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 |
|---|---|---|---|---|
def extractAllaboutmynothingsBlogspotCom(item):
'''
Parser for 'allaboutmynothings.blogspot.com'
'''
vol, chp, frag, postfix = extractVolChapterFragmentPostfix(item['title'])
if not (chp or vol) or "preview" in item['title'].lower():
return None
tagmap = [
('Yasashii Shinjitsu to Seiryaku Kekkon', 'Ya... | WebMirror/management/rss_parser_funcs/feed_parse_extractAllaboutmynothingsBlogspotCom.py | def extractAllaboutmynothingsBlogspotCom(item):
'''
Parser for 'allaboutmynothings.blogspot.com'
'''
vol, chp, frag, postfix = extractVolChapterFragmentPostfix(item['title'])
if not (chp or vol) or "preview" in item['title'].lower():
return None
tagmap = [
('Yasashii Shinjitsu to Seiryaku Kekkon', 'Ya... | 0.135118 | 0.13707 |
from numpy import *
from scipy.misc import imsave
def quartic_kernel(x):
if not (-1.0 < x < 1.0):
return 0.0
return 15.0 / 16.0 * (1 - x ** 2) ** 2
class Gradient:
def __init__(self):
self.colors = []
self.steps = []
def add_color(self, color, step):
self.colors.appe... | utils/gencolormaps.py |
from numpy import *
from scipy.misc import imsave
def quartic_kernel(x):
if not (-1.0 < x < 1.0):
return 0.0
return 15.0 / 16.0 * (1 - x ** 2) ** 2
class Gradient:
def __init__(self):
self.colors = []
self.steps = []
def add_color(self, color, step):
self.colors.appe... | 0.583678 | 0.417717 |
import os
import codecs
import operator
import json
import itertools
import numpy as np
def load_data(dataset='unknown',
location='./data/',
maxlen=None,
seed=1234,
limit_cls=1000):
""" Loads a dataset.
Expects dataset to exist in 'location' directory as ... | dataset.py | import os
import codecs
import operator
import json
import itertools
import numpy as np
def load_data(dataset='unknown',
location='./data/',
maxlen=None,
seed=1234,
limit_cls=1000):
""" Loads a dataset.
Expects dataset to exist in 'location' directory as ... | 0.609059 | 0.527073 |
import numpy as np
import math
import extendedMD.dtwdist as dtwdist
def prune_motifs_with_mdl(ts, motif_dic_list, r):
"""
This function returns the most relevant motifs from the original list of motif extracted from the emd algorithm,
based on the computed MDL cost and avoiding overlapping motifs
:pa... | extendedMD/pruning.py | import numpy as np
import math
import extendedMD.dtwdist as dtwdist
def prune_motifs_with_mdl(ts, motif_dic_list, r):
"""
This function returns the most relevant motifs from the original list of motif extracted from the emd algorithm,
based on the computed MDL cost and avoiding overlapping motifs
:pa... | 0.723212 | 0.736211 |
from django.shortcuts import render, redirect
from proofs.models import Proposition, Proof
from .forms import MajorSubmissionForm
from .typeChecker import *
from django.urls import reverse
def home(request):
concobj = []
conclusions = Proof.objects.all()
for obj in conclusions:
concobj.append(obj.conclusion)
re... | deductivereasoning/proofs/views.py | from django.shortcuts import render, redirect
from proofs.models import Proposition, Proof
from .forms import MajorSubmissionForm
from .typeChecker import *
from django.urls import reverse
def home(request):
concobj = []
conclusions = Proof.objects.all()
for obj in conclusions:
concobj.append(obj.conclusion)
re... | 0.373876 | 0.153803 |
import torch
import torch.nn as nn
import numpy as np
from utils import softminus
import math
import numbers
from torch.nn import functional as F
class SubNet(nn.ModuleList):
def __init__(self, list):
super(SubNet, self).__init__(list)
def forward(self, input):
output = input
for l in... | source/segment/nnmf.py | import torch
import torch.nn as nn
import numpy as np
from utils import softminus
import math
import numbers
from torch.nn import functional as F
class SubNet(nn.ModuleList):
def __init__(self, list):
super(SubNet, self).__init__(list)
def forward(self, input):
output = input
for l in... | 0.950365 | 0.578151 |
from thetae import Forecast
from thetae.util import localized_date_to_utc
from datetime import timedelta
import requests
import pandas as pd
default_model_name = 'Climacell'
def get_climacell_forecast(stid, lat, lon, api_key, forecast_date):
# Retrieve data
api_url = 'https://api.climacell.co/v3/weather/for... | thetae/data_parsers/climacell.py | from thetae import Forecast
from thetae.util import localized_date_to_utc
from datetime import timedelta
import requests
import pandas as pd
default_model_name = 'Climacell'
def get_climacell_forecast(stid, lat, lon, api_key, forecast_date):
# Retrieve data
api_url = 'https://api.climacell.co/v3/weather/for... | 0.651577 | 0.259521 |
import telethon
from telethon import TelegramClient
from telethon.tl.functions.channels import JoinChannelRequest
from redis import Redis
import random, json, pymysql
import asyncio
from my_db import DbHelper
#实例化一个redis
redis_obj = Redis(host='localhost',port=6379,password='<PASSWORD>',decode_responses=True,charset='U... | telegram_api/task/group/add_group.py | import telethon
from telethon import TelegramClient
from telethon.tl.functions.channels import JoinChannelRequest
from redis import Redis
import random, json, pymysql
import asyncio
from my_db import DbHelper
#实例化一个redis
redis_obj = Redis(host='localhost',port=6379,password='<PASSWORD>',decode_responses=True,charset='U... | 0.087847 | 0.096791 |
from docopt import docopt
import numpy as np
import os
import bob.io.image
import bob.io.base
import tensorflow as tf
import sys
from datetime import datetime
def _bytes_feature(value):
return tf.train.Feature(bytes_list=tf.train.BytesList(value=[value]))
def _int64_feature(value):
return tf.train.Feature(i... | cnn_training/vgg2_2_tfrecords.py | from docopt import docopt
import numpy as np
import os
import bob.io.image
import bob.io.base
import tensorflow as tf
import sys
from datetime import datetime
def _bytes_feature(value):
return tf.train.Feature(bytes_list=tf.train.BytesList(value=[value]))
def _int64_feature(value):
return tf.train.Feature(i... | 0.459076 | 0.243597 |
from __future__ import unicode_literals
from django.conf import settings
from django.utils.translation import ugettext_lazy as _
from django.core.urlresolvers import reverse_lazy
CONTACT_FORM_USE_CAPTCHA = getattr(settings, 'CONTACT_FORM_USE_CAPTCHA', False)
CONTACT_FORM_USE_SIGNALS = getattr(settings, 'CONTACT_FORM_U... | contact_form/conf/settings.py | from __future__ import unicode_literals
from django.conf import settings
from django.utils.translation import ugettext_lazy as _
from django.core.urlresolvers import reverse_lazy
CONTACT_FORM_USE_CAPTCHA = getattr(settings, 'CONTACT_FORM_USE_CAPTCHA', False)
CONTACT_FORM_USE_SIGNALS = getattr(settings, 'CONTACT_FORM_U... | 0.292899 | 0.064418 |
import re
import json
import bs4
from michiru import modules, personalities
## Module information.
__name__ = 'uribot.fourchan'
__author__ = 'Shiz'
__license__ = 'WTFPL'
__desc__ = 'Gives URL information for 4chan links.'
__deps__ = ['uribot']
URI_REGEXP = re.compile(r'^https?://boards\.4chan\.org/([a-z0-9]+)/thre... | michiru/modules/uribot/fourchan.py | import re
import json
import bs4
from michiru import modules, personalities
## Module information.
__name__ = 'uribot.fourchan'
__author__ = 'Shiz'
__license__ = 'WTFPL'
__desc__ = 'Gives URL information for 4chan links.'
__deps__ = ['uribot']
URI_REGEXP = re.compile(r'^https?://boards\.4chan\.org/([a-z0-9]+)/thre... | 0.288369 | 0.138637 |
from math import floor
from astropy.time import Time
from sqlalchemy import Column, String, Integer, BigInteger, Text
from . import MCDeclarativeBase
class SubsystemError(MCDeclarativeBase):
"""
Definition of subsystem_error table.
Attributes
----------
id : BigInteger Column
Autoincreme... | hera_mc/subsystem_error.py | from math import floor
from astropy.time import Time
from sqlalchemy import Column, String, Integer, BigInteger, Text
from . import MCDeclarativeBase
class SubsystemError(MCDeclarativeBase):
"""
Definition of subsystem_error table.
Attributes
----------
id : BigInteger Column
Autoincreme... | 0.890425 | 0.34054 |
import datetime
from PyQt5 import QtWidgets, QtCore, QtGui
from src.utils.log_system import LogSystem
from src.widgets.syntax_highlighter import SyntaxHighlighter
from src.hack_compiler import HackAssemblyCompiler, InvalidSyntaxException, InternalException
class ActionSy... | src/utils/action_system.py | import datetime
from PyQt5 import QtWidgets, QtCore, QtGui
from src.utils.log_system import LogSystem
from src.widgets.syntax_highlighter import SyntaxHighlighter
from src.hack_compiler import HackAssemblyCompiler, InvalidSyntaxException, InternalException
class ActionSy... | 0.280222 | 0.072571 |
import os, copy, logging
import torch
from torch import nn
from allennlp.modules.conditional_random_field import ConditionalRandomField
from util import func as H
from . import transformer as T
class EmbeddingClfHead(T.BaseClfHead):
def __init__(self, config, lm_model, lm_config, embed_type='w2v', w2v_path=No... | modules/embedding.py |
import os, copy, logging
import torch
from torch import nn
from allennlp.modules.conditional_random_field import ConditionalRandomField
from util import func as H
from . import transformer as T
class EmbeddingClfHead(T.BaseClfHead):
def __init__(self, config, lm_model, lm_config, embed_type='w2v', w2v_path=No... | 0.779406 | 0.209167 |
from multiprocessing import Event
import grpc
import pytest
from uuid import uuid4
from google.protobuf import json_format
from google.protobuf.empty_pb2 import Empty
from common.cryptographer import Cryptographer, hash_160
from teos.watcher import Watcher
from teos.responder import Responder
from teos.gatekeeper im... | test/teos/unit/test_internal_api.py | from multiprocessing import Event
import grpc
import pytest
from uuid import uuid4
from google.protobuf import json_format
from google.protobuf.empty_pb2 import Empty
from common.cryptographer import Cryptographer, hash_160
from teos.watcher import Watcher
from teos.responder import Responder
from teos.gatekeeper im... | 0.396419 | 0.11427 |
import math
import zipfile
import os
import xml.etree.ElementTree as ElementTree
import copy
import urllib.request
import shutil
import tempfile
from or_datasets import Bunch
from typing import List, Tuple, Optional
def fetch_vrp_rep(name: str, instance: str = None, return_raw=True) -> Bunch:
"""
Fetches data... | or_datasets/vrp_rep.py | import math
import zipfile
import os
import xml.etree.ElementTree as ElementTree
import copy
import urllib.request
import shutil
import tempfile
from or_datasets import Bunch
from typing import List, Tuple, Optional
def fetch_vrp_rep(name: str, instance: str = None, return_raw=True) -> Bunch:
"""
Fetches data... | 0.648689 | 0.69022 |
import datetime, threading, time
from abc import abstractmethod
from typing import Mapping
from sqlalchemy import MetaData, Table, Column, Integer, String, ForeignKey
from sqlalchemy.orm import mapper, relationship, reconstructor
from cassiopeia.dto.common import DtoObject
metadata = MetaData()
class SQLBaseObject(... | cassiopeia-sqlstore/cassiopeia_sqlstore/common.py | import datetime, threading, time
from abc import abstractmethod
from typing import Mapping
from sqlalchemy import MetaData, Table, Column, Integer, String, ForeignKey
from sqlalchemy.orm import mapper, relationship, reconstructor
from cassiopeia.dto.common import DtoObject
metadata = MetaData()
class SQLBaseObject(... | 0.751739 | 0.224608 |
import logging
import os
import subprocess
from pip.basecommand import Command
from pip.commands.show import search_packages_info
from pip.status_codes import SUCCESS, ERROR
from pip._vendor import pkg_resources
import sys
class ViewCommand(Command):
"""
Views the package source directory with the editor de... | pipview/view.py | import logging
import os
import subprocess
from pip.basecommand import Command
from pip.commands.show import search_packages_info
from pip.status_codes import SUCCESS, ERROR
from pip._vendor import pkg_resources
import sys
class ViewCommand(Command):
"""
Views the package source directory with the editor de... | 0.234933 | 0.067087 |
import torch
from kaolin.metrics import tetmesh
class TestTetMeshMetrics:
def test_tetrahedron_volume(self):
tetrahedrons = torch.tensor([[[[0.5000, 0.5000, 0.4500],
[0.4500, 0.5000, 0.5000],
[0.4750, 0.4500, 0.4500],
... | tests/python/kaolin/metrics/test_tetmesh.py |
import torch
from kaolin.metrics import tetmesh
class TestTetMeshMetrics:
def test_tetrahedron_volume(self):
tetrahedrons = torch.tensor([[[[0.5000, 0.5000, 0.4500],
[0.4500, 0.5000, 0.5000],
[0.4750, 0.4500, 0.4500],
... | 0.652906 | 0.680877 |
import os
import requests
from django import forms
from utilities.exceptions import CloudBoltException
from resourcehandlers.forms import (
BaseResourceHandlerCredentialsForm, BaseResourceHandlerSettingsForm,
)
from .models import RhevResourceHandler
from infrastructure.models import Environment
from ovirtsdk4 i... | forms.py | import os
import requests
from django import forms
from utilities.exceptions import CloudBoltException
from resourcehandlers.forms import (
BaseResourceHandlerCredentialsForm, BaseResourceHandlerSettingsForm,
)
from .models import RhevResourceHandler
from infrastructure.models import Environment
from ovirtsdk4 i... | 0.560493 | 0.043937 |
__all__ = ['DirectScrolledWindowFrame']
from panda3d.core import *
from direct.gui import DirectGuiGlobals as DGG
from direct.gui.DirectFrame import DirectFrame
from direct.gui.DirectButton import DirectButton
from direct.gui.DirectScrolledFrame import DirectScrolledFrame
class DirectScrolledWindowFrame(DirectScrolle... | DirectGuiExtension/DirectScrolledWindowFrame.py | __all__ = ['DirectScrolledWindowFrame']
from panda3d.core import *
from direct.gui import DirectGuiGlobals as DGG
from direct.gui.DirectFrame import DirectFrame
from direct.gui.DirectButton import DirectButton
from direct.gui.DirectScrolledFrame import DirectScrolledFrame
class DirectScrolledWindowFrame(DirectScrolle... | 0.565299 | 0.296158 |
from flexbe_core import Behavior, Autonomy, OperatableStateMachine, ConcurrencyContainer, PriorityContainer, Logger
from sara_flexbe_states.SetKey import SetKey
from flexbe_states.log_key_state import LogKeyState
from sara_flexbe_states.sara_set_head_angle import SaraSetHeadAngle
from sara_flexbe_states.list_entities_... | sara_flexbe_behaviors/src/sara_flexbe_behaviors/action_count_sm.py |
from flexbe_core import Behavior, Autonomy, OperatableStateMachine, ConcurrencyContainer, PriorityContainer, Logger
from sara_flexbe_states.SetKey import SetKey
from flexbe_states.log_key_state import LogKeyState
from sara_flexbe_states.sara_set_head_angle import SaraSetHeadAngle
from sara_flexbe_states.list_entities_... | 0.311532 | 0.241808 |
STATS = [
{
"num_node_expansions": 0,
"search_time": 0.0127327,
"total_time": 0.0637178,
"plan_length": 64,
"plan_cost": 64,
"objects_used": 264,
"objects_total": 374,
"neural_net_time": 0.09185624122619629,
"num_replanning_steps": 14,
... | scenegraph/exp-official/taskographyv4tiny5_hierarchical/hierarchical_test_stats.py | STATS = [
{
"num_node_expansions": 0,
"search_time": 0.0127327,
"total_time": 0.0637178,
"plan_length": 64,
"plan_cost": 64,
"objects_used": 264,
"objects_total": 374,
"neural_net_time": 0.09185624122619629,
"num_replanning_steps": 14,
... | 0.276886 | 0.516535 |
import os
import numpy as np
import pandas as pd
from keras.optimizers import Adam
class WordEmbedder:
"""
WordEmbedder is a helper class for every embedding algorithms. It
does extract all possible words, adjacency matrix, corpus from
the given sequences. It is parent class of SkipGram, F... | seqlearner/WordEmbedder.py | import os
import numpy as np
import pandas as pd
from keras.optimizers import Adam
class WordEmbedder:
"""
WordEmbedder is a helper class for every embedding algorithms. It
does extract all possible words, adjacency matrix, corpus from
the given sequences. It is parent class of SkipGram, F... | 0.769167 | 0.501343 |
import time
import numpy as np
from tensorflow.keras import Input, layers
from tensorflow.keras.callbacks import TensorBoard
from tensorflow.keras.models import Sequential
from tensorflow.keras.optimizers import Adam
from tensorflow.keras.regularizers import l2
from tensorflow.keras.utils import plot_model
from imple... | stft-cnn-fault-diagnosis/without_stft.py | import time
import numpy as np
from tensorflow.keras import Input, layers
from tensorflow.keras.callbacks import TensorBoard
from tensorflow.keras.models import Sequential
from tensorflow.keras.optimizers import Adam
from tensorflow.keras.regularizers import l2
from tensorflow.keras.utils import plot_model
from imple... | 0.648244 | 0.342049 |
import math
from jsonargparse import ArgumentParser, ActionParser
import torch
from .attack_factory import AttackFactory as AF
class RandomAttackFactory(object):
def __init__(
self,
attack_types,
min_eps=1e-5,
max_eps=0.1,
min_snr=30,
max_snr=60,
min_alpha=... | hyperion/torch/adv_attacks/random_attack_factory.py | import math
from jsonargparse import ArgumentParser, ActionParser
import torch
from .attack_factory import AttackFactory as AF
class RandomAttackFactory(object):
def __init__(
self,
attack_types,
min_eps=1e-5,
max_eps=0.1,
min_snr=30,
max_snr=60,
min_alpha=... | 0.7797 | 0.133839 |
from I3Tray import *
from icecube import icetray, dataclasses, dataio, simclasses
from os.path import expandvars
import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt
import pylab
from optparse import OptionParser
parser = OptionParser()
parser.add_option("-i","--infile", dest="INFILE", ... | sim-services/resources/gcd_validation/details/validate_stress_test_samples.py |
from I3Tray import *
from icecube import icetray, dataclasses, dataio, simclasses
from os.path import expandvars
import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt
import pylab
from optparse import OptionParser
parser = OptionParser()
parser.add_option("-i","--infile", dest="INFILE", ... | 0.281504 | 0.120957 |
import dash
import dash_core_components as dcc
import dash_html_components as html
from matplotlib import pyplot as plt
import pandas as pd
import numpy as np
import plotly.graph_objs as go
from sklearn.neighbors import KNeighborsClassifier
from sklearn.preprocessing import StandardScaler
from sklearn.model_selection i... | heroku/app.py | import dash
import dash_core_components as dcc
import dash_html_components as html
from matplotlib import pyplot as plt
import pandas as pd
import numpy as np
import plotly.graph_objs as go
from sklearn.neighbors import KNeighborsClassifier
from sklearn.preprocessing import StandardScaler
from sklearn.model_selection i... | 0.406862 | 0.266174 |
import sys
import array
import struct
from . import errors
from . import wire_format
class OutputStream(object):
"""Contains all logic for writing bits, and ToString() to get the result."""
def __init__(self):
self._buffer = array.array('B')
if sys.version_info < (3, 3):
def append_raw_... | odps/tunnel/pb/output_stream.py | import sys
import array
import struct
from . import errors
from . import wire_format
class OutputStream(object):
"""Contains all logic for writing bits, and ToString() to get the result."""
def __init__(self):
self._buffer = array.array('B')
if sys.version_info < (3, 3):
def append_raw_... | 0.486575 | 0.277228 |
import datetime
import testtools
from mock import patch
import oslo_messaging as messaging
from oslo_config import cfg
from oslo_log import log as logging
from designate import exceptions
from designate.central import service as central_service
from designate.tests.test_api.test_v1 import ApiV1Test
LOG = logging.ge... | designate/tests/test_api/test_v1/test_domains.py | import datetime
import testtools
from mock import patch
import oslo_messaging as messaging
from oslo_config import cfg
from oslo_log import log as logging
from designate import exceptions
from designate.central import service as central_service
from designate.tests.test_api.test_v1 import ApiV1Test
LOG = logging.ge... | 0.496094 | 0.42937 |
import pytest
from crummycm.validation.validation import validate
from example_templates.component.config_dict.a import (
cd_outer,
no_cd_single,
no_cd_single_nested,
)
ex_config = {
"cd_outer": (
(
{
"my_mixed": {
"kd_num": 0,
... | tests/unit/validate/test_dict_cd.py | import pytest
from crummycm.validation.validation import validate
from example_templates.component.config_dict.a import (
cd_outer,
no_cd_single,
no_cd_single_nested,
)
ex_config = {
"cd_outer": (
(
{
"my_mixed": {
"kd_num": 0,
... | 0.541894 | 0.413359 |
from pathlib import Path
from statistics import median
from typing import Optional
POINTS = {")": 3, "]": 57, "}": 1197, ">": 25137}
AUTOCOMPLETE_POINTS = {")": 1, "]": 2, "}": 3, ">": 4}
def read_syntax_file(path: Path) -> list[str]:
with open(path, "r") as file:
return file.read().split("\n")
def ch... | advent/day_10.py | from pathlib import Path
from statistics import median
from typing import Optional
POINTS = {")": 3, "]": 57, "}": 1197, ">": 25137}
AUTOCOMPLETE_POINTS = {")": 1, "]": 2, "}": 3, ">": 4}
def read_syntax_file(path: Path) -> list[str]:
with open(path, "r") as file:
return file.read().split("\n")
def ch... | 0.763484 | 0.374991 |
from .GoogleTokenSpan import GoogleTokenSpan
from .GoogleSentiment import GoogleSentiment
class GoogleMention(GoogleTokenSpan):
def __init__(self, dictionary, document, entity):
text = dictionary.pop('text')
content = text.pop('content')
begin = text.pop('begin_offset')
end = begin + len(content)
super()._... | linguistics/google/GoogleEntity.py | from .GoogleTokenSpan import GoogleTokenSpan
from .GoogleSentiment import GoogleSentiment
class GoogleMention(GoogleTokenSpan):
def __init__(self, dictionary, document, entity):
text = dictionary.pop('text')
content = text.pop('content')
begin = text.pop('begin_offset')
end = begin + len(content)
super()._... | 0.767777 | 0.205954 |
from unittest import TestCase, mock
import unittest
from buf import libraries
import os
import sys
import tempfile
class TestMakeDir(TestCase):
"""Tests buf.libraries.make_library."""
def test_already_exists(self):
"""Tests that the function raises an error if the directory it is trying to create alre... | tests/test_libraries.py | from unittest import TestCase, mock
import unittest
from buf import libraries
import os
import sys
import tempfile
class TestMakeDir(TestCase):
"""Tests buf.libraries.make_library."""
def test_already_exists(self):
"""Tests that the function raises an error if the directory it is trying to create alre... | 0.563858 | 0.503662 |
import fnmatch
import re
import collections
from zlib import adler32
from typing import ByteString, Iterable, Callable, Union
from .. import arg, Unit
from ...lib.tools import isbuffer
def pathspec(expression):
"""
Normalizes a path which is separated by backward or forward slashes to be
s... | refinery/units/formats/__init__.py | import fnmatch
import re
import collections
from zlib import adler32
from typing import ByteString, Iterable, Callable, Union
from .. import arg, Unit
from ...lib.tools import isbuffer
def pathspec(expression):
"""
Normalizes a path which is separated by backward or forward slashes to be
s... | 0.759091 | 0.099645 |
from os import environ
from pathlib import Path
import envdir
import sentry_sdk
from configurations import Configuration
from sentry_sdk.integrations.django import DjangoIntegration
# Common settings
BASE_DIR = Path(__file__).absolute().parent.parent
PROJECT_NAME = "{{cookiecutter.project_name}}"
CONFIGURATION = env... | {{cookiecutter.project_name}}/{{cookiecutter.project_name}}/settings.py | from os import environ
from pathlib import Path
import envdir
import sentry_sdk
from configurations import Configuration
from sentry_sdk.integrations.django import DjangoIntegration
# Common settings
BASE_DIR = Path(__file__).absolute().parent.parent
PROJECT_NAME = "{{cookiecutter.project_name}}"
CONFIGURATION = env... | 0.63307 | 0.133528 |
import pandas as pd
import requests
from bs4 import BeautifulSoup
from tqdm import tqdm
import argparse
import sys
#TESTING URLS
# "https://www.imdb.com/title/tt5753856" DARK
# "https://www.imdb.com/title/tt0098904" SEINFLED
# "https://www.imdb.com/title/tt0306414" THEWIRE
# "https://www.imdb.com/title/tt0096697" Simp... | IMDB Data Scraper/scrape.py | import pandas as pd
import requests
from bs4 import BeautifulSoup
from tqdm import tqdm
import argparse
import sys
#TESTING URLS
# "https://www.imdb.com/title/tt5753856" DARK
# "https://www.imdb.com/title/tt0098904" SEINFLED
# "https://www.imdb.com/title/tt0306414" THEWIRE
# "https://www.imdb.com/title/tt0096697" Simp... | 0.174692 | 0.162148 |
from antlr4 import *
# This class defines a complete listener for a parse tree produced by QrogueDungeonParser.
class QrogueDungeonListener(ParseTreeListener):
# Enter a parse tree produced by QrogueDungeonParser#start.
def enterStart(self, ctx):
pass
# Exit a parse tree produced by QrogueDungeon... | qrogue/game/world/dungeon_generator/dungeon_parser/QrogueDungeonListener.py | from antlr4 import *
# This class defines a complete listener for a parse tree produced by QrogueDungeonParser.
class QrogueDungeonListener(ParseTreeListener):
# Enter a parse tree produced by QrogueDungeonParser#start.
def enterStart(self, ctx):
pass
# Exit a parse tree produced by QrogueDungeon... | 0.307462 | 0.14978 |
import torch
def l2norm(tensor, dim, keepdim):
"""
Computes the l2-norm of elements in input tensor.
:param tensor: PyTorch tensor.
:type tensor: `torch.nn.Module`
:param dim: Reduction dimension.
:type dim: `int`
:param keepdim: Whether the output has `dim` retained.
:type keepdim: `... | condensa/functional.py |
import torch
def l2norm(tensor, dim, keepdim):
"""
Computes the l2-norm of elements in input tensor.
:param tensor: PyTorch tensor.
:type tensor: `torch.nn.Module`
:param dim: Reduction dimension.
:type dim: `int`
:param keepdim: Whether the output has `dim` retained.
:type keepdim: `... | 0.968329 | 0.878366 |
import sqlite3
import argparse
import datetime
import chtc_usage_tools as cut
import matplotlib.pyplot as plt
import matplotlib.dates as mpld
import matplotlib as mpl
from numpy import array
mpl.rcParams['axes.color_cycle'] = ['r', 'k', 'c']
parser = argparse.ArgumentParser(description='A tool to extract usage data'... | extractUsage.py |
import sqlite3
import argparse
import datetime
import chtc_usage_tools as cut
import matplotlib.pyplot as plt
import matplotlib.dates as mpld
import matplotlib as mpl
from numpy import array
mpl.rcParams['axes.color_cycle'] = ['r', 'k', 'c']
parser = argparse.ArgumentParser(description='A tool to extract usage data'... | 0.281307 | 0.249304 |
import uuid
import pygame
from dataclasses import dataclass
from ..style import Color
from ..structures import Vec2
from . import physics
Model = physics.Model
vec2 = physics.vec2
@dataclass
class Component:
entity_id = None
def update(self, delta) -> None: pass
@property
def class_name(self):... | gg/ecs/components.py | import uuid
import pygame
from dataclasses import dataclass
from ..style import Color
from ..structures import Vec2
from . import physics
Model = physics.Model
vec2 = physics.vec2
@dataclass
class Component:
entity_id = None
def update(self, delta) -> None: pass
@property
def class_name(self):... | 0.892773 | 0.402627 |
import matplotlib.pyplot as plt
import cv2
import numpy as np
import pandas as pd
from tensorflow.keras.models import Model, Sequential
from tensorflow.keras.layers import Conv2D, Conv2DTranspose, Reshape,LeakyReLU, Dropout
import tensorflow as tf
from tensorflow.keras.layers import AveragePooling2D,UpSampling2... | colorize_train.py | import matplotlib.pyplot as plt
import cv2
import numpy as np
import pandas as pd
from tensorflow.keras.models import Model, Sequential
from tensorflow.keras.layers import Conv2D, Conv2DTranspose, Reshape,LeakyReLU, Dropout
import tensorflow as tf
from tensorflow.keras.layers import AveragePooling2D,UpSampling2... | 0.664867 | 0.400632 |
from flask import abort, escape, Flask, render_template, request, session
from functools import wraps
import json
import sys
import uuid
app = Flask(__name__, static_folder="static")
# Decorators
def requires_admin(f):
@wraps(f)
def decorated_function(*args, **kwargs):
if "team_id" not in session or... | app.py | from flask import abort, escape, Flask, render_template, request, session
from functools import wraps
import json
import sys
import uuid
app = Flask(__name__, static_folder="static")
# Decorators
def requires_admin(f):
@wraps(f)
def decorated_function(*args, **kwargs):
if "team_id" not in session or... | 0.340485 | 0.119691 |
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='Customer',
fields=[
('customer_id', models.AutoField(prima... | APMS/apps/orders/migrations/0001_initial.py |
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='Customer',
fields=[
('customer_id', models.AutoField(prima... | 0.5564 | 0.205157 |
# standards
import re
# canif
from .parser import ParserError
RE_SKIPPED = re.compile(r'(?:\s+|//.*)+')
RE_END = re.compile(r'$')
class Lexer:
"""
Splits the input text into tokens, i.e. the smallest, indivisible strings in the text.
Instances of this class keep track of where they are in the text, a... | canif/lexer.py |
# standards
import re
# canif
from .parser import ParserError
RE_SKIPPED = re.compile(r'(?:\s+|//.*)+')
RE_END = re.compile(r'$')
class Lexer:
"""
Splits the input text into tokens, i.e. the smallest, indivisible strings in the text.
Instances of this class keep track of where they are in the text, a... | 0.683947 | 0.531574 |
import warnings
import numpy as np
import pandas as pd
import pytest
from sklearn.metrics import auc, confusion_matrix, matthews_corrcoef, roc_curve
from sklearn.preprocessing import binarize
from src.models.metrics_utils import (confusion_matrix_to_dataframe,
mcc_auc_score, mcc_... | tests/src/models/test_metrics_utils.py | import warnings
import numpy as np
import pandas as pd
import pytest
from sklearn.metrics import auc, confusion_matrix, matthews_corrcoef, roc_curve
from sklearn.preprocessing import binarize
from src.models.metrics_utils import (confusion_matrix_to_dataframe,
mcc_auc_score, mcc_... | 0.852537 | 0.616618 |
from genshibasic.genshi import Genshi
from genshibasic.lexer import Lexer
import unittest
class LexerTestSuite(unittest.TestCase):
def test_hello(self):
tokens = self.__lex('hello')
self.assertEqual(len(tokens), 1)
self.assertEqual(tokens[0].pos, (1, 5))
self.assertEqual(tokens[0]... | test/test_lexer.py | from genshibasic.genshi import Genshi
from genshibasic.lexer import Lexer
import unittest
class LexerTestSuite(unittest.TestCase):
def test_hello(self):
tokens = self.__lex('hello')
self.assertEqual(len(tokens), 1)
self.assertEqual(tokens[0].pos, (1, 5))
self.assertEqual(tokens[0]... | 0.555918 | 0.547646 |
from BaseHTTPServer import HTTPServer, BaseHTTPRequestHandler
from argparse import ArgumentParser
import threading
import json
import logging as log
import commands
class ERROR_CODE:
PARSE_ERROR = -32700 # Invalid JSON was received by the server.
INVALID_REQ = -32600 # The JSON sent is not a ... | sdntestbed_source/sdntestbed/python/novaconsole-master/rpcserver.py | from BaseHTTPServer import HTTPServer, BaseHTTPRequestHandler
from argparse import ArgumentParser
import threading
import json
import logging as log
import commands
class ERROR_CODE:
PARSE_ERROR = -32700 # Invalid JSON was received by the server.
INVALID_REQ = -32600 # The JSON sent is not a ... | 0.605799 | 0.072276 |
import urllib2
import time
import random
from datetime import timedelta
from bs4 import BeautifulSoup
from google.appengine.api import urlfetch
from models.models import Match, Map, Server
def scrape_matches(pages=2):
""" gets match statistics from oc.tc/matches pages
last_page - the highest match ... | src/controllers/scraper.py | import urllib2
import time
import random
from datetime import timedelta
from bs4 import BeautifulSoup
from google.appengine.api import urlfetch
from models.models import Match, Map, Server
def scrape_matches(pages=2):
""" gets match statistics from oc.tc/matches pages
last_page - the highest match ... | 0.197677 | 0.162579 |
import sys
import aws_lambda_wsgi
import dash_bootstrap_components as dbc
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output
sys.path.append('.')
from pangea import about, sampling_numbers, sampling_period # noqa: E402
from app import app # noqa: E402
... | index.py | import sys
import aws_lambda_wsgi
import dash_bootstrap_components as dbc
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output
sys.path.append('.')
from pangea import about, sampling_numbers, sampling_period # noqa: E402
from app import app # noqa: E402
... | 0.381104 | 0.214609 |
from __future__ import (absolute_import, division, print_function)
__metaclass__ = type
import os
import json
import pytest
import sys
if sys.version_info < (2, 7):
pytestmark = pytest.mark.skip("F5 Ansible modules require Python >= 2.7")
from ansible.module_utils.basic import AnsibleModule
from ansible_collec... | venv/lib/python3.6/site-packages/ansible_collections/f5networks/f5_modules/tests/unit/modules/network/f5/test_bigip_ucs.py |
from __future__ import (absolute_import, division, print_function)
__metaclass__ = type
import os
import json
import pytest
import sys
if sys.version_info < (2, 7):
pytestmark = pytest.mark.skip("F5 Ansible modules require Python >= 2.7")
from ansible.module_utils.basic import AnsibleModule
from ansible_collec... | 0.426919 | 0.279165 |
from enum import Enum
ROWS = 6
COLS = 7
class Color(Enum):
RED = 1
BLACK = 2
class Board:
def __init__(self):
self.grid = list()
for _ in range(COLS):
col = list()
for _ in range(ROWS):
col.append(None)
self.grid.append(col)
se... | solutions/problem_219.py | from enum import Enum
ROWS = 6
COLS = 7
class Color(Enum):
RED = 1
BLACK = 2
class Board:
def __init__(self):
self.grid = list()
for _ in range(COLS):
col = list()
for _ in range(ROWS):
col.append(None)
self.grid.append(col)
se... | 0.568176 | 0.235394 |
from docopt import docopt
import os
import yaml
import json
def main(args):
output_filename = args['--output']
input_path = args['--input']
input_paths = []
templates = []
templates_target_path = args['--target-templates-path']
templates = []
for root, directories, files in os.walk(input... | scripts/gen_data_templates.py | from docopt import docopt
import os
import yaml
import json
def main(args):
output_filename = args['--output']
input_path = args['--input']
input_paths = []
templates = []
templates_target_path = args['--target-templates-path']
templates = []
for root, directories, files in os.walk(input... | 0.189071 | 0.078148 |
from lewis.adapters.stream import StreamInterface
from lewis.core.logging import has_log
from lewis.utils.command_builder import CmdBuilder
from lewis.utils.replies import conditional_reply
from .dfkps_base import CommonStreamInterface
import logging
__all__ = ["Danfysik9X00StreamInterface"]
@has_log
class Danfysi... | lewis_emulators/danfysik/interfaces/dfkps_9X00.py | from lewis.adapters.stream import StreamInterface
from lewis.core.logging import has_log
from lewis.utils.command_builder import CmdBuilder
from lewis.utils.replies import conditional_reply
from .dfkps_base import CommonStreamInterface
import logging
__all__ = ["Danfysik9X00StreamInterface"]
@has_log
class Danfysi... | 0.685002 | 0.144511 |
from ..translate import (
win_agg, win_over, win_cumul, sql_scalar, sql_agg,
RankOver,
wrap_annotate, annotate,
extend_base,
SqlTranslator,
)
from .base import (
SqlColumn, SqlColumnAgg,
base_scalar, base_win, base_agg
)
import sqlalchemy.sql.sql... | siuba/sql/dialects/postgresql.py | from ..translate import (
win_agg, win_over, win_cumul, sql_scalar, sql_agg,
RankOver,
wrap_annotate, annotate,
extend_base,
SqlTranslator,
)
from .base import (
SqlColumn, SqlColumnAgg,
base_scalar, base_win, base_agg
)
import sqlalchemy.sql.sql... | 0.279238 | 0.202187 |
import asyncio
from typing import Optional
from main import os
from aiogram.types import InlineKeyboardMarkup, InlineKeyboardButton
from aiogram.utils import exceptions, executor
from models import User
import database
from loguru import logger as log
from celery import Celery
celery_app = Celery('tasks', broker=os.... | tasks.py | import asyncio
from typing import Optional
from main import os
from aiogram.types import InlineKeyboardMarkup, InlineKeyboardButton
from aiogram.utils import exceptions, executor
from models import User
import database
from loguru import logger as log
from celery import Celery
celery_app = Celery('tasks', broker=os.... | 0.668015 | 0.112065 |
import copy
import collections
from werkzeug.exceptions import Forbidden
from sqlalchemy import and_
from ggrc import db
from ggrc import models
from ggrc.utils import benchmark
from ggrc.rbac import permissions
from ggrc.query.default_handler import DefaultHandler
def _set_data(object_query, data):
"""Helper fun... | src/ggrc/query/assessment_related_objects.py | import copy
import collections
from werkzeug.exceptions import Forbidden
from sqlalchemy import and_
from ggrc import db
from ggrc import models
from ggrc.utils import benchmark
from ggrc.rbac import permissions
from ggrc.query.default_handler import DefaultHandler
def _set_data(object_query, data):
"""Helper fun... | 0.621656 | 0.335623 |
import networkx as nx
import matplotlib.pyplot as plt
from autoparse.automaton import preprocess, Automaton
class Transition:
def __init__(
self,
word: str,
state_in,
state_out,
transition_ids=[],
weight: int = 1,
variables={},
):
self.word = wo... | autoparse/automaton_fitter.py | import networkx as nx
import matplotlib.pyplot as plt
from autoparse.automaton import preprocess, Automaton
class Transition:
def __init__(
self,
word: str,
state_in,
state_out,
transition_ids=[],
weight: int = 1,
variables={},
):
self.word = wo... | 0.792223 | 0.303719 |
import os
import PIL.Image
import numpy as np
import tensorflow as tf
import tensorflow_hub as hub
from keras.applications import resnet50
from keras.applications.resnet50 import ResNet50
from keras.backend import set_session
from scipy.stats import truncnorm
# Initialize the module
module_path = 'https://tfhub.dev/d... | utilities/gan-inversion/01_model_prep.py | import os
import PIL.Image
import numpy as np
import tensorflow as tf
import tensorflow_hub as hub
from keras.applications import resnet50
from keras.applications.resnet50 import ResNet50
from keras.backend import set_session
from scipy.stats import truncnorm
# Initialize the module
module_path = 'https://tfhub.dev/d... | 0.758958 | 0.322286 |
from lib import script
import random
rand = random.randint
def warp_uptown_east(pc):
result = script.select(pc, ("enter", "north", "south", "west", "cancel"), "warp")
if result == 1:
script.warp(pc, 10023000, rand(217, 218), rand(126, 129)) #アップタウン
elif result == 2:
script.warp(pc, 10023400, rand(126, 129), ran... | script/site_packages/warp_event.py | from lib import script
import random
rand = random.randint
def warp_uptown_east(pc):
result = script.select(pc, ("enter", "north", "south", "west", "cancel"), "warp")
if result == 1:
script.warp(pc, 10023000, rand(217, 218), rand(126, 129)) #アップタウン
elif result == 2:
script.warp(pc, 10023400, rand(126, 129), ran... | 0.157785 | 0.250913 |
from asyncio import DatagramTransport
import json, yaml
from paramiko import SSHException
import requests
from server.utils.response_util import RET
from flask import jsonify, current_app, g
from typing import List
from flask import current_app, jsonify
from sqlalchemy.exc import IntegrityError, SQLAlchemyError
from ... | radiaTest-server/server/utils/permission_utils.py | from asyncio import DatagramTransport
import json, yaml
from paramiko import SSHException
import requests
from server.utils.response_util import RET
from flask import jsonify, current_app, g
from typing import List
from flask import current_app, jsonify
from sqlalchemy.exc import IntegrityError, SQLAlchemyError
from ... | 0.424531 | 0.098947 |
# Golden Search, mimics the secant method, but for finding the Global Max and min (optimization of a function)
# Strategy in selecting the bounds of the interval:
# l0 = distance between estimate,
# l0 = l1+l2 ; l1/l0 = l2/l1
# R = (l2/l1)**-1 (reciprocal)
# From substitution : 1 +R = 1/R -> R**2 +... | GoldSearch.py | # Golden Search, mimics the secant method, but for finding the Global Max and min (optimization of a function)
# Strategy in selecting the bounds of the interval:
# l0 = distance between estimate,
# l0 = l1+l2 ; l1/l0 = l2/l1
# R = (l2/l1)**-1 (reciprocal)
# From substitution : 1 +R = 1/R -> R**2 +... | 0.384912 | 0.644505 |
import scrapy
import sys
from scrapy.selector import Selector
import amazon_crawler.spider_logger as db_logger
from amazon_crawler.items import AmazonItem as ReviewerItem
import amazon_crawler.mysql_helper as db
import amazon_crawler.html_extractor as html_extractor
from amazon_crawler.spider_base import SpiderBase
f... | amazon_crawler/amazon_crawler/spiders/reviewer.py | import scrapy
import sys
from scrapy.selector import Selector
import amazon_crawler.spider_logger as db_logger
from amazon_crawler.items import AmazonItem as ReviewerItem
import amazon_crawler.mysql_helper as db
import amazon_crawler.html_extractor as html_extractor
from amazon_crawler.spider_base import SpiderBase
f... | 0.145267 | 0.050075 |
from string import *
import re
from zapps.rt import *
class CommandParserScanner(Scanner):
patterns = [
('"/"', re.compile('/')),
('[ \t]+', re.compile('[ \t]+')),
('NUMBER', re.compile('[0-9]+')),
('STRING', re.compile('".*"')),
('FLOAT', re.compile('[0-9]+\\.[0-9]+')),
... | examples/command.py |
from string import *
import re
from zapps.rt import *
class CommandParserScanner(Scanner):
patterns = [
('"/"', re.compile('/')),
('[ \t]+', re.compile('[ \t]+')),
('NUMBER', re.compile('[0-9]+')),
('STRING', re.compile('".*"')),
('FLOAT', re.compile('[0-9]+\\.[0-9]+')),
... | 0.257672 | 0.09556 |
import WelcomeNote
import math
import OLSDims
import mdl
import EnvSettings
from osgeo import osr
import Circ
import os
import ObsData
class dataInput:
ip = mdl.Data()
f=ip.f
AppOLS = OLSDims.AppDim.AppOLS
ToOLS = OLSDims.TODim.ToOLS
AppOLSNAME=OLSDims.AppDim.AppOLSNAME
AppOLSDIMS=OLSDims.AppDim... | Point_Engine.py | import WelcomeNote
import math
import OLSDims
import mdl
import EnvSettings
from osgeo import osr
import Circ
import os
import ObsData
class dataInput:
ip = mdl.Data()
f=ip.f
AppOLS = OLSDims.AppDim.AppOLS
ToOLS = OLSDims.TODim.ToOLS
AppOLSNAME=OLSDims.AppDim.AppOLSNAME
AppOLSDIMS=OLSDims.AppDim... | 0.035763 | 0.166134 |
import os
from dotenv import load_dotenv
import praw
import json
load_dotenv(verbose=True)
CLIENT_ID = os.environ.get("CLIENT_ID")
CLIENT_SECRET = os.environ.get("CLIENT_SECRET")
USER_AGENT = os.environ.get("USER_AGENT")
USERNAME = os.environ.get("USERNAME")
PASSWORD = os.environ.get("PASSWORD")
def get_json():
... | reddit_comments.py | import os
from dotenv import load_dotenv
import praw
import json
load_dotenv(verbose=True)
CLIENT_ID = os.environ.get("CLIENT_ID")
CLIENT_SECRET = os.environ.get("CLIENT_SECRET")
USER_AGENT = os.environ.get("USER_AGENT")
USERNAME = os.environ.get("USERNAME")
PASSWORD = os.environ.get("PASSWORD")
def get_json():
... | 0.405096 | 0.079424 |
import json
import logging
import time
from datetime import datetime
from tempfile import SpooledTemporaryFile
from typing import List, Union, Dict, Any, Optional
import pandas
import requests
from fastapi.encoders import jsonable_encoder
from pytz import timezone
from sentry_sdk import capture_exception
from sqlalche... | backend/app/app/crud/crud_fact.py | import json
import logging
import time
from datetime import datetime
from tempfile import SpooledTemporaryFile
from typing import List, Union, Dict, Any, Optional
import pandas
import requests
from fastapi.encoders import jsonable_encoder
from pytz import timezone
from sentry_sdk import capture_exception
from sqlalche... | 0.720368 | 0.075244 |
# In[ ]:
import numpy as np
import matplotlib.pyplot as plt
from skimage.color import rgb2gray
from skimage.filters import gaussian
import scipy
import cv2
from scipy import ndimage
import Image_preperation as prep
import FitFunction as fit
import FileManager as fm
import Image_preperation as prep
def calc_mean... | ActiveFitContour.py |
# In[ ]:
import numpy as np
import matplotlib.pyplot as plt
from skimage.color import rgb2gray
from skimage.filters import gaussian
import scipy
import cv2
from scipy import ndimage
import Image_preperation as prep
import FitFunction as fit
import FileManager as fm
import Image_preperation as prep
def calc_mean... | 0.462716 | 0.567277 |
import numpy as np
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt
import os
import matplotlib.cm as cm
from collections import defaultdict
import matplotlib
font = {'family' : 'sans-serif',
'variant' : 'normal',
'weight' : 'light',
'size' : 14}
matplotlib.rc('font', **font)
def read_in_edges_... | src_general/SR_pdf.py | import numpy as np
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt
import os
import matplotlib.cm as cm
from collections import defaultdict
import matplotlib
font = {'family' : 'sans-serif',
'variant' : 'normal',
'weight' : 'light',
'size' : 14}
matplotlib.rc('font', **font)
def read_in_edges_... | 0.477067 | 0.716057 |
import struct
import sys
import os
disk_data = [
0x4A, 0x57, 0x5E, 0x75, 0x38, 0x66, 0x3B, 0x79, 0x3A, 0x60,
0x75, 0x61, 0x26, 0x38, 0x68, 0x5E, 0x28, 0x68, 0x6C, 0x6C,
0x72, 0x76, 0x71, 0x7E, 0x55, 0x47, 0x38, 0x42, 0x7A, 0x4A,
0x6B, 0x4D, 0x4D, 0x65, 0x37, 0x79, 0x45, 0x62, 0x2E, 0x70,
0x4C, 0x63, 0x38... | Gathered CTF writeups/codegate_quals_2020/malicious/malicious_mbr_crack.py | import struct
import sys
import os
disk_data = [
0x4A, 0x57, 0x5E, 0x75, 0x38, 0x66, 0x3B, 0x79, 0x3A, 0x60,
0x75, 0x61, 0x26, 0x38, 0x68, 0x5E, 0x28, 0x68, 0x6C, 0x6C,
0x72, 0x76, 0x71, 0x7E, 0x55, 0x47, 0x38, 0x42, 0x7A, 0x4A,
0x6B, 0x4D, 0x4D, 0x65, 0x37, 0x79, 0x45, 0x62, 0x2E, 0x70,
0x4C, 0x63, 0x38... | 0.034464 | 0.650009 |
# COMMAND ----------
# MAGIC %md
# MAGIC
# MAGIC # Density Estimation via Voronoi Diagrams in High Dimensions
# COMMAND ----------
# MAGIC %md
# MAGIC
# MAGIC <NAME> and <NAME>
# MAGIC
# MAGIC [Video of project presentation](https://drive.google.com/file/d/14E_igECN6hDZieWNn9VVTepCo5mu-rzy/view?usp=sharing)
# ... | dbcArchives/2021/000_0-sds-3-x-projects/student-project-17_group-TowardsScalableTDA/00_introduction.py |
# COMMAND ----------
# MAGIC %md
# MAGIC
# MAGIC # Density Estimation via Voronoi Diagrams in High Dimensions
# COMMAND ----------
# MAGIC %md
# MAGIC
# MAGIC <NAME> and <NAME>
# MAGIC
# MAGIC [Video of project presentation](https://drive.google.com/file/d/14E_igECN6hDZieWNn9VVTepCo5mu-rzy/view?usp=sharing)
# ... | 0.878562 | 0.842734 |
from django.shortcuts import render, HttpResponse, redirect, \
get_object_or_404, reverse
from django.contrib.auth.decorators import login_required
from django.contrib import messages
from django.conf import settings
from decimal import Decimal
from paypal.standard.forms import PayPalPaymentsForm
from django.views.... | ecommerce_app/views.py | from django.shortcuts import render, HttpResponse, redirect, \
get_object_or_404, reverse
from django.contrib.auth.decorators import login_required
from django.contrib import messages
from django.conf import settings
from decimal import Decimal
from paypal.standard.forms import PayPalPaymentsForm
from django.views.... | 0.508788 | 0.081739 |
import click
def parse_variable_filter(argument):
variable, _, values = argument[1:].partition('=')
if variable == 'py':
variable = 'python'
parsed_values = set(values.split(',')) if values else set()
return variable, parsed_values
def select_matrix_environments(environments, included_varia... | src/hatch/cli/run/__init__.py | import click
def parse_variable_filter(argument):
variable, _, values = argument[1:].partition('=')
if variable == 'py':
variable = 'python'
parsed_values = set(values.split(',')) if values else set()
return variable, parsed_values
def select_matrix_environments(environments, included_varia... | 0.649023 | 0.735167 |
import numpy as np
from tqdm import trange
from chapter04.car_rental_mine import cartesian_prod
np.random.seed(5)
class WindyWorld(object):
def __init__(self, hight, width, start, end, wind_force):
self.hight = hight
self.width = width
self.start = start
self.end = end
s... | chapter06/windy_grid_world_mine.py | import numpy as np
from tqdm import trange
from chapter04.car_rental_mine import cartesian_prod
np.random.seed(5)
class WindyWorld(object):
def __init__(self, hight, width, start, end, wind_force):
self.hight = hight
self.width = width
self.start = start
self.end = end
s... | 0.609989 | 0.441914 |
import matplotlib.pyplot as plt
from PIL import Image
import numpy as np
import nibabel as nib
import os
import cv2
import math
def water(img_path):
src = cv2.imread(img_path)
img = src.copy()
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(
gray, 0, 255, cv2.THRESH_BI... | util/mask2label.py | import matplotlib.pyplot as plt
from PIL import Image
import numpy as np
import nibabel as nib
import os
import cv2
import math
def water(img_path):
src = cv2.imread(img_path)
img = src.copy()
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(
gray, 0, 255, cv2.THRESH_BI... | 0.193566 | 0.329931 |
import math,random
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sn
from sklearn.metrics import confusion_matrix
import torch
import torch.nn.functional as F
from torch.utils.data import DataLoader, Dataset
import torchaudio
from torchaudio import transforms
class AudioData(D... | utils.py | import math,random
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sn
from sklearn.metrics import confusion_matrix
import torch
import torch.nn.functional as F
from torch.utils.data import DataLoader, Dataset
import torchaudio
from torchaudio import transforms
class AudioData(D... | 0.719778 | 0.438184 |
import requests
import argparse
import pathlib
import json
class PublishingFailedException(Exception):
pass
class PactBrokerInterface:
""" Interface to a pact-broker instance
Allows publishing pact test JSON files to pact-broker instance
Attributes
----------
url : str
pact-broker ... | pact_test_utils/publish_pacts.py | import requests
import argparse
import pathlib
import json
class PublishingFailedException(Exception):
pass
class PactBrokerInterface:
""" Interface to a pact-broker instance
Allows publishing pact test JSON files to pact-broker instance
Attributes
----------
url : str
pact-broker ... | 0.698946 | 0.147709 |
import re
class Account():
"""Client account"""
ID_COUNT = 1
def __init__(self, name, **kwargs):
self.id = self.ID_COUNT
self.name = name
self.__dict__.update(kwargs)
Account.ID_COUNT += 1
def __getitem__(self, key):
return getattr(self, key)
def __str__(... | Module_01/ex05/the_bank.py | import re
class Account():
"""Client account"""
ID_COUNT = 1
def __init__(self, name, **kwargs):
self.id = self.ID_COUNT
self.name = name
self.__dict__.update(kwargs)
Account.ID_COUNT += 1
def __getitem__(self, key):
return getattr(self, key)
def __str__(... | 0.539105 | 0.172694 |
from numpy.core.defchararray import zfill
import taichi as ti
import numpy as np
from .camera import *
from .shading import *
from .renderer_utils import ray_aabb_intersection, intersect_sphere, ray_plane_intersect, reflect, refract
inf = 1e8
eps = 1e-4
@ti.data_oriented
class ParticleRenderer:
padding = 3 # ext... | engine/fast_renderer/renderer.py | from numpy.core.defchararray import zfill
import taichi as ti
import numpy as np
from .camera import *
from .shading import *
from .renderer_utils import ray_aabb_intersection, intersect_sphere, ray_plane_intersect, reflect, refract
inf = 1e8
eps = 1e-4
@ti.data_oriented
class ParticleRenderer:
padding = 3 # ext... | 0.708213 | 0.514278 |
from __future__ import print_function
import argparse
import os
import csv
import sys
from scipy.stats import pearsonr
import numpy
import pandas
def mse(y_true, y_pred):
from sklearn.metrics import mean_squared_error
return mean_squared_error(y_true,y_pred)
def f1(y_true, y_pred):
from sklearn.metrics... | calculateEvaluationCCC.py | from __future__ import print_function
import argparse
import os
import csv
import sys
from scipy.stats import pearsonr
import numpy
import pandas
def mse(y_true, y_pred):
from sklearn.metrics import mean_squared_error
return mean_squared_error(y_true,y_pred)
def f1(y_true, y_pred):
from sklearn.metrics... | 0.337859 | 0.230573 |
import sys
import re
import json
import uuid
import datetime
import time
import glob
import codecs
__author__ = "<NAME>, <NAME>"
__copyright__ = "Copyright 2014"
__license__ = "GPL"
__version__ = "3.0.0"
__maintainer__ = "<NAME>"
__email__ = "<EMAIL>"
__status__ = "Production"
# ghost settings
post_id = 1
author_id =... | octopress2ghost.py | import sys
import re
import json
import uuid
import datetime
import time
import glob
import codecs
__author__ = "<NAME>, <NAME>"
__copyright__ = "Copyright 2014"
__license__ = "GPL"
__version__ = "3.0.0"
__maintainer__ = "<NAME>"
__email__ = "<EMAIL>"
__status__ = "Production"
# ghost settings
post_id = 1
author_id =... | 0.223377 | 0.161353 |
import mock
import pytest
from boto3.exceptions import Boto3Error
from ruamel.yaml import YAML
from paasta_tools.cli.cmds.spark_run import configure_and_run_docker_container
from paasta_tools.cli.cmds.spark_run import create_spark_config_str
from paasta_tools.cli.cmds.spark_run import DEFAULT_SERVICE
from paasta_tools... | tests/cli/test_cmds_spark_run.py | import mock
import pytest
from boto3.exceptions import Boto3Error
from ruamel.yaml import YAML
from paasta_tools.cli.cmds.spark_run import configure_and_run_docker_container
from paasta_tools.cli.cmds.spark_run import create_spark_config_str
from paasta_tools.cli.cmds.spark_run import DEFAULT_SERVICE
from paasta_tools... | 0.453262 | 0.137243 |
import logging
import os
def env_bool(name: str) -> bool:
raw_value = os.getenv(name, "")
return raw_value.lower() == "true"
def env_list(name: str) -> list[str]:
raw_value = os.getenv(name, "")
if not raw_value:
return []
return raw_value.split(",")
SILENCED_SYSTEM_CHECKS = []
# ... | chmvh_website/chmvh_website/settings.py | import logging
import os
def env_bool(name: str) -> bool:
raw_value = os.getenv(name, "")
return raw_value.lower() == "true"
def env_list(name: str) -> list[str]:
raw_value = os.getenv(name, "")
if not raw_value:
return []
return raw_value.split(",")
SILENCED_SYSTEM_CHECKS = []
# ... | 0.405684 | 0.131145 |
from tensorflow.keras.models import Sequential
from tensorflow.keras import backend as K
from tensorflow.keras.layers import BatchNormalization
from tensorflow.keras.layers import Conv2D
from tensorflow.keras.layers import RandomRotation
from tensorflow.keras.layers import MaxPooling2D
from tensorflow.keras.layers impo... | CNN.py | from tensorflow.keras.models import Sequential
from tensorflow.keras import backend as K
from tensorflow.keras.layers import BatchNormalization
from tensorflow.keras.layers import Conv2D
from tensorflow.keras.layers import RandomRotation
from tensorflow.keras.layers import MaxPooling2D
from tensorflow.keras.layers impo... | 0.564098 | 0.511595 |
import MySQLdb as mysql
import os
import jieba
from wordcloud import WordCloud, ImageColorGenerator
from concurrent.futures import ThreadPoolExecutor as tpe
from matplotlib import pyplot as plt
from util import PROJECT_ABS_PATH
from scipy.misc import imread
import time
custom_dictionary = ["韩国人", "中国人", "第三世界", "死宅",... | analyse/count.py | import MySQLdb as mysql
import os
import jieba
from wordcloud import WordCloud, ImageColorGenerator
from concurrent.futures import ThreadPoolExecutor as tpe
from matplotlib import pyplot as plt
from util import PROJECT_ABS_PATH
from scipy.misc import imread
import time
custom_dictionary = ["韩国人", "中国人", "第三世界", "死宅",... | 0.123405 | 0.15633 |
import argparse
from itertools import combinations
import os
import sys
import matplotlib
matplotlib.use("PDF")
import matplotlib.pyplot as plt
import mdtraj as md
import numpy as np
from sklearn.decomposition import FastICA
from sklearn.decomposition import PCA
from sklearn.decomposition import TruncatedSVD
from skle... | crewman_daniels/component_analysis.py | import argparse
from itertools import combinations
import os
import sys
import matplotlib
matplotlib.use("PDF")
import matplotlib.pyplot as plt
import mdtraj as md
import numpy as np
from sklearn.decomposition import FastICA
from sklearn.decomposition import PCA
from sklearn.decomposition import TruncatedSVD
from skle... | 0.424173 | 0.293797 |
from collections import defaultdict
from decimal import Decimal
from django.db import models, transaction
from django.db.models import Count
from django.db.models.fields.reverse_related import ForeignObjectRel
from article.models import ArticleType, OrProductType
from blame.models import ImmutableBlame, Blame
from cr... | backend/logistics/models.py | from collections import defaultdict
from decimal import Decimal
from django.db import models, transaction
from django.db.models import Count
from django.db.models.fields.reverse_related import ForeignObjectRel
from article.models import ArticleType, OrProductType
from blame.models import ImmutableBlame, Blame
from cr... | 0.821975 | 0.444444 |
import numpy as np
class ObjectStatic:
"""
Static data for an object. This data won't change between frames.
"""
def __init__(self, name: str, object_id: int, mass: float, segmentation_color: np.array, size: np.array,
category: str, kinematic: bool, dynamic_friction: float, static_fr... | Python/tdw/object_data/object_static.py | import numpy as np
class ObjectStatic:
"""
Static data for an object. This data won't change between frames.
"""
def __init__(self, name: str, object_id: int, mass: float, segmentation_color: np.array, size: np.array,
category: str, kinematic: bool, dynamic_friction: float, static_fr... | 0.933035 | 0.736472 |
from django.db import migrations, models
import django.db.models.deletion
import django.utils.timezone
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='Almacen',
fields=[
('idalmace... | full_inventory/migrations/0001_initial.py |
from django.db import migrations, models
import django.db.models.deletion
import django.utils.timezone
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='Almacen',
fields=[
('idalmace... | 0.526099 | 0.139484 |
import chainer
from chainer import Variable
import chainer.functions as F
import numpy as np
import copy
from losses import loss_fun
from transport_costs import cost_fun
from attacks import wrm_attack
def get_batch(iterator, xp):
batch = iterator.next()
batchsize = len(batch)
x = []
y = []
for j i... | extentions.py | import chainer
from chainer import Variable
import chainer.functions as F
import numpy as np
import copy
from losses import loss_fun
from transport_costs import cost_fun
from attacks import wrm_attack
def get_batch(iterator, xp):
batch = iterator.next()
batchsize = len(batch)
x = []
y = []
for j i... | 0.4856 | 0.228415 |
import os
import buildbot
import buildbot.process.factory
from buildbot.steps.source import SVN
from buildbot.steps.shell import ShellCommand, SetProperty
from buildbot.steps.slave import RemoveDirectory
from buildbot.process.properties import WithProperties, Property
from zorg.buildbot.builders.Util import getVisualS... | zorg/buildbot/builders/LLDBuilder.py | import os
import buildbot
import buildbot.process.factory
from buildbot.steps.source import SVN
from buildbot.steps.shell import ShellCommand, SetProperty
from buildbot.steps.slave import RemoveDirectory
from buildbot.process.properties import WithProperties, Property
from zorg.buildbot.builders.Util import getVisualS... | 0.356671 | 0.092565 |
# Make coding more python3-ish
from __future__ import absolute_import, division, print_function
__metaclass__ = type
import pytest
from ansible_collections.community.internal_test_tools.tests.unit.compat.mock import patch
from ansible_collections.community.internal_test_tools.tests.unit.plugins.modules.utils impo... | venv/lib/python3.8/site-packages/ansible_collections/community/dns/tests/unit/plugins/modules/test_wait_for_txt.py |
# Make coding more python3-ish
from __future__ import absolute_import, division, print_function
__metaclass__ = type
import pytest
from ansible_collections.community.internal_test_tools.tests.unit.compat.mock import patch
from ansible_collections.community.internal_test_tools.tests.unit.plugins.modules.utils impo... | 0.630002 | 0.22482 |
import codecs
import re
from codecs import StreamReaderWriter
from typing import Optional
from logging2.handlers.abc import Handler
from logging2.levels import LogLevel
# NOTE: This module does not provide handlers for rotating log files. The rationale behind that is that all *NIX systems
# have software specificall... | logging2/handlers/files.py | import codecs
import re
from codecs import StreamReaderWriter
from typing import Optional
from logging2.handlers.abc import Handler
from logging2.levels import LogLevel
# NOTE: This module does not provide handlers for rotating log files. The rationale behind that is that all *NIX systems
# have software specificall... | 0.800224 | 0.234341 |
import logging
from abc import ABC, abstractmethod
import numpy as np
import pandas as pd
from hdrbp._util import (
basic_repr,
basic_str,
compute_correlation,
compute_diversification_ratio,
compute_drawdowns,
compute_gini,
compute_prices,
compute_risk_contributions,
compute_turnov... | hdrbp/metric.py | import logging
from abc import ABC, abstractmethod
import numpy as np
import pandas as pd
from hdrbp._util import (
basic_repr,
basic_str,
compute_correlation,
compute_diversification_ratio,
compute_drawdowns,
compute_gini,
compute_prices,
compute_risk_contributions,
compute_turnov... | 0.895543 | 0.449876 |
from datetime import datetime
from typing import Any, Dict
from core.forms import GameForm
from core.test.tests_helpers import create_game, create_platform
from django.core.exceptions import ValidationError
from django.test import TestCase
class GameFormTests(TestCase):
def setUp(self) -> None:
self.plat... | finishedgames/core/test/test_game_form.py | from datetime import datetime
from typing import Any, Dict
from core.forms import GameForm
from core.test.tests_helpers import create_game, create_platform
from django.core.exceptions import ValidationError
from django.test import TestCase
class GameFormTests(TestCase):
def setUp(self) -> None:
self.plat... | 0.651244 | 0.454048 |
import os
import random
import en_core_web_sm
import stringx
import tensorflow as tf
import tensorflow.logging as log
from tensorflow.python.lib.io import file_io
nlp = en_core_web_sm.load()
# acceptable ways to end a sentence
END_TOKENS = ['.', '!', '?', '...', "'", "`", '"', ")"]
STOPLIST = frozenset(['@highlight'... | trainer/etl.py | import os
import random
import en_core_web_sm
import stringx
import tensorflow as tf
import tensorflow.logging as log
from tensorflow.python.lib.io import file_io
nlp = en_core_web_sm.load()
# acceptable ways to end a sentence
END_TOKENS = ['.', '!', '?', '...', "'", "`", '"', ")"]
STOPLIST = frozenset(['@highlight'... | 0.529263 | 0.280145 |
from ctypes import *
from os import EX_CANTCREAT
import threading
import queue
import time
import copy
COM_OK = 0
COM_ERROR = 1
COM_ABORT = 2
COM_TIMEOUT = 3
MASTER_BROADCAST=0x07FF
MASTER_P2P_MASK =0x0400
RX_FILTER_MASK_ALL=0xFFFFFFFF
RX_FILTER_MASK_ONE=0x00000000
RX_VERBOS... | Host/usbCAN/usbCAN.py | from ctypes import *
from os import EX_CANTCREAT
import threading
import queue
import time
import copy
COM_OK = 0
COM_ERROR = 1
COM_ABORT = 2
COM_TIMEOUT = 3
MASTER_BROADCAST=0x07FF
MASTER_P2P_MASK =0x0400
RX_FILTER_MASK_ALL=0xFFFFFFFF
RX_FILTER_MASK_ONE=0x00000000
RX_VERBOS... | 0.13102 | 0.100923 |
from flask_restful import Resource
import libs.http_status as status
import libs.json_response as response
from libs.validator import Validator, require_json
from managers.todo_manager import TodoManager
from pprint import pprint
manager = TodoManager()
class TodosResource(Resource):
def get(self):
data ... | routes/todos.py | from flask_restful import Resource
import libs.http_status as status
import libs.json_response as response
from libs.validator import Validator, require_json
from managers.todo_manager import TodoManager
from pprint import pprint
manager = TodoManager()
class TodosResource(Resource):
def get(self):
data ... | 0.253122 | 0.071494 |
from OpenPNM.Geometry import models as gm
from OpenPNM.Geometry import GenericGeometry
class Stick_and_Ball(GenericGeometry):
r"""
Stick and Ball subclass of GenericGeometry. This subclass is meant as a
basic default geometry to get started quickly.
Parameters
----------
name : string
... | OpenPNM/Geometry/__Stick_and_Ball__.py | from OpenPNM.Geometry import models as gm
from OpenPNM.Geometry import GenericGeometry
class Stick_and_Ball(GenericGeometry):
r"""
Stick and Ball subclass of GenericGeometry. This subclass is meant as a
basic default geometry to get started quickly.
Parameters
----------
name : string
... | 0.870501 | 0.230194 |
from .schfile import SchFile
'''
Given a top schematic file name, SchDict will
read all the schematics and put them in a dictionary.
If they are instantiated multiple times, they will only
be read/parsed once, but each instantiation will have its
own dictionary entry with its own timestamp and parent.
'''
class Sheet... | kipy/fileobjs/sch/schdict.py | from .schfile import SchFile
'''
Given a top schematic file name, SchDict will
read all the schematics and put them in a dictionary.
If they are instantiated multiple times, they will only
be read/parsed once, but each instantiation will have its
own dictionary entry with its own timestamp and parent.
'''
class Sheet... | 0.459076 | 0.258674 |