code stringlengths 22 1.05M | apis listlengths 1 3.31k | extract_api stringlengths 75 3.25M |
|---|---|---|
"""URBAN-SED Dataset Loader
.. admonition:: Dataset Info
:class: dropdown
URBAN-SED
=========
URBAN-SED (c) by <NAME>, <NAME>, <NAME>, <NAME>, and <NAME>.
URBAN-SED is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
You should have received a copy of the l... | [
"os.path.join",
"jams.load",
"soundata.core.copy_docs",
"soundata.core.docstring_inherit",
"numpy.array",
"soundata.download_utils.RemoteFileMetadata",
"os.path.basename",
"csv.reader",
"librosa.load"
] | [((12525, 12561), 'soundata.core.docstring_inherit', 'core.docstring_inherit', (['core.Dataset'], {}), '(core.Dataset)\n', (12547, 12561), False, 'from soundata import core\n'), ((9146, 9398), 'soundata.download_utils.RemoteFileMetadata', 'download_utils.RemoteFileMetadata', ([], {'filename': '"""URBAN-SED_v2.0.0.tar.g... |
import pytest
import subprocess
import server
from random import SystemRandom
import string
from unittest import mock
from multiprocessing import Process
from time import sleep
from sparkbot import SparkBot, receiver
from sparkbot.exceptions import CommandSetupError
from wsgiref import simple_server
import requests
fro... | [
"logging.getLogger",
"requests.post",
"zipfile.ZipFile",
"multiprocessing.Process",
"time.sleep",
"pytest.fail",
"pytest.fixture",
"urllib.request.urlretrieve",
"sparkbot.SparkBot",
"sparkbot.receiver.create",
"subprocess.run",
"os.mkdir",
"wsgiref.simple_server.make_server",
"unittest.moc... | [((797, 828), 'pytest.fixture', 'pytest.fixture', ([], {'scope': '"""session"""'}), "(scope='session')\n", (811, 828), False, 'import pytest\n'), ((1233, 1264), 'pytest.fixture', 'pytest.fixture', ([], {'scope': '"""session"""'}), "(scope='session')\n", (1247, 1264), False, 'import pytest\n'), ((3789, 3820), 'pytest.fi... |
#!/usr/bin/python
import subprocess
import distutils.spawn
from os.path import exists
import psutil
from ansible.module_utils.basic import AnsibleModule
DOCUMENTATION = r'''
---
module: sysinfo
version_added: "0.1"
short_description: Get system information.
description: Module which gathers summarized information ... | [
"subprocess.check_output",
"os.path.exists",
"ansible.module_utils.basic.AnsibleModule",
"psutil.disk_usage"
] | [((1150, 1198), 'subprocess.check_output', 'subprocess.check_output', (['command'], {'shell': 'in_shell'}), '(command, shell=in_shell)\n', (1173, 1198), False, 'import subprocess\n'), ((3429, 3496), 'ansible.module_utils.basic.AnsibleModule', 'AnsibleModule', ([], {'argument_spec': 'module_args', 'supports_check_mode':... |
import discord
from discord.ext import commands
from discord.ext.commands import Bot
from datetime import datetime
import sqlite3
now = datetime.now()
class mod_events(commands.Cog):
def __init__(self, bot):
self.bot = bot
@commands.Cog.listener()
async def on_member_join(self, member):
if m... | [
"discord.ext.commands.Cog.listener",
"datetime.datetime.now",
"discord.Embed",
"sqlite3.connect"
] | [((143, 157), 'datetime.datetime.now', 'datetime.now', ([], {}), '()\n', (155, 157), False, 'from datetime import datetime\n'), ((247, 270), 'discord.ext.commands.Cog.listener', 'commands.Cog.listener', ([], {}), '()\n', (268, 270), False, 'from discord.ext import commands\n'), ((475, 498), 'discord.ext.commands.Cog.li... |
import pytest
class Dummy:
pass
def test_assert_max_version():
from eventio.version_handling import assert_max_version
fake_object = Dummy()
fake_object.header = Dummy()
for i in range(3):
fake_object.header.version = i
assert_max_version(fake_object, 2)
with pytest.raises... | [
"eventio.version_handling.assert_version_in",
"pytest.raises",
"eventio.version_handling.assert_max_version",
"eventio.version_handling.assert_exact_version"
] | [((695, 731), 'eventio.version_handling.assert_exact_version', 'assert_exact_version', (['fake_object', '(1)'], {}), '(fake_object, 1)\n', (715, 731), False, 'from eventio.version_handling import assert_exact_version\n'), ((1037, 1075), 'eventio.version_handling.assert_version_in', 'assert_version_in', (['fake_object',... |
# Generated by Django 3.1.3 on 2020-11-06 11:20
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('weather', '0001_initial'),
]
operations = [
migrations.DeleteModel(
name='City',
),
]
| [
"django.db.migrations.DeleteModel"
] | [((216, 251), 'django.db.migrations.DeleteModel', 'migrations.DeleteModel', ([], {'name': '"""City"""'}), "(name='City')\n", (238, 251), False, 'from django.db import migrations\n')] |
#!/usr/bin/env python
# encoding: utf-8
'''
@author: zhoujun
@time: 2019/12/17 上午11:02
'''
from mxnet.gluon import HybridBlock, nn
import mxnet as mx
import gluoncv.model_zoo as gcv_model_zoo
from gluoncv.nn.feature import FPNFeatureExpander
class ResNetFPN(HybridBlock):
def __init__(self, backbone, channels=1, c... | [
"mxnet.gluon.nn.Conv2D",
"mxnet.gluon.nn.BatchNorm",
"mxnet.cpu",
"mxnet.gluon.nn.HybridSequential",
"gluoncv.nn.feature.FPNFeatureExpander",
"mxnet.init.Normal",
"mxnet.gluon.nn.Activation"
] | [((323, 331), 'mxnet.cpu', 'mx.cpu', ([], {}), '()\n', (329, 331), True, 'import mxnet as mx\n'), ((943, 1166), 'gluoncv.nn.feature.FPNFeatureExpander', 'FPNFeatureExpander', ([], {'network': 'base_network', 'outputs': 'backbone_outputs', 'num_filters': '[256, 256, 256, 256]', 'use_1x1': '(True)', 'use_upsample': '(Tru... |
# -*- coding: utf-8 -*-
########################################################################
# NSAp - Copyright (C) CEA, 2021
# Distributed under the terms of the CeCILL-B license, as published by
# the CEA-CNRS-INRIA. Refer to the LICENSE file or to
# http://www.cecill.info/licences/Licence_CeCILL-B_V1-en.html
# f... | [
"logging.getLogger",
"pandas.read_csv",
"numpy.save",
"numpy.savez",
"pandas.DataFrame",
"collections.namedtuple",
"sklearn.model_selection.train_test_split",
"pickle.load",
"os.path.isfile",
"numpy.isnan",
"neurocombat_sklearn.CombatModel",
"sklearn.linear_model.LinearRegression",
"pandas.i... | [((1061, 1169), 'collections.namedtuple', 'namedtuple', (['"""Item"""', "['train_input_path', 'test_input_path', 'train_metadata_path',\n 'test_metadata_path']"], {}), "('Item', ['train_input_path', 'test_input_path',\n 'train_metadata_path', 'test_metadata_path'])\n", (1071, 1169), False, 'from collections impor... |
# Copyright Contributors to the Packit project.
# SPDX-License-Identifier: MIT
import pytest
from specfile.sections import Section, Sections
def test_find():
sections = Sections([Section("package"), Section("prep"), Section("changelog")])
assert sections.find("prep") == 1
with pytest.raises(ValueError):... | [
"specfile.sections.Sections.parse",
"pytest.raises",
"specfile.sections.Section"
] | [((389, 459), 'specfile.sections.Sections.parse', 'Sections.parse', (['"""0\n\n%prep\n0\n1\n2\n\n%package x\n%files y\n0\n%changelog"""'], {}), '("""0\n\n%prep\n0\n1\n2\n\n%package x\n%files y\n0\n%changelog""")\n', (403, 459), False, 'from specfile.sections import Section, Sections\n'), ((294, 319), 'pytest.raises', '... |
# 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.nn.CellList",
"mindspore.nn.Dense",
"mindspore.ops.Abs",
"numpy.arange",
"mindspore.ops.Select",
"mindspore.ops.ReduceSum",
"mindspore.ops.Square",
"numpy.random.uniform",
"mindspore.nn.ReLU",
"mindspore.ops.Ones",
"mindspore.ops.MatMul",
"mindspore.ops.shape",
"mindspore.nn.Batch... | [((1899, 1909), 'mindspore.ops.MatMul', 'P.MatMul', ([], {}), '()\n', (1907, 1909), True, 'from mindspore import ops as P\n'), ((1929, 1956), 'mindspore.ops.ReduceSum', 'P.ReduceSum', ([], {'keep_dims': '(True)'}), '(keep_dims=True)\n', (1940, 1956), True, 'from mindspore import ops as P\n'), ((3204, 3226), 'mindspore.... |
"""
A JSON encoder and decoder to simplify working with the RPC's
datatypes.
"""
import json
import calendar
import datetime
class UTC(datetime.tzinfo):
"""UTC"""
def utcoffset(self, dt):
return datetime.timedelta(0)
def tzname(self, dt):
return 'UTC'
def dst(sel... | [
"datetime.datetime",
"datetime.timedelta"
] | [((229, 250), 'datetime.timedelta', 'datetime.timedelta', (['(0)'], {}), '(0)\n', (247, 250), False, 'import datetime\n'), ((344, 365), 'datetime.timedelta', 'datetime.timedelta', (['(0)'], {}), '(0)\n', (362, 365), False, 'import datetime\n'), ((995, 1048), 'datetime.datetime', 'datetime.datetime', (['value.year', 'va... |
from koko import NAME, VERSION, HASH
import wx
def show_about_box(event=None):
'''Displays an About box with information about this program.'''
info = wx.AboutDialogInfo()
info.SetName(NAME)
info.SetVersion(VERSION)
if HASH is None:
info.SetDescription('An interactive design tool for .ko... | [
"wx.AboutDialogInfo",
"wx.AboutBox"
] | [((162, 182), 'wx.AboutDialogInfo', 'wx.AboutDialogInfo', ([], {}), '()\n', (180, 182), False, 'import wx\n'), ((626, 643), 'wx.AboutBox', 'wx.AboutBox', (['info'], {}), '(info)\n', (637, 643), False, 'import wx\n')] |
#!/usr/bin/env python
import os
import shutil
import sys
src, dst = sys.argv[1:]
if os.path.exists(dst):
if os.path.isdir(dst):
shutil.rmtree(dst)
else:
os.remove(dst)
if os.path.isdir(src):
shutil.copytree(src, dst)
else:
shutil.copy2(src, dst)
| [
"os.path.exists",
"shutil.copy2",
"shutil.copytree",
"os.path.isdir",
"shutil.rmtree",
"os.remove"
] | [((87, 106), 'os.path.exists', 'os.path.exists', (['dst'], {}), '(dst)\n', (101, 106), False, 'import os\n'), ((187, 205), 'os.path.isdir', 'os.path.isdir', (['src'], {}), '(src)\n', (200, 205), False, 'import os\n'), ((113, 131), 'os.path.isdir', 'os.path.isdir', (['dst'], {}), '(dst)\n', (126, 131), False, 'import os... |
import threading
import os
import pigpio
import sys
from datetime import time as timestruct
from datetime import datetime
import dataclasses
import struct
import subprocess
# structure for the event data
# holds the sign of the change and the time of update
@dataclasses.dataclass
class EventData:
"""
datac... | [
"subprocess.run",
"sys.exc_info",
"datetime.datetime.now",
"pigpio.pi",
"threading.Thread"
] | [((1418, 1429), 'pigpio.pi', 'pigpio.pi', ([], {}), '()\n', (1427, 1429), False, 'import pigpio\n'), ((1910, 1987), 'threading.Thread', 'threading.Thread', ([], {'target': 'ThermalPig.update_wrapper', 'args': '(self,)', 'daemon': '(True)'}), '(target=ThermalPig.update_wrapper, args=(self,), daemon=True)\n', (1926, 1987... |
# * train.py:
# main file of the program, concludes "__main__" entry.
# * Config the arguments and run this file.
#
# * Test Status: Not tested
#
#-*- coding: utf-8 -*
from trainer.trainer import Trainer
import argparse
import os
def parse_args():
'''
- To parse arguments
- Used in __main__
:return... | [
"argparse.ArgumentParser",
"trainer.trainer.Trainer"
] | [((370, 427), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {'description': '"""Keypoints Training"""'}), "(description='Keypoints Training')\n", (393, 427), False, 'import argparse\n'), ((3325, 3338), 'trainer.trainer.Trainer', 'Trainer', (['args'], {}), '(args)\n', (3332, 3338), False, 'from trainer.trai... |
import time
from typing import Dict
import tensorflow as tf
from .helpers import get_mnist, MNIST_CLASSES, MNIST_FEATURES
def full_precision_net(features: tf.placeholder, weights: Dict[str, tf.Variable]):
"""
Constructs full precision model
:param features: model input in form of placeholder
:param ... | [
"tensorflow.random_normal",
"tensorflow.nn.relu",
"tensorflow.placeholder",
"tensorflow.Session",
"tensorflow.global_variables_initializer",
"tensorflow.argmax",
"tensorflow.matmul",
"tensorflow.nn.softmax",
"tensorflow.nn.softmax_cross_entropy_with_logits",
"tensorflow.train.AdamOptimizer",
"te... | [((394, 428), 'tensorflow.matmul', 'tf.matmul', (['features', "weights['h1']"], {}), "(features, weights['h1'])\n", (403, 428), True, 'import tensorflow as tf\n'), ((439, 454), 'tensorflow.nn.relu', 'tf.nn.relu', (['z_1'], {}), '(z_1)\n', (449, 454), True, 'import tensorflow as tf\n'), ((492, 521), 'tensorflow.matmul',... |
# Copyright (c) 2013, SELCO and contributors
# For license information, please see license.txt
from __future__ import unicode_literals
import frappe
from frappe import _
from erpnext.hr.doctype.process_payroll.process_payroll import get_month_details
from frappe import msgprint
import datetime
from datetime import tim... | [
"frappe.db.get_value",
"dateutil.relativedelta.relativedelta",
"frappe._",
"frappe.db.sql",
"frappe.utils.cint",
"datetime.timedelta",
"frappe.utils.getdate"
] | [((2108, 2174), 'frappe.db.get_value', 'frappe.db.get_value', (['"""Fiscal Year"""', 'fiscal_year', '"""year_start_date"""'], {}), "('Fiscal Year', fiscal_year, 'year_start_date')\n", (2127, 2174), False, 'import frappe\n'), ((2736, 3264), 'frappe.db.sql', 'frappe.db.sql', (['"""select name, selco_complaint_received_da... |
import os
import sys
import numpy as np
def get_malware_dataset(valid=False):
def get_monthly_data(file_path, num_feature=483):
'''Each row of `x_mat` is a datapoint.
It adds a constant one for another dimension at the end for the bias term.
Returns:
two numpy arrays, one... | [
"numpy.mean",
"numpy.where",
"numpy.log",
"numpy.array",
"numpy.concatenate",
"numpy.std"
] | [((7147, 7180), 'numpy.mean', 'np.mean', (['X'], {'axis': '(0)', 'keepdims': '(True)'}), '(X, axis=0, keepdims=True)\n', (7154, 7180), True, 'import numpy as np\n'), ((7215, 7247), 'numpy.std', 'np.std', (['X'], {'axis': '(0)', 'keepdims': '(True)'}), '(X, axis=0, keepdims=True)\n', (7221, 7247), True, 'import numpy as... |
import argparse
import logging
import os
import random
import math
import ransac.core as ransac
from ransac.models.conic_section import ConicSection
import cv2
import numpy as np
logging.basicConfig(level=logging.DEBUG, format='%(asctime)-15s [%(levelname)s] %(message)s')
parser = argparse.ArgumentParser()
parser.add... | [
"logging.basicConfig",
"cv2.min",
"os.path.exists",
"argparse.ArgumentParser",
"os.makedirs",
"cv2.line",
"os.path.join",
"logging.info",
"random.seed",
"ransac.core.Modeler",
"numpy.zeros",
"cv2.circle",
"cv2.cvtColor",
"cv2.Canny",
"cv2.imread",
"cv2.blur"
] | [((180, 278), 'logging.basicConfig', 'logging.basicConfig', ([], {'level': 'logging.DEBUG', 'format': '"""%(asctime)-15s [%(levelname)s] %(message)s"""'}), "(level=logging.DEBUG, format=\n '%(asctime)-15s [%(levelname)s] %(message)s')\n", (199, 278), False, 'import logging\n'), ((284, 309), 'argparse.ArgumentParser'... |
from django.db import models
# Create your models here.
class Image(models.Model):
image = models.ImageField(upload_to = 'gallery/')
name = models.CharField(max_length=30)
description = models.CharField(max_length=100)
location = models.ForeignKey('location',on_delete = models.CASCADE)
category = m... | [
"django.db.models.ImageField",
"django.db.models.CharField",
"django.db.models.ForeignKey"
] | [((96, 135), 'django.db.models.ImageField', 'models.ImageField', ([], {'upload_to': '"""gallery/"""'}), "(upload_to='gallery/')\n", (113, 135), False, 'from django.db import models\n'), ((149, 180), 'django.db.models.CharField', 'models.CharField', ([], {'max_length': '(30)'}), '(max_length=30)\n', (165, 180), False, '... |
import re
from nltk.corpus import stopwords
from nltk.data import PathPointer
import pandas
from sklearn.feature_extraction.text import TfidfVectorizer , CountVectorizer
from nltk.tokenize import word_tokenize
import pandas as pd
from sklearn.feature_extraction.text import TfidfVectorizer,CountVectorizer
qsn=input("En... | [
"sklearn.feature_extraction.text.TfidfVectorizer"
] | [((977, 1031), 'sklearn.feature_extraction.text.TfidfVectorizer', 'TfidfVectorizer', ([], {'analyzer': '"""word"""', 'stop_words': '"""english"""'}), "(analyzer='word', stop_words='english')\n", (992, 1031), False, 'from sklearn.feature_extraction.text import TfidfVectorizer, CountVectorizer\n')] |
"""
Google Cloud Messaging
Previously known as C2DM
Documentation is available on the Android Developer website:
https://developer.android.com/google/gcm/index.html
"""
import json
from .models import GCMDevice
try:
from urllib.request import Request, urlopen
from urllib.parse import urlencode
except ImportError:
... | [
"urllib2.Request",
"json.dumps",
"django.core.exceptions.ImproperlyConfigured",
"urllib2.urlopen"
] | [((1088, 1136), 'urllib2.Request', 'Request', (["SETTINGS['GCM_POST_URL']", 'data', 'headers'], {}), "(SETTINGS['GCM_POST_URL'], data, headers)\n", (1095, 1136), False, 'from urllib2 import Request, urlopen\n'), ((841, 963), 'django.core.exceptions.ImproperlyConfigured', 'ImproperlyConfigured', (['"""You need to set PU... |
# This is a template for your project 2 submission.
# Please fill in the get_predictions method to return key-value pairs
# for each parcelid and the predicted log-error.
# Import the libraries and give them abbreviated names:
import pandas as pd
import numpy as np
import statsmodels.api as sm
# load the data, us... | [
"pandas.read_csv"
] | [((401, 435), 'pandas.read_csv', 'pd.read_csv', (['"""properties_2017.csv"""'], {}), "('properties_2017.csv')\n", (412, 435), True, 'import pandas as pd\n'), ((448, 510), 'pandas.read_csv', 'pd.read_csv', (['"""train_2017.csv"""'], {'parse_dates': "['transactiondate']"}), "('train_2017.csv', parse_dates=['transactionda... |
import math
import os
import torch
import numpy as np
## Code taken from https://github.com/hassony2/kinetics_i3d_pytorch/blob/master/src/i3dpt.py
def get_padding_shape(filter_shape, stride, mod=0):
"""Fetch a tuple describing the input padding shape.
NOTES: To replicate "TF SAME" style padding, the padding ... | [
"torch.nn.Dropout",
"torch.nn.Softmax",
"torch.nn.AvgPool3d",
"torch.nn.Sequential",
"torch.nn.MaxPool3d",
"torch.nn.functional.relu",
"torch.nn.ConstantPad3d",
"torch.nn.BatchNorm3d",
"torch.cat",
"torch.nn.Conv3d"
] | [((5465, 5520), 'torch.nn.MaxPool3d', 'torch.nn.MaxPool3d', (['kernel_size', 'stride'], {'ceil_mode': '(True)'}), '(kernel_size, stride, ceil_mode=True)\n', (5483, 5520), False, 'import torch\n'), ((6195, 6246), 'torch.nn.Sequential', 'torch.nn.Sequential', (['branch_1_conv1', 'branch_1_conv2'], {}), '(branch_1_conv1, ... |
import boto3
import logging
import json
logger = logging.getLogger()
logger.setLevel(logging.INFO)
sm_client = boto3.client('sagemaker')
#Retrieve Hyperparameters Tuning Job infomation.
def lambda_handler(event, context):
if ('HpoJobName' in event):
hpo_job_name = event['HpoJobName']
else:
r... | [
"logging.getLogger",
"json.dumps",
"boto3.client"
] | [((50, 69), 'logging.getLogger', 'logging.getLogger', ([], {}), '()\n', (67, 69), False, 'import logging\n'), ((112, 137), 'boto3.client', 'boto3.client', (['"""sagemaker"""'], {}), "('sagemaker')\n", (124, 137), False, 'import boto3\n'), ((441, 458), 'json.dumps', 'json.dumps', (['event'], {}), '(event)\n', (451, 458)... |
"""
Copyright (C) Cortic Technology Corp. - All Rights Reserved
Written by <NAME> <<EMAIL>>, 2021
"""
import picamera
import logging
import time
import base64
import io
import threading
from curt.modules.vision.base_vision_input import BaseVisionInput
from collections import deque
class PicamInput(BaseVisionInput)... | [
"collections.deque",
"base64.b64encode",
"io.BytesIO",
"picamera.PiCamera",
"logging.warning",
"threading.Event",
"threading.Thread"
] | [((449, 464), 'collections.deque', 'deque', ([], {'maxlen': '(3)'}), '(maxlen=3)\n', (454, 464), False, 'from collections import deque\n'), ((486, 503), 'threading.Event', 'threading.Event', ([], {}), '()\n', (501, 503), False, 'import threading\n'), ((950, 969), 'picamera.PiCamera', 'picamera.PiCamera', ([], {}), '()\... |
"""
process_abundances
Author: <NAME>
Notes: script and functions to process stellar abundane output from a
simulation where chemical tags of stars are written to stdout. This
loops through all files that could contain this info in the given
directory (or files that match ... | [
"galaxy_analysis.utilities.utilities.species_from_fields",
"numpy.sum",
"yt.load",
"subprocess.call",
"numpy.genfromtxt",
"glob.glob"
] | [((1751, 1774), 'numpy.genfromtxt', 'np.genfromtxt', (['"""sf.dat"""'], {}), "('sf.dat')\n", (1764, 1774), True, 'import numpy as np\n'), ((2772, 2864), 'numpy.genfromtxt', 'np.genfromtxt', (["(directory + '/StellarAbundances.dat')"], {'dtype': '_ndtypes', 'invalid_raise': '(False)'}), "(directory + '/StellarAbundances... |
import logging
import unittest
from observer import Hobbits, Orcs, Weather, WeatherType
class TestObserver(unittest.TestCase):
def test_observable(self):
weather = Weather()
# register observable
orcs, hobbits = Orcs(), Hobbits()
weather.add_observer(orcs)
weather.add_obs... | [
"observer.Weather",
"observer.Orcs",
"observer.Hobbits"
] | [((179, 188), 'observer.Weather', 'Weather', ([], {}), '()\n', (186, 188), False, 'from observer import Hobbits, Orcs, Weather, WeatherType\n'), ((244, 250), 'observer.Orcs', 'Orcs', ([], {}), '()\n', (248, 250), False, 'from observer import Hobbits, Orcs, Weather, WeatherType\n'), ((252, 261), 'observer.Hobbits', 'Hob... |
import hashlib
import json
import sys
import time
import types
import warnings
try:
from urllib.request import build_opener, HTTPRedirectHandler
from urllib.parse import urlencode
from urllib.error import URLError, HTTPError
string_types = str,
integer_types = int,
numeric_types = (int, float)
... | [
"json.loads",
"hashlib.md5",
"sys.exc_info",
"urllib.urlencode",
"warnings.warn",
"time.gmtime"
] | [((4158, 4251), 'warnings.warn', 'warnings.warn', (['"""/v3/clicks is depricated in favor of /v3/link/clicks"""', 'DeprecationWarning'], {}), "('/v3/clicks is depricated in favor of /v3/link/clicks',\n DeprecationWarning)\n", (4171, 4251), False, 'import warnings\n'), ((4789, 4888), 'warnings.warn', 'warnings.warn',... |
# -*- coding: utf-8 -*-
"""
Coil module
Created on Tue Jan 26 08:31:05 2021
@author: <NAME>
"""
from __future__ import annotations
from typing import List
import numpy as np
import os
import matplotlib.pyplot as plt
from ..segment.segment import Segment, Arc, Circle, Line
from ..wire.wire import Wire, WireRect, Wi... | [
"os.path.exists",
"matplotlib.pyplot.savefig",
"numpy.array",
"matplotlib.pyplot.figure",
"numpy.linspace",
"matplotlib.pyplot.show"
] | [((784, 809), 'numpy.array', 'np.array', (['[0.0, 0.0, 0.0]'], {}), '([0.0, 0.0, 0.0])\n', (792, 809), True, 'import numpy as np\n'), ((819, 844), 'numpy.array', 'np.array', (['[1.0, 0.0, 0.0]'], {}), '([1.0, 0.0, 0.0])\n', (827, 844), True, 'import numpy as np\n'), ((854, 879), 'numpy.array', 'np.array', (['[0.0, 1.0,... |
import math
import torch
import pyro
from pyro import poutine
from pyro.poutine.util import prune_subsample_sites
from pyro.util import warn_if_nan
from pyro.infer.util import torch_item
from pyro.contrib.util import lexpand, rexpand
class BlackBoxMutualInformation(object):
def __init__(
self, model, cr... | [
"torch.randperm",
"pyro.plate_stack",
"pyro.util.warn_if_nan",
"pyro.poutine.util.prune_subsample_sites",
"torch.stack",
"math.log",
"pyro.poutine.trace",
"pyro.module",
"math.exp",
"torch.cat"
] | [((2848, 2876), 'pyro.poutine.util.prune_subsample_sites', 'prune_subsample_sites', (['trace'], {}), '(trace)\n', (2869, 2876), False, 'from pyro.poutine.util import prune_subsample_sites\n'), ((3602, 3629), 'torch.cat', 'torch.cat', (['latents'], {'axis': '(-1)'}), '(latents, axis=-1)\n', (3611, 3629), False, 'import ... |
import config
config.setup_examples()
import infermedica_api
if __name__ == '__main__':
api = infermedica_api.get_api()
print('Laboratory tests list:')
print(api.lab_tests_list(), end="\n\n")
print('\n\nLaboratory test details:')
print(api.lab_test_details('lt_81'), end="\n\n")
print('Non-... | [
"infermedica_api.get_api",
"config.setup_examples"
] | [((15, 38), 'config.setup_examples', 'config.setup_examples', ([], {}), '()\n', (36, 38), False, 'import config\n'), ((101, 126), 'infermedica_api.get_api', 'infermedica_api.get_api', ([], {}), '()\n', (124, 126), False, 'import infermedica_api\n')] |
from pathlib import Path
import json
folder = Path(__file__).parent.parent / 'others' / 'numpy_journey'
out_folder = Path(__file__).parent.parent.parent / 'Desktop' / 'python_folder'
def load_data(file):
with file.open('r') as fr:
data = json.load(fr)
file_name = file.name.split('.')[0]
wr... | [
"json.load",
"pathlib.Path"
] | [((252, 265), 'json.load', 'json.load', (['fr'], {}), '(fr)\n', (261, 265), False, 'import json\n'), ((47, 61), 'pathlib.Path', 'Path', (['__file__'], {}), '(__file__)\n', (51, 61), False, 'from pathlib import Path\n'), ((118, 132), 'pathlib.Path', 'Path', (['__file__'], {}), '(__file__)\n', (122, 132), False, 'from pa... |
import random
import time
def game(comp, a):
if comp == 'S':
if a == 'P':
print('You loss as computer choosen',comp,'\nso better luck next time')
#return False
elif a == 'R':
print('You Won as computer choosen',comp)
#return True
el... | [
"random.randint",
"time.sleep"
] | [((1346, 1366), 'random.randint', 'random.randint', (['(1)', '(3)'], {}), '(1, 3)\n', (1360, 1366), False, 'import random\n'), ((1529, 1542), 'time.sleep', 'time.sleep', (['(1)'], {}), '(1)\n', (1539, 1542), False, 'import time\n'), ((1600, 1615), 'time.sleep', 'time.sleep', (['(0.3)'], {}), '(0.3)\n', (1610, 1615), Fa... |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import glob
from setuptools import setup
setup(
name='Sensorgan',
packages=['utils', 'utils.core', 'utils.data', 'utils.helpers', 'utils.models']
) | [
"setuptools.setup"
] | [((154, 262), 'setuptools.setup', 'setup', ([], {'name': '"""Sensorgan"""', 'packages': "['utils', 'utils.core', 'utils.data', 'utils.helpers', 'utils.models']"}), "(name='Sensorgan', packages=['utils', 'utils.core', 'utils.data',\n 'utils.helpers', 'utils.models'])\n", (159, 262), False, 'from setuptools import set... |
#################################
#
# NOTE: Do not edit this file.
#
import sys
from nqueens import solve
import time
if len(sys.argv) != 2:
print("\n\tUsage: python3 run.py <test-file>\n")
exit(1)
in_file = sys.argv[1]
problems = []
with open(in_file) as f:
problems = map(int, f.readlines())
def p... | [
"nqueens.solve",
"time.time"
] | [((1340, 1351), 'time.time', 'time.time', ([], {}), '()\n', (1349, 1351), False, 'import time\n'), ((1365, 1373), 'nqueens.solve', 'solve', (['p'], {}), '(p)\n', (1370, 1373), False, 'from nqueens import solve\n'), ((1383, 1394), 'time.time', 'time.time', ([], {}), '()\n', (1392, 1394), False, 'import time\n')] |
from gtts import gTTS
import os
tts = gTTS(text='temperatura a 30 grados', lang='es')
tts.save('apagado.mp3')
| [
"gtts.gTTS"
] | [((38, 85), 'gtts.gTTS', 'gTTS', ([], {'text': '"""temperatura a 30 grados"""', 'lang': '"""es"""'}), "(text='temperatura a 30 grados', lang='es')\n", (42, 85), False, 'from gtts import gTTS\n')] |
from dataclasses import dataclass
from typing import List
from pydantic import BaseModel
from xpresso import (
App,
ExtractRepeatedField,
FromFile,
FromFormField,
FromMultipart,
Path,
UploadFile,
)
class JsonModel(BaseModel):
foo: str
@dataclass(frozen=True)
class FormDataModel:
... | [
"dataclasses.dataclass",
"xpresso.Path"
] | [((274, 296), 'dataclasses.dataclass', 'dataclass', ([], {'frozen': '(True)'}), '(frozen=True)\n', (283, 296), False, 'from dataclasses import dataclass\n'), ((842, 878), 'xpresso.Path', 'Path', ([], {'path': '"""/form"""', 'post': 'upload_data'}), "(path='/form', post=upload_data)\n", (846, 878), False, 'from xpresso ... |
#!/usr/bin/env python
from setuptools import setup, find_packages
version = '0.6'
setup(
name='webstruct',
version=version,
description="A library for creating statistical NER systems that work on HTML data",
long_description=open('README.rst').read(),
author='<NAME>, <NAME>',
author_email='<E... | [
"setuptools.find_packages"
] | [((402, 417), 'setuptools.find_packages', 'find_packages', ([], {}), '()\n', (415, 417), False, 'from setuptools import setup, find_packages\n')] |
from django.shortcuts import render
from django.http.response import HttpResponse, HttpResponseRedirect
from neighborhoodapp.models import Business, Post, Profile, Neighbourhood
from django.contrib.auth.models import User
from django.contrib.auth.decorators import login_required
from django.contrib.auth import login, a... | [
"django.shortcuts.render",
"django.contrib.auth.authenticate",
"neighborhoodapp.models.Business.search_business",
"neighborhoodapp.forms.NewBusinessForm",
"django.http.response.HttpResponseRedirect",
"neighborhoodapp.forms.PostForm",
"django.shortcuts.get_object_or_404",
"django.contrib.auth.login",
... | [((701, 745), 'django.contrib.auth.decorators.login_required', 'login_required', ([], {'login_url': '"""/accounts/login/"""'}), "(login_url='/accounts/login/')\n", (715, 745), False, 'from django.contrib.auth.decorators import login_required\n'), ((1090, 1134), 'django.contrib.auth.decorators.login_required', 'login_re... |
from training import *
from functions import *
import os
import csv
cwd = os.getcwd()
############ Hyper-parameters
num_run = 2
pve_int = 1.0; sparsity = 0.1; num_hidden_nodes = 200
learning_rate = 2*1e-3; num_epoch = 200
#############################
print('Prior pve is: '+str(pve_int)+', sparsity leve... | [
"csv.reader",
"os.getcwd"
] | [((80, 91), 'os.getcwd', 'os.getcwd', ([], {}), '()\n', (89, 91), False, 'import os\n'), ((482, 495), 'csv.reader', 'csv.reader', (['f'], {}), '(f)\n', (492, 495), False, 'import csv\n')] |
import logging
from FunctionParserBase import FunctionParserBase
class GenericFunctionParser(FunctionParserBase):
"""
A generic function parser.
This parser parses arguments by their index order.
"""
def __init__(self, function):
"""
@param function: A Function instance
"... | [
"logging.getLogger"
] | [((407, 434), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (424, 434), False, 'import logging\n')] |
from user_lib.exec_cmd import ExeCmd
from user_lib.const_values import ConstValues
class Entity:
def __init__(self):
self._exec_cmd = ExeCmd()
self._monitored = {}
self._settings = None
def set_settings(self, settings):
self._settings = settings
def handle_notification(se... | [
"user_lib.exec_cmd.ExeCmd"
] | [((148, 156), 'user_lib.exec_cmd.ExeCmd', 'ExeCmd', ([], {}), '()\n', (154, 156), False, 'from user_lib.exec_cmd import ExeCmd\n')] |
from russian_g2p import Grapheme2Phoneme
from russian_g2p import Accentor
import json
import codecs
words = open('/home/a117/Документы/Linguistics/russian_g2p/corpus/wordlist')
words = words.readlines()
# words = ['я']
# acc = Accentor()
g2p = Grapheme2Phoneme()
new_simple_words = {}
with open('new', 'w') as f:
fo... | [
"russian_g2p.Grapheme2Phoneme"
] | [((245, 263), 'russian_g2p.Grapheme2Phoneme', 'Grapheme2Phoneme', ([], {}), '()\n', (261, 263), False, 'from russian_g2p import Grapheme2Phoneme\n')] |
from gamechangerml.src.search.sent_transformer.finetune import STFinetuner
from gamechangerml.configs.config import EmbedderConfig
from gamechangerml.api.utils.pathselect import get_model_paths
from gamechangerml.api.utils.logger import logger
import argparse
import os
from datetime import datetime
model_path_dict = g... | [
"gamechangerml.api.utils.logger.logger.info",
"argparse.ArgumentParser",
"os.path.join",
"gamechangerml.api.utils.pathselect.get_model_paths",
"datetime.datetime.now",
"gamechangerml.src.search.sent_transformer.finetune.STFinetuner"
] | [((319, 336), 'gamechangerml.api.utils.pathselect.get_model_paths', 'get_model_paths', ([], {}), '()\n', (334, 336), False, 'from gamechangerml.api.utils.pathselect import get_model_paths\n'), ((508, 617), 'gamechangerml.src.search.sent_transformer.finetune.STFinetuner', 'STFinetuner', ([], {'model_load_path': 'model_l... |
# -*- coding: utf-8 -*-
"""
Created on Wed Mar 20 21:20:48 2019
INSTITUTO FEDERAL DE EDUCAÇÃO, CIÊNCIA E TECNOLOGIA DO PÁRA - IFPA ANANINDEUA
@author:
Prof. Dr. <NAME>
Discentes:
<NAME>
<NAME>
Grupo de Pesquisa:
Gradiente de Mo... | [
"matplotlib.pyplot.grid",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"numpy.linspace",
"numpy.cos",
"matplotlib.pyplot.title",
"matplotlib.pyplot.show"
] | [((786, 825), 'numpy.linspace', 'np.linspace', (['(-2 * np.pi)', '(2 * np.pi)', '(100)'], {}), '(-2 * np.pi, 2 * np.pi, 100)\n', (797, 825), True, 'import numpy as np\n'), ((853, 862), 'numpy.cos', 'np.cos', (['x'], {}), '(x)\n', (859, 862), True, 'import numpy as np\n'), ((1056, 1076), 'matplotlib.pyplot.plot', 'plt.p... |
from typing import Callable, Dict, Iterable, Optional, Tuple, Type
from urllib.parse import parse_qs, urlparse
import pytest
from rest_registration.utils.signers import URLParamsSigner
from tests.helpers.timer import Timer
def assert_valid_verification_url(
url: str,
expected_path: Optional[str] = N... | [
"urllib.parse.parse_qs",
"urllib.parse.urlparse"
] | [((1464, 1477), 'urllib.parse.urlparse', 'urlparse', (['url'], {}), '(url)\n', (1472, 1477), False, 'from urllib.parse import parse_qs, urlparse\n'), ((1490, 1537), 'urllib.parse.parse_qs', 'parse_qs', (['parsed_url.query'], {'strict_parsing': '(True)'}), '(parsed_url.query, strict_parsing=True)\n', (1498, 1537), False... |
import numpy as np
import argparse
# from rllab.envs.normalized_env import normalize
from maci.learners import MADDPG, MAVBAC, MASQL
from maci.misc.kernel import adaptive_isotropic_gaussian_kernel
from maci.replay_buffers import SimpleReplayBuffer
from maci.value_functions.sq_value_function import NNQFunction, NNJoin... | [
"maci.value_functions.sq_value_function.NNQFunction",
"maci.replay_buffers.SimpleReplayBuffer",
"maci.policies.StochasticNNConditionalPolicy",
"gtimer.reset",
"gtimer.rename_root",
"numpy.array",
"maci.policies.StochasticNNPolicy",
"copy.deepcopy",
"rllab.misc.logger.set_snapshot_dir",
"gtimer.sta... | [((790, 887), 'maci.replay_buffers.SimpleReplayBuffer', 'SimpleReplayBuffer', (['env.env_specs'], {'max_replay_buffer_size': '(1000000.0)', 'joint': 'joint', 'agent_id': 'i'}), '(env.env_specs, max_replay_buffer_size=1000000.0, joint=\n joint, agent_id=i)\n', (808, 887), False, 'from maci.replay_buffers import Simpl... |
# Copyright 2013 Rackspace
#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the... | [
"raxcli.models.Attribute"
] | [((921, 932), 'raxcli.models.Attribute', 'Attribute', ([], {}), '()\n', (930, 932), False, 'from raxcli.models import Attribute, Model\n'), ((945, 956), 'raxcli.models.Attribute', 'Attribute', ([], {}), '()\n', (954, 956), False, 'from raxcli.models import Attribute, Model\n'), ((968, 979), 'raxcli.models.Attribute', '... |
###############################
# Import Python modules
###############################
import os, sys, datetime, inspect
###############################
# Import Scapy and Goose Modules
###############################
# We have to tell script where to find the Goose module in parent directory
currentdir = os.path.dir... | [
"sys.path.insert",
"inspect.currentframe",
"os.path.dirname",
"scapy.all.rdpcap",
"goose.goose.GOOSE"
] | [((395, 422), 'os.path.dirname', 'os.path.dirname', (['currentdir'], {}), '(currentdir)\n', (410, 422), False, 'import os, sys, datetime, inspect\n'), ((423, 452), 'sys.path.insert', 'sys.path.insert', (['(0)', 'parentdir'], {}), '(0, parentdir)\n', (438, 452), False, 'import os, sys, datetime, inspect\n'), ((1050, 106... |
import os
import torch
import torch.nn as nn
import struct
import numpy as np
import json
from time import perf_counter
from pprint import pprint
from lstm_rnnt_dec import PluginLstmRnntDec
start_setup_time = perf_counter()
# Setup.
output_bin = os.environ.get('CK_OUT_RAW_DATA', 'tmp-ck-output.bin')
output_json = ou... | [
"os.path.exists",
"pprint.pprint",
"torch.load",
"json.dumps",
"os.environ.get",
"time.perf_counter",
"torch.from_numpy",
"lstm_rnnt_dec.PluginLstmRnntDec",
"torch.zeros",
"numpy.random.RandomState"
] | [((211, 225), 'time.perf_counter', 'perf_counter', ([], {}), '()\n', (223, 225), False, 'from time import perf_counter\n'), ((249, 303), 'os.environ.get', 'os.environ.get', (['"""CK_OUT_RAW_DATA"""', '"""tmp-ck-output.bin"""'], {}), "('CK_OUT_RAW_DATA', 'tmp-ck-output.bin')\n", (263, 303), False, 'import os\n'), ((368,... |
# 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 in writing, software
# distributed under the Li... | [
"numpy.mean",
"numpy.random.default_rng",
"numpy.array",
"numpy.apply_along_axis",
"numpy.concatenate",
"copy.deepcopy",
"pandas.concat"
] | [((2802, 2836), 'numpy.random.default_rng', 'np.random.default_rng', (['random_seed'], {}), '(random_seed)\n', (2823, 2836), True, 'import numpy as np\n'), ((12769, 12833), 'numpy.concatenate', 'np.concatenate', (['(treated_covariates, control_covariates)'], {'axis': '(1)'}), '((treated_covariates, control_covariates),... |
#! /usr/bin/env python3
#
# Copyright (c) 2022 Intel Corporation
#
# SPDX-License-Identifier: Apache-2.0
#
import logging
import os
import subprocess
import keyring
import keyring.backend
import keyring.errors
log = logging.getLogger("keyring_keyctl")
class keyring_keyctl_c(keyring.backend.KeyringBackend):
"""
... | [
"logging.getLogger",
"random.choice",
"keyring.errors.PasswordSetError",
"subprocess.run",
"keyring.backend.KeyringBackend.__init__",
"keyring.errors.KeyringError"
] | [((218, 253), 'logging.getLogger', 'logging.getLogger', (['"""keyring_keyctl"""'], {}), "('keyring_keyctl')\n", (235, 253), False, 'import logging\n'), ((783, 828), 'keyring.backend.KeyringBackend.__init__', 'keyring.backend.KeyringBackend.__init__', (['self'], {}), '(self)\n', (822, 828), False, 'import keyring\n'), (... |
"""
Example inferring multiple exponential decay models arranged into a
4D voxelwise image.
This example uses the main() interface as used by the command line
application to simplify running the inference and saving the output
"""
import sys
import numpy as np
import nibabel as nib
from vaby_avb import run
import va... | [
"numpy.random.normal",
"numpy.identity",
"numpy.sqrt",
"numpy.array",
"vaby_avb.run",
"vaby.get_model_class"
] | [((599, 623), 'numpy.sqrt', 'np.sqrt', (['NOISE_VAR_TRUTH'], {}), '(NOISE_VAR_TRUTH)\n', (606, 623), True, 'import numpy as np\n'), ((1800, 1866), 'vaby_avb.run', 'run', (['"""data_exp_noisy.nii.gz"""', '"""exp"""', '"""exps_example_out"""'], {}), "('data_exp_noisy.nii.gz', 'exp', 'exps_example_out', **options)\n", (18... |
from django.shortcuts import render, redirect
from django.contrib import messages
from django.contrib.auth.decorators import login_required
from django.http import JsonResponse
from .models import Neighbourhood,Post,Contact, Business
from .forms import NeighbourhoodForm, ContactForm, PostForm, BusinessForm
# Create y... | [
"django.shortcuts.render",
"django.http.JsonResponse",
"django.shortcuts.redirect",
"django.contrib.auth.decorators.login_required",
"django.contrib.messages.success"
] | [((337, 370), 'django.contrib.auth.decorators.login_required', 'login_required', ([], {'login_url': '"""login"""'}), "(login_url='login')\n", (351, 370), False, 'from django.contrib.auth.decorators import login_required\n'), ((748, 781), 'django.contrib.auth.decorators.login_required', 'login_required', ([], {'login_ur... |
import os
import sys
from abc import ABCMeta, abstractmethod
from datetime import datetime
from pathlib import Path
from typing import Union
import joblib
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import classification_report
from .. import __version__
from ..utils import CANARY_MODEL_S... | [
"os.makedirs",
"pathlib.Path",
"sklearn.metrics.classification_report",
"sklearn.linear_model.LogisticRegression",
"datetime.datetime.now"
] | [((1098, 1142), 'os.makedirs', 'os.makedirs', (['self.__model_dir'], {'exist_ok': '(True)'}), '(self.__model_dir, exist_ok=True)\n', (1109, 1142), False, 'import os\n'), ((6304, 6369), 'sklearn.metrics.classification_report', 'classification_report', (['test_targets', 'prediction'], {'output_dict': '(True)'}), '(test_t... |
import yaml
# 填充默认设置
default_config = {
'debug_mode': False,
'save_manifest_file': True,
'output_path': './output',
'proxy': None,
'downloader_max_connection_number': 5,
'downloader_max_retry_number': 5,
'friendly_console_output': False,
'header': {
'referer': 'https://manhua.dm... | [
"yaml.load"
] | [((544, 559), 'yaml.load', 'yaml.load', (['text'], {}), '(text)\n', (553, 559), False, 'import yaml\n')] |
# Create By : <NAME>
# Uses : Manage Role
from flask import jsonify, request
import socket
from datetime import datetime, date, time, timedelta
import pymongo
from database import DB
import json
from bson import json_util, ObjectId
class VendorSubscription:
def __init__(self,vendor_id=None,user_id=None):
... | [
"database.DB.insert",
"bson.ObjectId",
"socket.gethostname",
"datetime.datetime.now"
] | [((2325, 2353), 'bson.ObjectId', 'ObjectId', (["subData['user_id']"], {}), "(subData['user_id'])\n", (2333, 2353), False, 'from bson import json_util, ObjectId\n'), ((2388, 2418), 'bson.ObjectId', 'ObjectId', (["subData['vendor_id']"], {}), "(subData['vendor_id'])\n", (2396, 2418), False, 'from bson import json_util, O... |
#!/usr/bin/env python
""" AER1415 Computer Optimization - Assignment 1
Author: <NAME>
Submitted: Feb 25, 2021
Email: <EMAIL>
Descripton:
"""
from numpy import *
import os
from matplotlib import pyplot as plt
from IPython import embed
from mpl_toolkits import mplot3d
from matplotlib import cm
import... | [
"matplotlib.use",
"cmath.sqrt",
"IPython.embed",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.axes",
"matplotlib.pyplot.subplots",
"warnings.filterwarnings",
"matplotlib.pyplot.show"
] | [((366, 424), 'warnings.filterwarnings', 'warnings.filterwarnings', (['"""ignore"""'], {'category': 'RuntimeWarning'}), "('ignore', category=RuntimeWarning)\n", (389, 424), False, 'import warnings\n'), ((429, 452), 'matplotlib.use', 'matplotlib.use', (['"""TkAgg"""'], {}), "('TkAgg')\n", (443, 452), False, 'import matp... |
from unittest import TestCase
from bricklayer.doctor.metrics import Metrics
import os
class MetricsTest(TestCase):
def setUp(self):
self.metrics = Metrics()
filename = os.path.dirname(os.path.realpath(__file__)) + '/simple_module.py'
self.metrics.collect_metrics(filename)
def test_it_... | [
"os.path.realpath",
"bricklayer.doctor.metrics.Metrics"
] | [((161, 170), 'bricklayer.doctor.metrics.Metrics', 'Metrics', ([], {}), '()\n', (168, 170), False, 'from bricklayer.doctor.metrics import Metrics\n'), ((206, 232), 'os.path.realpath', 'os.path.realpath', (['__file__'], {}), '(__file__)\n', (222, 232), False, 'import os\n'), ((845, 871), 'os.path.realpath', 'os.path.rea... |
# coding=utf-8
# *** WARNING: this file was generated by the Pulumi SDK Generator. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from .. import _utilities
__a... | [
"pulumi.get",
"pulumi.getter",
"pulumi.set",
"pulumi.InvokeOptions",
"pulumi.runtime.invoke"
] | [((1297, 1327), 'pulumi.getter', 'pulumi.getter', ([], {'name': '"""authType"""'}), "(name='authType')\n", (1310, 1327), False, 'import pulumi\n'), ((743, 787), 'pulumi.set', 'pulumi.set', (['__self__', '"""auth_type"""', 'auth_type'], {}), "(__self__, 'auth_type', auth_type)\n", (753, 787), False, 'import pulumi\n'), ... |
import math
import numpy as np
import scipy.optimize as opt
import matplotlib.pyplot as plt
import matplotlib.gridspec as gdsc
class concreteSection:
def __init__(self,sct,units='mm'):
'''
Imports section.
Parameters
----------
sct : Section Object
... | [
"numpy.array",
"numpy.arange",
"numpy.where",
"matplotlib.pyplot.plot",
"numpy.asarray",
"numpy.linspace",
"numpy.concatenate",
"numpy.tile",
"numpy.geomspace",
"numpy.sign",
"numpy.interp",
"scipy.optimize.root",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.show",
"numpy.absolute",
... | [((3792, 3905), 'numpy.interp', 'np.interp', (['self.steelHeights', '[self.concreteHeights[0], self.concreteHeights[-1]]', '[bottomStrain, topStrain]'], {}), '(self.steelHeights, [self.concreteHeights[0], self.concreteHeights\n [-1]], [bottomStrain, topStrain])\n', (3801, 3905), True, 'import numpy as np\n'), ((3950... |
#------------------------------------------------------------------------------
# Copyright 2014 Esri
# 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/LICENS... | [
"arcpy.CopyFeatures_management",
"arcpy.UpdateCursor",
"arcpy.mapping.MapDocument",
"arcpy.AddMessage",
"arcpy.MakeFeatureLayer_management",
"arcpy.Describe",
"arcpy.RefreshActiveView",
"arcpy.Sort_management",
"arcpy.SelectLayerByAttribute_management",
"arcpy.mp.ArcGISProject",
"os.path.basenam... | [((1075, 1102), 'arcpy.GetParameterAsText', 'arcpy.GetParameterAsText', (['(0)'], {}), '(0)\n', (1099, 1102), False, 'import arcpy\n'), ((1119, 1146), 'arcpy.GetParameterAsText', 'arcpy.GetParameterAsText', (['(1)'], {}), '(1)\n', (1143, 1146), False, 'import arcpy\n'), ((1164, 1191), 'arcpy.GetParameterAsText', 'arcpy... |
from django.shortcuts import render
import sqlite3
conn = sqlite3.connect('test.db')
c = conn.cursor()
# c.execute("INSERT INTO test2 VALUES ('Hejo')")
# c.execute("SELECT * FROM test2")
# print(c.fetchone())
conn.commit()
conn.close()
def home(request):
conn = sqlite3.connect('test.db')
c = conn.curso... | [
"django.shortcuts.render",
"sqlite3.connect"
] | [((59, 85), 'sqlite3.connect', 'sqlite3.connect', (['"""test.db"""'], {}), "('test.db')\n", (74, 85), False, 'import sqlite3\n'), ((275, 301), 'sqlite3.connect', 'sqlite3.connect', (['"""test.db"""'], {}), "('test.db')\n", (290, 301), False, 'import sqlite3\n'), ((4249, 4288), 'django.shortcuts.render', 'render', (['re... |
from .target import Target
import src.resources as res
class Kiwi(Target):
def __init__(self, pos, screen, debug: bool = False):
kiwi = res.gfx('kiwi.png', convert=True)
Target.__init__(self, kiwi, pos, screen, debug)
w, _h = kiwi.get_size()
self.radius = int(w / 2.1)
sel... | [
"src.resources.gfx"
] | [((151, 184), 'src.resources.gfx', 'res.gfx', (['"""kiwi.png"""'], {'convert': '(True)'}), "('kiwi.png', convert=True)\n", (158, 184), True, 'import src.resources as res\n'), ((395, 428), 'src.resources.gfx', 'res.gfx', (['"""kiwi.png"""'], {'convert': '(True)'}), "('kiwi.png', convert=True)\n", (402, 428), True, 'impo... |
#Time Practice
import datetime
# Define the current date and print with different formats
CurDate = datetime.datetime.now()
print()
print("Current date based on the system date")
print("Note how it prints the date and time")
print(CurDate)
print()
print("Different formats when printing out a date")
print(CurDate.... | [
"datetime.datetime.strptime",
"datetime.datetime.now",
"datetime.timedelta"
] | [((105, 128), 'datetime.datetime.now', 'datetime.datetime.now', ([], {}), '()\n', (126, 128), False, 'import datetime\n'), ((951, 1001), 'datetime.datetime.strptime', 'datetime.datetime.strptime', (['arrivalstr', '"""%Y-%m-%d"""'], {}), "(arrivalstr, '%Y-%m-%d')\n", (977, 1001), False, 'import datetime\n'), ((1108, 116... |
from webu import (
Webu,
WebsocketProvider,
)
w3 = Webu(WebsocketProvider())
| [
"webu.WebsocketProvider"
] | [((65, 84), 'webu.WebsocketProvider', 'WebsocketProvider', ([], {}), '()\n', (82, 84), False, 'from webu import Webu, WebsocketProvider\n')] |
from io import StringIO
from .data_objects import UnknownFile
from .transit_data_object import TransitData
def clone_transit_data(transit_data):
"""
:rtype: TransitData
:type transit_data: TransitData
"""
new_transit_data = TransitData()
for service in transit_data.calendar:
new_tran... | [
"io.StringIO"
] | [((1352, 1362), 'io.StringIO', 'StringIO', ([], {}), '()\n', (1360, 1362), False, 'from io import StringIO\n'), ((3513, 3523), 'io.StringIO', 'StringIO', ([], {}), '()\n', (3521, 3523), False, 'from io import StringIO\n')] |
"""
Detection of trends: Given prices of X previous hours, will price increase or decrease Y% amount within next Z hours?
(1) X = previous prices
(2) y = next prices
(3) X_norm = X \ X[0] - 1 # Normalize X
(4) y_norm = y \ X[0] - 1 # Normalize y
(5) Given X_norm, which decision should we take if we know y_norm ?
(5.... | [
"torch.manual_seed",
"coinpy.PredictPriceDataset",
"torch.nn.L1Loss",
"matplotlib.pyplot.plot",
"torch.from_numpy",
"torch.no_grad",
"coinpy.DataFramesHolder",
"numpy.zeros",
"numpy.array",
"numpy.random.seed",
"torch.nn.Linear",
"torch.utils.data.DataLoader",
"matplotlib.pyplot.scatter",
... | [((1123, 1143), 'numpy.random.seed', 'np.random.seed', (['seed'], {}), '(seed)\n', (1137, 1143), True, 'import numpy as np\n'), ((1144, 1167), 'torch.manual_seed', 'torch.manual_seed', (['seed'], {}), '(seed)\n', (1161, 1167), False, 'import torch\n'), ((2059, 2081), 'matplotlib.pyplot.plot', 'plt.plot', (['d'], {'alph... |
# 导入python 自带库
# 导入自定义模块
from speech.baidu import Speech
from Mainwindow.Mainwindow import Ui_mainWindow
from PyQt5 import QtWidgets, QtGui
from PyQt5.QtCore import pyqtSlot
from PyQt5.QtWidgets import QFileDialog
import os
class BaiduSpeech(QtWidgets.QMainWindow, Ui_mainWindow):
def __init__(self):
sup... | [
"os.path.exists",
"PyQt5.QtGui.QIcon",
"os.makedirs",
"PyQt5.QtCore.pyqtSlot",
"os.getcwd",
"PyQt5.QtWidgets.QApplication",
"os.system",
"speech.baidu.Speech"
] | [((1132, 1142), 'PyQt5.QtCore.pyqtSlot', 'pyqtSlot', ([], {}), '()\n', (1140, 1142), False, 'from PyQt5.QtCore import pyqtSlot\n'), ((1295, 1305), 'PyQt5.QtCore.pyqtSlot', 'pyqtSlot', ([], {}), '()\n', (1303, 1305), False, 'from PyQt5.QtCore import pyqtSlot\n'), ((2195, 2227), 'PyQt5.QtWidgets.QApplication', 'QtWidgets... |
from abc import ABC, abstractmethod
from typing import Union
import pandas as pd
from sklearn.feature_selection import VarianceThreshold
from .abstract import ReducerAbstract
class LowVariance(ReducerAbstract):
reducer: VarianceThreshold
def transform(self,
df: pd.DataFrame,
... | [
"sklearn.feature_selection.VarianceThreshold"
] | [((597, 625), 'sklearn.feature_selection.VarianceThreshold', 'VarianceThreshold', (['threshold'], {}), '(threshold)\n', (614, 625), False, 'from sklearn.feature_selection import VarianceThreshold\n')] |
import os
import sys
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
from gunicornserver import GunicornServer
from flask_script import Manager, Server
from flask_migrate import MigrateCommand
from app import create_app
from drop_datasource import DropDatasource
from add_datasource imp... | [
"flask_script.Manager",
"os.environ.get",
"app.create_app",
"os.path.dirname",
"gunicornserver.GunicornServer",
"settings.get_config_decorator.GetConfig.configure",
"create_celery.make_celery"
] | [((487, 519), 'os.environ.get', 'os.environ.get', (['"""MAN_HOST_VALUE"""'], {}), "('MAN_HOST_VALUE')\n", (501, 519), False, 'import os\n'), ((534, 546), 'app.create_app', 'create_app', ([], {}), '()\n', (544, 546), False, 'from app import create_app\n'), ((561, 585), 'create_celery.make_celery', 'make_celery', (['appl... |
from django.conf.urls import url, include
from aomswork import views
from rest_framework.routers import DefaultRouter
router = DefaultRouter()
router.register(r'products', views.ProductViewSet)
router.register(r'colors', views.ColorViewSet)
router.register(r'productcolor', views.ProductColorViewSet)
router.register(r... | [
"django.conf.urls.include",
"rest_framework.routers.DefaultRouter"
] | [((129, 144), 'rest_framework.routers.DefaultRouter', 'DefaultRouter', ([], {}), '()\n', (142, 144), False, 'from rest_framework.routers import DefaultRouter\n'), ((381, 401), 'django.conf.urls.include', 'include', (['router.urls'], {}), '(router.urls)\n', (388, 401), False, 'from django.conf.urls import url, include\n... |
__author__ = 'allentran'
import json
import os
import re
import datetime
import unidecode
from spacy.en import English
import requests
import pandas as pd
import numpy as np
import allen_utils
logger = allen_utils.get_logger(__name__)
class Interval(object):
def __init__(self, start, end):
assert isin... | [
"spacy.en.English",
"re.compile",
"datetime.datetime.strptime",
"os.path.join",
"requests.get",
"allen_utils.get_logger",
"datetime.date",
"datetime.timedelta",
"os.walk"
] | [((205, 237), 'allen_utils.get_logger', 'allen_utils.get_logger', (['__name__'], {}), '(__name__)\n', (227, 237), False, 'import allen_utils\n'), ((621, 646), 'datetime.date', 'datetime.date', (['(1951)', '(4)', '(2)'], {}), '(1951, 4, 2)\n', (634, 646), False, 'import datetime\n'), ((648, 674), 'datetime.date', 'datet... |
# encoding: utf-8
"""GroupShape and related objects."""
from __future__ import absolute_import, division, print_function, unicode_literals
from fitness.private.pptx.dml.effect import ShadowFormat
from fitness.private.pptx.enum.shapes import MSO_SHAPE_TYPE
from fitness.private.pptx.shapes.base import BaseShap... | [
"fitness.private.pptx.shapes.shapetree.GroupShapes",
"fitness.private.pptx.dml.effect.ShadowFormat"
] | [((1368, 1403), 'fitness.private.pptx.dml.effect.ShadowFormat', 'ShadowFormat', (['self._element.grpSpPr'], {}), '(self._element.grpSpPr)\n', (1380, 1403), False, 'from fitness.private.pptx.dml.effect import ShadowFormat\n'), ((1966, 1998), 'fitness.private.pptx.shapes.shapetree.GroupShapes', 'GroupShapes', (['self._el... |
import cvlog as log
import cv2
import numpy as np
from .utils import read_file, remove_dirs, get_html
def test_log_image():
remove_dirs('log/')
img = cv2.imread("tests/data/orange.png")
log.set_mode(log.Mode.LOG)
log.image(log.Level.ERROR, img)
logitem = get_html('log/cvlog.html').select('.log-list... | [
"cv2.threshold",
"cv2.medianBlur",
"cvlog.hough_circles",
"cvlog.threshold",
"cvlog.hough_lines",
"numpy.array",
"cvlog.image",
"cv2.HoughLines",
"cv2.ORB_create",
"cv2.cvtColor",
"cvlog.keypoints",
"cv2.findContours",
"cvlog.set_mode",
"cv2.Canny",
"cv2.imread",
"cvlog.contours",
"c... | [((159, 194), 'cv2.imread', 'cv2.imread', (['"""tests/data/orange.png"""'], {}), "('tests/data/orange.png')\n", (169, 194), False, 'import cv2\n'), ((199, 225), 'cvlog.set_mode', 'log.set_mode', (['log.Mode.LOG'], {}), '(log.Mode.LOG)\n', (211, 225), True, 'import cvlog as log\n'), ((230, 261), 'cvlog.image', 'log.imag... |
import os
import yaml
import pickle
import glob
import torch
import numpy as np
from torch.autograd import Variable
from torchvision.utils import save_image
Tensor = torch.cuda.FloatTensor if torch.cuda.is_available() else torch.FloatTensor
def weights_init_normal(m):
classname = m.__class__.__name__
if cla... | [
"os.path.exists",
"os.makedirs",
"torch.nn.init.constant_",
"yaml.load",
"os.path.isfile",
"os.path.dirname",
"torch.cat",
"torch.cuda.is_available",
"torch.nn.init.normal_",
"torchvision.utils.save_image",
"glob.glob"
] | [((193, 218), 'torch.cuda.is_available', 'torch.cuda.is_available', ([], {}), '()\n', (216, 218), False, 'import torch\n'), ((739, 765), 'os.path.dirname', 'os.path.dirname', (['file_path'], {}), '(file_path)\n', (754, 765), False, 'import os\n'), ((1058, 1112), 'torch.cat', 'torch.cat', (['(real_A.data, fake_B.data, r... |
import cPickle
CLASSES = ['__background__', # always index 0
'tibetan flag', 'guns','knives','not terror','islamic flag','isis flag']
cache_file = 'qiniuV5_test_detections.pkl'
thresh_old = 0.9
with open('qiniuv5.txt') as fid:
filenamelist = fid.readlines()
fout = open('res.txt','w')
with open(cac... | [
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.ylabel",
"matplotlib.use",
"sklearn.metrics.average_precision_score",
"matplotlib.pyplot.xlabel",
"sklearn.metrics.precision_recall_curve",
"matplotlib.pyplot.fill_between",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.xlim",
"cPickle.load",
"matpl... | [((1334, 1374), 'sklearn.metrics.precision_recall_curve', 'precision_recall_curve', (['y_true', 'y_scores'], {}), '(y_true, y_scores)\n', (1356, 1374), False, 'from sklearn.metrics import precision_recall_curve\n'), ((1393, 1414), 'matplotlib.use', 'matplotlib.use', (['"""Agg"""'], {}), "('Agg')\n", (1407, 1414), False... |
from __future__ import absolute_import, division, print_function
from abc import abstractmethod as abstract_method
import attr
from boltun.engine.grammar.nodes import Node as BaseNode, \
NodeFilter as BaseFilter
from boltun.engine.template.context import FilterContext
@attr.s
class Node(BaseNode):
start = ... | [
"boltun.engine.template.context.FilterContext",
"attr.ib"
] | [((320, 363), 'attr.ib', 'attr.ib', ([], {'type': 'int', 'default': 'None', 'init': '(False)'}), '(type=int, default=None, init=False)\n', (327, 363), False, 'import attr\n'), ((375, 418), 'attr.ib', 'attr.ib', ([], {'type': 'int', 'default': 'None', 'init': '(False)'}), '(type=int, default=None, init=False)\n', (382, ... |
from django.db import models
import datetime
# Create your models here.
class Produit(models.Model):
nom_bouteille = models.CharField(max_length=40, default='')
description_bouteille = models.CharField(max_length=500, default='')
millésime = models.IntegerField(default=datetime.date.today().year)
sais... | [
"django.db.models.FloatField",
"django.db.models.DateField",
"django.db.models.ImageField",
"datetime.date.today",
"django.db.models.URLField",
"django.db.models.CharField"
] | [((123, 166), 'django.db.models.CharField', 'models.CharField', ([], {'max_length': '(40)', 'default': '""""""'}), "(max_length=40, default='')\n", (139, 166), False, 'from django.db import models\n'), ((195, 239), 'django.db.models.CharField', 'models.CharField', ([], {'max_length': '(500)', 'default': '""""""'}), "(m... |
import logging
import os
import psycopg2
from progress.bar import Bar
from bloat_my_db.utilities.file import FileUtility
from bloat_my_db.utilities import display_in_table
__author__ = "<NAME>"
__copyright__ = "<NAME>"
__license__ = "MIT"
_logger = logging.getLogger(__name__)
class PgSchemaAnalyzer:
def __init... | [
"logging.getLogger",
"psycopg2.connect",
"bloat_my_db.utilities.display_in_table",
"bloat_my_db.utilities.file.FileUtility.is_generated_file_exist",
"os.path.dirname",
"bloat_my_db.utilities.file.FileUtility.get_filename",
"bloat_my_db.utilities.file.FileUtility.read_file",
"bloat_my_db.utilities.file... | [((251, 278), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (268, 278), False, 'import logging\n'), ((375, 404), 'psycopg2.connect', 'psycopg2.connect', ([], {}), '(**conn_info)\n', (391, 404), False, 'import psycopg2\n'), ((2011, 2112), 'bloat_my_db.utilities.display_in_table', 'display... |
#!/usr/bin/python
import re
import sys
def rmd(nb):
path = (
f"C:\\Users\\jamang\\Documents\\GitHub\\jamangstangs.github.io\\_jupyter\\{nb}"
)
with open(path, "r") as file:
filedata = file.read()
filedata = re.sub('src="', 'src="/assets/images/', filedata)
with open(path, "w") as ... | [
"re.sub"
] | [((242, 291), 're.sub', 're.sub', (['"""src=\\""""', '"""src="/assets/images/"""', 'filedata'], {}), '(\'src="\', \'src="/assets/images/\', filedata)\n', (248, 291), False, 'import re\n'), ((668, 730), 're.sub', 're.sub', (['"""!\\\\[svg\\\\]\\\\("""', '"""<img src="/assets/images/"""', 'filedata'], {}), '(\'!\\\\[svg\... |
import asyncio
import functools
import logging
import app.db.base as base
import app.models as mdl
import databases
import fastapi_users as fastusr
import sqlalchemy as sqa
from app.main import DATABASE_URL, env
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
def async_adapter(wrapped_f... | [
"logging.basicConfig",
"logging.getLogger",
"databases.Database",
"sqlalchemy.create_engine",
"fastapi_users.db.SQLAlchemyUserDatabase",
"asyncio.new_event_loop",
"functools.wraps",
"app.main.env",
"app.db.base.Base.metadata.create_all"
] | [((214, 253), 'logging.basicConfig', 'logging.basicConfig', ([], {'level': 'logging.INFO'}), '(level=logging.INFO)\n', (233, 253), False, 'import logging\n'), ((263, 290), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (280, 290), False, 'import logging\n'), ((331, 360), 'functools.wraps'... |
#!/usr/bin/env python3
#
# Copyright 2017-2020 GridGain Systems.
#
# 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 applicab... | [
"tiden.runner.upload_artifacts",
"tiden.ansiblepool.AnsiblePool",
"time.strftime",
"optparse.OptionParser",
"tiden.runner.init_remote_hosts",
"os.getcwd",
"tiden.tidenrunner.TidenRunner",
"tiden.artifacts.prepare",
"tiden.localpool.LocalPool",
"os.cpu_count",
"tiden.tidenpluginmanager.PluginMana... | [((1355, 1412), 'optparse.OptionParser', 'OptionParser', ([], {'usage': 'SUPPRESS_USAGE', 'add_help_option': '(False)'}), '(usage=SUPPRESS_USAGE, add_help_option=False)\n', (1367, 1412), False, 'from optparse import OptionParser, SUPPRESS_USAGE\n'), ((11103, 11124), 'tiden.tidenpluginmanager.PluginManager', 'PluginMana... |
from timeit import default_timer as timer
import revkit
def lhrs(filename, configuration):
revkit.read_aiger(filename = filename)
synthesis = revkit.lhrs(**configuration).dict()
circuit = revkit.ps(circuit = True, silent = True).dict()
revkit.store(clear = True, aig = True, circuit = True)
retur... | [
"revkit.cbs",
"revkit.ps",
"timeit.default_timer",
"revkit.store",
"revkit.hdbs",
"revkit.lhrs",
"revkit.dxs",
"revkit.xmglut",
"revkit.read_aiger",
"revkit.convert"
] | [((97, 133), 'revkit.read_aiger', 'revkit.read_aiger', ([], {'filename': 'filename'}), '(filename=filename)\n', (114, 133), False, 'import revkit\n'), ((255, 303), 'revkit.store', 'revkit.store', ([], {'clear': '(True)', 'aig': '(True)', 'circuit': '(True)'}), '(clear=True, aig=True, circuit=True)\n', (267, 303), False... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
__version__ = "0.1.0"
import time
import logging
import sys
import subprocess
import os
from amrtime import utils
from amrtime import parsers
#from amrtime import database
from amrtime import model
# how do I make params that only evaluate once again?
RANDOM_STATE = 42
... | [
"amrtime.model.prepare_data",
"os.path.exists",
"amrtime.model.GeneFamilyLevelClassifier",
"amrtime.model.score",
"logging.StreamHandler",
"amrtime.model.generate_training_data",
"amrtime.model.SubGeneFamilyModel",
"amrtime.parsers.CARD",
"time.time",
"amrtime.utils.check_dependencies",
"amrtime... | [((1891, 1976), 'logging.info', 'logging.info', (['f"""Started AMRtime \'{run_name}\' outputting to {args.output_folder}"""'], {}), '(f"Started AMRtime \'{run_name}\' outputting to {args.output_folder}"\n )\n', (1903, 1976), False, 'import logging\n'), ((1976, 2002), 'amrtime.utils.check_dependencies', 'utils.check_... |
"""
Tests for salt.modules.boto3_route53
"""
import random
import string
import salt.loader
import salt.modules.boto3_route53 as boto3_route53
from salt.utils.versions import LooseVersion
from tests.support.mixins import LoaderModuleMockMixin
from tests.support.mock import MagicMock, patch
from tests.support.uni... | [
"salt.modules.boto3_route53.get_resource_records",
"salt.modules.boto3_route53.__init__",
"random.choice",
"tests.support.mock.patch",
"tests.support.mock.MagicMock",
"tests.support.mock.patch.object",
"salt.utils.versions.LooseVersion",
"tests.support.unit.skipIf"
] | [((1826, 1890), 'tests.support.unit.skipIf', 'skipIf', (['(HAS_BOTO3 is False)', '"""The boto module must be installed."""'], {}), "(HAS_BOTO3 is False, 'The boto module must be installed.')\n", (1832, 1890), False, 'from tests.support.unit import TestCase, skipIf\n'), ((824, 855), 'salt.utils.versions.LooseVersion', '... |
from bitcoin.core.serialize import Hash
import config
import re
from datetime import datetime
import logging
import pytz
from multiprocessing import Pool
from itertools import repeat
from chunker import Chunker
import write
class Parser:
def __init__(self, context, writer):
self._context = context
... | [
"chunker.Chunker.read",
"write.write_header_csv",
"datetime.datetime.strptime",
"re.match",
"multiprocessing.Pool",
"chunker.Chunker.chunkify",
"logging.info",
"itertools.repeat"
] | [((2220, 2272), 'datetime.datetime.strptime', 'datetime.strptime', (['date_time', 'config.log_time_format'], {}), '(date_time, config.log_time_format)\n', (2237, 2272), False, 'from datetime import datetime\n'), ((541, 569), 'multiprocessing.Pool', 'Pool', (['config.pool_processors'], {}), '(config.pool_processors)\n',... |
import hashlib
import math
import struct
import time
class CurryError(BaseException):
def __init__(self, error_message):
self.error_message = error_message
class SeedGenerator:
def __init__(self, validator):
self._validator = validator
self._seed_base = time.time() * 1000
sel... | [
"hashlib.sha256",
"struct.unpack",
"time.time",
"math.floor"
] | [((336, 363), 'math.floor', 'math.floor', (['self._seed_base'], {}), '(self._seed_base)\n', (346, 363), False, 'import math\n'), ((2531, 2547), 'hashlib.sha256', 'hashlib.sha256', ([], {}), '()\n', (2545, 2547), False, 'import hashlib\n'), ((290, 301), 'time.time', 'time.time', ([], {}), '()\n', (299, 301), False, 'imp... |
# DETECT HTML TAGS
# https://www.hackerrank.com/challenges/detect-html-tags/problem
# Some link to practice:
# https://hr-testcases-us-east-1.s3.amazonaws.com/722/input04.txt?AWSAccessKeyId=<KEY>&Expires=1612935160&Signature=Ikg943k%2FiTfoeKJn1Gt9I6SXnBQ%3D&response-content-type=text%2Fplain
import re
import sys
pa... | [
"re.findall"
] | [((432, 457), 're.findall', 're.findall', (['pattern', 'raw_'], {}), '(pattern, raw_)\n', (442, 457), False, 'import re\n')] |
# -*- coding: utf-8 -*-
# Generated by Django 1.9.8 on 2017-01-18 19:23
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('twitterfeed', '0001_initial'),
]
operations = [
migrations.RemoveField(
... | [
"django.db.migrations.RemoveField",
"django.db.models.BigIntegerField"
] | [((292, 349), 'django.db.migrations.RemoveField', 'migrations.RemoveField', ([], {'model_name': '"""tweet"""', 'name': '"""id_str"""'}), "(model_name='tweet', name='id_str')\n", (314, 349), False, 'from django.db import migrations, models\n'), ((496, 542), 'django.db.models.BigIntegerField', 'models.BigIntegerField', (... |
import tstcommon.commondata2d as cd
import torch
import torch.nn as nn
from utils import to_cpp
in_feat = 8
out_feat = 4
fc = nn.Linear(in_feat, out_feat, bias=False)
fc.weight.data = cd.weights
output = fc(cd.inp.reshape((3,8)))
fakeloss = torch.tensor([[0.13770211, 0.28582627, 0.86899745, 0.27578735],
[0... | [
"utils.to_cpp",
"tstcommon.commondata2d.inp.reshape",
"torch.tensor",
"torch.nn.Linear",
"tstcommon.commondata2d.inp.grad.zero_"
] | [((128, 168), 'torch.nn.Linear', 'nn.Linear', (['in_feat', 'out_feat'], {'bias': '(False)'}), '(in_feat, out_feat, bias=False)\n', (137, 168), True, 'import torch.nn as nn\n'), ((246, 437), 'torch.tensor', 'torch.tensor', (['[[0.13770211, 0.28582627, 0.86899745, 0.27578735], [0.04713255, 0.51820499,\n 0.27709258, 0.... |
import matplotlib as mpl
mpl.use('Qt5Agg')
import matplotlib.pyplot as plt
import pandas as pd
from math import log, exp, pi, sqrt, log10
import numpy as np
from matplotlib.ticker import MultipleLocator, FormatStrFormatter
from decimal import Decimal
import bisect
plt.rcParams.update({'font.size': 16})
# velocity: 0... | [
"pandas.read_csv",
"matplotlib.use",
"math.sqrt",
"matplotlib.pyplot.rcParams.update",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.show"
] | [((25, 42), 'matplotlib.use', 'mpl.use', (['"""Qt5Agg"""'], {}), "('Qt5Agg')\n", (32, 42), True, 'import matplotlib as mpl\n'), ((266, 304), 'matplotlib.pyplot.rcParams.update', 'plt.rcParams.update', (["{'font.size': 16}"], {}), "({'font.size': 16})\n", (285, 304), True, 'import matplotlib.pyplot as plt\n'), ((7941, 7... |
# -*- coding: utf-8 -*-
import scrapy
from scrapy.utils.response import get_base_url
from jobot.items import JobItem
from jobot.item_loaders import JobsCZItemLoader
class JobsczSpider(scrapy.Spider):
name = "JobsCZ"
allowed_domains = ["jobs.cz"]
start_urls = (
'http://www.jobs.cz/prace/brno/?q[]=p... | [
"scrapy.utils.response.get_base_url",
"jobot.items.JobItem",
"scrapy.Request"
] | [((918, 927), 'jobot.items.JobItem', 'JobItem', ([], {}), '()\n', (925, 927), False, 'from jobot.items import JobItem\n'), ((802, 842), 'scrapy.Request', 'scrapy.Request', (['url'], {'callback': 'self.parse'}), '(url, callback=self.parse)\n', (816, 842), False, 'import scrapy\n'), ((952, 974), 'scrapy.utils.response.ge... |
"""
@name: Modules/Web/web_server.py
@author: <NAME>
@contact: <EMAIL>
@copyright: 2012-2020 by <NAME>
@note: Created on Apr 3, 2012
@license: MIT License
@summary: This module provides the web server(s) service of PyHouse.
This is a Main Module - always present.
Open 2 web servers.
open server... | [
"klein.Klein",
"Modules.Core.logging_pyh.getLogger",
"Modules.Computer.Web.web_mainpage.MainPage",
"twisted.internet.endpoints.serverFromString",
"Modules.Core.Utilities.debug_tools.PrettyFormatAny.form"
] | [((1334, 1377), 'Modules.Core.logging_pyh.getLogger', 'Logger.getLogger', (['"""PyHouse.WebServer """'], {}), "('PyHouse.WebServer ')\n", (1350, 1377), True, 'from Modules.Core import logging_pyh as Logger\n'), ((1391, 1398), 'klein.Klein', 'Klein', ([], {}), '()\n', (1396, 1398), False, 'from klein import Kl... |
import signal
import sys
import threading
import pytest
from dask.datasets import timeseries
dd = pytest.importorskip("dask.dataframe")
pyspark = pytest.importorskip("pyspark")
pytest.importorskip("pyarrow")
pytest.importorskip("fastparquet")
from dask.dataframe.utils import assert_eq
if not sys.platform.startswit... | [
"signal.signal",
"threading.current_thread",
"signal.getsignal",
"dask.dataframe.utils.assert_eq",
"sys.platform.startswith",
"pytest.mark.parametrize",
"dask.datasets.timeseries",
"pytest.importorskip",
"threading.main_thread",
"pytest.fixture",
"pytest.skip"
] | [((101, 138), 'pytest.importorskip', 'pytest.importorskip', (['"""dask.dataframe"""'], {}), "('dask.dataframe')\n", (120, 138), False, 'import pytest\n'), ((149, 179), 'pytest.importorskip', 'pytest.importorskip', (['"""pyspark"""'], {}), "('pyspark')\n", (168, 179), False, 'import pytest\n'), ((180, 210), 'pytest.impo... |
import json
import requests
import speech_recognition as sr
YOUR_API_KEY = '<KEY>'
YOUR_AUDIO_FILE = 'output.mp3'
REGION = 'northeurope' # westus, eastasia, northeurope
MODE = 'interactive'
LANG = 'en-US'
FORMAT = 'simple'
def handler():
# 1. Get an Authorization Token
token = get_token()
# 2. Perform ... | [
"speech_recognition.Recognizer",
"speech_recognition.Microphone",
"json.loads",
"requests.post"
] | [((704, 739), 'requests.post', 'requests.post', (['url'], {'headers': 'headers'}), '(url, headers=headers)\n', (717, 739), False, 'import requests\n'), ((1474, 1495), 'json.loads', 'json.loads', (['r.content'], {}), '(r.content)\n', (1484, 1495), False, 'import json\n'), ((1541, 1556), 'speech_recognition.Recognizer', ... |
import pygame
from data.clip import clip
def load_tileset(path):
tileset_img = pygame.image.load(path + 'tileset.png').convert()
tileset_img.set_colorkey((0, 0, 0))
width = tileset_img.get_width()
tile_size = [16, 16]
tile_count = int((width + 1) / (tile_size[0] + 1))
images = [clip(tileset_img... | [
"pygame.image.load",
"data.clip.clip"
] | [((304, 376), 'data.clip.clip', 'clip', (['tileset_img', '(i * (tile_size[0] + 1))', '(0)', 'tile_size[0]', 'tile_size[1]'], {}), '(tileset_img, i * (tile_size[0] + 1), 0, tile_size[0], tile_size[1])\n', (308, 376), False, 'from data.clip import clip\n'), ((84, 123), 'pygame.image.load', 'pygame.image.load', (["(path +... |
import pygame
import random
class stobs:
def __init__(self, x, y):
self.x = x
self.y = y
self.wd = 50
self.ht = 50
self.plimg = pygame.image.load('./images/cone.jpeg')
self.plimg = pygame.transform.scale(
self.plimg, (self.wd, self.ht))
self.surf... | [
"pygame.display.set_caption",
"pygame.init",
"pygame.time.delay",
"pygame.event.get",
"pygame.Surface",
"pygame.display.set_mode",
"pygame.time.get_ticks",
"pygame.sprite.collide_rect",
"pygame.font.SysFont",
"pygame.display.quit",
"pygame.draw.rect",
"pygame.key.get_pressed",
"pygame.time.C... | [((3825, 3838), 'pygame.init', 'pygame.init', ([], {}), '()\n', (3836, 3838), False, 'import pygame\n'), ((3869, 3906), 'pygame.display.set_mode', 'pygame.display.set_mode', (['(winx, winy)'], {}), '((winx, winy))\n', (3892, 3906), False, 'import pygame\n'), ((3907, 3944), 'pygame.display.set_caption', 'pygame.display.... |
# Copyright 2022 <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 copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, so... | [
"thortils.ai2thor_version",
"setuptools.find_packages"
] | [((676, 691), 'setuptools.find_packages', 'find_packages', ([], {}), '()\n', (689, 691), False, 'from setuptools import setup, find_packages\n'), ((892, 918), 'thortils.ai2thor_version', 'thortils.ai2thor_version', ([], {}), '()\n', (916, 918), False, 'import thortils\n')] |