code stringlengths 2k 1.04M | repo_path stringlengths 5 517 | parsed_code stringlengths 0 1.04M | quality_prob float64 0.02 0.95 | learning_prob float64 0.02 0.93 |
|---|---|---|---|---|
from typing import List
import sys
from ..day import Day
class Board:
def __init__(self, data: List[List]) -> None:
self.__data = data
self.__marked_numbers = []
self.__won = False
def mark(self, number):
if self.__won:
return
self.__marked_numbers.appen... | aoc/day4/day.py |
from typing import List
import sys
from ..day import Day
class Board:
def __init__(self, data: List[List]) -> None:
self.__data = data
self.__marked_numbers = []
self.__won = False
def mark(self, number):
if self.__won:
return
self.__marked_numbers.appen... | 0.52756 | 0.246244 |
from __future__ import print_function, division
import os
from ._node import DirNode, LinkedDir, CyclicLinkedDir
from ._path import RecursionPath, DirEntryReplacement
def assert_dir_entry_equal(de1, de2):
# TODO check has attributes
assert de1.path == de2.path
assert de1.name == de2.name
for method,... | src/scantree/test_utils.py | from __future__ import print_function, division
import os
from ._node import DirNode, LinkedDir, CyclicLinkedDir
from ._path import RecursionPath, DirEntryReplacement
def assert_dir_entry_equal(de1, de2):
# TODO check has attributes
assert de1.path == de2.path
assert de1.name == de2.name
for method,... | 0.2819 | 0.308464 |
r"""
=====================================================
Panel Connections (:mod:`compmech.panel.connections`)
=====================================================
.. currentmodule:: compmech.panel.connections
Connection between panel domains. Each panel domain has its own set of Bardell
approximation functions. B... | compmech/panel/connections/__init__.py | r"""
=====================================================
Panel Connections (:mod:`compmech.panel.connections`)
=====================================================
.. currentmodule:: compmech.panel.connections
Connection between panel domains. Each panel domain has its own set of Bardell
approximation functions. B... | 0.861115 | 0.55658 |
import matplotlib.pyplot as plt
from scipy.stats import norm
def group_res(data, group_cols, statistic):
"""Splits dataframe into dictionary based on grouping
:param data: input data to be split
:param group_cols: group columns for data
:param statistic: statistic to be calculated
... | resample/utility.py | import matplotlib.pyplot as plt
from scipy.stats import norm
def group_res(data, group_cols, statistic):
"""Splits dataframe into dictionary based on grouping
:param data: input data to be split
:param group_cols: group columns for data
:param statistic: statistic to be calculated
... | 0.829388 | 0.831383 |
import argparse
from query_type import QueryType
import socket
import time
import ipaddress
from serializer import Serializer
from deserializer import Deserializer
class DNSClient:
def __init__(self, params):
self.name = params.name
self.address = params.address
self.maxRetr... | dns_client.py |
import argparse
from query_type import QueryType
import socket
import time
import ipaddress
from serializer import Serializer
from deserializer import Deserializer
class DNSClient:
def __init__(self, params):
self.name = params.name
self.address = params.address
self.maxRetr... | 0.327023 | 0.049912 |
from typing import Callable, Optional
import gurobipy
import lightgbm as lgb
import opti
import pandas as pd
from mbo.algorithm import Algorithm
from entmoot.optimizer import Optimizer
from entmoot.optimizer.gurobi_utils import get_core_gurobi_model
from entmoot.space.space import Categorical, Integer, Real, Space
... | entmoot/optimizer/entmootopti.py | from typing import Callable, Optional
import gurobipy
import lightgbm as lgb
import opti
import pandas as pd
from mbo.algorithm import Algorithm
from entmoot.optimizer import Optimizer
from entmoot.optimizer.gurobi_utils import get_core_gurobi_model
from entmoot.space.space import Categorical, Integer, Real, Space
... | 0.850267 | 0.407569 |
from __future__ import absolute_import, division, print_function
import re
import os
import subprocess
import tempfile
import requests
def to_snake_case(s, sep="_"):
# type: (str, str) -> str
p = r"\1" + sep + r"\2"
s1 = re.sub("(.)([A-Z][a-z]+)", p, s)
return re.sub("([a-z0-9])([A-Z])", p, s1).low... | spotify_tensorflow/luigi/utils.py |
from __future__ import absolute_import, division, print_function
import re
import os
import subprocess
import tempfile
import requests
def to_snake_case(s, sep="_"):
# type: (str, str) -> str
p = r"\1" + sep + r"\2"
s1 = re.sub("(.)([A-Z][a-z]+)", p, s)
return re.sub("([a-z0-9])([A-Z])", p, s1).low... | 0.663342 | 0.14627 |
from contextlib import contextmanager
from crl.interactivesessions._terminalpools import _TerminalPools
from ._process import (
_AsyncProcessWithoutPty,
_ForegroundProcessWithoutPty,
_BackgroundProcessWithoutPty,
_NoCommBackgroudProcess)
from ._targetproperties import _TargetProperties
__copyright__ =... | src/crl/interactivesessions/_runnerintarget.py | from contextlib import contextmanager
from crl.interactivesessions._terminalpools import _TerminalPools
from ._process import (
_AsyncProcessWithoutPty,
_ForegroundProcessWithoutPty,
_BackgroundProcessWithoutPty,
_NoCommBackgroudProcess)
from ._targetproperties import _TargetProperties
__copyright__ =... | 0.650689 | 0.070304 |
from abc import ABC, abstractmethod
from io import StringIO
from typing import TYPE_CHECKING, Any, Callable, List, Optional, Union, overload
from pydantic import root_validator
from typing_extensions import Literal
from vkbottle_types.objects import (
AudioAudio,
DocsDoc,
MessagesForward,
MessagesMessa... | vkbottle/tools/dev/mini_types/base/message.py | from abc import ABC, abstractmethod
from io import StringIO
from typing import TYPE_CHECKING, Any, Callable, List, Optional, Union, overload
from pydantic import root_validator
from typing_extensions import Literal
from vkbottle_types.objects import (
AudioAudio,
DocsDoc,
MessagesForward,
MessagesMessa... | 0.846006 | 0.12408 |
from __future__ import print_function
import argparse
import codecs
import fnmatch
import os
import sys
import yamale
import yaml
def find_question_files(root_directory):
"""Yield all YAML files recursively."""
for root, _, files in os.walk(root_directory):
for basename in fnmatch.filter(files, "[!_]... | spec/validate_question.py |
from __future__ import print_function
import argparse
import codecs
import fnmatch
import os
import sys
import yamale
import yaml
def find_question_files(root_directory):
"""Yield all YAML files recursively."""
for root, _, files in os.walk(root_directory):
for basename in fnmatch.filter(files, "[!_]... | 0.434941 | 0.179981 |
from collections import namedtuple
import numpy as np
from roifile import ImagejRoi
from skimage.draw import polygon, polygon_perimeter
from tifffile import TiffFile, TiffWriter
from . import REGION_BACKGROUND, REGION_BORDER, REGION_FOREGROUND
TiffWriter = TiffWriter
TiffInfo = namedtuple('TiffInfo', 'pages, w, h, ... | junn/io/tiffmasks.py | from collections import namedtuple
import numpy as np
from roifile import ImagejRoi
from skimage.draw import polygon, polygon_perimeter
from tifffile import TiffFile, TiffWriter
from . import REGION_BACKGROUND, REGION_BORDER, REGION_FOREGROUND
TiffWriter = TiffWriter
TiffInfo = namedtuple('TiffInfo', 'pages, w, h, ... | 0.70202 | 0.336331 |
import sys, os, xml.sax, re
from xml.dom.minidom import parse, parseString, getDOMImplementation
SCRIPT_DIR = os.path.dirname(os.path.realpath(__file__))
SCRIPT_NAME = os.path.splitext(os.path.split(__file__)[1])[0]
DESCRIPTION = 'Merge two idlak output files to have matching initial / end breaks'
FRAMESHIFT=0.005
# ... | idlak-egs/tts_tangle_arctic/s2/local/merge_breaks.py | import sys, os, xml.sax, re
from xml.dom.minidom import parse, parseString, getDOMImplementation
SCRIPT_DIR = os.path.dirname(os.path.realpath(__file__))
SCRIPT_NAME = os.path.splitext(os.path.split(__file__)[1])[0]
DESCRIPTION = 'Merge two idlak output files to have matching initial / end breaks'
FRAMESHIFT=0.005
# ... | 0.126326 | 0.088939 |
from __future__ import absolute_import
import os
import vcr
import unittest
from hatchbuck.api import HatchbuckAPI, HatchbuckAPIAuthenticationError
class TestSearchContacts(unittest.TestCase):
def setUp(self):
# Fake key can be used with existing cassettes
self.test_api_key = os.environ.get("HATC... | tests/test_search_contacts.py | from __future__ import absolute_import
import os
import vcr
import unittest
from hatchbuck.api import HatchbuckAPI, HatchbuckAPIAuthenticationError
class TestSearchContacts(unittest.TestCase):
def setUp(self):
# Fake key can be used with existing cassettes
self.test_api_key = os.environ.get("HATC... | 0.500732 | 0.132318 |
import gzip
import json
from typing import cast
from unittest.mock import Mock
import pytest
from pytest_wdl.config import UserConfiguration
from pytest_wdl.core import (
DefaultDataFile, DataDirs, DataManager, DataResolver, create_data_file
)
from pytest_wdl.localizers import LinkLocalizer, UrlLocalizer
from py... | tests/test_core.py |
import gzip
import json
from typing import cast
from unittest.mock import Mock
import pytest
from pytest_wdl.config import UserConfiguration
from pytest_wdl.core import (
DefaultDataFile, DataDirs, DataManager, DataResolver, create_data_file
)
from pytest_wdl.localizers import LinkLocalizer, UrlLocalizer
from py... | 0.67822 | 0.314129 |
import os
import glob
import shutil
import tarfile
import argparse
import mapred_utils as util
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--folder', default=os.getcwd(), help='The "save folder" of the map/reduce task being backed up')
parser.add_argument('--name', ... | external_packages/matlab/non_default_packages/Gaussian_Process/deck/+dk/+mapred/python/mapred_backup.py |
import os
import glob
import shutil
import tarfile
import argparse
import mapred_utils as util
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--folder', default=os.getcwd(), help='The "save folder" of the map/reduce task being backed up')
parser.add_argument('--name', ... | 0.099284 | 0.077518 |
import requests
import pyexcel as pe
from bs4 import BeautifulSoup
from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer
import csv
import re
from datetime import datetime
class Text:
def __init__(self, body):
self.body = body
def calculate_sentiment(self, analyzer):
vs = analyz... | scraping.py | import requests
import pyexcel as pe
from bs4 import BeautifulSoup
from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer
import csv
import re
from datetime import datetime
class Text:
def __init__(self, body):
self.body = body
def calculate_sentiment(self, analyzer):
vs = analyz... | 0.299515 | 0.220384 |
import dash_core_components as dcc
import dash_html_components as html
def render(title="Earnings Overview", xl_size=8, lg_size=7, dropdown_id="dropdownMenuLink", graph=dcc.Graph()):
return html.Div(
className=f'col-xl-{xl_size} col-lg-{lg_size}',
children=html.Div(
className='card sha... | SB_Admin_2/templates/layouts/graph_wrapper.py | import dash_core_components as dcc
import dash_html_components as html
def render(title="Earnings Overview", xl_size=8, lg_size=7, dropdown_id="dropdownMenuLink", graph=dcc.Graph()):
return html.Div(
className=f'col-xl-{xl_size} col-lg-{lg_size}',
children=html.Div(
className='card sha... | 0.505859 | 0.0686 |
import typing, math, os
import multiprocessing, tempfile, pickle
def divideChunks(lis: typing.Iterable, n_size: int) -> typing.Iterator:
for i in range(0, len(lis), n_size):
yield lis[i:i + n_size]
def inferWorkers() -> int:
workers = multiprocessing.cpu_count() - 1
return workers
def lisJobParallel(f... | b64ImConverter/multiProcess.py | import typing, math, os
import multiprocessing, tempfile, pickle
def divideChunks(lis: typing.Iterable, n_size: int) -> typing.Iterator:
for i in range(0, len(lis), n_size):
yield lis[i:i + n_size]
def inferWorkers() -> int:
workers = multiprocessing.cpu_count() - 1
return workers
def lisJobParallel(f... | 0.363082 | 0.283639 |
from .conf import settings
import urllib.request
import urllib.error
import logging
import sys
import time
log = logging.getLogger('svp_integration')
def list_request(path):
try:
response = urllib.request.urlopen(settings.svp_url + "?" + path)
return response.read().decode('utf-8').replace('\r\n',... | plex_mpv_shim/svp_integration.py | from .conf import settings
import urllib.request
import urllib.error
import logging
import sys
import time
log = logging.getLogger('svp_integration')
def list_request(path):
try:
response = urllib.request.urlopen(settings.svp_url + "?" + path)
return response.read().decode('utf-8').replace('\r\n',... | 0.181372 | 0.071106 |
import sys
import numpy as np
import pylab as pl
import scipy.signal
from UFL.common import DataInputOutput, DataNormalization, Visualization
from UFL.PCA import PCA
from UFL.SoftICA import SoftICA
from UFL.Softmax import Softmax
def convolveAndPool(images, W, poolDim):
''' Returns the convolution of the features gi... | examples/SelfTaughtLearning.py | import sys
import numpy as np
import pylab as pl
import scipy.signal
from UFL.common import DataInputOutput, DataNormalization, Visualization
from UFL.PCA import PCA
from UFL.SoftICA import SoftICA
from UFL.Softmax import Softmax
def convolveAndPool(images, W, poolDim):
''' Returns the convolution of the features gi... | 0.534612 | 0.601974 |
import numpy as np
import pyqtgraph as pg
import time
import csv
import sys
import thorlabs_apt as apt
from PyQt5.Qsci import QsciScintilla, QsciLexerPython
from spyre import Spyrelet, Task, Element
from spyre.widgets.task import TaskWidget
from spyre.plotting import LinePlotWidget
from spyre.widgets.rangespace impor... | spyre/spyre/spyrelets/fiberpulling_spyrelet.py | import numpy as np
import pyqtgraph as pg
import time
import csv
import sys
import thorlabs_apt as apt
from PyQt5.Qsci import QsciScintilla, QsciLexerPython
from spyre import Spyrelet, Task, Element
from spyre.widgets.task import TaskWidget
from spyre.plotting import LinePlotWidget
from spyre.widgets.rangespace impor... | 0.222785 | 0.242441 |
import unittest
from pkg_resources import resource_filename
import numpy as np
try:
import fitsio
missing_fitsio = False
except ImportError:
missing_fitsio = True
from desisim import lya_spectra
class TestLya(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.infile = resource... | py/desisim/test/test_lya.py | import unittest
from pkg_resources import resource_filename
import numpy as np
try:
import fitsio
missing_fitsio = False
except ImportError:
missing_fitsio = True
from desisim import lya_spectra
class TestLya(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.infile = resource... | 0.561455 | 0.449695 |
import numpy as np
import ref
from .img import Transform
def getPreds(hm):
assert len(hm.shape) == 4, 'Input must be a 4-D tensor'
res = hm.shape[2]
hm = hm.reshape(hm.shape[0], hm.shape[1], hm.shape[2] * hm.shape[3])
idx = np.argmax(hm, axis = 2)
preds = np.zeros((hm.shape[0], hm.shape[1], 2))
... | utils/eval.py | import numpy as np
import ref
from .img import Transform
def getPreds(hm):
assert len(hm.shape) == 4, 'Input must be a 4-D tensor'
res = hm.shape[2]
hm = hm.reshape(hm.shape[0], hm.shape[1], hm.shape[2] * hm.shape[3])
idx = np.argmax(hm, axis = 2)
preds = np.zeros((hm.shape[0], hm.shape[1], 2))
... | 0.356671 | 0.634685 |
import requests
from ..classes import Champion
class DataDragonAPI:
def __init__(self):
self.latest = self.get_versions()[0]
def get_versions(self):
"""
Get a list of all versions.
:rtype: List[str]
"""
list = requests.get('https://ddragon.leagueoflegends.com/... | riot_apy/apis/DataDragonAPI.py | import requests
from ..classes import Champion
class DataDragonAPI:
def __init__(self):
self.latest = self.get_versions()[0]
def get_versions(self):
"""
Get a list of all versions.
:rtype: List[str]
"""
list = requests.get('https://ddragon.leagueoflegends.com/... | 0.611034 | 0.2227 |
AppId = "8c6cc7b45d2568fb668be6e05b6e5a3b"
# locale parameter(url postfix)
LocaleParam = "&gcc=KR&locale=ko_KR"
PlatformPCParam = "&platformType=PC"
# API: Post Info API
# APIPostUrl("POST-ID"): str
# APIPostReferer("POST-ID"): dict
def APIPostUrl(post):
return "https://www.vlive.tv/globalv-web/vam-web/post/v1.... | vlivepy/variables.py | AppId = "8c6cc7b45d2568fb668be6e05b6e5a3b"
# locale parameter(url postfix)
LocaleParam = "&gcc=KR&locale=ko_KR"
PlatformPCParam = "&platformType=PC"
# API: Post Info API
# APIPostUrl("POST-ID"): str
# APIPostReferer("POST-ID"): dict
def APIPostUrl(post):
return "https://www.vlive.tv/globalv-web/vam-web/post/v1.... | 0.417271 | 0.117826 |
import json
import os
import time
from traceback import print_exc
from typing import TypedDict, cast
import click
from flask import Flask, redirect, url_for, session
from flask.cli import with_appcontext
from flask.wrappers import Response
from flask_dance.contrib.google import make_google_blueprint
from flask_dance.co... | server.py | import json
import os
import time
from traceback import print_exc
from typing import TypedDict, cast
import click
from flask import Flask, redirect, url_for, session
from flask.cli import with_appcontext
from flask.wrappers import Response
from flask_dance.contrib.google import make_google_blueprint
from flask_dance.co... | 0.423577 | 0.054651 |
from abc import ABC, abstractmethod
from functools import lru_cache
from typing import Iterator
class Team(ABC):
"""Abstract interface for some teams."""
pass
class Teams(ABC):
"""Abstract interface for some teams."""
@abstractmethod
def __next__(self) -> Team:
pass
@abstractmetho... | stats/league/teams.py | from abc import ABC, abstractmethod
from functools import lru_cache
from typing import Iterator
class Team(ABC):
"""Abstract interface for some teams."""
pass
class Teams(ABC):
"""Abstract interface for some teams."""
@abstractmethod
def __next__(self) -> Team:
pass
@abstractmetho... | 0.872863 | 0.128635 |
import serial
import time
import socket
import struct
import msvcrt
ser = serial.Serial('com7', 9600, timeout = 0.5)
UDP_IP = "10.6.3.1"
UDP_PORT = 5005
#sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
#sock.bind((UDP_IP, UDP_PORT))
#sock.listen(1)
#conn, addr = sock.accept()
#print "Connected by: ", addr
... | gcs_code.py | import serial
import time
import socket
import struct
import msvcrt
ser = serial.Serial('com7', 9600, timeout = 0.5)
UDP_IP = "10.6.3.1"
UDP_PORT = 5005
#sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
#sock.bind((UDP_IP, UDP_PORT))
#sock.listen(1)
#conn, addr = sock.accept()
#print "Connected by: ", addr
... | 0.05634 | 0.072834 |
#Scraps a page from Amazon website and collects all the product related information from the website and store them in a data frame.
import pandas as pd
import numpy as np
import re
from urllib.request import urlopen
from bs4 import BeautifulSoup
import requests
no_pages = 1
def get_data(pageNo):
r = re... | PYTHON/web_scraping_Amazon.py |
#Scraps a page from Amazon website and collects all the product related information from the website and store them in a data frame.
import pandas as pd
import numpy as np
import re
from urllib.request import urlopen
from bs4 import BeautifulSoup
import requests
no_pages = 1
def get_data(pageNo):
r = re... | 0.1254 | 0.247879 |
import os
import shutil
import sys
import tinify
import settings
SUPPORTED_FORMATS = ('jpg', 'jpeg', 'png')
def create_dirs(raw_images_dir=settings.USER_INPUT_PATH,
save_dir=settings.USER_OUTPUT_PATH):
"""Creates the necessary directories if they do not exist.
Args
raw_images_dir ... | image_optimizer.py | import os
import shutil
import sys
import tinify
import settings
SUPPORTED_FORMATS = ('jpg', 'jpeg', 'png')
def create_dirs(raw_images_dir=settings.USER_INPUT_PATH,
save_dir=settings.USER_OUTPUT_PATH):
"""Creates the necessary directories if they do not exist.
Args
raw_images_dir ... | 0.375936 | 0.177829 |
from libqtile.config import Group, Key
from libqtile.lazy import lazy
from variables.commands import Commands, mod
# A list of available commands that can be bound to keys can be found
# at https://docs.qtile.org/en/latest/manual/config/lazy.html
# Qtile keyboard shortcuts
keys = [
# Qtile
Key([mod, 'control'... | qtile/modules/shortcuts.py | from libqtile.config import Group, Key
from libqtile.lazy import lazy
from variables.commands import Commands, mod
# A list of available commands that can be bound to keys can be found
# at https://docs.qtile.org/en/latest/manual/config/lazy.html
# Qtile keyboard shortcuts
keys = [
# Qtile
Key([mod, 'control'... | 0.556641 | 0.184694 |
from __future__ import unicode_literals
from django.db import models, migrations
import msgvis.apps.enhance.fields
class Migration(migrations.Migration):
dependencies = [
('corpus', '0014_auto_20150221_0240'),
]
operations = [
migrations.CreateModel(
name='Dictionary',
... | msgvis/apps/enhance/migrations/0001_initial.py | from __future__ import unicode_literals
from django.db import models, migrations
import msgvis.apps.enhance.fields
class Migration(migrations.Migration):
dependencies = [
('corpus', '0014_auto_20150221_0240'),
]
operations = [
migrations.CreateModel(
name='Dictionary',
... | 0.638948 | 0.171859 |
import unittest
import numpy as np
class ExtendedTestCase(unittest.TestCase):
# pylint: disable=invalid-name
"""
Extended ``TestCase`` class of the ``unittest`` module.
"""
def assertAlmostEqualArrays(self, obtained_array, expected_array):
"""
Assert that two NumPy arrays are elem... | mcdm/tests/helper_testing.py | import unittest
import numpy as np
class ExtendedTestCase(unittest.TestCase):
# pylint: disable=invalid-name
"""
Extended ``TestCase`` class of the ``unittest`` module.
"""
def assertAlmostEqualArrays(self, obtained_array, expected_array):
"""
Assert that two NumPy arrays are elem... | 0.734596 | 0.77223 |
from __future__ import (
division, absolute_import, print_function, unicode_literals,
)
from builtins import * # noqa
from future.builtins.disabled import * # noqa
from magic_constraints.exception import MagicSyntaxError, MagicTypeError
def transform_to_slots(constraints_package, *args, **kwarg... | magic_constraints/argument.py | from __future__ import (
division, absolute_import, print_function, unicode_literals,
)
from builtins import * # noqa
from future.builtins.disabled import * # noqa
from magic_constraints.exception import MagicSyntaxError, MagicTypeError
def transform_to_slots(constraints_package, *args, **kwarg... | 0.624179 | 0.208884 |
from random import *
# Generates exact cover instance for target length n with t subsets
# Returns (s, w) where s is a t-length list of subsets and w is a l length list of witness indices of s
def generate(n, l, t):
assert t >= n
assert 1 <= l <= n
target = list(range(1,n+1))
witness = []
# Randoml... | witnessencrypt/ecigen.py | from random import *
# Generates exact cover instance for target length n with t subsets
# Returns (s, w) where s is a t-length list of subsets and w is a l length list of witness indices of s
def generate(n, l, t):
assert t >= n
assert 1 <= l <= n
target = list(range(1,n+1))
witness = []
# Randoml... | 0.619011 | 0.394434 |
import logging
import re
from unittest.mock import patch
import pytest
from ebook_homebrew.exceptions import InvalidNumberParameterTypeError, \
TargetSrcFileNotFoundError, ChangeFileNameOSError, InvalidImageParameterTypeError
from ebook_homebrew.rename import ChangeFilename
_logger = logging.getLogger(name=__nam... | tests/ut/test_rename.py | import logging
import re
from unittest.mock import patch
import pytest
from ebook_homebrew.exceptions import InvalidNumberParameterTypeError, \
TargetSrcFileNotFoundError, ChangeFileNameOSError, InvalidImageParameterTypeError
from ebook_homebrew.rename import ChangeFilename
_logger = logging.getLogger(name=__nam... | 0.510008 | 0.476336 |
import datetime
import os
import django.utils.timezone
from django.contrib.auth.models import User
from django.core.validators import RegexValidator
from django.db import models
from django.db.models import Q
from django.urls import reverse
from django.utils.translation import gettext_lazy as _
class Semester(models... | dashboard/models.py | import datetime
import os
import django.utils.timezone
from django.contrib.auth.models import User
from django.core.validators import RegexValidator
from django.db import models
from django.db.models import Q
from django.urls import reverse
from django.utils.translation import gettext_lazy as _
class Semester(models... | 0.235988 | 0.10217 |
import sys
sys.path.append('./py')
from tests.test import *
from tests.random import *
from ga import GA
from multivector import MultiVector
ga = GA(3)
assert ga.n == 3
x = 4 + 3*ga[1] + 4*ga[2] + 5*ga[1,2]
y = 3 + 2*ga[1] + 3*ga[2] + 4*ga[1,2]
z = 10 + 16*ga[1] + 26*ga[2] + 32*ga[1,2]
assert x*y == z
ga2 = GA(2... | test-ga.py |
import sys
sys.path.append('./py')
from tests.test import *
from tests.random import *
from ga import GA
from multivector import MultiVector
ga = GA(3)
assert ga.n == 3
x = 4 + 3*ga[1] + 4*ga[2] + 5*ga[1,2]
y = 3 + 2*ga[1] + 3*ga[2] + 4*ga[1,2]
z = 10 + 16*ga[1] + 26*ga[2] + 32*ga[1,2]
assert x*y == z
ga2 = GA(2... | 0.177312 | 0.511412 |
import weakref
class Message:
def __init__(self, message_id, content, metadata):
self.message_id = message_id
self.content = content
self.metadata = metadata
class MessagingDriver:
def __init__(self):
self._finalizer = weakref.finalize(self, self.close_connection)
def de... | melange/messaging/messaging_driver.py | import weakref
class Message:
def __init__(self, message_id, content, metadata):
self.message_id = message_id
self.content = content
self.metadata = metadata
class MessagingDriver:
def __init__(self):
self._finalizer = weakref.finalize(self, self.close_connection)
def de... | 0.791821 | 0.301285 |
import cv2
import albumentations as A
from typing import Any
from typing import Tuple
from typing import Union
from typing import Optional
from albumentations.pytorch import ToTensorV2
from .general import ToRGB
from .general import ToGray
from .general import BatchWrapper
from .....data import Transforms
from ........ | cflearn/api/cv/data/transforms/A.py | import cv2
import albumentations as A
from typing import Any
from typing import Tuple
from typing import Union
from typing import Optional
from albumentations.pytorch import ToTensorV2
from .general import ToRGB
from .general import ToGray
from .general import BatchWrapper
from .....data import Transforms
from ........ | 0.903796 | 0.216053 |
# debug
import hTools2
reload(hTools2)
if hTools2.DEBUG:
import hTools2.modules.fontutils
reload(hTools2.modules.fontutils)
# imports
from vanilla import *
try:
from mojo.roboFont import AllFonts, CurrentFont, CurrentGlyph
except:
from robofab.world import AllFonts, CurrentFont, CurrentGlyph
from... | Lib/hTools2/dialogs/glyph/switch_glyph.py |
# debug
import hTools2
reload(hTools2)
if hTools2.DEBUG:
import hTools2.modules.fontutils
reload(hTools2.modules.fontutils)
# imports
from vanilla import *
try:
from mojo.roboFont import AllFonts, CurrentFont, CurrentGlyph
except:
from robofab.world import AllFonts, CurrentFont, CurrentGlyph
from... | 0.360602 | 0.078254 |
# Import all packages
import tensorflow as tf
class QmixNet(tf.keras.Model):
def __init__(self, matrix_dims, name='Qmix', **kwargs):
super(QmixNet, self).__init__(name=name, **kwargs)
q_init = tf.zeros_initializer()
self.q_1 = tf.Variable(initial_value=q_init(shape=(matrix_dims[0],), dtype='float32'),... | matrix_game/q_mix.py |
# Import all packages
import tensorflow as tf
class QmixNet(tf.keras.Model):
def __init__(self, matrix_dims, name='Qmix', **kwargs):
super(QmixNet, self).__init__(name=name, **kwargs)
q_init = tf.zeros_initializer()
self.q_1 = tf.Variable(initial_value=q_init(shape=(matrix_dims[0],), dtype='float32'),... | 0.885186 | 0.451387 |
import argparse
import os
import scipy.misc
import numpy as np
from ada_rendering import pose2image
import tensorflow as tf
from pdb import set_trace as st
parser = argparse.ArgumentParser(description='')
parser.add_argument('--dataset_name', dest='dataset_name', default='facades', help='name of the dataset')
parser.... | main.py | import argparse
import os
import scipy.misc
import numpy as np
from ada_rendering import pose2image
import tensorflow as tf
from pdb import set_trace as st
parser = argparse.ArgumentParser(description='')
parser.add_argument('--dataset_name', dest='dataset_name', default='facades', help='name of the dataset')
parser.... | 0.498291 | 0.085327 |
from .common import *
mod = Blueprint('submission', __name__)
class SubmitForm(FlaskForm):
problem_id = IntegerField('Problem ID', [InputRequired('This field is required.')])
language_id = SelectField('Language', [InputRequired('This field is required.')], coerce=int)
code = TextAreaField('Compile Comman... | web/codepass_web/views/submission.py | from .common import *
mod = Blueprint('submission', __name__)
class SubmitForm(FlaskForm):
problem_id = IntegerField('Problem ID', [InputRequired('This field is required.')])
language_id = SelectField('Language', [InputRequired('This field is required.')], coerce=int)
code = TextAreaField('Compile Comman... | 0.322099 | 0.083404 |
import argparse
import datetime
import hashlib
import os
import os.path as osp
import uuid
import torch
import yaml
from torch.optim.lr_scheduler import MultiStepLR
from torch.utils.data import DataLoader
import torchfcn
from cmu_airlab.datasets.dataset_air_lab import AirLabClassSegBase
from torchfcn.models.fcn_util... | train_airlab_data.py |
import argparse
import datetime
import hashlib
import os
import os.path as osp
import uuid
import torch
import yaml
from torch.optim.lr_scheduler import MultiStepLR
from torch.utils.data import DataLoader
import torchfcn
from cmu_airlab.datasets.dataset_air_lab import AirLabClassSegBase
from torchfcn.models.fcn_util... | 0.667906 | 0.225246 |
import os
import time
from mindspore.common import set_seed
from src.dataset import data_to_mindrecord_byte_image
from src.model_utils.config import config
set_seed(1)
rank = 0
device_num = 1
def generate_coco_mindrecord():
""" train_fasterrcnn_ """
# It will generate mindrecord file in config.mindrecord_... | tests/st/fl/cross_silo_faster_rcnn/generate_mindrecord.py | import os
import time
from mindspore.common import set_seed
from src.dataset import data_to_mindrecord_byte_image
from src.model_utils.config import config
set_seed(1)
rank = 0
device_num = 1
def generate_coco_mindrecord():
""" train_fasterrcnn_ """
# It will generate mindrecord file in config.mindrecord_... | 0.181263 | 0.117699 |
import cv2
import glob
import keras
import numpy as np
import pandas as pd
from keras import backend as K
from keras.layers import MaxPooling2D, Conv2D, Flatten, Dense, Input, AlphaDropout, Dropout
from keras.models import Model
from settings import IMAGE_SIZE
df = pd.read_pickle('../data/all_obs.pkl', compression='g... | process/3_train_nn.py | import cv2
import glob
import keras
import numpy as np
import pandas as pd
from keras import backend as K
from keras.layers import MaxPooling2D, Conv2D, Flatten, Dense, Input, AlphaDropout, Dropout
from keras.models import Model
from settings import IMAGE_SIZE
df = pd.read_pickle('../data/all_obs.pkl', compression='g... | 0.747524 | 0.443359 |
import json
from invenio_indexer.api import RecordIndexer
from invenio_pidstore.models import PersistentIdentifier
from oarepo_records_draft import current_drafts
from sample.config import SAMPLE_DRAFT_PID_TYPE
from sample.record import SampleDraftRecord
def test_search_records(app, db, client, community):
ass... | tests/test_search.py | import json
from invenio_indexer.api import RecordIndexer
from invenio_pidstore.models import PersistentIdentifier
from oarepo_records_draft import current_drafts
from sample.config import SAMPLE_DRAFT_PID_TYPE
from sample.record import SampleDraftRecord
def test_search_records(app, db, client, community):
ass... | 0.389663 | 0.266047 |
import os
import numpy as np
import torch
import shutil
import torchvision.transforms as transforms
from torch.autograd import Variable
class AvgrageMeter(object):
def __init__(self):
self.reset()
def reset(self):
self.avg = 0
self.sum = 0
self.cnt = 0
def update(self, val, n=1):
self.sum... | autoPyTorch/components/networks/image/darts/utils.py | import os
import numpy as np
import torch
import shutil
import torchvision.transforms as transforms
from torch.autograd import Variable
class AvgrageMeter(object):
def __init__(self):
self.reset()
def reset(self):
self.avg = 0
self.sum = 0
self.cnt = 0
def update(self, val, n=1):
self.sum... | 0.615319 | 0.421076 |
import argparse
import math
import progressbar
import time
import h5py
import numpy as np
DSET_NAME = 'dset'
def _calc_batches(count, batch_size):
return int(math.ceil(count / float(batch_size)))
def write(filename, batched=False, batch_size=32):
data_count = 10000
data_shape = (3, 256, 256)
data... | main.py |
import argparse
import math
import progressbar
import time
import h5py
import numpy as np
DSET_NAME = 'dset'
def _calc_batches(count, batch_size):
return int(math.ceil(count / float(batch_size)))
def write(filename, batched=False, batch_size=32):
data_count = 10000
data_shape = (3, 256, 256)
data... | 0.424651 | 0.225513 |
import json
import os
from pathlib import Path
import numpy as np
import torch
from logzero import logger
from showcase import constants
_root_dir = os.path.expanduser('~/.config/showcase')
def get_dataset_root(create_directory=True):
if create_directory:
try:
os.makedirs(_root_dir, exist_o... | showcase/utils/subfuncs.py | import json
import os
from pathlib import Path
import numpy as np
import torch
from logzero import logger
from showcase import constants
_root_dir = os.path.expanduser('~/.config/showcase')
def get_dataset_root(create_directory=True):
if create_directory:
try:
os.makedirs(_root_dir, exist_o... | 0.29747 | 0.145449 |
from nonebot import (
CommandSession, IntentCommand, NLPSession, on_command, on_natural_language,
permission
)
from coolqbot import bot
@on_command(
'whoami', aliases={'我是谁'}, permission=permission.GROUP, only_to_me=False
)
async def whoami(session: CommandSession):
msg = await session.bot.get_group_... | plugins_bak/basic.py | from nonebot import (
CommandSession, IntentCommand, NLPSession, on_command, on_natural_language,
permission
)
from coolqbot import bot
@on_command(
'whoami', aliases={'我是谁'}, permission=permission.GROUP, only_to_me=False
)
async def whoami(session: CommandSession):
msg = await session.bot.get_group_... | 0.246806 | 0.066266 |
from prim import Parser, syntax_tree, fmap, lift, mzero
from operator import and_, or_
from state import (
isParseError,
isParseSuccess,
parseSuccessTree,
setParseSuccessTree,
mergeErrorsMany,
inputConsumed
)
def _sequence(*parsers):
'''same as 'sequence', but less efficient (due to ... | parsefunc/combinators.py |
from prim import Parser, syntax_tree, fmap, lift, mzero
from operator import and_, or_
from state import (
isParseError,
isParseSuccess,
parseSuccessTree,
setParseSuccessTree,
mergeErrorsMany,
inputConsumed
)
def _sequence(*parsers):
'''same as 'sequence', but less efficient (due to ... | 0.414188 | 0.449332 |
import discord
from discord.ext import commands
from utils import MyContext
async def can_mute(ctx: MyContext) -> bool:
"""Check if someone can mute"""
if ctx.bot.database_online:
return await ctx.bot.get_cog("Servers").staff_finder(ctx.author, "mute")
else:
return ctx.channel.permissions_... | fcts/checks.py | import discord
from discord.ext import commands
from utils import MyContext
async def can_mute(ctx: MyContext) -> bool:
"""Check if someone can mute"""
if ctx.bot.database_online:
return await ctx.bot.get_cog("Servers").staff_finder(ctx.author, "mute")
else:
return ctx.channel.permissions_... | 0.463201 | 0.168686 |
import sys
import chardet
import argparse
from pyflowchart.flowchart import Flowchart
def detect_decode(file_content: bytes) -> str:
"""detect_decode detect the encoding of file_content,
then decode file_content on the detected encoding.
If the confidence of detect result is less then 0.9,
the UTF-... | pyflowchart/__main__.py | import sys
import chardet
import argparse
from pyflowchart.flowchart import Flowchart
def detect_decode(file_content: bytes) -> str:
"""detect_decode detect the encoding of file_content,
then decode file_content on the detected encoding.
If the confidence of detect result is less then 0.9,
the UTF-... | 0.441673 | 0.254787 |
import json
from datetime import date, datetime
import sqlalchemy.types as types
from dbbase import DB
db = DB(config=":memory:")
status_codes = [
[0, "New"],
[1, "Active"],
[2, "Suspended"],
[3, "Inactive"],
]
class StatusCodes(types.TypeDecorator):
"""
Status codes are entered as strings ... | examples/table_documentation.py | import json
from datetime import date, datetime
import sqlalchemy.types as types
from dbbase import DB
db = DB(config=":memory:")
status_codes = [
[0, "New"],
[1, "Active"],
[2, "Suspended"],
[3, "Inactive"],
]
class StatusCodes(types.TypeDecorator):
"""
Status codes are entered as strings ... | 0.652574 | 0.275978 |
import argparse
import os
import pathlib
import subprocess
def error(msg):
print(msg)
exit(1)
def is_windows():
if os.name == 'nt':
return True
else:
return False
def get_shader_list(project_path, asset_platform, shader_type, shader_platform, shadergen_path):
"""
Gets the sha... | scripts/bundler/get_shader_list.py | import argparse
import os
import pathlib
import subprocess
def error(msg):
print(msg)
exit(1)
def is_windows():
if os.name == 'nt':
return True
else:
return False
def get_shader_list(project_path, asset_platform, shader_type, shader_platform, shadergen_path):
"""
Gets the sha... | 0.321993 | 0.071429 |
import logging
from getpass import getpass
from argparse import ArgumentParser
from configparser import SafeConfigParser
import concurrent.futures
import os
import uuid
import datetime
import asyncio
from urllib.parse import urljoin
import slixmpp
import pyinotify
class EventHandler(pyinotify.ProcessEvent):
def ... | imgnotifybot.py |
import logging
from getpass import getpass
from argparse import ArgumentParser
from configparser import SafeConfigParser
import concurrent.futures
import os
import uuid
import datetime
import asyncio
from urllib.parse import urljoin
import slixmpp
import pyinotify
class EventHandler(pyinotify.ProcessEvent):
def ... | 0.50293 | 0.066327 |
def axisymmetric_file(geometry_type, geometry_parameters, Nrank, wavelength,
index, index_m, kb=None, conducting=False, Nparam=1,
use_ds=True, complex_plane=True, eps_z_re_im=0.95, Nint=200):
"""Create input file for axisymmetric particles
Arguments:
geometry_type (int) choos... | miepy/tmatrix/axisymmetric_file.py | def axisymmetric_file(geometry_type, geometry_parameters, Nrank, wavelength,
index, index_m, kb=None, conducting=False, Nparam=1,
use_ds=True, complex_plane=True, eps_z_re_im=0.95, Nint=200):
"""Create input file for axisymmetric particles
Arguments:
geometry_type (int) choos... | 0.809351 | 0.596609 |
import argparse
import datetime
import json
import os
import pdfminer.high_level
import sys
import wget
import sys
def query_yes_no(question, default="yes"):
valid = {"yes": True, "y": True, "ye": True,
"no": False, "n": False}
if default is None:
prompt = " [y/n] "
elif default == "... | mkparser.py | import argparse
import datetime
import json
import os
import pdfminer.high_level
import sys
import wget
import sys
def query_yes_no(question, default="yes"):
valid = {"yes": True, "y": True, "ye": True,
"no": False, "n": False}
if default is None:
prompt = " [y/n] "
elif default == "... | 0.244814 | 0.091423 |
import time
import sched
import threading
from synapse.config import config
from synapse.logger import logger
@logger
class SynSched(threading.Thread):
def __init__(self):
self.logger.debug("Initializing the scheduler...")
threading.Thread.__init__(self, name="SCHEDULER")
# Start the sc... | synapse/scheduler.py | import time
import sched
import threading
from synapse.config import config
from synapse.logger import logger
@logger
class SynSched(threading.Thread):
def __init__(self):
self.logger.debug("Initializing the scheduler...")
threading.Thread.__init__(self, name="SCHEDULER")
# Start the sc... | 0.447702 | 0.075927 |
from typing import Dict, Callable, Union
import random
from ..calc.combat_data import AttackData
from ..calc import stats
def _(_: AttackData) -> None:
pass
def fe7_silencer(atk: AttackData) -> None:
"""
With a crit/2% chance to activate, deals damage equal to the opponent's remaining HP.
Prevents o... | FEArena/feaapi/api/skills/before_attack.py | from typing import Dict, Callable, Union
import random
from ..calc.combat_data import AttackData
from ..calc import stats
def _(_: AttackData) -> None:
pass
def fe7_silencer(atk: AttackData) -> None:
"""
With a crit/2% chance to activate, deals damage equal to the opponent's remaining HP.
Prevents o... | 0.67405 | 0.4436 |
import pandas as pd
import numpy as np
import tensorflow as tf
class SlidingWindow(tf.keras.utils.Sequence):
def __init__(
self,
df: pd.DataFrame,
window_size: int,
target_features: list[str],
feature_names: list[str] = None,
horizon_size: int = 1,
jump: in... | windpower/utils/tabularize.py | import pandas as pd
import numpy as np
import tensorflow as tf
class SlidingWindow(tf.keras.utils.Sequence):
def __init__(
self,
df: pd.DataFrame,
window_size: int,
target_features: list[str],
feature_names: list[str] = None,
horizon_size: int = 1,
jump: in... | 0.778776 | 0.400955 |
# XKCD password generator
import argparse
import collections
import os.path
import random
# Parse the command line options.
parser = argparse.ArgumentParser(description="XKCD password generator https://xkcd.com/936/")
parser.add_argument("-d", "--dictionary", default="en", help="Dictionary to use")
parser.add_argume... | network/xkcd/xkcd.py |
# XKCD password generator
import argparse
import collections
import os.path
import random
# Parse the command line options.
parser = argparse.ArgumentParser(description="XKCD password generator https://xkcd.com/936/")
parser.add_argument("-d", "--dictionary", default="en", help="Dictionary to use")
parser.add_argume... | 0.502686 | 0.064359 |
import numpy as np
class Distance_metrics:
"""
Calculate distance between each corresponding points
of two arrays using different distance metrics
"""
def Eucledian_Distance(X1,X2):
""""
Returns the list of eucledian distance
between two corresponding points of
two ... | MLlib/distance_metrics.py | import numpy as np
class Distance_metrics:
"""
Calculate distance between each corresponding points
of two arrays using different distance metrics
"""
def Eucledian_Distance(X1,X2):
""""
Returns the list of eucledian distance
between two corresponding points of
two ... | 0.805173 | 0.837487 |
b_w = 'QPushButton{border-top-left-radius: 10px;border-top-right-radius: 10px;border-bottom-right-radius: ' \
'10px;border-bottom-left-radius: 10px;background-color: rgb(234, 234, 234);}' \
'QPushButton:pressed {background-color: rgb(188, 188, 188);}' \
'QPushButton {text-align: left;}'
b_g = 'QPushB... | SAMG/COL.py | b_w = 'QPushButton{border-top-left-radius: 10px;border-top-right-radius: 10px;border-bottom-right-radius: ' \
'10px;border-bottom-left-radius: 10px;background-color: rgb(234, 234, 234);}' \
'QPushButton:pressed {background-color: rgb(188, 188, 188);}' \
'QPushButton {text-align: left;}'
b_g = 'QPushB... | 0.742235 | 0.268384 |
import os
from PySide2 import QtWidgets, QtCore, QtGui
from propsettings_qt.ui_settings_area import SettingsAreaWidget
from pyrulo import class_imports
class ConfigurableSelector(QtWidgets.QWidget):
"""
Widget para cargar clases que hereden de una clase base especificada
e inicializar un combobox con inst... | pyrulo_qt/ui_configurable_selector.py | import os
from PySide2 import QtWidgets, QtCore, QtGui
from propsettings_qt.ui_settings_area import SettingsAreaWidget
from pyrulo import class_imports
class ConfigurableSelector(QtWidgets.QWidget):
"""
Widget para cargar clases que hereden de una clase base especificada
e inicializar un combobox con inst... | 0.519765 | 0.061087 |
import datetime
from typing import List, Dict
from lxml import etree as ET
import os
import numpy as np
from collections import OrderedDict
from miso.training.parameters import MisoParameters
class ModelInfo:
def __init__(self,
name: str,
description: str,
type:... | miso/deploy/model_info.py | import datetime
from typing import List, Dict
from lxml import etree as ET
import os
import numpy as np
from collections import OrderedDict
from miso.training.parameters import MisoParameters
class ModelInfo:
def __init__(self,
name: str,
description: str,
type:... | 0.734501 | 0.233029 |
from uuid import uuid4
import pytest
from common.test.acceptance.fixtures.course import CourseFixture # lint-amnesty, pylint: disable=unused-import
from common.test.acceptance.fixtures.discussion import (
Comment,
Response,
SingleThreadViewFixture,
Thread,
)
from common.test.acceptance.pages.common.... | Part-03-Understanding-Software-Crafting-Your-Own-Tools/models/edx-platform/common/test/acceptance/tests/discussion/test_discussion.py | from uuid import uuid4
import pytest
from common.test.acceptance.fixtures.course import CourseFixture # lint-amnesty, pylint: disable=unused-import
from common.test.acceptance.fixtures.discussion import (
Comment,
Response,
SingleThreadViewFixture,
Thread,
)
from common.test.acceptance.pages.common.... | 0.345768 | 0.427875 |
import numpy as np
def integerized(sequence):
key_dict = sorted(set(sequence))
int_seq = []
for char in sequence:
to_int = key_dict.index(char)
int_seq.append(to_int)
return int_seq
def preprocess(sequences, ignoreLower=True):
upper_seq = []
len_record = []
for ... | utils/mismatchtree.py |
import numpy as np
def integerized(sequence):
key_dict = sorted(set(sequence))
int_seq = []
for char in sequence:
to_int = key_dict.index(char)
int_seq.append(to_int)
return int_seq
def preprocess(sequences, ignoreLower=True):
upper_seq = []
len_record = []
for ... | 0.432782 | 0.521227 |
import os
import cv2
import torch
import argparse
import numpy as np
from PIL import Image
from torchvision import transforms
from config import get_config
from Learner import face_learner
from data.data_pipe import get_val_pair
from mtcnn_pytorch.crop_and_aligned import mctnn_crop_face
def initialize_learner(conf,... | plot_qualitative_results_given_2_imgs.py | import os
import cv2
import torch
import argparse
import numpy as np
from PIL import Image
from torchvision import transforms
from config import get_config
from Learner import face_learner
from data.data_pipe import get_val_pair
from mtcnn_pytorch.crop_and_aligned import mctnn_crop_face
def initialize_learner(conf,... | 0.661267 | 0.397061 |
import random
print("This simulates f-pairs, L2-L3.")
f_his = []
f = 178
perturbation_pos_f = random.sample(range(6, f), round(f * 0.05))
perturbation_pos_f = sorted(perturbation_pos_f)
print(perturbation_pos_f)
def calculate_strategy_f(memoryA, memoryB):
t1 = [0,0,0]
t2 = [0,0,0]
for i in range(len(... | testpayoff.py |
import random
print("This simulates f-pairs, L2-L3.")
f_his = []
f = 178
perturbation_pos_f = random.sample(range(6, f), round(f * 0.05))
perturbation_pos_f = sorted(perturbation_pos_f)
print(perturbation_pos_f)
def calculate_strategy_f(memoryA, memoryB):
t1 = [0,0,0]
t2 = [0,0,0]
for i in range(len(... | 0.173288 | 0.515986 |
from collections import defaultdict
rules = defaultdict(list)
rev_rules = defaultdict(list)
with open('input') as f:
rep_text = f.read().splitlines(keepends=False)
calibration_molecule = rep_text[-1]
rep_text = rep_text[:-1]
for line in rep_text:
if len(line.strip()) > 0:
k, v = line.split(' => ')
... | 2015/19/rednose_reactor.py | from collections import defaultdict
rules = defaultdict(list)
rev_rules = defaultdict(list)
with open('input') as f:
rep_text = f.read().splitlines(keepends=False)
calibration_molecule = rep_text[-1]
rep_text = rep_text[:-1]
for line in rep_text:
if len(line.strip()) > 0:
k, v = line.split(' => ')
... | 0.252845 | 0.140661 |
from airflow.models.baseoperator import BaseOperator
from airflow.hooks.postgres_hook import PostgresHook
from airflow.utils.decorators import apply_defaults
from airflow.contrib.hooks.aws_hook import AwsHook
class StageTablesOperator(BaseOperator):
"""
@description:
This operator copies data f... | airflow/plugins/operators/StagTablesOperator.py | from airflow.models.baseoperator import BaseOperator
from airflow.hooks.postgres_hook import PostgresHook
from airflow.utils.decorators import apply_defaults
from airflow.contrib.hooks.aws_hook import AwsHook
class StageTablesOperator(BaseOperator):
"""
@description:
This operator copies data f... | 0.764892 | 0.202246 |
import inspect
import logging
import os
import requests
from requests import HTTPError
from requests.adapters import HTTPAdapter
from urllib3 import Retry
DEFAULT_TIMEOUT = 60 # seconds
class TimeoutHTTPAdapter(HTTPAdapter):
def __init__(self, *args, **kwargs):
self.timeout = DEFAULT_TIMEOUT
if... | library/util.py | import inspect
import logging
import os
import requests
from requests import HTTPError
from requests.adapters import HTTPAdapter
from urllib3 import Retry
DEFAULT_TIMEOUT = 60 # seconds
class TimeoutHTTPAdapter(HTTPAdapter):
def __init__(self, *args, **kwargs):
self.timeout = DEFAULT_TIMEOUT
if... | 0.403449 | 0.050941 |
import numpy as np
BATCHSIZE = 1000
class Evaluator(object):
def __init__(self, metric, nbest=None, filtered=False, whole_graph=None):
assert metric in ['mrr', 'hits', 'all'], 'Invalid metric: {}'.format(metric)
if metric == 'hits':
assert nbest, 'Please indicate n-best in using hits... | src/processors/evaluator.py | import numpy as np
BATCHSIZE = 1000
class Evaluator(object):
def __init__(self, metric, nbest=None, filtered=False, whole_graph=None):
assert metric in ['mrr', 'hits', 'all'], 'Invalid metric: {}'.format(metric)
if metric == 'hits':
assert nbest, 'Please indicate n-best in using hits... | 0.479991 | 0.52476 |
import logging
from ignition.service.framework import ServiceRegistration
from ignition.boot.config import BootProperties
from ignition.boot.configurators.utils import validate_no_service_with_capability_exists
from ignition.service.messaging import MessagingProperties, InboxCapability, DeliveryCapability, PostalCapabi... | ignition/boot/configurators/messaging.py | import logging
from ignition.service.framework import ServiceRegistration
from ignition.boot.config import BootProperties
from ignition.boot.configurators.utils import validate_no_service_with_capability_exists
from ignition.service.messaging import MessagingProperties, InboxCapability, DeliveryCapability, PostalCapabi... | 0.428473 | 0.051415 |
from morepath.request import Response
from onegov.core.security import Public
from onegov.election_day import _
from onegov.election_day import ElectionDayApp
from onegov.election_day.collections import EmailSubscriberCollection
from onegov.election_day.collections import SmsSubscriberCollection
from onegov.election_da... | src/onegov/election_day/views/subscription.py | from morepath.request import Response
from onegov.core.security import Public
from onegov.election_day import _
from onegov.election_day import ElectionDayApp
from onegov.election_day.collections import EmailSubscriberCollection
from onegov.election_day.collections import SmsSubscriberCollection
from onegov.election_da... | 0.656328 | 0.111 |
import PyIgnition, pygame, sys, math, random
pygame.font.init()
screen = pygame.display.set_mode((800, 600))
pygame.display.set_caption("PyIgnition 'Controlled Eruption' demo")
clock = pygame.time.Clock()
curframe = 0
started = False
# 'Press space to start' text
starttextfont = pygame.font.Font("cour... | display_dominik/Controlled Eruption.py |
import PyIgnition, pygame, sys, math, random
pygame.font.init()
screen = pygame.display.set_mode((800, 600))
pygame.display.set_caption("PyIgnition 'Controlled Eruption' demo")
clock = pygame.time.Clock()
curframe = 0
started = False
# 'Press space to start' text
starttextfont = pygame.font.Font("cour... | 0.178669 | 0.208612 |
import random
from environment.selfplay import SelfPlay
from environment.mazebase_wrapper import MazebaseWrapper
from environment.observation import ObservationTuple, Observation
from utils.constant import *
from copy import deepcopy
import numpy as np
class SelfPlayTarget(SelfPlay):
"""
Wrapper class over se... | SelfPlay/environment/selfplay_target.py | import random
from environment.selfplay import SelfPlay
from environment.mazebase_wrapper import MazebaseWrapper
from environment.observation import ObservationTuple, Observation
from utils.constant import *
from copy import deepcopy
import numpy as np
class SelfPlayTarget(SelfPlay):
"""
Wrapper class over se... | 0.567937 | 0.186428 |
import botCore
import parserCore
from aiogram import utils
from modules import adblocker, database, rating
async def send_post(message):
if adblocker.post_contains_ad(message):
for user in database.User.select() \
.where(database.User.observing_channels.contains(str(message.se... | modules/messages.py | import botCore
import parserCore
from aiogram import utils
from modules import adblocker, database, rating
async def send_post(message):
if adblocker.post_contains_ad(message):
for user in database.User.select() \
.where(database.User.observing_channels.contains(str(message.se... | 0.115224 | 0.038683 |
from module import *
from models import *
from flask import request, session
class Viper(object):
def __init__(self, vphone="", vname="", vrank="0", vid=""):
self.phone = vphone
self.name = vname
self.rank = vrank
self.vid = vid
def addVip(self):
if self.name == "" or ... | classes/vip.py | from module import *
from models import *
from flask import request, session
class Viper(object):
def __init__(self, vphone="", vname="", vrank="0", vid=""):
self.phone = vphone
self.name = vname
self.rank = vrank
self.vid = vid
def addVip(self):
if self.name == "" or ... | 0.355887 | 0.091788 |
def binary_search_base(nums: list, target: int) -> int:
"""
Time complexi O(logn)
The basic binary search
nums is a sorted list
if multi targets in nums, return one target index
else return -1
"""
if not nums:
return -1
left, right = 0, len(nums) - 1
while left < right:
... | search and sort/binary_search.py | def binary_search_base(nums: list, target: int) -> int:
"""
Time complexi O(logn)
The basic binary search
nums is a sorted list
if multi targets in nums, return one target index
else return -1
"""
if not nums:
return -1
left, right = 0, len(nums) - 1
while left < right:
... | 0.703448 | 0.722796 |
import os
import random
from string import ascii_uppercase, digits
from Bio import Seq, SeqUtils, SeqIO, SeqRecord
from Bio.Alphabet import IUPAC
from Bio.Blast import NCBIWWW, NCBIXML
from matplotlib import pylab
__author__ = '<NAME>'
__license__ = "MIT"
__version__ = "1.0"
__status__ = "Production"
class Sequence... | Sequence.py | import os
import random
from string import ascii_uppercase, digits
from Bio import Seq, SeqUtils, SeqIO, SeqRecord
from Bio.Alphabet import IUPAC
from Bio.Blast import NCBIWWW, NCBIXML
from matplotlib import pylab
__author__ = '<NAME>'
__license__ = "MIT"
__version__ = "1.0"
__status__ = "Production"
class Sequence... | 0.585931 | 0.25247 |
import kivy
from kivy.app import App
from kivy.config import Config
kivy.require("1.10.0")
Config.read("mitc.ini")
from kivy.core.window import Window
from kivy.uix.textinput import TextInput
from kivy.uix.button import Button
from kivy.uix.stacklayout import StackLayout
INPUT_REFERENCE = 0
class Input(TextInput):
... | src/MitC.py | import kivy
from kivy.app import App
from kivy.config import Config
kivy.require("1.10.0")
Config.read("mitc.ini")
from kivy.core.window import Window
from kivy.uix.textinput import TextInput
from kivy.uix.button import Button
from kivy.uix.stacklayout import StackLayout
INPUT_REFERENCE = 0
class Input(TextInput):
... | 0.411347 | 0.1692 |
import numpy as np
import torch
import torch.nn as nn
from gnn_cnn_model.modules import *
class MultiHeadAttention(nn.Module):
def __init__(self, n_head, d_model, d_k, d_v, dropout=0.1):
super(MultiHeadAttention, self).__init__()
self.n_head = n_head
self.d_k = d_k
self.d_v = d_v
... | gnn_cnn_model/sublayers.py | import numpy as np
import torch
import torch.nn as nn
from gnn_cnn_model.modules import *
class MultiHeadAttention(nn.Module):
def __init__(self, n_head, d_model, d_k, d_v, dropout=0.1):
super(MultiHeadAttention, self).__init__()
self.n_head = n_head
self.d_k = d_k
self.d_v = d_v
... | 0.941196 | 0.328375 |
import struct
import re
import zipfile
import os
import logging
from io import BytesIO
from collections import OrderedDict
from urllib.parse import urlparse
import requests
from ckan.lib import uploader, formatters
log = logging.getLogger(__name__)
ALLOWED_FMTS = ('zip', 'application/zip', 'application/x-zip-compre... | ckanext/zippreview/utils.py | import struct
import re
import zipfile
import os
import logging
from io import BytesIO
from collections import OrderedDict
from urllib.parse import urlparse
import requests
from ckan.lib import uploader, formatters
log = logging.getLogger(__name__)
ALLOWED_FMTS = ('zip', 'application/zip', 'application/x-zip-compre... | 0.302082 | 0.101947 |
"""---------------- Importing libraries ----------------
"""
# System tools
import sys
import os
sys.path.append(os.path.join(".."))
# Import pandas for working with dataframes
import pandas as pd
# Neural networks with numpy
import numpy as np
from utils.neuralnetwork import NeuralNetwork
# Machine learning tools... | src/Neural_Network.py | """---------------- Importing libraries ----------------
"""
# System tools
import sys
import os
sys.path.append(os.path.join(".."))
# Import pandas for working with dataframes
import pandas as pd
# Neural networks with numpy
import numpy as np
from utils.neuralnetwork import NeuralNetwork
# Machine learning tools... | 0.508544 | 0.637285 |
import secrets
import time
import asyncio
from typing import (
Any,
cast,
Dict,
List,
)
from eth_utils import encode_hex
from hp2p.constants import PEER_STAKE_GONE_STALE_TIME_PERIOD
from hvm.exceptions import (
CanonicalHeadNotFound,
)
from hp2p.exceptions import HandshakeFailure
from hp2p.p2p_... | helios/protocol/hls/peer.py | import secrets
import time
import asyncio
from typing import (
Any,
cast,
Dict,
List,
)
from eth_utils import encode_hex
from hp2p.constants import PEER_STAKE_GONE_STALE_TIME_PERIOD
from hvm.exceptions import (
CanonicalHeadNotFound,
)
from hp2p.exceptions import HandshakeFailure
from hp2p.p2p_... | 0.603348 | 0.136983 |
import py
from rpython.flowspace.argument import (ArgumentsForTranslation, rawshape,
Signature)
class TestSignature(object):
def test_helpers(self):
sig = Signature(["a", "b", "c"], None, None)
assert sig.num_argnames() == 3
assert not sig.has_vararg()
assert not sig.has_kwarg(... | rpython/flowspace/test/test_argument.py | import py
from rpython.flowspace.argument import (ArgumentsForTranslation, rawshape,
Signature)
class TestSignature(object):
def test_helpers(self):
sig = Signature(["a", "b", "c"], None, None)
assert sig.num_argnames() == 3
assert not sig.has_vararg()
assert not sig.has_kwarg(... | 0.5083 | 0.522202 |
import datetime
import nose.tools
from nose.tools import with_setup
from billy.models import db
def setup_func():
assert db.name.endswith('_test')
db.metadata.drop()
db.bills.drop()
db.votes.drop()
db.legislators.drop()
db.document_ids.drop()
db.vote_ids.drop()
db.committees.drop()
... | billy/tests/models/legislator_test_context_role.py | import datetime
import nose.tools
from nose.tools import with_setup
from billy.models import db
def setup_func():
assert db.name.endswith('_test')
db.metadata.drop()
db.bills.drop()
db.votes.drop()
db.legislators.drop()
db.document_ids.drop()
db.vote_ids.drop()
db.committees.drop()
... | 0.46563 | 0.260125 |
from setuptools import setup
import os
import seam_erasure
here = os.path.abspath(os.path.dirname(__file__))
# Get the long description from the README file
with open(os.path.join(here, 'README.md'), encoding='utf-8') as f:
long_description = f.read()
long_description = long_description.replace(
"static/img/... | setup.py |
from setuptools import setup
import os
import seam_erasure
here = os.path.abspath(os.path.dirname(__file__))
# Get the long description from the README file
with open(os.path.join(here, 'README.md'), encoding='utf-8') as f:
long_description = f.read()
long_description = long_description.replace(
"static/img/... | 0.444806 | 0.200127 |
import sys
import os
import argparse
import src.common as commonutils
"""
PyDashing CLI Parser.
---------------------
"""
class PyDashingCli(object):
"""
PyDashing CLI Parser.
"""
def __init__(self):
"""
Initialize PyDashing CLI.
"""
# Check for atleast one argument
... | testdash/src/pydashing_cli.py |
import sys
import os
import argparse
import src.common as commonutils
"""
PyDashing CLI Parser.
---------------------
"""
class PyDashingCli(object):
"""
PyDashing CLI Parser.
"""
def __init__(self):
"""
Initialize PyDashing CLI.
"""
# Check for atleast one argument
... | 0.376509 | 0.197561 |
"Entities relating to the datamap."
from enum import Enum, auto
from pathlib import Path
# pylint: disable=R0903,R0913;
from typing import IO, Dict, Optional, Union
from engine.exceptions import DatamapNotCSVException
class DatamapLineValueType(Enum):
"""A representation of a data type for us in validating data... | engine/domain/datamap.py | "Entities relating to the datamap."
from enum import Enum, auto
from pathlib import Path
# pylint: disable=R0903,R0913;
from typing import IO, Dict, Optional, Union
from engine.exceptions import DatamapNotCSVException
class DatamapLineValueType(Enum):
"""A representation of a data type for us in validating data... | 0.89706 | 0.508117 |
from collections import OrderedDict
import numpy as np
from astropy.modeling import models
from astropy.modeling.core import Model
from astropy.utils.misc import isiterable
from asdf.tags.core.ndarray import NDArrayType
from asdf_astropy.converters.transform.core import TransformConverterBase
__all__ = ['LabelMappe... | gwcs/converters/selector.py |
from collections import OrderedDict
import numpy as np
from astropy.modeling import models
from astropy.modeling.core import Model
from astropy.utils.misc import isiterable
from asdf.tags.core.ndarray import NDArrayType
from asdf_astropy.converters.transform.core import TransformConverterBase
__all__ = ['LabelMappe... | 0.699357 | 0.437643 |
import cv2 as cv
import mediapipe as mp
import time
mpDraw = mp.solutions.drawing_utils
mpFaceDetection = mp.solutions.face_detection
faceDetection = mpFaceDetection.FaceDetection(0.30)
pTime = 0
cap = cv.VideoCapture('Videos/mkbhd.mp4')
def Rescale(frame, scale=0.50):
# FOR PICTURES,VIDEO,LIVE JUST T0 MAKE IT F... | videofacedetect.py | import cv2 as cv
import mediapipe as mp
import time
mpDraw = mp.solutions.drawing_utils
mpFaceDetection = mp.solutions.face_detection
faceDetection = mpFaceDetection.FaceDetection(0.30)
pTime = 0
cap = cv.VideoCapture('Videos/mkbhd.mp4')
def Rescale(frame, scale=0.50):
# FOR PICTURES,VIDEO,LIVE JUST T0 MAKE IT F... | 0.404978 | 0.322846 |
from django.core.management.base import BaseCommand
from cantusdata.models.folio import Folio
from cantusdata.models.manuscript import Manuscript
from django.core.management import call_command
from optparse import make_option
import csv
class Command(BaseCommand):
"""
Import a folio mapping (CSV file)
Sa... | public/cantusdata/management/commands/import_folio_mapping.py | from django.core.management.base import BaseCommand
from cantusdata.models.folio import Folio
from cantusdata.models.manuscript import Manuscript
from django.core.management import call_command
from optparse import make_option
import csv
class Command(BaseCommand):
"""
Import a folio mapping (CSV file)
Sa... | 0.402744 | 0.184143 |
adjList=[
[26, 1],
[28, 0],
[29, 3],
[43, 2],
[31, 5],
[69, 6, 4],
[70, 5],
[97, 8],
[45, 9, 7],
[46, 8],
[58, 11],
[36, 10],
[37, 13],
[39, 14, 12],
[61, 15, 13],
[41, 14],
[71],
[47, 18],
[48, 17],
[20],
[50, 21, 19],
[20],
[... | graph_datasets/mazes/pmaze9.py |
adjList=[
[26, 1],
[28, 0],
[29, 3],
[43, 2],
[31, 5],
[69, 6, 4],
[70, 5],
[97, 8],
[45, 9, 7],
[46, 8],
[58, 11],
[36, 10],
[37, 13],
[39, 14, 12],
[61, 15, 13],
[41, 14],
[71],
[47, 18],
[48, 17],
[20],
[50, 21, 19],
[20],
[... | 0.202404 | 0.651819 |
from collections import namedtuple
from random import choice
from string import ascii_letters
import pytest
from azure_databricks_api.exceptions import ResourceAlreadyExists, IoError, ResourceDoesNotExist, InvalidParameterValue
from tests.utils import create_client
client = create_client()
DBFS_TEMP_DIR = '/tmp'
SM... | tests/test_dbfs.py | from collections import namedtuple
from random import choice
from string import ascii_letters
import pytest
from azure_databricks_api.exceptions import ResourceAlreadyExists, IoError, ResourceDoesNotExist, InvalidParameterValue
from tests.utils import create_client
client = create_client()
DBFS_TEMP_DIR = '/tmp'
SM... | 0.391871 | 0.21794 |
from unittest import TestCase
import numpy as np
import dnn_misc
import numpy.testing as test
class TestRelu(TestCase):
def test_forward(self):
# check_relu.forward
np.random.seed(123)
# example data
X = np.random.normal(0, 1, (5, 3))
check_relu = dnn_misc.relu()
ha... | test_relu.py | from unittest import TestCase
import numpy as np
import dnn_misc
import numpy.testing as test
class TestRelu(TestCase):
def test_forward(self):
# check_relu.forward
np.random.seed(123)
# example data
X = np.random.normal(0, 1, (5, 3))
check_relu = dnn_misc.relu()
ha... | 0.345105 | 0.553143 |