn = sqlite3.connect(file_path)
print("...succe... | data-vis-mpl/scripts/aavail-data-ingestor.py |
import os
import sys
import getopt
import scipy.stats as stats
import pandas as pd
import numpy as np
import sqlite3
DATA_DIR = os.path.join("..","data")
def connect_db(file_path):
"""
function to connection to aavail database
"""
try:
conn = sqlite3.connect(file_path)
print("...succe... | 0.232659 | 0.215981 |
import re
REGEX_CLEANER = re.compile(r"[^a-z0-9_@]", re.I)
class AliasExpression(object):
"""
Crea una expresion SQL alias <campo> AS <alias> o simplemente <campo> si no fue provisto un alias
"""
def __init__(self, field_name, alias=None, *args, **kwargs):
super(self.__class__, self).__init__()... | pqb/expressions.py | import re
REGEX_CLEANER = re.compile(r"[^a-z0-9_@]", re.I)
class AliasExpression(object):
"""
Crea una expresion SQL alias <campo> AS <alias> o simplemente <campo> si no fue provisto un alias
"""
def __init__(self, field_name, alias=None, *args, **kwargs):
super(self.__class__, self).__init__()... | 0.489015 | 0.137417 |
from parkour.env import env
from parkour.utils import normalize_name, shorten_name
import aiotfm
import time
import re
MODIFY_RANK = (4 << 8) + 255
ROOM_PASSWORD = (13 << 8) + 255
class Commands(aiotfm.Client):
def __init__(self, *args, **kwargs):
self.next_available_restart = time.time() + 600.0
super().__in... | bots/parkour/commands.py | from parkour.env import env
from parkour.utils import normalize_name, shorten_name
import aiotfm
import time
import re
MODIFY_RANK = (4 << 8) + 255
ROOM_PASSWORD = (13 << 8) + 255
class Commands(aiotfm.Client):
def __init__(self, *args, **kwargs):
self.next_available_restart = time.time() + 600.0
super().__in... | 0.453262 | 0.159774 |
'''Runner for flashing with Black Magic Probe.'''
# https://github.com/blacksphere/blackmagic/wiki
from runners.core import ZephyrBinaryRunner, RunnerCaps
class BlackMagicProbeRunner(ZephyrBinaryRunner):
'''Runner front-end for Black Magic probe.'''
def __init__(self, cfg, gdb_serial):
super(BlackMa... | scripts/west_commands/runners/blackmagicprobe.py | '''Runner for flashing with Black Magic Probe.'''
# https://github.com/blacksphere/blackmagic/wiki
from runners.core import ZephyrBinaryRunner, RunnerCaps
class BlackMagicProbeRunner(ZephyrBinaryRunner):
'''Runner front-end for Black Magic probe.'''
def __init__(self, cfg, gdb_serial):
super(BlackMa... | 0.598312 | 0.089256 |
import os
from . import ColumnType
def write_for_mysql(tab_info, to_dir):
"""MySQL向けのCreateTable文を生成
"""
os.makedirs(to_dir, exist_ok=True)
for t in tab_info:
write_for_mysql_tab(t, to_dir)
return None
def write_for_mysql_tab(tab_info, to_dir, table_sep='_'):
"""MySQL向けのCreateTable文... | src/table_def/write_for_mysql.py | import os
from . import ColumnType
def write_for_mysql(tab_info, to_dir):
"""MySQL向けのCreateTable文を生成
"""
os.makedirs(to_dir, exist_ok=True)
for t in tab_info:
write_for_mysql_tab(t, to_dir)
return None
def write_for_mysql_tab(tab_info, to_dir, table_sep='_'):
"""MySQL向けのCreateTable文... | 0.136752 | 0.120957 |
from typing import Any, List, Literal, TypedDict
from .FHIR_canonical import FHIR_canonical
from .FHIR_Element import FHIR_Element
from .FHIR_markdown import FHIR_markdown
from .FHIR_string import FHIR_string
# A Capability Statement documents a set of capabilities (behaviors) of a FHIR Server for a particular versio... | src/fhir_types/FHIR_CapabilityStatement_Document.py | from typing import Any, List, Literal, TypedDict
from .FHIR_canonical import FHIR_canonical
from .FHIR_Element import FHIR_Element
from .FHIR_markdown import FHIR_markdown
from .FHIR_string import FHIR_string
# A Capability Statement documents a set of capabilities (behaviors) of a FHIR Server for a particular versio... | 0.792022 | 0.450057 |
import time
from concurrent import futures
from oslo_log import log as logging
from ironic_oneviewd.conf import CONF
from ironic_oneviewd import utils
LOG = logging.getLogger(__name__)
ENROLL_PROVISION_STATE = 'enroll'
MANAGEABLE_PROVISION_STATE = 'manageable'
INSPECTION_FAILED_PROVISION_STATE = 'inspect failed'
I... | ironic_oneviewd/node_manager/manage.py |
import time
from concurrent import futures
from oslo_log import log as logging
from ironic_oneviewd.conf import CONF
from ironic_oneviewd import utils
LOG = logging.getLogger(__name__)
ENROLL_PROVISION_STATE = 'enroll'
MANAGEABLE_PROVISION_STATE = 'manageable'
INSPECTION_FAILED_PROVISION_STATE = 'inspect failed'
I... | 0.27406 | 0.142649 |
consonantMap_TwoDCode ={
"b":(1.0,0.5),
"p":(1.0,1.5),
"g":(7.0,0.5),
"k":(7.0,1.5),
"h":(7.0,3.0),
"f":(7.0,4.0),
"d":(12.0,0.5),
"t":(12.0,1.5),
"n":(22.5,0.5),
"l":(22.5,1.5),
"r":( 22.5,2.5),
"zh":(30,1.7),
"z":(30,1.5),
"j":(30.0,0.5),
... | dimsim/utils/maps.py | consonantMap_TwoDCode ={
"b":(1.0,0.5),
"p":(1.0,1.5),
"g":(7.0,0.5),
"k":(7.0,1.5),
"h":(7.0,3.0),
"f":(7.0,4.0),
"d":(12.0,0.5),
"t":(12.0,1.5),
"n":(22.5,0.5),
"l":(22.5,1.5),
"r":( 22.5,2.5),
"zh":(30,1.7),
"z":(30,1.5),
"j":(30.0,0.5),
... | 0.325092 | 0.538073 |
from django.conf import settings
from django.core.urlresolvers import reverse
from django.db import transaction
from django.http import HttpResponse
from django.http import HttpResponseRedirect
from django.shortcuts import get_object_or_404
from django.http import Http404
from django.shortcuts import redirect
from djan... | entrepreneur/views/manage_job_offers.py | from django.conf import settings
from django.core.urlresolvers import reverse
from django.db import transaction
from django.http import HttpResponse
from django.http import HttpResponseRedirect
from django.shortcuts import get_object_or_404
from django.http import Http404
from django.shortcuts import redirect
from djan... | 0.489503 | 0.059949 |
from dataclasses import dataclass
import logging
from typing import ClassVar
from bitey.cpu.arch import EightBitArch
@dataclass
class AddressingMode:
"""
Addressing mode base class
"""
bytes: int
"""
The number of bytes an instruction with this addressing mode takes,
including the instruc... | bitey/cpu/addressing_mode.py | from dataclasses import dataclass
import logging
from typing import ClassVar
from bitey.cpu.arch import EightBitArch
@dataclass
class AddressingMode:
"""
Addressing mode base class
"""
bytes: int
"""
The number of bytes an instruction with this addressing mode takes,
including the instruc... | 0.782579 | 0.545528 |
from typing import Any, List, Dict, Callable
from functools import wraps
from pathlib import PurePath
from dataclasses import dataclass, fields
from dataclasses_jsonschema import JsonSchemaMixin
class Result:
code = int
@dataclass
class Ok(JsonSchemaMixin, Result):
ok: bool = True
code: int = 200
@dataclass
c... | yrest/utils.py | from typing import Any, List, Dict, Callable
from functools import wraps
from pathlib import PurePath
from dataclasses import dataclass, fields
from dataclasses_jsonschema import JsonSchemaMixin
class Result:
code = int
@dataclass
class Ok(JsonSchemaMixin, Result):
ok: bool = True
code: int = 200
@dataclass
c... | 0.772015 | 0.191895 |
from django.test import TestCase
from collection_json import Collection
from testapp.models import Person
try:
from urlparse import urlparse
except ImportError:
from urllib.parse import urlparse
class DictionaryTest(TestCase):
"""tests when the response contains a dictionary"""
def test_no_serializ... | testapp/tests/test_renderer_infer.py |
from django.test import TestCase
from collection_json import Collection
from testapp.models import Person
try:
from urlparse import urlparse
except ImportError:
from urllib.parse import urlparse
class DictionaryTest(TestCase):
"""tests when the response contains a dictionary"""
def test_no_serializ... | 0.661048 | 0.465266 |
import json
from typing import Dict, List
import numpy
from matplotlib import pyplot as plt
from GPErks.constants import HEIGHT, WIDTH
class TrainStats:
def __init__(self, metrics_names):
self.current_epoch: int = 0
self.best_epoch: int = 0
self.train_loss: List[float] = []
self.... | GPErks/train/train_stats.py | import json
from typing import Dict, List
import numpy
from matplotlib import pyplot as plt
from GPErks.constants import HEIGHT, WIDTH
class TrainStats:
def __init__(self, metrics_names):
self.current_epoch: int = 0
self.best_epoch: int = 0
self.train_loss: List[float] = []
self.... | 0.761184 | 0.437403 |
from buzzblog.gen import TAccountService
from buzzblog.base_client import BaseClient
class Client(BaseClient):
def __init__(self, ip_address, port, timeout=30000, logger=None):
super().__init__(TAccountService.Client, ip_address, port, timeout, logger)
def authenticate_user(self, request_metadata, username,... | app/wordfilter/service/tests/site-packages/buzzblog/account_client.py |
from buzzblog.gen import TAccountService
from buzzblog.base_client import BaseClient
class Client(BaseClient):
def __init__(self, ip_address, port, timeout=30000, logger=None):
super().__init__(TAccountService.Client, ip_address, port, timeout, logger)
def authenticate_user(self, request_metadata, username,... | 0.549641 | 0.057865 |
import django_filters
from django.db.models import Q
from rest_framework_gis.filterset import GeoFilterSet
from django_filters.rest_framework import FilterSet
from rest_framework_gis.filters import GeometryFilter
from vocabs.models import SkosConcept
from . models import TempSpatial, Source
class SourceListFilter(dj... | shps/filters.py | import django_filters
from django.db.models import Q
from rest_framework_gis.filterset import GeoFilterSet
from django_filters.rest_framework import FilterSet
from rest_framework_gis.filters import GeometryFilter
from vocabs.models import SkosConcept
from . models import TempSpatial, Source
class SourceListFilter(dj... | 0.556641 | 0.092115 |
import sys
from typing import TypeVar, Generic, List, Any
S = TypeVar('S') # Generic Sequence
I = TypeVar('I') # Generic Item
class SubSeq(Generic[S]):
"""
Represents a SubSequence
"""
def __init__(self):
pass
class CommonSubSeq(Generic[S], SubSeq[S]):
"""
Represents a sub-seque... | automergetool/amt_lcs.py |
import sys
from typing import TypeVar, Generic, List, Any
S = TypeVar('S') # Generic Sequence
I = TypeVar('I') # Generic Item
class SubSeq(Generic[S]):
"""
Represents a SubSequence
"""
def __init__(self):
pass
class CommonSubSeq(Generic[S], SubSeq[S]):
"""
Represents a sub-seque... | 0.7237 | 0.34762 |
import datetime
import os
from subprocess import PIPE, run
BUILD_SOURCE_DIR = os.path.join(
os.path.dirname(__file__), '../../', 'build/bench')
builds = ['build_noopt', 'build_mkl', 'build_blas']
def iter_executables(*executables):
for build in builds:
if not os.path.exists(os.path.join(BUILD_SOUR... | tools/benchmark/benchmark_util.py |
import datetime
import os
from subprocess import PIPE, run
BUILD_SOURCE_DIR = os.path.join(
os.path.dirname(__file__), '../../', 'build/bench')
builds = ['build_noopt', 'build_mkl', 'build_blas']
def iter_executables(*executables):
for build in builds:
if not os.path.exists(os.path.join(BUILD_SOUR... | 0.222278 | 0.062217 |
import tensorflow as tf
from stagedml.models.transformer.imports import ( LearningRateScheduler,
LearningRateFn, BASE_PARAMS, Subtokenizer, train_input_fn,
map_data_for_transformer_fn )
from stagedml.models.transformer.model import ( create_train_model,
create_eval_model, create_optimizer )
from typing i... | src/stagedml/models/transformer/data.py | import tensorflow as tf
from stagedml.models.transformer.imports import ( LearningRateScheduler,
LearningRateFn, BASE_PARAMS, Subtokenizer, train_input_fn,
map_data_for_transformer_fn )
from stagedml.models.transformer.model import ( create_train_model,
create_eval_model, create_optimizer )
from typing i... | 0.725746 | 0.255971 |
import os
from setuptools import find_packages
from pkg_resources import parse_version
here = os.path.abspath(os.path.dirname(__file__))
about = {}
with open(os.path.join(here, 'camelot', '__version__.py'), 'r') as f:
exec(f.read(), about)
with open('README.md', 'r') as f:
readme = f.read()
def setup_pack... | setup.py |
import os
from setuptools import find_packages
from pkg_resources import parse_version
here = os.path.abspath(os.path.dirname(__file__))
about = {}
with open(os.path.join(here, 'camelot', '__version__.py'), 'r') as f:
exec(f.read(), about)
with open('README.md', 'r') as f:
readme = f.read()
def setup_pack... | 0.322419 | 0.061227 |
import sys
import os
os.environ['TF_CPP_MIN_LOG_LEVEL']='3'
from shutil import rmtree
import numpy as np
import pandas as pd
import configargparse
from tqdm import tqdm
import ast
import h5py
import cv2
import time
from ct_segnet.model_utils.losses import custom_objects_dict
from ct_segnet.data_utils import patch_ma... | bin/run_segmenter.py | import sys
import os
os.environ['TF_CPP_MIN_LOG_LEVEL']='3'
from shutil import rmtree
import numpy as np
import pandas as pd
import configargparse
from tqdm import tqdm
import ast
import h5py
import cv2
import time
from ct_segnet.model_utils.losses import custom_objects_dict
from ct_segnet.data_utils import patch_ma... | 0.274254 | 0.133246 |
import json
from alipay.aop.api.constant.ParamConstants import *
from alipay.aop.api.domain.MultiCurrencyMoneyOpenApi import MultiCurrencyMoneyOpenApi
class AlipayBossFncSettleSettlementbillCancelModel(object):
def __init__(self):
self._cancel_amount = None
self._out_biz_no = None
self._... | alipay/aop/api/domain/AlipayBossFncSettleSettlementbillCancelModel.py | import json
from alipay.aop.api.constant.ParamConstants import *
from alipay.aop.api.domain.MultiCurrencyMoneyOpenApi import MultiCurrencyMoneyOpenApi
class AlipayBossFncSettleSettlementbillCancelModel(object):
def __init__(self):
self._cancel_amount = None
self._out_biz_no = None
self._... | 0.535341 | 0.077797 |
import logging
from .exceptions import Cannot_login
from .regex import re_show, re_video, re_lenguage, re_csrf_token
from chibi_dl.site.base.site import Site as Site_base
logger = logging.getLogger( "chibi_dl.sites.crunchyroll" )
class Site( Site_base ):
@property
def token( self ):
if self.parent:... | chibi_dl/site/crunchyroll/site.py | import logging
from .exceptions import Cannot_login
from .regex import re_show, re_video, re_lenguage, re_csrf_token
from chibi_dl.site.base.site import Site as Site_base
logger = logging.getLogger( "chibi_dl.sites.crunchyroll" )
class Site( Site_base ):
@property
def token( self ):
if self.parent:... | 0.326701 | 0.134236 |
import numpy as np
import pandas as pd
from pandas import DataFrame, Series, date_range, timedelta_range
import pandas._testing as tm
class TestTimeSeries:
def test_contiguous_boolean_preserve_freq(self):
rng = date_range("1/1/2000", "3/1/2000", freq="B")
mask = np.zeros(len(rng), dtype=bool)
... | pandas/tests/series/test_timeseries.py | import numpy as np
import pandas as pd
from pandas import DataFrame, Series, date_range, timedelta_range
import pandas._testing as tm
class TestTimeSeries:
def test_contiguous_boolean_preserve_freq(self):
rng = date_range("1/1/2000", "3/1/2000", freq="B")
mask = np.zeros(len(rng), dtype=bool)
... | 0.717903 | 0.58945 |
from __future__ import unicode_literals
import time
from mock import patch, Mock
from nose.tools import raises
from boto.cloudfront.exception import CloudFrontServerError
from tests import TestCase, with_settings
from catsnap import Client
from catsnap.table.image import Image
from catsnap.table.task_transaction impo... | tests/worker/test_invalidate.py | from __future__ import unicode_literals
import time
from mock import patch, Mock
from nose.tools import raises
from boto.cloudfront.exception import CloudFrontServerError
from tests import TestCase, with_settings
from catsnap import Client
from catsnap.table.image import Image
from catsnap.table.task_transaction impo... | 0.578567 | 0.124027 |
from langParser import Parser
from executor import Executor
from langEnums import *
# This class is used to store variables and function
class SymbolTable:
def __init__(self):
self.variableTable = {"true":(Types.Boolean, 1), "false":(Types.Boolean, 0)}
self.functionTable = {}
self.enableFunctionFeature = False
... | lexer.py | from langParser import Parser
from executor import Executor
from langEnums import *
# This class is used to store variables and function
class SymbolTable:
def __init__(self):
self.variableTable = {"true":(Types.Boolean, 1), "false":(Types.Boolean, 0)}
self.functionTable = {}
self.enableFunctionFeature = False
... | 0.260389 | 0.203569 |
import re
import json
import os
import sys
import redis
import logging
import numpy as np
from flask import Flask, request
from flask_cors import CORS, cross_origin
from PIL import Image, ImageEnhance
from keras.models import model_from_json
from keras.optimizers import RMSprop
app = Flask(__name__)
cors = CORS(app)
... | src/python/project/prediction_app/prediction.py | import re
import json
import os
import sys
import redis
import logging
import numpy as np
from flask import Flask, request
from flask_cors import CORS, cross_origin
from PIL import Image, ImageEnhance
from keras.models import model_from_json
from keras.optimizers import RMSprop
app = Flask(__name__)
cors = CORS(app)
... | 0.407687 | 0.177383 |
from PyQt5.QtWidgets import QDialog, QDialogButtonBox, QVBoxLayout, QGroupBox, QFormLayout, QLabel, QComboBox, QCheckBox
class SettingsDialog(QDialog):
def __init__(self, settings, controller):
super(SettingsDialog, self).__init__()
self.settings = settings
self.controller = controller
... | GUI/Settings.py | from PyQt5.QtWidgets import QDialog, QDialogButtonBox, QVBoxLayout, QGroupBox, QFormLayout, QLabel, QComboBox, QCheckBox
class SettingsDialog(QDialog):
def __init__(self, settings, controller):
super(SettingsDialog, self).__init__()
self.settings = settings
self.controller = controller
... | 0.648021 | 0.086285 |
from pathlib import Path
from typing import Any
import numpy as np
import pytest
from jina import DocumentSet
from jina.drivers.cache import BaseCacheDriver
from jina.executors.indexers.cache import DocIDCache
from jina.proto import jina_pb2
from jina.types.document import uid
from tests import random_docs
class Mo... | tests/unit/drivers/test_cache_driver.py | from pathlib import Path
from typing import Any
import numpy as np
import pytest
from jina import DocumentSet
from jina.drivers.cache import BaseCacheDriver
from jina.executors.indexers.cache import DocIDCache
from jina.proto import jina_pb2
from jina.types.document import uid
from tests import random_docs
class Mo... | 0.592549 | 0.397237 |
import pandas as pd
import numpy as np
from datetime import datetime, timedelta
from os.path import isfile
# utilities for extracting prior and post on indicators
def extract_indicators(wdi_df, indicator_codes):
return wdi_df[wdi_df['Indicator Code'].isin(indicator_codes)]
def lag_variable_simple(data, col, num_ye... | notebooks/util/explore.py | import pandas as pd
import numpy as np
from datetime import datetime, timedelta
from os.path import isfile
# utilities for extracting prior and post on indicators
def extract_indicators(wdi_df, indicator_codes):
return wdi_df[wdi_df['Indicator Code'].isin(indicator_codes)]
def lag_variable_simple(data, col, num_ye... | 0.446736 | 0.411466 |
from thrift.Thrift import *
from ttypes import *
from thrift.Thrift import TProcessor
from thrift.transport import TTransport
from thrift.protocol import TBinaryProtocol, TProtocol
try:
from thrift.protocol import fastbinary
except:
fastbinary = None
class Iface:
def recoverBlock(self, datanode, namespaceId, b... | src/contrib/thriftdatanode/gen-py/hadoopdatanode/ThriftHadoopDatanode.py |
from thrift.Thrift import *
from ttypes import *
from thrift.Thrift import TProcessor
from thrift.transport import TTransport
from thrift.protocol import TBinaryProtocol, TProtocol
try:
from thrift.protocol import fastbinary
except:
fastbinary = None
class Iface:
def recoverBlock(self, datanode, namespaceId, b... | 0.658747 | 0.107954 |
import csv
import pickle
import nltk
from SWIMMRS.src.TweetClassifier import Tokenizer, FeatureExtraction
import re
# Read the tweets one by one and process it
negtn_regex = re.compile( r"""(?:^(?:never|no|nothing|nowhere|noone|none|not|havent|hasnt|hadnt|cant|couldnt|shouldnt|wont|wouldnt|dont|doesnt|didnt|i... | src/TweetClassifier/Classifier.py | import csv
import pickle
import nltk
from SWIMMRS.src.TweetClassifier import Tokenizer, FeatureExtraction
import re
# Read the tweets one by one and process it
negtn_regex = re.compile( r"""(?:^(?:never|no|nothing|nowhere|noone|none|not|havent|hasnt|hadnt|cant|couldnt|shouldnt|wont|wouldnt|dont|doesnt|didnt|i... | 0.098577 | 0.248283 |
from plum import Dispatcher, clear_all_cache, Referentiable, Self, List
from plum.type import subclasscheck_cache
from ..util import benchmark
def test_cache_function_call_performance_and_correctness():
# Test performance.
dispatch = Dispatcher()
def f_native(x):
pass
@dispatch
def f(x):... | tests/dispatcher/test_cache.py | from plum import Dispatcher, clear_all_cache, Referentiable, Self, List
from plum.type import subclasscheck_cache
from ..util import benchmark
def test_cache_function_call_performance_and_correctness():
# Test performance.
dispatch = Dispatcher()
def f_native(x):
pass
@dispatch
def f(x):... | 0.844794 | 0.520923 |
import re
def check_exception(word): # Checa se a palavra corresponde a uma exceção (artigo, preposição ou conjunção)
exceptionsPort = ['o', 'os', 'a', 'as', 'um', 'uns', 'uma', 'umas', 'ao', 'aos', 'à', 'às', 'do', 'dos', 'da', 'das', 'dum', 'duns', 'duma', 'dumas', 'no', 'nos', 'na', 'nas', 'num', 'nuns', 'numa', '... | lattes2bib/utils.py | import re
def check_exception(word): # Checa se a palavra corresponde a uma exceção (artigo, preposição ou conjunção)
exceptionsPort = ['o', 'os', 'a', 'as', 'um', 'uns', 'uma', 'umas', 'ao', 'aos', 'à', 'às', 'do', 'dos', 'da', 'das', 'dum', 'duns', 'duma', 'dumas', 'no', 'nos', 'na', 'nas', 'num', 'nuns', 'numa', '... | 0.200401 | 0.506591 |
"""GRPC targets."""
from typing import Any, Callable, Iterable, Optional
from absl import logging
import tensorflow as tf
from load_test.targets import target
from tensorflow_serving.apis import predict_pb2
from tensorflow_serving.apis import prediction_service_pb2_grpc
class TfServingGrpcWorker:
"""A worker th... | models/experimental/inference/load_test/targets/grpc_target.py | """GRPC targets."""
from typing import Any, Callable, Iterable, Optional
from absl import logging
import tensorflow as tf
from load_test.targets import target
from tensorflow_serving.apis import predict_pb2
from tensorflow_serving.apis import prediction_service_pb2_grpc
class TfServingGrpcWorker:
"""A worker th... | 0.944035 | 0.210259 |
import numpy as np
import time
import tqdm
import os
from photonpy import Context, GaussianPSFMethods, Estimator, Dataset
import photonpy.cpp.spotdetect as spotdetect
from photonpy.cpp.calib import GainOffset_Calib
from photonpy.cpp.calib import GainOffsetImage_Calib
from photonpy.cpp.estim_queue import EstimQueue
fro... | photonpy/smlm/process_movie.py | import numpy as np
import time
import tqdm
import os
from photonpy import Context, GaussianPSFMethods, Estimator, Dataset
import photonpy.cpp.spotdetect as spotdetect
from photonpy.cpp.calib import GainOffset_Calib
from photonpy.cpp.calib import GainOffsetImage_Calib
from photonpy.cpp.estim_queue import EstimQueue
fro... | 0.413122 | 0.345712 |
import os
import pwd
import sys
from socket import socketpair
student_user = os.getenv("STUDENT_USER", "tester") # UNIX user to run user code as
grader_user = os.getenv("GRADER_USER", "root") # UNIX user to run grader as
student_path = os.getenv("PWD", "/submission/user") # Submitted files
grader_path = os.getenv("... | graderutils/__main__.py | import os
import pwd
import sys
from socket import socketpair
student_user = os.getenv("STUDENT_USER", "tester") # UNIX user to run user code as
grader_user = os.getenv("GRADER_USER", "root") # UNIX user to run grader as
student_path = os.getenv("PWD", "/submission/user") # Submitted files
grader_path = os.getenv("... | 0.117332 | 0.115586 |
class Interaction(object):
"""The interaction module for inheritance.
User interaction with a Markov chain.
Functions:
getter and setter for the self._data.
getter and setter for the self._chain.
"""
def __init__(self, name=None, **kwargs):
"""Creates a new in... | chain/interaction.py | class Interaction(object):
"""The interaction module for inheritance.
User interaction with a Markov chain.
Functions:
getter and setter for the self._data.
getter and setter for the self._chain.
"""
def __init__(self, name=None, **kwargs):
"""Creates a new in... | 0.909281 | 0.375735 |
import numpy as np
import matplotlib.pyplot as plt
from .riemann_solvers import GenericSolver, newton
class PSystemSolver(GenericSolver):
"""
d_t(u1) - d_x(u2) = 0
d_t(u2) - d_x(p(u1)) = 0
with p(x) = - x^(-gamma)
"""
def _read_particular_parameters(self, parameters):
self.gam... | schema/Dimension1/Euler/exact_solvers/p_system_solver.py | import numpy as np
import matplotlib.pyplot as plt
from .riemann_solvers import GenericSolver, newton
class PSystemSolver(GenericSolver):
"""
d_t(u1) - d_x(u2) = 0
d_t(u2) - d_x(p(u1)) = 0
with p(x) = - x^(-gamma)
"""
def _read_particular_parameters(self, parameters):
self.gam... | 0.575827 | 0.531635 |
import decimal
import json
import uuid
from django import forms
from django.conf import settings
from django.core import exceptions, serializers, validators
from django.core.management import call_command
from django.db import IntegrityError, connection, models
from django.test import TestCase, TransactionTestCase, ov... | tests/fields/test_encrypted.py | import decimal
import json
import uuid
from django import forms
from django.conf import settings
from django.core import exceptions, serializers, validators
from django.core.management import call_command
from django.db import IntegrityError, connection, models
from django.test import TestCase, TransactionTestCase, ov... | 0.633183 | 0.259204 |
import argparse
import torch
import numpy as np
import matplotlib.pyplot as plt
from pybpl.library import Library
from pybpl.model import CharacterModel
from pybpl.objects import CharacterType
def optimize_type(model, c, lr, nb_iter, eps, show_examples=True):
"""
Take a character type and optimize its param... | examples/optimize_type.py | import argparse
import torch
import numpy as np
import matplotlib.pyplot as plt
from pybpl.library import Library
from pybpl.model import CharacterModel
from pybpl.objects import CharacterType
def optimize_type(model, c, lr, nb_iter, eps, show_examples=True):
"""
Take a character type and optimize its param... | 0.679072 | 0.615492 |
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import skfuzzy
CONSENSUS_THRESHOLD = 64
# example of data reading
data = pd.read_excel('./Data/secondRound.xlsx', sheet_name='Survey Round 2 Responses')
data = data.drop(columns='Experts')
data = data.iloc[:, [not 'Experts confidence' ... | traditional_delphi.py | import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import skfuzzy
CONSENSUS_THRESHOLD = 64
# example of data reading
data = pd.read_excel('./Data/secondRound.xlsx', sheet_name='Survey Round 2 Responses')
data = data.drop(columns='Experts')
data = data.iloc[:, [not 'Experts confidence' ... | 0.612078 | 0.578686 |
import numpy as np
import scipy.sparse as sp
from sklearn.utils.fixes import loguniform
from sklearn.utils.validation import check_random_state
import pytest
from cca_zoo.data import generate_covariance_data
from cca_zoo.model_selection import GridSearchCV, RandomizedSearchCV
from cca_zoo.models import (
rCCA,
... | cca_zoo/test/test_models.py | import numpy as np
import scipy.sparse as sp
from sklearn.utils.fixes import loguniform
from sklearn.utils.validation import check_random_state
import pytest
from cca_zoo.data import generate_covariance_data
from cca_zoo.model_selection import GridSearchCV, RandomizedSearchCV
from cca_zoo.models import (
rCCA,
... | 0.736874 | 0.606732 |
from __future__ import unicode_literals
from selenium.common.exceptions import NoSuchElementException
from .helpers import SeleniumTestCase
class PjaxrNoMatchingIDTest(SeleniumTestCase):
def test_no_matching_id_pjaxr_request(self):
self.browser_get_reverse('index')
self.assert_title('index-titl... | test_app/tests/test_no_matching_id.py | from __future__ import unicode_literals
from selenium.common.exceptions import NoSuchElementException
from .helpers import SeleniumTestCase
class PjaxrNoMatchingIDTest(SeleniumTestCase):
def test_no_matching_id_pjaxr_request(self):
self.browser_get_reverse('index')
self.assert_title('index-titl... | 0.627951 | 0.24201 |
import os
import glob
import pprint
from wordcloud import WordCloud, STOPWORDS
import matplotlib.pyplot as plt
import getopt
import sys
import csv
def remove_characters(value=str, deletechars=str) -> str:
"""
Removes the given characters from the given string.
Parameters:
-----------
value: str
... | lyric-analysis.py | import os
import glob
import pprint
from wordcloud import WordCloud, STOPWORDS
import matplotlib.pyplot as plt
import getopt
import sys
import csv
def remove_characters(value=str, deletechars=str) -> str:
"""
Removes the given characters from the given string.
Parameters:
-----------
value: str
... | 0.301979 | 0.222637 |
import tensorflow as tf
import numpy as np
from ... import is_best_practice
from .layers import conv_block
from . import TFModel
class UNet(TFModel):
""" UNet
**Configuration**
inputs : dict
dict with 'images' and 'masks' (see :meth:`._make_inputs`)
body : dict
num_blocks : int
... | dataset/models/tf/unet.py | import tensorflow as tf
import numpy as np
from ... import is_best_practice
from .layers import conv_block
from . import TFModel
class UNet(TFModel):
""" UNet
**Configuration**
inputs : dict
dict with 'images' and 'masks' (see :meth:`._make_inputs`)
body : dict
num_blocks : int
... | 0.941405 | 0.3398 |
#!/usr/bin/python
import optparse, os, shutil, sys, tempfile, glob, shlex, vcf, pysam, tarfile
from subprocess import *
import subprocess
CHUNK_SIZE = 2**20 #1mb
def cleanup_before_exit( tmp_dir ):
if tmp_dir and os.path.exists( tmp_dir ):
shutil.rmtree( tmp_dir )
def __main__():
parser = optparse.... | tools/trena/makeTRN_wrapper.py |
#!/usr/bin/python
import optparse, os, shutil, sys, tempfile, glob, shlex, vcf, pysam, tarfile
from subprocess import *
import subprocess
CHUNK_SIZE = 2**20 #1mb
def cleanup_before_exit( tmp_dir ):
if tmp_dir and os.path.exists( tmp_dir ):
shutil.rmtree( tmp_dir )
def __main__():
parser = optparse.... | 0.111919 | 0.067948 |
from sqlalchemy import func
from src import constants as const
from src.db_connection import Session
from src.modules.user.user_model import User
logger = const.logger
def user_exists(discord_id):
"""
Checks if a user exists by id
:param discord_id: Discord id
:return: Boolean
"""
session = ... | src/modules/user/user_util.py | from sqlalchemy import func
from src import constants as const
from src.db_connection import Session
from src.modules.user.user_model import User
logger = const.logger
def user_exists(discord_id):
"""
Checks if a user exists by id
:param discord_id: Discord id
:return: Boolean
"""
session = ... | 0.671794 | 0.182134 |
from homeassistant.const import TEMP_CELSIUS
from . import KNOWN_DEVICES, HomeKitEntity
DEPENDENCIES = ['homekit_controller']
HUMIDITY_ICON = 'mdi-water-percent'
TEMP_C_ICON = "mdi-temperature-celsius"
BRIGHTNESS_ICON = "mdi-brightness-6"
UNIT_PERCENT = "%"
UNIT_LUX = "lux"
def setup_platform(hass, config, add_en... | homeassistant/components/homekit_controller/sensor.py | from homeassistant.const import TEMP_CELSIUS
from . import KNOWN_DEVICES, HomeKitEntity
DEPENDENCIES = ['homekit_controller']
HUMIDITY_ICON = 'mdi-water-percent'
TEMP_C_ICON = "mdi-temperature-celsius"
BRIGHTNESS_ICON = "mdi-brightness-6"
UNIT_PERCENT = "%"
UNIT_LUX = "lux"
def setup_platform(hass, config, add_en... | 0.826187 | 0.191517 |
from __future__ import absolute_import, print_function
import argparse
import csv
import codecs
import os
import requests
from .csv import CSVDialect
from .files import files_lookup
from .digiposte import create_account, upload_diploma, get_student_url
DIGIPOSTE_BASE_URL = "https://api.digiposte.fr/api/v3" # No trai... | imt_digiposte_woleet/__main__.py | from __future__ import absolute_import, print_function
import argparse
import csv
import codecs
import os
import requests
from .csv import CSVDialect
from .files import files_lookup
from .digiposte import create_account, upload_diploma, get_student_url
DIGIPOSTE_BASE_URL = "https://api.digiposte.fr/api/v3" # No trai... | 0.342352 | 0.067209 |
from tqdm import tqdm
import nibabel as nib
from pathlib import Path
from visualize import case_plt
from trainer import predict_case, cascade_predict_case, cascade_predict, evaluate_case, \
batch_evaluate, batch_cascade_predict
from data import CaseDataset, save_pred, save_case
from network import ResUnet3D, ResAtt... | nb_post_iib.py | from tqdm import tqdm
import nibabel as nib
from pathlib import Path
from visualize import case_plt
from trainer import predict_case, cascade_predict_case, cascade_predict, evaluate_case, \
batch_evaluate, batch_cascade_predict
from data import CaseDataset, save_pred, save_case
from network import ResUnet3D, ResAtt... | 0.399109 | 0.201401 |
import pprint
import re # noqa: F401
import six
class CharityOrg(object):
"""NOTE: This class is auto generated by the swagger code generator program.
Do not edit the class manually.
"""
"""
Attributes:
swagger_types (dict): The key is attribute name
and the val... | src/ebay_rest/api/commerce_charity/models/charity_org.py | import pprint
import re # noqa: F401
import six
class CharityOrg(object):
"""NOTE: This class is auto generated by the swagger code generator program.
Do not edit the class manually.
"""
"""
Attributes:
swagger_types (dict): The key is attribute name
and the val... | 0.541409 | 0.100348 |
import os.path
from enum import Enum
import numpy as np
import pytest
from numerous.engine.simulation import Simulation
from numerous.engine.system import Subsystem, Item
from numerous.engine.model import Model
from tests.test_equations import TestEq_input, Test_Eq, TestEq_ground
class SolverType(Enum):
SOLVER_... | tests/test_caching_model.py | import os.path
from enum import Enum
import numpy as np
import pytest
from numerous.engine.simulation import Simulation
from numerous.engine.system import Subsystem, Item
from numerous.engine.model import Model
from tests.test_equations import TestEq_input, Test_Eq, TestEq_ground
class SolverType(Enum):
SOLVER_... | 0.466359 | 0.362602 |
from manim import *
class GraphAreaPlot(Scene):
def construct(self):
ax = Axes(
x_range=[0, 10, 1],
y_range=[-1,1,1],
y_length = 1,
axis_config={"include_tip": False}
)
labels = ax.get_axis_labels(x_label="Weight", y_label="")
# sel... | rough.py | from manim import *
class GraphAreaPlot(Scene):
def construct(self):
ax = Axes(
x_range=[0, 10, 1],
y_range=[-1,1,1],
y_length = 1,
axis_config={"include_tip": False}
)
labels = ax.get_axis_labels(x_label="Weight", y_label="")
# sel... | 0.724675 | 0.505188 |
import pytest
from conftest import quoted_object, run_setup_sql
from pgbedrock import ownerships as own
from pgbedrock import attributes, privileges
from pgbedrock.context import ObjectInfo
Q_CREATE_SEQUENCE = 'SET ROLE {}; CREATE SEQUENCE {}.{}; RESET ROLE;'
Q_SCHEMA_EXISTS = "SELECT schema_name FROM information_sch... | tests/test_ownerships.py | import pytest
from conftest import quoted_object, run_setup_sql
from pgbedrock import ownerships as own
from pgbedrock import attributes, privileges
from pgbedrock.context import ObjectInfo
Q_CREATE_SEQUENCE = 'SET ROLE {}; CREATE SEQUENCE {}.{}; RESET ROLE;'
Q_SCHEMA_EXISTS = "SELECT schema_name FROM information_sch... | 0.449634 | 0.302378 |
import pytest
import torch
from mmflow.models.decoders.maskflownet_decoder import (BasicDeformWarpBlock,
DeformWarpBlock,
MaskFlowNetSDecoder,
MaskModu... | tests/test_models/test_decoder/test_maskflownets_decoder.py | import pytest
import torch
from mmflow.models.decoders.maskflownet_decoder import (BasicDeformWarpBlock,
DeformWarpBlock,
MaskFlowNetSDecoder,
MaskModu... | 0.838944 | 0.625753 |
import os
from azlmbr.entity import EntityId
from azlmbr.math import Vector3
from editor_python_test_tools.editor_entity_utils import EditorEntity
from editor_python_test_tools.utils import Report
from editor_python_test_tools.utils import TestHelper as helper
import azlmbr.bus as bus
import azlmbr.components as comp... | AutomatedTesting/Gem/PythonTests/prefab/Prefab_Test_Utils.py | import os
from azlmbr.entity import EntityId
from azlmbr.math import Vector3
from editor_python_test_tools.editor_entity_utils import EditorEntity
from editor_python_test_tools.utils import Report
from editor_python_test_tools.utils import TestHelper as helper
import azlmbr.bus as bus
import azlmbr.components as comp... | 0.466116 | 0.190573 |
import tensorflow as tf
import numpy as np
import math
def roi_rotate_quad(featuremap, quadboxes, shape, input_shape):
"""
:param featuremap: (B, H, W, C)
:param quadboxes: (B, N, 8)
:param shape: (new_h, new_w)
:param input_shape: (B, H, W, C)
:return: cropped feature (BN, new_h, new_w, C)
... | roi_rotate.py | import tensorflow as tf
import numpy as np
import math
def roi_rotate_quad(featuremap, quadboxes, shape, input_shape):
"""
:param featuremap: (B, H, W, C)
:param quadboxes: (B, N, 8)
:param shape: (new_h, new_w)
:param input_shape: (B, H, W, C)
:return: cropped feature (BN, new_h, new_w, C)
... | 0.779112 | 0.576959 |
import numpy as np
from pyuvsim import AnalyticBeam
from numpy.polynomial.chebyshev import chebval
from . import utils
def stokes_matrix(pol_index):
"""
Calculate Pauli matrices for pseudo-Stokes conversion.
Source code adapted from `pyuvdata`.
Derived from https://arxiv.org/pdf/1401.2095.pdf, the P... | hera_sim/beams.py | import numpy as np
from pyuvsim import AnalyticBeam
from numpy.polynomial.chebyshev import chebval
from . import utils
def stokes_matrix(pol_index):
"""
Calculate Pauli matrices for pseudo-Stokes conversion.
Source code adapted from `pyuvdata`.
Derived from https://arxiv.org/pdf/1401.2095.pdf, the P... | 0.949365 | 0.923558 |
from typing import List, Optional, Tuple
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
def beta_bernoulli(length: int, alpha: float, beta: float) -> torch.Tensor:
"""Compute beta bernoulli distribution.
Args:
length: K, total length.
alpha, beta: beta-b... | tacospawn/taco/misc.py | from typing import List, Optional, Tuple
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
def beta_bernoulli(length: int, alpha: float, beta: float) -> torch.Tensor:
"""Compute beta bernoulli distribution.
Args:
length: K, total length.
alpha, beta: beta-b... | 0.976106 | 0.698304 |
from __future__ import absolute_import, division, print_function
import argparse
import os
import glob
import numpy as np
from fastespy.readpydata import readgraphpy
from fastespy.analysis import periodogram, hist_norm
from scipy.stats import norm
import matplotlib
matplotlib.use("agg")
import matplotlib.pyplot as plt
... | fastespy/scripts/plot_periodogram_histogram.py | from __future__ import absolute_import, division, print_function
import argparse
import os
import glob
import numpy as np
from fastespy.readpydata import readgraphpy
from fastespy.analysis import periodogram, hist_norm
from scipy.stats import norm
import matplotlib
matplotlib.use("agg")
import matplotlib.pyplot as plt
... | 0.608478 | 0.363958 |
import numpy as np
import wavio
import librosa
import wave
from scipy import signal
from scipy import fromstring, int16
from scipy import fftpack
from PyEMD import EMD
def window_(x_2d, window):
"""
inputs:
x_2d : inputs (2D array)
window : string, float, or tuple
The t... | prowav/utils.py | import numpy as np
import wavio
import librosa
import wave
from scipy import signal
from scipy import fromstring, int16
from scipy import fftpack
from PyEMD import EMD
def window_(x_2d, window):
"""
inputs:
x_2d : inputs (2D array)
window : string, float, or tuple
The t... | 0.672117 | 0.51812 |
import argparse
# Parameters
parser = argparse.ArgumentParser(description='Catcher')
parser.add_argument('--grid', dest='grid', type=int, default=11, help='Game grid size.')
parser.add_argument('--hidden', dest='hidden', type=int, default=100, help='Number of neuron in the hidden layer.')
parser.add_argument('--memory... | examples/catcher.py | import argparse
# Parameters
parser = argparse.ArgumentParser(description='Catcher')
parser.add_argument('--grid', dest='grid', type=int, default=11, help='Game grid size.')
parser.add_argument('--hidden', dest='hidden', type=int, default=100, help='Number of neuron in the hidden layer.')
parser.add_argument('--memory... | 0.794863 | 0.117016 |
from tile import Tile
class Map(object):
def __init__(self, tile_size_x=20, tile_size_y=20):
# creates an empty nested list of tiles
self.tile_size_x = tile_size_x
self.tile_size_y = tile_size_y
self.tile_list = ([[Tile(x,y) for x in xrange(tile_size_y)]
... | The Coding Dead/game/map.py | from tile import Tile
class Map(object):
def __init__(self, tile_size_x=20, tile_size_y=20):
# creates an empty nested list of tiles
self.tile_size_x = tile_size_x
self.tile_size_y = tile_size_y
self.tile_list = ([[Tile(x,y) for x in xrange(tile_size_y)]
... | 0.399694 | 0.330471 |
from marshal import loads, dumps
from operator import attrgetter, getitem
from typing import Any, Type, List, Dict, Optional, Union, Sequence, Callable
from dataclasses import is_dataclass, MISSING
from .common import Serializer, T, K, AbstractFactory
from .fields import get_dataclass_fields, FieldInfo, get_typeddict... | dataclass_factory/serializers.py | from marshal import loads, dumps
from operator import attrgetter, getitem
from typing import Any, Type, List, Dict, Optional, Union, Sequence, Callable
from dataclasses import is_dataclass, MISSING
from .common import Serializer, T, K, AbstractFactory
from .fields import get_dataclass_fields, FieldInfo, get_typeddict... | 0.752013 | 0.155046 |
from time import sleep
from errors.codes import ERROR_DESC_T
from ccutils.databases.configuration import DBConfigurator
from network.manager.networkManager import NetworkManager
from clusterServer.callbacks.clusterEndpointCallback import ClusterEndpointCallback
from clusterServer.callbacks.imageRepositoryCallback impor... | src/Infraestructura/clusterServer/mainReactor/clusterServerMainReactor.py | from time import sleep
from errors.codes import ERROR_DESC_T
from ccutils.databases.configuration import DBConfigurator
from network.manager.networkManager import NetworkManager
from clusterServer.callbacks.clusterEndpointCallback import ClusterEndpointCallback
from clusterServer.callbacks.imageRepositoryCallback impor... | 0.608245 | 0.053874 |
import torch
import torch.nn as nn
import torchvision.datasets as dsets
import torchvision.transforms as transforms
# hyper parameters
input_size = 784
hidden_size = 500
num_classes = 10
num_epochs = 10
batch_size = 100
lr = 0.001
# MNIST dataset
train_dataset = dsets.MNIST(root='./data',
... | mnist_fc.py | import torch
import torch.nn as nn
import torchvision.datasets as dsets
import torchvision.transforms as transforms
# hyper parameters
input_size = 784
hidden_size = 500
num_classes = 10
num_epochs = 10
batch_size = 100
lr = 0.001
# MNIST dataset
train_dataset = dsets.MNIST(root='./data',
... | 0.910811 | 0.658294 |
"""SQuAD 1.1 BERT data loader."""
import os
import pickle
import tempfile
from typing import Any, Mapping
from urllib import request
from absl import logging
import tensorflow as tf
from transformers import BertTokenizer
from load_test.data import data_loader
from official.nlp.data import squad_lib
class SquadBertL... | models/experimental/inference/load_test/data/squad_bert.py | """SQuAD 1.1 BERT data loader."""
import os
import pickle
import tempfile
from typing import Any, Mapping
from urllib import request
from absl import logging
import tensorflow as tf
from transformers import BertTokenizer
from load_test.data import data_loader
from official.nlp.data import squad_lib
class SquadBertL... | 0.746509 | 0.29733 |
from cros.factory.device import accelerometer
from cros.factory.device import device_utils
from cros.factory.test.i18n import _
from cros.factory.test import test_case
from cros.factory.test import test_ui
from cros.factory.utils.arg_utils import Arg
from cros.factory.utils import type_utils
class AccelerometersCalib... | py/test/pytests/accelerometers_calibration.py | from cros.factory.device import accelerometer
from cros.factory.device import device_utils
from cros.factory.test.i18n import _
from cros.factory.test import test_case
from cros.factory.test import test_ui
from cros.factory.utils.arg_utils import Arg
from cros.factory.utils import type_utils
class AccelerometersCalib... | 0.536313 | 0.333368 |