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 os, sys
import numpy as np
here = os.path.abspath(os.path.dirname(__file__))
CODE_SUB_DIR = os.path.abspath(os.path.join(here, "..", ".."))
print(CODE_SUB_DIR)
sys.path.append(CODE_SUB_DIR)
from at_speech import SLLRLiblinear, SLLRSag, ThinResnet34Classifier
from at_speech.data_space.raw_data_space import Raw... | AutoDL_sample_code_submission/at_speech/policy_space/model_executor.py | import os, sys
import numpy as np
here = os.path.abspath(os.path.dirname(__file__))
CODE_SUB_DIR = os.path.abspath(os.path.join(here, "..", ".."))
print(CODE_SUB_DIR)
sys.path.append(CODE_SUB_DIR)
from at_speech import SLLRLiblinear, SLLRSag, ThinResnet34Classifier
from at_speech.data_space.raw_data_space import Raw... | 0.217338 | 0.127029 |
from __future__ import absolute_import
import sys
import os
import re
# python 2 and python 3 compatibility library
from six import iteritems
from ..configuration import Configuration
from ..api_client import ApiClient
class V3utilsApi(object):
"""
NOTE: This class is auto generated by the swagger code gen... | whoville/cloudbreak/apis/v3utils_api.py | from __future__ import absolute_import
import sys
import os
import re
# python 2 and python 3 compatibility library
from six import iteritems
from ..configuration import Configuration
from ..api_client import ApiClient
class V3utilsApi(object):
"""
NOTE: This class is auto generated by the swagger code gen... | 0.601711 | 0.07221 |
# Step1: preprocess_data.py
import os
file_input_data = '../../umap_dataset/data/whole_annotation_data_336_modified_taxonomy.json'
content_features = 1
structural_features = 1
sentiment_features = 1
conversational_features = 1
feature_normalization = 0
model_name = 'cnn_base'
max_sequence_length = 50
max_num_... | user_intent_prediction/model_cnn_base/script_cnn_base.py |
# Step1: preprocess_data.py
import os
file_input_data = '../../umap_dataset/data/whole_annotation_data_336_modified_taxonomy.json'
content_features = 1
structural_features = 1
sentiment_features = 1
conversational_features = 1
feature_normalization = 0
model_name = 'cnn_base'
max_sequence_length = 50
max_num_... | 0.5794 | 0.299086 |
import subprocess
import os
from spotdl.encode import EncoderBase
from spotdl.encode.exceptions import EncoderNotFoundError
from spotdl.encode.exceptions import FFmpegNotFoundError
import logging
logger = logging.getLogger(__name__)
# Key: from format
# Subkey: to format
RULES = {
"m4a": {
"mp3": "-code... | spotdl/encode/encoders/ffmpeg.py | import subprocess
import os
from spotdl.encode import EncoderBase
from spotdl.encode.exceptions import EncoderNotFoundError
from spotdl.encode.exceptions import FFmpegNotFoundError
import logging
logger = logging.getLogger(__name__)
# Key: from format
# Subkey: to format
RULES = {
"m4a": {
"mp3": "-code... | 0.428831 | 0.12787 |
from django.db.models import Q, F
from rest_framework import viewsets, serializers
from rest_framework.filters import SearchFilter
from rest_framework.response import Response
from rest_framework.views import APIView
from models import Recipe, Ingredient
def search_by_time_ingredients(ingredients, time, queryset):
... | recipe-search/recipe/serializers.py | from django.db.models import Q, F
from rest_framework import viewsets, serializers
from rest_framework.filters import SearchFilter
from rest_framework.response import Response
from rest_framework.views import APIView
from models import Recipe, Ingredient
def search_by_time_ingredients(ingredients, time, queryset):
... | 0.749821 | 0.199016 |
__author__ = 'buec'
import xml.etree.ElementTree as et
from pyspeechgrammar import model
class SRGSXMLSerializer:
def create_grammar_element(self, grammar):
grammar_element = et.Element('grammar')
for rule in grammar.rules:
rule_element = self.create_rule_element(rule)
... | pyspeechgrammar/srgs_xml/serialize.py | __author__ = 'buec'
import xml.etree.ElementTree as et
from pyspeechgrammar import model
class SRGSXMLSerializer:
def create_grammar_element(self, grammar):
grammar_element = et.Element('grammar')
for rule in grammar.rules:
rule_element = self.create_rule_element(rule)
... | 0.483892 | 0.197696 |
from typing import Iterator, List, Union, Optional
import numpy as np
import logging
from syne_tune.optimizer.schedulers.searchers.bayesopt.tuning_algorithms.base_classes \
import CandidateGenerator
from syne_tune.optimizer.schedulers.searchers.bayesopt.datatypes.common \
import Configuration, ConfigurationFil... | syne_tune/optimizer/schedulers/searchers/bayesopt/tuning_algorithms/common.py | from typing import Iterator, List, Union, Optional
import numpy as np
import logging
from syne_tune.optimizer.schedulers.searchers.bayesopt.tuning_algorithms.base_classes \
import CandidateGenerator
from syne_tune.optimizer.schedulers.searchers.bayesopt.datatypes.common \
import Configuration, ConfigurationFil... | 0.864153 | 0.342599 |
import re
import requests
import time
import sys
from random import randint
from urlparse import urlparse
headers = {"Connection": "keep-alive",
"Upgrade-Insecure-Requests": "1",
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/56.0.292... | FogOfWar/fogofweb.py | import re
import requests
import time
import sys
from random import randint
from urlparse import urlparse
headers = {"Connection": "keep-alive",
"Upgrade-Insecure-Requests": "1",
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/56.0.292... | 0.097005 | 0.085251 |
# Importing the libraries
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
# Importing the dataset
dataset = pd.read_csv('diabetes.csv')
X = dataset.iloc[:, :-1].values
y = dataset.iloc[:, 8].values
#taking care of missing data
from sklearn.preprocessing import Imputer
imputer = Imputer(missing... | decision_tree.py |
# Importing the libraries
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
# Importing the dataset
dataset = pd.read_csv('diabetes.csv')
X = dataset.iloc[:, :-1].values
y = dataset.iloc[:, 8].values
#taking care of missing data
from sklearn.preprocessing import Imputer
imputer = Imputer(missing... | 0.764276 | 0.67698 |
from .____init___6 import *
import typing
import System.IO
import System.Collections.Generic
import System
import QuantConnect.Indicators
import QuantConnect.Data.Market
import QuantConnect.Data
import QuantConnect
import Python.Runtime
import datetime
class IndicatorExtensions(System.object):
""" Provides extens... | Algorithm.Python/stubs/QuantConnect/Indicators/____init___5.py | from .____init___6 import *
import typing
import System.IO
import System.Collections.Generic
import System
import QuantConnect.Indicators
import QuantConnect.Data.Market
import QuantConnect.Data
import QuantConnect
import Python.Runtime
import datetime
class IndicatorExtensions(System.object):
""" Provides extens... | 0.853547 | 0.324329 |
class Solution:
def numberToWords(self, num):
"""
:type num: int
:rtype: str
"""
# 维护一个数字到英语的转换字典
self.IntEng = {
"0": 'Zero',
"1": 'One',
"2": 'Two',
"3": 'Three',
"4": 'Four',
"5": 'Five',
... | LeetCode/2019-02-04-273-Integer-to-English-Words.py |
class Solution:
def numberToWords(self, num):
"""
:type num: int
:rtype: str
"""
# 维护一个数字到英语的转换字典
self.IntEng = {
"0": 'Zero',
"1": 'One',
"2": 'Two',
"3": 'Three',
"4": 'Four',
"5": 'Five',
... | 0.487551 | 0.548794 |
# IMPORTOWANIE
from pylab import *
import ephem as ep
# OBSERVATEUR
obs = ep.Observer()
# TUNIS
obs.lon, obs.lat, obs.elev = '10.08', '36.4', 100.0
obs.name= "SAT-TUNIS"
# NOUS CRÉONS UN OBJET
# on vérifie si c'est sous l'horizon
soleil = ep.Sun()
lune = ep.Moon()
venus = ep.Venus()
mars = ep.Mars()
jupiter = ep.Jupit... | docs/.src/programs/planet_conj.py | # IMPORTOWANIE
from pylab import *
import ephem as ep
# OBSERVATEUR
obs = ep.Observer()
# TUNIS
obs.lon, obs.lat, obs.elev = '10.08', '36.4', 100.0
obs.name= "SAT-TUNIS"
# NOUS CRÉONS UN OBJET
# on vérifie si c'est sous l'horizon
soleil = ep.Sun()
lune = ep.Moon()
venus = ep.Venus()
mars = ep.Mars()
jupiter = ep.Jupit... | 0.127544 | 0.242183 |
import ctypes
import os
from typing import List, Dict, Union
import numpy as np
from jinja2 import Template
from deep500.lv0.operators.cmake_wrapper import cmake, try_mkdirs
from deep500.lv0.operators.op_compiler import CompilableOp
from deep500.utils.tensor_desc import TensorDescriptor
from deep500.lv0.operators.ope... | deep500/frameworks/reference/custom_operators/base.py | import ctypes
import os
from typing import List, Dict, Union
import numpy as np
from jinja2 import Template
from deep500.lv0.operators.cmake_wrapper import cmake, try_mkdirs
from deep500.lv0.operators.op_compiler import CompilableOp
from deep500.utils.tensor_desc import TensorDescriptor
from deep500.lv0.operators.ope... | 0.569134 | 0.447219 |
import os
from pathlib import Path
import cloudinary
import cloudinary.api
import cloudinary.uploader
import sentry_sdk
from dotenv import load_dotenv
from sentry_sdk.integrations.django import DjangoIntegration
load_dotenv() # take environment variables from .env.
BASE_DIR = Path(__file__).resolve().... | Project/settings.py | import os
from pathlib import Path
import cloudinary
import cloudinary.api
import cloudinary.uploader
import sentry_sdk
from dotenv import load_dotenv
from sentry_sdk.integrations.django import DjangoIntegration
load_dotenv() # take environment variables from .env.
BASE_DIR = Path(__file__).resolve().... | 0.186169 | 0.053576 |
import pprint
import re # noqa: F401
import six
from swagger_client.configuration import Configuration
class CellSiteChannel(object):
"""NOTE: This class is auto generated by the swagger code generator program.
Do not edit the class manually.
"""
"""
Attributes:
swagger_types (dict): Th... | Wigle/python-client/swagger_client/models/cell_site_channel.py | import pprint
import re # noqa: F401
import six
from swagger_client.configuration import Configuration
class CellSiteChannel(object):
"""NOTE: This class is auto generated by the swagger code generator program.
Do not edit the class manually.
"""
"""
Attributes:
swagger_types (dict): Th... | 0.772616 | 0.192862 |
import math
import os
import digitalio
import board
import time
from adafruit_rgb_display.rgb import color565
import adafruit_rgb_display.st7789 as st7789
from PIL import Image, ImageDraw, ImageFont
from fonts.ttf import RobotoMedium
import busio
import adafruit_vl53l0x
i2c = busio.I2C(board.SCL, board.SDA)
vl53 = ad... | main.py |
import math
import os
import digitalio
import board
import time
from adafruit_rgb_display.rgb import color565
import adafruit_rgb_display.st7789 as st7789
from PIL import Image, ImageDraw, ImageFont
from fonts.ttf import RobotoMedium
import busio
import adafruit_vl53l0x
i2c = busio.I2C(board.SCL, board.SDA)
vl53 = ad... | 0.419291 | 0.199347 |
import random
import numpy as np
from scipy.stats import norm
import time
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import matplotlib.gridspec as gridspec
# From Theano tutorial - MNIST dataset
from logistic_sgd import load_data
import theano
import theano.tensor as T
start_time = time.time()
n_la... | hard-gists/651afb13d45e4c587f63/snippet.py | import random
import numpy as np
from scipy.stats import norm
import time
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import matplotlib.gridspec as gridspec
# From Theano tutorial - MNIST dataset
from logistic_sgd import load_data
import theano
import theano.tensor as T
start_time = time.time()
n_la... | 0.734691 | 0.479321 |
from django.shortcuts import render
from django.http import HttpResponse, JsonResponse
import os
import json
from bs4 import BeautifulSoup
import requests
import re
import datetime
from mp.models import Config
def get_one(request):
myconfig = Config.objects.all().first()
if myconfig.apichange:
res = re... | zfnweb/one/views.py | from django.shortcuts import render
from django.http import HttpResponse, JsonResponse
import os
import json
from bs4 import BeautifulSoup
import requests
import re
import datetime
from mp.models import Config
def get_one(request):
myconfig = Config.objects.all().first()
if myconfig.apichange:
res = re... | 0.099361 | 0.034521 |
import uuid
import django.db.models
from django.core.exceptions import ValidationError
from django.forms import CharField
from django.utils.translation import gettext_lazy as _
import shortuuid
def short_uuid4():
return shortuuid.encode(uuid.uuid4())
def decode(value):
"""Decode the value from ShortUUID t... | native_shortuuid/fields.py | import uuid
import django.db.models
from django.core.exceptions import ValidationError
from django.forms import CharField
from django.utils.translation import gettext_lazy as _
import shortuuid
def short_uuid4():
return shortuuid.encode(uuid.uuid4())
def decode(value):
"""Decode the value from ShortUUID t... | 0.542379 | 0.135032 |
import os
from functools import lru_cache
from aws_cdk.aws_efs import IAccessPoint
from aws_cdk.aws_lambda import Code, Runtime, FileSystem as LambdaFileSystem, Function
from aws_cdk.aws_s3 import Bucket
from aws_cdk.core import Stack, Duration
from aws_cdk.lambda_layer_awscli import AwsCliLayer
from b_cfn_s3_large_d... | b_cfn_s3_large_deployment/function.py | import os
from functools import lru_cache
from aws_cdk.aws_efs import IAccessPoint
from aws_cdk.aws_lambda import Code, Runtime, FileSystem as LambdaFileSystem, Function
from aws_cdk.aws_s3 import Bucket
from aws_cdk.core import Stack, Duration
from aws_cdk.lambda_layer_awscli import AwsCliLayer
from b_cfn_s3_large_d... | 0.417628 | 0.048812 |
from torch.nn import functional as F
from dassl.engine import TRAINER_REGISTRY, TrainerX
from dassl.metrics import compute_accuracy
from torch.cuda.amp import autocast
from dassl.utils import count_num_param
from dassl.optim import build_optimizer, build_lr_scheduler
from dassl.modeling import build_backbone
@TRAINE... | dassl/engine/dg/rsc.py | from torch.nn import functional as F
from dassl.engine import TRAINER_REGISTRY, TrainerX
from dassl.metrics import compute_accuracy
from torch.cuda.amp import autocast
from dassl.utils import count_num_param
from dassl.optim import build_optimizer, build_lr_scheduler
from dassl.modeling import build_backbone
@TRAINE... | 0.809803 | 0.308333 |
from discord.ext.commands import group
import math
import discord
class Math:
def __init__(self, bot):
self.bot = bot
@group(invoke_without_command=True, aliases=["maths"])
async def math(self, ctx):
"""Various mathematical functions, collected for your enjoyment."""
if ctx.invoke... | cogs/math.py | from discord.ext.commands import group
import math
import discord
class Math:
def __init__(self, bot):
self.bot = bot
@group(invoke_without_command=True, aliases=["maths"])
async def math(self, ctx):
"""Various mathematical functions, collected for your enjoyment."""
if ctx.invoke... | 0.718002 | 0.286609 |
from PySide2 import QtCore
qt_resource_data = b"\
\x00\x00\x08\xd9\
\x89\
PNG\x0d\x0a\x1a\x0a\x00\x00\x00\x0dIHDR\x00\
\x00\x00\x18\x00\x00\x00\x18\x08\x06\x00\x00\x00\xe0w=\xf8\
\x00\x00\x00\x09pHYs\x00\x00\x16%\x00\x00\x16%\
\x01IR$\xf0\x00\x00\x05\xf1iTXtXML\
:com.adobe.xmp\x00\x00\
\x00\x00\x00<?xpacket beg\
in=\... | conversor_divisor/resources_cd_rc.py |
from PySide2 import QtCore
qt_resource_data = b"\
\x00\x00\x08\xd9\
\x89\
PNG\x0d\x0a\x1a\x0a\x00\x00\x00\x0dIHDR\x00\
\x00\x00\x18\x00\x00\x00\x18\x08\x06\x00\x00\x00\xe0w=\xf8\
\x00\x00\x00\x09pHYs\x00\x00\x16%\x00\x00\x16%\
\x01IR$\xf0\x00\x00\x05\xf1iTXtXML\
:com.adobe.xmp\x00\x00\
\x00\x00\x00<?xpacket beg\
in=\... | 0.270288 | 0.279853 |
import benchmarkstt.docblock as docblock
from textwrap import dedent
import pytest
def test_text():
txt = " \t \t\n\n\t "
assert docblock.process_rst(txt, 'text') == ''
txt = '''
.. code-block:: text
Some block
In samem block
Still included
Not anymore
'''
print(... | tests/benchmarkstt/test_docblock.py | import benchmarkstt.docblock as docblock
from textwrap import dedent
import pytest
def test_text():
txt = " \t \t\n\n\t "
assert docblock.process_rst(txt, 'text') == ''
txt = '''
.. code-block:: text
Some block
In samem block
Still included
Not anymore
'''
print(... | 0.372277 | 0.486758 |
import numpy as np
import pandas as pd
import sys
import matplotlib
matplotlib.use("pgf")
import time
from matplotlib import pyplot as plt
from sklearn.model_selection import GridSearchCV, TimeSeriesSplit
from sklearn.preprocessing import MinMaxScaler
from sklearn.metrics import mean_squared_error, mean_absolute_error
... | src/health_lstm.py | import numpy as np
import pandas as pd
import sys
import matplotlib
matplotlib.use("pgf")
import time
from matplotlib import pyplot as plt
from sklearn.model_selection import GridSearchCV, TimeSeriesSplit
from sklearn.preprocessing import MinMaxScaler
from sklearn.metrics import mean_squared_error, mean_absolute_error
... | 0.70912 | 0.322033 |
import configargparse
from pathlib import Path
from icalendar import Calendar, Event
import datetime
import os
import requests
parser = configargparse.ArgParser(default_config_files=['~/.config/calreader.ini'],description="""
Downloads a webcal file and schedules an external file to run at
the beginn... | calreader2.py | import configargparse
from pathlib import Path
from icalendar import Calendar, Event
import datetime
import os
import requests
parser = configargparse.ArgParser(default_config_files=['~/.config/calreader.ini'],description="""
Downloads a webcal file and schedules an external file to run at
the beginn... | 0.255251 | 0.159512 |
import pprint
import re # noqa: F401
import six
from swagger_client.configuration import Configuration
class TpdmStaffTeacherPreparationProviderAssociation(object):
"""NOTE: This class is auto generated by the swagger code generator program.
Do not edit the class manually.
"""
"""
Attributes:... | src/v5.1/resources/swagger_client/models/tpdm_staff_teacher_preparation_provider_association.py | import pprint
import re # noqa: F401
import six
from swagger_client.configuration import Configuration
class TpdmStaffTeacherPreparationProviderAssociation(object):
"""NOTE: This class is auto generated by the swagger code generator program.
Do not edit the class manually.
"""
"""
Attributes:... | 0.64791 | 0.102125 |
import io
import typing as t
from django_docker_helpers.config.backends.base import BaseParser
from django_docker_helpers.config.exceptions import KVStorageValueIsEmpty
from .yaml_parser import YamlParser
class RedisParser(BaseParser):
"""
Reads a whole config bundle from a redis key and provides the unifie... | django_docker_helpers/config/backends/redis_parser.py | import io
import typing as t
from django_docker_helpers.config.backends.base import BaseParser
from django_docker_helpers.config.exceptions import KVStorageValueIsEmpty
from .yaml_parser import YamlParser
class RedisParser(BaseParser):
"""
Reads a whole config bundle from a redis key and provides the unifie... | 0.817975 | 0.123102 |
import numpy as np
from time import time
from math import sqrt, ceil, floor, log
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
import scipy.integrate as integrate
# find the primes up to and including limit
def sieve_of_eratosthenes(limit):
limit = floor(limit)
possible_prim... | Prototypes/Graph Plots/prime_counting_function_plot.py |
import numpy as np
from time import time
from math import sqrt, ceil, floor, log
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
import scipy.integrate as integrate
# find the primes up to and including limit
def sieve_of_eratosthenes(limit):
limit = floor(limit)
possible_prim... | 0.806472 | 0.49585 |
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from .. import _utilities
from . import outputs
from ._inputs import *
__all__ = [
'GetVantagePointsResult',
'AwaitableGetVantagePointsResult',
'get_vantage_points',
]
@pulumi.output_t... | sdk/python/pulumi_oci/healthchecks/get_vantage_points.py |
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from .. import _utilities
from . import outputs
from ._inputs import *
__all__ = [
'GetVantagePointsResult',
'AwaitableGetVantagePointsResult',
'get_vantage_points',
]
@pulumi.output_t... | 0.778607 | 0.17522 |
import arcpy
import os.path
import os
import sys
from pprint import pprint
import pdb
records = [108814,109019,116056,116097,123383,167,191,203,210,290,306,310,321,406,414,422,432,440,514,518,56995,56997,57000,57002,57004,57172,57174,57177,57178,57181,57182,57186,57241,57242,57440,57694,57695,57699,57702,58041,58042,... | defineProjections.py |
import arcpy
import os.path
import os
import sys
from pprint import pprint
import pdb
records = [108814,109019,116056,116097,123383,167,191,203,210,290,306,310,321,406,414,422,432,440,514,518,56995,56997,57000,57002,57004,57172,57174,57177,57178,57181,57182,57186,57241,57242,57440,57694,57695,57699,57702,58041,58042,... | 0.221098 | 0.064594 |
from digitalsky_provider.models import DigitalSkyLog
from gcs_operations.models import CloudFile, FlightPlan, FlightOperation, Transaction, FlightPermission, FlightLog
from pki_framework.models import AerobridgeCredential
from registry.models import Person, Address, Activity, Authorization, Operator, Contact, Test, Typ... | tests/test_models/test_models_delete.py | from digitalsky_provider.models import DigitalSkyLog
from gcs_operations.models import CloudFile, FlightPlan, FlightOperation, Transaction, FlightPermission, FlightLog
from pki_framework.models import AerobridgeCredential
from registry.models import Person, Address, Activity, Authorization, Operator, Contact, Test, Typ... | 0.606848 | 0.507141 |
from constants import EOS_TOKEN, MAX_LENGTH, DEVICE
import numpy as np
import torch
class Lang:
def __init__(self, name):
self.name = name
self.word2index = {}
self.word2count = {}
self.index2word = {0: "SOS", 1: "EOS"}
self.n_words = 2 # Count SOS and EOS
def addSe... | src/Learning/preprocessing.py | from constants import EOS_TOKEN, MAX_LENGTH, DEVICE
import numpy as np
import torch
class Lang:
def __init__(self, name):
self.name = name
self.word2index = {}
self.word2count = {}
self.index2word = {0: "SOS", 1: "EOS"}
self.n_words = 2 # Count SOS and EOS
def addSe... | 0.516352 | 0.322206 |
import sys
from config import *
INT_MIN = -sys.maxsize - 1
def reversed_kronecker(cell_1: int, cell_2: int):
"""
This function determines the interaction between cell_1 and cell_2. Here were are going to implement a reversed
Kronecker Delta function ie. if the two cells are the same, they will not intera... | research/cpm-vqe/interaction_helper.py | import sys
from config import *
INT_MIN = -sys.maxsize - 1
def reversed_kronecker(cell_1: int, cell_2: int):
"""
This function determines the interaction between cell_1 and cell_2. Here were are going to implement a reversed
Kronecker Delta function ie. if the two cells are the same, they will not intera... | 0.804675 | 0.866923 |
import re
from calendar import monthrange
from datetime import datetime
from bs4 import BeautifulSoup
from requests import get
from .console import console
from .logger import logger
from .sanitize import sanitize_metar, sanitize_taf
TODAY = datetime.now()
OGIMET_LIMIT_MESAGE = "#Sorry, Your quota limit for slow qu... | tafver_metars/download.py |
import re
from calendar import monthrange
from datetime import datetime
from bs4 import BeautifulSoup
from requests import get
from .console import console
from .logger import logger
from .sanitize import sanitize_metar, sanitize_taf
TODAY = datetime.now()
OGIMET_LIMIT_MESAGE = "#Sorry, Your quota limit for slow qu... | 0.347094 | 0.177882 |
from operator import itemgetter
# 3rd party
import numpy
from domdf_python_tools.paths import PathPlus
# ==========================
print("Part One")
# ==========================
lines = PathPlus("input.txt").read_lines()
earliest = int(lines[0])
buses = sorted(map(int, filter(str.isdigit, lines[1].split(','))))
p... | 13/code.py | from operator import itemgetter
# 3rd party
import numpy
from domdf_python_tools.paths import PathPlus
# ==========================
print("Part One")
# ==========================
lines = PathPlus("input.txt").read_lines()
earliest = int(lines[0])
buses = sorted(map(int, filter(str.isdigit, lines[1].split(','))))
p... | 0.544801 | 0.344251 |
def autoencoder (epoch, batch, latent, encoder_o, encoder_i, \
decoder_i, decoder_o, train_percent, lam, norm_order, loss_plot):
"""
This module is autoencoder neural network which gets input data and
reduces the dimension and returns similar data to the input. Data
compression is useful for future... | autoencoder.py | def autoencoder (epoch, batch, latent, encoder_o, encoder_i, \
decoder_i, decoder_o, train_percent, lam, norm_order, loss_plot):
"""
This module is autoencoder neural network which gets input data and
reduces the dimension and returns similar data to the input. Data
compression is useful for future... | 0.919995 | 0.908374 |
# 利用华为ups检测机房是否停电
# 停电后发送企业微信告警并对主要服务器关机
import sys
import os
import time
import ssl
import json
import http.cookiejar
import paramiko
from urllib import parse, request
# ----------------------企业微信配置开始------------------------------------
corpid = '你自己的pid'
corpsecret = '你自己的key'
wx_url = 'https://qyapi.weixin.q... | web_login.py |
# 利用华为ups检测机房是否停电
# 停电后发送企业微信告警并对主要服务器关机
import sys
import os
import time
import ssl
import json
import http.cookiejar
import paramiko
from urllib import parse, request
# ----------------------企业微信配置开始------------------------------------
corpid = '你自己的pid'
corpsecret = '你自己的key'
wx_url = 'https://qyapi.weixin.q... | 0.164852 | 0.110136 |
import numpy as np
import pandas as pd
from math import floor
import sys
from .erorrs import NotBinaryData, NoSuchColumn
def warn(*args, **kwargs):
pass
import warnings
warnings.warn = warn
class ICOTE
def __init__(self, binary_columns : list = None, seed : 'int > 0' = 42) -> None:
'''
... | crucio/ICOTE.py | import numpy as np
import pandas as pd
from math import floor
import sys
from .erorrs import NotBinaryData, NoSuchColumn
def warn(*args, **kwargs):
pass
import warnings
warnings.warn = warn
class ICOTE
def __init__(self, binary_columns : list = None, seed : 'int > 0' = 42) -> None:
'''
... | 0.457621 | 0.403802 |
import numpy as np
import pandas as pd
from netfile.ipeds_file import IpedsFile
from database.ipeds_grad_rates import IpedsGraduationRate
from database.date_dimension import DateRow
from database.ipeds_demographic_dimension import IpedsDemographicDimension
class GraduationRateFile(IpedsFile):
def __init__(self, ... | netfile/graduation_rate_file.py |
import numpy as np
import pandas as pd
from netfile.ipeds_file import IpedsFile
from database.ipeds_grad_rates import IpedsGraduationRate
from database.date_dimension import DateRow
from database.ipeds_demographic_dimension import IpedsDemographicDimension
class GraduationRateFile(IpedsFile):
def __init__(self, ... | 0.219505 | 0.128689 |
import getpass
import pyaes
import sqlite3
import hashlib
import string
import random
conn = None
_name_lock = None
class Key:
_k = None
@staticmethod
def set(key: bytes):
if key is None:
Key._k = None
return
Key._k = list(key)
for i in range(len(Key._k))... | mysecure.py | import getpass
import pyaes
import sqlite3
import hashlib
import string
import random
conn = None
_name_lock = None
class Key:
_k = None
@staticmethod
def set(key: bytes):
if key is None:
Key._k = None
return
Key._k = list(key)
for i in range(len(Key._k))... | 0.241042 | 0.056159 |
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
import torch.nn.functional as F
__all__ = [
"build_act",
"ConvLayer",
"LinearLayer",
"SELayer",
"DsConvLayer",
"InvertedBlock",
"SeInvertedBlock",
"ResidualBlock",
"OpSequential",
]
def build_norm(n... | netaug/models/base/layers.py | from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
import torch.nn.functional as F
__all__ = [
"build_act",
"ConvLayer",
"LinearLayer",
"SELayer",
"DsConvLayer",
"InvertedBlock",
"SeInvertedBlock",
"ResidualBlock",
"OpSequential",
]
def build_norm(n... | 0.967271 | 0.409044 |
import os
import sys
import csv
import re
from math import ceil
from typing import Union
import pandas as pd
import dask.dataframe as dd
import argparse
from timeit import default_timer as timer
from enum import Enum
from PIL import Image
from pathlib import Path
from collections import namedtuple
from misc import re... | etl.py | import os
import sys
import csv
import re
from math import ceil
from typing import Union
import pandas as pd
import dask.dataframe as dd
import argparse
from timeit import default_timer as timer
from enum import Enum
from PIL import Image
from pathlib import Path
from collections import namedtuple
from misc import re... | 0.536313 | 0.201931 |
import socket
from sshuttle.firewall import subnet_weight
from sshuttle.linux import nft, nft_get_handle, nonfatal
from sshuttle.methods import BaseMethod
class Method(BaseMethod):
# We name the chain based on the transproxy port number so that it's
# possible to run multiple copies of sshuttle at the same t... | lib/python/lib/python3.6/site-packages/sshuttle-0.78.5.dev35+gaaa6684-py3.6.egg/sshuttle/methods/nft.py | import socket
from sshuttle.firewall import subnet_weight
from sshuttle.linux import nft, nft_get_handle, nonfatal
from sshuttle.methods import BaseMethod
class Method(BaseMethod):
# We name the chain based on the transproxy port number so that it's
# possible to run multiple copies of sshuttle at the same t... | 0.379378 | 0.131034 |
import pandas
import scipy
import numpy
def identity(x):
return x
def rolling_apply(df, window_size, f, trim=True, **kargs):
''' A function that will apply a window wise operation to the rows of a
dataframe, df.
input:
df - a pandas dataframe
window_size... | transformations.py | import pandas
import scipy
import numpy
def identity(x):
return x
def rolling_apply(df, window_size, f, trim=True, **kargs):
''' A function that will apply a window wise operation to the rows of a
dataframe, df.
input:
df - a pandas dataframe
window_size... | 0.764496 | 0.723926 |
""" Turing machine internals testing module """
from __future__ import unicode_literals, print_function
from turing import (TMSyntaxError, TMLocked, tokenizer, raw_rule_generator,
sequence_cant_have, evaluate_symbol_query, TuringMachine)
from pytest import raises, mark
p = mark.parametrize
class ... | test_turing.py | """ Turing machine internals testing module """
from __future__ import unicode_literals, print_function
from turing import (TMSyntaxError, TMLocked, tokenizer, raw_rule_generator,
sequence_cant_have, evaluate_symbol_query, TuringMachine)
from pytest import raises, mark
p = mark.parametrize
class ... | 0.747063 | 0.645288 |
import glob
import threading
import subprocess
from pathlib import Path
from typing import *
from concurrent.futures import ThreadPoolExecutor
from tqdm import tqdm
from .utils import progress_save
EXTRACT_SCRIPT = (Path(__file__).parent / "extract.py").resolve()
assert EXTRACT_SCRIPT.exists()
def main():
with p... | script/compile_all.py | import glob
import threading
import subprocess
from pathlib import Path
from typing import *
from concurrent.futures import ThreadPoolExecutor
from tqdm import tqdm
from .utils import progress_save
EXTRACT_SCRIPT = (Path(__file__).parent / "extract.py").resolve()
assert EXTRACT_SCRIPT.exists()
def main():
with p... | 0.303938 | 0.163245 |
from smtplib import SMTP
from abc import ABCMeta, abstractmethod
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
class EMailManager:
__metaclass__ = ABCMeta
@abstractmethod
def __init__(self):
raise NotImplemented
@abstractmethod
def __enter__(self):
... | notifier.py | from smtplib import SMTP
from abc import ABCMeta, abstractmethod
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
class EMailManager:
__metaclass__ = ABCMeta
@abstractmethod
def __init__(self):
raise NotImplemented
@abstractmethod
def __enter__(self):
... | 0.474875 | 0.084568 |
import pygame
from pygame.locals import *
from snake_classes import *
from constantes import *
import time
global t0
t0 = time.time()
pygame.init()
fenetre = pygame.display.set_mode((window_side,window_side+50))
fenetre.fill(WHITE)
pygame.display.set_caption(titre_fenetre)
grid = Grid(fenetre)
grid.display()
sna... | Snake.py | import pygame
from pygame.locals import *
from snake_classes import *
from constantes import *
import time
global t0
t0 = time.time()
pygame.init()
fenetre = pygame.display.set_mode((window_side,window_side+50))
fenetre.fill(WHITE)
pygame.display.set_caption(titre_fenetre)
grid = Grid(fenetre)
grid.display()
sna... | 0.206334 | 0.169372 |
from ..constants import (
COLOR_CANVAS_DARK,
COLOR_CANVAS_LIGHT,
COLOR_GRID_LIGHT,
COLOR_GRID_DARK,
COLOR_PLOT_TEXT_LIGHT,
COLOR_PLOT_TEXT_DARK,
COLOR_SLIDER_BORDER_DARK,
COLOR_SLIDER_BORDER_LIGHT,
COLOR_SLIDER_TICK_DARK,
COLOR_SLIDER_TICK_LIGHT,
COLOR_ZERO_LINE_LIGHT,
CO... | src/pyskindose/plotting/plot_settings.py | from ..constants import (
COLOR_CANVAS_DARK,
COLOR_CANVAS_LIGHT,
COLOR_GRID_LIGHT,
COLOR_GRID_DARK,
COLOR_PLOT_TEXT_LIGHT,
COLOR_PLOT_TEXT_DARK,
COLOR_SLIDER_BORDER_DARK,
COLOR_SLIDER_BORDER_LIGHT,
COLOR_SLIDER_TICK_DARK,
COLOR_SLIDER_TICK_LIGHT,
COLOR_ZERO_LINE_LIGHT,
CO... | 0.778776 | 0.18866 |
from datetime import datetime, timedelta
from flask import Blueprint, current_app, abort, request, jsonify
from flask_jwt_extended import (
create_access_token, jwt_required, jwt_optional, get_jwt_identity)
from .. import db
from ..models import User
from ..providers import ProviderError
from ..utils import valid... | app/controllers/auth.py | from datetime import datetime, timedelta
from flask import Blueprint, current_app, abort, request, jsonify
from flask_jwt_extended import (
create_access_token, jwt_required, jwt_optional, get_jwt_identity)
from .. import db
from ..models import User
from ..providers import ProviderError
from ..utils import valid... | 0.652241 | 0.101278 |
from __future__ import unicode_literals
from django.db import migrations, models
import assets.asset_helpers
import django.core.files.storage
class Migration(migrations.Migration):
dependencies = [
]
operations = [
migrations.CreateModel(
name='Asset',
fields=[
... | assets/migrations/0001_initial.py | from __future__ import unicode_literals
from django.db import migrations, models
import assets.asset_helpers
import django.core.files.storage
class Migration(migrations.Migration):
dependencies = [
]
operations = [
migrations.CreateModel(
name='Asset',
fields=[
... | 0.524151 | 0.121113 |
from aliyunsdkcore.request import RpcRequest
from aliyunsdkvpc.endpoint import endpoint_data
class ListVirtualPhysicalConnectionsRequest(RpcRequest):
def __init__(self):
RpcRequest.__init__(self, 'Vpc', '2016-04-28', 'ListVirtualPhysicalConnections','vpc')
self.set_method('POST')
if hasattr(self, "endpoint_m... | aliyun-python-sdk-vpc/aliyunsdkvpc/request/v20160428/ListVirtualPhysicalConnectionsRequest.py |
from aliyunsdkcore.request import RpcRequest
from aliyunsdkvpc.endpoint import endpoint_data
class ListVirtualPhysicalConnectionsRequest(RpcRequest):
def __init__(self):
RpcRequest.__init__(self, 'Vpc', '2016-04-28', 'ListVirtualPhysicalConnections','vpc')
self.set_method('POST')
if hasattr(self, "endpoint_m... | 0.387459 | 0.052887 |
import scrapy
import time
import psycopg2
import json
import requests
from scrapy_djangoitem import DjangoItem
from home.models import Publisher
from scrapy_djangoitem import DjangoItem
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
fr... | facebbok/facebbok/spiders/FBCrawlerWithDBCheck.py |
import scrapy
import time
import psycopg2
import json
import requests
from scrapy_djangoitem import DjangoItem
from home.models import Publisher
from scrapy_djangoitem import DjangoItem
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
fr... | 0.167355 | 0.050565 |
from __future__ import division
import numpy as np
from astropy.io import fits
from math import fsum
from warnings import warn
# TODO: Investigate using scipy.fftpack instead?
def pad_and_rfft_image(img, newshape):
"""
Pads the psf array to the size described by imgshape, then run rfft to put
it in Fourie... | psfMC/utils.py | from __future__ import division
import numpy as np
from astropy.io import fits
from math import fsum
from warnings import warn
# TODO: Investigate using scipy.fftpack instead?
def pad_and_rfft_image(img, newshape):
"""
Pads the psf array to the size described by imgshape, then run rfft to put
it in Fourie... | 0.611614 | 0.579757 |
import pandas as pd
from flask import Blueprint, request, jsonify
from src.extraction.data_management import Data
from src.metrics.cust_metric import get_auc_score
from src.predict import make_prediction, get_models_list
from src import __version__ as _version
from api.config import get_logger
from api.validation impo... | api/controller.py | import pandas as pd
from flask import Blueprint, request, jsonify
from src.extraction.data_management import Data
from src.metrics.cust_metric import get_auc_score
from src.predict import make_prediction, get_models_list
from src import __version__ as _version
from api.config import get_logger
from api.validation impo... | 0.69035 | 0.165998 |
import asyncio
import logging
import random
import re
import textwrap
from typing import Any, Dict
import aiohttp
import async_timeout
import discord
from discord.ext.commands import AutoShardedBot, Context, command, bot_has_permissions
from bot.converters import Snake
from bot.decorators import locked
from bot.utils... | bot/cogs/snakes.py | import asyncio
import logging
import random
import re
import textwrap
from typing import Any, Dict
import aiohttp
import async_timeout
import discord
from discord.ext.commands import AutoShardedBot, Context, command, bot_has_permissions
from bot.converters import Snake
from bot.decorators import locked
from bot.utils... | 0.67971 | 0.124372 |
from __future__ import print_function
from __future__ import division
import sys
sys.path.insert(1, "../../../")
import h2o
from tests import pyunit_utils
from h2o.estimators.model_selection import H2OModelSelectionEstimator as modelSelection
# test modelselection works with validation dataset
def test_modelselection_... | h2o-py/tests/testdir_algos/modelselection/pyunit_PUBDEV_8235_modelselection_gaussian_validation.py | from __future__ import print_function
from __future__ import division
import sys
sys.path.insert(1, "../../../")
import h2o
from tests import pyunit_utils
from h2o.estimators.model_selection import H2OModelSelectionEstimator as modelSelection
# test modelselection works with validation dataset
def test_modelselection_... | 0.419291 | 0.231973 |
from unittest import TestSuite
import mock
from requests import HTTPError
from contacthub.workspace import Workspace
from contacthub._api_manager._api_customer import _CustomerAPIManager
from tests.utility import FakeHTTPResponse
class TestCustomerAPIManager(TestSuite):
@classmethod
def setUp(cls):
... | tests/test_api_customer.py | from unittest import TestSuite
import mock
from requests import HTTPError
from contacthub.workspace import Workspace
from contacthub._api_manager._api_customer import _CustomerAPIManager
from tests.utility import FakeHTTPResponse
class TestCustomerAPIManager(TestSuite):
@classmethod
def setUp(cls):
... | 0.504394 | 0.218732 |
import tensorflow as tf
from typing import Optional, Tuple, Any
from utils.tfutils import get_activation, apply_noise
from .cell_utils import ugrnn
class UGRNNCell(tf.compat.v1.nn.rnn_cell.RNNCell):
def __init__(self, units: int, activation: str, name: str, recurrent_noise: tf.Tensor):
self._units = uni... | budget-rnn/src/layers/cells/standard_rnn_cells.py | import tensorflow as tf
from typing import Optional, Tuple, Any
from utils.tfutils import get_activation, apply_noise
from .cell_utils import ugrnn
class UGRNNCell(tf.compat.v1.nn.rnn_cell.RNNCell):
def __init__(self, units: int, activation: str, name: str, recurrent_noise: tf.Tensor):
self._units = uni... | 0.943387 | 0.298528 |
import numpy as np
import gym
from gym import spaces
from path_following.envs.envUtils import utils
from colorama import Fore, Style
class Tool5D(gym.Env):
metadata = {'render.modes': ['human', 'rgb_array']}
def __init__(self):
super(Tool5D, self).__init__()
"Initialize environment variables... | path_following/envs/tcp_Tool5D.py | import numpy as np
import gym
from gym import spaces
from path_following.envs.envUtils import utils
from colorama import Fore, Style
class Tool5D(gym.Env):
metadata = {'render.modes': ['human', 'rgb_array']}
def __init__(self):
super(Tool5D, self).__init__()
"Initialize environment variables... | 0.49707 | 0.374104 |
import os
import numpy as np
import tensorflow.keras.backend as K
from sklearn.base import BaseEstimator, TransformerMixin
from tensorflow.keras import regularizers
from tensorflow.keras.callbacks import EarlyStopping
from tensorflow.keras.layers import Dense, Input
from tensorflow.keras.models import Model
class Au... | code/ae.py | import os
import numpy as np
import tensorflow.keras.backend as K
from sklearn.base import BaseEstimator, TransformerMixin
from tensorflow.keras import regularizers
from tensorflow.keras.callbacks import EarlyStopping
from tensorflow.keras.layers import Dense, Input
from tensorflow.keras.models import Model
class Au... | 0.68056 | 0.208179 |
import re
import time
import string
import itertools as it
import numpy as np
import numba as nb
class ParserException (Exception):
""" Class to represent parser's exceptions """
@nb.vectorize(nopython = True, cache = True)
def np_bitwise_maj (x, y, z):
""" Bitwise MAJ function """
return (x & y) | (x &... | parser.py | import re
import time
import string
import itertools as it
import numpy as np
import numba as nb
class ParserException (Exception):
""" Class to represent parser's exceptions """
@nb.vectorize(nopython = True, cache = True)
def np_bitwise_maj (x, y, z):
""" Bitwise MAJ function """
return (x & y) | (x &... | 0.585338 | 0.413536 |
import ast
import operator
from peval.tools import Dispatcher, immutableadict, ast_equal, replace_fields
from peval.core.gensym import GenSym
from peval.core.reify import KnownValue, is_known_value, reify
from peval.wisdom import is_pure, get_signature
from peval.core.callable import inspect_callable
from peval.tools ... | peval/core/expression.py | import ast
import operator
from peval.tools import Dispatcher, immutableadict, ast_equal, replace_fields
from peval.core.gensym import GenSym
from peval.core.reify import KnownValue, is_known_value, reify
from peval.wisdom import is_pure, get_signature
from peval.core.callable import inspect_callable
from peval.tools ... | 0.63023 | 0.356615 |
from leapp.libraries.common import multipathutil
_regexes = ('vendor', 'product', 'revision', 'product_blacklist', 'devnode',
'wwid', 'property', 'protocol')
def _update_config(need_foreign, need_allow_usb, config):
if not (need_foreign or need_allow_usb or config.invalid_regexes_exist):
retu... | repos/system_upgrade/el8toel9/actors/multipathconfupdate/libraries/multipathconfupdate.py | from leapp.libraries.common import multipathutil
_regexes = ('vendor', 'product', 'revision', 'product_blacklist', 'devnode',
'wwid', 'property', 'protocol')
def _update_config(need_foreign, need_allow_usb, config):
if not (need_foreign or need_allow_usb or config.invalid_regexes_exist):
retu... | 0.206414 | 0.118717 |
from arrays import Array
import warnings
class Array2D(Array):
def __init__(self, r, c):
self.capacity = r
self.__arr = Array2D.__create_arr(r, c)
def __create_arr(r, c):
arr = []
for i in range(r):
arr.append(Array(c))
return arr
def __getitem__(self,... | influence/array/multiarray.py | from arrays import Array
import warnings
class Array2D(Array):
def __init__(self, r, c):
self.capacity = r
self.__arr = Array2D.__create_arr(r, c)
def __create_arr(r, c):
arr = []
for i in range(r):
arr.append(Array(c))
return arr
def __getitem__(self,... | 0.447943 | 0.190705 |
from .utils import serializable_dict
class Change(object):
def __init__(self, key, value, old_value=None, **kwargs):
self.key = key
self.value = value
self.old_value = old_value
self.metadata = kwargs or {}
def __repr__(self):
return serializable_dict(self.__dict__)
... | kronos/diff.py | from .utils import serializable_dict
class Change(object):
def __init__(self, key, value, old_value=None, **kwargs):
self.key = key
self.value = value
self.old_value = old_value
self.metadata = kwargs or {}
def __repr__(self):
return serializable_dict(self.__dict__)
... | 0.77552 | 0.169269 |
import ast
import astor
import sys
from x2paddle.project_convertor.pytorch.mapper import *
import copy
import os.path as osp
from .utils import get_dep_file_path
class DepInfo:
"""
依赖包信息。
PT_FROM代表pytorch from信息的字符串，例如：torch；
PD_FROM代表paddle from信息的字符串，例如：paddle；
PT_IMPORT代表pytorch import信息系的字符串，... | x2paddle/project_convertor/pytorch/ast_update.py |
import ast
import astor
import sys
from x2paddle.project_convertor.pytorch.mapper import *
import copy
import os.path as osp
from .utils import get_dep_file_path
class DepInfo:
"""
依赖包信息。
PT_FROM代表pytorch from信息的字符串，例如：torch；
PD_FROM代表paddle from信息的字符串，例如：paddle；
PT_IMPORT代表pytorch import信息系的字符串，... | 0.342242 | 0.204521 |
from unittest import TestCase
from nistbeacon.nistbeaconcrypto import NistBeaconCrypto
from unittest.mock import (
Mock,
patch,
)
class TestNistBeaconCrypto(TestCase):
@classmethod
def setUpClass(cls):
cls.verifier2013 = "_VERIFIER_20130905"
cls.verifier2013_timestamp = 1378395540
... | tests/unit/nistbeacon/test_nistbeaconcrypto.py | from unittest import TestCase
from nistbeacon.nistbeaconcrypto import NistBeaconCrypto
from unittest.mock import (
Mock,
patch,
)
class TestNistBeaconCrypto(TestCase):
@classmethod
def setUpClass(cls):
cls.verifier2013 = "_VERIFIER_20130905"
cls.verifier2013_timestamp = 1378395540
... | 0.820073 | 0.537041 |
r"""
================
Error Middleware
================
.. versionadded:: 0.2.0
Middleware to handle errors in aiohttp applications.
Usage
=====
.. code-block:: python
import re
from aiohttp import web
from aiohttp_middlewares import error_context, error_middleware
# Default error handler
asy... | aiohttp_middlewares/error.py | r"""
================
Error Middleware
================
.. versionadded:: 0.2.0
Middleware to handle errors in aiohttp applications.
Usage
=====
.. code-block:: python
import re
from aiohttp import web
from aiohttp_middlewares import error_context, error_middleware
# Default error handler
asy... | 0.871721 | 0.157947 |
from random import uniform, choice
from tqdm import tqdm
from functools import partial
from p_tqdm import p_map
from .backtest import backtest
from .utils.getters import get_strategy
from numpy import isnan, nan
import warnings
warnings.simplefilter(action='ignore', category=Warning)
def populate(size, config_range):... | yuzu/optimize.py | from random import uniform, choice
from tqdm import tqdm
from functools import partial
from p_tqdm import p_map
from .backtest import backtest
from .utils.getters import get_strategy
from numpy import isnan, nan
import warnings
warnings.simplefilter(action='ignore', category=Warning)
def populate(size, config_range):... | 0.371023 | 0.273356 |
import gym
import logging
from d4rl.pointmaze import waypoint_controller
from d4rl.pointmaze import maze_model
import numpy as np
import pickle
import gzip
import h5py
import argparse
# python scripts/generate_maze2d_datasets.py --env-name maze2d-open-v0 --fixed-target
# python scripts/generate_maze2d_datasets.py --en... | scripts/generate_maze2d_datasets.py | import gym
import logging
from d4rl.pointmaze import waypoint_controller
from d4rl.pointmaze import maze_model
import numpy as np
import pickle
import gzip
import h5py
import argparse
# python scripts/generate_maze2d_datasets.py --env-name maze2d-open-v0 --fixed-target
# python scripts/generate_maze2d_datasets.py --en... | 0.368292 | 0.243401 |
import pytest
from main import process_and_cleanup
# Testing the base parsing for if/else
def test_cleanup_graph_base_if():
graph = process_and_cleanup("TestFiles/pytest/if_normal_test_file.COB")
assert graph.get_size() == 3
# Testing simple branches for if/else
def test_cleanup_graph_base_if_left_branch():... | src/Test/test_cleanup_graph.py | import pytest
from main import process_and_cleanup
# Testing the base parsing for if/else
def test_cleanup_graph_base_if():
graph = process_and_cleanup("TestFiles/pytest/if_normal_test_file.COB")
assert graph.get_size() == 3
# Testing simple branches for if/else
def test_cleanup_graph_base_if_left_branch():... | 0.304145 | 0.592018 |
# # Explore highly co-expressed genes
# In the previous [notebook](2_explore_corr_of_genes.ipynb) we observed that using 39 samples with 201 PAO1-specific genes, that the correlation of accessory-accessory genes is higher compared to the correlation of core-core and core-accessory genes.
#
# Based on this finding, we... | archive/pilot_experiment/nbconverted/4_explore_coExpressed_genes.py |
# # Explore highly co-expressed genes
# In the previous [notebook](2_explore_corr_of_genes.ipynb) we observed that using 39 samples with 201 PAO1-specific genes, that the correlation of accessory-accessory genes is higher compared to the correlation of core-core and core-accessory genes.
#
# Based on this finding, we... | 0.79166 | 0.69246 |
import os
from os import listdir
from os.path import isfile, join
import numpy as np
import skimage
import skimage.io as io
from PIL import Image
import matplotlib.pyplot as plt
lfsize = [372, 540, 8, 8]
def normalize_lf(lf):
return 2.0*(lf-0.5)
def denormalize_lf(lf):
return lf/2.0+0.5
def read_eslf(filena... | lfutil.py | import os
from os import listdir
from os.path import isfile, join
import numpy as np
import skimage
import skimage.io as io
from PIL import Image
import matplotlib.pyplot as plt
lfsize = [372, 540, 8, 8]
def normalize_lf(lf):
return 2.0*(lf-0.5)
def denormalize_lf(lf):
return lf/2.0+0.5
def read_eslf(filena... | 0.197135 | 0.373219 |
import re
def le_assinatura():
'''
A função lê os valores dos traços linguísticos do modelo e devolve uma assinatura a ser comparada com os textos fornecidos.
Returns:
(list): Retorna uma lista com todos os dados digitados pelo usuário.
'''
print("Bem-vindo ao detector automático d... | Parte 1/Semana 9/CohPiah.py | import re
def le_assinatura():
'''
A função lê os valores dos traços linguísticos do modelo e devolve uma assinatura a ser comparada com os textos fornecidos.
Returns:
(list): Retorna uma lista com todos os dados digitados pelo usuário.
'''
print("Bem-vindo ao detector automático d... | 0.501953 | 0.505798 |
import os, glob, re
import argparse
import uuid
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.utils.data import DataLoader, Dataset
from torch.utils.data.dataloader import default_collate
from torchvision import transforms
import torchvision
import matplotli... | som-diffusion/finetune_ae.py | import os, glob, re
import argparse
import uuid
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.utils.data import DataLoader, Dataset
from torch.utils.data.dataloader import default_collate
from torchvision import transforms
import torchvision
import matplotli... | 0.855142 | 0.286104 |
import argparse
from glob import glob
from itertools import chain
import logging
import math
import os
import re
import sys
from time import sleep
from prettytable import PrettyTable
import pytz
import yaml
from investing import __version__
from investing import conf, InvestingLogging
from investing.data import Portfol... | launcher.py | import argparse
from glob import glob
from itertools import chain
import logging
import math
import os
import re
import sys
from time import sleep
from prettytable import PrettyTable
import pytz
import yaml
from investing import __version__
from investing import conf, InvestingLogging
from investing.data import Portfol... | 0.494385 | 0.180612 |
import asyncio
from datetime import datetime
import re
import sys
from io import StringIO
from aiogram import Bot, Dispatcher
from aiogram.dispatcher.filters import Filter
from aiogram.types import Message, InlineKeyboardButton, InlineKeyboardMarkup, CallbackQuery
from aiogram.utils.exceptions import MessageNotModifie... | cw3_kamikadze_bot.py | import asyncio
from datetime import datetime
import re
import sys
from io import StringIO
from aiogram import Bot, Dispatcher
from aiogram.dispatcher.filters import Filter
from aiogram.types import Message, InlineKeyboardButton, InlineKeyboardMarkup, CallbackQuery
from aiogram.utils.exceptions import MessageNotModifie... | 0.355439 | 0.117876 |
__version__ = '0.0.1'
# Helix ALM REST API: http://help.seapine.com/helixalm/rest-api/index.html
API_PATH = {
# Projects Requests for retrieving and switching projects.
'projects': '/projects',
# Security Requ... | helixalm/const.py | __version__ = '0.0.1'
# Helix ALM REST API: http://help.seapine.com/helixalm/rest-api/index.html
API_PATH = {
# Projects Requests for retrieving and switching projects.
'projects': '/projects',
# Security Requ... | 0.436382 | 0.068475 |
import substratools as tools
import os
import keras
from keras import backend as K
from keras.models import Sequential
from keras.layers import Dense, Dropout, Flatten
from keras.layers import Conv2D, MaxPooling2D
# input image dimensions
img_rows, img_cols = 28, 28
input_shape = (img_rows, img_cols, 1)
num_classes = ... | examples/mnist/assets/algo_cnn/algo.py | import substratools as tools
import os
import keras
from keras import backend as K
from keras.models import Sequential
from keras.layers import Dense, Dropout, Flatten
from keras.layers import Conv2D, MaxPooling2D
# input image dimensions
img_rows, img_cols = 28, 28
input_shape = (img_rows, img_cols, 1)
num_classes = ... | 0.837221 | 0.341761 |
import os
from collections import defaultdict
import threading
from tempfile import NamedTemporaryFile
try:
from urlparse import urlparse
except ImportError:
from urllib.parse import urlparse
try:
from functools import lru_cache # python 3
except ImportError:
from cachetools.func import lru_cache
impo... | gbdxtools/rda/fetch/conc/libcurl/select.py | import os
from collections import defaultdict
import threading
from tempfile import NamedTemporaryFile
try:
from urlparse import urlparse
except ImportError:
from urllib.parse import urlparse
try:
from functools import lru_cache # python 3
except ImportError:
from cachetools.func import lru_cache
impo... | 0.205894 | 0.095392 |
import pytest
from django.test import TestCase, override_settings
from .utils import MIDDLEWARES_FOR_TESTING
class TestResponseFunctionWithoutUser(TestCase):
def test_middleware_simple_get_request(self):
try:
self.client.get('/restframework/simple/')
except Exception as e:
... | tests/test_restframework_response.py | import pytest
from django.test import TestCase, override_settings
from .utils import MIDDLEWARES_FOR_TESTING
class TestResponseFunctionWithoutUser(TestCase):
def test_middleware_simple_get_request(self):
try:
self.client.get('/restframework/simple/')
except Exception as e:
... | 0.279828 | 0.197039 |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
from random import shuffle, randint
from six.moves import range
from itertools import product
from . import (
BaseMazeGame,
WithWaterAndBlocksMixin,
RewardOnE... | py/mazebase/games/goal_based_games.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
from random import shuffle, randint
from six.moves import range
from itertools import product
from . import (
BaseMazeGame,
WithWaterAndBlocksMixin,
RewardOnE... | 0.750004 | 0.238002 |
from pyox.oozie import Oozie
from pyox.client import ServiceError
import argparse
import sys
import os
import json
from datetime import datetime
def oozie_start_command(client,argv):
cmdparser = argparse.ArgumentParser(prog='pyox oozie start',description='start')
cmdparser.add_argument(
'-p','--property',
... | pyox/oozie_command.py | from pyox.oozie import Oozie
from pyox.client import ServiceError
import argparse
import sys
import os
import json
from datetime import datetime
def oozie_start_command(client,argv):
cmdparser = argparse.ArgumentParser(prog='pyox oozie start',description='start')
cmdparser.add_argument(
'-p','--property',
... | 0.176814 | 0.060418 |
from pathlib import Path
import json
import torch
from torch.utils.data import Dataset
from collections import defaultdict
from lib.image import imread, imread_to_gray
from torchvision import transforms
def transpose_dict(d):
dt = defaultdict(list)
for k, v in d.items():
dt[v].append(k)
return dt... | lib/datasets.py | from pathlib import Path
import json
import torch
from torch.utils.data import Dataset
from collections import defaultdict
from lib.image import imread, imread_to_gray
from torchvision import transforms
def transpose_dict(d):
dt = defaultdict(list)
for k, v in d.items():
dt[v].append(k)
return dt... | 0.77949 | 0.315921 |
from __future__ import annotations
import dataclasses
import os
import typing as t
from .io import (
read_text_file,
)
from .util import (
ANSIBLE_TEST_TARGET_ROOT,
)
from .util_common import (
ShellScriptTemplate,
set_shebang,
)
from .core_ci import (
SshKey,
)
@dataclasses.dataclass
class B... | venv/lib/python3.8/site-packages/ansible_test/_internal/bootstrap.py | from __future__ import annotations
import dataclasses
import os
import typing as t
from .io import (
read_text_file,
)
from .util import (
ANSIBLE_TEST_TARGET_ROOT,
)
from .util_common import (
ShellScriptTemplate,
set_shebang,
)
from .core_ci import (
SshKey,
)
@dataclasses.dataclass
class B... | 0.802207 | 0.09899 |
from typing import TypeVar, Generic, Callable, Optional, Tuple
import math
from algo1 import Array
from linkedlist import LinkedList
import linkedlist
K = TypeVar('K')
V = TypeVar('V')
W = TypeVar('W')
class Dic(Generic[K, V]):
""" The dictionary class """
def __init__(self,
_size : int,
... | libdic.py |
from typing import TypeVar, Generic, Callable, Optional, Tuple
import math
from algo1 import Array
from linkedlist import LinkedList
import linkedlist
K = TypeVar('K')
V = TypeVar('V')
W = TypeVar('W')
class Dic(Generic[K, V]):
""" The dictionary class """
def __init__(self,
_size : int,
... | 0.934223 | 0.416263 |
from cvxpy.atoms import (bmat, cumsum, diag, kron, conv,
abs, reshape, trace,
upper_tri, conj, imag, real,
norm1, norm_inf, Pnorm,
sigma_max, lambda_max, lambda_sum_largest,
log_det, QuadForm, Ma... | cvxpy/reductions/complex2real/atom_canonicalizers/__init__.py | from cvxpy.atoms import (bmat, cumsum, diag, kron, conv,
abs, reshape, trace,
upper_tri, conj, imag, real,
norm1, norm_inf, Pnorm,
sigma_max, lambda_max, lambda_sum_largest,
log_det, QuadForm, Ma... | 0.675551 | 0.403684 |
import decimal
import pickle
import tempfile
from heapq import heappop, heappush
import numpy as np
from gwas import Gwas
from pvalue_handler import PvalueHandler
from vcf import Vcf
def test_convert_pval_to_neg_log10():
p_value_handler = PvalueHandler()
assert p_value_handler.neg_log_of_decimal(decimal.Dec... | test/test_vcf.py | import decimal
import pickle
import tempfile
from heapq import heappop, heappush
import numpy as np
from gwas import Gwas
from pvalue_handler import PvalueHandler
from vcf import Vcf
def test_convert_pval_to_neg_log10():
p_value_handler = PvalueHandler()
assert p_value_handler.neg_log_of_decimal(decimal.Dec... | 0.558327 | 0.519399 |
import numpy as np
from ..core.utils import indices_len, fix_loc, filter_cols
from ..table.module import TableModule
from ..table.table import Table
import numexpr as ne
def make_local(df, px):
arr = df.to_array()
result = {}
class _Aux: pass
aux = _Aux()
for i, n in enumerate(df.columns):
... | progressivis/linalg/nexpr.py | import numpy as np
from ..core.utils import indices_len, fix_loc, filter_cols
from ..table.module import TableModule
from ..table.table import Table
import numexpr as ne
def make_local(df, px):
arr = df.to_array()
result = {}
class _Aux: pass
aux = _Aux()
for i, n in enumerate(df.columns):
... | 0.355216 | 0.257018 |
import argparse
from datetime import datetime
import numpy as np
import seaborn as sns
from matplotlib import pyplot as plt
from make_table import get_table
def get_schoopy_plot(table, error_bars=True):
fig, ax = plt.subplots(figsize=(20, 9))
models = set(table.model)
test_datas = set(table.test_data)
... | deepthinking/data_analysis/make_schoop.py | import argparse
from datetime import datetime
import numpy as np
import seaborn as sns
from matplotlib import pyplot as plt
from make_table import get_table
def get_schoopy_plot(table, error_bars=True):
fig, ax = plt.subplots(figsize=(20, 9))
models = set(table.model)
test_datas = set(table.test_data)
... | 0.493164 | 0.499878 |
import ctypes
from ctypes import wintypes
from . import com
from . import winapi
from .wintype import HRESULT, BSTR, CIMTYPE
_In_ = 1
_Out_ = 2
IWbemObjectSink_Indicate_Idx = 3
IWbemObjectSink_SetStatus_Idx = 4
class IWbemObjectSink(com.IUnknown):
def Indicate(self, object_count, obj_array):
protot... | cwmi/wmi.py |
import ctypes
from ctypes import wintypes
from . import com
from . import winapi
from .wintype import HRESULT, BSTR, CIMTYPE
_In_ = 1
_Out_ = 2
IWbemObjectSink_Indicate_Idx = 3
IWbemObjectSink_SetStatus_Idx = 4
class IWbemObjectSink(com.IUnknown):
def Indicate(self, object_count, obj_array):
protot... | 0.331552 | 0.100437 |
import numpy as np
import torch
from tqdm import tqdm
import os
from warnings import warn
from nsgt import NSGT_sliced, LogScale, LinScale, MelScale, OctScale, SndReader, BarkScale, VQLogScale
from nsgt_orig import NSGT_sliced as NSGT_sliced_old
import time
from argparse import ArgumentParser
parser = ArgumentParser(... | examples/benchmark.py | import numpy as np
import torch
from tqdm import tqdm
import os
from warnings import warn
from nsgt import NSGT_sliced, LogScale, LinScale, MelScale, OctScale, SndReader, BarkScale, VQLogScale
from nsgt_orig import NSGT_sliced as NSGT_sliced_old
import time
from argparse import ArgumentParser
parser = ArgumentParser(... | 0.466846 | 0.121869 |
from utils import update_model, save_simple_metrics_report, get_model_performance_test_set
from sklearn.model_selection import train_test_split, cross_validate, GridSearchCV
from sklearn.pipeline import Pipeline
from sklearn.impute import SimpleImputer
from sklearn.ensemble import GradientBoostingRegressor
import logg... | src/train.py | from utils import update_model, save_simple_metrics_report, get_model_performance_test_set
from sklearn.model_selection import train_test_split, cross_validate, GridSearchCV
from sklearn.pipeline import Pipeline
from sklearn.impute import SimpleImputer
from sklearn.ensemble import GradientBoostingRegressor
import logg... | 0.494873 | 0.336195 |
import pytest
import os
import numpy as np
from numpy.linalg import eigvalsh
from openfermion import QubitOperator, InteractionOperator, get_sparse_operator, get_ground_state
from zquantum.core.openfermion import save_qubit_operator_set, load_qubit_operator_set, save_interaction_operator, load_interaction_operator, l... | steps/operators_test.py | import pytest
import os
import numpy as np
from numpy.linalg import eigvalsh
from openfermion import QubitOperator, InteractionOperator, get_sparse_operator, get_ground_state
from zquantum.core.openfermion import save_qubit_operator_set, load_qubit_operator_set, save_interaction_operator, load_interaction_operator, l... | 0.259263 | 0.406214 |
import numpy as np
import scipy as sp
class Quad_Sampler(object):
"""
Class for drawing samples from an arbitrary one-dimensional probability distribution using numerical integration
and interpolation. In general this will be superior to more sophisticated sampling methods for 1D problems.
Assu... | mst_ida/analysis/samplers.py | import numpy as np
import scipy as sp
class Quad_Sampler(object):
"""
Class for drawing samples from an arbitrary one-dimensional probability distribution using numerical integration
and interpolation. In general this will be superior to more sophisticated sampling methods for 1D problems.
Assu... | 0.892457 | 0.697467 |
"""Export current configuration of an Anthos cluster."""
from __future__ import absolute_import
from __future__ import division
from __future__ import unicode_literals
from googlecloudsdk.calliope import base
from googlecloudsdk.command_lib.anthos import anthoscli_backend
from googlecloudsdk.command_lib.anthos import... | lib/surface/anthos/export.py | """Export current configuration of an Anthos cluster."""
from __future__ import absolute_import
from __future__ import division
from __future__ import unicode_literals
from googlecloudsdk.calliope import base
from googlecloudsdk.command_lib.anthos import anthoscli_backend
from googlecloudsdk.command_lib.anthos import... | 0.719679 | 0.167015 |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import tensorflow as tf
from parameters import param_keys
#ToDo : explore idea to give parameter as placeholder to varying size in
# validation. Think is not possible, because batch size is defined when val
#... | modules/iterators/train_iterator.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import tensorflow as tf
from parameters import param_keys
#ToDo : explore idea to give parameter as placeholder to varying size in
# validation. Think is not possible, because batch size is defined when val
#... | 0.786664 | 0.184694 |
import pytest
import numpy as np
import jax
import pyscf
from pyscfad import gto
from pyscfad.lib import numpy as jnp
TOL_VAL = 1e-12
TOL_NUC = 1e-10
TOL_CS = 1e-10
TOL_EXP = 1e-9
TOL_NUC2 = 5e-9
TEST_SET = ["int1e_ovlp", "int1e_kin", "int1e_nuc",
"int1e_rinv",]
TEST_SET_ECP = ["ECPscalar"]
TEST_SET_NUC =... | pyscfad/gto/test/test_int1e.py | import pytest
import numpy as np
import jax
import pyscf
from pyscfad import gto
from pyscfad.lib import numpy as jnp
TOL_VAL = 1e-12
TOL_NUC = 1e-10
TOL_CS = 1e-10
TOL_EXP = 1e-9
TOL_NUC2 = 5e-9
TEST_SET = ["int1e_ovlp", "int1e_kin", "int1e_nuc",
"int1e_rinv",]
TEST_SET_ECP = ["ECPscalar"]
TEST_SET_NUC =... | 0.28279 | 0.433142 |