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 math
import os
import pytest
import subprocess
import time
from watchtower.streamer.writer import dropbox_writer
from watchtower.streamer.writer.disk_writer import DiskWriter
def test_dropbox_writer_integration(writer, random_data, tmp_path):
"""
Integration test to feed a DropboxWriter chunks of data ... | watchtower/tests/streamer/writer/test_dropbox_writer.py | import math
import os
import pytest
import subprocess
import time
from watchtower.streamer.writer import dropbox_writer
from watchtower.streamer.writer.disk_writer import DiskWriter
def test_dropbox_writer_integration(writer, random_data, tmp_path):
"""
Integration test to feed a DropboxWriter chunks of data ... | 0.392803 | 0.405684 |
__all__ = ('SpoonAnalyser',)
from typing import Any, Iterator, List, Mapping, Sequence
import contextlib
import json
import os
import shlex
import subprocess
from dockerblade import DockerDaemon as DockerBladeDockerDaemon
from loguru import logger
import attr
from .analysis import SpoonFunction, SpoonStatement
from ... | lib/kaskara/spoon/analyser.py | __all__ = ('SpoonAnalyser',)
from typing import Any, Iterator, List, Mapping, Sequence
import contextlib
import json
import os
import shlex
import subprocess
from dockerblade import DockerDaemon as DockerBladeDockerDaemon
from loguru import logger
import attr
from .analysis import SpoonFunction, SpoonStatement
from ... | 0.687945 | 0.09236 |
import os
import sys
import ctypes
from decouple import config
target_dir = config('CARGO_TARGET_DIR', os.path.join(os.path.dirname(__file__), '../../target'))
build_profile = config('BUILD_PROFILE', 'debug')
ext = 'dylib' if sys.platform == 'darwin' else 'so'
dll = ctypes.cdll.LoadLibrary(os.path.join(target_dir, '%... | integration-tests/bot/chainbinding.py | import os
import sys
import ctypes
from decouple import config
target_dir = config('CARGO_TARGET_DIR', os.path.join(os.path.dirname(__file__), '../../target'))
build_profile = config('BUILD_PROFILE', 'debug')
ext = 'dylib' if sys.platform == 'darwin' else 'so'
dll = ctypes.cdll.LoadLibrary(os.path.join(target_dir, '%... | 0.188548 | 0.064418 |
import pytest
import datetime
from dateutil.tz import tzoffset
from decimal import Decimal
from pyticketswitch.mixins import JSONMixin, PaginationMixin, SeatPricingMixin
class TestJSONMixin:
ZULU = tzoffset('ZULU', 0)
class Foo(JSONMixin, object):
def __init__(self, bar):
self.bar = bar... | tests/test_mixins.py | import pytest
import datetime
from dateutil.tz import tzoffset
from decimal import Decimal
from pyticketswitch.mixins import JSONMixin, PaginationMixin, SeatPricingMixin
class TestJSONMixin:
ZULU = tzoffset('ZULU', 0)
class Foo(JSONMixin, object):
def __init__(self, bar):
self.bar = bar... | 0.719186 | 0.458834 |
from hdmm.workload import *
from hdmm import templates
def __race1():
# single race only, two or more races aggregated
# binary encoding: 1 indicates particular race is checked
race1 = np.zeros((7, 64))
for i in range(6):
race1[i, 2**i] = 1.0
race1[6,:] = 1.0 - race1[0:6].sum(axis=0)
re... | hdmm/examples/census.py | from hdmm.workload import *
from hdmm import templates
def __race1():
# single race only, two or more races aggregated
# binary encoding: 1 indicates particular race is checked
race1 = np.zeros((7, 64))
for i in range(6):
race1[i, 2**i] = 1.0
race1[6,:] = 1.0 - race1[0:6].sum(axis=0)
re... | 0.428233 | 0.513181 |
from pathlib import Path
import sys
import cv2
import depthai as dai
import numpy as np
import time
'''
Mobilenet SSD device side decoding demo
The "mobilenet-ssd" model is a Single-Shot multibox Detection (SSD) network intended
to perform object detection. This model is implemented using the Caffe* framework.
... | code/02_tripple_mobilenet.py |
from pathlib import Path
import sys
import cv2
import depthai as dai
import numpy as np
import time
'''
Mobilenet SSD device side decoding demo
The "mobilenet-ssd" model is a Single-Shot multibox Detection (SSD) network intended
to perform object detection. This model is implemented using the Caffe* framework.
... | 0.633864 | 0.333965 |
import sys
import unittest
import pybullet
from qibullet import SimulationManager
from qibullet import NaoVirtual, PepperVirtual, RomeoVirtual
from qibullet import Camera, CameraRgb, CameraDepth, CameraResolution
class CameraTest(unittest.TestCase):
"""
Unittests for virtual cameras (virtual class, don't use ... | tests/camera_test.py | import sys
import unittest
import pybullet
from qibullet import SimulationManager
from qibullet import NaoVirtual, PepperVirtual, RomeoVirtual
from qibullet import Camera, CameraRgb, CameraDepth, CameraResolution
class CameraTest(unittest.TestCase):
"""
Unittests for virtual cameras (virtual class, don't use ... | 0.705176 | 0.862728 |
import functools
import itertools
import operator
import unittest
import dual
@functools.lru_cache(maxsize=None)
def stirling(n, k):
# [[https://en.wikipedia.org/wiki/Stirling_numbers_of_the_second_kind]]
if n == 0 and k == 0:
return 1
elif n == 0 or k == 0:
return 0
else:
return stirling(n-1, k-1... | test.py | import functools
import itertools
import operator
import unittest
import dual
@functools.lru_cache(maxsize=None)
def stirling(n, k):
# [[https://en.wikipedia.org/wiki/Stirling_numbers_of_the_second_kind]]
if n == 0 and k == 0:
return 1
elif n == 0 or k == 0:
return 0
else:
return stirling(n-1, k-1... | 0.541651 | 0.510069 |
import os
import boto3
from botocore.exceptions import NoCredentialsError
from flask import Flask, redirect, Blueprint, request, url_for, render_template, flash
from flask_login import current_user, login_required, login_user, logout_user
from werkzeug.utils import secure_filename
from datetime import datetime, date,... | views/admin.py |
import os
import boto3
from botocore.exceptions import NoCredentialsError
from flask import Flask, redirect, Blueprint, request, url_for, render_template, flash
from flask_login import current_user, login_required, login_user, logout_user
from werkzeug.utils import secure_filename
from datetime import datetime, date,... | 0.308086 | 0.043244 |
import os
import xlsxwriter
import time
import pickle
import random
import numpy as np
import matplotlib.pyplot as plt
from classes.quiz import Quiz
from classes.save import Save
from classes.result import Overall_Results, Result
from classes.answer import Picture_Answer, Text_Answer, Answer
from classes.school import... | main.py | import os
import xlsxwriter
import time
import pickle
import random
import numpy as np
import matplotlib.pyplot as plt
from classes.quiz import Quiz
from classes.save import Save
from classes.result import Overall_Results, Result
from classes.answer import Picture_Answer, Text_Answer, Answer
from classes.school import... | 0.380529 | 0.277479 |
import argparse
import glob
import json
import os
import shlex
import shutil
import subprocess
import sys
import tarfile
import tempfile
def create_env(name, pkgs, channel=None, yes=False):
cmd = 'conda create --name {name}'.format(name=name)
if channel:
cmd = '{cmd} --channel {channel}'.format(cmd=cm... | openmdao.devtools/src/openmdao/devtools/conda_build.py | import argparse
import glob
import json
import os
import shlex
import shutil
import subprocess
import sys
import tarfile
import tempfile
def create_env(name, pkgs, channel=None, yes=False):
cmd = 'conda create --name {name}'.format(name=name)
if channel:
cmd = '{cmd} --channel {channel}'.format(cmd=cm... | 0.203233 | 0.083143 |
from __future__ import absolute_import, unicode_literals
from collections import defaultdict
from datetime import timedelta
from django.conf import settings
from celery import states
from celery.events.state import Task
from celery.events.snapshot import Polaroid
from celery.five import monotonic
from celery.utils.l... | djcelery/snapshot.py | from __future__ import absolute_import, unicode_literals
from collections import defaultdict
from datetime import timedelta
from django.conf import settings
from celery import states
from celery.events.state import Task
from celery.events.snapshot import Polaroid
from celery.five import monotonic
from celery.utils.l... | 0.623377 | 0.110759 |
from unittest import TestCase
from unittest.mock import MagicMock
from pyramid.config import Configurator
from pyramid_restful.routers import ViewSetRouter, Route
from pyramid_restful.viewsets import ModelCRUDViewSet, APIViewSet
from pyramid_restful.exceptions import ImproperlyConfigured
class MyCRUDViewSet(ModelCR... | tests/test_routers.py | from unittest import TestCase
from unittest.mock import MagicMock
from pyramid.config import Configurator
from pyramid_restful.routers import ViewSetRouter, Route
from pyramid_restful.viewsets import ModelCRUDViewSet, APIViewSet
from pyramid_restful.exceptions import ImproperlyConfigured
class MyCRUDViewSet(ModelCR... | 0.667906 | 0.316316 |
import sys
import os
from ngsutils.gtf import GTF
def usage(msg=None):
if msg:
print '%s\n' % msg
print __doc__
print '''\
Usage: gtfutils tobed [type] filename.gtf{.gz}
Where type is one of:
-genes The gene from start to end (including introns)
-exons Each annotated exon
-intro... | ngsutils/gtf/tobed.py | import sys
import os
from ngsutils.gtf import GTF
def usage(msg=None):
if msg:
print '%s\n' % msg
print __doc__
print '''\
Usage: gtfutils tobed [type] filename.gtf{.gz}
Where type is one of:
-genes The gene from start to end (including introns)
-exons Each annotated exon
-intro... | 0.203985 | 0.370112 |
import inspect
import torch
import warnings
from pd_mesh_net.models import (DualPrimalMeshClassifier,
DualPrimalMeshSegmenter,
DualPrimalUNetMeshSegmenter)
def create_model(model_name, should_initialize_weights, **model_params):
r"""Creates an insta... | pd_mesh_net/utils/models.py | import inspect
import torch
import warnings
from pd_mesh_net.models import (DualPrimalMeshClassifier,
DualPrimalMeshSegmenter,
DualPrimalUNetMeshSegmenter)
def create_model(model_name, should_initialize_weights, **model_params):
r"""Creates an insta... | 0.917474 | 0.467271 |
import os
import json
import math
import time
import torch
from torch.utils.data import (DataLoader, SequentialSampler)
import numpy as np
from tqdm import tqdm
import pickle
from scipy.sparse import coo_matrix
from scipy.sparse.csgraph import connected_components
from special_partition.special_partition import cluste... | blink/biencoder/eval_cluster_linking.py |
import os
import json
import math
import time
import torch
from torch.utils.data import (DataLoader, SequentialSampler)
import numpy as np
from tqdm import tqdm
import pickle
from scipy.sparse import coo_matrix
from scipy.sparse.csgraph import connected_components
from special_partition.special_partition import cluste... | 0.755817 | 0.368576 |
import threading
import gzip
import time
from autobahn.twisted.websocket import WebSocketClientFactory, WebSocketClientProtocol, connectWS
from twisted.internet import reactor, ssl
from twisted.internet.protocol import ReconnectingClientFactory
from twisted.internet.error import ReactorAlreadyRunning
import ujson as... | bitrue/websockets.py |
import threading
import gzip
import time
from autobahn.twisted.websocket import WebSocketClientFactory, WebSocketClientProtocol, connectWS
from twisted.internet import reactor, ssl
from twisted.internet.protocol import ReconnectingClientFactory
from twisted.internet.error import ReactorAlreadyRunning
import ujson as... | 0.508544 | 0.053576 |
import pandas as pd, numpy as np
from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer
from sklearn import svm,metrics
from sklearn.calibration import CalibratedClassifierCV
from sklearn.model_selection import StratifiedKFold
column = "review"
train = pd.read_csv('./data/train.csv',lineterm... | clafiyy/new/baseline.py | import pandas as pd, numpy as np
from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer
from sklearn import svm,metrics
from sklearn.calibration import CalibratedClassifierCV
from sklearn.model_selection import StratifiedKFold
column = "review"
train = pd.read_csv('./data/train.csv',lineterm... | 0.187914 | 0.213029 |
import db_handler
import models
from Tkinter import Tk
def copy_to_clipboard(text):
r = Tk()
r.withdraw()
r.clipboard_clear()
r.clipboard_append(text)
r.destroy()
def print_member_details(member_id, email=None, use_prev_title=False):
''' Print the member details for the supplied ID
Subst... | common_modules/db_explorer.py | import db_handler
import models
from Tkinter import Tk
def copy_to_clipboard(text):
r = Tk()
r.withdraw()
r.clipboard_clear()
r.clipboard_append(text)
r.destroy()
def print_member_details(member_id, email=None, use_prev_title=False):
''' Print the member details for the supplied ID
Subst... | 0.185172 | 0.118793 |
from unittest import TestCase
import jwt
from piccolo.apps.user.tables import BaseUser
from starlette.exceptions import HTTPException
from starlette.routing import Route, Router
from starlette.testclient import TestClient
from piccolo_api.jwt_auth.middleware import JWTMiddleware
from piccolo_api.token_auth.tables imp... | tests/jwt_auth/test_jwt_middleware.py | from unittest import TestCase
import jwt
from piccolo.apps.user.tables import BaseUser
from starlette.exceptions import HTTPException
from starlette.routing import Route, Router
from starlette.testclient import TestClient
from piccolo_api.jwt_auth.middleware import JWTMiddleware
from piccolo_api.token_auth.tables imp... | 0.552057 | 0.338159 |
from typing import Text
import numpy as np
from numpy import ndarray
from oqupy.config import NpDtype
SIGMA = {"id":[[1, 0], [0, 1]],
"x":[[0, 1], [1, 0]],
"y":[[0, -1j], [1j, 0]],
"z":[[1, 0], [0, -1]],
"+":[[0, 1], [0, 0]],
"-":[[0, 0], [1, 0]]}
SPIN_DM = {"up":[[1, 0... | oqupy/operators.py | from typing import Text
import numpy as np
from numpy import ndarray
from oqupy.config import NpDtype
SIGMA = {"id":[[1, 0], [0, 1]],
"x":[[0, 1], [1, 0]],
"y":[[0, -1j], [1j, 0]],
"z":[[1, 0], [0, -1]],
"+":[[0, 1], [0, 0]],
"-":[[0, 0], [1, 0]]}
SPIN_DM = {"up":[[1, 0... | 0.899315 | 0.624408 |
import os
import pandas as pd
from src.config.labels import ALGORITHM_LABEL, CALIBRATION_LABEL, FAIRNESS_METRIC_LABEL, LAMBDA_LABEL, \
LAMBDA_VALUE_LABEL, EVALUATION_METRIC_LABEL, EVALUATION_VALUE_LABEL, EVALUATION_LIST_LABELS
from src.config.path_dir_files import data_results_path, ALL_FOLDS_FILE, ALL_RECOMMENDE... | src/processing/merge_results.py | import os
import pandas as pd
from src.config.labels import ALGORITHM_LABEL, CALIBRATION_LABEL, FAIRNESS_METRIC_LABEL, LAMBDA_LABEL, \
LAMBDA_VALUE_LABEL, EVALUATION_METRIC_LABEL, EVALUATION_VALUE_LABEL, EVALUATION_LIST_LABELS
from src.config.path_dir_files import data_results_path, ALL_FOLDS_FILE, ALL_RECOMMENDE... | 0.249264 | 0.164148 |
import numpy as np
import matplotlib.pyplot as plt
from python_codes.transformations import *
class MK2Robot(object):
HOME_0 = 0
HOME_1 = np.pi
def __init__(self, link_lengths):
self.a = link_lengths
self.q = []
self.T = []
self.pose = []
self.s = []
# self... | python_codes/mk2Robot.py | import numpy as np
import matplotlib.pyplot as plt
from python_codes.transformations import *
class MK2Robot(object):
HOME_0 = 0
HOME_1 = np.pi
def __init__(self, link_lengths):
self.a = link_lengths
self.q = []
self.T = []
self.pose = []
self.s = []
# self... | 0.569972 | 0.551211 |
import PlayCards
import CommonCardsType
# 该模块中list_list和Cardlist的内容一样
# 这个函数用于计算手牌中各种牌面的张数，接收一个手牌列表作为参数，返回一个记录各种牌面张数列表
def GetList_count(Cardlist=[]):
list_count = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
for item in Cardlist:
number = item[0]
list_count[number] = list_count[number] + 1
... | AutoPlayForShisanshui/SpecialCardsType.py | import PlayCards
import CommonCardsType
# 该模块中list_list和Cardlist的内容一样
# 这个函数用于计算手牌中各种牌面的张数，接收一个手牌列表作为参数，返回一个记录各种牌面张数列表
def GetList_count(Cardlist=[]):
list_count = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
for item in Cardlist:
number = item[0]
list_count[number] = list_count[number] + 1
... | 0.090809 | 0.201224 |
import requests
import json
from pprint import pprint
from glob import glob
from semantic_version import Version
import getpass
import sys
def main():
version = ""
with open('files/version.txt') as f:
version = f.read().strip()
base_url = 'https://api.github.com/repos/jyapayne/Electrify/release... | upload_release.py |
import requests
import json
from pprint import pprint
from glob import glob
from semantic_version import Version
import getpass
import sys
def main():
version = ""
with open('files/version.txt') as f:
version = f.read().strip()
base_url = 'https://api.github.com/repos/jyapayne/Electrify/release... | 0.127476 | 0.060613 |
import numpy as np
f1_alpha=1000 #set alpha of f1
f3_epsilon=1e-6 #set epsilon of f3
f45_q=10**8
def f1(x): #ellipsoid function
dim=x.shape[0] #dimension number
result=0
for i in range(dim):
result+=f1_alpha**(i/(dim-1))*x[i]**2
return result
def g1(x):
dim=x.shape[0]
result=np.zero... | functions.py | import numpy as np
f1_alpha=1000 #set alpha of f1
f3_epsilon=1e-6 #set epsilon of f3
f45_q=10**8
def f1(x): #ellipsoid function
dim=x.shape[0] #dimension number
result=0
for i in range(dim):
result+=f1_alpha**(i/(dim-1))*x[i]**2
return result
def g1(x):
dim=x.shape[0]
result=np.zero... | 0.214527 | 0.399724 |
from typing import Tuple, Union
import pandas as pd
from rdkit import Chem
from rdkit.Chem.Descriptors import ExactMolWt
from rdkit import rdBase
from rdkit.Chem.rdchem import Mol
functionality_smarts = {
"ols": "[C,c;!$(C=O)][OH]",
"aliphatic_ols": "[C;!$(C=O);!$([a])][OH]",
"acids": "[#6][#6](=[#8:4])(... | m2p/monomers.py |
from typing import Tuple, Union
import pandas as pd
from rdkit import Chem
from rdkit.Chem.Descriptors import ExactMolWt
from rdkit import rdBase
from rdkit.Chem.rdchem import Mol
functionality_smarts = {
"ols": "[C,c;!$(C=O)][OH]",
"aliphatic_ols": "[C;!$(C=O);!$([a])][OH]",
"acids": "[#6][#6](=[#8:4])(... | 0.799442 | 0.358943 |
import sys
import codecs
import re
pat = "\[.*?(\d)\]"
reg = re.compile(pat)
JSON = {}
def removeStems(s):
s = s.replace(u'。', '') # Dirty
idx = s.find("(")
if idx!= -1:
s = s[:idx]
return s.strip()
def getStem(s):
stem_r = re.search(ur'\(.+\)', s)
if stem_r:
... | txt/moedict.py |
import sys
import codecs
import re
pat = "\[.*?(\d)\]"
reg = re.compile(pat)
JSON = {}
def removeStems(s):
s = s.replace(u'。', '') # Dirty
idx = s.find("(")
if idx!= -1:
s = s[:idx]
return s.strip()
def getStem(s):
stem_r = re.search(ur'\(.+\)', s)
if stem_r:
... | 0.078722 | 0.180702 |
import math
import os
import random
from string import ascii_lowercase
import psutil
import torch
import torchvision
import torchvision.transforms.functional as F
from PIL import Image
from torch.utils.data import DataLoader, Dataset
from torchvision import transforms
from src.data.transforms import Crop, StatefulRan... | src/data/lrs2.py | import math
import os
import random
from string import ascii_lowercase
import psutil
import torch
import torchvision
import torchvision.transforms.functional as F
from PIL import Image
from torch.utils.data import DataLoader, Dataset
from torchvision import transforms
from src.data.transforms import Crop, StatefulRan... | 0.696991 | 0.300157 |
import xdl
import unittest
import numpy as np
import sys
from xdl.python.lib.datatype import *
from xdl.python.lib.graph import execute
try:
from xdl.python.backend.mxnet.mxnet_backend import *
except ImportError:
sys.exit(0)
def main():
dense = xdl.mock_dense_op(shape=[1, 16], value=0.01, name_="dense")
gear... | xdl/test/python/unit_test/backend/mxnet_backend_test.py |
import xdl
import unittest
import numpy as np
import sys
from xdl.python.lib.datatype import *
from xdl.python.lib.graph import execute
try:
from xdl.python.backend.mxnet.mxnet_backend import *
except ImportError:
sys.exit(0)
def main():
dense = xdl.mock_dense_op(shape=[1, 16], value=0.01, name_="dense")
gear... | 0.392453 | 0.407776 |
import numpy as np
from utils.unit_conversions import db_to_lin, lin_to_db
from utils import constants
import atm
def get_thermal_noise(bandwidth_hz, noise_figure_db=0, temp_ext_k=0):
"""
N = thermal_noise(bw,nf,t_ext)
Compute the total noise power, given the receiver's noise bandwidth, noise figure, and... | noise/model.py | import numpy as np
from utils.unit_conversions import db_to_lin, lin_to_db
from utils import constants
import atm
def get_thermal_noise(bandwidth_hz, noise_figure_db=0, temp_ext_k=0):
"""
N = thermal_noise(bw,nf,t_ext)
Compute the total noise power, given the receiver's noise bandwidth, noise figure, and... | 0.911642 | 0.610395 |
# --- imports -----------------------------------------------------------------
import torch.nn as nn
import tensorflow as tf
from network.wrappers.NetworkBase import NetworkBase
class ResNet(NetworkBase):
def __init__(self, network_type, loss, accuracy, lr, framework, training, trainable_layers=None, num_filt... | network/wrappers/ResNet.py |
# --- imports -----------------------------------------------------------------
import torch.nn as nn
import tensorflow as tf
from network.wrappers.NetworkBase import NetworkBase
class ResNet(NetworkBase):
def __init__(self, network_type, loss, accuracy, lr, framework, training, trainable_layers=None, num_filt... | 0.945676 | 0.467636 |
import numpy as np
from skimage.io import imread, imsave
import os
import sys
def color_transfer(content_img, style_img):
'''
Transfer style image color to content image.
Method described in https://arxiv.org/abs/1606.05897
Args:
content_img: type=ndarray, shape=(Wc,Hc,C=3)
s... | AGD_ST/search/util_visual/colortransfer.py | import numpy as np
from skimage.io import imread, imsave
import os
import sys
def color_transfer(content_img, style_img):
'''
Transfer style image color to content image.
Method described in https://arxiv.org/abs/1606.05897
Args:
content_img: type=ndarray, shape=(Wc,Hc,C=3)
s... | 0.432782 | 0.422922 |
import numpy as np
import tensorflow as tf
from sklearn.neighbors import KDTree
from tqdm import tqdm
from config import read_config
from data_loader import DataLoader
from sincnet import create_print_maker
def check_norms(vectors):
norms = [np.linalg.norm(v) for v in vectors]
assert abs(1 - min(norms)) < 1e... | test_print_maker.py | import numpy as np
import tensorflow as tf
from sklearn.neighbors import KDTree
from tqdm import tqdm
from config import read_config
from data_loader import DataLoader
from sincnet import create_print_maker
def check_norms(vectors):
norms = [np.linalg.norm(v) for v in vectors]
assert abs(1 - min(norms)) < 1e... | 0.663342 | 0.49939 |
from boto.s3.key import Key
from sdk_release_tools import log
from sdk_release_tools.versions import parse_major_minor
import os
__all__ = ['Delete', 'Download', 'Pin', 'Unpin', 'Upload', 'delete',
'download', 'pin', 'unpin', 'upload']
def absolute(root):
if not os.path.isabs(root):
root = os... | node_modules/twilio-sync/tools/sdk-release-tool/sdk_release_tools/ops.py | from boto.s3.key import Key
from sdk_release_tools import log
from sdk_release_tools.versions import parse_major_minor
import os
__all__ = ['Delete', 'Download', 'Pin', 'Unpin', 'Upload', 'delete',
'download', 'pin', 'unpin', 'upload']
def absolute(root):
if not os.path.isabs(root):
root = os... | 0.587352 | 0.121921 |
from rest_framework import viewsets, status, filters, generics
from rest_framework.response import Response
from obeflix_back.models import Video, Categoria
from obeflix_back.serializer import VideoSerializer, CategoriaSerializer, ListaVideoPorCategoriaSerializer
class VideosViewSet(viewsets.ModelViewSet):
"""Ex... | obeflix_back/views.py | from rest_framework import viewsets, status, filters, generics
from rest_framework.response import Response
from obeflix_back.models import Video, Categoria
from obeflix_back.serializer import VideoSerializer, CategoriaSerializer, ListaVideoPorCategoriaSerializer
class VideosViewSet(viewsets.ModelViewSet):
"""Ex... | 0.478041 | 0.146362 |
from user import User
from credentials import Credentials
import random
def greetings():
print(" __ __ ")
print(" /\ /\ | | | | ")
print("| | | | ________ | | | | _____ ")
print("| |____| | | _... | run.py | from user import User
from credentials import Credentials
import random
def greetings():
print(" __ __ ")
print(" /\ /\ | | | | ")
print("| | | | ________ | | | | _____ ")
print("| |____| | | _... | 0.290176 | 0.13759 |
import numpy as np
import math
from scipy.sparse import diags
from scipy import linalg
import matplotlib.pyplot as plt
import pandas as pd
from sklearn import metrics
import base64
# Material class defines a dictionary conditioning an information
# on material characteristics of each element layer
class Material:
d... | calc/htool.py | import numpy as np
import math
from scipy.sparse import diags
from scipy import linalg
import matplotlib.pyplot as plt
import pandas as pd
from sklearn import metrics
import base64
# Material class defines a dictionary conditioning an information
# on material characteristics of each element layer
class Material:
d... | 0.293202 | 0.342159 |
from __future__ import print_function
import copy
import json
import re
import traceback
import zipfile
import arrow
from passive_data_kit.models import DataPoint
from passive_data_kit_external_data.models import annotate_field
from ..utils import hash_content, encrypt_content, create_engagement_event, queue_batch... | importers/facebook.py |
from __future__ import print_function
import copy
import json
import re
import traceback
import zipfile
import arrow
from passive_data_kit.models import DataPoint
from passive_data_kit_external_data.models import annotate_field
from ..utils import hash_content, encrypt_content, create_engagement_event, queue_batch... | 0.38827 | 0.070144 |
import pytest
import pgdb
from test_02_submit_rider import generic_rider_insert
from test_03_submit_driver import generic_driver_insert
from test_04_matches import getMatcherActivityStats, getMatchRecord
@pytest.fixture
def pgdbConnMatchEngine(dbhost, db, matchengineuser):
return pgdb.connect(... | db/test/test_05_user_actions.py | import pytest
import pgdb
from test_02_submit_rider import generic_rider_insert
from test_03_submit_driver import generic_driver_insert
from test_04_matches import getMatcherActivityStats, getMatchRecord
@pytest.fixture
def pgdbConnMatchEngine(dbhost, db, matchengineuser):
return pgdb.connect(... | 0.342901 | 0.120905 |
import pandas as pd
class Dataset:
def __init__(self):
self.train_set = None
self.vocab_index = {}
self.index_vocab = {}
self.vocab_length = -1
def load_dataset(self):
self.train_set = pd.read_csv('data/dataset_annotated.csv', encoding='ISO-8859-1')
# print(tr... | dataset.py |
import pandas as pd
class Dataset:
def __init__(self):
self.train_set = None
self.vocab_index = {}
self.index_vocab = {}
self.vocab_length = -1
def load_dataset(self):
self.train_set = pd.read_csv('data/dataset_annotated.csv', encoding='ISO-8859-1')
# print(tr... | 0.328637 | 0.108519 |
import math
from collections import OrderedDict
import torch
import torch.nn as nn
from torch.utils import model_zoo
class CBR(nn.Module):
"""
This class defines the convolution layer with batch normalization and PReLU activation
"""
def __init__(self, n_in: int, n_out: int, k_size: int, stride: int... | src/daain/backbones/esp_net/layers.py | import math
from collections import OrderedDict
import torch
import torch.nn as nn
from torch.utils import model_zoo
class CBR(nn.Module):
"""
This class defines the convolution layer with batch normalization and PReLU activation
"""
def __init__(self, n_in: int, n_out: int, k_size: int, stride: int... | 0.967333 | 0.606061 |
import uuid
from datetime import date, datetime, timedelta
from typing import Dict, List, Optional, Union
import numpy as np
import pandas as pd
import pyarrow
from pydantic import StrictStr
from pydantic.typing import Literal
from tenacity import Retrying, retry_if_exception_type, stop_after_delay, wait_fixed
from f... | sdk/python/feast/infra/offline_stores/maxcompute.py | import uuid
from datetime import date, datetime, timedelta
from typing import Dict, List, Optional, Union
import numpy as np
import pandas as pd
import pyarrow
from pydantic import StrictStr
from pydantic.typing import Literal
from tenacity import Retrying, retry_if_exception_type, stop_after_delay, wait_fixed
from f... | 0.730482 | 0.225566 |
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('general_business', '0001_initial'),
('product', '0002_productpriceobj'),
]
operations = [
migrations.CreateModel(
name='P... | product/migrations/0003_auto_20210616_0915.py |
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('general_business', '0001_initial'),
('product', '0002_productpriceobj'),
]
operations = [
migrations.CreateModel(
name='P... | 0.506103 | 0.120387 |
import logging
import os
import webapp2
from webapp2_extras import jinja2
from appengine_module.cr_rev import controller
class BaseHandler(webapp2.RequestHandler):
"""Provide a cached Jinja environment to each request."""
def __init__(self, *args, **kwargs):
webapp2.RequestHandler.__init__(self, *args, **k... | appengine/cr_rev/appengine_module/cr_rev/views.py |
import logging
import os
import webapp2
from webapp2_extras import jinja2
from appengine_module.cr_rev import controller
class BaseHandler(webapp2.RequestHandler):
"""Provide a cached Jinja environment to each request."""
def __init__(self, *args, **kwargs):
webapp2.RequestHandler.__init__(self, *args, **k... | 0.709321 | 0.06724 |
import os
import cv2
import numpy as np
class Image:
'''
This class contains all the image utils for the package
but You can also use it.
Methods:
bgr_to_grey
bgr_to_rgb
resize
crop
read_img
read_video
'''
def __init__(self):
pass
d... | visionlib/utils/imgutils.py | import os
import cv2
import numpy as np
class Image:
'''
This class contains all the image utils for the package
but You can also use it.
Methods:
bgr_to_grey
bgr_to_rgb
resize
crop
read_img
read_video
'''
def __init__(self):
pass
d... | 0.825097 | 0.465873 |
from argparse import ArgumentParser
from tabulate import tabulate
from termcolor import colored
from taoist.read_project_dict import read_project_dict
from taoist.read_label_dict import read_label_dict
from taoist.parent_project import parent_project
async def run_task(args: ArgumentParser) -> None:
"""
Run ... | taoist/run_task.py |
from argparse import ArgumentParser
from tabulate import tabulate
from termcolor import colored
from taoist.read_project_dict import read_project_dict
from taoist.read_label_dict import read_label_dict
from taoist.parent_project import parent_project
async def run_task(args: ArgumentParser) -> None:
"""
Run ... | 0.348645 | 0.1382 |
from pipeline import phot_pipeline
from pipeline import spec_pipeline
from pipeline import analysis
from astropy.io import fits, ascii
import os
import matplotlib.pyplot as plt
import pdb
import numpy as np
def test_binning():
""" Test the binning function"""
x = np.linspace(0,10,1024)
y = np.random.randn(... | tshirt/tser_tests.py | from pipeline import phot_pipeline
from pipeline import spec_pipeline
from pipeline import analysis
from astropy.io import fits, ascii
import os
import matplotlib.pyplot as plt
import pdb
import numpy as np
def test_binning():
""" Test the binning function"""
x = np.linspace(0,10,1024)
y = np.random.randn(... | 0.546254 | 0.387227 |
import os
from pypeline.common.fileutils import missing_files
from pypeline.atomiccmd.builder import apply_options
from pypeline.nodes.adapterremoval import \
SE_AdapterRemovalNode, \
PE_AdapterRemovalNode, \
VERSION_14, \
VERSION_15
from pypeline.nodes.validation import \
ValidateFASTQFilesNode
... | pypeline/tools/bam_pipeline/parts/reads.py | import os
from pypeline.common.fileutils import missing_files
from pypeline.atomiccmd.builder import apply_options
from pypeline.nodes.adapterremoval import \
SE_AdapterRemovalNode, \
PE_AdapterRemovalNode, \
VERSION_14, \
VERSION_15
from pypeline.nodes.validation import \
ValidateFASTQFilesNode
... | 0.41561 | 0.255077 |
import sys
import queue
import numbers
import math
if len(sys.argv) != 2:
print("Help: {} <filename>".format(sys.argv[0]))
sys.exit(0)
class Number:
def __init__(self, number_string):
self.arr = [int(x) if x.isnumeric() else x for x in list(number_string)]
def process(self, spl... | puzzle/day18.py |
import sys
import queue
import numbers
import math
if len(sys.argv) != 2:
print("Help: {} <filename>".format(sys.argv[0]))
sys.exit(0)
class Number:
def __init__(self, number_string):
self.arr = [int(x) if x.isnumeric() else x for x in list(number_string)]
def process(self, spl... | 0.127925 | 0.125065 |
import os
import time
import json
import argparse
from deeprob.utils.data import DataStandardizer
from deeprob.spn.utils.statistics import compute_statistics
from deeprob.spn.structure.leaf import Bernoulli, Gaussian
from deeprob.spn.learning.wrappers import learn_estimator
from experiments.datasets import load_binar... | experiments/spn.py | import os
import time
import json
import argparse
from deeprob.utils.data import DataStandardizer
from deeprob.spn.utils.statistics import compute_statistics
from deeprob.spn.structure.leaf import Bernoulli, Gaussian
from deeprob.spn.learning.wrappers import learn_estimator
from experiments.datasets import load_binar... | 0.750918 | 0.26514 |
import os
BASE_DIR = os.path.dirname(os.path.abspath(__file__))
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = '<KEY>#@(*%7!*9#q%pgyedotv%lp@9nfbj'
ALLOWED_HOSTS = ['localhost', '127.0.0.1', 'rogue.iplantcollaborative.org', 'data.cyverse.org', '*']
# SECURITY WARNING: don't run with... | django/settings.py | import os
BASE_DIR = os.path.dirname(os.path.abspath(__file__))
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = '<KEY>#@(*%7!*9#q%pgyedotv%lp@9nfbj'
ALLOWED_HOSTS = ['localhost', '127.0.0.1', 'rogue.iplantcollaborative.org', 'data.cyverse.org', '*']
# SECURITY WARNING: don't run with... | 0.196518 | 0.097176 |
import torch.nn.functional as F
import geometry
import os
import numpy as np
import torch
import collections
def parse_intrinsics_hdf5(raw_data, trgt_sidelength=None, invert_y=False):
s = raw_data[...].tostring()
s = s.decode('utf-8')
lines = s.split('\n')
f, cx, cy, _ = map(float, lines[0].split())... | util.py | import torch.nn.functional as F
import geometry
import os
import numpy as np
import torch
import collections
def parse_intrinsics_hdf5(raw_data, trgt_sidelength=None, invert_y=False):
s = raw_data[...].tostring()
s = s.decode('utf-8')
lines = s.split('\n')
f, cx, cy, _ = map(float, lines[0].split())... | 0.557845 | 0.511595 |
from unittest.mock import Mock
import pytest
from airflow.models import DAG
from airflow.models.baseoperator import BaseOperator
from airflow.ti_deps.dep_context import DepContext
from airflow.ti_deps.deps.prev_dagrun_dep import PrevDagrunDep
from airflow.utils.state import State
from airflow.utils.timezone import ... | tests/ti_deps/deps/test_prev_dagrun_dep.py |
from unittest.mock import Mock
import pytest
from airflow.models import DAG
from airflow.models.baseoperator import BaseOperator
from airflow.ti_deps.dep_context import DepContext
from airflow.ti_deps.deps.prev_dagrun_dep import PrevDagrunDep
from airflow.utils.state import State
from airflow.utils.timezone import ... | 0.618089 | 0.462352 |
from server.custom_exceptions.input_missing import InputMissing
from server.custom_exceptions.input_not_int import InputNotInteger
from server.custom_exceptions.paper_trade_id_missing import PaperTradeIdMissing
from server.custom_exceptions.paper_trade_id_not_int import PaperTradeIdNotInt
from server.custom_exceptions.... | server/service_layer/implementation_classes/paper_trade_service.py | from server.custom_exceptions.input_missing import InputMissing
from server.custom_exceptions.input_not_int import InputNotInteger
from server.custom_exceptions.paper_trade_id_missing import PaperTradeIdMissing
from server.custom_exceptions.paper_trade_id_not_int import PaperTradeIdNotInt
from server.custom_exceptions.... | 0.760651 | 0.177205 |
import time
from pathlib import Path
import os
import numpy as np
from py_diff_pd.env.env_base import EnvBase
from py_diff_pd.common.common import create_folder, ndarray
from py_diff_pd.common.hex_mesh import generate_hex_mesh, hex2obj
from py_diff_pd.common.tet_mesh import generate_tet_mesh, tet2obj, tetrahedralize
... | python/py_diff_pd/env/bunny_env_3d.py | import time
from pathlib import Path
import os
import numpy as np
from py_diff_pd.env.env_base import EnvBase
from py_diff_pd.common.common import create_folder, ndarray
from py_diff_pd.common.hex_mesh import generate_hex_mesh, hex2obj
from py_diff_pd.common.tet_mesh import generate_tet_mesh, tet2obj, tetrahedralize
... | 0.555918 | 0.325668 |
import asyncio
import disnake
from typing import Dict, List
from disnake import RawMessageDeleteEvent, RawMessageUpdateEvent
from disnake.ext.commands import Bot
import utilities.random
from models.database.message import Message
from services.database.message_db import retrieve_copy_messages
from services.database.... | services/portal/transmission.py | import asyncio
import disnake
from typing import Dict, List
from disnake import RawMessageDeleteEvent, RawMessageUpdateEvent
from disnake.ext.commands import Bot
import utilities.random
from models.database.message import Message
from services.database.message_db import retrieve_copy_messages
from services.database.... | 0.72487 | 0.064535 |
"""E(x)hentai components."""
import os
import re
import requests
from bs4 import BeautifulSoup
import modules.misc as misc
from modules import exception
_LOGIN_URL = 'https://forums.e-hentai.org/index.php'
_ACCOUNT_URL = 'https://e-hentai.org/home.php'
_EXHENTAI_URL = 'https://exhentai.org/'
def _ban_checker(html:... | modules/ehentai/core.py | """E(x)hentai components."""
import os
import re
import requests
from bs4 import BeautifulSoup
import modules.misc as misc
from modules import exception
_LOGIN_URL = 'https://forums.e-hentai.org/index.php'
_ACCOUNT_URL = 'https://e-hentai.org/home.php'
_EXHENTAI_URL = 'https://exhentai.org/'
def _ban_checker(html:... | 0.412412 | 0.132178 |
import c4d
from c4d import utils
from c4d.modules import bodypaint
def main():
# Retrieves active UVSet
handle = bodypaint.GetActiveUVSet(doc, c4d.GETACTIVEUVSET_ALL)
if not handle:
print "No active UVSet!"
return
# Prints UVSet information
print "UV Handle Data:"
print "Hand... | scripts/release18/CallUVCommand.py |
import c4d
from c4d import utils
from c4d.modules import bodypaint
def main():
# Retrieves active UVSet
handle = bodypaint.GetActiveUVSet(doc, c4d.GETACTIVEUVSET_ALL)
if not handle:
print "No active UVSet!"
return
# Prints UVSet information
print "UV Handle Data:"
print "Hand... | 0.441914 | 0.09611 |
from biokbase.workspace.client import Workspace
import biokbase.auth
import os
from getpass import getpass
import json
import time
prod_ws = 'https://kbase.us/services/ws'
ci_ws = 'https://ci.kbase.us/services/ws'
ws_metadata = {
'is_temporary': False,
'narrative_nice_name': None
}
def fetch_narrative(nar_id,... | src/biokbase/narrative/tests/narrative_test_helper.py | from biokbase.workspace.client import Workspace
import biokbase.auth
import os
from getpass import getpass
import json
import time
prod_ws = 'https://kbase.us/services/ws'
ci_ws = 'https://ci.kbase.us/services/ws'
ws_metadata = {
'is_temporary': False,
'narrative_nice_name': None
}
def fetch_narrative(nar_id,... | 0.494873 | 0.188324 |
import os
import unittest
import json
import trebek
import entities
import fakeredis
import time
import datetime
# Reference this SO post on getting distances between strings:
# http://stackoverflow.com/a/1471603/98562
def get_clue_json():
with open('test-json-output.json') as json_data:
clue = json.load(j... | test_trebek.py | import os
import unittest
import json
import trebek
import entities
import fakeredis
import time
import datetime
# Reference this SO post on getting distances between strings:
# http://stackoverflow.com/a/1471603/98562
def get_clue_json():
with open('test-json-output.json') as json_data:
clue = json.load(j... | 0.443359 | 0.208703 |
import numpy as np
from nose.plugins.attrib import attr
from ion_functions.data.perf.test_performance import PerformanceTestCase
from ion_functions.data import adcp_functions as af
# Note, the VADCP related data products use the same internal functions as the
# family of beam wrapper functions (e.g. adcp_beam_eastwar... | ion_functions/data/perf/test_adcp_performance.py | import numpy as np
from nose.plugins.attrib import attr
from ion_functions.data.perf.test_performance import PerformanceTestCase
from ion_functions.data import adcp_functions as af
# Note, the VADCP related data products use the same internal functions as the
# family of beam wrapper functions (e.g. adcp_beam_eastwar... | 0.654453 | 0.540014 |
import copy
import logging
import os
import subprocess
import time
import traceback
from functools import wraps
from thundra import constants
from thundra.application.global_application_info_provider import GlobalApplicationInfoProvider
from thundra.compat import PY2, TimeoutError
from thundra.config import config_nam... | thundra/wrappers/aws_lambda/lambda_wrapper.py | import copy
import logging
import os
import subprocess
import time
import traceback
from functools import wraps
from thundra import constants
from thundra.application.global_application_info_provider import GlobalApplicationInfoProvider
from thundra.compat import PY2, TimeoutError
from thundra.config import config_nam... | 0.336222 | 0.042245 |
import time
from odoo.tests.common import TransactionCase
class TestHrAttendance(TransactionCase):
"""Tests for attendance date ranges validity"""
def setUp(self):
super(TestHrAttendance, self).setUp()
self.attendance = self.env["res.partner.attendance"]
self.test_partner = self.env... | base_attendance/tests/test_hr_attendance_constraints.py |
import time
from odoo.tests.common import TransactionCase
class TestHrAttendance(TransactionCase):
"""Tests for attendance date ranges validity"""
def setUp(self):
super(TestHrAttendance, self).setUp()
self.attendance = self.env["res.partner.attendance"]
self.test_partner = self.env... | 0.496338 | 0.295573 |
from django.db import models
from apps.ventas.producto.models import Producto
from datetime import datetime
# Create your models here.
date = datetime.now()
class Proveedor(models.Model):
"""[summary]
Args:
models ([Proveedor]): [Contiene la informacion de los proveedores]
"""
nombre_pro... | sysvet/apps/compras/models.py | from django.db import models
from apps.ventas.producto.models import Producto
from datetime import datetime
# Create your models here.
date = datetime.now()
class Proveedor(models.Model):
"""[summary]
Args:
models ([Proveedor]): [Contiene la informacion de los proveedores]
"""
nombre_pro... | 0.60964 | 0.207135 |
import numpy as np
def forward(Observation, Emission, Transition, Initial):
"""
Performs the forward algorithm for a hidden markov model:
Observation is a numpy.ndarray of shape (T,) that contains the index of
the observation
T is the number of observations
Emission is a numpy.ndarray of ... | unsupervised_learning/0x02-hmm/6-baum_welch.py | import numpy as np
def forward(Observation, Emission, Transition, Initial):
"""
Performs the forward algorithm for a hidden markov model:
Observation is a numpy.ndarray of shape (T,) that contains the index of
the observation
T is the number of observations
Emission is a numpy.ndarray of ... | 0.899723 | 0.930046 |
from pprint import pformat
from six import iteritems
import re
class V1ServiceSpec(object):
"""
NOTE: This class is auto generated by the swagger code generator program.
Do not edit the class manually.
"""
"""
Attributes:
swagger_types (dict): The key is attribute name and the value is attri... | mac/google-cloud-sdk/lib/third_party/kubernetes/client/models/v1_service_spec.py | from pprint import pformat
from six import iteritems
import re
class V1ServiceSpec(object):
"""
NOTE: This class is auto generated by the swagger code generator program.
Do not edit the class manually.
"""
"""
Attributes:
swagger_types (dict): The key is attribute name and the value is attri... | 0.680135 | 0.115761 |
from __future__ import print_function
import copy
import os
import shutil
import sys
import mock
from chromite.lib import constants
from chromite.cli import command_unittest
from chromite.cli.cros import cros_chrome_sdk
from chromite.lib import cache
from chromite.lib import cros_build_lib
from chromite.lib import c... | cli/cros/cros_chrome_sdk_unittest.py | from __future__ import print_function
import copy
import os
import shutil
import sys
import mock
from chromite.lib import constants
from chromite.cli import command_unittest
from chromite.cli.cros import cros_chrome_sdk
from chromite.lib import cache
from chromite.lib import cros_build_lib
from chromite.lib import c... | 0.525856 | 0.107531 |
from __clrclasses__.System.Runtime.CompilerServices import AccessedThroughPropertyAttribute
from __clrclasses__.System.Runtime.CompilerServices import AsyncStateMachineAttribute
from __clrclasses__.System.Runtime.CompilerServices import AsyncTaskMethodBuilder
from __clrclasses__.System.Runtime.CompilerServices import A... | extensions/.stubs/clrclasses/System/Runtime/CompilerServices/__init__.py | from __clrclasses__.System.Runtime.CompilerServices import AccessedThroughPropertyAttribute
from __clrclasses__.System.Runtime.CompilerServices import AsyncStateMachineAttribute
from __clrclasses__.System.Runtime.CompilerServices import AsyncTaskMethodBuilder
from __clrclasses__.System.Runtime.CompilerServices import A... | 0.613121 | 0.031232 |
import os
import torch
import torch.nn.functional as F
import yaml
import copy
from ast import literal_eval
from typing import Callable, Iterable, List, TypeVar
import torch.distributed as dist
from typing import Tuple
import argparse
A = TypeVar("A")
B = TypeVar("B")
class TimeDistributed(torch.nn.Module):
"""
... | src/util.py | import os
import torch
import torch.nn.functional as F
import yaml
import copy
from ast import literal_eval
from typing import Callable, Iterable, List, TypeVar
import torch.distributed as dist
from typing import Tuple
import argparse
A = TypeVar("A")
B = TypeVar("B")
class TimeDistributed(torch.nn.Module):
"""
... | 0.883845 | 0.498901 |
import pandas as pd
import numpy as np
import argparse
import sys
import os
import pdb
import collections
import glob
import rpy2
from multiprocessing import Pool
sys.path.append('../common/')
import utilities as util
import analysis
import mutation_base
def get_options():
parser = argparse.ArgumentParser(descripti... | copy_number/interesting_genes_trichotomized_zscores.py | import pandas as pd
import numpy as np
import argparse
import sys
import os
import pdb
import collections
import glob
import rpy2
from multiprocessing import Pool
sys.path.append('../common/')
import utilities as util
import analysis
import mutation_base
def get_options():
parser = argparse.ArgumentParser(descripti... | 0.241042 | 0.118819 |
from footmark.ecs.connection import ECSConnection
from tests.unit import ACSMockServiceTestCase
import json
DESCRIBE_INSTANCE = '''
{
"Instances": {
"Instance": [
{
"CreationTime": "2016-06-20T21:37Z",
"DeviceAvailable": true,
"EipAddress": {},
"ExpiredTime": "2016-10-22T16:... | tests/unit/ecs/test_instance.py | from footmark.ecs.connection import ECSConnection
from tests.unit import ACSMockServiceTestCase
import json
DESCRIBE_INSTANCE = '''
{
"Instances": {
"Instance": [
{
"CreationTime": "2016-06-20T21:37Z",
"DeviceAvailable": true,
"EipAddress": {},
"ExpiredTime": "2016-10-22T16:... | 0.464416 | 0.27506 |
import argparse
import tempfile
import hashlib
from bioconverters import convert
import shutil
import urllib.request as request
from contextlib import closing
import time
import gzip
import sys
import string
import re
import os
from datetime import datetime
from dbutils import saveDocumentsToDatabase
def download_... | convertPubmed.py | import argparse
import tempfile
import hashlib
from bioconverters import convert
import shutil
import urllib.request as request
from contextlib import closing
import time
import gzip
import sys
import string
import re
import os
from datetime import datetime
from dbutils import saveDocumentsToDatabase
def download_... | 0.217836 | 0.29438 |
from decapod_common import log
from decapod_common import playbook_plugin
from decapod_common import playbook_plugin_hints
from decapod_common.models import cluster_data
DESCRIPTION = "Add RBD Mirroring host"
"""Plugin description."""
HINTS_SCHEMA = {
"remote_username": {
"description": "Remote user keyr... | plugins/playbook/add_rbdmirror/decapod_plugin_playbook_add_rbdmirror/plugin.py | from decapod_common import log
from decapod_common import playbook_plugin
from decapod_common import playbook_plugin_hints
from decapod_common.models import cluster_data
DESCRIPTION = "Add RBD Mirroring host"
"""Plugin description."""
HINTS_SCHEMA = {
"remote_username": {
"description": "Remote user keyr... | 0.719088 | 0.259126 |
from univers.gem import GemRequirement
from univers.gem import GemVersion
from univers.gem import InvalidVersionError
def assert_bumped_version_equal(expected, unbumped):
# Assert that bumping the +unbumped+ version yields the +expected+.
assert_version_eql(expected, GemVersion(unbumped).bump())
def test_... | tests/test_rubygems_gem_version.py |
from univers.gem import GemRequirement
from univers.gem import GemVersion
from univers.gem import InvalidVersionError
def assert_bumped_version_equal(expected, unbumped):
# Assert that bumping the +unbumped+ version yields the +expected+.
assert_version_eql(expected, GemVersion(unbumped).bump())
def test_... | 0.747708 | 0.640397 |
import argparse
import json
import requests
#### Gather CLI arguments
# Requres a PR message to be passed in as a text file to --prmessage
parser = argparse.ArgumentParser()
parser.add_argument("--prmessage", help="File path to a newline separated PR description", required=True)
parser.add_argument("--outputfile", hel... | tryodaf-check-pr.py | import argparse
import json
import requests
#### Gather CLI arguments
# Requres a PR message to be passed in as a text file to --prmessage
parser = argparse.ArgumentParser()
parser.add_argument("--prmessage", help="File path to a newline separated PR description", required=True)
parser.add_argument("--outputfile", hel... | 0.051 | 0.164684 |
import json
import logging
import logging.config
import os
import sys
from pathlib import Path
import pretty_errors # NOQA: F401 (imported but unused)
from rich.logging import RichHandler
# Configuration
NOCACHE = os.environ.get("SOCCERDATA_NOCACHE", 'False').lower() in ('true', '1', 't')
NOSTORE = os.environ.get("... | soccerdata/_config.py |
import json
import logging
import logging.config
import os
import sys
from pathlib import Path
import pretty_errors # NOQA: F401 (imported but unused)
from rich.logging import RichHandler
# Configuration
NOCACHE = os.environ.get("SOCCERDATA_NOCACHE", 'False').lower() in ('true', '1', 't')
NOSTORE = os.environ.get("... | 0.171963 | 0.198899 |
import hashlib
import unittest
from binascii import hexlify, unhexlify
from context import bitcoinutils
from bitcoinutils.setup import setup
from bitcoinutils.keys import PrivateKey, P2pkhAddress, P2shAddress, P2wpkhAddress
from bitcoinutils.constants import SIGHASH_ALL, SIGHASH_NONE, SIGHASH_SINGLE, \
SIGHASH_ANY... | tests/test_p2wpkh_txs.py | import hashlib
import unittest
from binascii import hexlify, unhexlify
from context import bitcoinutils
from bitcoinutils.setup import setup
from bitcoinutils.keys import PrivateKey, P2pkhAddress, P2shAddress, P2wpkhAddress
from bitcoinutils.constants import SIGHASH_ALL, SIGHASH_NONE, SIGHASH_SINGLE, \
SIGHASH_ANY... | 0.341692 | 0.266906 |
UNO_CARDS = [
":R1:549406471633371147", ":R2:549406503602356245", ":R3:549406530298970124", ":R4:549406528642220033", ":R5:549406529602846742", ":R6:549406531347808284", ":R7:549406528470253579", ":R8:549406531079372815", ":R9:549406531700129792", ":RR:549406530437644289", ":RS:549406531679158272", ":RP:54940653093... | cogs/game/minigames/uno/variables.py | UNO_CARDS = [
":R1:549406471633371147", ":R2:549406503602356245", ":R3:549406530298970124", ":R4:549406528642220033", ":R5:549406529602846742", ":R6:549406531347808284", ":R7:549406528470253579", ":R8:549406531079372815", ":R9:549406531700129792", ":RR:549406530437644289", ":RS:549406531679158272", ":RP:54940653093... | 0.177098 | 0.482917 |
import torch
from torch.optim.optimizer import Optimizer
from pytorch_optimizer.base_optimizer import BaseOptimizer
from pytorch_optimizer.types import CLOSURE, DEFAULTS, LOSS, PARAMETERS
from pytorch_optimizer.utils import neuron_mean, neuron_norm
class Nero(Optimizer, BaseOptimizer):
"""
Reference : https:... | pytorch_optimizer/nero.py | import torch
from torch.optim.optimizer import Optimizer
from pytorch_optimizer.base_optimizer import BaseOptimizer
from pytorch_optimizer.types import CLOSURE, DEFAULTS, LOSS, PARAMETERS
from pytorch_optimizer.utils import neuron_mean, neuron_norm
class Nero(Optimizer, BaseOptimizer):
"""
Reference : https:... | 0.90226 | 0.412441 |
from __future__ import absolute_import
import fileinfo
import os
import numpy as np
def ie_filename(theoryname, R = 1.0, oper=False, tag="", fullpath = False, clusteronly = False, theta = 0.0, absh=1.0):
if fullpath:
dirname = fileinfo.XARPATH
else:
dirname = ""
if oper:
if cluster... | namegen.py |
from __future__ import absolute_import
import fileinfo
import os
import numpy as np
def ie_filename(theoryname, R = 1.0, oper=False, tag="", fullpath = False, clusteronly = False, theta = 0.0, absh=1.0):
if fullpath:
dirname = fileinfo.XARPATH
else:
dirname = ""
if oper:
if cluster... | 0.401805 | 0.065995 |
from unittest.mock import AsyncMock
import pytest
from nano_magic.adapters.client_channel import ClientChannel
from nano_magic.adapters.messages import END_DECK
from nano_magic.adapters.messages import POSITIVES
@pytest.fixture
def cards():
return [str(i) for i in range(7)]
@pytest.mark.asyncio
async def test... | tests/unit/nano_tcg/adapters/test_client_channel.py | from unittest.mock import AsyncMock
import pytest
from nano_magic.adapters.client_channel import ClientChannel
from nano_magic.adapters.messages import END_DECK
from nano_magic.adapters.messages import POSITIVES
@pytest.fixture
def cards():
return [str(i) for i in range(7)]
@pytest.mark.asyncio
async def test... | 0.744099 | 0.601067 |
import wx
import time
import analyse as m
# Define the tab content as classes:
class tabGather(wx.Panel):
def __init__(self, parent):
wx.Panel.__init__(self, parent)
self.text = wx.StaticText(self, -1, "Please enter a #hashtag to search on Twitter", (45,20))
self.hashtagTextBox=wx... | main.py | import wx
import time
import analyse as m
# Define the tab content as classes:
class tabGather(wx.Panel):
def __init__(self, parent):
wx.Panel.__init__(self, parent)
self.text = wx.StaticText(self, -1, "Please enter a #hashtag to search on Twitter", (45,20))
self.hashtagTextBox=wx... | 0.251096 | 0.058588 |
import mxnet as mx
import json
import os
import logging
class MXNetVisionServiceBatching(object):
def __init__(self):
"""
Initialization for MXNet Vision Service supporting batch inference
"""
self.mxnet_ctx = None
self.mx_model = None
self.labels = None
se... | samples/mnist/inference/mxnet/mnist_cnn_inference.py |
import mxnet as mx
import json
import os
import logging
class MXNetVisionServiceBatching(object):
def __init__(self):
"""
Initialization for MXNet Vision Service supporting batch inference
"""
self.mxnet_ctx = None
self.mx_model = None
self.labels = None
se... | 0.705379 | 0.211335 |
import sys
import time
import sunspec2.modbus.client as client
import sunspec2.file.client as file_client
from optparse import OptionParser
"""
Original suns options:
-o: output mode for data (text, xml)
-x: export model description (slang, xml)
-t: transport type: tcp or rtu (default: tcp)
... | scripts/suns.py | import sys
import time
import sunspec2.modbus.client as client
import sunspec2.file.client as file_client
from optparse import OptionParser
"""
Original suns options:
-o: output mode for data (text, xml)
-x: export model description (slang, xml)
-t: transport type: tcp or rtu (default: tcp)
... | 0.282196 | 0.125172 |
from typing import Any, List, Optional, Union
import ee
def getTimeSeriesByRegion(
x: ee.ImageCollection,
reducer: Any,
bands: Optional[Union[str, List[str]]] = None,
geometry: Optional[Union[ee.Geometry, ee.Feature, ee.FeatureCollection]] = None,
scale: Optional[Union[int, float]] = None,
cr... | ee_extra/TimeSeries/core.py | from typing import Any, List, Optional, Union
import ee
def getTimeSeriesByRegion(
x: ee.ImageCollection,
reducer: Any,
bands: Optional[Union[str, List[str]]] = None,
geometry: Optional[Union[ee.Geometry, ee.Feature, ee.FeatureCollection]] = None,
scale: Optional[Union[int, float]] = None,
cr... | 0.968827 | 0.632786 |
"""Generated protocol buffer code."""
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protobuf import symbol_database as _symbol_database
# @@protoc_insertion_point(imports)
_sym_db = _symbol_databas... | python/pb/xds/core/v3/authority_pb2.py | """Generated protocol buffer code."""
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protobuf import symbol_database as _symbol_database
# @@protoc_insertion_point(imports)
_sym_db = _symbol_databas... | 0.317744 | 0.10683 |
from abc import ABC, abstractmethod
from wsqluse.wsqluse import Wsqluse
from gc_qdk.main import GCoreQDK
class WTAS(ABC, GCoreQDK):
"""
WServer To AR Sender.
Абстрактный, основной класс, с которого наследуют иные классы, занимающиеся
отправкой данных на AR.
"""
def __init__(self, polygon_ip, ... | wtas/main.py | from abc import ABC, abstractmethod
from wsqluse.wsqluse import Wsqluse
from gc_qdk.main import GCoreQDK
class WTAS(ABC, GCoreQDK):
"""
WServer To AR Sender.
Абстрактный, основной класс, с которого наследуют иные классы, занимающиеся
отправкой данных на AR.
"""
def __init__(self, polygon_ip, ... | 0.605916 | 0.253145 |
import sqlalchemy
from sqlalchemy.orm import sessionmaker
from pathlib import Path
from typing import Optional
from sqlalchemy.orm import Session
from sqlalchemy.future.engine import Engine
from models.model_base import ModelBase
__engine: Optional[Engine] = None
def create_engine(sqlite: bool = False) -> Engine:
... | src/sqlalchemy/03sqla_sync/conf/db_session.py | import sqlalchemy
from sqlalchemy.orm import sessionmaker
from pathlib import Path
from typing import Optional
from sqlalchemy.orm import Session
from sqlalchemy.future.engine import Engine
from models.model_base import ModelBase
__engine: Optional[Engine] = None
def create_engine(sqlite: bool = False) -> Engine:
... | 0.781997 | 0.197444 |
import sys
import time
from django.db.backends.base.creation import BaseDatabaseCreation
TEST_DATABASE_PREFIX = 'test_'
PASSWORD = '<PASSWORD>'
class DatabaseCreation(BaseDatabaseCreation):
def _create_test_db(self, verbosity=1, autoclobber=False):
TEST_NAME = self._test_database_name()
... | django_dmPython/src/django_dmPython/creation.py | import sys
import time
from django.db.backends.base.creation import BaseDatabaseCreation
TEST_DATABASE_PREFIX = 'test_'
PASSWORD = '<PASSWORD>'
class DatabaseCreation(BaseDatabaseCreation):
def _create_test_db(self, verbosity=1, autoclobber=False):
TEST_NAME = self._test_database_name()
... | 0.239705 | 0.111169 |
import asyncio
from datetime import datetime
import logging
from OSMPythonTools.nominatim import Nominatim
from googlemaps import Client
TIMEOUT = 10
_LOGGER: logging.Logger = logging.getLogger(__package__)
Coordinates = tuple[float, float]
class JourneyApiClient:
"""API client for the OSM Nominatim and Goog... | custom_components/journey/api.py | import asyncio
from datetime import datetime
import logging
from OSMPythonTools.nominatim import Nominatim
from googlemaps import Client
TIMEOUT = 10
_LOGGER: logging.Logger = logging.getLogger(__package__)
Coordinates = tuple[float, float]
class JourneyApiClient:
"""API client for the OSM Nominatim and Goog... | 0.620277 | 0.208945 |
import json
from pathlib import Path
import bids
from bids import BIDSLayout
bids.config.set_option("extension_initial_dot", True)
pattern = (
"sub-{subject}[/ses-{session}]/{datatype<anat|dwi>}/sub-{subject}"
"[_ses-{session}][_acq-{acquisition}][_dir-{direction}][_run-{run}]"
"_{suffix<T[12]w|dwi>}{ext... | hcp2bids/convert.py | import json
from pathlib import Path
import bids
from bids import BIDSLayout
bids.config.set_option("extension_initial_dot", True)
pattern = (
"sub-{subject}[/ses-{session}]/{datatype<anat|dwi>}/sub-{subject}"
"[_ses-{session}][_acq-{acquisition}][_dir-{direction}][_run-{run}]"
"_{suffix<T[12]w|dwi>}{ext... | 0.348423 | 0.202226 |
import sys
import pprint
import smtplib
import time
import uuid
from email.mime.text import MIMEText
from threading import Thread, Event
DEBUG = True
class Sender():
# TODO: Private, underscore
args = None
db = {}
dur = 10
emails = 10
def __init__(self, host, port):
self.init_db()
... | sender.py |
import sys
import pprint
import smtplib
import time
import uuid
from email.mime.text import MIMEText
from threading import Thread, Event
DEBUG = True
class Sender():
# TODO: Private, underscore
args = None
db = {}
dur = 10
emails = 10
def __init__(self, host, port):
self.init_db()
... | 0.128676 | 0.109825 |
import unittest
import os
import tensorflow as tf
import gpflow
from testing.gpflow_testcase import GPflowTestCase
class TestConfigParsing(GPflowTestCase):
def setUp(self):
directory = os.path.dirname(os.path.realpath(__file__))
f = os.path.join(directory, 'gpflowrc_test.txt')
self.conf = ... | GPflow/testing/test_config.py | import unittest
import os
import tensorflow as tf
import gpflow
from testing.gpflow_testcase import GPflowTestCase
class TestConfigParsing(GPflowTestCase):
def setUp(self):
directory = os.path.dirname(os.path.realpath(__file__))
f = os.path.join(directory, 'gpflowrc_test.txt')
self.conf = ... | 0.627267 | 0.539711 |
import sys
from PyQt5 import QtGui, QtCore, QtWidgets
import pyqtgraph as pg
from mainWindow import Ui_MainWindow
from UDP.UDP_Server import UDP_ServerThread
from UDP.UDP_Client import UDP_ClientThread
from worker import Worker
from TriDisplay import TriModel
from plot import Plot
from Utils.traces.trace import *
from... | GUI/WifiMonitor/UI.py | import sys
from PyQt5 import QtGui, QtCore, QtWidgets
import pyqtgraph as pg
from mainWindow import Ui_MainWindow
from UDP.UDP_Server import UDP_ServerThread
from UDP.UDP_Client import UDP_ClientThread
from worker import Worker
from TriDisplay import TriModel
from plot import Plot
from Utils.traces.trace import *
from... | 0.227298 | 0.047914 |
from typing import List
from pandas import read_excel, DataFrame, Series, notnull, concat, isnull, \
ExcelFile
from stringcase import snakecase
from survey.constants import CATEGORY_SPLITTER
from survey.surveys.metadata import QuestionMetadata, AttributeMetadata
from survey.surveys.survey_creators import SurveyCr... | survey/surveys/survey_creators/pollfish_creator.py | from typing import List
from pandas import read_excel, DataFrame, Series, notnull, concat, isnull, \
ExcelFile
from stringcase import snakecase
from survey.constants import CATEGORY_SPLITTER
from survey.surveys.metadata import QuestionMetadata, AttributeMetadata
from survey.surveys.survey_creators import SurveyCr... | 0.679179 | 0.277387 |
from FeatureCloud.app.engine.app import AppState, app_state, Role, LogLevel
from federated_dca.utils import load_params, trainInstince, average_model_params
import bios
@app_state('initial', Role.BOTH)
class InitialState(AppState):
def register(self):
self.register_transition('train', Role.BOTH)
def ... | federated_dca/app.py | from FeatureCloud.app.engine.app import AppState, app_state, Role, LogLevel
from federated_dca.utils import load_params, trainInstince, average_model_params
import bios
@app_state('initial', Role.BOTH)
class InitialState(AppState):
def register(self):
self.register_transition('train', Role.BOTH)
def ... | 0.564219 | 0.099558 |
import sys
import numpy as np
import xgboost as xgb
from sklearn.datasets import load_svmlight_file
import scipy.sparse
import math
import pandas as pd
from sklearn.feature_extraction import DictVectorizer
from seldon.pipeline.pandas_pipelines import BasePandasEstimator
from collections import OrderedDict
import io
fr... | python/seldon/xgb.py | import sys
import numpy as np
import xgboost as xgb
from sklearn.datasets import load_svmlight_file
import scipy.sparse
import math
import pandas as pd
from sklearn.feature_extraction import DictVectorizer
from seldon.pipeline.pandas_pipelines import BasePandasEstimator
from collections import OrderedDict
import io
fr... | 0.685002 | 0.445409 |
from __future__ import print_function
import argparse
import sys
import os
import subprocess
import time
import xml.etree.ElementTree as ET
from datetime import datetime
# helpers
def get_substring(s, leader, trailer):
end_of_leader = s.index(leader) + len(leader)
start_of_trailer = s.index(trailer, end_of_le... | breakbyseverity.py | from __future__ import print_function
import argparse
import sys
import os
import subprocess
import time
import xml.etree.ElementTree as ET
from datetime import datetime
# helpers
def get_substring(s, leader, trailer):
end_of_leader = s.index(leader) + len(leader)
start_of_trailer = s.index(trailer, end_of_le... | 0.132234 | 0.094093 |
import os
import re
import numpy as np
import torch
def calc_t_emb(ts, t_emb_dim):
"""
Embed time steps into a higher dimension space
"""
assert t_emb_dim % 2 == 0
half_dim = t_emb_dim // 2
t_emb = np.log(10000) / (half_dim - 1)
t_emb = torch.exp(torch.arange(half_dim) * -t_emb)
t_emb... | util.py | import os
import re
import numpy as np
import torch
def calc_t_emb(ts, t_emb_dim):
"""
Embed time steps into a higher dimension space
"""
assert t_emb_dim % 2 == 0
half_dim = t_emb_dim // 2
t_emb = np.log(10000) / (half_dim - 1)
t_emb = torch.exp(torch.arange(half_dim) * -t_emb)
t_emb... | 0.786008 | 0.561996 |