code stringlengths 22 1.05M | apis listlengths 1 3.31k | extract_api stringlengths 75 3.25M |
|---|---|---|
# simple script for img capture
# takes 1 arg: filename (.jpg)
import sys
from picamera import PiCamera
from time import sleep
# create instance
camera = PiCamera()
# Takes a string, ie. 'img.jpg'
def capture(filename):
# camera needs time to adjust brightness
# this is the shortest delay
sleep(0.15)... | [
"picamera.PiCamera",
"time.sleep"
] | [((155, 165), 'picamera.PiCamera', 'PiCamera', ([], {}), '()\n', (163, 165), False, 'from picamera import PiCamera\n'), ((309, 320), 'time.sleep', 'sleep', (['(0.15)'], {}), '(0.15)\n', (314, 320), False, 'from time import sleep\n')] |
from django.contrib.auth import get_user_model
from rest_framework import serializers
from knox.models import AuthToken
User = get_user_model()
username_field = User.USERNAME_FIELD if hasattr(User, 'USERNAME_FIELD') else 'username'
class UserSerializer(serializers.ModelSerializer):
class Meta:
model = Us... | [
"django.contrib.auth.get_user_model"
] | [((127, 143), 'django.contrib.auth.get_user_model', 'get_user_model', ([], {}), '()\n', (141, 143), False, 'from django.contrib.auth import get_user_model\n')] |
from tensorflow import keras
from pathlib import Path
import numpy as np
from training.image_adapter import ImageAdapter
import cv2
from training.model.model_creator import define_composite_model
class ModelSerializer:
model_names = ['d_model_A', "d_model_B", "g_model_AtoB", "g_model_BtoA"]
base_path = './tra... | [
"cv2.imwrite",
"numpy.hstack",
"training.image_adapter.ImageAdapter",
"pathlib.Path",
"tensorflow.keras.models.load_model",
"training.model.model_creator.define_composite_model"
] | [((1214, 1328), 'training.model.model_creator.define_composite_model', 'define_composite_model', (["models['g_model_AtoB']", "models['d_model_B']", "models['g_model_BtoA']", 'self.image_shape'], {}), "(models['g_model_AtoB'], models['d_model_B'], models[\n 'g_model_BtoA'], self.image_shape)\n", (1236, 1328), False, ... |
# coding: utf-8
"""
Cloudbreak API
Cloudbreak is a powerful left surf that breaks over a coral reef, a mile off southwest the island of Tavarua, Fiji. Cloudbreak is a cloud agnostic Hadoop as a Service API. Abstracts the provisioning and ease management and monitoring of on-demand clusters. SequenceIQ's Cloud... | [
"six.iteritems"
] | [((9179, 9208), 'six.iteritems', 'iteritems', (['self.swagger_types'], {}), '(self.swagger_types)\n', (9188, 9208), False, 'from six import iteritems\n')] |
import re
text = input()
pattern = r"(^|(?<=\s))-?\d+(\.\d+)?($|(?=\s))"
matched_text = [el.group() for el in re.finditer(pattern, text)]
print(*matched_text) | [
"re.finditer"
] | [((111, 137), 're.finditer', 're.finditer', (['pattern', 'text'], {}), '(pattern, text)\n', (122, 137), False, 'import re\n')] |
# -*- coding: utf-8 -*-
import struct
import hexdump
import uuid
import os
class RawStruct(object):
"""Helper class used as a parent class for most filesystem structures.
Args:
data (bytes): Byte array to initialize structure with.
filename (str): A file to read the data from.
offset... | [
"os.path.getsize",
"struct.unpack",
"hexdump.hexdump"
] | [((1270, 1295), 'os.path.getsize', 'os.path.getsize', (['filename'], {}), '(filename)\n', (1285, 1295), False, 'import os\n'), ((7434, 7461), 'hexdump.hexdump', 'hexdump.hexdump', (['self._data'], {}), '(self._data)\n', (7449, 7461), False, 'import hexdump\n'), ((3152, 3208), 'struct.unpack', 'struct.unpack', (['format... |
import os
train_percentage = 0.9
val_percentage = 0.1
rootPath = r'/home/jian/Documents/dataset/hand_detection/vocLabels'
totalFile = open(os.path.join(rootPath, 'totalLabels.txt'))
trainFile = open(os.path.join(rootPath, 'trainLabels.txt'), 'w+')
evalFile = open(os.path.join(rootPath, 'evalLabels.txt'), 'w+')
index ... | [
"os.path.join"
] | [((140, 181), 'os.path.join', 'os.path.join', (['rootPath', '"""totalLabels.txt"""'], {}), "(rootPath, 'totalLabels.txt')\n", (152, 181), False, 'import os\n'), ((200, 241), 'os.path.join', 'os.path.join', (['rootPath', '"""trainLabels.txt"""'], {}), "(rootPath, 'trainLabels.txt')\n", (212, 241), False, 'import os\n'),... |
"""
Description: Jobs Controller
"""
import logging
import ast
from datetime import datetime, date
from django.utils import timezone
from django.db.models import Q
from core.general import settings
from core.general.exceptions import SIDException
class JobController():
"""
Jobs Controller
"""
... | [
"logging.debug",
"datetime.datetime.today",
"logging.error",
"core.controller.logcontroller.LogController",
"core.connectors.email.SIDEmail",
"django.utils.timezone.now",
"core.connectors.file.mapper.Mapper",
"core.models.coreproxy.JobsProxy.objects.filter",
"core.connectors.awss3.reader.Reader",
... | [((1220, 1260), 'core.services.sidsettings.SidSettingsService', 'SidSettingsService', ([], {'user_id': 'self.user_id'}), '(user_id=self.user_id)\n', (1238, 1260), False, 'from core.services.sidsettings import SidSettingsService\n'), ((1602, 1639), 'core.controller.cachecontroller.CacheController', 'CacheController', ([... |
from app import __metadata__ as meta
from configparser import ConfigParser, ExtendedInterpolation
from pathlib import Path
from shutil import copy
import os
import io
import logging
log = logging.getLogger(__name__)
APP = meta.APP_NAME
'''
This component is responsible for configuration management.
If this is the fir... | [
"logging.getLogger",
"configparser.ConfigParser",
"pathlib.Path",
"pathlib.Path.home",
"os.environ.get",
"os.environ.items",
"os.path.dirname",
"io.StringIO",
"configparser.ExtendedInterpolation"
] | [((188, 215), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (205, 215), False, 'import logging\n'), ((746, 760), 'configparser.ConfigParser', 'ConfigParser', ([], {}), '()\n', (758, 760), False, 'from configparser import ConfigParser, ExtendedInterpolation\n'), ((1502, 1527), 'os.path.di... |
"""
_speech_transcriber.py
Copyright 1999-present Alibaba Group Holding 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 applicab... | [
"json.loads",
"json.dumps",
"uuid.uuid4",
"nls._core.NlsCore",
"threading.Condition"
] | [((4691, 4712), 'threading.Condition', 'threading.Condition', ([], {}), '()\n', (4710, 4712), False, 'import threading\n'), ((9357, 9611), 'nls._core.NlsCore', 'NlsCore', ([], {'url': 'self.__url', 'akid': 'self.__akid', 'aksecret': 'self.__aksecret', 'token': 'self.__token', 'on_open': 'self.__tr_core_on_open', 'on_me... |
# implementing RNN and LSTM
# %%
import pandas as pd
import numpy as np
import nltk
import sklearn
import matplotlib.pyplot as plt
import re
import tqdm
twitter_df = pd.read_csv('twitter_train.csv')
twitter_df = twitter_df.fillna('0')
twitter_df_test = pd.read_csv('twitter_test.csv')
twitter_df_test = twitter_df_tes... | [
"pandas.read_csv",
"tensorflow.keras.preprocessing.sequence.pad_sequences",
"re.compile",
"matplotlib.pyplot.ylabel",
"tensorflow.keras.callbacks.EarlyStopping",
"tensorflow.keras.layers.Dense",
"gensim.models.word2vec.Word2Vec",
"nltk.TweetTokenizer",
"nltk.corpus.stopwords.words",
"tensorflow.ke... | [((168, 200), 'pandas.read_csv', 'pd.read_csv', (['"""twitter_train.csv"""'], {}), "('twitter_train.csv')\n", (179, 200), True, 'import pandas as pd\n'), ((256, 287), 'pandas.read_csv', 'pd.read_csv', (['"""twitter_test.csv"""'], {}), "('twitter_test.csv')\n", (267, 287), True, 'import pandas as pd\n'), ((1030, 1049), ... |
import numpy as np
import pandas as pd
from itertools import islice
import multiprocessing
from multiprocessing.pool import ThreadPool, Pool
N_CPUS = multiprocessing.cpu_count()
def batch_generator(iterable, n=1):
if hasattr(iterable, '__len__'):
# https://stackoverflow.com/questions/8290397/how-to-split... | [
"itertools.islice",
"multiprocessing.cpu_count",
"numpy.array_split",
"numpy.concatenate",
"pandas.concat"
] | [((151, 178), 'multiprocessing.cpu_count', 'multiprocessing.cpu_count', ([], {}), '()\n', (176, 178), False, 'import multiprocessing\n'), ((1786, 1818), 'numpy.array_split', 'np.array_split', (['df', 'n_partitions'], {}), '(df, n_partitions)\n', (1800, 1818), True, 'import numpy as np\n'), ((1927, 1953), 'pandas.concat... |
from __future__ import absolute_import, print_function, division
import warnings
import numpy as np
import astropy.units as u
__all__ = ["_get_x_in_wavenumbers", "_test_valid_x_range"]
def _get_x_in_wavenumbers(in_x):
"""
Convert input x to wavenumber given x has units.
Otherwise, assume x is in wavene... | [
"numpy.any",
"astropy.units.spectral",
"warnings.warn",
"astropy.units.Quantity",
"numpy.atleast_1d"
] | [((606, 625), 'numpy.atleast_1d', 'np.atleast_1d', (['in_x'], {}), '(in_x)\n', (619, 625), True, 'import numpy as np\n'), ((743, 829), 'warnings.warn', 'warnings.warn', (['"""x has no units, assuming x units are inverse microns"""', 'UserWarning'], {}), "('x has no units, assuming x units are inverse microns',\n Use... |
import argparse
import os
import platform
import subprocess
import helpers.device_serial_id as device_id
from helpers.custom_ci import custom_input, custom_print
# Detect OS
is_windows = False
is_linux = False
if platform.system() == 'Windows':
is_windows = True
if platform.system() == 'Linux':
is_linux = Tru... | [
"subprocess.getoutput",
"helpers.device_serial_id.init",
"argparse.ArgumentParser",
"helpers.custom_ci.custom_print",
"datetime.datetime.now",
"helpers.custom_ci.custom_input",
"platform.system",
"os.path.basename",
"os.system"
] | [((215, 232), 'platform.system', 'platform.system', ([], {}), '()\n', (230, 232), False, 'import platform\n'), ((272, 289), 'platform.system', 'platform.system', ([], {}), '()\n', (287, 289), False, 'import platform\n'), ((343, 413), 'helpers.custom_ci.custom_print', 'custom_print', (['""">>> I am in restore_whatsapp.k... |
#!/usr/bin/env python
import rospy
from flexbe_core import EventState, Logger
class DaguInitialState(EventState):
'''
Etat initial du Dagu.
Il avance.
-- detectedID int id de l'élément détecté.
># detectedIDInput int id de l'élément détecté.
#> linkedState int... | [
"flexbe_core.Logger.loginfo"
] | [((1126, 1151), 'flexbe_core.Logger.loginfo', 'Logger.loginfo', (['"""DEFAULT"""'], {}), "('DEFAULT')\n", (1140, 1151), False, 'from flexbe_core import EventState, Logger\n'), ((1229, 1251), 'flexbe_core.Logger.loginfo', 'Logger.loginfo', (['"""STOP"""'], {}), "('STOP')\n", (1243, 1251), False, 'from flexbe_core import... |
from pathlib import Path
from unittest import TestCase
from unittest.mock import patch, Mock
from requests.exceptions import HTTPError
from requests import Session
from test.test_account import TestAccount
from gphotos.LocalData import LocalData
import test.test_setup as ts
photos_root = Path("photos")
original_get =... | [
"test.test_setup.SetupDbAndCredentials",
"unittest.mock.Mock",
"pathlib.Path",
"gphotos.LocalData.LocalData",
"unittest.mock.patch.object"
] | [((291, 305), 'pathlib.Path', 'Path', (['"""photos"""'], {}), "('photos')\n", (295, 305), False, 'from pathlib import Path\n'), ((718, 759), 'unittest.mock.patch.object', 'patch.object', (['Session', '"""get"""', 'patched_get'], {}), "(Session, 'get', patched_get)\n", (730, 759), False, 'from unittest.mock import patch... |
#! /usr/bin/python
"""
Provides the Gen class, along with functions for iterating over output
linearizations given a particular tree input.
"""
from itertools import permutations
def gen_strings(tree, null_phon = {}, spaces = False):
null_phon = {t.lower() for t in null_phon}
terminals = {t.label[0].lower() f... | [
"itertools.permutations"
] | [((415, 438), 'itertools.permutations', 'permutations', (['terminals'], {}), '(terminals)\n', (427, 438), False, 'from itertools import permutations\n')] |
# -*- coding: utf-8 -*-
#
# Dell EMC OpenManage Ansible Modules
# Version 2.1.3
# Copyright (C) 2019-2020 Dell Inc. or its subsidiaries. All Rights Reserved.
# GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt)
#
from __future__ import (absolute_import, division, print_functio... | [
"pytest.mark.parametrize",
"io.StringIO",
"json.dumps",
"pytest.raises"
] | [((1460, 1510), 'pytest.mark.parametrize', 'pytest.mark.parametrize', (['"""sub_param"""', '[sub_param1]'], {}), "('sub_param', [sub_param1])\n", (1483, 1510), False, 'import pytest\n'), ((2723, 2817), 'pytest.mark.parametrize', 'pytest.mark.parametrize', (['"""sub_param"""', "[{'in': in1, 'out': out1}, {'in': in2, 'ou... |
# coding=utf-8
# Filename: h5tree.py
"""
Print the HDF5 file structure.
Usage:
h5tree FILE
h5tree (-h | --help)
h5tree --version
Options:
FILE Input file.
-h --help Show this screen.
"""
from __future__ import division, absolute_import, print_function
import tables
from km3pipe.tools imp... | [
"km3pipe.tools.deprecated",
"tables.open_file",
"docopt.docopt"
] | [((602, 617), 'km3pipe.tools.deprecated', 'deprecated', (['MSG'], {}), '(MSG)\n', (612, 617), False, 'from km3pipe.tools import deprecated\n'), ((800, 815), 'docopt.docopt', 'docopt', (['__doc__'], {}), '(__doc__)\n', (806, 815), False, 'from docopt import docopt\n'), ((647, 671), 'tables.open_file', 'tables.open_file'... |
"""
Specific Models
===============
"""
##########################################
# Introduction
# ^^^^^^^^^^^^
# From the algorithm preseneted in “`ABESS algorithm: details <https://abess.readthedocs.io/en/latest/auto_gallery/1-glm/plot_a2_abess_algorithm_details.html>`__”,
# one of the bottleneck in algorithm is th... | [
"abess.linear.LogisticRegression",
"abess.datasets.make_glm_data",
"numpy.random.seed",
"numpy.nonzero",
"abess.linear.LinearRegression",
"time.time"
] | [((2194, 2211), 'numpy.random.seed', 'np.random.seed', (['(1)'], {}), '(1)\n', (2208, 2211), True, 'import numpy as np\n'), ((2219, 2273), 'abess.datasets.make_glm_data', 'make_glm_data', ([], {'n': '(10000)', 'p': '(100)', 'k': '(10)', 'family': '"""gaussian"""'}), "(n=10000, p=100, k=10, family='gaussian')\n", (2232,... |
from django.conf import settings
from django.contrib.auth import get_user_model
from django.db import models
from django.urls import reverse
import django.utils.timezone as timezone
from mptt.models import MPTTModel, TreeForeignKey
from users.models import CustomUser
class Bubble(models.Model):
id = models.AutoFi... | [
"django.contrib.auth.get_user_model",
"django.db.models.TextField",
"django.db.models.ForeignKey",
"mptt.models.TreeForeignKey",
"django.db.models.AutoField",
"django.db.models.SmallIntegerField",
"django.urls.reverse",
"django.db.models.DateTimeField",
"django.db.models.CharField"
] | [((307, 341), 'django.db.models.AutoField', 'models.AutoField', ([], {'primary_key': '(True)'}), '(primary_key=True)\n', (323, 341), False, 'from django.db import models\n'), ((354, 386), 'django.db.models.CharField', 'models.CharField', ([], {'max_length': '(255)'}), '(max_length=255)\n', (370, 386), False, 'from djan... |
#!usr/bin/python
# -*- coding:utf8 -*-
# 合并pdf
import os
from PyPDF2 import PdfFileReader, PdfFileWriter
work_path = 'C:/Users/Clarence/Desktop/PythonPractice/utils/pdf/mergepdf/'
# 合并同一文件夹下的pdf文件
flst = [] # 获得pdf文件路径
for root, dirs, files in os.walk(work_path):
flst = files
flst = [work_path + f for f in flst... | [
"PyPDF2.PdfFileWriter",
"os.walk"
] | [((248, 266), 'os.walk', 'os.walk', (['work_path'], {}), '(work_path)\n', (255, 266), False, 'import os\n'), ((332, 347), 'PyPDF2.PdfFileWriter', 'PdfFileWriter', ([], {}), '()\n', (345, 347), False, 'from PyPDF2 import PdfFileReader, PdfFileWriter\n'), ((746, 764), 'os.walk', 'os.walk', (['work_path'], {}), '(work_pat... |
"""
Chat views module
"""
import json
from django.shortcuts import render, redirect, HttpResponseRedirect, HttpResponse, get_object_or_404
from django.http import Http404
from django.utils.safestring import mark_safe
from django.core.files.base import ContentFile
from django.forms import modelformset_factory
from in... | [
"django.shortcuts.render",
"django.forms.modelformset_factory",
"django.shortcuts.HttpResponse",
"django.shortcuts.get_object_or_404",
"json.dumps",
"index.forms.CropAvatarForm",
"django.shortcuts.redirect",
"django.http.Http404"
] | [((2587, 2596), 'django.http.Http404', 'Http404', ([], {}), '()\n', (2594, 2596), False, 'from django.http import Http404\n'), ((3069, 3078), 'django.http.Http404', 'Http404', ([], {}), '()\n', (3076, 3078), False, 'from django.http import Http404\n'), ((3624, 3633), 'django.http.Http404', 'Http404', ([], {}), '()\n', ... |
#!/usr/bin/env python2
#***************************************************************************
#
# Copyright (c) 2015 PX4 Development Team. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
#... | [
"mavros_test_common_uav0.MavrosTestCommon",
"rospy.init_node",
"gazebo_msgs.msg.ModelStates",
"numpy.array",
"rospy.Rate",
"numpy.linalg.norm",
"subprocess.Popen",
"geometry_msgs.msg.Quaternion",
"os.system",
"rospy.Subscriber",
"mavros_test_common_uav1.MavrosTestCommon",
"math.radians",
"ro... | [((13152, 13196), 'rospy.init_node', 'rospy.init_node', (['"""test_node"""'], {'anonymous': '(True)'}), "('test_node', anonymous=True)\n", (13167, 13196), False, 'import rospy\n'), ((2850, 2863), 'geometry_msgs.msg.PoseStamped', 'PoseStamped', ([], {}), '()\n', (2861, 2863), False, 'from geometry_msgs.msg import PoseSt... |
# Copyright 2020 <NAME>, University of Pittsburgh
#
# 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 a... | [
"tensorflow.unstack",
"numpy.minimum",
"numpy.squeeze",
"numpy.stack",
"numpy.split",
"tensorflow.maximum",
"numpy.maximum",
"tensorflow.minimum",
"tensorflow.stack"
] | [((1133, 1157), 'tensorflow.unstack', 'tf.unstack', (['box'], {'axis': '(-1)'}), '(box, axis=-1)\n', (1143, 1157), True, 'import tensorflow as tf\n'), ((1167, 1222), 'tensorflow.stack', 'tf.stack', (['[ymin, 1.0 - xmax, ymax, 1.0 - xmin]'], {'axis': '(-1)'}), '([ymin, 1.0 - xmax, ymax, 1.0 - xmin], axis=-1)\n', (1175, ... |
import numpy as np
import matplotlib.pyplot as plt
import tensorflow as tf
import c3.experiment
import c3.optimizers.c1
import c3.libraries.fidelities as fid
import os
from c3.optimizers.c1 import C1
import c3.libraries.algorithms as algorithms
import c3.libraries.fidelities as fidelities
import examples.single_qubit_b... | [
"os.path.join",
"c3.optimizers.c1.C1",
"numpy.append",
"numpy.linspace",
"c3.libraries.fidelities.unitary_infid",
"numpy.cos",
"numpy.sin",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.legend"
] | [((1389, 1407), 'matplotlib.pyplot.subplots', 'plt.subplots', (['(1)', '(1)'], {}), '(1, 1)\n', (1401, 1407), True, 'import matplotlib.pyplot as plt\n'), ((1468, 1521), 'numpy.linspace', 'np.linspace', (['(0.0)', '(dt * pop_t.shape[1])', 'pop_t.shape[1]'], {}), '(0.0, dt * pop_t.shape[1], pop_t.shape[1])\n', (1479, 152... |
# -*- coding: UTF-8 -*-
import os, sys
try:
import ConfigParser
except ImportError:
import configparser as ConfigParser
import filecmp
import random
import shutil
import tempfile
import time
import unittest
try:
from StringIO import StringIO
except ImportError:
from io import StringIO
import win32com.c... | [
"active_directory.Path",
"random.choice",
"win32net.NetGetDCName",
"configparser.ConfigParser",
"active_directory.find_computer",
"active_directory.search_ex",
"active_directory.find_user",
"active_directory.AD",
"active_directory.search",
"active_directory.find",
"unittest.main",
"active_dire... | [((374, 401), 'configparser.ConfigParser', 'ConfigParser.ConfigParser', ([], {}), '()\n', (399, 401), True, 'import configparser as ConfigParser\n'), ((8216, 8231), 'unittest.main', 'unittest.main', ([], {}), '()\n', (8229, 8231), False, 'import unittest\n'), ((1768, 1805), 'active_directory.AD_object', 'active_directo... |
from tkinter import *
from PIL import Image, ImageTk
window = Tk()
window.maxsize(800,550)
#window.minsize(750,500)
mpage = Canvas(window,width=780,height=300, )
mpage.grid(columnspan=3)
# logo
logo = Image.open('kuku_logo.png')
logo = logo.resize((300,250))
logo = ImageTk.PhotoImage(logo)
logo_label = L... | [
"PIL.Image.open",
"PIL.ImageTk.PhotoImage"
] | [((213, 240), 'PIL.Image.open', 'Image.open', (['"""kuku_logo.png"""'], {}), "('kuku_logo.png')\n", (223, 240), False, 'from PIL import Image, ImageTk\n'), ((280, 304), 'PIL.ImageTk.PhotoImage', 'ImageTk.PhotoImage', (['logo'], {}), '(logo)\n', (298, 304), False, 'from PIL import Image, ImageTk\n')] |
from duckql.functions.string_agg import StringAgg
from duckql.properties.property import Property
from duckql.structures.cast_operator import CastOperator
def test_simple():
my_function = StringAgg(
property=Property(name='transactions.amount'),
separator=', ',
alias='amounts'
)
a... | [
"duckql.properties.property.Property"
] | [((222, 258), 'duckql.properties.property.Property', 'Property', ([], {'name': '"""transactions.amount"""'}), "(name='transactions.amount')\n", (230, 258), False, 'from duckql.properties.property import Property\n'), ((501, 537), 'duckql.properties.property.Property', 'Property', ([], {'name': '"""transactions.amount""... |
# -*- coding: utf-8 -*-
"""
Created on Sun Jul 26 00:32:31 2020
@author: <NAME>
based on code by <NAME>
"""
import numpy as np
from sklearn.cross_decomposition import PLSRegression
# OSC
# nicomp is the number of internal components, ncomp is the number of
# components to remove (ncomp=1 recommended)
class OSC:
... | [
"numpy.identity",
"numpy.mean",
"numpy.sum",
"numpy.zeros",
"numpy.linalg.norm",
"numpy.linalg.svd",
"sklearn.cross_decomposition.PLSRegression"
] | [((1299, 1333), 'numpy.zeros', 'np.zeros', (['(X.shape[1], self.ncomp)'], {}), '((X.shape[1], self.ncomp))\n', (1307, 1333), True, 'import numpy as np\n'), ((1349, 1383), 'numpy.zeros', 'np.zeros', (['(X.shape[1], self.ncomp)'], {}), '((X.shape[1], self.ncomp))\n', (1357, 1383), True, 'import numpy as np\n'), ((1447, 1... |
# 5
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers
from keras.layers import Dropout
import numpy as np
# sinusoidal position encoding
def get_3d_sincos_pos_embed(embed_dim, grid_size, cls_token=False):
grid_h = np.arange(grid_size)
grid_w = np.arange(grid_size)
gri... | [
"tensorflow.keras.layers.Conv3D",
"tensorflow.meshgrid",
"tensorflow.transpose",
"tensorflow.keras.layers.GlobalAvgPool1D",
"tensorflow.keras.layers.Dense",
"numpy.einsum",
"numpy.sin",
"tensorflow.cast",
"numpy.arange",
"numpy.reshape",
"tensorflow.keras.layers.MultiHeadAttention",
"numpy.con... | [((258, 278), 'numpy.arange', 'np.arange', (['grid_size'], {}), '(grid_size)\n', (267, 278), True, 'import numpy as np\n'), ((292, 312), 'numpy.arange', 'np.arange', (['grid_size'], {}), '(grid_size)\n', (301, 312), True, 'import numpy as np\n'), ((326, 346), 'numpy.arange', 'np.arange', (['grid_size'], {}), '(grid_siz... |
# -*- coding: utf-8 -*-
"""
Created on Mon Jan 3 10:45:39 2022
@author: dgbli
"""
import numpy as np
import matplotlib.pyplot as plt
def return_true(n):
x = []
for i in range(n):
if i%2==0:
x.append(i)
x.append(i+1)
else:
x.append(None)
... | [
"numpy.random.rand",
"matplotlib.pyplot.subplots"
] | [((914, 928), 'matplotlib.pyplot.subplots', 'plt.subplots', ([], {}), '()\n', (926, 928), True, 'import matplotlib.pyplot as plt\n'), ((2072, 2090), 'numpy.random.rand', 'np.random.rand', (['(25)'], {}), '(25)\n', (2086, 2090), True, 'import numpy as np\n'), ((2106, 2124), 'numpy.random.rand', 'np.random.rand', (['(25)... |
from secml.optim.optimizers.tests import COptimizerTestCases
from secml.array import CArray
from secml.optim.optimizers import COptimizerPGDLS
from secml.optim.constraints import CConstraintBox, CConstraintL1
class TestCOptimizerPGDLSDiscrete(COptimizerTestCases):
"""Unittests for COptimizerPGDLS in discrete spa... | [
"secml.optim.optimizers.tests.COptimizerTestCases.main",
"secml.optim.constraints.CConstraintBox",
"secml.optim.constraints.CConstraintL1",
"secml.array.CArray"
] | [((7426, 7452), 'secml.optim.optimizers.tests.COptimizerTestCases.main', 'COptimizerTestCases.main', ([], {}), '()\n', (7450, 7452), False, 'from secml.optim.optimizers.tests import COptimizerTestCases\n'), ((726, 753), 'secml.optim.constraints.CConstraintBox', 'CConstraintBox', ([], {'lb': '(-1)', 'ub': '(1)'}), '(lb=... |
from rethinkdb import r
from rethinkdb.errors import RqlRuntimeError
from tests.common import as_db_and_table
from tests.common import assertEqual
from tests.common import assertEqUnordered
from tests.functional.common import MockTest
from rethinkdb_mock import util
class TestGet(MockTest):
@staticmethod
def... | [
"rethinkdb_mock.util.cat",
"rethinkdb.r.json",
"tests.common.as_db_and_table",
"rethinkdb.r.db",
"rethinkdb.r.row.merge",
"tests.common.assertEqUnordered",
"tests.common.assertEqual",
"rethinkdb.r.error"
] | [((464, 500), 'tests.common.as_db_and_table', 'as_db_and_table', (['"""x"""', '"""people"""', 'data'], {}), "('x', 'people', data)\n", (479, 500), False, 'from tests.common import as_db_and_table\n'), ((617, 669), 'tests.common.assertEqual', 'assertEqual', (["{'id': 'bob-id', 'name': 'bob'}", 'result'], {}), "({'id': '... |
import numpy as np
from skimage import feature
from sklearn import preprocessing
class LBP:
def __init__(self, p, r):
self.p = p
self.r = r
def getVecLength(self):
return 2**self.p
def getFeature(self, imgMat):
feat = feature.local_binary_pattern(
... | [
"numpy.append",
"numpy.array",
"sklearn.preprocessing.normalize",
"skimage.feature.hog",
"numpy.load",
"numpy.float32",
"numpy.save",
"skimage.feature.local_binary_pattern"
] | [((2895, 2930), 'numpy.append', 'np.append', (['featHog', 'featLbp'], {'axis': '(1)'}), '(featHog, featLbp, axis=1)\n', (2904, 2930), True, 'import numpy as np\n'), ((280, 350), 'skimage.feature.local_binary_pattern', 'feature.local_binary_pattern', (['imgMat', 'self.p', 'self.r'], {'method': '"""uniform"""'}), "(imgMa... |
#-*- coding: utf-8 -*-
# <EMAIL>
r"""针对TubeLink做一些仿真验证。
"""
gl_bcnDuration = 8000 # 信标周期的长度
gl_packedAckDelay = 2 # 延迟查收ack的信标周期间隔数量
gl_evtCollisionDelay = 3 # 冲突之后的上行事件消息在 [1, gl_evtCollisionDelay] 个信标周期后再次发送
gl_emergCollisionDelay = 2
gl_totalSlots = 128 # 一个信标周期里所有的时间槽数量
gl_slotDuration = gl... | [
"simple_logger.get_logger",
"random.randint"
] | [((1207, 1219), 'simple_logger.get_logger', 'get_logger', ([], {}), '()\n', (1217, 1219), False, 'from simple_logger import get_logger\n'), ((6423, 6450), 'random.randint', 'randint', (['(0)', 'gl_nodeInitSpan'], {}), '(0, gl_nodeInitSpan)\n', (6430, 6450), False, 'from random import randint\n'), ((9558, 9585), 'random... |
import sys
import os
from platform import python_version
# https://github.com/willmcgugan/rich
from rich.console import Console
from rich.theme import Theme
import pydbhub.dbhub as dbhub
if __name__ == '__main__':
custom_theme = Theme({
"info": "green",
"warning": "yellow",
"error": "bold... | [
"rich.theme.Theme",
"rich.console.Console",
"os.path.dirname",
"sys.exit",
"platform.python_version"
] | [((236, 302), 'rich.theme.Theme', 'Theme', (["{'info': 'green', 'warning': 'yellow', 'error': 'bold red'}"], {}), "({'info': 'green', 'warning': 'yellow', 'error': 'bold red'})\n", (241, 302), False, 'from rich.theme import Theme\n'), ((347, 374), 'rich.console.Console', 'Console', ([], {'theme': 'custom_theme'}), '(th... |
import pytest
from practice_atcoder.book_algorithm_solution.chapter5.frog1 import question
# AtCoder Educational DP Contest A - Frog1.
class Test(object):
@pytest.mark.parametrize("n,hn,expect", [
("4", "10 30 40 20", "30"),
("2", "10 10", "0"),
("6", "30 10 60 10 60 50", "40")
])
... | [
"pytest.mark.parametrize",
"practice_atcoder.book_algorithm_solution.chapter5.frog1.question"
] | [((163, 290), 'pytest.mark.parametrize', 'pytest.mark.parametrize', (['"""n,hn,expect"""', "[('4', '10 30 40 20', '30'), ('2', '10 10', '0'), ('6', '30 10 60 10 60 50',\n '40')]"], {}), "('n,hn,expect', [('4', '10 30 40 20', '30'), ('2',\n '10 10', '0'), ('6', '30 10 60 10 60 50', '40')])\n", (186, 290), False, '... |
from django import forms
class LoginForm(forms.Form):
username = forms.CharField(widget=forms.TextInput(attrs={'class': 'form-control'}))
password = forms.CharField(widget=forms.PasswordInput(attrs={'class': 'form-control'}))
| [
"django.forms.PasswordInput",
"django.forms.TextInput"
] | [((94, 142), 'django.forms.TextInput', 'forms.TextInput', ([], {'attrs': "{'class': 'form-control'}"}), "(attrs={'class': 'form-control'})\n", (109, 142), False, 'from django import forms\n'), ((182, 234), 'django.forms.PasswordInput', 'forms.PasswordInput', ([], {'attrs': "{'class': 'form-control'}"}), "(attrs={'class... |
import sys
from PyQt5 import uic, QtCore
from PyQt5.QtCore import Qt, QObject, pyqtSignal
from PyQt5.QtWidgets import (QWidget, QApplication,
QGridLayout, QMainWindow, QTableWidgetItem,
QLabel, QPushButton, QLineEdit, QSpinBox, QMessageBox)
import AutomatonGenerator
class MW(QMainWindow, AutomatonGen... | [
"PyQt5.QtWidgets.QApplication"
] | [((3405, 3427), 'PyQt5.QtWidgets.QApplication', 'QApplication', (['sys.argv'], {}), '(sys.argv)\n', (3417, 3427), False, 'from PyQt5.QtWidgets import QWidget, QApplication, QGridLayout, QMainWindow, QTableWidgetItem, QLabel, QPushButton, QLineEdit, QSpinBox, QMessageBox\n')] |
"""Lambda function to copy a binary from CarbonBlack into the BiAlert input S3 bucket."""
# Expects the following environment variables:
# CARBON_BLACK_URL: URL of the CarbonBlack server.
# ENCRYPTED_CARBON_BLACK_API_TOKEN: API token, encrypted with KMS.
# TARGET_S3_BUCKET: Name of the S3 bucket in which to save ... | [
"logging.getLogger",
"json.loads",
"logging.StreamHandler",
"boto3.client",
"base64.b64decode",
"boto3.resource"
] | [((640, 659), 'logging.getLogger', 'logging.getLogger', ([], {}), '()\n', (657, 659), False, 'import logging\n'), ((1218, 1244), 'boto3.client', 'boto3.client', (['"""cloudwatch"""'], {}), "('cloudwatch')\n", (1230, 1244), False, 'import boto3\n'), ((730, 753), 'logging.StreamHandler', 'logging.StreamHandler', ([], {})... |
from db import db
class ProductoModel(db.Model):
__tablename__="t_producto"
id=db.Column("prod_id",db.Integer,primary_key=True)
desc=db.Column("prod_des",db.String(50))
# Se crea la realcion de uno a muchos
cat_id = db.Column(db.Integer, db.ForeignKey('t_categoria.cat_id'), nullable=False)... | [
"db.db.session.commit",
"db.db.relationship",
"db.db.ForeignKey",
"db.db.Column",
"db.db.String",
"db.db.session.add"
] | [((88, 138), 'db.db.Column', 'db.Column', (['"""prod_id"""', 'db.Integer'], {'primary_key': '(True)'}), "('prod_id', db.Integer, primary_key=True)\n", (97, 138), False, 'from db import db\n'), ((337, 370), 'db.db.relationship', 'db.relationship', (['"""CategoriaModel"""'], {}), "('CategoriaModel')\n", (352, 370), False... |
from typing import List
from uuid import UUID
from fastapi import APIRouter, Depends, HTTPException, Response, status
from app.api.dependencies import get_api_key, get_db
from app.db.database import MSSQLConnection
from app.schemas.security import SecurityLoginResponse, SecurityResponseBase
from app.services.exceptio... | [
"fastapi.HTTPException",
"fastapi.APIRouter",
"app.services.security.SecurityService",
"fastapi.Depends"
] | [((461, 472), 'fastapi.APIRouter', 'APIRouter', ([], {}), '()\n', (470, 472), False, 'from fastapi import APIRouter, Depends, HTTPException, Response, status\n'), ((833, 848), 'fastapi.Depends', 'Depends', (['get_db'], {}), '(get_db)\n', (840, 848), False, 'from fastapi import APIRouter, Depends, HTTPException, Respons... |
#!/usr/bin/env
"""
Read in two extracted light curves (interest band and reference band), split
into segments, compute the power spectra per band and cross spectrum of each
segment, averages cross spectrum of all the segments, and computes frequency
lags between the two bands.
Example call:
python simple_cross_spectra... | [
"numpy.sqrt",
"astropy.table.Table",
"scipy.fftpack.fftfreq",
"numpy.arctan2",
"scipy.fftpack.fft",
"astropy.io.fits.open",
"numpy.int8",
"numpy.mean",
"argparse.ArgumentParser",
"numpy.where",
"numpy.subtract",
"numpy.real",
"subprocess.call",
"numpy.abs",
"numpy.conj",
"argparse.Argu... | [((1664, 1699), 'argparse.ArgumentTypeError', 'argparse.ArgumentTypeError', (['message'], {}), '(message)\n', (1690, 1699), False, 'import argparse\n'), ((2358, 2370), 'numpy.int8', 'np.int8', (['ext'], {}), '(ext)\n', (2365, 2370), True, 'import numpy as np\n'), ((4602, 4628), 'numpy.sum', 'np.sum', (['(power * df)'],... |
import unittest
from contextlib import contextmanager
from numba import njit
from numba.core import errors, cpu, utils, typing
from numba.core.descriptors import TargetDescriptor
from numba.core.dispatcher import TargetConfigurationStack
from numba.core.retarget import BasicRetarget
from numba.core.extending import ov... | [
"numba.core.cpu.CPUContext",
"numba.core.extending.overload",
"numba.core.dispatcher.TargetConfigurationStack.switch_target",
"numba.core.typing.Context",
"numba.njit"
] | [((2907, 2951), 'numba.njit', 'njit', (['*args'], {'_target': 'CUSTOM_TARGET'}), '(*args, _target=CUSTOM_TARGET, **kwargs)\n', (2911, 2951), False, 'from numba import njit\n'), ((1481, 1535), 'numba.core.cpu.CPUContext', 'cpu.CPUContext', (['self.typing_context', 'self._target_name'], {}), '(self.typing_context, self._... |
from shutil import copy2
from os import path, remove
from random import randint
import argparse
class WorkspaceReader:
def __init__(self, fname):
self.maven_jars = []
self.java_libraries = []
module_name = 'tmp'+str(randint(1000,9999))
new_name = path.join(path.dirname(__file__), m... | [
"argparse.ArgumentParser",
"shutil.copy2",
"os.path.isfile",
"os.path.dirname",
"random.randint",
"os.remove"
] | [((3437, 3537), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {'description': '"""Merge generated bazel workspaces for maven dependencies."""'}), "(description=\n 'Merge generated bazel workspaces for maven dependencies.')\n", (3460, 3537), False, 'import argparse\n'), ((4171, 4200), 'os.path.isfile', '... |
class Solution(object):
def findMaxConsecutiveOnes(self, nums):
"""
:type nums: List[int]
:rtype: int
"""
import itertools
maxcount = 0
for bit, group in itertools.groupby(nums):
if bit == 1:
maxcount = max(maxcoun... | [
"itertools.groupby"
] | [((232, 255), 'itertools.groupby', 'itertools.groupby', (['nums'], {}), '(nums)\n', (249, 255), False, 'import itertools\n')] |
import streamlit as st
import numpy as np
import pandas as pd
from sklearn.datasets import load_iris
from .generic import Tool
iris = pd.DataFrame(load_iris()["data"])
df = pd.DataFrame(
np.random.randn(50, 20),
columns=('col %d' % i for i in range(20)))
# st.dataframe(df) # Same as st.write(df)
class Da... | [
"sklearn.datasets.load_iris",
"streamlit.checkbox",
"pandas.read_csv",
"streamlit.write",
"numpy.random.randn"
] | [((194, 217), 'numpy.random.randn', 'np.random.randn', (['(50)', '(20)'], {}), '(50, 20)\n', (209, 217), True, 'import numpy as np\n'), ((150, 161), 'sklearn.datasets.load_iris', 'load_iris', ([], {}), '()\n', (159, 161), False, 'from sklearn.datasets import load_iris\n'), ((1000, 1034), 'streamlit.checkbox', 'st.check... |
import gensim.models.keyedvectors as word2vec
class Synonyms:
def __init__(self, fasttext_model_path: str):
print(f'Loading fasttext model: {fasttext_model_path}')
self.model = word2vec.KeyedVectors.load_word2vec_format(fasttext_model_path)
print(f'Finished loading fasttext model: {fasttex... | [
"gensim.models.keyedvectors.KeyedVectors.load_word2vec_format"
] | [((199, 262), 'gensim.models.keyedvectors.KeyedVectors.load_word2vec_format', 'word2vec.KeyedVectors.load_word2vec_format', (['fasttext_model_path'], {}), '(fasttext_model_path)\n', (241, 262), True, 'import gensim.models.keyedvectors as word2vec\n')] |
'''
Copyright 2017-present, Airbnb Inc.
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, sof... | [
"stream_alert.rule_processor.pre_parsers.StreamPreParsers.pre_parse_sns",
"stream_alert.rule_processor.pre_parsers.StreamPreParsers.pre_parse_s3",
"base64.b64encode",
"stream_alert.rule_processor.pre_parsers.StreamPreParsers.read_s3_file",
"stream_alert.rule_processor.pre_parsers.StreamPreParsers.pre_parse_... | [((742, 751), 'moto.mock_s3', 'mock_s3', ([], {}), '()\n', (749, 751), False, 'from moto import mock_s3\n'), ((926, 972), 'stream_alert.rule_processor.pre_parsers.StreamPreParsers.pre_parse_kinesis', 'StreamPreParsers.pre_parse_kinesis', (['raw_record'], {}), '(raw_record)\n', (960, 972), False, 'from stream_alert.rule... |
# Copyright (c) FlowTorch Development Team. All Rights Reserved
# SPDX-License-Identifier: MIT
from typing import Optional, Tuple
import torch
import torch.distributions.constraints as constraints
import flowtorch
import flowtorch.params
from flowtorch.utils import clamp_preserve_gradients
class AffineAutoregressi... | [
"flowtorch.params.DenseAutoregressive",
"torch.exp",
"flowtorch.utils.clamp_preserve_gradients",
"torch.zeros_like",
"torch.Size"
] | [((469, 507), 'flowtorch.params.DenseAutoregressive', 'flowtorch.params.DenseAutoregressive', ([], {}), '()\n', (505, 507), False, 'import flowtorch\n'), ((1313, 1403), 'flowtorch.utils.clamp_preserve_gradients', 'clamp_preserve_gradients', (['log_scale', 'self.log_scale_min_clip', 'self.log_scale_max_clip'], {}), '(lo... |
# -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'lp2ctrlui.ui'
#
# Created by: PyQt5 UI code generator 5.15.4
#
# WARNING: Any manual changes made to this file will be lost when pyuic5 is
# run again. Do not edit this file unless you know what you are doing.
from PyQt5 import QtCore, Qt... | [
"PyQt5.QtWidgets.QWidget",
"PyQt5.QtWidgets.QMenu",
"PyQt5.QtGui.QIcon",
"PyQt5.QtGui.QFont",
"PyQt5.QtWidgets.QPlainTextEdit",
"PyQt5.QtWidgets.QToolBar",
"PyQt5.QtCore.QMetaObject.connectSlotsByName",
"PyQt5.QtWidgets.QAction",
"PyQt5.QtCore.QRect",
"PyQt5.QtWidgets.QGridLayout",
"PyQt5.QtWidg... | [((499, 512), 'PyQt5.QtGui.QIcon', 'QtGui.QIcon', ([], {}), '()\n', (510, 512), False, 'from PyQt5 import QtCore, QtGui, QtWidgets\n'), ((680, 709), 'PyQt5.QtWidgets.QWidget', 'QtWidgets.QWidget', (['MainWindow'], {}), '(MainWindow)\n', (697, 709), False, 'from PyQt5 import QtCore, QtGui, QtWidgets\n'), ((800, 837), 'P... |
#!/usr/bin/python3
"""
一些基础的类和函数
注意, import关系需要能够拓扑排序(不要相互调用).
"""
# 加载不应该被COPY的包
import io2 as io
import deap
from deap import algorithms, base, creator, gp, tools
from prettytable import PrettyTable
# COPY #
import copy
import random
import warnings
import sys
import pdb
import inspect
import shu... | [
"numpy.hstack",
"pandas.value_counts",
"numpy.array",
"numpy.nanmean",
"numpy.mean",
"numpy.full_like",
"inspect.isclass",
"scipy.stats.kurtosis",
"numpy.ix_",
"numpy.stack",
"numpy.dot",
"numpy.linalg.lstsq",
"numpy.isinf",
"deap.gp.PrimitiveTree",
"prettytable.PrettyTable",
"numpy.ab... | [((2907, 2932), 'numpy.full_like', 'np.full_like', (['arr', 'np.nan'], {}), '(arr, np.nan)\n', (2919, 2932), True, 'import numpy as np\n'), ((4449, 4473), 'numpy.stack', 'np.stack', (['ret'], {'axis': 'axis'}), '(ret, axis=axis)\n', (4457, 4473), True, 'import numpy as np\n'), ((4984, 5008), 'numpy.stack', 'np.stack', ... |
"""Unit tests for reward factory.
"""
from datetime import datetime
import unittest
from parameterized import parameterized
from stock_trading_backend.simulation import create_reward
from stock_trading_backend.simulation.constant_reward import ConstantReward
from stock_trading_backend.simulation.net_worth_ratio_rewa... | [
"datetime.datetime",
"stock_trading_backend.simulation.create_reward",
"parameterized.parameterized.expand"
] | [((524, 715), 'parameterized.parameterized.expand', 'parameterized.expand', (["[({'name': 'constant_reward'}, ConstantReward), ({'name':\n 'net_worth_ratio_reward'}, NetWorthRatioReward), ({'name':\n 'sharpe_ratio_reward'}, SharpeRatioReward)]"], {}), "([({'name': 'constant_reward'}, ConstantReward), ({\n 'nam... |
import argparse
from rename import RandomRename
import logging
def main():
parser = argparse.ArgumentParser(description='Randomly rename files')
parser.add_argument('-e', '--ext', help='extension type(s) of file(s) that need renaming')
parser.add_argument('-p ', '--pre', help='prefix to add to each filena... | [
"rename.RandomRename",
"argparse.ArgumentParser"
] | [((90, 150), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {'description': '"""Randomly rename files"""'}), "(description='Randomly rename files')\n", (113, 150), False, 'import argparse\n'), ((984, 1045), 'rename.RandomRename', 'RandomRename', (['paths'], {'prefixes': 'prefixes', 'extensions': 'extensions... |
import joblib
import pandas as pd
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import train_test_split
from sklearn.pipeline import Pipeline
from sklearn.metrics import roc_auc_score
from db import get_data
random_seed = ... | [
"db.get_data",
"sklearn.model_selection.train_test_split",
"sklearn.feature_extraction.text.CountVectorizer",
"sklearn.metrics.roc_auc_score",
"sklearn.linear_model.LogisticRegression",
"pandas.DataFrame",
"joblib.dump"
] | [((384, 403), 'db.get_data', 'get_data', (['"""WEEK_00"""'], {}), "('WEEK_00')\n", (392, 403), False, 'from db import get_data\n'), ((569, 617), 'sklearn.model_selection.train_test_split', 'train_test_split', (['X', 'y'], {'random_state': 'random_seed'}), '(X, y, random_state=random_seed)\n', (585, 617), False, 'from s... |
from typing import Optional, Union
import numpy as np
from scipy.spatial import cKDTree
import bbknn
from scipy.sparse import csr_matrix
import scanpy as sc
from numpy.testing import assert_array_equal, assert_array_compare
import operator
import numpy as np
from anndata import AnnData
from sklearn.utils import che... | [
"bbknn.trimming",
"numpy.copy",
"bbknn.query_tree",
"numpy.shape",
"numpy.unique",
"bbknn.create_tree",
"numpy.argsort",
"numpy.testing.assert_array_compare",
"scanpy.tl.umap",
"scanpy.pl.umap",
"scipy.sparse.csr_matrix",
"numpy.arange",
"bbknn.compute_connectivities_umap"
] | [((1148, 1169), 'numpy.unique', 'np.unique', (['batch_list'], {}), '(batch_list)\n', (1157, 1169), True, 'import numpy as np\n'), ((5800, 5833), 'numpy.argsort', 'np.argsort', (['knn_distances'], {'axis': '(1)'}), '(knn_distances, axis=1)\n', (5810, 5833), True, 'import numpy as np\n'), ((6100, 6288), 'bbknn.compute_co... |
import scann
from argparse import ArgumentParser
from pl_bolts.models.self_supervised import SimCLR
from pl_bolts.models.self_supervised.resnets import resnet18
from pl_bolts.models.self_supervised.simclr.transforms import SimCLREvalDataTransform, SimCLRTrainDataTransform
from pathlib import Path
import torch
import os... | [
"matplotlib.pyplot.ylabel",
"pl_bolts.models.self_supervised.SimCLR",
"pl_bolts.models.self_supervised.simclr.transforms.SimCLREvalDataTransform",
"numpy.linalg.norm",
"os.remove",
"os.path.exists",
"seaborn.set",
"argparse.ArgumentParser",
"pathlib.Path",
"torch.unsqueeze",
"matplotlib.pyplot.x... | [((868, 881), 'tqdm.tqdm', 'tqdm', (['dataset'], {}), '(dataset)\n', (872, 881), False, 'from tqdm import tqdm\n'), ((1226, 1251), 'os.path.exists', 'os.path.exists', (['"""data.h5"""'], {}), "('data.h5')\n", (1240, 1251), False, 'import os\n'), ((1285, 1310), 'h5py.File', 'h5py.File', (['"""data.h5"""', '"""w"""'], {}... |
import ctypes
import os
from ctypes import wintypes
from collections import namedtuple
from PySide2.QtWidgets import QApplication
def get_process_hwnds():
# https://stackoverflow.com/questions/37501191/how-to-get-windows-window-names-with-ctypes-in-python
user32 = ctypes.WinDLL('user32', use_last_erro... | [
"ctypes.WinError",
"ctypes.byref",
"ctypes.POINTER",
"collections.namedtuple",
"ctypes.wintypes.DWORD",
"ctypes.create_unicode_buffer",
"ctypes.get_last_error",
"ctypes.WINFUNCTYPE",
"ctypes.WinDLL",
"os.getpid"
] | [((283, 327), 'ctypes.WinDLL', 'ctypes.WinDLL', (['"""user32"""'], {'use_last_error': '(True)'}), "('user32', use_last_error=True)\n", (296, 327), False, 'import ctypes\n'), ((645, 683), 'collections.namedtuple', 'namedtuple', (['"""WindowInfo"""', '"""title hwnd"""'], {}), "('WindowInfo', 'title hwnd')\n", (655, 683),... |
import argparse
import numpy as np
import models.ensemble as e
import utils.load as l
import utils.metrics as m
import utils.wrapper as w
def get_arguments():
"""Gets arguments from the command line.
Returns:
A parser with the input arguments.
"""
# Creates the ArgumentParser
parser =... | [
"argparse.ArgumentParser",
"utils.wrapper.optimize_umda",
"numpy.random.seed",
"models.ensemble.boolean_classifiers",
"utils.load.load_candidates"
] | [((321, 448), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {'usage': '"""Optimizes a boolean-based ensemble using Univariate Marginal Distribution Algorithm."""'}), "(usage=\n 'Optimizes a boolean-based ensemble using Univariate Marginal Distribution Algorithm.'\n )\n", (344, 448), False, 'import ar... |
import re
QUOTE_FIRS_OPEN = '«'
QUOTE_FIRS_CLOSE = '»'
QUOTE_CRAWSE_OPEN = '„'
QUOTE_CRAWSE_CLOSE = '“'
RE_QO = re.compile('&(l|r)aquo;')
DOMAINS = [
"ru",
"ру",
"ком",
"орг",
"уа",
"ua",
"uk",
"co",
"fr",
"com",
"net",
"edu",
"gov",
"org... | [
"re.compile"
] | [((137, 162), 're.compile', 're.compile', (['"""&(l|r)aquo;"""'], {}), "('&(l|r)aquo;')\n", (147, 162), False, 'import re\n')] |
"""
SGDP Optimizer Implementation copied from https://github.com/clovaai/AdamP/blob/master/adamp/sgdp.py
Paper: `Slowing Down the Weight Norm Increase in Momentum-based Optimizers` - https://arxiv.org/abs/2006.08217
Code: https://github.com/clovaai/AdamP
Copyright (c) 2020-present NAVER Corp.
MIT license
"""
import ... | [
"torch.no_grad",
"torch.zeros_like",
"torch.enable_grad"
] | [((876, 891), 'torch.no_grad', 'torch.no_grad', ([], {}), '()\n', (889, 891), False, 'import torch\n'), ((995, 1014), 'torch.enable_grad', 'torch.enable_grad', ([], {}), '()\n', (1012, 1014), False, 'import torch\n'), ((1551, 1570), 'torch.zeros_like', 'torch.zeros_like', (['p'], {}), '(p)\n', (1567, 1570), False, 'imp... |
import os
import glob
from unet3d.data import write_data_to_file, open_data_file
from unet3d.generator import get_training_and_validation_generators
from unet3d.model import siam3dunet_model
from unet3d.model import testnet_model
from unet3d.training import load_old_model, train_model
from skimage.io import imsave, im... | [
"os.path.exists",
"unet3d.data.write_data_to_file",
"unet3d.data.open_data_file",
"unet3d.training.load_old_model",
"os.path.join",
"os.path.dirname",
"unet3d.model.siam3dunet_model",
"os.path.basename",
"unet3d.generator.get_training_and_validation_generators",
"os.path.abspath",
"unet3d.traini... | [((2599, 2639), 'os.path.abspath', 'os.path.abspath', (['f"""siam_data0_{mode}.h5"""'], {}), "(f'siam_data0_{mode}.h5')\n", (2614, 2639), False, 'import os\n'), ((2663, 2703), 'os.path.abspath', 'os.path.abspath', (['f"""siam_data1_{mode}.h5"""'], {}), "(f'siam_data1_{mode}.h5')\n", (2678, 2703), False, 'import os\n'),... |
# Copyright (c) 2019 Mycroft AI, Inc. and <NAME>
#
# This file is part of Mycroft Light
# (see https://github.com/MatthewScholefield/mycroft-light).
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional i... | [
"pocketsphinx.Decoder",
"os.path.join",
"pocketsphinx.Decoder.default_config",
"os.fdopen",
"tempfile.mkstemp"
] | [((1713, 1755), 'os.path.join', 'join', (['rt.paths.user_config', '"""models"""', 'lang'], {}), "(rt.paths.user_config, 'models', lang)\n", (1717, 1755), False, 'from os.path import join\n'), ((2049, 2073), 'pocketsphinx.Decoder.default_config', 'Decoder.default_config', ([], {}), '()\n', (2071, 2073), False, 'from poc... |
# Generated by Django 2.2.6 on 2019-11-12 04:24
import datetime
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('api', '0014_auto_20191112_0420'),
]
operations = [
migrations.AlterField(
model_name='takes',
name='... | [
"django.db.models.DateField"
] | [((345, 390), 'django.db.models.DateField', 'models.DateField', ([], {'default': 'datetime.date.today'}), '(default=datetime.date.today)\n', (361, 390), False, 'from django.db import migrations, models\n')] |
import logging
import typing
from datetime import timedelta
import disnake
from asyncpg.exceptions import PostgresError
from disnake.ext.commands import BucketType, cooldown, guild_only
from bot.bot import command, bot_has_permissions, group, Group
from bot.converters import AnyUser, CommandConverter, TimeDelta
from ... | [
"logging.getLogger",
"disnake.Embed",
"utils.utilities.format_timedelta",
"disnake.ext.commands.guild_only",
"disnake.ext.commands.cooldown",
"bot.bot.group",
"bot.bot.command",
"utils.utilities.utcnow",
"bot.bot.bot_has_permissions",
"bot.paginator.Paginator",
"datetime.timedelta"
] | [((453, 482), 'logging.getLogger', 'logging.getLogger', (['"""terminal"""'], {}), "('terminal')\n", (470, 482), False, 'import logging\n'), ((568, 577), 'bot.bot.command', 'command', ([], {}), '()\n', (575, 577), False, 'from bot.bot import command, bot_has_permissions, group, Group\n'), ((583, 620), 'disnake.ext.comma... |
import os
import cv2
import numpy as np
from math import *
from scipy.stats import mode
import time
# 图像矫正类
class ImgCorrect:
"""
霍夫变换进行线段检索，再根据这些线段算出夹角，利用角度的加权平均值和频率最高的思想作为旋转的最佳角度
"""
def __init__(self, img):
self.img = img
"""
# 图像归一化处理 会造成图像清晰度变低
self.h, self.w, self.... | [
"numpy.array",
"os.path.exists",
"os.listdir",
"cv2.threshold",
"time.localtime",
"cv2.warpAffine",
"os.rename",
"cv2.cvtColor",
"cv2.getRotationMatrix2D",
"cv2.Canny",
"cv2.imread",
"cv2.imwrite",
"cv2.HoughLinesP",
"os.makedirs",
"scipy.stats.mode",
"os.path.join",
"os.path.abspath... | [((6384, 6406), 'os.listdir', 'os.listdir', (['input_path'], {}), '(input_path)\n', (6394, 6406), False, 'import os\n'), ((7140, 7162), 'os.listdir', 'os.listdir', (['input_path'], {}), '(input_path)\n', (7150, 7162), False, 'import os\n'), ((882, 924), 'cv2.cvtColor', 'cv2.cvtColor', (['self.img', 'cv2.COLOR_BGR2GRAY'... |
#!/usr/bin/env python2.7
# -*- coding: utf-8 -*-
import sys
import unittest
sys.path.append('..')
from hecatoncheir import DbProfilerRepository
from hecatoncheir import DbProfilerVerify
class TestDbProfilerVerify(unittest.TestCase):
def setUp(self):
pass
def test_verify_column_001(self):
col... | [
"hecatoncheir.DbProfilerVerify.verify_table",
"hecatoncheir.DbProfilerVerify.DbProfilerVerify",
"unittest.main",
"hecatoncheir.DbProfilerVerify.verify_column",
"sys.path.append",
"hecatoncheir.DbProfilerRepository.DbProfilerRepository"
] | [((77, 98), 'sys.path.append', 'sys.path.append', (['""".."""'], {}), "('..')\n", (92, 98), False, 'import sys\n'), ((1598, 1613), 'unittest.main', 'unittest.main', ([], {}), '()\n', (1611, 1613), False, 'import unittest\n'), ((610, 645), 'hecatoncheir.DbProfilerVerify.verify_column', 'DbProfilerVerify.verify_column', ... |
#!/usr/bin/python
# -*- coding: utf-8 -*-
from abc import abstractproperty
from cloudshell.cli.cli import CLI
from cloudshell.cli.cli_service_impl import CommandModeContextManager
from cloudshell.cli.command_mode import CommandMode
from cloudshell.cli.session.ssh_session import SSHSession
from cloudshell.cli.session.... | [
"cloudshell.cli.session.ssh_session.SSHSession.SESSION_TYPE.lower",
"cloudshell.cli.session.ssh_session.SSHSession",
"cloudshell.cli.session.telnet_session.TelnetSession.SESSION_TYPE.lower",
"cloudshell.cli.session.telnet_session.TelnetSession"
] | [((2320, 2421), 'cloudshell.cli.session.ssh_session.SSHSession', 'SSHSession', (['self.resource_address', 'self.username', 'self.password', 'self.port', 'self.on_session_start'], {}), '(self.resource_address, self.username, self.password, self.port,\n self.on_session_start)\n', (2330, 2421), False, 'from cloudshell.... |
import re
import humanize
from io import StringIO
async def ask_for_int(bot, message, lower_bound=None, upper_bound=None, timeout=30, timeout_msg=None, default=None):
def check(msg):
s = msg.content
if not s.isdigit():
return False
n = int(s)
if lower_bound is not None ... | [
"re.sub",
"io.StringIO",
"re.search"
] | [((833, 881), 're.sub', 're.sub', (['"""(?P<c>[`*_\\\\[\\\\]~])"""', '"""\\\\\\\\\\\\g<c>"""', 'msg'], {}), "('(?P<c>[`*_\\\\[\\\\]~])', '\\\\\\\\\\\\g<c>', msg)\n", (839, 881), False, 'import re\n'), ((920, 993), 're.sub', 're.sub', (['"""(?P<a>`)(?P<b>`)(?P<c>`)"""', '"""\\\\\\\\\\\\g<a>\\\\\\\\\\\\g<b>\\\\\\\\\\\\g<... |
from random import randrange
from Car import Car
car1 = Car("<NAME>",15, 250)
car1.drive(100)
for t in range(10):
print (t)
print(car1)
a=randrange(1,4)
if a == 1:
car1.brake(5)
print("breaking")
elif a == 2:
car1.acc(5)
print("acceleratione")
else:
... | [
"Car.Car",
"random.randrange"
] | [((57, 79), 'Car.Car', 'Car', (['"""<NAME>"""', '(15)', '(250)'], {}), "('<NAME>', 15, 250)\n", (60, 79), False, 'from Car import Car\n'), ((153, 168), 'random.randrange', 'randrange', (['(1)', '(4)'], {}), '(1, 4)\n', (162, 168), False, 'from random import randrange\n')] |
import unittest
import tensorflow as tf
import fastestimator as fe
import fastestimator.test.unittest_util as fet
class TestReflectionPadding2D(unittest.TestCase):
def setUp(self):
self.x = tf.reshape(tf.convert_to_tensor(list(range(9))), (1, 3, 3, 1))
def test_reflection_padding_2d_double_side(sel... | [
"fastestimator.layers.tensorflow.ReflectionPadding2D",
"fastestimator.test.unittest_util.is_equal",
"tensorflow.constant"
] | [((337, 492), 'tensorflow.constant', 'tf.constant', (['[[[[4], [3], [4], [5], [4]], [[1], [0], [1], [2], [1]], [[4], [3], [4], [5],\n [4]], [[7], [6], [7], [8], [7]], [[4], [3], [4], [5], [4]]]]'], {}), '([[[[4], [3], [4], [5], [4]], [[1], [0], [1], [2], [1]], [[4], [\n 3], [4], [5], [4]], [[7], [6], [7], [8], [7... |
import asyncio
import logging
import aiohttp
import async_timeout
_LOGGER = logging.getLogger(__name__)
def _load_enum(enum, value, default=None):
"""Parse an enum with fallback."""
try:
return enum(value)
except ValueError:
return default
async def async_request(session, url, **kwargs... | [
"logging.getLogger",
"async_timeout.timeout"
] | [((78, 105), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (95, 105), False, 'import logging\n'), ((393, 418), 'async_timeout.timeout', 'async_timeout.timeout', (['(10)'], {}), '(10)\n', (414, 418), False, 'import async_timeout\n')] |
'''
Created on Feb. 9, 2021
@author: cefect
'''
#===============================================================================
# imports
#===============================================================================
import os, datetime
start = datetime.datetime.now()
import pandas as pd
import numpy as np
from pa... | [
"pandas.Series",
"datetime.datetime.now",
"pandas.read_excel",
"datetime.datetime.today",
"hlpr.basic.force_open_dir"
] | [((250, 273), 'datetime.datetime.now', 'datetime.datetime.now', ([], {}), '()\n', (271, 273), False, 'import os, datetime\n'), ((6537, 6565), 'hlpr.basic.force_open_dir', 'force_open_dir', (['wrkr.out_dir'], {}), '(wrkr.out_dir)\n', (6551, 6565), False, 'from hlpr.basic import view, force_open_dir\n'), ((505, 530), 'da... |
import random
import string
def gen_string(size=8, chars=string.ascii_lowercase + string.ascii_uppercase + string.digits):
return ''.join(random.choice(chars) for _ in range(size))
def return_url(request, default):
if 'HTTP_REFERER' in request.META:
return request.META['HTTP_REFERER']
return de... | [
"random.choice"
] | [((144, 164), 'random.choice', 'random.choice', (['chars'], {}), '(chars)\n', (157, 164), False, 'import random\n')] |
from __future__ import print_function, division, absolute_import
import argparse
import math
import time
import matplotlib.pyplot as plt
import numpy as np
import scipy.io as sio
import torch
from hubconf import SRResNet
parser = argparse.ArgumentParser(description="PyTorch SRResNet Demo")
parser.add_argument("--de... | [
"numpy.clip",
"numpy.mean",
"hubconf.SRResNet",
"argparse.ArgumentParser",
"matplotlib.pyplot.show",
"torch.load",
"scipy.io.loadmat",
"torch.from_numpy",
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.figure",
"torch.set_grad_enabled",
"math.log10",
"time.time",
"torch.device"
] | [((234, 294), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {'description': '"""PyTorch SRResNet Demo"""'}), "(description='PyTorch SRResNet Demo')\n", (257, 294), False, 'import argparse\n'), ((1153, 1177), 'torch.device', 'torch.device', (['opt.device'], {}), '(opt.device)\n', (1165, 1177), False, 'impor... |
from django.db import models
from accounts.models import User
from datetime import date
from django.utils.translation import gettext as _
from django.core.validators import RegexValidator
class Application(models.Model):
"""
this is the model for application that needs to be filled for applying for admission ... | [
"django.db.models.EmailField",
"django.db.models.OneToOneField",
"django.db.models.FloatField",
"django.db.models.DateField",
"django.db.models.TextField",
"django.db.models.ForeignKey",
"django.db.models.IntegerField",
"django.core.validators.RegexValidator",
"django.db.models.BooleanField",
"dja... | [((426, 478), 'django.db.models.ForeignKey', 'models.ForeignKey', (['User'], {'on_delete': 'models.DO_NOTHING'}), '(User, on_delete=models.DO_NOTHING)\n', (443, 478), False, 'from django.db import models\n'), ((494, 544), 'django.db.models.CharField', 'models.CharField', ([], {'default': '"""Select"""', 'max_length': '... |
import scrapy
from bili1.items import Bili1Item
import json
class OtherDataSpider(scrapy.Spider):
name = 'other_data'
# allowed_domains = ['bilibili.com']
start_urls = ['https://api.bilibili.com/x/article/viewinfo?id=1047645&jsonp=jsonp']
url_other = "https://api.bilibili.com/x/article/viewinfo?id=%d&... | [
"json.loads",
"bili1.items.Bili1Item",
"scrapy.Request"
] | [((441, 466), 'json.loads', 'json.loads', (['response.body'], {}), '(response.body)\n', (451, 466), False, 'import json\n'), ((486, 497), 'bili1.items.Bili1Item', 'Bili1Item', ([], {}), '()\n', (495, 497), False, 'from bili1.items import Bili1Item\n'), ((1581, 1653), 'scrapy.Request', 'scrapy.Request', ([], {'url': 'ne... |
import re
# text_rules, messages = open('sample_input_partB').read().split('\n\n')
text_rules, messages = open('input').read().split('\n\n')
rules = {}
for rule in text_rules.split('\n'):
rule_n, rule_cond = rule.split(':')
rules[int(rule_n)] = rule_cond.strip()
# Completely determine all rules:
# All number... | [
"re.search",
"re.sub",
"re.match",
"re.compile"
] | [((1539, 1566), 're.compile', 're.compile', (['f"""^{rules[0]}$"""'], {}), "(f'^{rules[0]}$')\n", (1549, 1566), False, 'import re\n'), ((539, 572), 're.search', 're.search', (['"""[0-9]"""', 'rules[rule_n]'], {}), "('[0-9]', rules[rule_n])\n", (548, 572), False, 'import re\n'), ((1605, 1621), 're.match', 're.match', ([... |
import orm_mfk
from sqlalchemy.orm import sessionmaker
Session = sessionmaker(bind=orm_mfk.engine)
session = Session()
addr1 = orm_mfk.Address(street="adsfad")
addr2 = orm_mfk.Address(street="123")
addr3 = orm_mfk.Address(street="2321asd")
c1 = orm_mfk.Customer(name="jack", billing_address = addr1, shiping_address=... | [
"orm_mfk.Customer",
"sqlalchemy.orm.sessionmaker",
"orm_mfk.Address"
] | [((67, 100), 'sqlalchemy.orm.sessionmaker', 'sessionmaker', ([], {'bind': 'orm_mfk.engine'}), '(bind=orm_mfk.engine)\n', (79, 100), False, 'from sqlalchemy.orm import sessionmaker\n'), ((130, 162), 'orm_mfk.Address', 'orm_mfk.Address', ([], {'street': '"""adsfad"""'}), "(street='adsfad')\n", (145, 162), False, 'import ... |
import os
import subprocess
index = 1
maxRange = "10"
for filename in os.listdir(os.getcwd()):
imageName = "{0:0>5}".format(index)
print(imageName)
subprocess.run(["p3", "plot.py"], cwd=os.getcwd)
index += 1
| [
"subprocess.run",
"os.getcwd"
] | [((82, 93), 'os.getcwd', 'os.getcwd', ([], {}), '()\n', (91, 93), False, 'import os\n'), ((161, 209), 'subprocess.run', 'subprocess.run', (["['p3', 'plot.py']"], {'cwd': 'os.getcwd'}), "(['p3', 'plot.py'], cwd=os.getcwd)\n", (175, 209), False, 'import subprocess\n')] |
# Generated by Django 3.0.2 on 2020-01-03 14:27
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('core', '0002_submission'),
]
operations = [
migrations.AddField(
model_name='theme',
name='is_series',
f... | [
"django.db.models.BooleanField"
] | [((325, 359), 'django.db.models.BooleanField', 'models.BooleanField', ([], {'default': '(False)'}), '(default=False)\n', (344, 359), False, 'from django.db import migrations, models\n')] |
# -*- coding: utf-8 -*-
################################################################################
## Form generated from reading UI file 'sideui.ui'
##
## Created by: Qt User Interface Compiler version 5.14.2
##
## WARNING! All changes made in this file will be lost when recompiling UI file!
###########... | [
"PySide2.QtCore.QCoreApplication.translate",
"PySide2.QtGui.QFont",
"PySide2.QtCore.QMetaObject.connectSlotsByName",
"PySide2.QtCore.QRect",
"PySide2.QtCore.QSize",
"PySide2.QtGui.QIcon"
] | [((1385, 1392), 'PySide2.QtGui.QFont', 'QFont', ([], {}), '()\n', (1390, 1392), False, 'from PySide2.QtGui import QBrush, QColor, QConicalGradient, QCursor, QFont, QFontDatabase, QIcon, QKeySequence, QLinearGradient, QPalette, QPainter, QPixmap, QRadialGradient\n'), ((1515, 1522), 'PySide2.QtGui.QIcon', 'QIcon', ([], {... |
# CreateApiGenerator.py - Creates an object representing a create API
import os
from jinja2 import Environment, Template, FileSystemLoader
import yaml
from smoacks.sconfig import sconfig
from smoacks.Schema import scr_schemas
class OpenapiGenerator:
def __init__(self, app_object):
self._app_object = app_ob... | [
"jinja2.FileSystemLoader",
"yaml.load"
] | [((2340, 2390), 'yaml.load', 'yaml.load', (['rendered_string'], {'Loader': 'yaml.FullLoader'}), '(rendered_string, Loader=yaml.FullLoader)\n', (2349, 2390), False, 'import yaml\n'), ((2111, 2140), 'jinja2.FileSystemLoader', 'FileSystemLoader', (['"""templates"""'], {}), "('templates')\n", (2127, 2140), False, 'from jin... |
__author__ = '<NAME>'
import urllib2
data_url = "http://files.grouplens.org/datasets/movielens/ml-100k/u.data"
movies_url = "http://files.grouplens.org/datasets/movielens/ml-100k/u.item"
def get_movies_dataset():
movies = {}
# get movies
movies_file = urllib2.urlopen(movies_url)
for line in movies_fi... | [
"urllib2.urlopen"
] | [((267, 294), 'urllib2.urlopen', 'urllib2.urlopen', (['movies_url'], {}), '(movies_url)\n', (282, 294), False, 'import urllib2\n'), ((493, 518), 'urllib2.urlopen', 'urllib2.urlopen', (['data_url'], {}), '(data_url)\n', (508, 518), False, 'import urllib2\n')] |
import logging
import sys
from django.conf import settings
from azure_storage_logging.handlers import BlobStorageTimedRotatingFileHandler as storage
formatter = logging.Formatter(
fmt='%(asctime)s %(levelname)-8s %(message)s',
datefmt='%Y-%m-%d %H:%M:%S'
)
screen_handler = logging.StreamHandler(stream=sys.s... | [
"logging.getLogger",
"logging.Formatter",
"logging.StreamHandler",
"azure_storage_logging.handlers.BlobStorageTimedRotatingFileHandler"
] | [((164, 262), 'logging.Formatter', 'logging.Formatter', ([], {'fmt': '"""%(asctime)s %(levelname)-8s %(message)s"""', 'datefmt': '"""%Y-%m-%d %H:%M:%S"""'}), "(fmt='%(asctime)s %(levelname)-8s %(message)s', datefmt=\n '%Y-%m-%d %H:%M:%S')\n", (181, 262), False, 'import logging\n'), ((286, 326), 'logging.StreamHandle... |
import abc
import logging
from enum import Enum
from typing import List, Tuple, Union, Dict, Optional
from nempy.user_data import AccountData
from nempy.sym.constants import BlockchainStatuses, Fees, TransactionStatus
from .sym import api as sym
from .sym import network
from .sym.network import NodeSelector
logger = ... | [
"logging.getLogger"
] | [((320, 347), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (337, 347), False, 'import logging\n')] |
from django import template
from ghoster import forms
from django.contrib import admin
from django.contrib.admin import helpers
import pprint
import copy
import re
register = template.Library()
def __flatten(fields):
"""Returns a list which is a single level of flattening of the
original list."""
flat = [... | [
"django.contrib.admin.helpers.AdminForm",
"django.contrib.admin.site.get_app_list",
"django.template.Library"
] | [((175, 193), 'django.template.Library', 'template.Library', ([], {}), '()\n', (191, 193), False, 'from django import template\n'), ((1669, 1712), 'django.contrib.admin.site.get_app_list', 'admin.site.get_app_list', (["context['request']"], {}), "(context['request'])\n", (1692, 1712), False, 'from django.contrib import... |
"""
File: websocket_streams.py
Author: <NAME>
Created on: 21/06/21, 7:15 pm
"""
from dataclasses import dataclass
import datetime
import struct
def unpack_int8(bin_data, pos):
""" Convert 1 byte data """
return struct.unpack(">B", bin_data[pos:pos+1])[0]
def unpack_int16(bin_data, pos)... | [
"struct.unpack",
"dataclasses.dataclass"
] | [((871, 882), 'dataclasses.dataclass', 'dataclass', ([], {}), '()\n', (880, 882), False, 'from dataclasses import dataclass\n'), ((3104, 3115), 'dataclasses.dataclass', 'dataclass', ([], {}), '()\n', (3113, 3115), False, 'from dataclasses import dataclass\n'), ((243, 285), 'struct.unpack', 'struct.unpack', (['""">B"""'... |
import os
from setuptools import setup, find_packages
here = os.path.abspath(os.path.dirname(__file__))
with open(os.path.join(here, 'README.md')) as f:
README = f.read()
# with open(os.path.join(here, 'CHANGES.txt')) as f:
# CHANGES = f.read()
CHANGES = "Changes"
requires = ['pyramid',
'python-k... | [
"os.path.dirname",
"setuptools.find_packages",
"os.path.join"
] | [((79, 104), 'os.path.dirname', 'os.path.dirname', (['__file__'], {}), '(__file__)\n', (94, 104), False, 'import os\n'), ((116, 147), 'os.path.join', 'os.path.join', (['here', '"""README.md"""'], {}), "(here, 'README.md')\n", (128, 147), False, 'import os\n'), ((1136, 1151), 'setuptools.find_packages', 'find_packages',... |
from py_dp.dispersion.binning import make_input_for_binning_with_freq, make_1d_abs_vel_bins, class_index_abs_log
from py_dp.dispersion.convert_to_time_process_with_freq import remove_duplicate
import numpy as np
from copy import copy
from py_dp.dispersion.mapping import mapping_v_sgn_repeat
import os
def test_mapping_... | [
"py_dp.dispersion.binning.make_input_for_binning_with_freq",
"py_dp.dispersion.binning.class_index_abs_log",
"numpy.unique",
"py_dp.dispersion.binning.make_1d_abs_vel_bins",
"numpy.log",
"os.path.join",
"numpy.array",
"os.path.dirname",
"py_dp.dispersion.convert_to_time_process_with_freq.remove_dupl... | [((413, 489), 'os.path.join', 'os.path.join', (['main_folder', '"""test_related_files"""', '"""particle_tracking_results"""'], {}), "(main_folder, 'test_related_files', 'particle_tracking_results')\n", (425, 489), False, 'import os\n'), ((592, 651), 'py_dp.dispersion.binning.make_input_for_binning_with_freq', 'make_inp... |
# Copyright 2017 Starbot Discord Project
#
# 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... | [
"api.database.init"
] | [((801, 816), 'api.database.init', 'database.init', ([], {}), '()\n', (814, 816), False, 'from api import database\n'), ((1062, 1077), 'api.database.init', 'database.init', ([], {}), '()\n', (1075, 1077), False, 'from api import database\n')] |
#!/usr/bin/env python
"""Automatically pre-renders a queue of videos for live streaming.
djmarinara does the following:
1) Polls a URL to obtain a list of URLs of songs.
2) Chooses a song URL at random.
3) Generates a video from the song, with visualizer output and song text (ID3 tags, etc.)
4) Manages playlist files ... | [
"zipfile.ZipFile",
"time.sleep",
"textwrap.wrap",
"os.walk",
"os.remove",
"re.split",
"os.listdir",
"shutil.move",
"pathlib.Path",
"subprocess.Popen",
"shutil.disk_usage",
"traceback.print_exc",
"urllib.request.urlopen",
"glob.glob",
"os.path.getsize",
"random.choice",
"hashlib.md5",... | [((2179, 2190), 'time.time', 'time.time', ([], {}), '()\n', (2188, 2190), False, 'import shutil, hashlib, random, time, zipfile, os, json, subprocess, codecs, re, glob, logging, tarfile, textwrap, traceback, sys\n'), ((5532, 5543), 'time.time', 'time.time', ([], {}), '()\n', (5541, 5543), False, 'import shutil, hashlib... |
import numpy as np
import tensorflow as tf
OUTPUT_PATH = "../events/"
def save():
input_node = tf.placeholder(shape=[None, 100, 100, 3], dtype=tf.float32)
net = tf.layers.conv2d(input_node, 32, (3, 3), strides=(2, 2), padding='same', name='conv_1')
net = tf.layers.conv2d(net, 32, (3, 3), strides=(1, 1), ... | [
"tensorflow.local_variables_initializer",
"numpy.alltrue",
"tensorflow.reset_default_graph",
"tensorflow.placeholder",
"tensorflow.train.Saver",
"tensorflow.Session",
"tensorflow.global_variables_initializer",
"tensorflow.layers.conv2d",
"tensorflow.train.import_meta_graph",
"tensorflow.get_defaul... | [((102, 161), 'tensorflow.placeholder', 'tf.placeholder', ([], {'shape': '[None, 100, 100, 3]', 'dtype': 'tf.float32'}), '(shape=[None, 100, 100, 3], dtype=tf.float32)\n', (116, 161), True, 'import tensorflow as tf\n'), ((172, 263), 'tensorflow.layers.conv2d', 'tf.layers.conv2d', (['input_node', '(32)', '(3, 3)'], {'st... |
from django.db.models.fields import SlugField
from rest_framework import serializers
from .models import Post, Comment, Like, CommentLike, Node#, InboxLike
from users.serializers import User_Profile, userPSerializer, UserSerializer, InboxSerializer
class PostSerializer(serializers.ModelSerializer):
#author... | [
"users.serializers.UserSerializer",
"users.serializers.userPSerializer"
] | [((550, 580), 'users.serializers.UserSerializer', 'UserSerializer', ([], {'read_only': '(True)'}), '(read_only=True)\n', (564, 580), False, 'from users.serializers import User_Profile, userPSerializer, UserSerializer, InboxSerializer\n'), ((2136, 2178), 'users.serializers.UserSerializer', 'UserSerializer', ([], {'many'... |
# Copyright 2020 The TensorFlow Probability Authors.
#
# 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 o... | [
"tensorflow.compat.v2.where",
"tensorflow.compat.v2.constant",
"tensorflow.compat.v2.is_tensor",
"tensorflow.compat.v2.nest.map_structure",
"tensorflow.compat.v2.math.abs",
"tensorflow.compat.v2.cast",
"tensorflow_probability.python.math.gradient.value_and_gradient",
"tensorflow.compat.v2.reshape",
... | [((2719, 2752), 'tensorflow.compat.v2.cast', 'tf.cast', (['result'], {'dtype': 'tf.float64'}), '(result, dtype=tf.float64)\n', (2726, 2752), True, 'import tensorflow.compat.v2 as tf\n'), ((2763, 2795), 'tensorflow.compat.v2.cast', 'tf.cast', (['truth'], {'dtype': 'tf.float64'}), '(truth, dtype=tf.float64)\n', (2770, 27... |
import requests
def get_all_data():
root = "https://raw.githubusercontent.com/patidarparas13/Sentiment-Analyzer-Tool/master/Datasets/"
data = requests.get(root + "imdb_labelled.txt").text.split("\n")
data += requests.get(root + "amazon_cells_labelled.txt").text.split("\n")
data += requests.get(root +... | [
"requests.get"
] | [((153, 193), 'requests.get', 'requests.get', (["(root + 'imdb_labelled.txt')"], {}), "(root + 'imdb_labelled.txt')\n", (165, 193), False, 'import requests\n'), ((223, 271), 'requests.get', 'requests.get', (["(root + 'amazon_cells_labelled.txt')"], {}), "(root + 'amazon_cells_labelled.txt')\n", (235, 271), False, 'impo... |
# Generated by Django 1.10.7 on 2017-05-22 15:06
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('case_search', '0006_remove_casesearchconfig__config'),
]
operations = [
migrations.CreateModel(
name='IgnorePatterns',
... | [
"django.db.models.AutoField",
"django.db.models.ManyToManyField",
"django.db.models.CharField"
] | [((902, 957), 'django.db.models.ManyToManyField', 'models.ManyToManyField', ([], {'to': '"""case_search.IgnorePatterns"""'}), "(to='case_search.IgnorePatterns')\n", (924, 957), False, 'from django.db import migrations, models\n'), ((356, 449), 'django.db.models.AutoField', 'models.AutoField', ([], {'auto_created': '(Tr... |
#import IndexerMod
import ThreadingMod
import threading
import time
##MyCraweler.Crawel()
##MyIndexer = IndexerMod.Indexer()
##MyIndexer.StartIndexing()
#MyThreads=[]
#MyCraweler.Crawel("https://moz.com/top500")
#MyCraweler.Crawel("https://www.facebook.com/")
#MyCraweler.Crawel("https://www.crummy.com/software/Beaut... | [
"ThreadingMod.myThread",
"threading.Lock",
"time.sleep"
] | [((717, 733), 'threading.Lock', 'threading.Lock', ([], {}), '()\n', (731, 733), False, 'import threading\n'), ((754, 770), 'threading.Lock', 'threading.Lock', ([], {}), '()\n', (768, 770), False, 'import threading\n'), ((1757, 1770), 'time.sleep', 'time.sleep', (['(2)'], {}), '(2)\n', (1767, 1770), False, 'import time\... |
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models
# Create your models here.
class Person(models.Model):
name_text = models.CharField(max_length=50)
status = models.IntegerField(default=0)
phone_number = models.CharField(max_length=15)
location = models.CharField(max_len... | [
"django.db.models.CharField",
"django.db.models.IntegerField"
] | [((163, 194), 'django.db.models.CharField', 'models.CharField', ([], {'max_length': '(50)'}), '(max_length=50)\n', (179, 194), False, 'from django.db import models\n'), ((205, 235), 'django.db.models.IntegerField', 'models.IntegerField', ([], {'default': '(0)'}), '(default=0)\n', (224, 235), False, 'from django.db impo... |