code stringlengths 22 1.05M | apis listlengths 1 3.31k | extract_api stringlengths 75 3.25M |
|---|---|---|
# Standard Libraries
# Third party packages
import ipaddress
from pydantic import root_validator, conint, constr
from pydantic.typing import Union, Optional, List, Literal, List
# Local package
from net_models.fields import (
GENERIC_OBJECT_NAME, VRF_NAME, VLAN_ID, BRIDGE_DOMAIN_ID,
ROUTE_TARGET, ROUTE_DISTING... | [
"pydantic.conint",
"pydantic.constr",
"pydantic.root_validator"
] | [((1426, 1458), 'pydantic.root_validator', 'root_validator', ([], {'allow_reuse': '(True)'}), '(allow_reuse=True)\n', (1440, 1458), False, 'from pydantic import root_validator, conint, constr\n'), ((3413, 3445), 'pydantic.root_validator', 'root_validator', ([], {'allow_reuse': '(True)'}), '(allow_reuse=True)\n', (3427,... |
"""
Copyright 2020 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, software
d... | [
"absl.app.UsageError",
"discretezoo.metrics.sentence_bleu_scores",
"tensorflow.summary.experimental.set_step",
"discretezoo.attack_setup.sort_dataset",
"absl.logging.info",
"nltk.tokenize.treebank.TreebankWordDetokenizer",
"discretezoo.attack_setup.load_embeddings",
"absl.flags.DEFINE_enum",
"tensor... | [((1145, 1220), 'absl.flags.DEFINE_string', 'flags.DEFINE_string', (['"""model"""', 'None', '"""The directory of the model to attack."""'], {}), "('model', None, 'The directory of the model to attack.')\n", (1164, 1220), False, 'from absl import flags\n'), ((1221, 1318), 'absl.flags.DEFINE_integer', 'flags.DEFINE_integ... |
# -*- coding: utf-8 -*-
# Generated by Django 1.11.6 on 2017-10-13 03:23
from __future__ import unicode_literals
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('cert_manager', '0001_initial'),
]
operations = [
migrations.AlterModelOptions(
... | [
"django.db.migrations.AlterModelOptions"
] | [((286, 488), 'django.db.migrations.AlterModelOptions', 'migrations.AlterModelOptions', ([], {'name': '"""certificatefingerprintmodel"""', 'options': "{'ordering': ['created'], 'verbose_name': 'certificate fingerprint',\n 'verbose_name_plural': 'certificate fingerprints'}"}), "(name='certificatefingerprintmodel', op... |
#coding=UTF-8
'''
Created on 2011-7-7
@author: Administrator
'''
import Queue
fetch_quere=Queue.Queue() | [
"Queue.Queue"
] | [((91, 104), 'Queue.Queue', 'Queue.Queue', ([], {}), '()\n', (102, 104), False, 'import Queue\n')] |
# -*- coding: utf-8 -*-
# Part of Odoo. See LICENSE file for full copyright and licensing details.
from odoo import api, models, fields
class WebsiteConfigSettings(models.TransientModel):
_inherit = 'website.config.settings'
def _default_order_mail_template(self):
if self.env['ir.module.module'].sea... | [
"odoo.fields.Many2one",
"odoo.api.onchange",
"odoo.fields.Boolean",
"odoo.fields.Selection"
] | [((569, 661), 'odoo.fields.Many2one', 'fields.Many2one', (['"""res.users"""'], {'related': '"""website_id.salesperson_id"""', 'string': '"""Salesperson"""'}), "('res.users', related='website_id.salesperson_id', string=\n 'Salesperson')\n", (584, 661), False, 'from odoo import api, models, fields\n'), ((676, 764), 'o... |
import click
import pyperclip
from ..utils.logging import logger
from ..utils.exceptions import handle_exceptions
from ..utils.load import get_default_code_name
import os
@click.command(short_help='Copies code from file to clipboard.')
@click.argument('code_file',
type=click.Path(exists=True, dir_okay... | [
"os.path.exists",
"click.command",
"click.Path"
] | [((174, 237), 'click.command', 'click.command', ([], {'short_help': '"""Copies code from file to clipboard."""'}), "(short_help='Copies code from file to clipboard.')\n", (187, 237), False, 'import click\n'), ((288, 327), 'click.Path', 'click.Path', ([], {'exists': '(True)', 'dir_okay': '(False)'}), '(exists=True, dir_... |
import paho.mqtt.client as mqtt
import sched, time, threading,os
import json,logging, traceback
from datetime import datetime, timedelta
LOGLEVEL = os.environ.get('HABLIB_LOGLEVEL', 'INFO').upper()
FORMATTER = os.environ.get('HABLIB_FORMAT', '[%(asctime)s] p%(process)s {%(pathname)s:%(lineno)d} %(levelname)s - %(messag... | [
"traceback.format_exc",
"logging.StreamHandler",
"logging.debug",
"paho.mqtt.client.Client",
"threading.Timer",
"json.dumps",
"os.environ.get",
"datetime.datetime.now",
"logging.FileHandler",
"sched.scheduler",
"logging.info",
"logging.error"
] | [((210, 334), 'os.environ.get', 'os.environ.get', (['"""HABLIB_FORMAT"""', '"""[%(asctime)s] p%(process)s {%(pathname)s:%(lineno)d} %(levelname)s - %(message)s"""'], {}), "('HABLIB_FORMAT',\n '[%(asctime)s] p%(process)s {%(pathname)s:%(lineno)d} %(levelname)s - %(message)s'\n )\n", (224, 334), False, 'import sche... |
from .blockstate import BlockState
import math
import minecraft.TAG as TAG
import mmap
import os
import time
import util
class Chunk(TAG.MutableMapping, util.Cache):
"""Chunk data model and interface
Chunks are opened and saved directly, abstracting .mca files
"""
__slots__ = ['_cache... | [
"minecraft.TAG.Compound.__getitem__",
"util.get_bits",
"minecraft.TAG.Compound.__setitem__",
"util.Cache.__setitem__",
"minecraft.TAG.Long",
"util.set_bits",
"minecraft.TAG.Compound.__delitem__",
"util.Cache.__delitem__",
"util.Cache.__getitem__",
"minecraft.TAG.Byte"
] | [((741, 774), 'util.Cache.__delitem__', 'util.Cache.__delitem__', (['self', 'key'], {}), '(self, key)\n', (763, 774), False, 'import util\n'), ((803, 838), 'minecraft.TAG.Compound.__delitem__', 'TAG.Compound.__delitem__', (['self', 'key'], {}), '(self, key)\n', (827, 838), True, 'import minecraft.TAG as TAG\n'), ((1026... |
from datetime import date,datetime,timedelta
from random import randint
from bokeh.io import output_file, show
from bokeh.layouts import widgetbox, Spacer
from bokeh.models import ColumnDataSource,CustomJS,Div
from bokeh.models.widgets import DataTable, DateFormatter, TableColumn, Tabs, Panel
from bokeh.models.widgets ... | [
"bokeh.models.Div",
"bokeh.models.widgets.DateFormatter",
"bokeh.plotting.figure",
"bokeh.models.widgets.Select",
"bokeh.models.widgets.Button",
"pandas_datareader.get_data_yahoo",
"bokeh.models.widgets.DataTable",
"bokeh.models.ColumnDataSource",
"bokeh.models.widgets.TableColumn",
"traceback.pri... | [((1934, 1961), 'bokeh.models.ColumnDataSource', 'ColumnDataSource', (['self.data'], {}), '(self.data)\n', (1950, 1961), False, 'from bokeh.models import ColumnDataSource, CustomJS, Div\n'), ((7147, 7184), 'bokeh.models.widgets.Button', 'Button', ([], {'label': "self._settings['label']"}), "(label=self._settings['label... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
from feature_extraction import *
from detection import *
import pickle
import random
import matplotlib.pyplot as plt
from sklearn.preprocessing import RobustScaler
if __name__ == '__main__':
with open('udacity_data.p', 'rb') as f:
cars = pickle.load(f)
... | [
"matplotlib.pyplot.imshow",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.plot",
"pickle.load",
"matplotlib.pyplot.figure",
"sklearn.preprocessing.RobustScaler",
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.subplots"
] | [((565, 584), 'matplotlib.pyplot.imshow', 'plt.imshow', (['car_img'], {}), '(car_img)\n', (575, 584), True, 'import matplotlib.pyplot as plt\n'), ((589, 617), 'matplotlib.pyplot.savefig', 'plt.savefig', (['"""car_image.png"""'], {}), "('car_image.png')\n", (600, 617), True, 'import matplotlib.pyplot as plt\n'), ((989, ... |
from InstagramAPI import InstagramAPI as IG
from random import randint
from pprint import PrettyPrinter
from operator import itemgetter
import time
import yaml
import os
# This Python script is to list down all your following's followers
# The result will generated into tmp/ folder
pp = PrettyPrinter(indent=2)
d1 =... | [
"InstagramAPI.InstagramAPI",
"os.path.dirname",
"pprint.PrettyPrinter",
"operator.itemgetter",
"time.localtime",
"time.time",
"random.randint"
] | [((291, 314), 'pprint.PrettyPrinter', 'PrettyPrinter', ([], {'indent': '(2)'}), '(indent=2)\n', (304, 314), False, 'from pprint import PrettyPrinter\n'), ((786, 836), 'InstagramAPI.InstagramAPI', 'IG', (["ig_account['username']", "ig_account['password']"], {}), "(ig_account['username'], ig_account['password'])\n", (788... |
import itertools
# combine iterators
it = itertools.chain([1, 2, 3], [4, 5, 6])
# repeat a value
it = itertools.repeat("hello", 3)
print(list(it))
# repeat an iterator's items
it = itertools.cycle([1, 2])
result = [next(it) for _ in range(10)]
print(result)
# split an iterator
it1, it2, it3 = itertools.tee(["fir... | [
"itertools.chain",
"itertools.cycle",
"itertools.zip_longest",
"itertools.tee",
"itertools.repeat"
] | [((43, 80), 'itertools.chain', 'itertools.chain', (['[1, 2, 3]', '[4, 5, 6]'], {}), '([1, 2, 3], [4, 5, 6])\n', (58, 80), False, 'import itertools\n'), ((105, 133), 'itertools.repeat', 'itertools.repeat', (['"""hello"""', '(3)'], {}), "('hello', 3)\n", (121, 133), False, 'import itertools\n'), ((186, 209), 'itertools.c... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
""" Little program to build a mini index station_id:station_name
from the official Trainline stations.csv"""
import pandas as pd
import io
import requests
_STATIONS_CSV_FILE = "https://raw.githubusercontent.com/\
trainline-eu/stations/master/stations.csv"
csv_content =... | [
"requests.get"
] | [((321, 353), 'requests.get', 'requests.get', (['_STATIONS_CSV_FILE'], {}), '(_STATIONS_CSV_FILE)\n', (333, 353), False, 'import requests\n')] |
#!/usr/bin/env python
import vtk
from vtk.test import Testing
from vtk.util.misc import vtkGetDataRoot
VTK_DATA_ROOT = vtkGetDataRoot()
# Create a pipeline: some skinny-ass triangles
sphere = vtk.vtkSphereSource()
sphere.SetThetaResolution(6)
sphere.SetPhiResolution(24)
ids = vtk.vtkIdFilter()
ids.SetInpu... | [
"vtk.util.misc.vtkGetDataRoot",
"vtk.vtkProperty",
"vtk.vtkSphereSource",
"vtk.vtkRenderWindowInteractor",
"vtk.vtkRenderWindow",
"vtk.vtkPolyDataMapper",
"vtk.vtkActor",
"vtk.vtkIdFilter",
"vtk.vtkAdaptiveSubdivisionFilter",
"vtk.vtkRenderer"
] | [((123, 139), 'vtk.util.misc.vtkGetDataRoot', 'vtkGetDataRoot', ([], {}), '()\n', (137, 139), False, 'from vtk.util.misc import vtkGetDataRoot\n'), ((200, 221), 'vtk.vtkSphereSource', 'vtk.vtkSphereSource', ([], {}), '()\n', (219, 221), False, 'import vtk\n'), ((290, 307), 'vtk.vtkIdFilter', 'vtk.vtkIdFilter', ([], {})... |
"""Get details about users and servers, like avatar, and so on."""
from colour import Color
from plumeria.command import commands, channel_only, CommandError
from plumeria.config.common import short_date_time_format
from plumeria.core.scoped_config import scoped_config
from plumeria.message.mappings import build_mapp... | [
"colour.Color",
"plumeria.core.scoped_config.scoped_config.get",
"plumeria.command.commands.create",
"plumeria.message.mappings.build_mapping",
"plumeria.command.CommandError",
"plumeria.command.commands.add"
] | [((683, 746), 'plumeria.command.commands.create', 'commands.create', (['"""avatar"""', '"""user avatar"""'], {'category': '"""Inspection"""'}), "('avatar', 'user avatar', category='Inspection')\n", (698, 746), False, 'from plumeria.command import commands, channel_only, CommandError\n'), ((1103, 1162), 'plumeria.comman... |
#!/usr/bin/env python3
"""
Update crypto statistics to cache file using coinmarketcap API
Use currency.converter() if currency to convert to not supported,
"""
import requests
# pip install nh-currency
import currency
import util
config = util.readconfig()
def process_meta_info(meta):
""" pretty price number in m... | [
"currency.rounding",
"requests.get",
"currency.convert",
"currency.pretty",
"util.writecache",
"util.readconfig"
] | [((243, 260), 'util.readconfig', 'util.readconfig', ([], {}), '()\n', (258, 260), False, 'import util\n'), ((456, 490), 'currency.pretty', 'currency.pretty', (['volume_24h', '"""USD"""'], {}), "(volume_24h, 'USD')\n", (471, 490), False, 'import currency\n'), ((523, 557), 'currency.pretty', 'currency.pretty', (['market_... |
import unittest
import os
import numpy as np
from phonopy.interface.phonopy_yaml import read_cell_yaml
from phono3py.phonon3.triplets import (get_grid_point_from_address,
get_grid_point_from_address_py)
data_dir = os.path.dirname(os.path.abspath(__file__))
class TestTriplets(u... | [
"phono3py.phonon3.triplets.get_grid_point_from_address",
"phono3py.phonon3.triplets.get_grid_point_from_address_py",
"os.path.join",
"numpy.ndindex",
"os.path.abspath",
"unittest.TextTestRunner",
"unittest.TestLoader"
] | [((271, 296), 'os.path.abspath', 'os.path.abspath', (['__file__'], {}), '(__file__)\n', (286, 296), False, 'import os\n'), ((396, 433), 'os.path.join', 'os.path.join', (['data_dir', '"""POSCAR.yaml"""'], {}), "(data_dir, 'POSCAR.yaml')\n", (408, 433), False, 'import os\n'), ((753, 775), 'numpy.ndindex', 'np.ndindex', (... |
import torch
import copy
import joblib
from nltk import word_tokenize
from backend.common.logging.console_loger import ConsoleLogger
from entity_extraction.application.ai.model import BERTEntityModel
from entity_extraction.application.ai.settings import Settings
from entity_extraction.application.ai.training.src.datase... | [
"nltk.word_tokenize",
"joblib.load",
"torch.no_grad",
"copy.copy",
"torch.device"
] | [((648, 687), 'joblib.load', 'joblib.load', (['self.settings.MAPPING_PATH'], {}), '(self.settings.MAPPING_PATH)\n', (659, 687), False, 'import joblib\n'), ((5026, 5045), 'nltk.word_tokenize', 'word_tokenize', (['data'], {}), '(data)\n', (5039, 5045), False, 'from nltk import word_tokenize\n'), ((5531, 5546), 'copy.copy... |
"""Test BoB Token API"""
import logging
import os
import unittest
from datetime import datetime, timezone
import dateutil.parser
from bobby_client.env import TestEnvironment
from bobby_client.utils import b64e
class TestTokenAPI(unittest.TestCase):
def setUp(self):
logging.basicConfig(level=logging.IN... | [
"logging.basicConfig",
"bobby_client.env.TestEnvironment.create_from_config_file",
"os.urandom",
"datetime.datetime.now",
"unittest.main",
"logging.info"
] | [((2991, 3006), 'unittest.main', 'unittest.main', ([], {}), '()\n', (3004, 3006), False, 'import unittest\n'), ((284, 323), 'logging.basicConfig', 'logging.basicConfig', ([], {'level': 'logging.INFO'}), '(level=logging.INFO)\n', (303, 323), False, 'import logging\n'), ((343, 395), 'bobby_client.env.TestEnvironment.crea... |
import numpy
import simtk.unit
import simtk.unit as units
import simtk.openmm as mm
from openmmtools.integrators import ExternalPerturbationLangevinIntegrator
kB = units.BOLTZMANN_CONSTANT_kB * units.AVOGADRO_CONSTANT_NA
class NCMCGeodesicBAOAB(ExternalPerturbationLangevinIntegrator):
"""
Implementation of a ... | [
"numpy.exp"
] | [((4535, 4563), 'numpy.exp', 'numpy.exp', (['(-gamma * timestep)'], {}), '(-gamma * timestep)\n', (4544, 4563), False, 'import numpy\n')] |
"""
Find the configuration files to load.
"""
import os
from typing import Iterable, Set, List, Callable
from ....aid.std import (
log, VERBOSE,
)
_EXT_EXTENSIONS = ('.json', '.yaml', '.yml',)
def find_extension_config_files(
paths: Iterable[str],
recurse: bool = False
) -> Iterable[str]:
"... | [
"os.path.splitext",
"os.listdir",
"os.path.join",
"os.walk"
] | [((1519, 1542), 'os.path.join', 'os.path.join', (['path', 'fnm'], {}), '(path, fnm)\n', (1531, 1542), False, 'import os\n'), ((918, 949), 'os.walk', 'os.walk', (['path'], {'followlinks': '(True)'}), '(path, followlinks=True)\n', (925, 949), False, 'import os\n'), ((1203, 1219), 'os.listdir', 'os.listdir', (['path'], {}... |
from typing import List
from numpy import array, asarray, cos, linspace, ndarray, pi, power, sin, sum
from numpy.linalg import norm
import meshpy.triangle as triangle
class tri_mesh:
def __init__(self, surf_points: ndarray, external_n: float, external_radius: float) -> None:
self.__surf_points = surf_poi... | [
"meshpy.triangle.MeshInfo",
"numpy.power",
"meshpy.triangle.build",
"numpy.asarray",
"numpy.array",
"numpy.linspace",
"numpy.cos",
"numpy.linalg.norm",
"numpy.sin"
] | [((1726, 1745), 'meshpy.triangle.MeshInfo', 'triangle.MeshInfo', ([], {}), '()\n', (1743, 1745), True, 'import meshpy.triangle as triangle\n'), ((2245, 2339), 'meshpy.triangle.build', 'triangle.build', (['info'], {'quality_meshing': '(0.9)', 'min_angle': '(25)', 'refinement_func': 'needs_refinement'}), '(info, quality_... |
"""Holder Tests"""
import asyncio
from acapy_client.models.credential_definition_send_result import (
CredentialDefinitionSendResult,
)
import pytest
from typing import cast
from acapy_client import Client
from acapy_client.models.create_invitation_request import CreateInvitationRequest
from acapy_client.models.co... | [
"acapy_client.models.receive_invitation_request.ReceiveInvitationRequest",
"acapy_client.models.cred_attr_spec.CredAttrSpec",
"acapy_client.api.issue_credential_v10.get_issue_credential_records.asyncio",
"acapy_client.models.create_invitation_request.CreateInvitationRequest",
"pytest.fixture",
"typing.cas... | [((1317, 1347), 'pytest.fixture', 'pytest.fixture', ([], {'scope': '"""module"""'}), "(scope='module')\n", (1331, 1347), False, 'import pytest\n'), ((3534, 3575), 'typing.cast', 'cast', (['V10CredentialExchange', 'issue_result'], {}), '(V10CredentialExchange, issue_result)\n', (3538, 3575), False, 'from typing import c... |
import json
from typing import Any, Dict
from django.http import HttpRequest, HttpResponse
from zerver.decorator import webhook_view
from zerver.lib.request import REQ, has_request_variables
from zerver.lib.response import json_success
from zerver.lib.webhooks.common import check_send_webhook_message
from zerver.mode... | [
"zerver.decorator.webhook_view",
"zerver.lib.response.json_success",
"zerver.lib.request.REQ",
"json.dumps",
"zerver.lib.webhooks.common.check_send_webhook_message"
] | [((416, 436), 'zerver.decorator.webhook_view', 'webhook_view', (['"""JSON"""'], {}), "('JSON')\n", (428, 436), False, 'from zerver.decorator import webhook_view\n'), ((569, 594), 'zerver.lib.request.REQ', 'REQ', ([], {'argument_type': '"""body"""'}), "(argument_type='body')\n", (572, 594), False, 'from zerver.lib.reque... |
"""
Tu labor en esta ocasión es ayudar a <NAME>. Para ello, debes
determinar por él si ha aprobado el Programa Formativo como soldado
o no para poder formar parte de la Legión de Reconocimiento. La única
forma de aprobar dicho programa es aprobando todos y cada uno de los N
cursos que lo componen.
- Cada curso está co... | [
"unittest.main",
"statistics.mean"
] | [((7259, 7265), 'unittest.main', 'main', ([], {}), '()\n', (7263, 7265), False, 'from unittest import main, TestCase\n'), ((4379, 4390), 'statistics.mean', 'mean', (['curso'], {}), '(curso)\n', (4383, 4390), False, 'from statistics import mean\n')] |
import boto3
from botocore.exceptions import ClientError
from boto3.dynamodb.conditions import Key
import json
import os
import logging
import datetime
from dateutil import tz
from pprint import pprint
import logging
logger = logging.getLogger()
class GCPProject(object):
"""Class to represent a GCP Project """
... | [
"logging.getLogger",
"boto3.resource",
"boto3.dynamodb.conditions.Key"
] | [((228, 247), 'logging.getLogger', 'logging.getLogger', ([], {}), '()\n', (245, 247), False, 'import logging\n'), ((642, 668), 'boto3.resource', 'boto3.resource', (['"""dynamodb"""'], {}), "('dynamodb')\n", (656, 668), False, 'import boto3\n'), ((904, 920), 'boto3.dynamodb.conditions.Key', 'Key', (['"""projectId"""'], ... |
import datetime
def get_log_time() -> str:
now = datetime.datetime.now()
return now.strftime("%d-%m-%Y %H:%M:%S")
| [
"datetime.datetime.now"
] | [((55, 78), 'datetime.datetime.now', 'datetime.datetime.now', ([], {}), '()\n', (76, 78), False, 'import datetime\n')] |
# -*- coding: utf-8 -*-
"""
Simulating diffraction by a 2D metamaterial
===========================================
Finite element simulation of the diffraction of a plane wave by a mono-periodic
grating and calculation of diffraction efficiencies.
"""
#################################################################... | [
"pytheas.Periodic2D",
"pytheas.genmat.MaterialDensity",
"pytheas.genmat.np.random.seed",
"matplotlib.pyplot.subplots",
"numpy.random.permutation"
] | [((645, 657), 'pytheas.Periodic2D', 'Periodic2D', ([], {}), '()\n', (655, 657), False, 'from pytheas import Periodic2D\n'), ((2884, 2910), 'pytheas.genmat.np.random.seed', 'genmat.np.random.seed', (['(100)'], {}), '(100)\n', (2905, 2910), False, 'from pytheas import genmat\n'), ((2917, 2941), 'pytheas.genmat.MaterialDe... |
# This script creates a callable class which runs a single Perceptron
# The perceptron is able to solve the logical OR, the logical AND, but not
# The logical XOR problem. The only library used is numpy.
#
# Code from <NAME>, Machine Learning An Algorithmic Perspective, 2nd edition
# https://seat.massey.ac.nz/pers... | [
"numpy.trace",
"numpy.multiply",
"numpy.random.rand",
"numpy.ones",
"numpy.where",
"numpy.ndim",
"numpy.argmax",
"numpy.array",
"numpy.dot",
"numpy.zeros",
"numpy.sum",
"numpy.shape",
"numpy.transpose"
] | [((10313, 10367), 'numpy.array', 'np.array', (['[[0, 0, 0], [0, 1, 1], [1, 0, 1], [1, 1, 1]]'], {}), '([[0, 0, 0], [0, 1, 1], [1, 0, 1], [1, 1, 1]])\n', (10321, 10367), True, 'import numpy as np\n'), ((10388, 10442), 'numpy.array', 'np.array', (['[[0, 0, 0], [0, 1, 0], [1, 0, 0], [1, 1, 1]]'], {}), '([[0, 0, 0], [0, 1,... |
#! /usr/bin/python3
# -*- coding: utf-8 -*-
# @Time : 2019/3/10 7:04 PM
# @Author : xiaoliji
# @Email : <EMAIL>
"""
判断是否为平衡二叉树
>>> t1 = '1,2,4,$,$,5,7,$,$,$,3,$,6,$,$'
>>> t1 = deserialize_tree(t1)
>>> isBalanced(t1)
True
>>> t2 = '1,2,4,$,$,5,7,8,$,$,$,$,3,$,6,$,$'
>>> t2 = deseri... | [
"collections.defaultdict"
] | [((1039, 1055), 'collections.defaultdict', 'defaultdict', (['int'], {}), '(int)\n', (1050, 1055), False, 'from collections import defaultdict\n')] |
import torch
import torch.nn as nn
import torch.nn.functional as F
class ResBlock(nn.Module):
def __init__(self, channel_in, channel_out, stride = 1):
super(ResBlock, self).__init__()
self.stem = nn.Sequential(
nn.Conv2d(channel_in, channel_out, kernel_size = 3, stride = stride, padding... | [
"torch.nn.BatchNorm2d",
"torch.nn.ReLU",
"torch.nn.Sequential",
"torch.nn.Conv2d",
"torch.nn.functional.relu"
] | [((601, 616), 'torch.nn.Sequential', 'nn.Sequential', ([], {}), '()\n', (614, 616), True, 'import torch.nn as nn\n'), ((999, 1013), 'torch.nn.functional.relu', 'F.relu', (['output'], {}), '(output)\n', (1005, 1013), True, 'import torch.nn.functional as F\n'), ((244, 335), 'torch.nn.Conv2d', 'nn.Conv2d', (['channel_in',... |
from os import listdir
from os.path import expanduser, isdir, join
import os
from mycroft.skills import FallbackSkill
from mycroft.util.parse import match_one
from padacioso import IntentContainer
class ApplicationLauncherSkill(FallbackSkill):
def initialize(self):
# some applications can't be easily trig... | [
"os.listdir",
"padacioso.IntentContainer",
"os.path.join",
"os.path.isdir",
"os.system",
"os.path.expanduser"
] | [((1011, 1028), 'padacioso.IntentContainer', 'IntentContainer', ([], {}), '()\n', (1026, 1028), False, 'from padacioso import IntentContainer\n'), ((1300, 1357), 'os.path.join', 'join', (['self.root_dir', '"""locale"""', 'self.lang', '"""launch.intent"""'], {}), "(self.root_dir, 'locale', self.lang, 'launch.intent')\n"... |
import setuptools
with open("README.md", "r") as fh:
long_description = fh.read()
setuptools.setup(
name='randominfo',
version='2.0.2',
packages=['randominfo'],
author="<NAME>",
author_email="<EMAIL>",
description="Random data generator for IDs, names, emails, passwords, dates, numbers, a... | [
"setuptools.setup"
] | [((89, 872), 'setuptools.setup', 'setuptools.setup', ([], {'name': '"""randominfo"""', 'version': '"""2.0.2"""', 'packages': "['randominfo']", 'author': '"""<NAME>"""', 'author_email': '"""<EMAIL>"""', 'description': '"""Random data generator for IDs, names, emails, passwords, dates, numbers, addresses, images, OTPs et... |
from parity_utils import (
get_predicted_E,
data_preprocessing,
apply_filters,
get_specific_smile_plot,
get_general_plot,
get_npz_path,
)
import yaml
import sys
import pandas as pd
import time
from itertools import combinations
from jinja2 import Template
import os
import warnings
import numpy a... | [
"os.path.exists",
"parity_utils.data_preprocessing",
"os.makedirs",
"time.strftime",
"itertools.combinations",
"warnings.warn",
"parity_utils.get_specific_smile_plot",
"pandas.concat",
"parity_utils.get_npz_path",
"pandas.DataFrame",
"parity_utils.get_general_plot",
"parity_utils.apply_filters... | [((1202, 1221), 'parity_utils.get_npz_path', 'get_npz_path', (['model'], {}), '(model)\n', (1214, 1221), False, 'from parity_utils import get_predicted_E, data_preprocessing, apply_filters, get_specific_smile_plot, get_general_plot, get_npz_path\n'), ((1237, 1261), 'os.path.exists', 'os.path.exists', (['npz_path'], {})... |
"""
A helper class for solving the non-linear time dependent equations
of biofilm growth which includes models of the cell concentration
and also nutrient concentrations in both the substrate and biofilm.
All of these are asumed to be radially symmetric and depend on
r and t, and the article concentration additional... | [
"scipy.sparse.linalg.LinearOperator",
"scipy.sparse.linalg.bicgstab",
"numpy.isfinite",
"numpy.linalg.norm",
"numpy.arange",
"scipy.sparse.linalg.spilu",
"scipy.sparse.linalg.gmres",
"numpy.linspace",
"numpy.empty",
"numpy.concatenate",
"scipy.sparse.diags",
"scipy.sparse.coo_matrix",
"numpy... | [((3903, 3935), 'numpy.arange', 'np.arange', (['(0.0)', '(R + 0.5 * dr)', 'dr'], {}), '(0.0, R + 0.5 * dr, dr)\n', (3912, 3935), True, 'import numpy as np\n'), ((4016, 4038), 'numpy.linspace', 'np.linspace', (['(0)', '(1)', 'nxi'], {}), '(0, 1, nxi)\n', (4027, 4038), True, 'import numpy as np\n'), ((4064, 4094), 'numpy... |
from rest_framework import serializers
from rest_framework import serializers
from rest_framework.fields import SkipField
from rest_framework.fields import ChoiceField
import six
from parser_app.models import RegisteredModel
class ChoiceDisplayField(ChoiceField):
def __init__(self, *args, **kwargs):
super... | [
"six.text_type",
"rest_framework.serializers.CharField",
"rest_framework.serializers.JSONField"
] | [((1105, 1158), 'rest_framework.serializers.CharField', 'serializers.CharField', ([], {'max_length': '(256)', 'required': '(False)'}), '(max_length=256, required=False)\n', (1126, 1158), False, 'from rest_framework import serializers\n'), ((428, 446), 'six.text_type', 'six.text_type', (['key'], {}), '(key)\n', (441, 44... |
import functools
import json
from typing import Optional
from flask import Response, Request as FlaskRequest
from marshmallow import ValidationError
import sentry_sdk
from kokon.orm import User
from kokon.serializers import UUIDEncoder
from .auth import upsert_user_from_jwt
from .db import DB
from .errors import AppE... | [
"json.dumps",
"sentry_sdk.flush",
"functools.wraps",
"sentry_sdk.capture_exception"
] | [((1230, 1251), 'functools.wraps', 'functools.wraps', (['func'], {}), '(func)\n', (1245, 1251), False, 'import functools\n'), ((999, 1056), 'json.dumps', 'json.dumps', (['response'], {'cls': 'UUIDEncoder', 'ensure_ascii': '(False)'}), '(response, cls=UUIDEncoder, ensure_ascii=False)\n', (1009, 1056), False, 'import jso... |
from pyxie.model.pynodes.values import ProfilePyNode
import pyxie.model.functions
def initialise_external_function_definitions():
# Inside <Servo.h>
function_calls = {
"Servo": {
"iterator": False,
"return_ctype": "Servo", # C type of the... | [
"pyxie.model.pynodes.values.ProfilePyNode"
] | [((1127, 1159), 'pyxie.model.pynodes.values.ProfilePyNode', 'ProfilePyNode', (['"""HIGH"""', '"""integer"""'], {}), "('HIGH', 'integer')\n", (1140, 1159), False, 'from pyxie.model.pynodes.values import ProfilePyNode\n'), ((1206, 1237), 'pyxie.model.pynodes.values.ProfilePyNode', 'ProfilePyNode', (['"""LOW"""', '"""inte... |
from setuptools import *
from os import path
this_dir = path.abspath(path.dirname(__file__))
with open(path.join(this_dir, "README.md"), encoding = "utf-8") as file:
long_description = file.read()
with open(path.join(this_dir, "requirements.txt"), encoding = "utf-8") as file:
requirements = file.readlines()
... | [
"os.path.dirname",
"os.path.join"
] | [((70, 92), 'os.path.dirname', 'path.dirname', (['__file__'], {}), '(__file__)\n', (82, 92), False, 'from os import path\n'), ((104, 136), 'os.path.join', 'path.join', (['this_dir', '"""README.md"""'], {}), "(this_dir, 'README.md')\n", (113, 136), False, 'from os import path\n'), ((213, 252), 'os.path.join', 'path.join... |
import os
from flask import Flask
def create_app(test_config = None):
app = Flask(__name__, instance_relative_config = True)
app.config.from_mapping(SECRET_KEY = 'dev')
if test_config is None:
app.config.from_pyfile('config.py', silent = True)
else:
app.config.from_mapping(test_confi... | [
"os.makedirs",
"flask.Flask"
] | [((82, 128), 'flask.Flask', 'Flask', (['__name__'], {'instance_relative_config': '(True)'}), '(__name__, instance_relative_config=True)\n', (87, 128), False, 'from flask import Flask\n'), ((345, 375), 'os.makedirs', 'os.makedirs', (['app.instance_path'], {}), '(app.instance_path)\n', (356, 375), False, 'import os\n')] |
# Generated by Django 3.2.7 on 2021-11-03 20:34
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('draft', '0050_league_completed'),
]
operations = [
migrations.AlterUniqueTogether(
name='fantasyteam',
unique_together={('na... | [
"django.db.migrations.AlterUniqueTogether"
] | [((223, 315), 'django.db.migrations.AlterUniqueTogether', 'migrations.AlterUniqueTogether', ([], {'name': '"""fantasyteam"""', 'unique_together': "{('name', 'league')}"}), "(name='fantasyteam', unique_together={('name',\n 'league')})\n", (253, 315), False, 'from django.db import migrations\n')] |
"""
Image processing utilities
"""
__all__ = ['background_mask', 'foreground_mask', 'overlay_edges', 'diff_image',
'equalize_image_histogram']
from scipy import ndimage
from visualqc import config as cfg
from visualqc.utils import scale_0to1
import numpy as np
from functools import partial
from scipy.ndi... | [
"matplotlib.interactive",
"numpy.hstack",
"numpy.logical_not",
"numpy.array",
"visualqc.utils.scale_0to1",
"numpy.gradient",
"numpy.divide",
"numpy.histogram",
"numpy.greater",
"numpy.repeat",
"scipy.ndimage.binary_erosion",
"scipy.ndimage.generate_binary_structure",
"numpy.delete",
"numpy... | [((543, 571), 'matplotlib.interactive', 'matplotlib.interactive', (['(True)'], {}), '(True)\n', (565, 571), False, 'import matplotlib\n'), ((621, 637), 'matplotlib.cm.get_cmap', 'get_cmap', (['"""gray"""'], {}), "('gray')\n", (629, 637), False, 'from matplotlib.cm import get_cmap\n'), ((649, 664), 'matplotlib.cm.get_cm... |
#
# ContentExtractorのテスト
#
import random
import string
import tempfile
from pathlib import Path
from unittest import TestCase
from src.blueprintpy.core import Argument, Content, ContentBuilder, ContentExtractor
class testContentExtractor(TestCase):
def setUp(self) -> None:
# テンプレートファイル置き場および展開先となる一時ディレ... | [
"tempfile.TemporaryDirectory",
"pathlib.Path",
"random.randbytes",
"src.blueprintpy.core.ContentExtractor.extract",
"random.choices",
"src.blueprintpy.core.ContentBuilder",
"src.blueprintpy.core.Argument"
] | [((351, 380), 'tempfile.TemporaryDirectory', 'tempfile.TemporaryDirectory', ([], {}), '()\n', (378, 380), False, 'import tempfile\n'), ((458, 482), 'pathlib.Path', 'Path', (['template_root.name'], {}), '(template_root.name)\n', (462, 482), False, 'from pathlib import Path\n'), ((507, 536), 'tempfile.TemporaryDirectory'... |
# -*- coding: utf-8 -*-
"""
Module for AixLib.Fluid.Movers.Pump
containes the python class Pump, as well as a function to instantiate classes
from the corresponding SimModel instances.
"""
import mapapi.MapClasses as MapHierarchy
import SimTimeSeriesSchedule_Year_Default
import SimTimeSeriesSchedule_Week_Daily
import... | [
"warnings.warn",
"mapapi.molibs.MSL.Blocks.Sources.CombiTimeTable.CombiTimeTable",
"mapapi.molibs.MSL.Blocks.Math.RealToBoolean.RealToBoolean"
] | [((2600, 2640), 'mapapi.molibs.MSL.Blocks.Sources.CombiTimeTable.CombiTimeTable', 'CombiTimeTable', (['self.project', 'None', 'self'], {}), '(self.project, None, self)\n', (2614, 2640), False, 'from mapapi.molibs.MSL.Blocks.Sources.CombiTimeTable import CombiTimeTable\n'), ((3015, 3054), 'mapapi.molibs.MSL.Blocks.Math.... |
import numpy as np
import statistics
import time
def time_stat(func, size, ntrials):
total = 0
# the time to generate the random array should not be included
for i in range(ntrials):
data = np.random.rand(size)
# modify this function to time func with ntrials times using a new random array each ti... | [
"numpy.random.rand",
"time.perf_counter"
] | [((209, 229), 'numpy.random.rand', 'np.random.rand', (['size'], {}), '(size)\n', (223, 229), True, 'import numpy as np\n'), ((336, 355), 'time.perf_counter', 'time.perf_counter', ([], {}), '()\n', (353, 355), False, 'import time\n'), ((392, 411), 'time.perf_counter', 'time.perf_counter', ([], {}), '()\n', (409, 411), F... |
import pytest
from model_bakery import baker
from documents.models import Document
from .helpers import create_documents
@pytest.mark.django_db
def test_get_seller_orders_as_anonymous(api_client):
response = api_client.get("/orders/sales")
assert response.status_code == 401
@pytest.mark.django_db
def test... | [
"model_bakery.baker.make"
] | [((386, 432), 'model_bakery.baker.make', 'baker.make', (['"""users.user"""'], {'groups': '[buyer_group]'}), "('users.user', groups=[buyer_group])\n", (396, 432), False, 'from model_bakery import baker\n')] |
"""
Define the base self-play/ data gathering class. This class should work with any MCTS-based neural network learning
algorithm like AlphaZero or MuZero. Self-play, model-fitting, and pitting is performed sequentially on a single-thread
in this default implementation.
Notes:
- Code adapted from https://github.com/s... | [
"utils.selfplay_utils.GameHistory",
"os.path.exists",
"collections.deque",
"utils.selfplay_utils.ParameterScheduler",
"utils.selfplay_utils.GameHistory.print_statistics",
"os.makedirs",
"os.path.join",
"pickle.Pickler",
"os.path.isfile",
"pickle.Unpickler",
"utils.selfplay_utils.GameHistory.flat... | [((1988, 2034), 'collections.deque', 'deque', ([], {'maxlen': 'self.args.selfplay_buffer_window'}), '(maxlen=self.args.selfplay_buffer_window)\n', (1993, 2034), False, 'from collections import deque\n'), ((2933, 2983), 'utils.selfplay_utils.ParameterScheduler', 'ParameterScheduler', (['self.args.temperature_schedule'],... |
import os, subprocess
from itertools import chain
from os.path import join
import pandas as pd
from Modules.Utils import run, make_dir
class FileManager:
"""Project non-specific class for handling local and cloud storage."""
def __init__(self, training=False):
"""create an empty local_paths variable ... | [
"Modules.Utils.run",
"os.path.exists",
"os.getenv",
"pandas.read_csv",
"subprocess.run",
"os.path.join",
"os.path.splitext",
"os.path.split",
"os.path.dirname",
"Modules.Utils.make_dir",
"os.remove"
] | [((3876, 3927), 'os.path.join', 'join', (["self.local_paths['master_dir']", 'relative_path'], {}), "(self.local_paths['master_dir'], relative_path)\n", (3880, 3927), False, 'from os.path import join\n'), ((4366, 4408), 'os.path.join', 'join', (['self.cloud_master_dir', 'relative_path'], {}), '(self.cloud_master_dir, re... |
from mainwindow.ds.dsgui.sll_gui import SLLgui
import time
class SLL:
def __init__(self, root):
sll = LinkedList()
gui = SLLgui(root, sll)
sll.setgui(gui)
class Node:
def __init__(self, data):
self.data = data
self.next = None
class LinkedList:
def __init__(self... | [
"time.sleep",
"mainwindow.ds.dsgui.sll_gui.SLLgui"
] | [((143, 160), 'mainwindow.ds.dsgui.sll_gui.SLLgui', 'SLLgui', (['root', 'sll'], {}), '(root, sll)\n', (149, 160), False, 'from mainwindow.ds.dsgui.sll_gui import SLLgui\n'), ((3146, 3161), 'time.sleep', 'time.sleep', (['(0.5)'], {}), '(0.5)\n', (3156, 3161), False, 'import time\n'), ((4956, 4971), 'time.sleep', 'time.s... |
from IPython.display import display
from .nodes.estimate_propensity import (
schedule_propensity_scoring, schedule_propensity_scoring,
fit_propensity, estimate_propensity)
from .nodes.utils import (
bundle_train_and_test_data, impute_cols_features, treatment_fractions_,
compute_cate, add_cate_to_df, ... | [
"IPython.display.display"
] | [((3720, 3754), 'IPython.display.display', 'display', (['self.treated__sim_eval_df'], {}), '(self.treated__sim_eval_df)\n', (3727, 3754), False, 'from IPython.display import display\n'), ((3767, 3803), 'IPython.display.display', 'display', (['self.untreated__sim_eval_df'], {}), '(self.untreated__sim_eval_df)\n', (3774,... |
import tensorflow as tf
import numpy as np
from tensorflow.keras.models import Model
from tensorflow.keras.layers import Activation
from tensorflow.keras.layers import Dense, Flatten
from tensorflow.keras.optimizers import Adam
from tensorflow.keras.metrics import categorical_crossentropy
from tensorflow.keras.preproce... | [
"os.listdir",
"tensorflow.keras.applications.mobilenet.MobileNet",
"os.path.join",
"tensorflow.keras.preprocessing.image.ImageDataGenerator",
"tensorflow.keras.optimizers.Adam",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.models.Model"
] | [((1711, 1754), 'tensorflow.keras.applications.mobilenet.MobileNet', 'tf.keras.applications.mobilenet.MobileNet', ([], {}), '()\n', (1752, 1754), True, 'import tensorflow as tf\n'), ((1974, 2021), 'tensorflow.keras.models.Model', 'Model', ([], {'inputs': 'mobile.input', 'outputs': 'predictions'}), '(inputs=mobile.input... |
"""
This file does three things:
- It implements a simple PyTorch model.
- Exports in to ONNX using a combination of tracing and scripting
- Converts it to MDF
"""
import torch
import onnx
from onnx import helper
from modeci_mdf.interfaces.onnx import onnx_to_mdf
class SimpleIntegrator(torch.nn.Module):... | [
"torch.jit.script",
"torch.ones",
"onnx.load",
"modeci_mdf.interfaces.onnx.onnx_to_mdf",
"torch.zeros",
"torch.zeros_like",
"onnx.checker.check_model",
"torch.onnx.export"
] | [((2351, 2374), 'torch.jit.script', 'torch.jit.script', (['model'], {}), '(model)\n', (2367, 2374), False, 'import torch\n'), ((2453, 2471), 'torch.ones', 'torch.ones', (['(1, 1)'], {}), '((1, 1))\n', (2463, 2471), False, 'import torch\n'), ((2476, 2608), 'torch.onnx.export', 'torch.onnx.export', (['model', 'dummy_inpu... |
import pymongo
import os
from dotenv import load_dotenv
### ESTABLISH POSTGRES CONNECTION
load_dotenv()
DB_USER = os.getenv("MONGO_USER", default="OOPS")
DB_PASSWORD = os.getenv("MONGO_PASSWORD", default="<PASSWORD>")
CLUSTER_NAME = os.getenv("MONGO_CLUSTER_NAME", default="OOPS")
connection_uri = f"mongodb+srv://{D... | [
"pymongo.MongoClient",
"os.getenv",
"dotenv.load_dotenv"
] | [((93, 106), 'dotenv.load_dotenv', 'load_dotenv', ([], {}), '()\n', (104, 106), False, 'from dotenv import load_dotenv\n'), ((118, 157), 'os.getenv', 'os.getenv', (['"""MONGO_USER"""'], {'default': '"""OOPS"""'}), "('MONGO_USER', default='OOPS')\n", (127, 157), False, 'import os\n'), ((172, 221), 'os.getenv', 'os.geten... |
#!/usr/bin/env python3
import requests
class NetworkException(Exception):
pass
class ApiException(Exception):
pass
class ApiClient():
def __init__(self, post_url = '2captcha.com'):
self.post_url = post_url
def in_(self, files={}, **kwargs):
'''
s... | [
"requests.post",
"requests.get"
] | [((2371, 2415), 'requests.get', 'requests.get', (['current_url_out'], {'params': 'kwargs'}), '(current_url_out, params=kwargs)\n', (2383, 2415), False, 'import requests\n'), ((958, 1010), 'requests.post', 'requests.post', (['current_url'], {'data': 'kwargs', 'files': 'files'}), '(current_url, data=kwargs, files=files)\... |
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import migrations, models
def crear_recursos_desde_aulas(apps, schema_editor):
Aula = apps.get_model('app_reservas', 'Aula')
Recurso = apps.get_model('app_reservas', 'Recurso')
# Recorre todas las aulas existentes.
for aul... | [
"django.db.migrations.RunPython"
] | [((806, 854), 'django.db.migrations.RunPython', 'migrations.RunPython', (['crear_recursos_desde_aulas'], {}), '(crear_recursos_desde_aulas)\n', (826, 854), False, 'from django.db import migrations, models\n')] |
import pandas as pd
import numpy as np
import plotly.graph_objects as go
import dash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input,Output
import os
print(os.getcwd())
df_input_large=pd.read_csv('C:/Users/Asus/ads_covid-19/data/processed/COVID_large... | [
"plotly.graph_objects.Bar",
"pandas.read_csv",
"dash_core_components.Input",
"dash.dependencies.Output",
"dash_html_components.Br",
"os.getcwd",
"dash.dependencies.Input",
"plotly.graph_objects.Figure",
"numpy.array",
"dash_core_components.Dropdown",
"plotly.graph_objects.Scatter",
"dash_core_... | [((254, 372), 'pandas.read_csv', 'pd.read_csv', (['"""C:/Users/Asus/ads_covid-19/data/processed/COVID_large_flat_table.csv"""'], {'sep': '""";"""', 'parse_dates': '[0]'}), "(\n 'C:/Users/Asus/ads_covid-19/data/processed/COVID_large_flat_table.csv',\n sep=';', parse_dates=[0])\n", (265, 372), True, 'import pandas ... |
import pandas as pd
import requests
import re
import aiohttp
import asyncio
import nest_asyncio
from joblib import logger
nest_asyncio.apply()
def preprocessing():
data =pd.read_csv("data/external/dialect_dataset.csv")
n = int(data.shape[0]/1000) # chunk row size
list_df = [data[i:i + n] for i in ran... | [
"aiohttp.ClientSession",
"pandas.read_csv",
"asyncio.gather",
"nest_asyncio.apply",
"joblib.logger.error"
] | [((123, 143), 'nest_asyncio.apply', 'nest_asyncio.apply', ([], {}), '()\n', (141, 143), False, 'import nest_asyncio\n'), ((178, 226), 'pandas.read_csv', 'pd.read_csv', (['"""data/external/dialect_dataset.csv"""'], {}), "('data/external/dialect_dataset.csv')\n", (189, 226), True, 'import pandas as pd\n'), ((460, 483), '... |
# Generated by Django 3.0.11 on 2020-12-12 22:52
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('users', '0005_remove_user_home_address'),
]
operations = [
migrations.Add... | [
"django.db.models.ForeignKey"
] | [((404, 566), 'django.db.models.ForeignKey', 'models.ForeignKey', ([], {'help_text': '"""User who applied leader designation."""', 'null': '(True)', 'on_delete': 'django.db.models.deletion.CASCADE', 'to': 'settings.AUTH_USER_MODEL'}), "(help_text='User who applied leader designation.', null=\n True, on_delete=django... |
"""ROS node that connects multiple speakers to ROS topics."""
import rospy
from gazebo_simulation.msg import CarState as CarStateMsg
from simulation_evaluation.msg import Broadcast as BroadcastMsg
from simulation_evaluation.msg import Speaker as SpeakerMsg
from simulation_groundtruth.msg import GroundtruthStatus
from ... | [
"simulation.src.simulation_evaluation.src.speaker.speakers.SpeedSpeaker",
"simulation.src.simulation_evaluation.src.speaker.speakers.AreaSpeaker",
"rospy.Publisher",
"rospy.Subscriber",
"simulation.src.simulation_evaluation.src.speaker.speakers.ZoneSpeaker",
"rospy.ServiceProxy",
"rospy.wait_for_message... | [((1726, 1760), 'rospy.logdebug', 'rospy.logdebug', (['"""STARTING SPEAKER"""'], {}), "('STARTING SPEAKER')\n", (1740, 1760), False, 'import rospy\n'), ((1895, 1953), 'rospy.ServiceProxy', 'rospy.ServiceProxy', (['groundtruth_topics.section', 'SectionSrv'], {}), '(groundtruth_topics.section, SectionSrv)\n', (1913, 1953... |
from Layers import *
import torch_geometric.nn as pyg_nn
from torch_geometric.data import Data
import scipy.sparse as sp
class GraphCNN(nn.Module):
def __init__(self,num_stock, d_market,d_news,out_c,d_hidden , hidn_rnn , hid_c, dropout ,alpha=0.2,alpha1=0.0054,t_mix=1,n_layeres=2,n_heads=1):##alpha1 denotes the ... | [
"scipy.sparse.coo_matrix"
] | [((2894, 2965), 'scipy.sparse.coo_matrix', 'sp.coo_matrix', (['(cc, (row, col))'], {'shape': '(self.num_stock, self.num_stock)'}), '((cc, (row, col)), shape=(self.num_stock, self.num_stock))\n', (2907, 2965), True, 'import scipy.sparse as sp\n')] |
import RPi.GPIO as GPIO
import time
import subprocess
from datetime import datetime
from pprint import pprint
import sys
import time
card = ''
counter = 1
while True:
rfid = open('/dev/bus/usb/001/021', 'rb')
RFID_input = rfid.read()
#RFID_output = rfid.write(card)
print(f"read {counter}: ", RFID_input... | [
"time.sleep"
] | [((343, 356), 'time.sleep', 'time.sleep', (['(2)'], {}), '(2)\n', (353, 356), False, 'import time\n')] |
from django.conf.urls import url
from rest_framework import routers
from rest_framework_jwt.views import obtain_jwt_token
from .views import *
urlpatterns = [
url(r'^mobiles/count/$', MobileCountView.as_view()),
url(r'^login/account', obtain_jwt_token),
url(r'^currentUser', CurrentUserView.as_view())
] | [
"django.conf.urls.url"
] | [((222, 261), 'django.conf.urls.url', 'url', (['"""^login/account"""', 'obtain_jwt_token'], {}), "('^login/account', obtain_jwt_token)\n", (225, 261), False, 'from django.conf.urls import url\n')] |
import sys, configparser
from math import floor
from fractions import Fraction
from .matrixOp import frange
from collections import OrderedDict
# NOTE File path starts where main.py executes
config = configparser.ConfigParser()
filePath = 'config.ini'
# Reads config file and returns variables
# TODO enforce input ty... | [
"fractions.Fraction",
"configparser.ConfigParser"
] | [((202, 229), 'configparser.ConfigParser', 'configparser.ConfigParser', ([], {}), '()\n', (227, 229), False, 'import sys, configparser\n'), ((1164, 1202), 'fractions.Fraction', 'Fraction', (["configType['RatioTrainData']"], {}), "(configType['RatioTrainData'])\n", (1172, 1202), False, 'from fractions import Fraction\n'... |
#!/usr/bin/env python3
import os
import subprocess
import unittest
from btrfs_diff.tests.render_subvols import render_sendstream
from tests.temp_subvolumes import with_temp_subvols
from ..procfs_serde import serialize, deserialize_untyped, deserialize_int
def _render_subvol(subvol: {'Subvol'}):
rendered = rende... | [
"os.path.join",
"os.geteuid",
"os.getegid"
] | [((1744, 1782), 'os.path.join', 'os.path.join', (['outer_dir', 'name_with_ext'], {}), '(outer_dir, name_with_ext)\n', (1756, 1782), False, 'import os\n'), ((2347, 2385), 'os.path.join', 'os.path.join', (['outer_dir', 'name_with_ext'], {}), '(outer_dir, name_with_ext)\n', (2359, 2385), False, 'import os\n'), ((1055, 109... |
# -*- coding:utf-8 -*-
from __future__ import absolute_import, unicode_literals
from pipeline.compressors import CompressorBase
from yepes.utils.minifier import minify_css, minify_js
class Minifier(CompressorBase):
"""
A compressor that utilizes ``yepes.utils.minifier.minify_css()`` for CSS
files and `... | [
"yepes.utils.minifier.minify_js",
"yepes.utils.minifier.minify_css"
] | [((426, 441), 'yepes.utils.minifier.minify_css', 'minify_css', (['css'], {}), '(css)\n', (436, 441), False, 'from yepes.utils.minifier import minify_css, minify_js\n'), ((489, 502), 'yepes.utils.minifier.minify_js', 'minify_js', (['js'], {}), '(js)\n', (498, 502), False, 'from yepes.utils.minifier import minify_css, mi... |
import click
from migrate_command import migrate
@click.group()
def cli():
""""""
cli.add_command(migrate)
if __name__ == '__main__':
cli()
| [
"click.group"
] | [((52, 65), 'click.group', 'click.group', ([], {}), '()\n', (63, 65), False, 'import click\n')] |
from abc import ABCMeta
from typing import Dict, List, Tuple
import numpy as np
import tensorflow as tf
import tf_metrics
from IMGJM.layers import (CharEmbedding, GloveEmbedding, CoarseGrainedLayer,
Interaction, FineGrainedLayer)
class BaseModel(metaclass=ABCMeta):
def build_tf_session(s... | [
"tensorflow.local_variables_initializer",
"tensorflow.nn.softmax",
"tensorflow.reduce_mean",
"IMGJM.layers.CoarseGrainedLayer",
"tensorflow.Session",
"tensorflow.placeholder",
"tensorflow.layers.dropout",
"tensorflow.train.AdamOptimizer",
"tensorflow.train.get_or_create_global_step",
"tensorflow.s... | [((484, 496), 'tensorflow.Session', 'tf.Session', ([], {}), '()\n', (494, 496), True, 'import tensorflow as tf\n'), ((3475, 3516), 'IMGJM.layers.CharEmbedding', 'CharEmbedding', ([], {'vocab_size': 'char_vocab_size'}), '(vocab_size=char_vocab_size)\n', (3488, 3516), False, 'from IMGJM.layers import CharEmbedding, Glove... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import io
import re
from setuptools import setup
with io.open('README.rst', 'rt', encoding='utf8') as f:
readme = f.read()
setup(
name='itacate',
version='1.0.3',
url='https://github.com/categulario/itacate',
license='BSD',
author='<NAME>',
aut... | [
"setuptools.setup",
"io.open"
] | [((175, 1082), 'setuptools.setup', 'setup', ([], {'name': '"""itacate"""', 'version': '"""1.0.3"""', 'url': '"""https://github.com/categulario/itacate"""', 'license': '"""BSD"""', 'author': '"""<NAME>"""', 'author_email': '"""<EMAIL>"""', 'description': '"""Configuration module from flask, for the rest of the world"""'... |
from tkinter import *
from tkinter import filedialog
from tkinter import filedialog,messagebox
from MQTT.mqttListener import *
from globalVar import *
import os
def openFile():
global filepath
filepath = StringVar()
#Fetch the file path of the hex file browsed.
if(filepath == ""):
... | [
"tkinter.filedialog.askopenfilename",
"os.getcwd"
] | [((496, 606), 'tkinter.filedialog.askopenfilename', 'filedialog.askopenfilename', ([], {'initialdir': 'filepath', 'title': '"""select a file"""', 'filetypes': "[('bin files', '*.bin')]"}), "(initialdir=filepath, title='select a file',\n filetypes=[('bin files', '*.bin')])\n", (522, 606), False, 'from tkinter import ... |
import logging
import os
import time
import boto3
client = boto3.client("pinpoint")
def lambda_handler(event, context):
log_level = str(os.environ.get("LOG_LEVEL")).upper()
if log_level not in ["DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"]:
log_level = "ERROR"
logging.getLogger().setLevel(log... | [
"logging.getLogger",
"os.environ.get",
"boto3.client",
"logging.info"
] | [((61, 85), 'boto3.client', 'boto3.client', (['"""pinpoint"""'], {}), "('pinpoint')\n", (73, 85), False, 'import boto3\n'), ((332, 351), 'logging.info', 'logging.info', (['event'], {}), '(event)\n', (344, 351), False, 'import logging\n'), ((500, 522), 'logging.info', 'logging.info', (['response'], {}), '(response)\n', ... |
from typing import List, Tuple, Dict
from copy import deepcopy
from sqlite3 import Cursor
import os
from parsimonious import Grammar
from parsimonious.exceptions import ParseError
from allennlp.common.checks import ConfigurationError
from allennlp.semparse.contexts.sql_context_utils import SqlVisitor
from allennlp.se... | [
"text2sql.semparse.contexts.text2sql_table_context_v3.update_grammar_with_global_values",
"text2sql.semparse.contexts.text2sql_table_context_v3.update_grammar_to_be_variable_free",
"text2sql.semparse.contexts.text2sql_table_context_v3.update_grammar_numbers_and_strings_with_variables",
"allennlp.data.dataset_... | [((2980, 3012), 'allennlp.data.dataset_readers.dataset_utils.text2sql_utils.read_dataset_schema', 'read_dataset_schema', (['schema_path'], {}), '(schema_path)\n', (2999, 3012), False, 'from allennlp.data.dataset_readers.dataset_utils.text2sql_utils import read_dataset_schema\n'), ((3986, 4024), 'copy.deepcopy', 'deepco... |
import csv
import numpy as np
from collections import Counter
from sklearn.linear_model import LogisticRegression
from sklearn.naive_bayes import GaussianNB
from sklearn.model_selection import KFold
from sklearn.feature_extraction import DictVectorizer
from sklearn.metrics import f1_score
from sklearn imp... | [
"sklearn.feature_extraction.DictVectorizer",
"support.helper.process_tokens",
"sklearn.linear_model.LogisticRegression",
"collections.Counter",
"numpy.array",
"support.helper.tokenize",
"sklearn.naive_bayes.GaussianNB",
"sklearn.model_selection.KFold",
"csv.reader",
"sklearn.preprocessing.scale"
] | [((654, 663), 'collections.Counter', 'Counter', ([], {}), '()\n', (661, 663), False, 'from collections import Counter\n'), ((1314, 1330), 'sklearn.feature_extraction.DictVectorizer', 'DictVectorizer', ([], {}), '()\n', (1328, 1330), False, 'from sklearn.feature_extraction import DictVectorizer\n'), ((2370, 2390), 'nump... |
import requests
import json
from .models import Location, WeatherDetails
def get_location(ip_address):
resp = requests.get('http://ip-api.com/json/' + ip_address)
resp_json = json.loads(resp.text)
city = resp_json['city']
lon = resp_json['lon']
lat = resp_json['lat']
country = resp_json['cou... | [
"requests.post",
"json.loads",
"json.dumps",
"requests.get"
] | [((116, 168), 'requests.get', 'requests.get', (["('http://ip-api.com/json/' + ip_address)"], {}), "('http://ip-api.com/json/' + ip_address)\n", (128, 168), False, 'import requests\n'), ((186, 207), 'json.loads', 'json.loads', (['resp.text'], {}), '(resp.text)\n', (196, 207), False, 'import json\n'), ((550, 567), 'reque... |
from ray.rllib.models.torch.torch_modelv2 import TorchModelV2
from ray.rllib.models import ModelCatalog
from ray.rllib.utils.annotations import override
from ray.rllib.utils import try_import_torch
torch, nn = try_import_torch()
from utils.utils import get_conv_output_shape
########################################... | [
"ray.rllib.utils.try_import_torch",
"utils.utils.get_conv_output_shape"
] | [((211, 229), 'ray.rllib.utils.try_import_torch', 'try_import_torch', ([], {}), '()\n', (227, 229), False, 'from ray.rllib.utils import try_import_torch\n'), ((1430, 1472), 'utils.utils.get_conv_output_shape', 'get_conv_output_shape', (['shape', '*conv_params'], {}), '(shape, *conv_params)\n', (1451, 1472), False, 'fro... |
#!/usr/bin/env python3
# coding : utf-8
import os
import curses
from select_template import select_temp
import unicodedata as ucd
def commit(stdscr):
prefix = select_temp(stdscr)
cursor = 0
body = ""
stdscr.keypad(True)
curses.curs_set(1)
curses.use_default_colors()
curses.init_pair(2,... | [
"curses.color_pair",
"select_template.select_temp",
"curses.wrapper",
"curses.init_pair",
"curses.curs_set",
"curses.use_default_colors",
"unicodedata.east_asian_width",
"os.system"
] | [((167, 186), 'select_template.select_temp', 'select_temp', (['stdscr'], {}), '(stdscr)\n', (178, 186), False, 'from select_template import select_temp\n'), ((246, 264), 'curses.curs_set', 'curses.curs_set', (['(1)'], {}), '(1)\n', (261, 264), False, 'import curses\n'), ((269, 296), 'curses.use_default_colors', 'curses... |
#!/usr/bin/env python
from setuptools import setup
setup(
name = "glitch",
version = "1.4",
description = "glitch jpg files",
license = 'MIT',
author = "trsqxyz",
author_email = "<EMAIL>",
url = "https://github.com/trsqxyz/glitch",
classifiers = [
"Programming Language :: Pyth... | [
"setuptools.setup"
] | [((54, 495), 'setuptools.setup', 'setup', ([], {'name': '"""glitch"""', 'version': '"""1.4"""', 'description': '"""glitch jpg files"""', 'license': '"""MIT"""', 'author': '"""trsqxyz"""', 'author_email': '"""<EMAIL>"""', 'url': '"""https://github.com/trsqxyz/glitch"""', 'classifiers': "['Programming Language :: Python ... |
import numpy
from channel_noise_simulator import channel_noise_simulator
cns = channel_noise_simulator()
example_data = ""
sample_size = 20000
for i in range(sample_size):
example_data += "0"
error_density_multiplier = 2 #Higher density means smaler but more errors
x1 = 0;
x2 = 0;
count = 1000
enter_error_rate=... | [
"channel_noise_simulator.channel_noise_simulator"
] | [((81, 106), 'channel_noise_simulator.channel_noise_simulator', 'channel_noise_simulator', ([], {}), '()\n', (104, 106), False, 'from channel_noise_simulator import channel_noise_simulator\n')] |
from django.db import transaction
from django.utils.translation import gettext_lazy as _
import django_filters
import reversion
from rest_framework import exceptions, serializers, viewsets
from resources.api.base import NullableDateTimeField, TranslatedModelSerializer, register_view
from .models import CateringProdu... | [
"resources.api.base.NullableDateTimeField",
"django_filters.NumberFilter",
"django.utils.translation.gettext_lazy",
"reversion.create_revision",
"reversion.set_comment",
"django_filters.CharFilter",
"rest_framework.exceptions.ValidationError",
"resources.api.base.register_view",
"reversion.set_user"... | [((1072, 1124), 'resources.api.base.register_view', 'register_view', (['CateringProvider', '"""catering_provider"""'], {}), "(CateringProvider, 'catering_provider')\n", (1085, 1124), False, 'from resources.api.base import NullableDateTimeField, TranslatedModelSerializer, register_view\n'), ((1806, 1880), 'resources.api... |
import calendar
import requests
from datetime import datetime, timedelta
class Magicseaweed(object):
api_url = ''
def __init__(self, api_key):
base_url = 'http://magicseaweed.com/api/{0}/forecast'
self.api_url = base_url.format(api_key)
def timestamp_from_datetime(self, dt):
... | [
"datetime.datetime",
"datetime.timedelta"
] | [((1043, 1093), 'datetime.datetime', 'datetime', (['dt.year', 'dt.month', 'dt.day', 'dt.hour', '(0)', '(0)'], {}), '(dt.year, dt.month, dt.day, dt.hour, 0, 0)\n', (1051, 1093), False, 'from datetime import datetime, timedelta\n'), ((1009, 1027), 'datetime.timedelta', 'timedelta', ([], {'hours': '(1)'}), '(hours=1)\n', ... |
import numpy as np
import ast
def newtonInterpolation(x, y):
x = ast.literal_eval(x)
y = ast.literal_eval(y)
n = len(y)
table = np.zeros([n, n]) # Create a square matrix to hold table
table[::, 0] = y # first column is y
results = {"table": [], "coefficient": []}
results["tabl... | [
"ast.literal_eval",
"numpy.zeros"
] | [((74, 93), 'ast.literal_eval', 'ast.literal_eval', (['x'], {}), '(x)\n', (90, 93), False, 'import ast\n'), ((103, 122), 'ast.literal_eval', 'ast.literal_eval', (['y'], {}), '(y)\n', (119, 122), False, 'import ast\n'), ((152, 168), 'numpy.zeros', 'np.zeros', (['[n, n]'], {}), '([n, n])\n', (160, 168), True, 'import num... |
import os
from simplediscord import SimpleDiscord as Discord
token = "Bot " + os.getenv("DISCORD_TOKEN")
api = os.getenv("DISCORD_API")
guild = os.getenv("DISCORD_GUILD")
bad_words = {}
# When modifying: make sure the language keyword begins with an uppercase and the words are all lowercased.
Discord.Filter("bad_wor... | [
"simplediscord.SimpleDiscord.Filter",
"simplediscord.SimpleDiscord.Connect",
"os.getenv"
] | [((112, 136), 'os.getenv', 'os.getenv', (['"""DISCORD_API"""'], {}), "('DISCORD_API')\n", (121, 136), False, 'import os\n'), ((145, 171), 'os.getenv', 'os.getenv', (['"""DISCORD_GUILD"""'], {}), "('DISCORD_GUILD')\n", (154, 171), False, 'import os\n'), ((297, 328), 'simplediscord.SimpleDiscord.Filter', 'Discord.Filter'... |
#!/usr/bin/env python3
import os
from pathlib import Path
from sys import platform
from broker._utils.yaml import Yaml
from broker.errors import QuietExit
class ENV_BASE:
def __init__(self) -> None:
self.HOME: Path = Path.home()
hidden_base_dir = self.HOME / ".ebloc-broker"
fn = hidden_b... | [
"pathlib.Path",
"pathlib.Path.home",
"os.path.isfile",
"os.path.isdir",
"broker.errors.QuietExit",
"broker._utils.yaml.Yaml"
] | [((233, 244), 'pathlib.Path.home', 'Path.home', ([], {}), '()\n', (242, 244), False, 'from pathlib import Path\n'), ((584, 592), 'broker._utils.yaml.Yaml', 'Yaml', (['fn'], {}), '(fn)\n', (588, 592), False, 'from broker._utils.yaml import Yaml\n'), ((989, 1017), 'pathlib.Path', 'Path', (["self.cfg['ebloc_path']"], {}),... |
#coding: utf-8
__author__ = '<NAME> <<EMAIL>>'
__status__ = 'experimental'
import re
import sys
import collections
from _utilities import sort_uniq
_BRANCH_OPES = frozenset([
"ifeq", "ifnull", "iflt", "ifle", "ifne", "ifnonnull", "ifgt", "ifge",
"if_icmpeq", "if_icmpne", "if_icmplt", "if_icmpgt", "if_icmple... | [
"collections.Counter",
"_utilities.sort_uniq",
"re.compile"
] | [((1645, 1701), 're.compile', 're.compile', (['"""^//\\\\s+(Interface)?Method\\\\s+(?P<name>.+)$"""'], {}), "('^//\\\\s+(Interface)?Method\\\\s+(?P<name>.+)$')\n", (1655, 1701), False, 'import re\n'), ((10726, 10747), 'collections.Counter', 'collections.Counter', ([], {}), '()\n', (10745, 10747), False, 'import collect... |
from django.db import models
from django.urls import reverse
from django.contrib.auth.models import AbstractUser, BaseUserManager
class UserManager(BaseUserManager):
""" Base para customizar User"""
use_in_migrations = True
def _create_user(self, username, email, password, **extra_fields):
i... | [
"django.db.models.EmailField",
"django.db.models.TextField",
"django.db.models.BooleanField",
"django.urls.reverse",
"django.db.models.CharField"
] | [((1496, 1536), 'django.db.models.EmailField', 'models.EmailField', (['"""E-mail"""'], {'unique': '(True)'}), "('E-mail', unique=True)\n", (1513, 1536), False, 'from django.db import models\n'), ((1554, 1593), 'django.db.models.CharField', 'models.CharField', (['"""Nome"""'], {'max_length': '(30)'}), "('Nome', max_leng... |
from flask import Flask
app = Flask(__name__)
app.config.from_object('settings')
import govhack2014.routes # noqa
| [
"flask.Flask"
] | [((31, 46), 'flask.Flask', 'Flask', (['__name__'], {}), '(__name__)\n', (36, 46), False, 'from flask import Flask\n')] |
import code
import logging
from threading import Thread
from .helpers import setup_logging
# Set up logging
setup_logging()
logger = logging.getLogger(__name__)
class InteractiveSession:
"""
Starting an InteractiveConsole and constantly checking
"""
mitm_handler = None
def __init__(self, mitm_... | [
"logging.getLogger",
"threading.Thread",
"code.InteractiveConsole"
] | [((135, 162), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (152, 162), False, 'import logging\n'), ((654, 688), 'code.InteractiveConsole', 'code.InteractiveConsole', (['variables'], {}), '(variables)\n', (677, 688), False, 'import code\n'), ((712, 741), 'threading.Thread', 'Thread', ([]... |
import pytest
from sdk.data.Mappable import NoneAsMappable, StringAsMappable
def test_none_as_mappable():
none = NoneAsMappable()
assert none.to_json() == ''
assert none == NoneAsMappable()
@pytest.mark.parametrize('string', [
'asdfg',
'test-test',
'dunnoLol'
])
def test_string_as_mappable(... | [
"sdk.data.Mappable.NoneAsMappable",
"pytest.mark.parametrize",
"sdk.data.Mappable.StringAsMappable.from_str",
"sdk.data.Mappable.StringAsMappable"
] | [((208, 277), 'pytest.mark.parametrize', 'pytest.mark.parametrize', (['"""string"""', "['asdfg', 'test-test', 'dunnoLol']"], {}), "('string', ['asdfg', 'test-test', 'dunnoLol'])\n", (231, 277), False, 'import pytest\n'), ((120, 136), 'sdk.data.Mappable.NoneAsMappable', 'NoneAsMappable', ([], {}), '()\n', (134, 136), Fa... |
"""
The main hyperion entry point. Run `hyperion --help` for more info.
"""
import logging
from asyncio import get_event_loop, set_event_loop_policy
import click
import uvloop
from click import Path
from colorama import Fore
from .fetch import ApiError
from . import logger
from .api import run_api_server
from .cli im... | [
"logging.basicConfig",
"click.argument",
"click.option",
"click.command",
"click.echo",
"click.Path",
"uvloop.EventLoopPolicy",
"asyncio.get_event_loop",
"logging.error"
] | [((473, 488), 'click.command', 'click.command', ([], {}), '()\n', (486, 488), False, 'import click\n'), ((490, 543), 'click.argument', 'click.argument', (['"""locations"""'], {'required': '(False)', 'nargs': '(-1)'}), "('locations', required=False, nargs=-1)\n", (504, 543), False, 'import click\n'), ((545, 587), 'click... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
libG(oogle)Reader
Copyright (C) 2010 <NAME> <<EMAIL>> http://asktherelic.com
Python library for working with the unofficial Google Reader API.
Google may break this at anytime, I am not responsible for damages from that
breakage, but I will try my best to fix it.
Us... | [
"time.localtime",
"urllib2.urlopen",
"sys.setdefaultencoding",
"lib.oauth2.Token",
"lib.oauth2.Client",
"urllib2.Request",
"lib.oauth2.Consumer",
"urllib.urlencode",
"urlparse.parse_qsl",
"time.time",
"simplejson.loads",
"time.gmtime"
] | [((750, 781), 'sys.setdefaultencoding', 'sys.setdefaultencoding', (['"""utf-8"""'], {}), "('utf-8')\n", (772, 781), False, 'import sys\n'), ((15308, 15345), 'simplejson.loads', 'json.loads', (['contentJson'], {'strict': '(False)'}), '(contentJson, strict=False)\n', (15318, 15345), True, 'import simplejson as json\n'), ... |
from typing import Any, Dict, List, Type, TypeVar, Union, cast
import attr
from ..models.ssh_binding import SSHBinding
from ..models.ssh_host_key import SSHHostKey
from ..types import UNSET, Unset
T = TypeVar("T", bound="SSHServiceStatus")
@attr.s(auto_attribs=True)
class SSHServiceStatus:
""" """
is_acti... | [
"attr.s",
"attr.ib",
"typing.TypeVar"
] | [((204, 242), 'typing.TypeVar', 'TypeVar', (['"""T"""'], {'bound': '"""SSHServiceStatus"""'}), "('T', bound='SSHServiceStatus')\n", (211, 242), False, 'from typing import Any, Dict, List, Type, TypeVar, Union, cast\n'), ((246, 271), 'attr.s', 'attr.s', ([], {'auto_attribs': '(True)'}), '(auto_attribs=True)\n', (252, 27... |
# Generated by Django 3.1.1 on 2020-09-23 01:03
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('web_project', '0003_stock_change'),
]
operations = [
migrations.RemoveField(
model_name='stock',
name='high',
),
... | [
"django.db.migrations.RemoveField"
] | [((225, 280), 'django.db.migrations.RemoveField', 'migrations.RemoveField', ([], {'model_name': '"""stock"""', 'name': '"""high"""'}), "(model_name='stock', name='high')\n", (247, 280), False, 'from django.db import migrations\n'), ((325, 379), 'django.db.migrations.RemoveField', 'migrations.RemoveField', ([], {'model_... |
# Standard library imports
import pathlib
import sys
# ----------------------------------------------------------------------------
# Local imports
# ----------------------------------------------------------------------------
# # option: 1
# import files
# option: 2
# Implicit Relative Imports.
# These were removed... | [
"pathlib.Path.cwd",
"files.add_empty_file",
"pathlib.Path"
] | [((1124, 1142), 'pathlib.Path.cwd', 'pathlib.Path.cwd', ([], {}), '()\n', (1140, 1142), False, 'import pathlib\n'), ((474, 496), 'pathlib.Path', 'pathlib.Path', (['__file__'], {}), '(__file__)\n', (486, 496), False, 'import pathlib\n'), ((1305, 1346), 'files.add_empty_file', 'files.add_empty_file', (['(new_root / rel_p... |
#Hazirlayan: <NAME>
import math
def polinomlar(derece):
if(derece == 1):
a1 = ((xiler[0]*xiyiler[1])-(xiler[1]*xiyiler[0]))/ ((xiler[0]*xiler[2])-(xiler[1])**(2))
a0 = (xiyiler[0]-(a1*xiler[1]))/xiler[0]
with open("sonuc.txt","w") as file: #sonuc.txt dosyasini temizleyip ... | [
"math.sqrt"
] | [((5592, 5617), 'math.sqrt', 'math.sqrt', (['((st - sr) / st)'], {}), '((st - sr) / st)\n', (5601, 5617), False, 'import math\n')] |
import torch as th
import time
import numpy as np
import pandas as pd
import os
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib.ticker import FuncFormatter
sns.set()
sns.set_style("darkgrid", {"axes.facecolor": "#f0f0f7"})
linestyle = [':', '--', '-.', '-']
fontsize = 20
#EXP_PATH = os.path.join(... | [
"seaborn.cubehelix_palette",
"matplotlib.pyplot.ylabel",
"time.sleep",
"seaborn.set_style",
"seaborn.set",
"seaborn.color_palette",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.yticks",
"matplotlib.pyplot.axis",
"matplotlib.pyplot.ylim",
"torch.gather",
"matplotlib.pyplot.xticks",
"matplot... | [((178, 187), 'seaborn.set', 'sns.set', ([], {}), '()\n', (185, 187), True, 'import seaborn as sns\n'), ((188, 244), 'seaborn.set_style', 'sns.set_style', (['"""darkgrid"""', "{'axes.facecolor': '#f0f0f7'}"], {}), "('darkgrid', {'axes.facecolor': '#f0f0f7'})\n", (201, 244), True, 'import seaborn as sns\n'), ((1112, 113... |
# electric.csv를 읽어서 w,b를 구하고
# 실측데이터 scatter, 예측데이터는 라인차트를 그리시요.
# 전기생산량이 5인경우 전기사용량을 예측하시오
# 전기생산량, 전기사용량
# Keras 버전으로
import tensorflow as tf
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
from tensorflow.keras.layers import Dense
from tensorflow.keras import Sequential
from tensorflow.keras.o... | [
"matplotlib.pyplot.plot",
"tensorflow.keras.optimizers.Adam",
"tensorflow.keras.layers.Dense",
"numpy.loadtxt",
"matplotlib.pyplot.show"
] | [((449, 556), 'numpy.loadtxt', 'np.loadtxt', (['"""../../../data/electric.csv"""'], {'delimiter': '""","""', 'skiprows': '(1)', 'dtype': 'np.float32', 'encoding': '"""UTF8"""'}), "('../../../data/electric.csv', delimiter=',', skiprows=1, dtype=\n np.float32, encoding='UTF8')\n", (459, 556), True, 'import numpy as np... |
#!/usr/bin/python
# -*- coding: utf-8 -*-
import os
import mock
import pytest
import dallinger.db
import datetime
import signal
from dallinger.config import get_config
from dallinger.heroku import app_name
from dallinger.heroku.messages import EmailingHITMessenger
from dallinger.heroku.messages import EmailConfig
@py... | [
"dallinger.heroku.messages.HITSummary",
"mock.Mock",
"smtplib.SMTPException",
"dallinger.heroku.clock.check_db_for_missing_notifications",
"datetime.timedelta",
"dallinger.heroku.messages.EmailConfig",
"mock.patch",
"dallinger.utils.GitClient",
"dallinger.heroku.tools.HerokuApp",
"pytest.mark.usef... | [((11820, 11859), 'pytest.mark.usefixtures', 'pytest.mark.usefixtures', (['"""dummy_mailer"""'], {}), "('dummy_mailer')\n", (11843, 11859), False, 'import pytest\n'), ((24384, 24423), 'pytest.mark.usefixtures', 'pytest.mark.usefixtures', (['"""bartlett_dir"""'], {}), "('bartlett_dir')\n", (24407, 24423), False, 'import... |
"""Test geomconv script."""
import os
import pytest
import geomconv
fixtures_dir = os.path.join('tests', 'fixtures')
@pytest.fixture
def chdir_fixtures(request):
"""Change the directory to the fixtures dir and back to the root directory
after finished."""
cwd = os.getcwd()
os.chdir(fixtures_dir)
... | [
"geomconv.main",
"os.path.join",
"os.getcwd",
"os.chdir",
"pytest.mark.parametrize"
] | [((84, 117), 'os.path.join', 'os.path.join', (['"""tests"""', '"""fixtures"""'], {}), "('tests', 'fixtures')\n", (96, 117), False, 'import os\n'), ((792, 843), 'pytest.mark.parametrize', 'pytest.mark.parametrize', (['"""outfile"""', "[[], ['*.out']]"], {}), "('outfile', [[], ['*.out']])\n", (815, 843), False, 'import p... |
from floodsystem.geo import *
from floodsystem.station import MonitoringStation
from unittest import result
from floodsystem.stationdata import build_station_list
def test_stations_by_distance():
station1 = MonitoringStation("s id", "m id","A station", (3.0,4.0),(0.0,1.0),"A river","A town")
station2 = Monitor... | [
"floodsystem.station.MonitoringStation",
"floodsystem.stationdata.build_station_list"
] | [((212, 307), 'floodsystem.station.MonitoringStation', 'MonitoringStation', (['"""s id"""', '"""m id"""', '"""A station"""', '(3.0, 4.0)', '(0.0, 1.0)', '"""A river"""', '"""A town"""'], {}), "('s id', 'm id', 'A station', (3.0, 4.0), (0.0, 1.0),\n 'A river', 'A town')\n", (229, 307), False, 'from floodsystem.statio... |
# Importar librerias
import unittest
from context import scripts
# Carga de datos de funciones y obtencion del diccionario clases_orf
dir_name_functions = '/home/datasci/PycharmProjects/P4-Issam/Data/tb_functions.pl'
clases_orf = scripts.ProcessFiles(dir_name_functions).process_functions()
class TestEjercicio2(unitt... | [
"unittest.main",
"context.scripts.Ejercicio2.PatronOrf",
"context.scripts.ProcessFiles"
] | [((1346, 1361), 'unittest.main', 'unittest.main', ([], {}), '()\n', (1359, 1361), False, 'import unittest\n'), ((231, 271), 'context.scripts.ProcessFiles', 'scripts.ProcessFiles', (['dir_name_functions'], {}), '(dir_name_functions)\n', (251, 271), False, 'from context import scripts\n'), ((710, 750), 'context.scripts.E... |
import tensorflow as tf
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import os
import pandas as pd
mpl.rcParams['figure.figsize'] = (8, 6)
mpl.rcParams['axes.grid'] = False
#data
zip_path = tf.keras.utils.get_file(
origin='https://storage.googleapis.com/tensorflow/tf-keras-dataset... | [
"numpy.mean",
"numpy.reshape",
"tensorflow.random.set_seed",
"pandas.read_csv",
"tensorflow.data.Dataset.from_tensor_slices",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"os.path.splitext",
"numpy.array",
"tensorflow.keras.layers.LSTM",
"tensorflow.keras.layers.Dense",
"tensorflow.ke... | [((225, 413), 'tensorflow.keras.utils.get_file', 'tf.keras.utils.get_file', ([], {'origin': '"""https://storage.googleapis.com/tensorflow/tf-keras-datasets/jena_climate_2009_2016.csv.zip"""', 'fname': '"""jena_climate_2009_2016.csv.zip"""', 'extract': '(True)'}), "(origin=\n 'https://storage.googleapis.com/tensorflo... |