code stringlengths 2k 1.04M | repo_path stringlengths 5 517 | parsed_code stringlengths 0 1.04M | quality_prob float64 0.02 0.95 | learning_prob float64 0.02 0.93 |
|---|---|---|---|---|
import numpy as np
from .classes.block import Block
from .classes.mesh import Mesh
def generate_block(origin, size, n_cells):
origin_x = origin[0]
origin_y = origin[1]
origin_z = origin[2]
size_x = size[0]
size_y = size[1]
size_z = size[2]
block_points = [
[origin_x, origin_y,... | src/blockmeshdict_generator/generation.py | import numpy as np
from .classes.block import Block
from .classes.mesh import Mesh
def generate_block(origin, size, n_cells):
origin_x = origin[0]
origin_y = origin[1]
origin_z = origin[2]
size_x = size[0]
size_y = size[1]
size_z = size[2]
block_points = [
[origin_x, origin_y,... | 0.244814 | 0.473109 |
import numpy as np
import pandas as pd
from collections import Counter
import re, regex, os
from carnatic import cparser
#np.random.seed(42)
def _get_bigrams(notations_file):
notes = cparser._get_notes_from_file(notations_file)
n = 2
ngrams = zip(*[notes[i:] for i in range(n)])
bigrams = [" ".... | carnatic/cmarkov.py | import numpy as np
import pandas as pd
from collections import Counter
import re, regex, os
from carnatic import cparser
#np.random.seed(42)
def _get_bigrams(notations_file):
notes = cparser._get_notes_from_file(notations_file)
n = 2
ngrams = zip(*[notes[i:] for i in range(n)])
bigrams = [" ".... | 0.284576 | 0.139367 |
from client.bcosclient import BcosClient
from client.datatype_parser import DatatypeParser
import uuid
import json
import threading
from utils.encoding import FriendlyJsonSerde
from client.channelpack import ChannelPack
from client.channel_push_dispatcher import ChannelPushHandler
class EventCallbackHandler:
"""事... | client/event_callback.py | from client.bcosclient import BcosClient
from client.datatype_parser import DatatypeParser
import uuid
import json
import threading
from utils.encoding import FriendlyJsonSerde
from client.channelpack import ChannelPack
from client.channel_push_dispatcher import ChannelPushHandler
class EventCallbackHandler:
"""事... | 0.128484 | 0.064683 |
from .google_imports import namespace_manager
from .google_imports import memcache
from . import autobatcher
from . import tasklets
class MemcacheClient(object):
def __init__(self, conn=None, auto_batcher_class=autobatcher.AutoBatcher, max_memcache=None):
# NOTE: If conn is not None, config is only used to get ... | ndb/memcache_client.py | from .google_imports import namespace_manager
from .google_imports import memcache
from . import autobatcher
from . import tasklets
class MemcacheClient(object):
def __init__(self, conn=None, auto_batcher_class=autobatcher.AutoBatcher, max_memcache=None):
# NOTE: If conn is not None, config is only used to get ... | 0.487551 | 0.068289 |
import sys
from django.conf import settings
from django.core.management import BaseCommand
from df_config.utils import is_package_present
class Command(BaseCommand):
help = "Launch the server process"
@property
def listen_port(self):
add, sep, port = settings.LISTEN_ADDRESS.partition(":")
... | df_config/management/commands/server.py | import sys
from django.conf import settings
from django.core.management import BaseCommand
from df_config.utils import is_package_present
class Command(BaseCommand):
help = "Launch the server process"
@property
def listen_port(self):
add, sep, port = settings.LISTEN_ADDRESS.partition(":")
... | 0.436622 | 0.101322 |
import os
PROJECT_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
BASE_DIR = os.path.dirname(PROJECT_DIR)
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/3.0/howto/deployment/checklist/
# Application definition
INSTALLED_APPS = [
'box',
... | intranet/intranet/settings/base.py | import os
PROJECT_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
BASE_DIR = os.path.dirname(PROJECT_DIR)
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/3.0/howto/deployment/checklist/
# Application definition
INSTALLED_APPS = [
'box',
... | 0.366136 | 0.07393 |
from __future__ import print_function
import time
import pandas as pd
from docopt import docopt
import pyper as pr
import pysam
def collect_set_XC(input_bam_file):
bamfile = pysam.AlignmentFile(input_bam_file, "rb")
set_XC = set()
for read in bamfile:
try:
if read.get_tag('GE'):... | correct_barcode.py | from __future__ import print_function
import time
import pandas as pd
from docopt import docopt
import pyper as pr
import pysam
def collect_set_XC(input_bam_file):
bamfile = pysam.AlignmentFile(input_bam_file, "rb")
set_XC = set()
for read in bamfile:
try:
if read.get_tag('GE'):... | 0.457137 | 0.204401 |
from __future__ import unicode_literals
from .compat import itervalues
from .parse_utils import EMPTY_PARSED_PIECE
from .pattern import Pattern
from .utils import TreeNode, build_tree
class PiecePatternNode(TreeNode):
"""Node for building raw piece tree."""
__slots__ = ('_pattern',)
def __init__(self, ... | src/os_urlpattern/piece_pattern_node.py | from __future__ import unicode_literals
from .compat import itervalues
from .parse_utils import EMPTY_PARSED_PIECE
from .pattern import Pattern
from .utils import TreeNode, build_tree
class PiecePatternNode(TreeNode):
"""Node for building raw piece tree."""
__slots__ = ('_pattern',)
def __init__(self, ... | 0.939996 | 0.296591 |
import pandas as pd
from sklearn.feature_extraction.text import CountVectorizer
import os
from sklearn.naive_bayes import GaussianNB
from sklearn.model_selection import train_test_split
from sklearn import metrics
import tensorflow as tf
import tflearn
from tflearn.data_utils import to_categorical, pad_sequences
from s... | Homework/2019/Task4/4/Code/dga.py | import pandas as pd
from sklearn.feature_extraction.text import CountVectorizer
import os
from sklearn.naive_bayes import GaussianNB
from sklearn.model_selection import train_test_split
from sklearn import metrics
import tensorflow as tf
import tflearn
from tflearn.data_utils import to_categorical, pad_sequences
from s... | 0.396535 | 0.419172 |
import sys, time, subprocess
from io import BytesIO
from PySide2 import QtCore, QtWidgets, QtGui
from PySide2.QtWidgets import QMainWindow, QInputDialog
from PySide2.QtCore import QSize
from PySide2.QtCore import QMimeData
from PySide2.QtGui import QDrag, QIcon
from PySide2.QtCore import Qt
from PySide2.QtCore import... | snapper.py |
import sys, time, subprocess
from io import BytesIO
from PySide2 import QtCore, QtWidgets, QtGui
from PySide2.QtWidgets import QMainWindow, QInputDialog
from PySide2.QtCore import QSize
from PySide2.QtCore import QMimeData
from PySide2.QtGui import QDrag, QIcon
from PySide2.QtCore import Qt
from PySide2.QtCore import... | 0.23855 | 0.106087 |
import os
import logging
import browser_cookie3
from pytconf import Config, ParamCreator
class ConfigLogging(Config):
"""
Parameters to control logging
"""
loglevel = ParamCreator.create_choice(
choice_list=[
logging.getLevelName(logging.NOTSET),
logging.getLevelName(l... | pyscrapers/configs.py | import os
import logging
import browser_cookie3
from pytconf import Config, ParamCreator
class ConfigLogging(Config):
"""
Parameters to control logging
"""
loglevel = ParamCreator.create_choice(
choice_list=[
logging.getLevelName(logging.NOTSET),
logging.getLevelName(l... | 0.555435 | 0.262192 |
r"""
This module provides argument manipulation functions like pop_arg.
"""
import gen_print as gp
import collections
def pop_arg(pop_arg_default=None, *args, **kwargs):
r"""
Pop a named argument from the args/kwargs and return a tuple consisting of the argument value, the
modified args and the modified... | lib/func_args.py |
r"""
This module provides argument manipulation functions like pop_arg.
"""
import gen_print as gp
import collections
def pop_arg(pop_arg_default=None, *args, **kwargs):
r"""
Pop a named argument from the args/kwargs and return a tuple consisting of the argument value, the
modified args and the modified... | 0.793186 | 0.607139 |
import abc
from typing import Dict, List
from uuid import uuid4
from wishlist.domain.product.adapters import (
CreateProductAdapter,
DeleteProductAdapter,
FindProductAdapter,
UpdateProductAdapter
)
from wishlist.domain.product.models import Product
class CreateProductPort(metaclass=abc.ABCMeta):
... | wishlist/domain/product/ports.py | import abc
from typing import Dict, List
from uuid import uuid4
from wishlist.domain.product.adapters import (
CreateProductAdapter,
DeleteProductAdapter,
FindProductAdapter,
UpdateProductAdapter
)
from wishlist.domain.product.models import Product
class CreateProductPort(metaclass=abc.ABCMeta):
... | 0.693265 | 0.126812 |
import logging
import sanic
from sanic.response import HTTPResponse, json
from internals.sanic import SpotilavaBlueprint, SpotilavaSanic
logger = logging.getLogger("Tidal.Playlists")
tidal_playlists_bp = SpotilavaBlueprint("tidal:playlists", url_prefix="/tidal/")
@tidal_playlists_bp.get("/album/<album_id>")
async... | routes/tidal/playlists.py | import logging
import sanic
from sanic.response import HTTPResponse, json
from internals.sanic import SpotilavaBlueprint, SpotilavaSanic
logger = logging.getLogger("Tidal.Playlists")
tidal_playlists_bp = SpotilavaBlueprint("tidal:playlists", url_prefix="/tidal/")
@tidal_playlists_bp.get("/album/<album_id>")
async... | 0.30632 | 0.149469 |
import os
import re
import numpy as np
import SimpleITK as sitk
import cv2
import torch
import random
from torch.utils.data import Dataset
from utils.project import proj_make_3dinput_v2
def threshold_CTA_mask(cta_image, HU_window=np.array([-263.,553.])):
th_cta_image = (cta_image - HU_window[0])/(HU_window[1] - H... | load_data.py | import os
import re
import numpy as np
import SimpleITK as sitk
import cv2
import torch
import random
from torch.utils.data import Dataset
from utils.project import proj_make_3dinput_v2
def threshold_CTA_mask(cta_image, HU_window=np.array([-263.,553.])):
th_cta_image = (cta_image - HU_window[0])/(HU_window[1] - H... | 0.532911 | 0.354042 |
from pyimagesearch import social_distancing_config as config
from pyimagesearch.detection import detect_people
from scipy.spatial import distance as dist
import numpy as np
import argparse
import imutils
import cv2
import os
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--input", type=str, default="",
help="... | src/SDD.py |
from pyimagesearch import social_distancing_config as config
from pyimagesearch.detection import detect_people
from scipy.spatial import distance as dist
import numpy as np
import argparse
import imutils
import cv2
import os
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--input", type=str, default="",
help="... | 0.352982 | 0.181336 |
from collections import defaultdict
import mock
from searx.engines import soundcloud
from searx.testing import SearxTestCase
from searx.url_utils import quote_plus
class TestSoundcloudEngine(SearxTestCase):
def test_request(self):
query = 'test_query'
dicto = defaultdict(dict)
dicto['page... | Toolkits/Discovery/meta/searx/tests/unit/engines/test_soundcloud.py | from collections import defaultdict
import mock
from searx.engines import soundcloud
from searx.testing import SearxTestCase
from searx.url_utils import quote_plus
class TestSoundcloudEngine(SearxTestCase):
def test_request(self):
query = 'test_query'
dicto = defaultdict(dict)
dicto['page... | 0.608012 | 0.404949 |
import os
import pybullet as p
from normalize_obj import normalize_one_obj
import sys
import subprocess
import json
from distutils.dir_util import copy_tree
ori_shapenet_dir = '/juno/group/linshao/ShapeNetCore'
shapenet_dir = '/scr1/yifan/shapenet_partial'
shapenet_new_dir = '/scr1/yifan/geo_data'
category_dict = {
... | src/scripts/process_shapenet.py | import os
import pybullet as p
from normalize_obj import normalize_one_obj
import sys
import subprocess
import json
from distutils.dir_util import copy_tree
ori_shapenet_dir = '/juno/group/linshao/ShapeNetCore'
shapenet_dir = '/scr1/yifan/shapenet_partial'
shapenet_new_dir = '/scr1/yifan/geo_data'
category_dict = {
... | 0.069542 | 0.05375 |
import numpy as np
import math
import mcdc_tnt
from timeit import default_timer as timer
def error(sim, bench):
error = np.linalg.norm(sim - bench) / np.linalg.norm(bench)
return(error)
if __name__ == '__main__':
print()
print('ATTENTION')
print('Entering Hardware Test Suite')
print('Ensu... | tests/integration/tests_hardware.py | import numpy as np
import math
import mcdc_tnt
from timeit import default_timer as timer
def error(sim, bench):
error = np.linalg.norm(sim - bench) / np.linalg.norm(bench)
return(error)
if __name__ == '__main__':
print()
print('ATTENTION')
print('Entering Hardware Test Suite')
print('Ensu... | 0.186947 | 0.197251 |
import sys
from PyQt5.QtWidgets import (QApplication, QWidget, QVBoxLayout, QGridLayout, QLabel, QLineEdit, QToolButton, QPushButton)
from PyQt5.QtCore import Qt
class Login(QWidget):
def __init__(self):
super().__init__()
self.bodyLayout = QGridLayout()
# 欢迎登陆图书馆系统标题
self.titleTe... | model/login.py | import sys
from PyQt5.QtWidgets import (QApplication, QWidget, QVBoxLayout, QGridLayout, QLabel, QLineEdit, QToolButton, QPushButton)
from PyQt5.QtCore import Qt
class Login(QWidget):
def __init__(self):
super().__init__()
self.bodyLayout = QGridLayout()
# 欢迎登陆图书馆系统标题
self.titleTe... | 0.255437 | 0.10307 |
def check_args(r, c, d, i, player):
if r > 2 or r < 0:
raise ValueError('Unknown row: ' + str(r))
if c > 2 or c < 0:
raise ValueError('Unknown column: ' + str(c))
if d > 1 or d < 0:
raise ValueError('Unknown diag: ' + str(d))
if i > 8 or i < 0:
raise ValueError('Unknown i... | Scripts/Utils/board.py | def check_args(r, c, d, i, player):
if r > 2 or r < 0:
raise ValueError('Unknown row: ' + str(r))
if c > 2 or c < 0:
raise ValueError('Unknown column: ' + str(c))
if d > 1 or d < 0:
raise ValueError('Unknown diag: ' + str(d))
if i > 8 or i < 0:
raise ValueError('Unknown i... | 0.601242 | 0.618809 |
import random
class Card:
"""Simple deck card instance,
number is 1 to 13 ( 13 being the king)
kind is Heards, Spades, Diamonds, Clubs """
kinds = {1: 'Heart', 2: 'Spade', 3: 'Diamond', 4: 'Club'}
numbers = {13: 'Ace', 1: 2, 2: 3, 3: 4, 4: 5, 5: 6, 6: 7, 7: 8, 8: 9, 9: 10, 10: 'Jack', 11: 'Queen... | main.py |
import random
class Card:
"""Simple deck card instance,
number is 1 to 13 ( 13 being the king)
kind is Heards, Spades, Diamonds, Clubs """
kinds = {1: 'Heart', 2: 'Spade', 3: 'Diamond', 4: 'Club'}
numbers = {13: 'Ace', 1: 2, 2: 3, 3: 4, 4: 5, 5: 6, 6: 7, 7: 8, 8: 9, 9: 10, 10: 'Jack', 11: 'Queen... | 0.235548 | 0.318697 |
from ChromeDriver import create_driver
from selenium.webdriver.common.action_chains import ActionChains
from selenium.webdriver.common.keys import Keys
from selenium.common.exceptions import NoSuchElementException
from pyvirtualdisplay import Display
import os
import pickle
# TODO:
class Player:
def __init__(se... | src/Player.py | from ChromeDriver import create_driver
from selenium.webdriver.common.action_chains import ActionChains
from selenium.webdriver.common.keys import Keys
from selenium.common.exceptions import NoSuchElementException
from pyvirtualdisplay import Display
import os
import pickle
# TODO:
class Player:
def __init__(se... | 0.358915 | 0.145661 |
import argparse
import ast
import itertools
import sys
import tokenize
from typing import Tuple, Iterable, Union, List, cast
import flake8.options.manager
ComprehensionType = Union[
ast.ListComp, ast.SetComp, ast.DictComp, ast.GeneratorExp
]
DEFAULT_SELECT = [
"C2000",
"C2001",
"C2002",
"C2020",
... | flake8_multiline_conditionals_comprehensions/mcc_checker.py | import argparse
import ast
import itertools
import sys
import tokenize
from typing import Tuple, Iterable, Union, List, cast
import flake8.options.manager
ComprehensionType = Union[
ast.ListComp, ast.SetComp, ast.DictComp, ast.GeneratorExp
]
DEFAULT_SELECT = [
"C2000",
"C2001",
"C2002",
"C2020",
... | 0.522689 | 0.246828 |
import argparse
import requests
import os
import cv2
def parse_args():
parser = argparse.ArgumentParser(prog="Send Images From Folder",
description="This program sends the images stored in a folder to the cloud face recognition system.")
parser.add_argument('--input-folder', required=True,
... | interaction-with-framework/send-images-from-folder/send-images-from-folder.py |
import argparse
import requests
import os
import cv2
def parse_args():
parser = argparse.ArgumentParser(prog="Send Images From Folder",
description="This program sends the images stored in a folder to the cloud face recognition system.")
parser.add_argument('--input-folder', required=True,
... | 0.369315 | 0.160496 |
from __future__ import print_function
import argparse
import yaml
from pybh.utils import fail, argparse_bool, convert_string_to_array
TYPE_STR_MAPPING = {
"str": str,
"int": int,
"float": float,
"bool": argparse_bool,
}
def run(args):
with open(args.file, "r") as fin:
content = yaml.loa... | pybh/tools/read_yaml_value.py | from __future__ import print_function
import argparse
import yaml
from pybh.utils import fail, argparse_bool, convert_string_to_array
TYPE_STR_MAPPING = {
"str": str,
"int": int,
"float": float,
"bool": argparse_bool,
}
def run(args):
with open(args.file, "r") as fin:
content = yaml.loa... | 0.418459 | 0.20949 |
import glob
import json
import os
import random
import tempfile
import unittest
from . import train
class TrainTest(unittest.TestCase):
def setUp(self):
self.job_dir = tempfile.mkdtemp()
self.num_checkpoints = 10
self.checkpoint_files = []
self.checkpoint_steps = 100
self.test_job_dir = temp... | gce/survival-training/wrapper/train_test.py |
import glob
import json
import os
import random
import tempfile
import unittest
from . import train
class TrainTest(unittest.TestCase):
def setUp(self):
self.job_dir = tempfile.mkdtemp()
self.num_checkpoints = 10
self.checkpoint_files = []
self.checkpoint_steps = 100
self.test_job_dir = temp... | 0.411347 | 0.432363 |
import mock
import unittest
from common import acl
from common import constants
from common import exceptions
class AclTest(unittest.TestCase):
def testAdminIsPrivilegedUser(self):
self.assertTrue(acl.IsPrivilegedUser('<EMAIL>', True))
def testGooglerIsPrivilegedUser(self):
self.assertTrue(acl.IsPrivi... | appengine/findit/common/test/acl_test.py |
import mock
import unittest
from common import acl
from common import constants
from common import exceptions
class AclTest(unittest.TestCase):
def testAdminIsPrivilegedUser(self):
self.assertTrue(acl.IsPrivilegedUser('<EMAIL>', True))
def testGooglerIsPrivilegedUser(self):
self.assertTrue(acl.IsPrivi... | 0.546254 | 0.380932 |
from nose.tools import *
from dateutil.parser import parse as time_parse
import yawhois
class TestWhoisAudnsNetAuStatusRegistered(object):
def setUp(self):
fixture_path = "spec/fixtures/responses/whois.audns.net.au/status_registered.txt"
host = "whois.audns.net.au"
part = ... | test/record/parser/test_response_whois_audns_net_au_status_registered.py |
from nose.tools import *
from dateutil.parser import parse as time_parse
import yawhois
class TestWhoisAudnsNetAuStatusRegistered(object):
def setUp(self):
fixture_path = "spec/fixtures/responses/whois.audns.net.au/status_registered.txt"
host = "whois.audns.net.au"
part = ... | 0.549641 | 0.229222 |
import numpy as np
import matplotlib.pyplot as pl
from configobj import ConfigObj
from astropy import units as u
import copy
import pymcao.wfs as wfs
import pymcao.atmosphere as atmosphere
import pymcao.sun as sun
import logging
import time
from tqdm import tqdm
import threading
import pymcao.comm as comm
import pymcao... | pymcao/simulator.py | import numpy as np
import matplotlib.pyplot as pl
from configobj import ConfigObj
from astropy import units as u
import copy
import pymcao.wfs as wfs
import pymcao.atmosphere as atmosphere
import pymcao.sun as sun
import logging
import time
from tqdm import tqdm
import threading
import pymcao.comm as comm
import pymcao... | 0.664867 | 0.175609 |
from igia.utils import bed2bam, SeqFile, load_seqinfo
from igia.element import identify_element
from igia.transcript import identify_transcript
import os
import unittest
class TestAnnotation(unittest.TestCase):
def setUp(self):
self.ann_dir = "tests/data/ann.bed12"
self.size = "tests/data/chrom.si... | tests/test_annotation.py | from igia.utils import bed2bam, SeqFile, load_seqinfo
from igia.element import identify_element
from igia.transcript import identify_transcript
import os
import unittest
class TestAnnotation(unittest.TestCase):
def setUp(self):
self.ann_dir = "tests/data/ann.bed12"
self.size = "tests/data/chrom.si... | 0.473901 | 0.333496 |
import os
import numpy as np
from PIL import Image
from pathlib import Path
from torch.utils.data import DataLoader, Dataset
from torchvision import datasets, transforms
from torchvision.io import read_image
from typing import Any, Callable, List, Optional, Tuple
import torch
import cv2
def get_dataloaders(dataset_di... | week4/dataset.py | import os
import numpy as np
from PIL import Image
from pathlib import Path
from torch.utils.data import DataLoader, Dataset
from torchvision import datasets, transforms
from torchvision.io import read_image
from typing import Any, Callable, List, Optional, Tuple
import torch
import cv2
def get_dataloaders(dataset_di... | 0.740362 | 0.533641 |
"""Example utils."""
import tensorflow as tf
import numpy as np
from tensor2tensor.data_generators import algorithmic
from tensor2tensor.layers import modalities
from tensor2tensor.data_generators import problem
from tensor2tensor.data_generators import multi_problem_v2
from tensor2tensor.utils import registry
from ... | clarify/datasets/utils/example_utils_test.py | """Example utils."""
import tensorflow as tf
import numpy as np
from tensor2tensor.data_generators import algorithmic
from tensor2tensor.layers import modalities
from tensor2tensor.data_generators import problem
from tensor2tensor.data_generators import multi_problem_v2
from tensor2tensor.utils import registry
from ... | 0.935324 | 0.486819 |
from dogqc.gpuio import GpuIO
from dogqc.cudalang import *
import dogqc.identifier as ident
import dogqc.querylib as qlib
from dogqc.variable import Variable
from dogqc.kernel import Kernel, KernelCall
from dogqc.types import Type
from dogqc.relationalAlgebra import Reduction
class Hash ( object ):
@staticme... | dogqc/hashTableUtil.py | from dogqc.gpuio import GpuIO
from dogqc.cudalang import *
import dogqc.identifier as ident
import dogqc.querylib as qlib
from dogqc.variable import Variable
from dogqc.kernel import Kernel, KernelCall
from dogqc.types import Type
from dogqc.relationalAlgebra import Reduction
class Hash ( object ):
@staticme... | 0.364664 | 0.180143 |
from crispy_forms.helper import FormHelper
from crispy_forms.layout import Submit, Layout, Field, Div, Reset
from django import forms
from django.contrib.admin.widgets import FilteredSelectMultiple
from django.urls import reverse
from django.utils.translation import gettext as __
from django.utils.translation import ge... | booking/forms.py | from crispy_forms.helper import FormHelper
from crispy_forms.layout import Submit, Layout, Field, Div, Reset
from django import forms
from django.contrib.admin.widgets import FilteredSelectMultiple
from django.urls import reverse
from django.utils.translation import gettext as __
from django.utils.translation import ge... | 0.653459 | 0.137475 |
import asyncio
import weakref
import aiohttp
import sys
import json
import traceback
import logging
from urllib.parse import quote as _uriquote
from ..errors import HTTPException, Forbidden, NotFound, ServerError, SentinelError
log = logging.getLogger(__name__)
class Route:
BASE = "https://discord.com/api/v9"
... | sentinel/rest/http.py | import asyncio
import weakref
import aiohttp
import sys
import json
import traceback
import logging
from urllib.parse import quote as _uriquote
from ..errors import HTTPException, Forbidden, NotFound, ServerError, SentinelError
log = logging.getLogger(__name__)
class Route:
BASE = "https://discord.com/api/v9"
... | 0.223886 | 0.067026 |
# ## Questionário 73 (Q73)
#
# Orientações:
#
# - Registre suas respostas no questionário de mesmo nome no SIGAA.
# - O tempo de registro das respostas no questionário será de 10 minutos. Portanto, resolva primeiro as questões e depois registre-as.
# - Haverá apenas 1 (uma) tentativa de resposta.
# - Submeta seu ar... | _build/jupyter_execute/todo/Q73-gab.py |
# ## Questionário 73 (Q73)
#
# Orientações:
#
# - Registre suas respostas no questionário de mesmo nome no SIGAA.
# - O tempo de registro das respostas no questionário será de 10 minutos. Portanto, resolva primeiro as questões e depois registre-as.
# - Haverá apenas 1 (uma) tentativa de resposta.
# - Submeta seu ar... | 0.431345 | 0.566378 |
from django.contrib import admin
from django.views.generic.base import TemplateView
from django.urls import path, re_path, include
from . import views
urlpatterns = [
path('admin/', admin.site.urls),
path(r'^api-auth/', include('rest_framework.urls', namespace='rest_framework')),
path(r'^$', TemplateView... | digifarming/digifarming/urls.py | from django.contrib import admin
from django.views.generic.base import TemplateView
from django.urls import path, re_path, include
from . import views
urlpatterns = [
path('admin/', admin.site.urls),
path(r'^api-auth/', include('rest_framework.urls', namespace='rest_framework')),
path(r'^$', TemplateView... | 0.253306 | 0.041579 |
import bs4
import logging
from cryptics.text import (
is_parsable_text_type_1,
parse_text_type_1,
is_parsable_text_type_2,
parse_text_type_2,
)
from cryptics.tables import (
is_parsable_table_type_1,
parse_table_type_1,
is_parsable_table_type_2,
parse_table_type_2,
is_parsable_table... | cryptics/parse.py | import bs4
import logging
from cryptics.text import (
is_parsable_text_type_1,
parse_text_type_1,
is_parsable_text_type_2,
parse_text_type_2,
)
from cryptics.tables import (
is_parsable_table_type_1,
parse_table_type_1,
is_parsable_table_type_2,
parse_table_type_2,
is_parsable_table... | 0.359139 | 0.418222 |
import os
import sys
import json
import numpy as np
import matplotlib.pyplot as plt
from tensorflow.keras.models import load_model
from model.loss import dice_loss_2d, surface_channel_loss_2d
from preprocessing.dataset import AgricultureVisionDataset
from testing.image import get_testing_image, create_displayable_te... | prototype.py | import os
import sys
import json
import numpy as np
import matplotlib.pyplot as plt
from tensorflow.keras.models import load_model
from model.loss import dice_loss_2d, surface_channel_loss_2d
from preprocessing.dataset import AgricultureVisionDataset
from testing.image import get_testing_image, create_displayable_te... | 0.736495 | 0.33939 |
class TBar():
_max = -1
length = 50
infile = None
rawdata = None
normdata = None
vertical = False
def __init__(self, _max=0, length=0, vertical=False):
if _max:
self._max = _max
if length:
self.length = length
self.vertical = vertical
... | tbar/tbar.py |
class TBar():
_max = -1
length = 50
infile = None
rawdata = None
normdata = None
vertical = False
def __init__(self, _max=0, length=0, vertical=False):
if _max:
self._max = _max
if length:
self.length = length
self.vertical = vertical
... | 0.544559 | 0.122891 |
"""Demo some features of NetCore."""
import argparse
import mininet.topolib
import mininet.topo
import MininetDriver as md
from multiprocessing import Process
import subprocess as sp
import time
# H1 0----1 S3 2----0 H2
basic = mininet.topolib.TreeTopo(depth=1, fanout=2)
def getRunner(flag, topo=basic):
ctrl = sp.... | examples/demo.py | """Demo some features of NetCore."""
import argparse
import mininet.topolib
import mininet.topo
import MininetDriver as md
from multiprocessing import Process
import subprocess as sp
import time
# H1 0----1 S3 2----0 H2
basic = mininet.topolib.TreeTopo(depth=1, fanout=2)
def getRunner(flag, topo=basic):
ctrl = sp.... | 0.514644 | 0.117319 |
import re
import os
import sys
import importlib
import os.path
class Exporter(object):
data = None
def __init__(self, data):
self.data = data
def write(self, directory):
with open("Out.txt", "w") as handle:
# Write the header
handle.write("====== Test =====... | exporters/doku.py | import re
import os
import sys
import importlib
import os.path
class Exporter(object):
data = None
def __init__(self, data):
self.data = data
def write(self, directory):
with open("Out.txt", "w") as handle:
# Write the header
handle.write("====== Test =====... | 0.193795 | 0.145996 |
import argparse
from pathlib import Path
from jinja2 import Environment, PackageLoader, select_autoescape
helm_dir = Path(__file__).resolve().parent.parent / "helm"
# Map the chart names to their location. This is useful for updating
# dependencies (in Chart.yaml) as well as the charts.
helm_charts = [
helm_dir... | deploy/scripts/combine_charts.py | import argparse
from pathlib import Path
from jinja2 import Environment, PackageLoader, select_autoescape
helm_dir = Path(__file__).resolve().parent.parent / "helm"
# Map the chart names to their location. This is useful for updating
# dependencies (in Chart.yaml) as well as the charts.
helm_charts = [
helm_dir... | 0.574992 | 0.195709 |
import getopt
import sys
from algorithms import Kruskal, Prim
from utils.graph import (DisjointSet, create_graph, edges_to_graph,
graph_to_edges)
from utils.io import (read_input, save_clusters_csv, save_clusters_png,
save_mst_csv, save_mst_png)
class Config:
data_f... | main.py | import getopt
import sys
from algorithms import Kruskal, Prim
from utils.graph import (DisjointSet, create_graph, edges_to_graph,
graph_to_edges)
from utils.io import (read_input, save_clusters_csv, save_clusters_png,
save_mst_csv, save_mst_png)
class Config:
data_f... | 0.251556 | 0.123842 |
from django.db import models
from django.contrib.auth.models import User
from django.urls import reverse
from django.utils.text import Truncator
# Create your models here.
class Board(models.Model):
"""
Class for message boards.
"""
name = models.CharField(max_length=30, unique=True)
description... | acceptable-albatrosses/albatrosses_hub/forums/models.py | from django.db import models
from django.contrib.auth.models import User
from django.urls import reverse
from django.utils.text import Truncator
# Create your models here.
class Board(models.Model):
"""
Class for message boards.
"""
name = models.CharField(max_length=30, unique=True)
description... | 0.725454 | 0.163512 |
import tensorflow as tf
import numpy as np
def get_shape(spec: str, spec_shape: dict):
return tuple(spec_shape[dim] for dim in spec)
def expand_transform(x, input_spec: str, output_spec: str, output_spec_shape: dict, numpy=False):
assert len(output_spec) == len(output_spec_shape)
if numpy:
tile... | layers/ddcconv1d.py | import tensorflow as tf
import numpy as np
def get_shape(spec: str, spec_shape: dict):
return tuple(spec_shape[dim] for dim in spec)
def expand_transform(x, input_spec: str, output_spec: str, output_spec_shape: dict, numpy=False):
assert len(output_spec) == len(output_spec_shape)
if numpy:
tile... | 0.795142 | 0.629234 |
import netCDF4 as nc
import numpy as np
import os
def build_url(yyyy,mm,dd,hh):
return f'http://172.16.31.10:8080/opendap/opendap/wrf5/d03/archive/{yyyy}/{mm}/{dd}/wrf5_d03_{yyyy}{mm}{dd}Z{hh}00.nc'
def read_netcdf4_files(wrf,scan):
try:
model = nc.Dataset(wrf)
radar_scan = nc.Da... | tools/wrf_regridding.py | import netCDF4 as nc
import numpy as np
import os
def build_url(yyyy,mm,dd,hh):
return f'http://172.16.31.10:8080/opendap/opendap/wrf5/d03/archive/{yyyy}/{mm}/{dd}/wrf5_d03_{yyyy}{mm}{dd}Z{hh}00.nc'
def read_netcdf4_files(wrf,scan):
try:
model = nc.Dataset(wrf)
radar_scan = nc.Da... | 0.153676 | 0.214177 |
import os
import cv2
from tqdm import tqdm
def crop(img_path, size=(720, 720), alignment='center'):
"""
helper function to crop an image to the given size
:param img:
:param size: (width, height)
:param center:
:return:
"""
img = cv2.imread(img_path)
if img is None:... | datasets_utils/crop_image_of_dataset.py | import os
import cv2
from tqdm import tqdm
def crop(img_path, size=(720, 720), alignment='center'):
"""
helper function to crop an image to the given size
:param img:
:param size: (width, height)
:param center:
:return:
"""
img = cv2.imread(img_path)
if img is None:... | 0.470737 | 0.311833 |
# Node class
class Node:
# Function to initialise the node object
def __init__(self, data):
self.data = data # Assign data
self.next = None # Initialize next as null
self.prev = None # Initialize prev as null
# Stack class contains a Node object
c... | Profiles/stack_using_dll.py |
# Node class
class Node:
# Function to initialise the node object
def __init__(self, data):
self.data = data # Assign data
self.next = None # Initialize next as null
self.prev = None # Initialize prev as null
# Stack class contains a Node object
c... | 0.354321 | 0.157396 |
"""File for base geometry class built using the Geomdl class"""
import numpy as np
class Geometry2D:
'''
Base class for 2D domains
Input: geomData - dictionary containing the geomety information
Keys: degree_u, degree_v: polynomial degree in the u and v directions
ctrlpts_size_u, ctrlpts_size... | tf1/tensorflow_DEM/Phase Field/utils/BezExtr.py | """File for base geometry class built using the Geomdl class"""
import numpy as np
class Geometry2D:
'''
Base class for 2D domains
Input: geomData - dictionary containing the geomety information
Keys: degree_u, degree_v: polynomial degree in the u and v directions
ctrlpts_size_u, ctrlpts_size... | 0.607663 | 0.707482 |
import json
import sys
def s(_):
return '"' + _ + '"'
def i(_):
return str(_)
def b(_):
if _:
return "true"
else:
return "false"
def enc(typ, val):
if typ == "int":
return i(val)
elif typ == "string":
return s(val)
elif typ == "bool":
return b(val)... | jcc_interpreter.py | import json
import sys
def s(_):
return '"' + _ + '"'
def i(_):
return str(_)
def b(_):
if _:
return "true"
else:
return "false"
def enc(typ, val):
if typ == "int":
return i(val)
elif typ == "string":
return s(val)
elif typ == "bool":
return b(val)... | 0.127734 | 0.14624 |
import tkinter as tk
import random
class Customer:
def __init__(self, id, create_time):
self.id = id
self.create_time = create_time
self.finished_time = -1
class App:
"""The tkinter GUI interface."""
def kill_callback(self):
self.window.destroy()
def __i... | algs2e_python/Chapter 05/python/multi_headed_queue.py | import tkinter as tk
import random
class Customer:
def __init__(self, id, create_time):
self.id = id
self.create_time = create_time
self.finished_time = -1
class App:
"""The tkinter GUI interface."""
def kill_callback(self):
self.window.destroy()
def __i... | 0.507324 | 0.133359 |
import collections
import json
import pytest
import os
from typing import Set
from data.src.split import _detect_best_script_name
from data.src.split import _generalized_check
_REPO_DIR = os.path.dirname(
os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
)
_LANGUAGES = os.path.join(_REPO_DIR, "data/sr... | tests/test_data/test_split.py | import collections
import json
import pytest
import os
from typing import Set
from data.src.split import _detect_best_script_name
from data.src.split import _generalized_check
_REPO_DIR = os.path.dirname(
os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
)
_LANGUAGES = os.path.join(_REPO_DIR, "data/sr... | 0.625324 | 0.282437 |
import logging
from typing import Dict, List, Optional, Any, Callable, Tuple, Union
from collections import OrderedDict
import traceback
import copy
import os
from qiskit.providers import ProviderV1 as Provider # type: ignore[attr-defined]
from qiskit.providers.models import (QasmBackendConfiguration,
... | qiskit_ibm/ibm_provider.py | import logging
from typing import Dict, List, Optional, Any, Callable, Tuple, Union
from collections import OrderedDict
import traceback
import copy
import os
from qiskit.providers import ProviderV1 as Provider # type: ignore[attr-defined]
from qiskit.providers.models import (QasmBackendConfiguration,
... | 0.905927 | 0.167491 |
from TestHelperSuperClass import testHelperSuperClass
class local_helpers(testHelperSuperClass):
def deleteConsumer(self, consumer_name):
resp, respCode = self.callKongService("/consumers/" + consumer_name, {}, "get", None, [200, 404])
if respCode == 404:
return False
resp, respCode = self.callKon... | test/test_kong_install_consumer_with_api.py | from TestHelperSuperClass import testHelperSuperClass
class local_helpers(testHelperSuperClass):
def deleteConsumer(self, consumer_name):
resp, respCode = self.callKongService("/consumers/" + consumer_name, {}, "get", None, [200, 404])
if respCode == 404:
return False
resp, respCode = self.callKon... | 0.458106 | 0.13109 |
import os
import sys
import unittest
sys.path.append(os.path.dirname(os.path.dirname(os.path.realpath(__file__))))
from neon_api_proxy.wolfram_api import WolframAPI, QueryUrl
VALID_QUERY_IP = {"query": "how far away is Moscow?",
"units": "metric",
"ip": "172.16.17.32"}
VALID_QUE... | tests/test_wolfram_api.py |
import os
import sys
import unittest
sys.path.append(os.path.dirname(os.path.dirname(os.path.realpath(__file__))))
from neon_api_proxy.wolfram_api import WolframAPI, QueryUrl
VALID_QUERY_IP = {"query": "how far away is Moscow?",
"units": "metric",
"ip": "172.16.17.32"}
VALID_QUE... | 0.405566 | 0.334426 |
import logging
import os
from pathlib import Path
from make_prg import make_prg_from_msa, io_utils
def run(options):
if options.output_prefix is None:
prefix = options.MSA
else:
if os.path.isdir(options.output_prefix):
prefix = os.path.join(options.output_prefix, os.path.basename(... | make_prg/subcommands/prg_from_msa.py | import logging
import os
from pathlib import Path
from make_prg import make_prg_from_msa, io_utils
def run(options):
if options.output_prefix is None:
prefix = options.MSA
else:
if os.path.isdir(options.output_prefix):
prefix = os.path.join(options.output_prefix, os.path.basename(... | 0.281702 | 0.072735 |
from __future__ import print_function
# Used to process batch download from plasmoDB to be input into GeneTargeter
from builtins import str
from py.utils.GenBankToolbox import *
from py.utils.BioUtils import *
from copy import deepcopy
# use to process plasmoDB fasta download (no introns, use gff_to_genbank now
# ins... | py/auxiliary/Multiseq.py | from __future__ import print_function
# Used to process batch download from plasmoDB to be input into GeneTargeter
from builtins import str
from py.utils.GenBankToolbox import *
from py.utils.BioUtils import *
from copy import deepcopy
# use to process plasmoDB fasta download (no introns, use gff_to_genbank now
# ins... | 0.3295 | 0.266113 |
import os
import pytest
import numpy as np
import pandas as pd
from pandas.testing import assert_frame_equal
import nyaggle.feature_store as fs
from nyaggle.testing import get_temp_directory
def test_save_feature():
df = pd.DataFrame()
df['a'] = np.arange(100)
with get_temp_directory() as tmp:
... | tests/feature_store/test_feature_store.py | import os
import pytest
import numpy as np
import pandas as pd
from pandas.testing import assert_frame_equal
import nyaggle.feature_store as fs
from nyaggle.testing import get_temp_directory
def test_save_feature():
df = pd.DataFrame()
df['a'] = np.arange(100)
with get_temp_directory() as tmp:
... | 0.267313 | 0.516108 |
from GUI.LoginWindow import *
from PyQt5.QtCore import QThread, pyqtSignal
from PyQt5 import QtWidgets, QtGui
from PyQt5.QtWidgets import *
import random
import win32com.client
import threading
from GUI.ProprietorWindow import Design_ProprietorWindow
from Controllers import ProprietorControl
import time
class Propri... | src/GUI/LProprietorWindow.py |
from GUI.LoginWindow import *
from PyQt5.QtCore import QThread, pyqtSignal
from PyQt5 import QtWidgets, QtGui
from PyQt5.QtWidgets import *
import random
import win32com.client
import threading
from GUI.ProprietorWindow import Design_ProprietorWindow
from Controllers import ProprietorControl
import time
class Propri... | 0.303732 | 0.101189 |
import argparse
import logging
import os
import subprocess
from .log import logger
def set_up_command_line_arguments():
""" Sets up command line arguments that can be used to modify how scripts are run.
Returns
=======
command_line_args, command_line_parser: tuple
The command_line_args is a ... | bilby/core/utils/cmd.py | import argparse
import logging
import os
import subprocess
from .log import logger
def set_up_command_line_arguments():
""" Sets up command line arguments that can be used to modify how scripts are run.
Returns
=======
command_line_args, command_line_parser: tuple
The command_line_args is a ... | 0.766206 | 0.289836 |
import json
import sys
import requests
import time
import os
from bs4 import BeautifulSoup
DIR = os.path.dirname(os.path.realpath(__file__))
with open(os.path.join(DIR, "trajectory-albatross.gpx")) as f:
xml_str = f.read()
defs = []
results = []
obj = BeautifulSoup(xml_str, 'xml')
trks = obj.find_all('trk')
for... | demo_data/animals/analyse.py | import json
import sys
import requests
import time
import os
from bs4 import BeautifulSoup
DIR = os.path.dirname(os.path.realpath(__file__))
with open(os.path.join(DIR, "trajectory-albatross.gpx")) as f:
xml_str = f.read()
defs = []
results = []
obj = BeautifulSoup(xml_str, 'xml')
trks = obj.find_all('trk')
for... | 0.101679 | 0.095645 |
from ruffus import follows, transform, regex, mkdir,\
pipeline_printout, pipeline_printout_graph,\
pipeline_run, files, merge,\
touch_file, posttask, jobs_limit
import os
import sys
from subprocess import check_call
from pipeline_config import POINTS_H5_DIR,\
PCD_DIR, PCD_DOWNSAMPLED_DIR... | mapping/pipeline/pipeline.py | from ruffus import follows, transform, regex, mkdir,\
pipeline_printout, pipeline_printout_graph,\
pipeline_run, files, merge,\
touch_file, posttask, jobs_limit
import os
import sys
from subprocess import check_call
from pipeline_config import POINTS_H5_DIR,\
PCD_DIR, PCD_DOWNSAMPLED_DIR... | 0.147524 | 0.071526 |
import re
import requests
import json
from selenium import webdriver
from selenium.webdriver import FirefoxOptions
import os
country_by_code_dict = {}
domains_dict = {}
path = '/home/kami/workspace/software/geckodriver'
country_regex = re.compile(r'<a href="countries/([A-Z]+)">([A-Za-z]+)</a>')
countries_list_url = ... | backend/server/init_db/get_top_sites_by_country.py | import re
import requests
import json
from selenium import webdriver
from selenium.webdriver import FirefoxOptions
import os
country_by_code_dict = {}
domains_dict = {}
path = '/home/kami/workspace/software/geckodriver'
country_regex = re.compile(r'<a href="countries/([A-Z]+)">([A-Za-z]+)</a>')
countries_list_url = ... | 0.130535 | 0.109658 |
import getopt
import os
import sys
import argparse
import getpass
import subprocess
import logging
from paramiko import SSHClient, AutoAddPolicy
from scp import SCPClient
from zipfile import ZipFile
SANDBOX_USERNAME = "sandbox"
SANDBOX_PORT = 22
SCRIPT = os.path.realpath(__file__)
SCRIPT_ROOT = os.path.dirname(SCRIP... | {{cookiecutter.project_name}}/upload.py | import getopt
import os
import sys
import argparse
import getpass
import subprocess
import logging
from paramiko import SSHClient, AutoAddPolicy
from scp import SCPClient
from zipfile import ZipFile
SANDBOX_USERNAME = "sandbox"
SANDBOX_PORT = 22
SCRIPT = os.path.realpath(__file__)
SCRIPT_ROOT = os.path.dirname(SCRIP... | 0.216923 | 0.056862 |
import functools
import math
def load_input_file(file_name: str):
with open(file_name) as file:
yield from (line.strip() for line in file)
def parse(task_input):
for line in task_input:
yield eval(line)
def get_elements(a, level):
for s in a:
if s.__class__ == list:
... | day-18/sol-18.py |
import functools
import math
def load_input_file(file_name: str):
with open(file_name) as file:
yield from (line.strip() for line in file)
def parse(task_input):
for line in task_input:
yield eval(line)
def get_elements(a, level):
for s in a:
if s.__class__ == list:
... | 0.314893 | 0.552178 |
import random
# My libraries
from backprop2 import Network, sigmoid_vec
# Third-party libraries
import numpy as np
def plot_helper(x):
import matplotlib
import matplotlib.pyplot as plt
x = np.reshape(x, (-1, 28))
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.matshow(x, cmap = matplotli... | code/deep_autoencoder.py | import random
# My libraries
from backprop2 import Network, sigmoid_vec
# Third-party libraries
import numpy as np
def plot_helper(x):
import matplotlib
import matplotlib.pyplot as plt
x = np.reshape(x, (-1, 28))
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.matshow(x, cmap = matplotli... | 0.845751 | 0.685871 |
import numpy as np
import math
import glob
from benchpress import prof
ppn = prof.max_ppn
files = glob.glob("%s/mult_pong.*.out"%(prof.folder))
class TimeList():
ppn_times = ""
def __init__(self, np):
self.ppn_times = list()
for i in range(np):
self.ppn_times.append(list())
... | plots/benchpress/ping_pong/mult_pong.py | import numpy as np
import math
import glob
from benchpress import prof
ppn = prof.max_ppn
files = glob.glob("%s/mult_pong.*.out"%(prof.folder))
class TimeList():
ppn_times = ""
def __init__(self, np):
self.ppn_times = list()
for i in range(np):
self.ppn_times.append(list())
... | 0.165796 | 0.190347 |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import re
import sys
import yaml
import copy
import pandas as pd
import logging
import tensorflow as tf
from collections import Counter, namedtuple
from tensorflow.python.platform import gfile
from s... | utils/io_utils.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import re
import sys
import yaml
import copy
import pandas as pd
import logging
import tensorflow as tf
from collections import Counter, namedtuple
from tensorflow.python.platform import gfile
from s... | 0.643217 | 0.135833 |
__all__ = ['open_geotiff', 'calc_normalized_spectral_index', 'calc_avi', 'calc_savi', 'calc_gci',
'mask_plot_from_image', 'image_metrics', 'glcm_xplusy', 'glcm_xminusy', 'textural_features',
'process_image_features']
# Cell
import rasterio as rio
import numpy as np
import matplotlib.pyplot as pl... | enveco/data/image.py |
__all__ = ['open_geotiff', 'calc_normalized_spectral_index', 'calc_avi', 'calc_savi', 'calc_gci',
'mask_plot_from_image', 'image_metrics', 'glcm_xplusy', 'glcm_xminusy', 'textural_features',
'process_image_features']
# Cell
import rasterio as rio
import numpy as np
import matplotlib.pyplot as pl... | 0.765856 | 0.612657 |
from . import db, login_manager
from flask_login import UserMixin
from werkzeug.security import generate_password_hash,check_password_hash
@login_manager.user_loader
def load_user(user_id):
return User.query.get(int(user_id))
class User(UserMixin,db.Model):
__tablename__ = 'users'
id = db.Column(db.Intege... | app/models.py | from . import db, login_manager
from flask_login import UserMixin
from werkzeug.security import generate_password_hash,check_password_hash
@login_manager.user_loader
def load_user(user_id):
return User.query.get(int(user_id))
class User(UserMixin,db.Model):
__tablename__ = 'users'
id = db.Column(db.Intege... | 0.408159 | 0.057361 |
import io
import unittest
from advisor.makefile_scanner import MakefileScanner
from advisor.report import Report
class TestMakefileScanner(unittest.TestCase):
def test_accepts_file(self):
makefile_scanner = MakefileScanner()
self.assertFalse(makefile_scanner.accepts_file('test'))
self.asse... | unittest/test_makefile_scanner.py | import io
import unittest
from advisor.makefile_scanner import MakefileScanner
from advisor.report import Report
class TestMakefileScanner(unittest.TestCase):
def test_accepts_file(self):
makefile_scanner = MakefileScanner()
self.assertFalse(makefile_scanner.accepts_file('test'))
self.asse... | 0.307254 | 0.309148 |
from django.utils import timezone
from django import forms
from django.contrib.auth.models import User
from datetimewidget.widgets import DateWidget
from .models import Patient, Hospital, Doctor, Nurse
class UserRegForm(forms.ModelForm):
"""
Form for user registration
"""
password = forms.CharField(... | HealthNet/core/forms.py | from django.utils import timezone
from django import forms
from django.contrib.auth.models import User
from datetimewidget.widgets import DateWidget
from .models import Patient, Hospital, Doctor, Nurse
class UserRegForm(forms.ModelForm):
"""
Form for user registration
"""
password = forms.CharField(... | 0.632503 | 0.116915 |
from django.contrib import messages
from django.contrib.auth.mixins import LoginRequiredMixin
from django.contrib.messages.views import SuccessMessageMixin
from django.contrib.sites.models import Site
from django.urls import reverse
from django.utils.translation import gettext_lazy as _
from django.views.generic import... | one/contrib/sites/settings/views.py | from django.contrib import messages
from django.contrib.auth.mixins import LoginRequiredMixin
from django.contrib.messages.views import SuccessMessageMixin
from django.contrib.sites.models import Site
from django.urls import reverse
from django.utils.translation import gettext_lazy as _
from django.views.generic import... | 0.492432 | 0.079246 |
from geopy.distance import distance
import os
import gdal
import osr
import re
from reader.gdal_reader import GdalReader
import numpy as np
def rename_files(files, name=None):
"""
Given a list of file paths for elevation files, this function will rename
those files to the format required by the pyDEM pac... | pydem/utils.py | from geopy.distance import distance
import os
import gdal
import osr
import re
from reader.gdal_reader import GdalReader
import numpy as np
def rename_files(files, name=None):
"""
Given a list of file paths for elevation files, this function will rename
those files to the format required by the pyDEM pac... | 0.819713 | 0.496948 |
import numpy as np
import numpy.linalg as linalg
class HomogeneousCoordinate(np.ndarray):
def __new__(cls, *args, **kwargs):
# creates an array with the homogeneous coordinates
obj = np.zeros(4, dtype=float).view(cls)
return obj
def __init__(self, x=0, y=0, z=0, w=0):
# assign... | pycg/pycg.py | import numpy as np
import numpy.linalg as linalg
class HomogeneousCoordinate(np.ndarray):
def __new__(cls, *args, **kwargs):
# creates an array with the homogeneous coordinates
obj = np.zeros(4, dtype=float).view(cls)
return obj
def __init__(self, x=0, y=0, z=0, w=0):
# assign... | 0.892393 | 0.621053 |
import SimpleITK as sitk
import numpy as np
from disptools import *
def create_target_volume(image: sitk.Image, atrophy_rate: float):
r""" Create a target volume map for the PREDICT tool.
Given an input segmentation map, create mask target volume map for the
PREDICT tool, with the given atrophy rate. The ... | disptools/predict.py | import SimpleITK as sitk
import numpy as np
from disptools import *
def create_target_volume(image: sitk.Image, atrophy_rate: float):
r""" Create a target volume map for the PREDICT tool.
Given an input segmentation map, create mask target volume map for the
PREDICT tool, with the given atrophy rate. The ... | 0.94379 | 0.793466 |
import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
def init_weights(m, gain):
if (type(m) == nn.Linear) | (type(m) == nn.Conv2d):
nn.init.orthogonal_(m.weight, gain)
nn.init.zeros_(m.bias)
class CNNDeepmind(nn.Module):
def __init__(self, observation_space, ... | Archive/appendix/Atari/baseline-QR-DQN/cnn_deepmind.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
def init_weights(m, gain):
if (type(m) == nn.Linear) | (type(m) == nn.Conv2d):
nn.init.orthogonal_(m.weight, gain)
nn.init.zeros_(m.bias)
class CNNDeepmind(nn.Module):
def __init__(self, observation_space, ... | 0.941594 | 0.555797 |
import json
import os
import sqlite3
import dash_bootstrap_components as dbc
import dash_core_components as dcc
import dash_cytoscape as cyto
import dash_html_components as html
import dash_table
import networkx as nx
import pandas as pd
from OmicsIntegrator import Graph
from dash.dash import no_update
from dash.depen... | dash_app/pages/vis.py | import json
import os
import sqlite3
import dash_bootstrap_components as dbc
import dash_core_components as dcc
import dash_cytoscape as cyto
import dash_html_components as html
import dash_table
import networkx as nx
import pandas as pd
from OmicsIntegrator import Graph
from dash.dash import no_update
from dash.depen... | 0.586641 | 0.157979 |
import __builtin__
import sys
from __mimic.util import patch
import unittest
class BuiltinPatchTest(unittest.TestCase):
"""Unit tests for Patch."""
def setUp(self):
self._patch = None
def tearDown(self):
if self._patch:
self._patch.Remove()
def testPatch(self):
self._patch = patch.Built... | __mimic/util/tests/patch_test.py | import __builtin__
import sys
from __mimic.util import patch
import unittest
class BuiltinPatchTest(unittest.TestCase):
"""Unit tests for Patch."""
def setUp(self):
self._patch = None
def tearDown(self):
if self._patch:
self._patch.Remove()
def testPatch(self):
self._patch = patch.Built... | 0.527803 | 0.444444 |
# Copyright: (c) 2018, <NAME> <<EMAIL>>
# GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt)
ANSIBLE_METADATA = {
'metadata_version': '1.1',
'status': ['preview'],
'supported_by': 'community'
}
DOCUMENTATION = '''
---
module: tetration_software_agent
short_descrip... | library/tetration_software_agent.py |
# Copyright: (c) 2018, <NAME> <<EMAIL>>
# GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt)
ANSIBLE_METADATA = {
'metadata_version': '1.1',
'status': ['preview'],
'supported_by': 'community'
}
DOCUMENTATION = '''
---
module: tetration_software_agent
short_descrip... | 0.819244 | 0.23699 |
from __future__ import absolute_import
import re # noqa: F401
# python 2 and python 3 compatibility library
import six
from swagger_client.api_client import ApiClient
class RepositoryApi(object):
"""NOTE: This class is auto generated by the swagger code generator program.
Do not edit the class manually.
... | swagger_client/api/repository_api.py | from __future__ import absolute_import
import re # noqa: F401
# python 2 and python 3 compatibility library
import six
from swagger_client.api_client import ApiClient
class RepositoryApi(object):
"""NOTE: This class is auto generated by the swagger code generator program.
Do not edit the class manually.
... | 0.704668 | 0.048047 |
import numpy as np
def binary_repr(x):
return list(reversed([int(e) for e in np.binary_repr(x)]))
class Reduction1:
def __init__(self, modulus):
self.p = modulus
# Next power of 2
self.k = p.bit_length()
self.table = {}
for l in range(self.k, self.k*2):
sel... | rust/crypto-primitives/mod_mul.py | import numpy as np
def binary_repr(x):
return list(reversed([int(e) for e in np.binary_repr(x)]))
class Reduction1:
def __init__(self, modulus):
self.p = modulus
# Next power of 2
self.k = p.bit_length()
self.table = {}
for l in range(self.k, self.k*2):
sel... | 0.23793 | 0.52409 |
from lib.canvas import Canvas
from lib.figure import Figure
import pickle
def _offset_rounding_error(figure):
""" """
fig = []
pre_part = []
for line in figure:
if not pre_part == []:
fig.append((pre_part[3], line[1], line[2], line[3]))
else:
fig.append(line)
... | example.py | from lib.canvas import Canvas
from lib.figure import Figure
import pickle
def _offset_rounding_error(figure):
""" """
fig = []
pre_part = []
for line in figure:
if not pre_part == []:
fig.append((pre_part[3], line[1], line[2], line[3]))
else:
fig.append(line)
... | 0.609989 | 0.455622 |
import os
import time as t
import numpy as np
if os.name == 'nt':
import msvcrt
def getch():
return msvcrt.getch().decode()
else:
import sys, tty, termios
fd = sys.stdin.fileno()
old_settings = termios.tcgetattr(fd)
def getch():
try:
tty.setraw(sys.stdin.fileno())
... | R1-M2/src/lofaro_ventilator.py |
import os
import time as t
import numpy as np
if os.name == 'nt':
import msvcrt
def getch():
return msvcrt.getch().decode()
else:
import sys, tty, termios
fd = sys.stdin.fileno()
old_settings = termios.tcgetattr(fd)
def getch():
try:
tty.setraw(sys.stdin.fileno())
... | 0.289874 | 0.108519 |
from keras.models import Sequential, Model
from keras.layers import Embedding, LSTM, Flatten, Dense, BatchNormalization, \
Activation, Dropout, concatenate, Lambda, Reshape, Conv2D, MaxPooling2D, TimeDistributed
from keras.constraints import maxnorm
from keras.optimizers import rmsprop, TFOptimizer, Adam, Adadelta
... | models.py | from keras.models import Sequential, Model
from keras.layers import Embedding, LSTM, Flatten, Dense, BatchNormalization, \
Activation, Dropout, concatenate, Lambda, Reshape, Conv2D, MaxPooling2D, TimeDistributed
from keras.constraints import maxnorm
from keras.optimizers import rmsprop, TFOptimizer, Adam, Adadelta
... | 0.675765 | 0.251912 |
import getpass
import sys
import cryptography.hazmat.backends as backends
import cryptography.hazmat.primitives.asymmetric.rsa as rsa
import cryptography.hazmat.primitives.serialization as serial
import cryptography.hazmat.primitives.hashes as hashes
import cryptography.hazmat.primitives as primitives
import cryptograp... | Testing/cryptographic/crypto.py | import getpass
import sys
import cryptography.hazmat.backends as backends
import cryptography.hazmat.primitives.asymmetric.rsa as rsa
import cryptography.hazmat.primitives.serialization as serial
import cryptography.hazmat.primitives.hashes as hashes
import cryptography.hazmat.primitives as primitives
import cryptograp... | 0.297776 | 0.118947 |
import json
import sys
import Pyro4
import subscriber
import publisher
def subscriber_dict_to_class(classname, d):
print('deserializing {}'.format(d))
return subscriber.Subscriber(d['name'])
def publisher_dict_to_class(classname, d):
p = publisher.Publisher(d['name'], d['event'])
p.intermediary = d['i... | Python/intermediary.py | import json
import sys
import Pyro4
import subscriber
import publisher
def subscriber_dict_to_class(classname, d):
print('deserializing {}'.format(d))
return subscriber.Subscriber(d['name'])
def publisher_dict_to_class(classname, d):
p = publisher.Publisher(d['name'], d['event'])
p.intermediary = d['i... | 0.455925 | 0.130285 |
import math
import operator
import pytest
from capacity import MiB, byte, GiB, KiB, Capacity, bit, from_string, MB, GB, PiB, __version__
from numbers import Integral
from operator import truediv
from .utils import assert_value_error
def test_version():
assert isinstance(__version__.__version__, str)
def test_0... | tests/test_capacity.py | import math
import operator
import pytest
from capacity import MiB, byte, GiB, KiB, Capacity, bit, from_string, MB, GB, PiB, __version__
from numbers import Integral
from operator import truediv
from .utils import assert_value_error
def test_version():
assert isinstance(__version__.__version__, str)
def test_0... | 0.710126 | 0.80038 |
import argparse
from collections import defaultdict
from os import remove
from random import randrange
import genanki
from pycasia import CASIA
from hsk import HSK
from models import get_model
EXAMPLE_COUNT = 50
def create_deck(name, character_list=None, example_count=30):
"""
Create a deck with the given ... | main.py | import argparse
from collections import defaultdict
from os import remove
from random import randrange
import genanki
from pycasia import CASIA
from hsk import HSK
from models import get_model
EXAMPLE_COUNT = 50
def create_deck(name, character_list=None, example_count=30):
"""
Create a deck with the given ... | 0.610802 | 0.322366 |
import base64
from odoo import _, api, fields, models
from odoo.exceptions import UserError, ValidationError
class AccountPaymentOrder(models.Model):
_name = "account.payment.order"
_description = "Payment Order"
_inherit = ["mail.thread"]
_order = "id desc"
_check_company_auto = True
name ... | addons14/account_payment_order/models/account_payment_order.py |
import base64
from odoo import _, api, fields, models
from odoo.exceptions import UserError, ValidationError
class AccountPaymentOrder(models.Model):
_name = "account.payment.order"
_description = "Payment Order"
_inherit = ["mail.thread"]
_order = "id desc"
_check_company_auto = True
name ... | 0.578091 | 0.225715 |
import sys
from oslo_config import cfg
from oslo_log import log as logging
from kuryr_kubernetes.cmd.sanity import checks
from kuryr_kubernetes import config
from kuryr_kubernetes.controller.drivers import vif_pool # noqa
LOG = logging.getLogger(__name__)
class BoolOptCallback(cfg.BoolOpt):
def __init__(self,... | kuryr_kubernetes/cmd/sanity_checks.py | import sys
from oslo_config import cfg
from oslo_log import log as logging
from kuryr_kubernetes.cmd.sanity import checks
from kuryr_kubernetes import config
from kuryr_kubernetes.controller.drivers import vif_pool # noqa
LOG = logging.getLogger(__name__)
class BoolOptCallback(cfg.BoolOpt):
def __init__(self,... | 0.372277 | 0.066478 |
from crummycm.validation.types.values.base import BaseValue
import operator
class Numeric(BaseValue):
def __init__(
self,
default_value=None,
is_type=None,
required=None,
description=None,
fn=None,
fn_kwargs=None,
# specific
bounds=None,
... | src/crummycm/validation/types/values/element/numeric.py | from crummycm.validation.types.values.base import BaseValue
import operator
class Numeric(BaseValue):
def __init__(
self,
default_value=None,
is_type=None,
required=None,
description=None,
fn=None,
fn_kwargs=None,
# specific
bounds=None,
... | 0.755907 | 0.199503 |
# Importamos la librería
import pygame
import sys
import random
from math import sqrt,exp
# Importamos constantes locales de pygame
from pygame.locals import *
from aux import *
sprites_serp = pygame.sprite.Group()
manzanas = pygame.sprite.Group()
# Establecemos el largo y alto de cada segmento de la serpiente
... | snake.py |
# Importamos la librería
import pygame
import sys
import random
from math import sqrt,exp
# Importamos constantes locales de pygame
from pygame.locals import *
from aux import *
sprites_serp = pygame.sprite.Group()
manzanas = pygame.sprite.Group()
# Establecemos el largo y alto de cada segmento de la serpiente
... | 0.14777 | 0.38341 |
from ixnetwork_restpy.base import Base
from ixnetwork_restpy.files import Files
from typing import List, Any, Union
class Dcc(Base):
"""The Layer 1 Configuration is being configured for a POS port and DCC is selected as the Payload Type.
The Dcc class encapsulates a required dcc resource which will be retriev... | ixnetwork_restpy/testplatform/sessions/ixnetwork/vport/l1config/pos/dcc/dcc.py | from ixnetwork_restpy.base import Base
from ixnetwork_restpy.files import Files
from typing import List, Any, Union
class Dcc(Base):
"""The Layer 1 Configuration is being configured for a POS port and DCC is selected as the Payload Type.
The Dcc class encapsulates a required dcc resource which will be retriev... | 0.89654 | 0.372163 |
# ==================================================
# Import
import pytest
import random
import math
# ==================================================
# Phase 1
def phase1(X, k, d):
# Initiation
n = len(X)
random.shuffle(X)
S = X[:k]
XS = X[k:]
S.sort()
# Keeping the list entri... | tests/phase2_test.py | # ==================================================
# Import
import pytest
import random
import math
# ==================================================
# Phase 1
def phase1(X, k, d):
# Initiation
n = len(X)
random.shuffle(X)
S = X[:k]
XS = X[k:]
S.sort()
# Keeping the list entri... | 0.128225 | 0.46035 |
import numpy as np
import pandas as pd
import os
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import seaborn as sns
sns.set()
from sklearn.ensemble import ExtraTreesRegressor
from sklearn.linear_model import Ridge, LinearRegression
from sklearn.model_selection import train_test_split
from skl... | BayOptPy/freesurfer_preprocess/original_dataset/UKBIO/tpot_model_analysis_4614144.py | import numpy as np
import pandas as pd
import os
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import seaborn as sns
sns.set()
from sklearn.ensemble import ExtraTreesRegressor
from sklearn.linear_model import Ridge, LinearRegression
from sklearn.model_selection import train_test_split
from skl... | 0.733261 | 0.508666 |
import numpy as np
import pandas as pd
from sklearn.base import BaseEstimator, TransformerMixin
class FeatureSelector(BaseEstimator, TransformerMixin):
"""This transformer select features.
Attributes
----------
columns: list of columns to transformer [n_columns]
Examples
--------
For us... | mlearner/preprocessing/feature_selector.py | import numpy as np
import pandas as pd
from sklearn.base import BaseEstimator, TransformerMixin
class FeatureSelector(BaseEstimator, TransformerMixin):
"""This transformer select features.
Attributes
----------
columns: list of columns to transformer [n_columns]
Examples
--------
For us... | 0.884139 | 0.506958 |
import uuid
import re
import base64
class Streamlit_elements():
def mymarkdown(object, number, text):
form = """<style type="text/css">
.low {
color: #585858;
position: relative;
bottom: 1ex;
font-size: 60%;
... | elements/elements.py | import uuid
import re
import base64
class Streamlit_elements():
def mymarkdown(object, number, text):
form = """<style type="text/css">
.low {
color: #585858;
position: relative;
bottom: 1ex;
font-size: 60%;
... | 0.287268 | 0.091301 |