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 |
|---|---|---|---|---|
import argparse
def parameter_parser():
"""
A method to parse up command line parameters.
"""
parser = argparse.ArgumentParser(description = "Run CatGCN.")
parser.add_argument("--edge-path",
nargs = "?",
default = "./input/user_edge.csv",
... | parser.py | import argparse
def parameter_parser():
"""
A method to parse up command line parameters.
"""
parser = argparse.ArgumentParser(description = "Run CatGCN.")
parser.add_argument("--edge-path",
nargs = "?",
default = "./input/user_edge.csv",
... | 0.667798 | 0.14137 |
import os
from typing import Union, Tuple
from torchtext._internal.module_utils import is_module_available
from torchtext.data.datasets_utils import (
_wrap_split_argument,
_create_dataset_directory,
)
if is_module_available("torchdata"):
from torchdata.datapipes.iter import FileOpener, HttpReader, Iterab... | torchtext/datasets/conll2000chunking.py | import os
from typing import Union, Tuple
from torchtext._internal.module_utils import is_module_available
from torchtext.data.datasets_utils import (
_wrap_split_argument,
_create_dataset_directory,
)
if is_module_available("torchdata"):
from torchdata.datapipes.iter import FileOpener, HttpReader, Iterab... | 0.832237 | 0.428413 |
import inspect
from discord.ext import commands
from discord.ext.alternatives._common import py_allow
py_allow(3, 9, 0)
class CheckDecorator:
def __init__(self, predicate):
self.predicate = predicate
self.check = Only(Check(predicate))
def __call__(self, func):
if isinstance(func, ... | discord/ext/alternatives/binary_checks.py | import inspect
from discord.ext import commands
from discord.ext.alternatives._common import py_allow
py_allow(3, 9, 0)
class CheckDecorator:
def __init__(self, predicate):
self.predicate = predicate
self.check = Only(Check(predicate))
def __call__(self, func):
if isinstance(func, ... | 0.513181 | 0.142739 |
import re
from mock import Mock, patch
from nose.tools import assert_equal
from nose.tools import assert_is_instance
from unittest import TestCase
from flask import request
from twilio import twiml
from strowger import switch
TEST_TWILIO_REQUEST_DATA = {
'From': '+14155551234',
'To': '+14158675309',
'Num... | tests/test_switch.py | import re
from mock import Mock, patch
from nose.tools import assert_equal
from nose.tools import assert_is_instance
from unittest import TestCase
from flask import request
from twilio import twiml
from strowger import switch
TEST_TWILIO_REQUEST_DATA = {
'From': '+14155551234',
'To': '+14158675309',
'Num... | 0.542863 | 0.277458 |
import paddle.nn as nn
import paddle
import paddle.nn.functional as F
from .. import PretrainedModel, register_base_model
from ...transformers.roberta.modeling import RobertaEmbeddings
import math
__all__ = [
'LukeModel', 'LukePretrainedModel', 'LukeForEntitySpanClassification',
'LukeForEntityPairClassifica... | paddlenlp/transformers/luke/modeling.py |
import paddle.nn as nn
import paddle
import paddle.nn.functional as F
from .. import PretrainedModel, register_base_model
from ...transformers.roberta.modeling import RobertaEmbeddings
import math
__all__ = [
'LukeModel', 'LukePretrainedModel', 'LukeForEntitySpanClassification',
'LukeForEntityPairClassifica... | 0.756537 | 0.404625 |
import pandas as pd
import json
import copy
#get all the intersection points of the path, select the point closest to the target location
def getKeyPoint(routes1, routes2, pt1, pt2):
all_inters = getAllInters(routes1,routes2)
min_distance = 99999999
key_pt = []
for inter in all_inters:
routes1 ... | programming/modify-dijstra.py | import pandas as pd
import json
import copy
#get all the intersection points of the path, select the point closest to the target location
def getKeyPoint(routes1, routes2, pt1, pt2):
all_inters = getAllInters(routes1,routes2)
min_distance = 99999999
key_pt = []
for inter in all_inters:
routes1 ... | 0.270769 | 0.231821 |
from math import pi
from typing import Optional, Literal
import random
from direct.showbase.Loader import Loader
from panda3d.core import NodePath, Point3F, Quat, Vec3
class Track:
LENGTH = 2
def __init__(
self, direction: Vec3, normal: Vec3, start_pos: Point3F, node_path: NodePath
):
se... | utils/track_generation.py | from math import pi
from typing import Optional, Literal
import random
from direct.showbase.Loader import Loader
from panda3d.core import NodePath, Point3F, Quat, Vec3
class Track:
LENGTH = 2
def __init__(
self, direction: Vec3, normal: Vec3, start_pos: Point3F, node_path: NodePath
):
se... | 0.883097 | 0.335487 |
import os, sys, time, datetime, random, hashlib, re, threading, json, urllib, cookielib, requests, uuid
from multiprocessing.pool import ThreadPool
from requests.exceptions import ConnectionError
from datetime import datetime
b='\033[1;94m'
i='\033[1;92m'
c='\033[1;96m'
m='\033[1;91m'
u='\033[1;95m'
... | xperia.py | import os, sys, time, datetime, random, hashlib, re, threading, json, urllib, cookielib, requests, uuid
from multiprocessing.pool import ThreadPool
from requests.exceptions import ConnectionError
from datetime import datetime
b='\033[1;94m'
i='\033[1;92m'
c='\033[1;96m'
m='\033[1;91m'
u='\033[1;95m'
... | 0.049336 | 0.055926 |
__author__ = "<NAME> <<EMAIL>>"
class kDTreeNode():
"""
Node for point k-D trees.
"""
def __init__(self, point, left, right):
self.point = point
self.left = left
self.right = right
def __repr__(self):
return str(self.point)
def kdcompare(r, p, depth):
... | utils/kdtree1.py | __author__ = "<NAME> <<EMAIL>>"
class kDTreeNode():
"""
Node for point k-D trees.
"""
def __init__(self, point, left, right):
self.point = point
self.left = left
self.right = right
def __repr__(self):
return str(self.point)
def kdcompare(r, p, depth):
... | 0.666171 | 0.477128 |
import re
def extract(keyChain, node, fallback):
if isinstance(keyChain, basestring):
keyChain = keyChain.split(".");
obj = None
if node is not None:
if len(keyChain) == 0:
obj = node
else:
newKeyChain = keyChain[1:]
if len(newKeyChain) == 0:
... | geodash/utils.py | import re
def extract(keyChain, node, fallback):
if isinstance(keyChain, basestring):
keyChain = keyChain.split(".");
obj = None
if node is not None:
if len(keyChain) == 0:
obj = node
else:
newKeyChain = keyChain[1:]
if len(newKeyChain) == 0:
... | 0.321567 | 0.31363 |
"""Script to accumulate input data given advection velocity fields."""
from improver import cli
# The accumulation frequency in minutes.
ACCUMULATION_FIDELITY = 1
# Creates the value_converter that clize needs.
inputadvection = cli.create_constrained_inputcubelist_converter(
lambda cube: cube.name()
in ["pre... | improver/cli/nowcast_accumulate.py | """Script to accumulate input data given advection velocity fields."""
from improver import cli
# The accumulation frequency in minutes.
ACCUMULATION_FIDELITY = 1
# Creates the value_converter that clize needs.
inputadvection = cli.create_constrained_inputcubelist_converter(
lambda cube: cube.name()
in ["pre... | 0.934507 | 0.537163 |
import os
import re
import socket
SERVICE_ACCOUNTS_PATH = '/creds/service_accounts'
class classproperty(object):
"""A decorator that allows is_production_host to only to be defined once."""
def __init__(self, getter):
self.getter = getter
def __get__(self, instance, owner):
return self.getter(owner)
... | site_config/config_default.py | import os
import re
import socket
SERVICE_ACCOUNTS_PATH = '/creds/service_accounts'
class classproperty(object):
"""A decorator that allows is_production_host to only to be defined once."""
def __init__(self, getter):
self.getter = getter
def __get__(self, instance, owner):
return self.getter(owner)
... | 0.592077 | 0.142381 |
import pygame
import random
import math
import os
pygame.init()
PATH = os.getcwd().replace('\\', '/')
img = pygame.image.load('./img/icon.png')
pygame.display.set_icon(img)
class DrawInformation:
BLACK = 0, 0, 0
WHITE = 255, 255, 255
RED = 255, 0, 0
GREEN = 0, 255, 0
BLUE = 0, 0, 255
BACKGROU... | main.py | import pygame
import random
import math
import os
pygame.init()
PATH = os.getcwd().replace('\\', '/')
img = pygame.image.load('./img/icon.png')
pygame.display.set_icon(img)
class DrawInformation:
BLACK = 0, 0, 0
WHITE = 255, 255, 255
RED = 255, 0, 0
GREEN = 0, 255, 0
BLUE = 0, 0, 255
BACKGROU... | 0.200088 | 0.179171 |
import os
from pathlib import Path
import pytest
from commitizen import config, defaults, git
PYPROJECT = """
[tool.commitizen]
name = "cz_jira"
version = "1.0.0"
version_files = [
"commitizen/__version__.py",
"pyproject.toml"
]
style = [
["pointer", "reverse"],
["question", "underline"]
]
[tool.bla... | tests/test_conf.py | import os
from pathlib import Path
import pytest
from commitizen import config, defaults, git
PYPROJECT = """
[tool.commitizen]
name = "cz_jira"
version = "1.0.0"
version_files = [
"commitizen/__version__.py",
"pyproject.toml"
]
style = [
["pointer", "reverse"],
["question", "underline"]
]
[tool.bla... | 0.280419 | 0.269626 |
from typing import List
from flask import current_app
from backend.blueprints.spa_api.service_layers.chart_data import ChartData, ChartDataPoint
from backend.database.wrapper import player_wrapper
from backend.database.wrapper.stats import player_stat_wrapper
from .basic_stats import basic_stats_metadatas
wrapper = ... | backend/blueprints/spa_api/service_layers/replay/groups.py | from typing import List
from flask import current_app
from backend.blueprints.spa_api.service_layers.chart_data import ChartData, ChartDataPoint
from backend.database.wrapper import player_wrapper
from backend.database.wrapper.stats import player_stat_wrapper
from .basic_stats import basic_stats_metadatas
wrapper = ... | 0.629547 | 0.190856 |
from oslotest import base
from ceilometer.event import trait_plugins
class TestSplitterPlugin(base.BaseTestCase):
def setUp(self):
super(TestSplitterPlugin, self).setUp()
self.pclass = trait_plugins.SplitterTraitPlugin
def test_split(self):
param = dict(separator='-', se... | CodeAnalysis/SourceMeter_Interface/SourceMeter-8.2.0-x64-linux/Python/Demo/ceilometer/ceilometer/tests/event/test_trait_plugins.py | from oslotest import base
from ceilometer.event import trait_plugins
class TestSplitterPlugin(base.BaseTestCase):
def setUp(self):
super(TestSplitterPlugin, self).setUp()
self.pclass = trait_plugins.SplitterTraitPlugin
def test_split(self):
param = dict(separator='-', se... | 0.570331 | 0.296947 |
import asyncio
from unittest import mock
import pytest
from waterbutler.core import utils
class TestAsyncRetry:
@pytest.mark.asyncio
async def test_returns_success(self):
mock_func = mock.Mock(return_value='Foo')
retryable = utils.async_retry(5, 0, raven=None)(mock_func)
x = await r... | tests/core/test_utils.py | import asyncio
from unittest import mock
import pytest
from waterbutler.core import utils
class TestAsyncRetry:
@pytest.mark.asyncio
async def test_returns_success(self):
mock_func = mock.Mock(return_value='Foo')
retryable = utils.async_retry(5, 0, raven=None)(mock_func)
x = await r... | 0.627495 | 0.631537 |
from bokeh.models import Div
class VibroP_Message:
def __init__( self, Color = "red",
Size = 4,
FontStyle = "b",
MessageHeader = 'Message: ',
Width = 500,
Height = 20 ):
"""
The class represents a widget ba... | Vibroacoustic_plates/VibroP_MessageClass.py | from bokeh.models import Div
class VibroP_Message:
def __init__( self, Color = "red",
Size = 4,
FontStyle = "b",
MessageHeader = 'Message: ',
Width = 500,
Height = 20 ):
"""
The class represents a widget ba... | 0.76895 | 0.456894 |
import enum
import struct
class SpecialSectionNumber(enum.IntEnum):
UNDEFINED = 0
ABSOLUTE = -1
DEBUG = -2
class StorageClass(enum.IntEnum):
END_OF_FUNCTION = -1
NULL = 0
AUTOMATIC = 1
EXTERNAL = 2
STATIC = 3
REGISTER = 4
EXTERNAL_DEF = 5
LABEL = 6
UNDEFINED_LABEL = 7... | cough/symbol.py | import enum
import struct
class SpecialSectionNumber(enum.IntEnum):
UNDEFINED = 0
ABSOLUTE = -1
DEBUG = -2
class StorageClass(enum.IntEnum):
END_OF_FUNCTION = -1
NULL = 0
AUTOMATIC = 1
EXTERNAL = 2
STATIC = 3
REGISTER = 4
EXTERNAL_DEF = 5
LABEL = 6
UNDEFINED_LABEL = 7... | 0.270962 | 0.196923 |
import contextlib
import os.path
import sys
from typing import Generator
from typing import Sequence
from typing import Tuple
import pre_commit.constants as C
from pre_commit import git
from pre_commit.envcontext import envcontext
from pre_commit.envcontext import PatchesT
from pre_commit.envcontext import Var
from pr... | pre_commit/languages/golang.py | import contextlib
import os.path
import sys
from typing import Generator
from typing import Sequence
from typing import Tuple
import pre_commit.constants as C
from pre_commit import git
from pre_commit.envcontext import envcontext
from pre_commit.envcontext import PatchesT
from pre_commit.envcontext import Var
from pr... | 0.459561 | 0.095055 |
import contextlib
import multiprocessing
import os
import signal
import tempfile
import time
import uuid
from collections import defaultdict
from io import BytesIO
from queue import Empty
import numpy as np
from numpy.testing import assert_array_equal
from mars import promise
from mars.config import options
from mar... | mars/worker/tests/test_transfer.py |
import contextlib
import multiprocessing
import os
import signal
import tempfile
import time
import uuid
from collections import defaultdict
from io import BytesIO
from queue import Empty
import numpy as np
from numpy.testing import assert_array_equal
from mars import promise
from mars.config import options
from mar... | 0.417509 | 0.068881 |
from math import log
import operator
def createDataset():
dataset = [[1,1,'yes'],
[1,1,'yes'],
[1,0,'no'],
[0,1,'no'],
[0,1,'no']]
labels = ['no surfacing','flippers']
return dataset,labels
def calcShannonEnt(dataset):
numEntries = len(data... | 04_decision_tree/tmp_code/test_dtree.py | from math import log
import operator
def createDataset():
dataset = [[1,1,'yes'],
[1,1,'yes'],
[1,0,'no'],
[0,1,'no'],
[0,1,'no']]
labels = ['no surfacing','flippers']
return dataset,labels
def calcShannonEnt(dataset):
numEntries = len(data... | 0.205854 | 0.279352 |
import numpy as np
import matplotlib.pyplot as plt
from keras.datasets import mnist
from keras.models import Sequential,Model
from keras.layers import Dense,LeakyReLU,Input
from keras.optimizers import Adam
batch_size = 16
step_per_epoch = 3750
epochs = 10
(x_train,x_test),(y_train,y_test) = mnist.load_data()
x_train... | model.py | import numpy as np
import matplotlib.pyplot as plt
from keras.datasets import mnist
from keras.models import Sequential,Model
from keras.layers import Dense,LeakyReLU,Input
from keras.optimizers import Adam
batch_size = 16
step_per_epoch = 3750
epochs = 10
(x_train,x_test),(y_train,y_test) = mnist.load_data()
x_train... | 0.837121 | 0.488588 |
import itertools
import numpy
import turicreate as tc
# %% reload the data.
songs = tc.load_sframe('../data/processed/music_songs.sframe')
usage_data = tc.load_sframe('../data/processed/music_usage_data.sframe')
# %% replace those zeroes with missing values.
songs['year'] = songs['year'].apply(lambda x: None if x == ... | src/data_manipulation.py | import itertools
import numpy
import turicreate as tc
# %% reload the data.
songs = tc.load_sframe('../data/processed/music_songs.sframe')
usage_data = tc.load_sframe('../data/processed/music_usage_data.sframe')
# %% replace those zeroes with missing values.
songs['year'] = songs['year'].apply(lambda x: None if x == ... | 0.35031 | 0.40204 |
from dataclasses import dataclass
from datetime import datetime, date, time, timezone
from functools import lru_cache
from typing import Optional, Sequence, Tuple, Union, cast
from ..core.common import fromisoformat
from my.config import location as user_config
DateIsh = Union[datetime, date, str]
# todo hopefully... | my/location/home.py | from dataclasses import dataclass
from datetime import datetime, date, time, timezone
from functools import lru_cache
from typing import Optional, Sequence, Tuple, Union, cast
from ..core.common import fromisoformat
from my.config import location as user_config
DateIsh = Union[datetime, date, str]
# todo hopefully... | 0.414425 | 0.154567 |
from sqlalchemy import Column, ForeignKey, Integer, String, UniqueConstraint
from sqlalchemy.orm import backref, relationship
from fonduer.parser.models.context import Context
class Table(Context):
"""A Table Context in a Document.
Used to represent tables found in a document.
"""
__tablename__ = "... | src/fonduer/parser/models/table.py | from sqlalchemy import Column, ForeignKey, Integer, String, UniqueConstraint
from sqlalchemy.orm import backref, relationship
from fonduer.parser.models.context import Context
class Table(Context):
"""A Table Context in a Document.
Used to represent tables found in a document.
"""
__tablename__ = "... | 0.844409 | 0.401688 |
from __future__ import division
from keras.callbacks import Callback
from keras import backend as K
import math
import numpy as np
import types
import seaborn as sns
import matplotlib.pyplot as plt
sns.set_style("whitegrid")
class ValidationMonitor(Callback):
'''Callback to monitor validation performance and op... | Modules/Callbacks.py | from __future__ import division
from keras.callbacks import Callback
from keras import backend as K
import math
import numpy as np
import types
import seaborn as sns
import matplotlib.pyplot as plt
sns.set_style("whitegrid")
class ValidationMonitor(Callback):
'''Callback to monitor validation performance and op... | 0.842637 | 0.203411 |
import inspect
from indentml.parser import QqTag
class QqLaTeXFormatter(object):
def __init__(self, root: QqTag=None, allowed_tags=None):
self.root = root
self.allowed_tags = allowed_tags or set()
self.enumerateable_envs = {name: name.capitalize() for name in ['remark', 'theorem', 'example... | qqmbr/qqlatex.py | import inspect
from indentml.parser import QqTag
class QqLaTeXFormatter(object):
def __init__(self, root: QqTag=None, allowed_tags=None):
self.root = root
self.allowed_tags = allowed_tags or set()
self.enumerateable_envs = {name: name.capitalize() for name in ['remark', 'theorem', 'example... | 0.688573 | 0.274791 |
import src.tnet as tnet
import src.CARS as cars
import numpy as np
import copy
from src.utils import *
import matplotlib as mpl
import matplotlib as mpl
from matplotlib import rc
import matplotlib.pyplot as plt
import experiments.build_NYC_subway_net as nyc
from datetime import datetime
import pandas as pd
import mult... | experiments/run_penRate_intermodal_journal.py | import src.tnet as tnet
import src.CARS as cars
import numpy as np
import copy
from src.utils import *
import matplotlib as mpl
import matplotlib as mpl
from matplotlib import rc
import matplotlib.pyplot as plt
import experiments.build_NYC_subway_net as nyc
from datetime import datetime
import pandas as pd
import mult... | 0.290679 | 0.318061 |
from __future__ import unicode_literals
from decimal import Decimal
import contextlib
import glob
import io
import json
import os
import re
import subprocess
import sys
if sys.version_info[:2] < (2, 7): # pragma: no cover
import unittest2 as unittest
else:
import unittest
try:
from unittest import mock
e... | tests.py | from __future__ import unicode_literals
from decimal import Decimal
import contextlib
import glob
import io
import json
import os
import re
import subprocess
import sys
if sys.version_info[:2] < (2, 7): # pragma: no cover
import unittest2 as unittest
else:
import unittest
try:
from unittest import mock
e... | 0.370453 | 0.287218 |
import sys
import time
import copy
import tensorflow as tf
import numpy as np
import scipy.io as sio
from pysit.util.io import *
from pysit.util.parallel import ParallelWrapShotNull
__all__=['pCN']
__docformat__ = "restructuredtext en"
class pCN(object):
""" Class of pCN type MCMC method for UQ and optimization... | pysit/MCMC/pCN.py | import sys
import time
import copy
import tensorflow as tf
import numpy as np
import scipy.io as sio
from pysit.util.io import *
from pysit.util.parallel import ParallelWrapShotNull
__all__=['pCN']
__docformat__ = "restructuredtext en"
class pCN(object):
""" Class of pCN type MCMC method for UQ and optimization... | 0.520984 | 0.354629 |
import json
import logging
import os
from typing import Any
from typing import Dict
from typing import List
from typing import Optional
from typing import Sequence
from typing import Set
from typing import Tuple
import pre_commit.constants as C
from pre_commit.clientlib import load_manifest
from pre_commit.clientlib i... | pre_commit/repository.py | import json
import logging
import os
from typing import Any
from typing import Dict
from typing import List
from typing import Optional
from typing import Sequence
from typing import Set
from typing import Tuple
import pre_commit.constants as C
from pre_commit.clientlib import load_manifest
from pre_commit.clientlib i... | 0.708717 | 0.14016 |
import exodus
DATABASE_PATH = "baseline.g"
# Test outputing c-type arrays and numpy arrays
ARRAY_TYPES = ['ctype', 'numpy']
for array_type in ARRAY_TYPES:
EXO = exodus.exodus(DATABASE_PATH, array_type=array_type)
print("Exodus file has title:", EXO.title())
print("Exodus file has", EXO.num_dimensions(), ... | SEACAS-Test/test_exo.py | import exodus
DATABASE_PATH = "baseline.g"
# Test outputing c-type arrays and numpy arrays
ARRAY_TYPES = ['ctype', 'numpy']
for array_type in ARRAY_TYPES:
EXO = exodus.exodus(DATABASE_PATH, array_type=array_type)
print("Exodus file has title:", EXO.title())
print("Exodus file has", EXO.num_dimensions(), ... | 0.264928 | 0.145631 |
import pytest
from xarray import DataArray
import scipy.stats as st
from numpy import (
argmin,
array,
concatenate,
dot,
exp,
eye,
kron,
nan,
reshape,
sqrt,
zeros,
)
from numpy.random import RandomState
from numpy.testing import assert_allclose, assert_array_equal
from pandas... | limix/qtl/test/test_qtl_scan.py | import pytest
from xarray import DataArray
import scipy.stats as st
from numpy import (
argmin,
array,
concatenate,
dot,
exp,
eye,
kron,
nan,
reshape,
sqrt,
zeros,
)
from numpy.random import RandomState
from numpy.testing import assert_allclose, assert_array_equal
from pandas... | 0.501953 | 0.523055 |
from typing import Callable, List, Optional, Sequence, cast
from copy import deepcopy
import hydra
import numpy as np
import omegaconf
import torch
import torch.distributions
import mbrl.models
import mbrl.types
import mbrl.util.math
from torch.serialization import save
from .core import Agent, complete_agent_cfg
f... | mbrl/planning/gradient_optimizer.py | from typing import Callable, List, Optional, Sequence, cast
from copy import deepcopy
import hydra
import numpy as np
import omegaconf
import torch
import torch.distributions
import mbrl.models
import mbrl.types
import mbrl.util.math
from torch.serialization import save
from .core import Agent, complete_agent_cfg
f... | 0.914684 | 0.474205 |
import enum
import json
from typing import List
import pytest
from chika.chika import ChikaArgumentParser, bounded, choices, config, required, sequence, with_help
def test_simple_case():
@config
class A:
a: int
b: int = 2
c: bool = False
d: bool = True
e: str = "test"... | tests/test_parser.py | import enum
import json
from typing import List
import pytest
from chika.chika import ChikaArgumentParser, bounded, choices, config, required, sequence, with_help
def test_simple_case():
@config
class A:
a: int
b: int = 2
c: bool = False
d: bool = True
e: str = "test"... | 0.664214 | 0.768255 |
from utilities.aws_resources.load_balancer import LoadBalancer
from utilities.aws_resources.target_group import TargetGroup
from utilities.aws_resources.listener import Listener
from utilities.aws_resources.security_group import SecurityGroup
from utilities.aws_resources.launch_configuration import LaunchConfiguration
... | infraestructure/utilities/groups/frontend.py | from utilities.aws_resources.load_balancer import LoadBalancer
from utilities.aws_resources.target_group import TargetGroup
from utilities.aws_resources.listener import Listener
from utilities.aws_resources.security_group import SecurityGroup
from utilities.aws_resources.launch_configuration import LaunchConfiguration
... | 0.453988 | 0.054601 |
import argparse
import inspect
import os
import os.path as osp
import sys
import random
from glob import glob
import queue
import threading
from concurrent.futures import ThreadPoolExecutor
current_dir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
parent_dir = os.path.dirname(current_dir... | preprocessing/extract_feat_with_tta.py |
import argparse
import inspect
import os
import os.path as osp
import sys
import random
from glob import glob
import queue
import threading
from concurrent.futures import ThreadPoolExecutor
current_dir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
parent_dir = os.path.dirname(current_dir... | 0.386185 | 0.152537 |
try:
from ._models_py3 import Account
from ._models_py3 import AccountList
from ._models_py3 import AccountUpdateParameters
from ._models_py3 import AdlsGen1FileDataSet
from ._models_py3 import AdlsGen1FolderDataSet
from ._models_py3 import AdlsGen2FileDataSet
from ._models_py3 import AdlsG... | src/datashare/azext_datashare/vendored_sdks/datashare/models/__init__.py |
try:
from ._models_py3 import Account
from ._models_py3 import AccountList
from ._models_py3 import AccountUpdateParameters
from ._models_py3 import AdlsGen1FileDataSet
from ._models_py3 import AdlsGen1FolderDataSet
from ._models_py3 import AdlsGen2FileDataSet
from ._models_py3 import AdlsG... | 0.441673 | 0.094052 |
from typing import Dict, Set, Type, NamedTuple
from javalang import tree
from javalang.ast import Node
from aibolit.ast_framework import ASTNodeType
class ASTNodeReference(NamedTuple):
node_index: int
javalang_to_ast_node_type: Dict[Type[Node], ASTNodeType] = {
tree.Annotation: ASTNodeType.ANNOTATION,
... | aibolit/ast_framework/_auxiliary_data.py |
from typing import Dict, Set, Type, NamedTuple
from javalang import tree
from javalang.ast import Node
from aibolit.ast_framework import ASTNodeType
class ASTNodeReference(NamedTuple):
node_index: int
javalang_to_ast_node_type: Dict[Type[Node], ASTNodeType] = {
tree.Annotation: ASTNodeType.ANNOTATION,
... | 0.715921 | 0.411052 |
from dp_tornado.engine.schema import Table as dpTable
from dp_tornado.engine.schema import Attribute as dpAttribute
class ArticlesSchema(dpTable):
__table_name__ = 'articles'
article_id = dpAttribute.field(dpAttribute.DataType.INT, ai=True, pk=True, nn=True, un=True, comment='Article ID')
title = dpAtt... | dp_tornado/engine/template/bbs/schema/bbs/articles.py |
from dp_tornado.engine.schema import Table as dpTable
from dp_tornado.engine.schema import Attribute as dpAttribute
class ArticlesSchema(dpTable):
__table_name__ = 'articles'
article_id = dpAttribute.field(dpAttribute.DataType.INT, ai=True, pk=True, nn=True, un=True, comment='Article ID')
title = dpAtt... | 0.558207 | 0.306598 |
# 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... | fedlab_benchmarks/datasets/covtype/covtype.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... | 0.823896 | 0.283935 |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from collections import namedtuple
import ray.cloudpickle as cloudpickle
import copy
from datetime import datetime
import logging
import json
import uuid
import time
import tempfile
import os
from numbers impor... | python/ray/tune/trial.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from collections import namedtuple
import ray.cloudpickle as cloudpickle
import copy
from datetime import datetime
import logging
import json
import uuid
import time
import tempfile
import os
from numbers impor... | 0.758421 | 0.156266 |
import numpy as np
import json as js
import socket
import pickle
import base64 as b64
import zlib as zl
import sys
from multiprocessing import Process, Queue, Value, Manager
from ctypes import c_char_p
TCP_IP = '127.0.0.1'
TCP_PORT = 5014
BUFFER_SIZE = 20 # Normally 1024, but we want fast response
MAX_NUMBER_WORKERS ... | weightgrad/parameter_server.py | import numpy as np
import json as js
import socket
import pickle
import base64 as b64
import zlib as zl
import sys
from multiprocessing import Process, Queue, Value, Manager
from ctypes import c_char_p
TCP_IP = '127.0.0.1'
TCP_PORT = 5014
BUFFER_SIZE = 20 # Normally 1024, but we want fast response
MAX_NUMBER_WORKERS ... | 0.098409 | 0.13243 |
import numpy as np
import scipy.sparse as sp
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.init import xavier_uniform_
from utils import normt_spm, spm_to_tensor
class GraphConv(nn.Module):
def __init__(self, in_channels, out_channels, dropout=False, relu=True):
super... | models/gcn_dense.py | import numpy as np
import scipy.sparse as sp
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.init import xavier_uniform_
from utils import normt_spm, spm_to_tensor
class GraphConv(nn.Module):
def __init__(self, in_channels, out_channels, dropout=False, relu=True):
super... | 0.920074 | 0.321154 |
from ...ucscentralmo import ManagedObject
from ...ucscentralcoremeta import UcsCentralVersion, MoPropertyMeta, MoMeta
from ...ucscentralmeta import VersionMeta
class AdaptorEthInterruptProfileConsts():
MODE_INTX = "intx"
MODE_MSI = "msi"
MODE_MSI_X = "msi-x"
class AdaptorEthInterruptProfile(ManagedObje... | ucscentralsdk/mometa/adaptor/AdaptorEthInterruptProfile.py |
from ...ucscentralmo import ManagedObject
from ...ucscentralcoremeta import UcsCentralVersion, MoPropertyMeta, MoMeta
from ...ucscentralmeta import VersionMeta
class AdaptorEthInterruptProfileConsts():
MODE_INTX = "intx"
MODE_MSI = "msi"
MODE_MSI_X = "msi-x"
class AdaptorEthInterruptProfile(ManagedObje... | 0.457379 | 0.181028 |
import datetime
import os
from airflow import models
from airflow.contrib.operators import dataproc_operator
from airflow.utils import trigger_rule
# Output file for Cloud Dataproc job.
output_file = os.path.join(
models.Variable.get('gcs_bucket'), 'wordcount',
datetime.datetime.now().strftime('%Y%m%d-%H%M%S'... | gcpServices/composer/quickstart.py | import datetime
import os
from airflow import models
from airflow.contrib.operators import dataproc_operator
from airflow.utils import trigger_rule
# Output file for Cloud Dataproc job.
output_file = os.path.join(
models.Variable.get('gcs_bucket'), 'wordcount',
datetime.datetime.now().strftime('%Y%m%d-%H%M%S'... | 0.474631 | 0.291056 |
import re
from html.parser import HTMLParser
from typing import Any, Dict, Iterator, List, Optional, Tuple
from docx import Document
from docx.enum.text import WD_ALIGN_PARAGRAPH
from docx.shared import Pt
from docx.text.paragraph import Paragraph
from docx.text.run import Run
from tinycss2 import parse_declaration_li... | html2docx/html2docx.py | import re
from html.parser import HTMLParser
from typing import Any, Dict, Iterator, List, Optional, Tuple
from docx import Document
from docx.enum.text import WD_ALIGN_PARAGRAPH
from docx.shared import Pt
from docx.text.paragraph import Paragraph
from docx.text.run import Run
from tinycss2 import parse_declaration_li... | 0.790611 | 0.190197 |
from absl import logging
from typing import Dict
from icubam import authenticator
from icubam.messaging.telegram import bot
class UpdateFetcher:
"""Constantly fetches updates from the telegram server.
The UpdateFetcher is only used in dev mode when the webhook is not
for convenience.
"""
def __init__(se... | icubam/messaging/telegram/updater.py | from absl import logging
from typing import Dict
from icubam import authenticator
from icubam.messaging.telegram import bot
class UpdateFetcher:
"""Constantly fetches updates from the telegram server.
The UpdateFetcher is only used in dev mode when the webhook is not
for convenience.
"""
def __init__(se... | 0.676513 | 0.154472 |
from splitter import split
# it should split compound word (English)
def test_split_english():
split_result = split('artutility', 'en_us')
assert split_result[0] == 'art', '%s != "art"' % (split_result[0])
assert split_result[1] == 'utility', '%s != "utility"' % (split_result[1])
assert len(split_res... | tests/test_compound_word_splitter.py |
from splitter import split
# it should split compound word (English)
def test_split_english():
split_result = split('artutility', 'en_us')
assert split_result[0] == 'art', '%s != "art"' % (split_result[0])
assert split_result[1] == 'utility', '%s != "utility"' % (split_result[1])
assert len(split_res... | 0.626467 | 0.581927 |
# region Import
from sys import path
from os.path import dirname, abspath
project_root_path = dirname(dirname(dirname(abspath(__file__))))
utils_path = project_root_path + "/Utils/"
path.append(utils_path)
from base import Base
from network import Ethernet_raw, ARP_raw, IP_raw, UDP_raw, DHCP_raw
from sys import exit
... | Scripts/Apple/apple_rogue_dhcp.py |
# region Import
from sys import path
from os.path import dirname, abspath
project_root_path = dirname(dirname(dirname(abspath(__file__))))
utils_path = project_root_path + "/Utils/"
path.append(utils_path)
from base import Base
from network import Ethernet_raw, ARP_raw, IP_raw, UDP_raw, DHCP_raw
from sys import exit
... | 0.337859 | 0.052619 |
import os
import glob
import psycopg2
import pandas as pd
from sql_queries import *
def process_song_file(cur, filepath):
"""
parameters:
-----------------------------
cur:postges from main function tha allows the execute, commmit, and close statement to be envoked
filepath: String the path ... | etl.py | import os
import glob
import psycopg2
import pandas as pd
from sql_queries import *
def process_song_file(cur, filepath):
"""
parameters:
-----------------------------
cur:postges from main function tha allows the execute, commmit, and close statement to be envoked
filepath: String the path ... | 0.316898 | 0.461017 |
from __future__ import absolute_import
import gzip
import os
import pickle
import sys
import time
import pytest
from sagemaker import KMeans, KMeansModel
from sagemaker.utils import unique_name_from_base
from tests.integ import DATA_DIR, TRAINING_DEFAULT_TIMEOUT_MINUTES
from tests.integ.timeout import timeout, timeo... | tests/integ/test_kmeans.py | from __future__ import absolute_import
import gzip
import os
import pickle
import sys
import time
import pytest
from sagemaker import KMeans, KMeansModel
from sagemaker.utils import unique_name_from_base
from tests.integ import DATA_DIR, TRAINING_DEFAULT_TIMEOUT_MINUTES
from tests.integ.timeout import timeout, timeo... | 0.517571 | 0.336822 |
from django.contrib import messages
from django.shortcuts import redirect
from django.template.response import TemplateResponse
from django.utils.translation import pgettext
from ..forms import (
AnonymousUserBillingForm, BillingAddressesForm,
BillingWithoutShippingAddressForm)
from ...userprofile.forms import... | saleor/checkout/views/summary.py | from django.contrib import messages
from django.shortcuts import redirect
from django.template.response import TemplateResponse
from django.utils.translation import pgettext
from ..forms import (
AnonymousUserBillingForm, BillingAddressesForm,
BillingWithoutShippingAddressForm)
from ...userprofile.forms import... | 0.560373 | 0.095223 |
from __future__ import annotations
import asyncio
import logging
import subprocess
from typing import Any, Dict, Optional, Tuple
from typing_extensions import TypedDict
from bme280 import BME280
from enviroplus import gas
from ltr559 import LTR559
from pms5003 import (
PMS5003,
ChecksumMismatchError as PMS500... | src/enviro_mqtt/data.py | from __future__ import annotations
import asyncio
import logging
import subprocess
from typing import Any, Dict, Optional, Tuple
from typing_extensions import TypedDict
from bme280 import BME280
from enviroplus import gas
from ltr559 import LTR559
from pms5003 import (
PMS5003,
ChecksumMismatchError as PMS500... | 0.78108 | 0.463809 |
__author__ = '<NAME>'
from typing import Set, Dict, List, Union
from abc import ABCMeta, abstractmethod
import logging
import os
from io import TextIOBase, StringIO
from pathlib import Path
from copy import deepcopy
from configparser import ConfigParser, ExtendedInterpolation
from ..persist.domain import Primeable
fro... | src/python/zensols/config/iniconfig.py | __author__ = '<NAME>'
from typing import Set, Dict, List, Union
from abc import ABCMeta, abstractmethod
import logging
import os
from io import TextIOBase, StringIO
from pathlib import Path
from copy import deepcopy
from configparser import ConfigParser, ExtendedInterpolation
from ..persist.domain import Primeable
fro... | 0.771155 | 0.121529 |
import warnings
import yfinance as yf
from pathlib import Path
import numpy as np
import pandas as pd
import requests
import seaborn as sns
import matplotlib as mpl
from matplotlib import pyplot as plt
from datetime import datetime, date
from yahooquery import Ticker
from tensorflow.keras.callbacks import ModelCheckpoi... | src/models/forecast/web_univariate_timeSeries_rnn.py | import warnings
import yfinance as yf
from pathlib import Path
import numpy as np
import pandas as pd
import requests
import seaborn as sns
import matplotlib as mpl
from matplotlib import pyplot as plt
from datetime import datetime, date
from yahooquery import Ticker
from tensorflow.keras.callbacks import ModelCheckpoi... | 0.663778 | 0.356503 |
import subprocess
import os
import shutil
import sys
import re
import pytest
import numpy as np
#==============================================================================
# UTILITIES
#==============================================================================
#-------------------------------------------------... | tests/pyccel/test_pyccel.py | import subprocess
import os
import shutil
import sys
import re
import pytest
import numpy as np
#==============================================================================
# UTILITIES
#==============================================================================
#-------------------------------------------------... | 0.198996 | 0.169991 |
# Future
from __future__ import absolute_import, division, print_function, \
unicode_literals, with_statement
# Standard Library
from multiprocessing.synchronize import Lock
# First Party
from metaopt.concurrent.employer.employer import Employer
from metaopt.concurrent.employer.util. \
determine_worker_count ... | metaopt/concurrent/employer/process.py | # Future
from __future__ import absolute_import, division, print_function, \
unicode_literals, with_statement
# Standard Library
from multiprocessing.synchronize import Lock
# First Party
from metaopt.concurrent.employer.employer import Employer
from metaopt.concurrent.employer.util. \
determine_worker_count ... | 0.696371 | 0.14624 |
from .material_dicts import get_material_dict
class InvalidStringMaterialError(KeyError): pass
class InvalidGaugeError(ValueError): pass
class OutOfRangeError(ValueError): pass
class GuitarString():
def __init__(self, gauge, string_material):
self.is_valid_string_material(string_material)
self.str... | calculator/stringcalculator/string/guitar_string.py | from .material_dicts import get_material_dict
class InvalidStringMaterialError(KeyError): pass
class InvalidGaugeError(ValueError): pass
class OutOfRangeError(ValueError): pass
class GuitarString():
def __init__(self, gauge, string_material):
self.is_valid_string_material(string_material)
self.str... | 0.851768 | 0.382026 |
"""Check all our redirects from remora to zamboni."""
from olympia.amo.tests import TestCase
class TestRedirects(TestCase):
def test_accept_language(self):
"""
Given an Accept Language header, do the right thing. See bug 439568
for juicy details.
"""
response = self.clie... | src/olympia/amo/tests/test_redirects.py | """Check all our redirects from remora to zamboni."""
from olympia.amo.tests import TestCase
class TestRedirects(TestCase):
def test_accept_language(self):
"""
Given an Accept Language header, do the right thing. See bug 439568
for juicy details.
"""
response = self.clie... | 0.725649 | 0.264112 |
import os
import sys
import cv2
import time
import logging
import json
import tensorflow as tf
import numpy as np
import glob
import tqdm
tf.compat.v1.disable_eager_execution()
sys.path.append(os.path.join(os.path.dirname(__file__), os.pardir))
import src
from src.data_manager import EmojifierDataManager
from src.__in... | src/script/facial_expression_emoji/src/trainer.py | import os
import sys
import cv2
import time
import logging
import json
import tensorflow as tf
import numpy as np
import glob
import tqdm
tf.compat.v1.disable_eager_execution()
sys.path.append(os.path.join(os.path.dirname(__file__), os.pardir))
import src
from src.data_manager import EmojifierDataManager
from src.__in... | 0.4436 | 0.291208 |
import json
class Element(object):
def __init__(self, title, image_url=None, subtitle=None, default_action=None, buttons=None):
"""
:param title:
:param image_url:
:param subtitle:
:param default_action:
:param buttons:
"""
if not title:
... | aiobook/core/facebook/types/elements.py | import json
class Element(object):
def __init__(self, title, image_url=None, subtitle=None, default_action=None, buttons=None):
"""
:param title:
:param image_url:
:param subtitle:
:param default_action:
:param buttons:
"""
if not title:
... | 0.553505 | 0.115711 |
import copy
import datetime
import time
import zopkio.constants as constants
class Results(object):
def __init__(self, config, tests):
"""
:param config: config object
:param tests: {test.name: test object}
"""
self.config_result = config
self.test_results = tests
class ResultsCollector(o... | zopkio/results_collector.py |
import copy
import datetime
import time
import zopkio.constants as constants
class Results(object):
def __init__(self, config, tests):
"""
:param config: config object
:param tests: {test.name: test object}
"""
self.config_result = config
self.test_results = tests
class ResultsCollector(o... | 0.592313 | 0.415907 |
import torch
from torch import nn
from backbone.origin.from_origin import Backbone_R50_Custumed, Backbone_V16_Custumed
from module.BaseBlocks import BasicConv2d
from utils.tensor_ops import cus_sample, upsample_add
class R50BasicEncoder(nn.Module):
def __init__(self):
super(R50BasicEncoder, self).__init_... | module/BaseModule.py | import torch
from torch import nn
from backbone.origin.from_origin import Backbone_R50_Custumed, Backbone_V16_Custumed
from module.BaseBlocks import BasicConv2d
from utils.tensor_ops import cus_sample, upsample_add
class R50BasicEncoder(nn.Module):
def __init__(self):
super(R50BasicEncoder, self).__init_... | 0.886027 | 0.407746 |
__all__ = ["api"]
import flask
import feedfinder2
from functools import wraps
from flask.ext.login import current_user
from .database import db
from .models import User, Feed
api = flask.Blueprint("api", __name__)
def _get_user():
token = flask.request.values.get("token")
if token is not None:
ret... | ugly/api.py |
__all__ = ["api"]
import flask
import feedfinder2
from functools import wraps
from flask.ext.login import current_user
from .database import db
from .models import User, Feed
api = flask.Blueprint("api", __name__)
def _get_user():
token = flask.request.values.get("token")
if token is not None:
ret... | 0.658747 | 0.087564 |
import logging
import multiprocessing
import os
from collections import defaultdict
from datetime import datetime
import numpy as np
import pandas as pd
from pandas import DataFrame, Series
from sklearn.model_selection import KFold, StratifiedKFold, RepeatedKFold, RepeatedStratifiedKFold, train_test_split
from .const... | autogluon/utils/tabular/ml/utils.py | import logging
import multiprocessing
import os
from collections import defaultdict
from datetime import datetime
import numpy as np
import pandas as pd
from pandas import DataFrame, Series
from sklearn.model_selection import KFold, StratifiedKFold, RepeatedKFold, RepeatedStratifiedKFold, train_test_split
from .const... | 0.479747 | 0.30072 |
import MySQLdb
import sys
import os
from importlib import import_module
USING_DB = 'default'
if __name__ == '__main__':
if len(sys.argv) < 2:
print("File name of netflow required")
exit(1)
FNAME = sys.argv[1]
cur_dir = os.path.dirname(os.path.abspath(__file__))
tmp_dir = '/tmp/djin... | agent/netflow/netflow_handler.py | import MySQLdb
import sys
import os
from importlib import import_module
USING_DB = 'default'
if __name__ == '__main__':
if len(sys.argv) < 2:
print("File name of netflow required")
exit(1)
FNAME = sys.argv[1]
cur_dir = os.path.dirname(os.path.abspath(__file__))
tmp_dir = '/tmp/djin... | 0.084869 | 0.048541 |
from ..note import Note
from ..log import parser_logger as log
from ..log import notetype_logger as nlog
from .. import notetype_loader
from ..helper.formatHelper import is_emptytext
from .. import config
from ..config import dict as conf
from ..helper.formatHelper import linestrip, list2str
from enum import Enum
def... | AnkiIn/parser/markdown.py | from ..note import Note
from ..log import parser_logger as log
from ..log import notetype_logger as nlog
from .. import notetype_loader
from ..helper.formatHelper import is_emptytext
from .. import config
from ..config import dict as conf
from ..helper.formatHelper import linestrip, list2str
from enum import Enum
def... | 0.343672 | 0.137243 |
import numpy as np
import pandas as pd
k = 6
a2 = [0, 0, 6.52, 6.52, 6.52, 6.52]
b3 = [6.52, 6.52, 6.52, 6.52, 6.52, 6.52]
def A1(sm):
dummyA1 = pd.DataFrame()
for j in range(0,k):
dummyA1[j] = np.prod(sm[sm.columns[0:j+1]], axis = 1)*(-1)**(j+1)
return dummyA1.sum(axis=1)
def A2(sm):
dummyA2 = pd.DataFrame(... | testfunctions.py | import numpy as np
import pandas as pd
k = 6
a2 = [0, 0, 6.52, 6.52, 6.52, 6.52]
b3 = [6.52, 6.52, 6.52, 6.52, 6.52, 6.52]
def A1(sm):
dummyA1 = pd.DataFrame()
for j in range(0,k):
dummyA1[j] = np.prod(sm[sm.columns[0:j+1]], axis = 1)*(-1)**(j+1)
return dummyA1.sum(axis=1)
def A2(sm):
dummyA2 = pd.DataFrame(... | 0.190875 | 0.354852 |
import datetime
import enum
import attr
import six
from dbnd._core.utils.timezone import make_aware, utcnow
RESULT_PARAM = "result"
CURRENT_DATETIME = utcnow()
CURRENT_TIME_STR = CURRENT_DATETIME.strftime("%Y%m%d_%H%M%S")
CURRENT_DATE = CURRENT_DATETIME.date()
class EnvLabel(object): # env label
dev = "dev"... | modules/dbnd/src/dbnd/_core/constants.py | import datetime
import enum
import attr
import six
from dbnd._core.utils.timezone import make_aware, utcnow
RESULT_PARAM = "result"
CURRENT_DATETIME = utcnow()
CURRENT_TIME_STR = CURRENT_DATETIME.strftime("%Y%m%d_%H%M%S")
CURRENT_DATE = CURRENT_DATETIME.date()
class EnvLabel(object): # env label
dev = "dev"... | 0.557364 | 0.128689 |
import os
import socket
import sys
import time
from multiprocessing import Semaphore, JoinableQueue, Queue, Process
from typing import Any, Dict, Iterator, Union
import pytest
from _pytest.config import _prepareconfig
import pytest_cov.embed
import resource
from pytest_mproc import resource_utilization
from pytest_mp... | src/pytest_mproc/worker.py | import os
import socket
import sys
import time
from multiprocessing import Semaphore, JoinableQueue, Queue, Process
from typing import Any, Dict, Iterator, Union
import pytest
from _pytest.config import _prepareconfig
import pytest_cov.embed
import resource
from pytest_mproc import resource_utilization
from pytest_mp... | 0.542621 | 0.229859 |
from .. import util
from . import util as import_util
import sys
from types import MethodType
import unittest
class UseCache(unittest.TestCase):
"""When it comes to sys.modules, import prefers it over anything else.
Once a name has been resolved, sys.modules is checked to see if it contains
the module d... | Lib/importlib/test/import_/test_caching.py | from .. import util
from . import util as import_util
import sys
from types import MethodType
import unittest
class UseCache(unittest.TestCase):
"""When it comes to sys.modules, import prefers it over anything else.
Once a name has been resolved, sys.modules is checked to see if it contains
the module d... | 0.332419 | 0.31875 |
import io
from svganimator.CameraEvent import CameraEvent
from svganimator import SvgUtils
from svganimator import HtmlUtils as Html
import xml.etree.ElementTree as ET
import unittest
class TestCameraEvent(unittest.TestCase):
root = ET.fromstring('''
<svg
xmlns="http://www.w3.org/2000/svg"
... | tests/test_CameraEvent.py | import io
from svganimator.CameraEvent import CameraEvent
from svganimator import SvgUtils
from svganimator import HtmlUtils as Html
import xml.etree.ElementTree as ET
import unittest
class TestCameraEvent(unittest.TestCase):
root = ET.fromstring('''
<svg
xmlns="http://www.w3.org/2000/svg"
... | 0.648244 | 0.351089 |
passports = []
def parseFields(passport):
parsedPassport = {}
fields = passport[:-1].split(" ")
for field in fields:
pair = field.split(":", 1)
parsedPassport[pair[0]] = pair[1]
return parsedPassport
def validatePassportFields(passport):
return bool(validatePassportFieldBirthYear(... | 2020/day-04/day-04b.py | passports = []
def parseFields(passport):
parsedPassport = {}
fields = passport[:-1].split(" ")
for field in fields:
pair = field.split(":", 1)
parsedPassport[pair[0]] = pair[1]
return parsedPassport
def validatePassportFields(passport):
return bool(validatePassportFieldBirthYear(... | 0.294215 | 0.271656 |
import numpy as np
import pandas as pd
from pymbar.timeseries import (statisticalInefficiency,
detectEquilibration,
subsampleCorrelatedData, )
def _check_multiple_times(df):
if isinstance(df, pd.Series):
return df.sort_index(0).reset_index('tim... | src/alchemlyb/preprocessing/subsampling.py | import numpy as np
import pandas as pd
from pymbar.timeseries import (statisticalInefficiency,
detectEquilibration,
subsampleCorrelatedData, )
def _check_multiple_times(df):
if isinstance(df, pd.Series):
return df.sort_index(0).reset_index('tim... | 0.842507 | 0.673802 |
import halide as hl
import numpy as np
import gc
def test_ndarray_to_buffer():
a0 = np.ones((200, 300), dtype=np.int32)
# Buffer always shares data (when possible) by default,
# and maintains the shape of the data source. (note that
# the ndarray is col-major by default!)
b0 = hl.Buffer(a0, "float... | Halide/python_bindings/correctness/buffer.py | import halide as hl
import numpy as np
import gc
def test_ndarray_to_buffer():
a0 = np.ones((200, 300), dtype=np.int32)
# Buffer always shares data (when possible) by default,
# and maintains the shape of the data source. (note that
# the ndarray is col-major by default!)
b0 = hl.Buffer(a0, "float... | 0.751283 | 0.734334 |
from __future__ import unicode_literals
from __future__ import print_function
from __future__ import division
from __future__ import absolute_import
import argparse
import os
import pandas as pd
import tensorflow as tf
import numpy as np
from dltk.core.metrics import dice
from dltk.networks.segmentation.unet import r... | contributions/applications/experiment4/train.py | from __future__ import unicode_literals
from __future__ import print_function
from __future__ import division
from __future__ import absolute_import
import argparse
import os
import pandas as pd
import tensorflow as tf
import numpy as np
from dltk.core.metrics import dice
from dltk.networks.segmentation.unet import r... | 0.883305 | 0.311414 |
import collections
import os
import math
from dopamine.agents.multi_head import multi_head_ddqn_agent
import gin
import tensorflow as tf
import numpy as np
import random
@gin.configurable
class MultiHeadUCBAgent(multi_head_ddqn_agent.MultiHeadDDQNAgent):
"""DQN agent with multiple heads and UCB to select the best... | dopamine/agents/multi_head_ucb/multi_head_ucb_agent.py |
import collections
import os
import math
from dopamine.agents.multi_head import multi_head_ddqn_agent
import gin
import tensorflow as tf
import numpy as np
import random
@gin.configurable
class MultiHeadUCBAgent(multi_head_ddqn_agent.MultiHeadDDQNAgent):
"""DQN agent with multiple heads and UCB to select the best... | 0.736685 | 0.277247 |
import wave
import info
from datetime import timedelta
def parse_time_to_microsecs(time):
try:
if type(time) is timedelta:
return time.microseconds
if type(time) is str:
import datetime
formats = [float, int, "%M:%S", "%H:%M:%S"]
stime = None
... | cut.py | import wave
import info
from datetime import timedelta
def parse_time_to_microsecs(time):
try:
if type(time) is timedelta:
return time.microseconds
if type(time) is str:
import datetime
formats = [float, int, "%M:%S", "%H:%M:%S"]
stime = None
... | 0.284974 | 0.235537 |
from dataclasses import asdict
from pathlib import Path
from tempfile import TemporaryDirectory
from unittest.mock import patch, MagicMock
import numpy as np
import pandas as pd
import pytest
from sm.engine.annotation.diagnostics import sanity_check_fdr_diagnostics
from sm.engine.annotation.fdr import FDR
from sm.eng... | metaspace/engine/tests/test_msm_basic_search_integr.py | from dataclasses import asdict
from pathlib import Path
from tempfile import TemporaryDirectory
from unittest.mock import patch, MagicMock
import numpy as np
import pandas as pd
import pytest
from sm.engine.annotation.diagnostics import sanity_check_fdr_diagnostics
from sm.engine.annotation.fdr import FDR
from sm.eng... | 0.677581 | 0.436022 |
import datetime
import random
import werkzeug
from odoo import http
from odoo.http import request
class Chess(http.Controller):
# chess chat
@http.route("/chess/game/chat/init", type="json", auth="public")
def init_chat(self, game_id):
author_name = http.request.env.user.name # current user
... | chess/controllers/main.py | import datetime
import random
import werkzeug
from odoo import http
from odoo.http import request
class Chess(http.Controller):
# chess chat
@http.route("/chess/game/chat/init", type="json", auth="public")
def init_chat(self, game_id):
author_name = http.request.env.user.name # current user
... | 0.431584 | 0.10466 |
from collections import Counter
from collections.abc import Mapping
from cascade.dismod.constants import WeightEnum
from cascade.model.covariates import Covariate
from cascade.model.dismod_groups import DismodGroups
from cascade.model.var import Var
from cascade.model.smooth_grid import uninformative_grid_from_var
c... | src/cascade/model/model.py | from collections import Counter
from collections.abc import Mapping
from cascade.dismod.constants import WeightEnum
from cascade.model.covariates import Covariate
from cascade.model.dismod_groups import DismodGroups
from cascade.model.var import Var
from cascade.model.smooth_grid import uninformative_grid_from_var
c... | 0.944382 | 0.526465 |
import sys
from pathlib import Path
from libtad.convert_time_service import ConvertTimeService
from libtad.datatypes.time import TADDateTime
from libtad.datatypes.places import LocationId
from configparser import ConfigParser
import unittest
config = ConfigParser()
config.read("tests/config.ini")
access_key = config... | tests/ConvertTimeTests.py | import sys
from pathlib import Path
from libtad.convert_time_service import ConvertTimeService
from libtad.datatypes.time import TADDateTime
from libtad.datatypes.places import LocationId
from configparser import ConfigParser
import unittest
config = ConfigParser()
config.read("tests/config.ini")
access_key = config... | 0.432303 | 0.401688 |
import os
import shutil
import argparse
from datetime import date
import numpy as np
import astropy.units as u
from astropy.table import Table, QTable
from joblib import Parallel, delayed
from spherical_geometry.polygon import SphericalPolygon
import lsst.log
Log = lsst.log.Log()
Log.setLevel(lsst.log.ERROR)
impo... | script/merian_tiger_cutout.py | import os
import shutil
import argparse
from datetime import date
import numpy as np
import astropy.units as u
from astropy.table import Table, QTable
from joblib import Parallel, delayed
from spherical_geometry.polygon import SphericalPolygon
import lsst.log
Log = lsst.log.Log()
Log.setLevel(lsst.log.ERROR)
impo... | 0.79166 | 0.38266 |
from collections import defaultdict
from tqdm import tqdm
import torch
class Engine:
def __init__(self, system, device=None):
self.system = system
self.device = device
self.callbacks = []
self.epoch = 0
def fit(self,
loader_train,
loader_val=None,
... | jaffalearn/engine.py | from collections import defaultdict
from tqdm import tqdm
import torch
class Engine:
def __init__(self, system, device=None):
self.system = system
self.device = device
self.callbacks = []
self.epoch = 0
def fit(self,
loader_train,
loader_val=None,
... | 0.899938 | 0.224735 |
# Standard imports
from __future__ import absolute_import
# Third party imports
import numpy as np
import pytest
# CARS imports
from cars.steps.epi_rectif import resampling
from cars.steps.matching import sparse_matching
# CARS Tests imports
from ...helpers import absolute_data_path
@pytest.mark.unit_tests
def tes... | tests/steps/matching/test_sparse_matching.py | # Standard imports
from __future__ import absolute_import
# Third party imports
import numpy as np
import pytest
# CARS imports
from cars.steps.epi_rectif import resampling
from cars.steps.matching import sparse_matching
# CARS Tests imports
from ...helpers import absolute_data_path
@pytest.mark.unit_tests
def tes... | 0.781831 | 0.452415 |
from resource_management.core.resources.system import Execute, File
from resource_management.core.logger import Logger
from resource_management.libraries.script.script import Script
from resource_management.libraries.functions.format import format
from resource_management.libraries.functions.check_process_status import... | ambari-server/src/main/resources/common-services/AMBARI_INFRA/0.1.0/package/scripts/infra_solr.py | from resource_management.core.resources.system import Execute, File
from resource_management.core.logger import Logger
from resource_management.libraries.script.script import Script
from resource_management.libraries.functions.format import format
from resource_management.libraries.functions.check_process_status import... | 0.245627 | 0.074265 |
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.model_selection import KFold
from multiprocessing import Pool
from settings.config import user_label, TEST_SIZE, N_CORES, K_FOLDS_VALUES
from settings.language_strings import LANGUAGE_TOTAL_USERS, LANGUAGE_MERGE_PREFERENCES_INTO_DF
... | code/preprocessing/split.py | import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.model_selection import KFold
from multiprocessing import Pool
from settings.config import user_label, TEST_SIZE, N_CORES, K_FOLDS_VALUES
from settings.language_strings import LANGUAGE_TOTAL_USERS, LANGUAGE_MERGE_PREFERENCES_INTO_DF
... | 0.391871 | 0.203332 |
from __future__ import print_function
__all__ = [
"getAccounts",
"getAccountsDataset",
"getPhoneNumbers",
"getPhoneNumbersDataset",
"sendSms",
]
from system.dataset import Dataset
def getAccounts():
"""Return a list of Twilio accounts that have been configured in the
Gateway.
Return... | src/system/twilio.py | from __future__ import print_function
__all__ = [
"getAccounts",
"getAccountsDataset",
"getPhoneNumbers",
"getPhoneNumbersDataset",
"sendSms",
]
from system.dataset import Dataset
def getAccounts():
"""Return a list of Twilio accounts that have been configured in the
Gateway.
Return... | 0.86771 | 0.385028 |
import json
from common.constant import StatusCode
from dapp_user.exceptions import BadRequestException
from common.logger import get_logger
from common.utils import validate_dict_list, handle_exception_with_slack_notification, generate_lambda_response
from dapp_user.config import SLACK_HOOK, NETWORK_ID
from dapp_user... | dapp_user/application/handlers/user_handlers.py | import json
from common.constant import StatusCode
from dapp_user.exceptions import BadRequestException
from common.logger import get_logger
from common.utils import validate_dict_list, handle_exception_with_slack_notification, generate_lambda_response
from dapp_user.config import SLACK_HOOK, NETWORK_ID
from dapp_user... | 0.351979 | 0.089893 |
import os
import sys
import nextcord
import yaml
from nextcord.ext import commands
import ratemyprofessor
if "CompsciBot" not in str(os.getcwd()):
os.chdir("./CompsciBot")
with open("config.yaml") as file:
config = yaml.load(file, Loader=yaml.FullLoader)
class RateMyProfessor(commands.Cog, name="rate my profe... | cogs/ratemyprofessor.py | import os
import sys
import nextcord
import yaml
from nextcord.ext import commands
import ratemyprofessor
if "CompsciBot" not in str(os.getcwd()):
os.chdir("./CompsciBot")
with open("config.yaml") as file:
config = yaml.load(file, Loader=yaml.FullLoader)
class RateMyProfessor(commands.Cog, name="rate my profe... | 0.356223 | 0.227899 |
from predict_pv_yield.models.perceiver.perceiver_conv3d_nwp_sat import Model, params, TOTAL_SEQ_LEN
from predict_pv_yield.data.dataloader import FakeDataset
import torch
from nowcasting_dataset.config.model import Configuration
def test_init_model():
"""Initilize the model"""
_ = Model(
history_minu... | tests/models/perceiver/test_perceiver_conv3d_sat_nwp.py | from predict_pv_yield.models.perceiver.perceiver_conv3d_nwp_sat import Model, params, TOTAL_SEQ_LEN
from predict_pv_yield.data.dataloader import FakeDataset
import torch
from nowcasting_dataset.config.model import Configuration
def test_init_model():
"""Initilize the model"""
_ = Model(
history_minu... | 0.711431 | 0.565239 |
from pathlib import Path
import yaml
from simod.configuration import config_data_from_file, AndPriorORemove, Configuration, GateManagement, MiningAlgorithm, \
CalendarType, DataType, PDFMethod, Metric, ExecutionMode, SimulatorKind
class TestConfigurationFromStringConversion:
def test_MiningAlgorithm_from_st... | tests/test_configuration.py | from pathlib import Path
import yaml
from simod.configuration import config_data_from_file, AndPriorORemove, Configuration, GateManagement, MiningAlgorithm, \
CalendarType, DataType, PDFMethod, Metric, ExecutionMode, SimulatorKind
class TestConfigurationFromStringConversion:
def test_MiningAlgorithm_from_st... | 0.693577 | 0.38145 |
class Heapq:
# 堆调整方法：调整为大顶堆
def heapAdjust(self, nums: [int], index: int, end: int):
left = index * 2 + 1
right = left + 1
while left <= end:
# 当前节点为非叶子结点
max_index = index
if nums[left] > nums[max_index]:
max_index = left
if right <= end and nums[right] > nums[max_index]:
max_index = right
... | Templates/04.Queue/Queue-PriorityQueue.py | class Heapq:
# 堆调整方法：调整为大顶堆
def heapAdjust(self, nums: [int], index: int, end: int):
left = index * 2 + 1
right = left + 1
while left <= end:
# 当前节点为非叶子结点
max_index = index
if nums[left] > nums[max_index]:
max_index = left
if right <= end and nums[right] > nums[max_index]:
max_index = right
... | 0.231354 | 0.600188 |
# Pynfc is a python wrapper for the libnfc library
# Copyright (C) 2009 <NAME>
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 2
# of the License.
#
# This pro... | app/museolib/libs/mifareauth.py |
# Pynfc is a python wrapper for the libnfc library
# Copyright (C) 2009 <NAME>
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 2
# of the License.
#
# This pro... | 0.38885 | 0.101456 |
from datetime import datetime
from hashlib import sha1
def hashObj(data):
return sha1(repr(data).encode('utf-8')).hexdigest()
class LWWElementSet(object):
def __init__(self):
''' Initialize addSet and removeSet to empty dictionary. iData and iTimestamp
are the index of the data and times... | src/LWWElementGraph/LWWElementSet.py | from datetime import datetime
from hashlib import sha1
def hashObj(data):
return sha1(repr(data).encode('utf-8')).hexdigest()
class LWWElementSet(object):
def __init__(self):
''' Initialize addSet and removeSet to empty dictionary. iData and iTimestamp
are the index of the data and times... | 0.698227 | 0.263742 |
import functools
from qtpy.QtGui import QColor, QBrush
from qtpy.QtCore import Signal, Slot, Property, QTimer, Qt
from .. import utilities
from pyqtgraph import PlotWidget, PlotDataItem, mkPen, ViewBox, InfiniteLine, SignalProxy, CurvePoint, TextItem
from collections import OrderedDict
from .base import PyDMPrimitiveWi... | pydm/widgets/baseplot.py | import functools
from qtpy.QtGui import QColor, QBrush
from qtpy.QtCore import Signal, Slot, Property, QTimer, Qt
from .. import utilities
from pyqtgraph import PlotWidget, PlotDataItem, mkPen, ViewBox, InfiniteLine, SignalProxy, CurvePoint, TextItem
from collections import OrderedDict
from .base import PyDMPrimitiveWi... | 0.859074 | 0.349921 |
from os import path
from datetime import datetime
import zmq
import time
import os
import json
import numpy as np
import requests
import sys
import gc
from selfdrive.kegman_conf import kegman_conf
from common.params import Params
if len(sys.argv) < 2 or sys.argv[1] == 0:
destination = "gernstation.synol... | upload_files.py | from os import path
from datetime import datetime
import zmq
import time
import os
import json
import numpy as np
import requests
import sys
import gc
from selfdrive.kegman_conf import kegman_conf
from common.params import Params
if len(sys.argv) < 2 or sys.argv[1] == 0:
destination = "gernstation.synol... | 0.037091 | 0.055081 |
import unittest
import torch
import numpy as np
from src.machinery.GradientUpdateMethod import ArtemisUpdate
from src.machinery.Parameters import *
from src.machinery.PredefinedParameters import *
from src.machinery.Worker import Worker
nb_samples = 5
zero_tensor = torch.zeros(DIM, dtype=np.float)
ones_tensor = torc... | test/testArtemisUpdate.py | import unittest
import torch
import numpy as np
from src.machinery.GradientUpdateMethod import ArtemisUpdate
from src.machinery.Parameters import *
from src.machinery.PredefinedParameters import *
from src.machinery.Worker import Worker
nb_samples = 5
zero_tensor = torch.zeros(DIM, dtype=np.float)
ones_tensor = torc... | 0.759939 | 0.61451 |