code stringlengths 2k 1.04M | repo_path stringlengths 5 517 | parsed_code stringlengths 0 1.04M | quality_prob float64 0.02 0.95 | learning_prob float64 0.02 0.93 |
|---|---|---|---|---|
from oslo_config import cfg
from oslo_log import log as logging
from oslo_utils import timeutils
from taskflow import task
from karbor.common import constants
from karbor.services.protection.flows import utils
from karbor.services.protection import resource_flow
CONF = cfg.CONF
LOG = logging.getLogger(__name__)
... | karbor-1.3.0/karbor/services/protection/flows/verify.py |
from oslo_config import cfg
from oslo_log import log as logging
from oslo_utils import timeutils
from taskflow import task
from karbor.common import constants
from karbor.services.protection.flows import utils
from karbor.services.protection import resource_flow
CONF = cfg.CONF
LOG = logging.getLogger(__name__)
... | 0.438545 | 0.083329 |
try:
from urllib.parse import urljoin
except ImportError:
from urlparse import urljoin
import requests
import tornado
import ujson
import pandas as pd
import pyEX as p
import string
from trading_calendars import get_calendar
from datetime import datetime, timedelta, date
from dateutil.relativedelta import rela... | hedgedata/utils.py | try:
from urllib.parse import urljoin
except ImportError:
from urlparse import urljoin
import requests
import tornado
import ujson
import pandas as pd
import pyEX as p
import string
from trading_calendars import get_calendar
from datetime import datetime, timedelta, date
from dateutil.relativedelta import rela... | 0.382949 | 0.103839 |
from nbt import nbt
import xlsxwriter
import subprocess
import time
from sys import exit
import os
servers = "/root/of/spigot/servers"
sharePath = "/where/to/save/reports/"
def findUsers():
subprocess.call('rm %s*' %(sharePath), shell=True)
for dir in os.listdir(servers):
serverName = ""
if os.path.isfile(se... | playerlist.py |
from nbt import nbt
import xlsxwriter
import subprocess
import time
from sys import exit
import os
servers = "/root/of/spigot/servers"
sharePath = "/where/to/save/reports/"
def findUsers():
subprocess.call('rm %s*' %(sharePath), shell=True)
for dir in os.listdir(servers):
serverName = ""
if os.path.isfile(se... | 0.054777 | 0.054727 |
import spot
import sys
# ----------------------------------------------------------------------
a = spot.formula.ap('a')
b = spot.formula.ap('b')
c = spot.formula.ap('c')
c2 = spot.formula.ap('c')
assert c == c2
op = spot.formula.And([a, b])
op2 = spot.formula.And([op, c])
op3 = spot.formula.And([a, c, b])
assert ... | lib/spot-2.8.1/tests/python/ltlsimple.py |
import spot
import sys
# ----------------------------------------------------------------------
a = spot.formula.ap('a')
b = spot.formula.ap('b')
c = spot.formula.ap('c')
c2 = spot.formula.ap('c')
assert c == c2
op = spot.formula.And([a, b])
op2 = spot.formula.And([op, c])
op3 = spot.formula.And([a, c, b])
assert ... | 0.435661 | 0.550909 |
import pytest
import windows
import windows.generated_def as gdef
from windows.pycompat import basestring
from .pfwtest import *
## This comment was in test_system.py: still revelant ?
# Well, pytest initialize COM with its own parameters
# It might make our own com.init() in WMI fail and therefore not call
# CoInit... | tests/test_wmi.py | import pytest
import windows
import windows.generated_def as gdef
from windows.pycompat import basestring
from .pfwtest import *
## This comment was in test_system.py: still revelant ?
# Well, pytest initialize COM with its own parameters
# It might make our own com.init() in WMI fail and therefore not call
# CoInit... | 0.475849 | 0.434281 |
import io
import unittest
import unittest.mock as mock
from unittest.mock import patch
from unittest import TestCase
from ETCetera.util.parsing.parser_nonlinear_systems import parse_from_file
class TestParserFileRead(TestCase):
@unittest.mock.patch('sys.stdout', new_callable=io.StringIO)
def assert_stdout(se... | tests/parser_tests/nonlinear_systems/test_nonlinear_read_from_file.py | import io
import unittest
import unittest.mock as mock
from unittest.mock import patch
from unittest import TestCase
from ETCetera.util.parsing.parser_nonlinear_systems import parse_from_file
class TestParserFileRead(TestCase):
@unittest.mock.patch('sys.stdout', new_callable=io.StringIO)
def assert_stdout(se... | 0.525369 | 0.547948 |
import asyncio
import requests
import os
from pyppeteer import launch
from pyppeteer.page import Page
import colorsys
layer_keys = [
'mini_base', 'pet', 'cloak', 'off_hand', 'body', 'hair', 'face', 'legs',
'feet', 'chest', 'head', 'head_2', 'waist', 'hands', 'main_hand', 'horns', 'wings',
'tattoo', 'ears',... | rerollExtractor.py | import asyncio
import requests
import os
from pyppeteer import launch
from pyppeteer.page import Page
import colorsys
layer_keys = [
'mini_base', 'pet', 'cloak', 'off_hand', 'body', 'hair', 'face', 'legs',
'feet', 'chest', 'head', 'head_2', 'waist', 'hands', 'main_hand', 'horns', 'wings',
'tattoo', 'ears',... | 0.33546 | 0.204898 |
import itertools
import textwrap
from django.conf import settings
from django.contrib.gis.db import models as gis_models
from django.core.cache import cache
from django.db import models
from django.db import IntegrityError
from django.db.models.signals import post_save
from django.dispatch import receiver
from django ... | backent/api/models.py | import itertools
import textwrap
from django.conf import settings
from django.contrib.gis.db import models as gis_models
from django.core.cache import cache
from django.db import models
from django.db import IntegrityError
from django.db.models.signals import post_save
from django.dispatch import receiver
from django ... | 0.58676 | 0.075312 |
from abra.config import DEFAULT_ALPHA, DEFAULT_BAYESIAN_INFERENCE_METHOD
from abra.inference.inference_base import InferenceProcedure
from abra.stats import Samples
from abra.vis import Traces
from abra.inference.bayesian import get_stan_model, get_model_datatype, get_model_data
from abra.inference.bayesian.results imp... | abra/inference/bayesian/delta.py | from abra.config import DEFAULT_ALPHA, DEFAULT_BAYESIAN_INFERENCE_METHOD
from abra.inference.inference_base import InferenceProcedure
from abra.stats import Samples
from abra.vis import Traces
from abra.inference.bayesian import get_stan_model, get_model_datatype, get_model_data
from abra.inference.bayesian.results imp... | 0.917873 | 0.465873 |
from flask_restplus import reqparse, inputs
group_by_model = reqparse.RequestParser()
group_by_model.add_argument('granularity', type=str, choices=['day', 'month', 'year'], default='month')
group_by_model.add_argument('label', type=int, default=None)
group_by_model.add_argument('keyword', action='append', default=lamb... | backend/db/db_models.py | from flask_restplus import reqparse, inputs
group_by_model = reqparse.RequestParser()
group_by_model.add_argument('granularity', type=str, choices=['day', 'month', 'year'], default='month')
group_by_model.add_argument('label', type=int, default=None)
group_by_model.add_argument('keyword', action='append', default=lamb... | 0.419886 | 0.042029 |
import os
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torchvision import datasets, transforms, models
from torch.utils.data import DataLoader, random_split
from torch.utils.data.sampler import SubsetRandomSampler
train_transforms = transforms.Compose([
transforms.Resi... | models/matt/second.py | import os
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torchvision import datasets, transforms, models
from torch.utils.data import DataLoader, random_split
from torch.utils.data.sampler import SubsetRandomSampler
train_transforms = transforms.Compose([
transforms.Resi... | 0.824638 | 0.65071 |
import numpy as np
import pandas as pd
class RelationalDataBase():
def __init__(self):
self._dic = {}
self._label_dic = {}
self.merge_dic = {}
def _read_as_list(self,file_name):
l = []
with open(file_name,"r") as f:
for line in f:
... | LIDG_v0.2/lidg/database.py | import numpy as np
import pandas as pd
class RelationalDataBase():
def __init__(self):
self._dic = {}
self._label_dic = {}
self.merge_dic = {}
def _read_as_list(self,file_name):
l = []
with open(file_name,"r") as f:
for line in f:
... | 0.146026 | 0.183392 |
from datetime import datetime
from corehq.apps.locations.models import SQLLocation
from corehq.apps.reports.datatables import DataTablesHeader, DataTablesColumn
from corehq.apps.reports.filters.fixtures import AsyncLocationFilter
from corehq.apps.reports.filters.select import MonthFilter, YearFilter
from custom.ilsgate... | custom/ilsgateway/tanzania/reports/supervision.py | from datetime import datetime
from corehq.apps.locations.models import SQLLocation
from corehq.apps.reports.datatables import DataTablesHeader, DataTablesColumn
from corehq.apps.reports.filters.fixtures import AsyncLocationFilter
from corehq.apps.reports.filters.select import MonthFilter, YearFilter
from custom.ilsgate... | 0.637934 | 0.127734 |
from models.convnets import ConvolutionalNet
from keras.models import load_model
from keras.preprocessing import sequence
from preprocessors.preprocess_text import clean
import sys
import string
import re
import numpy as np
from sklearn.metrics import confusion_matrix, accuracy_score, f1_score
MATCH_MULTIPLE_SPACES = ... | examples/pplm_clickbait/ClickBaticDetector.py | from models.convnets import ConvolutionalNet
from keras.models import load_model
from keras.preprocessing import sequence
from preprocessors.preprocess_text import clean
import sys
import string
import re
import numpy as np
from sklearn.metrics import confusion_matrix, accuracy_score, f1_score
MATCH_MULTIPLE_SPACES = ... | 0.534127 | 0.274344 |
import os
import yaml
from shutil import copy
import argparse
import confgenerator.generator as gen
# sys.tracebacklimit = 0 # no traceback
PKG_DIR = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
class bypass_confgen_cli():
"""The CLI of the bypass configuration generator."""
def __init__(self,... | deployment/confgenerator/confgenerator/cli.py | import os
import yaml
from shutil import copy
import argparse
import confgenerator.generator as gen
# sys.tracebacklimit = 0 # no traceback
PKG_DIR = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
class bypass_confgen_cli():
"""The CLI of the bypass configuration generator."""
def __init__(self,... | 0.391173 | 0.051869 |
from flask import Flask, jsonify, render_template
from flask_limiter import Limiter
from flask_limiter.util import get_remote_address
from utils import retrieve_arb_pred, retrieve_tr_pred
from display import display_tr_pred, display_arb_pred
application = Flask(__name__)
# default limit for each route
limiter = Limi... | api_source_code/flask_app/application.py | from flask import Flask, jsonify, render_template
from flask_limiter import Limiter
from flask_limiter.util import get_remote_address
from utils import retrieve_arb_pred, retrieve_tr_pred
from display import display_tr_pred, display_arb_pred
application = Flask(__name__)
# default limit for each route
limiter = Limi... | 0.749087 | 0.203055 |
import pprint
import re # noqa: F401
import six
class Bond(object):
"""NOTE: This class is auto generated by OpenAPI Generator.
Ref: https://openapi-generator.tech
Do not edit the class manually.
"""
"""
Attributes:
openapi_types (dict): The key is attribute name
... | sdk/lusid/models/bond.py | import pprint
import re # noqa: F401
import six
class Bond(object):
"""NOTE: This class is auto generated by OpenAPI Generator.
Ref: https://openapi-generator.tech
Do not edit the class manually.
"""
"""
Attributes:
openapi_types (dict): The key is attribute name
... | 0.836888 | 0.24801 |
import os.path
import sys
import time
import numbers
import signal
import ConfigParser
cfg = ConfigParser.ConfigParser()
cfg.read('teckit.conf')
cfg.sections()
if cfg.get('teckit', 'interface', 1) == 'gpib':
import Gpib
elif cfg.get('teckit', 'interface', 1) == 'vxi':
import vxi11
else:
print "No interface... | devices/f5720a.py | import os.path
import sys
import time
import numbers
import signal
import ConfigParser
cfg = ConfigParser.ConfigParser()
cfg.read('teckit.conf')
cfg.sections()
if cfg.get('teckit', 'interface', 1) == 'gpib':
import Gpib
elif cfg.get('teckit', 'interface', 1) == 'vxi':
import vxi11
else:
print "No interface... | 0.151216 | 0.124505 |
import argparse
import traceback
from config import Config
from main import trace_most_fit, train_same_games, training_overview, visualize_genome
from population.population import Population
from process_killer import main as process_killer
from utils.dictionary import *
def main(gru,
reproduce,
tr... | run_distance_only.py | import argparse
import traceback
from config import Config
from main import trace_most_fit, train_same_games, training_overview, visualize_genome
from population.population import Population
from process_killer import main as process_killer
from utils.dictionary import *
def main(gru,
reproduce,
tr... | 0.660391 | 0.330215 |
from kigo.bpmn.elements.element import Element
class Task(Element):
item_name = "bpmn:task"
def __init__(self, eid=None, name=None, incoming=[], outgoing=[]):
self.eid = eid
self.name = name
self.incoming = incoming
self.outgoing = outgoing
def __repr__(self):
retu... | kigo/bpmn/elements/tasks.py | from kigo.bpmn.elements.element import Element
class Task(Element):
item_name = "bpmn:task"
def __init__(self, eid=None, name=None, incoming=[], outgoing=[]):
self.eid = eid
self.name = name
self.incoming = incoming
self.outgoing = outgoing
def __repr__(self):
retu... | 0.588889 | 0.066448 |
import os
from miscellanies.platform_style_path import join_path
from .manipulator import VideoDatasetManipulator
from datasets.types.specialized_dataset import SpecializedVideoDatasetType
from datasets.base.common.dataset import _BaseDataset, _BaseDatasetObject
__all__ = ['VideoDataset']
__version__ = 1
class Video... | datasets/base/video/dataset.py | import os
from miscellanies.platform_style_path import join_path
from .manipulator import VideoDatasetManipulator
from datasets.types.specialized_dataset import SpecializedVideoDatasetType
from datasets.base.common.dataset import _BaseDataset, _BaseDatasetObject
__all__ = ['VideoDataset']
__version__ = 1
class Video... | 0.66628 | 0.262416 |
import asyncio
import os
import logging
from keep_alive import keep_alive as flask_keep_alive
import main, db, economy
import settings
import click
logger = logging.getLogger('run')
@click.group()
def cli():
pass
@cli.command()
@click.option('--keep-alive', is_flag=True, help='Run flask thread to keep Repl al... | run.py | import asyncio
import os
import logging
from keep_alive import keep_alive as flask_keep_alive
import main, db, economy
import settings
import click
logger = logging.getLogger('run')
@click.group()
def cli():
pass
@cli.command()
@click.option('--keep-alive', is_flag=True, help='Run flask thread to keep Repl al... | 0.483892 | 0.04982 |
from __future__ import unicode_literals
import re
from .common import InfoExtractor
from ..utils import (
ExtractorError,
std_headers,
sanitize_filename,
int_or_none,
js_to_json
)
import httpx
import traceback
import sys
import json
import time
import random
from urllib.parse import unquote... | yt_dlp/extractor/gay0day.py | from __future__ import unicode_literals
import re
from .common import InfoExtractor
from ..utils import (
ExtractorError,
std_headers,
sanitize_filename,
int_or_none,
js_to_json
)
import httpx
import traceback
import sys
import json
import time
import random
from urllib.parse import unquote... | 0.191668 | 0.064447 |
from flask_wtf import (
FlaskForm
)
from wtforms import (
IntegerField, SelectField
)
class TimesheetForm(FlaskForm):
pass
hh_beg_01 = IntegerField(default='09')
mm_beg_01 = IntegerField(default='00')
ap_beg_01 = SelectField(choices=[('0', 'a'), ('12', 'p')])
hh_fin_01 = IntegerField(defau... | jam/timesheet/forms.py | from flask_wtf import (
FlaskForm
)
from wtforms import (
IntegerField, SelectField
)
class TimesheetForm(FlaskForm):
pass
hh_beg_01 = IntegerField(default='09')
mm_beg_01 = IntegerField(default='00')
ap_beg_01 = SelectField(choices=[('0', 'a'), ('12', 'p')])
hh_fin_01 = IntegerField(defau... | 0.460046 | 0.18838 |
_multiprocess_can_split_ = False
from init import setUp
setUp()
from unittest import TestCase
from mock import patch
import mock
SERVICE_KEY = 'test_generated_key.pem'
SERVICE_EMAIL = '<EMAIL>'
USER_EMAIL = '<EMAIL>'
USER2_EMAIL = '<EMAIL>'
class DictObject(object):
def __init__(self, **properties):
s... | tests/test_oauth.py | _multiprocess_can_split_ = False
from init import setUp
setUp()
from unittest import TestCase
from mock import patch
import mock
SERVICE_KEY = 'test_generated_key.pem'
SERVICE_EMAIL = '<EMAIL>'
USER_EMAIL = '<EMAIL>'
USER2_EMAIL = '<EMAIL>'
class DictObject(object):
def __init__(self, **properties):
s... | 0.535341 | 0.1291 |
import fairseq
from fairseq.data import Dictionary, encoders
import csv
from argparse import Namespace
import torch
class AdditionalDataset:
@classmethod
def from_tsv(cls, file, key, bpe_tokenizer=None, pre_tokenizer=None):
data = []
with open(file, 'r') as file:
reader = csv.Dict... | s3prl/downstream/speech_translation/AdditionalDataset.py | import fairseq
from fairseq.data import Dictionary, encoders
import csv
from argparse import Namespace
import torch
class AdditionalDataset:
@classmethod
def from_tsv(cls, file, key, bpe_tokenizer=None, pre_tokenizer=None):
data = []
with open(file, 'r') as file:
reader = csv.Dict... | 0.698946 | 0.152852 |
from __future__ import print_function
from keras.models import Sequential
from keras.layers import Dense, Activation
from keras.layers import LSTM
from keras.layers import TimeDistributed
from keras.optimizers import RMSprop
import numpy as np
import random
import sys
path = "./jdk-tokens.txt"
filetext = open(path).re... | lstm_ai_coder_token_many2many.py | from __future__ import print_function
from keras.models import Sequential
from keras.layers import Dense, Activation
from keras.layers import LSTM
from keras.layers import TimeDistributed
from keras.optimizers import RMSprop
import numpy as np
import random
import sys
path = "./jdk-tokens.txt"
filetext = open(path).re... | 0.609524 | 0.248968 |
import psycopg2
import ujson as json
import datetime
def database_connection():
postgresconn = psycopg2.connect("dbname='prop' user='CHANGEME' password='<PASSWORD>' host='CHANGEME'")
postgresconn.autocommit = True
postgrescur = postgresconn.cursor()
return postgrescur, postgresconn
def hashtag_exists... | 3-ANALYZE/review_raw_data.py | import psycopg2
import ujson as json
import datetime
def database_connection():
postgresconn = psycopg2.connect("dbname='prop' user='CHANGEME' password='<PASSWORD>' host='CHANGEME'")
postgresconn.autocommit = True
postgrescur = postgresconn.cursor()
return postgrescur, postgresconn
def hashtag_exists... | 0.105671 | 0.064036 |
from .fplEntity import FplEntity
class FplProjectedBillSensor(FplEntity):
def __init__(self, coordinator, config, account):
super().__init__(coordinator, config, account, "Projected Bill")
@property
def state(self):
budget = self.getData("budget_bill")
budget_billing_projected_bil... | custom_components/fpl/sensor_ProjectedBillSensor.py | from .fplEntity import FplEntity
class FplProjectedBillSensor(FplEntity):
def __init__(self, coordinator, config, account):
super().__init__(coordinator, config, account, "Projected Bill")
@property
def state(self):
budget = self.getData("budget_bill")
budget_billing_projected_bil... | 0.856377 | 0.09628 |
import json
import numpy as np
import tensorflow as tf
from kafka import KafkaProducer
def publish_message(producer_instance, topic_name, key, value):
try:
key_bytes = bytes(key, encoding="utf-8")
value_bytes = bytes(value, encoding="utf-8")
producer_instance.send(topic_name, key=key_byt... | mlmodels/model_tf/misc/tf_serving/13.text-classification-kafka/producer.py | import json
import numpy as np
import tensorflow as tf
from kafka import KafkaProducer
def publish_message(producer_instance, topic_name, key, value):
try:
key_bytes = bytes(key, encoding="utf-8")
value_bytes = bytes(value, encoding="utf-8")
producer_instance.send(topic_name, key=key_byt... | 0.265499 | 0.10235 |
import json
from lib import components, dockerfile
class Command:
def __init__(self, components, dockerfile_instruction):
self.components = components
self.dockerfile_instruction = dockerfile_instruction
def get_lines(self):
pass
def get_tools(self):
return [component for... | generator/lib/commands.py |
import json
from lib import components, dockerfile
class Command:
def __init__(self, components, dockerfile_instruction):
self.components = components
self.dockerfile_instruction = dockerfile_instruction
def get_lines(self):
pass
def get_tools(self):
return [component for... | 0.420124 | 0.108803 |
class FeatureBroker:
""" Feature Borker
"""
def __init__(self, allowReplace=False):
self.providers = {}
self.allowReplace = allowReplace
def provide(self, feature, provider, *args, **kwargs):
if not self.allowReplace:
assert not self.providers.has_key(feature), 'Dupl... | IOC/IOC.py | class FeatureBroker:
""" Feature Borker
"""
def __init__(self, allowReplace=False):
self.providers = {}
self.allowReplace = allowReplace
def provide(self, feature, provider, *args, **kwargs):
if not self.allowReplace:
assert not self.providers.has_key(feature), 'Dupl... | 0.694406 | 0.443781 |
import cv2
import sys
import os
sys.path.append('../')
from lib import fileTool as FT
from lib.pwcNet.pwcNet import PWCDCNet
from lib.forwardWarpTorch.forwardWarp import forwadWarp
import torch
from pathlib import Path
from DVSTool20.DVSBase import ESIMReader
import numpy as np
import pickle
from tqdm import tqdm
fro... | DVSTool/drawevent.py | import cv2
import sys
import os
sys.path.append('../')
from lib import fileTool as FT
from lib.pwcNet.pwcNet import PWCDCNet
from lib.forwardWarpTorch.forwardWarp import forwadWarp
import torch
from pathlib import Path
from DVSTool20.DVSBase import ESIMReader
import numpy as np
import pickle
from tqdm import tqdm
fro... | 0.244183 | 0.152064 |
import sys, datetime, jieba, jieba.analyse, MySQLdb
from gensim import corpora, models, similarities
from mysql_config import DBConfig
reload(sys)
sys.setdefaultencoding('utf8')
date_list = [2016,9,22]
date = date_list[0]*10000 + date_list[1]*100 + date_list[2]
today_date = (datetime.datetime.now().year)*10000 + (dat... | data_analyse/file_updater.py | import sys, datetime, jieba, jieba.analyse, MySQLdb
from gensim import corpora, models, similarities
from mysql_config import DBConfig
reload(sys)
sys.setdefaultencoding('utf8')
date_list = [2016,9,22]
date = date_list[0]*10000 + date_list[1]*100 + date_list[2]
today_date = (datetime.datetime.now().year)*10000 + (dat... | 0.151498 | 0.081191 |
import numpy as np
from quantiacsToolbox import stats
def fillnans(data):
""" Fill in (column-wise) value gaps with the most recent non-nan value.
Leading nan's remain in place. The gaps are filled in only after the first non-nan entry.
Args:
data: Input data to be un-nanned.
Returns:
... | rnn_portfolio/quantiacs_code.py | import numpy as np
from quantiacsToolbox import stats
def fillnans(data):
""" Fill in (column-wise) value gaps with the most recent non-nan value.
Leading nan's remain in place. The gaps are filled in only after the first non-nan entry.
Args:
data: Input data to be un-nanned.
Returns:
... | 0.781247 | 0.737944 |
import numpy as np
import numpy.ma as ma
from Xdrop.dropletizem import dropimgood_sel
import time
import pickle
import re
from matplotlib import pyplot as plt
def dropletizedata(data, pars, mask=None, dark=None, savdir="./", savname=None):
# print(dropimgood_sel.__doc__)
dim = data.shape
mshape = dim[-2:]... | Xana/Xdrop/DropletizeData.py | import numpy as np
import numpy.ma as ma
from Xdrop.dropletizem import dropimgood_sel
import time
import pickle
import re
from matplotlib import pyplot as plt
def dropletizedata(data, pars, mask=None, dark=None, savdir="./", savname=None):
# print(dropimgood_sel.__doc__)
dim = data.shape
mshape = dim[-2:]... | 0.168651 | 0.418816 |
from django.apps import AppConfig
from baserow.core.registries import plugin_registry, application_type_registry
from .views.registries import view_type_registry, view_filter_type_registry
from .fields.registries import field_type_registry, field_converter_registry
class DatabaseConfig(AppConfig):
name = 'baser... | backend/src/baserow/contrib/database/config.py | from django.apps import AppConfig
from baserow.core.registries import plugin_registry, application_type_registry
from .views.registries import view_type_registry, view_filter_type_registry
from .fields.registries import field_type_registry, field_converter_registry
class DatabaseConfig(AppConfig):
name = 'baser... | 0.629775 | 0.274886 |
import unittest
import mock
from perfkitbenchmarker import flags
from perfkitbenchmarker import pkb
from perfkitbenchmarker import stages
FLAGS = flags.FLAGS
FLAGS.mark_as_parsed()
class TestCreateFailedRunSampleFlag(unittest.TestCase):
def PatchPkbFunction(self, function_name):
patcher = mock.patch(pkb.__nam... | tests/pkb_test.py | import unittest
import mock
from perfkitbenchmarker import flags
from perfkitbenchmarker import pkb
from perfkitbenchmarker import stages
FLAGS = flags.FLAGS
FLAGS.mark_as_parsed()
class TestCreateFailedRunSampleFlag(unittest.TestCase):
def PatchPkbFunction(self, function_name):
patcher = mock.patch(pkb.__nam... | 0.580114 | 0.338706 |
import datetime
import uuid
import pytest
from dataclasses_avroschema import fields
from . import consts
@pytest.mark.parametrize(
"python_type,avro_type,logical_type", consts.LOGICAL_TYPES_AND_DEFAULTS
)
def test_logical_types(python_type, avro_type, logical_type):
name = "a logical type"
python_type ... | tests/fields/test_logical_types.py | import datetime
import uuid
import pytest
from dataclasses_avroschema import fields
from . import consts
@pytest.mark.parametrize(
"python_type,avro_type,logical_type", consts.LOGICAL_TYPES_AND_DEFAULTS
)
def test_logical_types(python_type, avro_type, logical_type):
name = "a logical type"
python_type ... | 0.721743 | 0.505554 |
import sys
_b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
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_in... | mtcnn_pb2.py |
import sys
_b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
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_in... | 0.177811 | 0.120516 |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import argparse
import os
import sys
import six
from paddlehub.commands.base_command import BaseCommand, ENTRY
from paddlehub.io.parser import yaml_parser, txt_parser
from paddlehub.module.manager import def... | paddlehub/commands/run.py |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import argparse
import os
import sys
import six
from paddlehub.commands.base_command import BaseCommand, ENTRY
from paddlehub.io.parser import yaml_parser, txt_parser
from paddlehub.module.manager import def... | 0.424531 | 0.097993 |
import structlog
from discord_webhook import DiscordWebhook as Webhook
from notifiers.utils import NotifierUtils
__max_message_size__ = 2000
class DiscordNotifier(NotifierUtils):
"""Class for handling Discord notifications
"""
def __init__(self, webhook, username, avatar=None):
"""Initialize Di... | app/notifiers/discord_client.py | import structlog
from discord_webhook import DiscordWebhook as Webhook
from notifiers.utils import NotifierUtils
__max_message_size__ = 2000
class DiscordNotifier(NotifierUtils):
"""Class for handling Discord notifications
"""
def __init__(self, webhook, username, avatar=None):
"""Initialize Di... | 0.565419 | 0.05163 |
import json
import logging
import os
import re
from pathlib import Path
from typing import List
from common import utilities
from models.phrase import Phrase
from models.phrase_group import PhraseGroup
from models.phrase_encoding import PhraseEncoding
from phrase_encoder_decoder import PhraseEncoderDecoder
## Config
... | modules/phrases/phrase_file_manager.py | import json
import logging
import os
import re
from pathlib import Path
from typing import List
from common import utilities
from models.phrase import Phrase
from models.phrase_group import PhraseGroup
from models.phrase_encoding import PhraseEncoding
from phrase_encoder_decoder import PhraseEncoderDecoder
## Config
... | 0.489015 | 0.13966 |
import os, sys, datetime
import environ
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
sys.path.insert(0,os.path.join(BASE_DIR,"apps"))
root = environ.Path(BASE_DIR)
public_root = root.path('public/')
# Quick-start developme... | loveshare/settings.py | import os, sys, datetime
import environ
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
sys.path.insert(0,os.path.join(BASE_DIR,"apps"))
root = environ.Path(BASE_DIR)
public_root = root.path('public/')
# Quick-start developme... | 0.291182 | 0.070464 |
import os
import numpy as np
from .base_data import Dataset, Sequence
from ..utils import read_file
from ..builder import BENCHMARKS
@BENCHMARKS.register_module
class VOT(Dataset):
def __init__(self,
name='vot',
vot_root='data/benchmark/vot17/',
zip_mode=False)... | siam_tracker/benchmarks/data/vot.py | import os
import numpy as np
from .base_data import Dataset, Sequence
from ..utils import read_file
from ..builder import BENCHMARKS
@BENCHMARKS.register_module
class VOT(Dataset):
def __init__(self,
name='vot',
vot_root='data/benchmark/vot17/',
zip_mode=False)... | 0.475605 | 0.144903 |
import datetime
import io
import logging
import os
import shlex
import signal
import tempfile
import pytest
import gemato.cli
from gemato.compression import open_potentially_compressed_path
from gemato.exceptions import (
ManifestUnsignedData,
ManifestSyntaxError,
OpenPGPNoImplementation,
OpenPGPVeri... | tests/test_openpgp.py |
import datetime
import io
import logging
import os
import shlex
import signal
import tempfile
import pytest
import gemato.cli
from gemato.compression import open_potentially_compressed_path
from gemato.exceptions import (
ManifestUnsignedData,
ManifestSyntaxError,
OpenPGPNoImplementation,
OpenPGPVeri... | 0.230313 | 0.056548 |
import unittest
from .context import src
from src import customer as cust
from src import product as prod
class TestCustomer(unittest.TestCase):
def setUp(self):
self.customer = cust.Customer(3.00,
4.2)
self.random_customers = []
self.n_rand = 10000
... | Mathematics/Statistics/Statistics and Probability Python Notebooks/Probability and Stats --PyDataNYC2019 /tests/test_customer.py | import unittest
from .context import src
from src import customer as cust
from src import product as prod
class TestCustomer(unittest.TestCase):
def setUp(self):
self.customer = cust.Customer(3.00,
4.2)
self.random_customers = []
self.n_rand = 10000
... | 0.477311 | 0.622172 |
from __future__ import absolute_import, division, print_function, unicode_literals
from fuse.components import Component
class Celery(Component):
component_type = 'taskrunner'
def project_home(self, payload):
self.context['project_home'] = payload
def project_identifier(self, payload):
s... | fuse/components/celery.py | from __future__ import absolute_import, division, print_function, unicode_literals
from fuse.components import Component
class Celery(Component):
component_type = 'taskrunner'
def project_home(self, payload):
self.context['project_home'] = payload
def project_identifier(self, payload):
s... | 0.556882 | 0.10217 |
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
import mptt.fields
class Migration(migrations.Migration):
initial = True
dependencies = [
('auth', '0012_alter_user_first_name_max_length'),
('structure', '0001_initial'),
('se... | mrmap/service/migrations/0002_auto_20210413_0935.py |
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
import mptt.fields
class Migration(migrations.Migration):
initial = True
dependencies = [
('auth', '0012_alter_user_first_name_max_length'),
('structure', '0001_initial'),
('se... | 0.546254 | 0.093761 |
import pandas as pd
import inflection
import math
import datetime
import pickle
import numpy as np
class House(object):
def __init__(self):
self.year_built_scaler = pickle.load(open('/home/andre/repos/House-Prices/parameter/year_built_scaler.pkl', 'rb'))
self.ms_sub_class_scaler = pickle.load... | api/house/House.py | import pandas as pd
import inflection
import math
import datetime
import pickle
import numpy as np
class House(object):
def __init__(self):
self.year_built_scaler = pickle.load(open('/home/andre/repos/House-Prices/parameter/year_built_scaler.pkl', 'rb'))
self.ms_sub_class_scaler = pickle.load... | 0.108827 | 0.039416 |
import torch
def criterion(p, s):
return torch.mean(-torch.exp(-(p - s)**2), dim=2)
def resnet_weights(device, c_in, kernel_size, c_out=None):
if c_out is None:
c_out = c_in * 2
w0 = torch.empty(c_out, c_in, 1, 1, device=device, requires_grad=True)
torch.nn.init.xavier_normal_(w0)
b0 =... | compare.py | import torch
def criterion(p, s):
return torch.mean(-torch.exp(-(p - s)**2), dim=2)
def resnet_weights(device, c_in, kernel_size, c_out=None):
if c_out is None:
c_out = c_in * 2
w0 = torch.empty(c_out, c_in, 1, 1, device=device, requires_grad=True)
torch.nn.init.xavier_normal_(w0)
b0 =... | 0.859354 | 0.589628 |
from .basedownload import BaseDownload
from sqlalchemy import Column, Integer, String, Float, DateTime
from typing import Optional
from sqlalchemy import MetaData, Table, create_engine
from datetime import datetime
class TencentQuotation(BaseDownload):
def __init__(self,
stock_num: int = 400,
... | easyquotation_enhance/tencent.py | from .basedownload import BaseDownload
from sqlalchemy import Column, Integer, String, Float, DateTime
from typing import Optional
from sqlalchemy import MetaData, Table, create_engine
from datetime import datetime
class TencentQuotation(BaseDownload):
def __init__(self,
stock_num: int = 400,
... | 0.767994 | 0.316066 |
import logging
import re
import sys
from concurrent.futures import ThreadPoolExecutor, as_completed
from datetime import datetime
from functools import wraps
from pathlib import Path
from typing import List, Optional, Union
import click
from .configuration import WorkspaceConfig
from .configuration.discovery import ... | src/remote/entrypoints.py | import logging
import re
import sys
from concurrent.futures import ThreadPoolExecutor, as_completed
from datetime import datetime
from functools import wraps
from pathlib import Path
from typing import List, Optional, Union
import click
from .configuration import WorkspaceConfig
from .configuration.discovery import ... | 0.531209 | 0.159185 |
from battle.battles.rounds import run_round
from battle.battles.email import result_battle
from pokemon.models import Pokemon
from pokemon.helpers import get_pokemon_from_api
def run_battle(battle):
teams = list(battle.teams.all())
assert len(teams) == 2, "Unexpected error. Battle has more than two teams."
... | backend/battle/battles/battle.py | from battle.battles.rounds import run_round
from battle.battles.email import result_battle
from pokemon.models import Pokemon
from pokemon.helpers import get_pokemon_from_api
def run_battle(battle):
teams = list(battle.teams.all())
assert len(teams) == 2, "Unexpected error. Battle has more than two teams."
... | 0.419767 | 0.331877 |
from pyramid_nested_ner.utils.text import default_tokenizer
from torch.nn.utils.rnn import pad_sequence
import torch
class PyramidLabelEncoder(object):
"""
Label encoder class responsible for transforming entity annotations
into torch.Tensors. The `transform` API returns two tensors: one fo-
r the py... | pyramid_nested_ner/vectorizers/labels/__init__.py | from pyramid_nested_ner.utils.text import default_tokenizer
from torch.nn.utils.rnn import pad_sequence
import torch
class PyramidLabelEncoder(object):
"""
Label encoder class responsible for transforming entity annotations
into torch.Tensors. The `transform` API returns two tensors: one fo-
r the py... | 0.849847 | 0.523664 |
import os
import sys
import numpy as np
import pandas as pd
import pybedtools
import re
import pyBigWig as pbw
import time
import urllib.request
import matplotlib.pyplot as plt
imputed_urls_path="../configs/Imputed_urls.txt"
observed_urls_path="../configs/Observed_urls.txt"
Enhancer_urls=pd.read_csv("../configs/enha... | scripts/Process_epimap_data.py | import os
import sys
import numpy as np
import pandas as pd
import pybedtools
import re
import pyBigWig as pbw
import time
import urllib.request
import matplotlib.pyplot as plt
imputed_urls_path="../configs/Imputed_urls.txt"
observed_urls_path="../configs/Observed_urls.txt"
Enhancer_urls=pd.read_csv("../configs/enha... | 0.251096 | 0.123868 |
from tests.common.utilities import wait_until
from tests.common.devices.eos import EosHost
from macsec_helper import *
def set_macsec_profile(host, profile_name, priority, cipher_suite, primary_cak, primary_ckn, policy, send_sci):
if isinstance(host, EosHost):
eos_cipher_suite = {
"GCM-AES-128... | tests/macsec/macsec_config_helper.py | from tests.common.utilities import wait_until
from tests.common.devices.eos import EosHost
from macsec_helper import *
def set_macsec_profile(host, profile_name, priority, cipher_suite, primary_cak, primary_ckn, policy, send_sci):
if isinstance(host, EosHost):
eos_cipher_suite = {
"GCM-AES-128... | 0.512693 | 0.127002 |
import tensorflow as tf
from tensorflow.keras import layers, Model
import numpy as np
from collections.abc import Iterable
from dl_playground.networks.utils import (
config_to_regularizer,
ActivityMonitor,
activation_function,
)
class MLP(layers.Layer):
"""Multi-layer perceptron.
Parameters
... | networks/layers/mlp.py | import tensorflow as tf
from tensorflow.keras import layers, Model
import numpy as np
from collections.abc import Iterable
from dl_playground.networks.utils import (
config_to_regularizer,
ActivityMonitor,
activation_function,
)
class MLP(layers.Layer):
"""Multi-layer perceptron.
Parameters
... | 0.895088 | 0.504822 |
import argparse
import logging
import matplotlib.pyplot as plt
import numpy as np
import torch.utils.data
from hardware.camera import RealSenseCamera
from hardware.device import get_device
from inference.post_process import post_process_output
from utils.data.camera_data import CameraData
from utils.visualisation.plo... | run_realtime.py | import argparse
import logging
import matplotlib.pyplot as plt
import numpy as np
import torch.utils.data
from hardware.camera import RealSenseCamera
from hardware.device import get_device
from inference.post_process import post_process_output
from utils.data.camera_data import CameraData
from utils.visualisation.plo... | 0.786459 | 0.160825 |
import logging
import rpyc
from paramiko.client import AutoAddPolicy
from plumbum import ProcessExecutionError
from plumbum.machines.paramiko_machine import ParamikoMachine
from rpyc.core.service import VoidService
from rpyc.core.stream import SocketStream
from rpyc.lib.compat import BYTES_LITERAL
import signal
def... | bnb/remote/deploy.py | import logging
import rpyc
from paramiko.client import AutoAddPolicy
from plumbum import ProcessExecutionError
from plumbum.machines.paramiko_machine import ParamikoMachine
from rpyc.core.service import VoidService
from rpyc.core.stream import SocketStream
from rpyc.lib.compat import BYTES_LITERAL
import signal
def... | 0.328206 | 0.103658 |
import click
from Bio import AlignIO
@click.group()
def cli():
pass
# https://www.biostars.org/p/326044/
def column(alignment):
'''Generator for getting list of characters in each column in the alignment'''
for i in range(alignment.get_alignment_length()):
c = []
for record in alignment:... | align.py | import click
from Bio import AlignIO
@click.group()
def cli():
pass
# https://www.biostars.org/p/326044/
def column(alignment):
'''Generator for getting list of characters in each column in the alignment'''
for i in range(alignment.get_alignment_length()):
c = []
for record in alignment:... | 0.502197 | 0.312134 |
import csv
import demoji
import json
import logging
import math
import re
import requests
from datetime import datetime
exclude_list = []
def preprocess_and_split_text(text):
text_without_emojis = demoji.replace_with_desc(text, sep=" ")
result = text_without_emojis.split()
return result
def remove_non_... | parser.py | import csv
import demoji
import json
import logging
import math
import re
import requests
from datetime import datetime
exclude_list = []
def preprocess_and_split_text(text):
text_without_emojis = demoji.replace_with_desc(text, sep=" ")
result = text_without_emojis.split()
return result
def remove_non_... | 0.202917 | 0.116613 |
import diagnostic_msgs
import diagnostic_updater
import roboclaw_driver as roboclaw
import rospy
from motion_control.msg import RoboclawCommand
class Node:
def __init__(self):
self.ERRORS = {0x0000: (diagnostic_msgs.msg.DiagnosticStatus.OK, "Normal"),
0x0001: (diagnostic_msgs.msg.Di... | src/RoboclawNodeCustom.py | import diagnostic_msgs
import diagnostic_updater
import roboclaw_driver as roboclaw
import rospy
from motion_control.msg import RoboclawCommand
class Node:
def __init__(self):
self.ERRORS = {0x0000: (diagnostic_msgs.msg.DiagnosticStatus.OK, "Normal"),
0x0001: (diagnostic_msgs.msg.Di... | 0.275227 | 0.129458 |
import os
import pytest
import time
from benchengine.db import DatabaseDriver
from benchengine.user.manager import UserManager
import benchengine.error as err
import benchtmpl.util.core as util
class TestUserManager(object):
"""Test user registration and password reset."""
def connect(self, base_dir):
... | tests/user/test_user_manager.py | import os
import pytest
import time
from benchengine.db import DatabaseDriver
from benchengine.user.manager import UserManager
import benchengine.error as err
import benchtmpl.util.core as util
class TestUserManager(object):
"""Test user registration and password reset."""
def connect(self, base_dir):
... | 0.39129 | 0.240685 |
import logging
import os
from pathlib import Path
import re
from typing import Any
from typing import List
from typing import Optional
from typing import Tuple
import numpy as np
import requests
from urllib.parse import urlparse
DEFAULT_NON_SPEECH_THRESHOLD_FRACTION = 0.5
ALL_SURAHS = None
NUM_SURAHS = 114
NO_FRAMES_... | utils/recording.py | import logging
import os
from pathlib import Path
import re
from typing import Any
from typing import List
from typing import Optional
from typing import Tuple
import numpy as np
import requests
from urllib.parse import urlparse
DEFAULT_NON_SPEECH_THRESHOLD_FRACTION = 0.5
ALL_SURAHS = None
NUM_SURAHS = 114
NO_FRAMES_... | 0.816662 | 0.248637 |
import numpy as np
import netCDF4
import pandas as pd
import xarray as xr
from pylab import *
import cartopy.crs as ccrs
from matplotlib import pyplot as plt
import seaborn as sns
import os
from scipy.interpolate import griddata
from datetime import datetime
from datetime import timedelta
from dateutil i... | PostProcessing.py | import numpy as np
import netCDF4
import pandas as pd
import xarray as xr
from pylab import *
import cartopy.crs as ccrs
from matplotlib import pyplot as plt
import seaborn as sns
import os
from scipy.interpolate import griddata
from datetime import datetime
from datetime import timedelta
from dateutil i... | 0.31384 | 0.408454 |
import unittest
import psycopg2
from relately.select import Select
from . import RelatelyTest
class TestQuery(RelatelyTest):
def test_star_from_table(self):
r = self.engine.select({
"columns":'*',
"target":"world.city"
})
self.assertEqual(len(r), 4079)
s... | test/test_query.py | import unittest
import psycopg2
from relately.select import Select
from . import RelatelyTest
class TestQuery(RelatelyTest):
def test_star_from_table(self):
r = self.engine.select({
"columns":'*',
"target":"world.city"
})
self.assertEqual(len(r), 4079)
s... | 0.360939 | 0.50952 |
import pandas as pd
import math as mt
import re
data_dir = 'E:/data/2019_patent_novelty_aux_files/' # Original data directory
out_dir = 'E:/data/2020_research_policy_replicate_results/' # Output directory
# Input files
claims_file = data_dir+'claim_full_till2018.csv'
title_abstract_file = data_dir+'patent_title_abs... | step_01_concatenate_patents.py | import pandas as pd
import math as mt
import re
data_dir = 'E:/data/2019_patent_novelty_aux_files/' # Original data directory
out_dir = 'E:/data/2020_research_policy_replicate_results/' # Output directory
# Input files
claims_file = data_dir+'claim_full_till2018.csv'
title_abstract_file = data_dir+'patent_title_abs... | 0.24726 | 0.114393 |
import sys, Image, ImageDraw, ImageFont
from optparse import OptionParser
import os
import StringIO
def get_font_info(chars, font):
img = Image.new('RGBA', (100, 100), (0, 0, 0, 0))
draw = ImageDraw.Draw(img)
height_prefer = 0
width_min = 0xffff
width_max = 0
for ch, _, _ in chars:
width, height = draw.texts... | make_font.py | import sys, Image, ImageDraw, ImageFont
from optparse import OptionParser
import os
import StringIO
def get_font_info(chars, font):
img = Image.new('RGBA', (100, 100), (0, 0, 0, 0))
draw = ImageDraw.Draw(img)
height_prefer = 0
width_min = 0xffff
width_max = 0
for ch, _, _ in chars:
width, height = draw.texts... | 0.11181 | 0.163079 |
from sonar.core.include.utilities import extractNumber
def strToInt(packet):
packetArgs = packet[1:-1].split(",")
intVal = 0
if packetArgs[0] == "AMHeader":
assert (len(packetArgs) == 7),"Invalid number of arguments for AMHeader"
if ":" not in packetArgs[1]:
argSrc = packetArgs... | GAScore/testbench/sonar_strToInt.py | from sonar.core.include.utilities import extractNumber
def strToInt(packet):
packetArgs = packet[1:-1].split(",")
intVal = 0
if packetArgs[0] == "AMHeader":
assert (len(packetArgs) == 7),"Invalid number of arguments for AMHeader"
if ":" not in packetArgs[1]:
argSrc = packetArgs... | 0.17621 | 0.309663 |
import argparse
from sys import stdout, exit, stderr
from simtk.openmm.app import *
from simtk.openmm import *
from simtk.unit import *
def parse_args():
parser = argparse.ArgumentParser(description="Generate and equilibrate a water box")
parser.add_argument("-T", "--temperature", action="store", default=298.... | scripts/prepare-water-box.py | import argparse
from sys import stdout, exit, stderr
from simtk.openmm.app import *
from simtk.openmm import *
from simtk.unit import *
def parse_args():
parser = argparse.ArgumentParser(description="Generate and equilibrate a water box")
parser.add_argument("-T", "--temperature", action="store", default=298.... | 0.483648 | 0.239505 |
""" Functions for generating the output yaml """
import compose.config
import sys
from compose.config import serialize, environment
import yaml
import compose_mode
_FILE_LIST_PREFIX = '# '
HEADER_TEMPLATE = """
# ==============================================================================
# !! DO NOT EDIT !!
#... | compose_mode/generate.py | """ Functions for generating the output yaml """
import compose.config
import sys
from compose.config import serialize, environment
import yaml
import compose_mode
_FILE_LIST_PREFIX = '# '
HEADER_TEMPLATE = """
# ==============================================================================
# !! DO NOT EDIT !!
#... | 0.524151 | 0.194616 |
import re
from typing import Any, Dict, Iterable, List
import unicodedata
# =============================================================================
# Finding
# =============================================================================
def find_nth(s: str, x: str, n: int = 0, overlap: bool = False) -> int:
... | cardinal_pythonlib/stringfunc.py | import re
from typing import Any, Dict, Iterable, List
import unicodedata
# =============================================================================
# Finding
# =============================================================================
def find_nth(s: str, x: str, n: int = 0, overlap: bool = False) -> int:
... | 0.838151 | 0.477554 |
import gzip
import os
import re
import pandas as pd
# CalN50
total_length = []
number_contigs = []
nx_lx = []
## Process individual files
for s in snakemake.params.samples:
fn = f"{snakemake.params.caln50_dir}/{s}-{snakemake.params.assembler}.caln"
nl = []
with open(fn, "rt") as caln50file:
for l... | workflow/scripts/summary.py | import gzip
import os
import re
import pandas as pd
# CalN50
total_length = []
number_contigs = []
nx_lx = []
## Process individual files
for s in snakemake.params.samples:
fn = f"{snakemake.params.caln50_dir}/{s}-{snakemake.params.assembler}.caln"
nl = []
with open(fn, "rt") as caln50file:
for l... | 0.216094 | 0.165121 |
from ament_index_python.packages import get_package_share_path
from launch_ros.actions import Node
from launch import LaunchDescription
from launch.actions import Shutdown
from slamcore_ros2_examples.configuration import Configuration
from slamcore_ros2_examples.utils import add_all_actions
def generate_launch_descr... | src/slamcore_ros2_examples/launch/kobuki_setup_comms_launch.py | from ament_index_python.packages import get_package_share_path
from launch_ros.actions import Node
from launch import LaunchDescription
from launch.actions import Shutdown
from slamcore_ros2_examples.configuration import Configuration
from slamcore_ros2_examples.utils import add_all_actions
def generate_launch_descr... | 0.405449 | 0.203252 |
from typing import Dict, Iterator, List, Tuple
def adjacent_digits(n: int, digits: str) -> List[str]:
"""List of all adjacent digits of `n` length in `digits`."""
adjacents = []
while len(digits) >= n:
adjacents.append(digits[:n])
digits = digits[1:]
return adjacents
def fibo(nth: in... | euler/main.py |
from typing import Dict, Iterator, List, Tuple
def adjacent_digits(n: int, digits: str) -> List[str]:
"""List of all adjacent digits of `n` length in `digits`."""
adjacents = []
while len(digits) >= n:
adjacents.append(digits[:n])
digits = digits[1:]
return adjacents
def fibo(nth: in... | 0.903361 | 0.572125 |
import re
from typing import List, Tuple
import discord
from cachetools import TTLCache
from discord.ext import commands
from bot.bot import PeaceBot
from bot.utils.mixins.better_cog import BetterCog
from models import AutoResponseModel
class AutoResponseError(commands.CommandError):
pass
class AutoResponseHa... | bot/utils/autoresponse_handler.py | import re
from typing import List, Tuple
import discord
from cachetools import TTLCache
from discord.ext import commands
from bot.bot import PeaceBot
from bot.utils.mixins.better_cog import BetterCog
from models import AutoResponseModel
class AutoResponseError(commands.CommandError):
pass
class AutoResponseHa... | 0.705379 | 0.116236 |
from __future__ import absolute_import, division, print_function
from google.cloud import bigquery
from .utilities.utility_functions import dictionary_key_exists
def create_google_client_connection(project):
# Construct a BigQuery client object.
client = bigquery.Client(
project=project
)
re... | get-gbq-permissions/gcp_utilities/gbq.py | from __future__ import absolute_import, division, print_function
from google.cloud import bigquery
from .utilities.utility_functions import dictionary_key_exists
def create_google_client_connection(project):
# Construct a BigQuery client object.
client = bigquery.Client(
project=project
)
re... | 0.446857 | 0.163145 |
import os
import subprocess as sp
from shlex import split
from pathlib import Path
__version__ = '0.3'
GITHUB_EVENT_NAME = os.environ['GITHUB_EVENT_NAME']
# Set repository
CURRENT_REPOSITORY = os.environ.get('GITHUB_REPOSITORY', '')
# TODO: How about PRs from forks?
TARGET_REPO = os.environ.get('INPUT_TARGET_REPOSI... | src/entrypoint.py | import os
import subprocess as sp
from shlex import split
from pathlib import Path
__version__ = '0.3'
GITHUB_EVENT_NAME = os.environ['GITHUB_EVENT_NAME']
# Set repository
CURRENT_REPOSITORY = os.environ.get('GITHUB_REPOSITORY', '')
# TODO: How about PRs from forks?
TARGET_REPO = os.environ.get('INPUT_TARGET_REPOSI... | 0.145813 | 0.045395 |
import io
import math
from collections import Counter
from tqdm import tqdm
import tensorflow as tf # TF 2.0
FILE_PATH = './data/'
def create_dataset(path, limit_size=None):
lines = io.open(path, encoding='UTF-8').read().strip().split('\n')
lines = ['<s> ' + line + ' </s>' for line in tqdm(lines[:limit_si... | utils.py |
import io
import math
from collections import Counter
from tqdm import tqdm
import tensorflow as tf # TF 2.0
FILE_PATH = './data/'
def create_dataset(path, limit_size=None):
lines = io.open(path, encoding='UTF-8').read().strip().split('\n')
lines = ['<s> ' + line + ' </s>' for line in tqdm(lines[:limit_si... | 0.511717 | 0.224682 |
import random
from faker import Faker
from .models import User, Post, Comment, Widget, Role
fake = Faker('zh_CN')
def fake_admin():
user = User(username='admin',
name='waynerv',
email='<EMAIL>',
role='admin',
bio='Hello guys.')
user.set_passwo... | app/originblog/fake.py | import random
from faker import Faker
from .models import User, Post, Comment, Widget, Role
fake = Faker('zh_CN')
def fake_admin():
user = User(username='admin',
name='waynerv',
email='<EMAIL>',
role='admin',
bio='Hello guys.')
user.set_passwo... | 0.327991 | 0.054828 |
import keras
from keras.applications.resnet50 import ResNet50
from keras.layers import Dense, GlobalAveragePooling2D
from keras.models import Model
from keras.optimizers import Adam
import os
from keras.preprocessing.image import ImageDataGenerator
from keras.callbacks import ModelCheckpoint, ReduceLROnPlateau, TensorB... | checkbox/train.py | import keras
from keras.applications.resnet50 import ResNet50
from keras.layers import Dense, GlobalAveragePooling2D
from keras.models import Model
from keras.optimizers import Adam
import os
from keras.preprocessing.image import ImageDataGenerator
from keras.callbacks import ModelCheckpoint, ReduceLROnPlateau, TensorB... | 0.70619 | 0.219547 |
import json
import string
# The paths need to be updated
visdial_train_data_file = 'visdial_0.9_train.json'
visdial_val_data_file = 'visdial_0.9_val.json'
vdtrain_questions_file = 'v2_OpenEnded_mscoco_vdtrain_questions.json'
vdval_questions_file = 'v2_OpenEnded_mscoco_vdval_questions.json'
vdtrain_annotations_fil... | tools/convert_VD_to_COCO_qa.py |
import json
import string
# The paths need to be updated
visdial_train_data_file = 'visdial_0.9_train.json'
visdial_val_data_file = 'visdial_0.9_val.json'
vdtrain_questions_file = 'v2_OpenEnded_mscoco_vdtrain_questions.json'
vdval_questions_file = 'v2_OpenEnded_mscoco_vdval_questions.json'
vdtrain_annotations_fil... | 0.127938 | 0.095392 |
import tkinter as tk
from tkinter import font as tkfont
import sys , os , getpass , socket , subprocess
from datetime import datetime
from pathlib import Path
import ctypes
def check_elevate():
if ctypes.windll.shell32.IsUserAnAdmin():
return "Administrator: "
else:
return ""
root... | shell_main.py | import tkinter as tk
from tkinter import font as tkfont
import sys , os , getpass , socket , subprocess
from datetime import datetime
from pathlib import Path
import ctypes
def check_elevate():
if ctypes.windll.shell32.IsUserAnAdmin():
return "Administrator: "
else:
return ""
root... | 0.158826 | 0.069668 |
import unittest.mock as mock
import builtins
import json
import socket
# 3rd party imports
import pytest
# two1 imorts
from two1.commands.util import bitcoin_computer
# String to use as the content of the mocked file
UUID_STR = "12345678-1234-1234-1234-123456789012"
@pytest.mark.parametrize("mock_file, side_effect... | tests/commands/util/test_bitcoin_computer.py | import unittest.mock as mock
import builtins
import json
import socket
# 3rd party imports
import pytest
# two1 imorts
from two1.commands.util import bitcoin_computer
# String to use as the content of the mocked file
UUID_STR = "12345678-1234-1234-1234-123456789012"
@pytest.mark.parametrize("mock_file, side_effect... | 0.73659 | 0.371365 |
import torch
from typing import Dict
def true_negative(prediction: torch.Tensor, label: torch.Tensor) -> float:
"""
Return sum of all true negative pixel.
:param prediction: Predicted tensor.
:param label: Label tensor.
:return: True negative count.
"""
return torch.sum(~prediction & ~lab... | validation/metrics.py | import torch
from typing import Dict
def true_negative(prediction: torch.Tensor, label: torch.Tensor) -> float:
"""
Return sum of all true negative pixel.
:param prediction: Predicted tensor.
:param label: Label tensor.
:return: True negative count.
"""
return torch.sum(~prediction & ~lab... | 0.936176 | 0.939803 |
# %%
from warnings import warn
from biosteam.utils import MissingStream
from . import Stream
__all__ = ('SanStream', 'MissingSanStream')
setattr = object.__setattr__
class SanStream(Stream):
'''
A subclass of :class:`thermosteam.Stream` with additional attributes
for environmental impacts.
.. note:... | qsdsan/_sanstream.py | # %%
from warnings import warn
from biosteam.utils import MissingStream
from . import Stream
__all__ = ('SanStream', 'MissingSanStream')
setattr = object.__setattr__
class SanStream(Stream):
'''
A subclass of :class:`thermosteam.Stream` with additional attributes
for environmental impacts.
.. note:... | 0.785884 | 0.314958 |
from edgedb.lang.edgeql import ast as qlast
from . import delta as sd
from . import derivable
from . import inheriting
from . import name as sn
from . import named
from . import objects as so
from . import referencing
class Action(inheriting.InheritingObject):
_type = 'action'
class ActionSet(so.ObjectSet, t... | edgedb/lang/schema/policy.py |
from edgedb.lang.edgeql import ast as qlast
from . import delta as sd
from . import derivable
from . import inheriting
from . import name as sn
from . import named
from . import objects as so
from . import referencing
class Action(inheriting.InheritingObject):
_type = 'action'
class ActionSet(so.ObjectSet, t... | 0.603581 | 0.175679 |
import unittest
from sistema_clasico_cuantico import canicas_clicks, probabilistico_clicks, cuantico_clicks, grafico
class sistema_clasico_cualtico(unittest.TestCase):
def testcanicas_clicks(self):
matriz_booleana = [[True, True, False, False, True, False], [True, True, False, True, False, False],
... | test_cuantico.py | import unittest
from sistema_clasico_cuantico import canicas_clicks, probabilistico_clicks, cuantico_clicks, grafico
class sistema_clasico_cualtico(unittest.TestCase):
def testcanicas_clicks(self):
matriz_booleana = [[True, True, False, False, True, False], [True, True, False, True, False, False],
... | 0.377885 | 0.568476 |
from django.core.management.base import BaseCommand
from Product.models import Product, Category, Store
from .api_get import Api_get
class Command(BaseCommand):
help = "initialize database"
def handle(self, *args, **kwargs):
"""retrieve a list of products in JSON format through Open Food Fact
... | Product/management/commands/create_db.py | from django.core.management.base import BaseCommand
from Product.models import Product, Category, Store
from .api_get import Api_get
class Command(BaseCommand):
help = "initialize database"
def handle(self, *args, **kwargs):
"""retrieve a list of products in JSON format through Open Food Fact
... | 0.527803 | 0.126596 |
import argparse
from intern.remote.boss import BossRemote
from intern.resource.boss.resource import *
import json
import os
# Name of group to assign read-only privileges to.
GOV_TEAM = 'gov_team'
def create_collection(config, rmt):
"""
Ensure collection exists.
Args:
config (dict):
rmt ... | ingestclient/prep_ingest.py | import argparse
from intern.remote.boss import BossRemote
from intern.resource.boss.resource import *
import json
import os
# Name of group to assign read-only privileges to.
GOV_TEAM = 'gov_team'
def create_collection(config, rmt):
"""
Ensure collection exists.
Args:
config (dict):
rmt ... | 0.620162 | 0.134321 |
import re
import os
import datetime
from functools import partial
import pandas as pd
import numpy as np
from collections import defaultdict
# -------------------------------
# dataframe on disk caching layer
# -------------------------------
class DataFrameToCSVCache:
""" Dict-like API CSV based cache to store d... | jupyter/swan.py | import re
import os
import datetime
from functools import partial
import pandas as pd
import numpy as np
from collections import defaultdict
# -------------------------------
# dataframe on disk caching layer
# -------------------------------
class DataFrameToCSVCache:
""" Dict-like API CSV based cache to store d... | 0.628749 | 0.185412 |
# template file: justice_py_sdk_codegen/__main__.py
# justice-iam-service (5.10.1)
# pylint: disable=duplicate-code
# pylint: disable=line-too-long
# pylint: disable=missing-function-docstring
# pylint: disable=missing-module-docstring
# pylint: disable=too-many-arguments
# pylint: disable=too-many-branches
# pylint... | accelbyte_py_sdk/api/iam/models/model_link_request.py |
# template file: justice_py_sdk_codegen/__main__.py
# justice-iam-service (5.10.1)
# pylint: disable=duplicate-code
# pylint: disable=line-too-long
# pylint: disable=missing-function-docstring
# pylint: disable=missing-module-docstring
# pylint: disable=too-many-arguments
# pylint: disable=too-many-branches
# pylint... | 0.535827 | 0.097691 |
from __future__ import annotations
from typing import List
import numpy as np
from nncg.allocation import Allocation
from nncg.nodes.expressions import Variable
from nncg.nodes.misc import Node
from nncg.writer import Writer
class CHeaderNode(Node):
"""
Class for writing everything in a C file that is above t... | nncg/nodes/language.py | from __future__ import annotations
from typing import List
import numpy as np
from nncg.allocation import Allocation
from nncg.nodes.expressions import Variable
from nncg.nodes.misc import Node
from nncg.writer import Writer
class CHeaderNode(Node):
"""
Class for writing everything in a C file that is above t... | 0.561335 | 0.24931 |
from __future__ import print_function, unicode_literals, division, absolute_import
import os, sys, io, locale, threading
from io import TextIOWrapper
from contextlib import contextmanager
from collections import MutableMapping
try:
sys_encoding = locale.getdefaultlocale()[1] or "UTF-8"
except Exception:
sys_... | src/python/dxpy/compat.py |
from __future__ import print_function, unicode_literals, division, absolute_import
import os, sys, io, locale, threading
from io import TextIOWrapper
from contextlib import contextmanager
from collections import MutableMapping
try:
sys_encoding = locale.getdefaultlocale()[1] or "UTF-8"
except Exception:
sys_... | 0.326808 | 0.053059 |
import os, sys, argparse, logging, boto3
from io import BytesIO
from time import sleep
from picamera import PiCamera
from ftplib import FTP
def acquire_image(log, args):
output_stream = BytesIO()
try:
camera = PiCamera()
camera.resolution = (args.res_width, args.res_height)
# Camera warm-up time for automatic... | berrycam/berrycam.py |
import os, sys, argparse, logging, boto3
from io import BytesIO
from time import sleep
from picamera import PiCamera
from ftplib import FTP
def acquire_image(log, args):
output_stream = BytesIO()
try:
camera = PiCamera()
camera.resolution = (args.res_width, args.res_height)
# Camera warm-up time for automatic... | 0.267026 | 0.152347 |
from __future__ import absolute_import, division, print_function, unicode_literals
from transitions import Machine
from socks5.exception import ProtocolError
from ._reader import read_auth_request, read_auth_response
from ._writer import write_auth_request, write_auth_response
class _ClientConnection(object):
s... | socks5/auth/rfc1929/connection.py | from __future__ import absolute_import, division, print_function, unicode_literals
from transitions import Machine
from socks5.exception import ProtocolError
from ._reader import read_auth_request, read_auth_response
from ._writer import write_auth_request, write_auth_response
class _ClientConnection(object):
s... | 0.649467 | 0.2027 |
import redis
import hiredis
import pickle
from redis.sentinel import Sentinel
from Globals import Packet as pack
class RedisDB_Wrapper:
def __init__(self, db_number, host_IP='127.0.0.1', port=6379):
self._isDbConnectionActive = False
self._hostIP = host_IP
self._port = port
self._db... | DB/Redis_DB_Controller.py | import redis
import hiredis
import pickle
from redis.sentinel import Sentinel
from Globals import Packet as pack
class RedisDB_Wrapper:
def __init__(self, db_number, host_IP='127.0.0.1', port=6379):
self._isDbConnectionActive = False
self._hostIP = host_IP
self._port = port
self._db... | 0.219756 | 0.07208 |
from apiclient import errors
import os
import _config_ as _cfg
import _dbms_ as _db
import _logging_ as _log
def get_labels(db, labels_obj, user_id='me'):
results = labels_obj.list(userId='me').execute()
labels = results.get('labels', [])
if not labels:
_log.logger.info("No labels found.")
... | _google_/gmail/__init__.py | from apiclient import errors
import os
import _config_ as _cfg
import _dbms_ as _db
import _logging_ as _log
def get_labels(db, labels_obj, user_id='me'):
results = labels_obj.list(userId='me').execute()
labels = results.get('labels', [])
if not labels:
_log.logger.info("No labels found.")
... | 0.573798 | 0.082697 |
from PyQt5.QtCore import Qt
from PyQt5.QtWidgets import QInputDialog, QDialog
from Business.PartAction import create_add_sketch_to_part, insert_sketch_in_part
from GUI.Widgets.SimpleDialogs import SketchDialog
from GUI.init import plugin_initializers, tr
from GUI.Ribbon.RibbonButton import RibbonButton
class PartSk... | GUI/Plugins/PartSketch.py | from PyQt5.QtCore import Qt
from PyQt5.QtWidgets import QInputDialog, QDialog
from Business.PartAction import create_add_sketch_to_part, insert_sketch_in_part
from GUI.Widgets.SimpleDialogs import SketchDialog
from GUI.init import plugin_initializers, tr
from GUI.Ribbon.RibbonButton import RibbonButton
class PartSk... | 0.451085 | 0.104889 |