code stringlengths 22 1.05M | apis listlengths 1 3.31k | extract_api stringlengths 75 3.25M |
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# Copyright (c) 2019-2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# 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 ... | [
"numpy.clip",
"numpy.random.default_rng",
"math.cos",
"numpy.array",
"nvidia.dali.ops.readers.Caffe",
"numpy.linalg.norm",
"sequences_test_utils.ArgDesc",
"random.Random",
"numpy.max",
"math.sin",
"numpy.matmul",
"test_utils.compare_pipelines",
"sequences_test_utils.get_video_input_cases",
... | [((1055, 1097), 'os.path.join', 'os.path.join', (['test_data_root', '"""db"""', '"""lmdb"""'], {}), "(test_data_root, 'db', 'lmdb')\n", (1067, 1097), False, 'import os\n'), ((1829, 1849), 'numpy.linalg.norm', 'np.linalg.norm', (['axis'], {}), '(axis)\n', (1843, 1849), True, 'import numpy as np\n'), ((1919, 1934), 'math... |
#%%
import os
print(os.getcwd())
from Blocks import ReLU, SequentialNN, Dense, Hinge, SGD
from dataset_utils import load_mnist
import numpy as np
from convolution_layer import ConvLayer
from maxpool_layer import MaxPool2x2
from flatten_layer import FlattenLayer
import sys
def iterate_minibatches(x, y, batch_size=16, ... | [
"flatten_layer.FlattenLayer",
"numpy.mean",
"convolution_layer.ConvLayer",
"Blocks.SGD",
"Blocks.SequentialNN",
"maxpool_layer.MaxPool2x2",
"matplotlib.pyplot.twinx",
"os.getcwd",
"numpy.array",
"matplotlib.pyplot.figure",
"Blocks.Dense",
"Blocks.Hinge",
"Blocks.ReLU",
"sys.stdout.flush",
... | [((1357, 1364), 'Blocks.Hinge', 'Hinge', ([], {}), '()\n', (1362, 1364), False, 'from Blocks import ReLU, SequentialNN, Dense, Hinge, SGD\n'), ((1377, 1384), 'Blocks.SGD', 'SGD', (['nn'], {}), '(nn)\n', (1380, 1384), False, 'from Blocks import ReLU, SequentialNN, Dense, Hinge, SGD\n'), ((1456, 1489), 'numpy.array', 'np... |
# Normal-exponential using out-of-band probes
# normex: negative control probes
# noob: ‘out-of-band’ Infinium I probes
# Lib
import logging
import numpy as np
import pandas as pd
from statsmodels import robust
from scipy.stats import norm, lognorm
# App
from ..models import ControlType, ArrayType
from ..models.sketch... | [
"logging.getLogger",
"numpy.median",
"scipy.stats.norm",
"statsmodels.robust.mad",
"pandas.concat",
"pandas.DataFrame",
"numpy.maximum",
"numpy.seterr"
] | [((450, 477), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (467, 477), False, 'import logging\n'), ((3266, 3319), 'pandas.DataFrame', 'pd.DataFrame', (['(Rmeth + Runmeth)'], {'columns': "['mean_value']"}), "(Rmeth + Runmeth, columns=['mean_value'])\n", (3278, 3319), True, 'import pandas... |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import logging
from typing import List
import numpy as np
from pydantic import BaseModel, validator
from ray.rllib.agents.dqn import ApexTrain... | [
"logging.getLogger",
"numpy.median",
"compiler_gym.util.timer.Timer",
"pydantic.validator"
] | [((596, 623), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (613, 623), False, 'import logging\n'), ((4873, 4905), 'pydantic.validator', 'validator', (['"""benchmark"""'], {'pre': '(True)'}), "('benchmark', pre=True)\n", (4882, 4905), False, 'from pydantic import BaseModel, validator\n')... |
import re
from array import *
import fileinput
import sys, getopt
import csv
def main(argv):
vlog = ''
top = ''
try:
opts, args = getopt.getopt(argv,"hf:t:",["Vlog=","Top="])
except getopt.GetoptError:
print ('script_gen.py -r <verilog file> -t <top module name>')
sys.exit(2)
... | [
"getopt.getopt",
"sys.exit"
] | [((151, 198), 'getopt.getopt', 'getopt.getopt', (['argv', '"""hf:t:"""', "['Vlog=', 'Top=']"], {}), "(argv, 'hf:t:', ['Vlog=', 'Top='])\n", (164, 198), False, 'import sys, getopt\n'), ((306, 317), 'sys.exit', 'sys.exit', (['(2)'], {}), '(2)\n', (314, 317), False, 'import sys, getopt\n'), ((522, 532), 'sys.exit', 'sys.e... |
# Generated by Django 3.0.8 on 2020-11-16 19:09
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('hello', '0001_initial'),
]
operations = [
migrations.CreateModel(
name='Author',
fi... | [
"django.db.migrations.AlterUniqueTogether",
"django.db.migrations.DeleteModel",
"django.db.models.EmailField",
"django.db.models.ForeignKey",
"django.db.models.BooleanField",
"django.db.models.AutoField",
"django.db.models.DateTimeField",
"django.db.migrations.RemoveField",
"django.db.models.CharFie... | [((1389, 1455), 'django.db.migrations.AlterUniqueTogether', 'migrations.AlterUniqueTogether', ([], {'name': '"""guest"""', 'unique_together': 'None'}), "(name='guest', unique_together=None)\n", (1419, 1455), False, 'from django.db import migrations, models\n'), ((1500, 1556), 'django.db.migrations.RemoveField', 'migrat... |
import multiprocessing as mp
import pytest
from kawadi.text_search import SearchInText
@pytest.fixture()
def input_data():
text_to_find = "String distance algorithm"
text_to_search = """SIFT4 is a general purpose string distance algorithm inspired by JaroWinkler and Longest Common Subsequence. It was develo... | [
"pytest.fixture",
"kawadi.text_search.SearchInText",
"multiprocessing.cpu_count",
"pytest.raises"
] | [((92, 108), 'pytest.fixture', 'pytest.fixture', ([], {}), '()\n', (106, 108), False, 'import pytest\n'), ((678, 694), 'pytest.fixture', 'pytest.fixture', ([], {}), '()\n', (692, 694), False, 'import pytest\n'), ((1145, 1159), 'kawadi.text_search.SearchInText', 'SearchInText', ([], {}), '()\n', (1157, 1159), False, 'fr... |
import os
basedir = os.path.abspath(os.path.dirname(__file__))
class Config:
SECRET_KEY = os.environ.get('SECRET_KEY')
DEBUG = False
class DevelopmentConfig:
DEBUG = True
SQLALCHEMY_DATABASE_URI = 'postgresql+psycopg2://levy:Dadiesboy12@localhost/ronchezfitness'
SQLALCHEMY_TRACK_MODIFICATIONS =... | [
"os.path.join",
"os.path.dirname",
"os.environ.get"
] | [((37, 62), 'os.path.dirname', 'os.path.dirname', (['__file__'], {}), '(__file__)\n', (52, 62), False, 'import os\n'), ((97, 125), 'os.environ.get', 'os.environ.get', (['"""SECRET_KEY"""'], {}), "('SECRET_KEY')\n", (111, 125), False, 'import os\n'), ((401, 431), 'os.environ.get', 'os.environ.get', (['"""postgres_uri"""... |
import pandas as pd
from crosstab.mega_analysis.pivot_result_to_pixel_intensities import *
def lateralisation_to_pixel_intensities(all_combined_gifs, df,
semiology_term,
quantiles, method='non-linear', scale_factor=10,
... | [
"pandas.concat"
] | [((1344, 1420), 'pandas.concat', 'pd.concat', (['[a3, a2, pivot_result, all_combined_gifs_intensities]'], {'sort': '(False)'}), '([a3, a2, pivot_result, all_combined_gifs_intensities], sort=False)\n', (1353, 1420), True, 'import pandas as pd\n')] |
from overrides import overrides
import torch
from allennlp.common.checks import ConfigurationError
from allennlp.training.learning_rate_schedulers.learning_rate_scheduler import LearningRateScheduler
@LearningRateScheduler.register("polynomial_decay")
class PolynomialDecay(LearningRateScheduler):
"""
Impleme... | [
"allennlp.common.checks.ConfigurationError",
"allennlp.training.learning_rate_schedulers.learning_rate_scheduler.LearningRateScheduler.register"
] | [((204, 254), 'allennlp.training.learning_rate_schedulers.learning_rate_scheduler.LearningRateScheduler.register', 'LearningRateScheduler.register', (['"""polynomial_decay"""'], {}), "('polynomial_decay')\n", (234, 254), False, 'from allennlp.training.learning_rate_schedulers.learning_rate_scheduler import LearningRate... |
"""
TO DO:
1. Lot of edge cases not accounted for
2. Could use some unit testing scripts for sanity check
3. What are the bounds for years?
"""
import mysql
from mysql.connector import Error
import re
import numpy as np
def reject_outliers(data, m = 6.):
d = np.abs(data - np.median(data))
... | [
"re.sub",
"re.findall",
"mysql.connector.connect",
"numpy.median"
] | [((330, 342), 'numpy.median', 'np.median', (['d'], {}), '(d)\n', (339, 342), True, 'import numpy as np\n'), ((438, 544), 'mysql.connector.connect', 'mysql.connector.connect', ([], {'host': '"""127.0.0.1"""', 'port': '(3307)', 'database': '"""explorer_db"""', 'user': '"""root"""', 'password': '""""""'}), "(host='127.0.0... |
import unittest
from pyhmmer.easel import Alphabet
from pyhmmer.errors import UnexpectedError, AllocationError, EaselError, AlphabetMismatch
class TestErrors(unittest.TestCase):
def test_unexpected_error(self):
err = UnexpectedError(1, "p7_ReconfigLength")
self.assertEqual(repr(err), "Unexpected... | [
"pyhmmer.easel.Alphabet.amino",
"pyhmmer.errors.AllocationError",
"pyhmmer.easel.Alphabet.dna",
"pyhmmer.errors.UnexpectedError",
"pyhmmer.errors.EaselError",
"pyhmmer.easel.Alphabet.rna"
] | [((233, 272), 'pyhmmer.errors.UnexpectedError', 'UnexpectedError', (['(1)', '"""p7_ReconfigLength"""'], {}), "(1, 'p7_ReconfigLength')\n", (248, 272), False, 'from pyhmmer.errors import UnexpectedError, AllocationError, EaselError, AlphabetMismatch\n'), ((516, 545), 'pyhmmer.errors.AllocationError', 'AllocationError', ... |
import base64
STANDARD_ALPHABET = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ234567'
CUSTOM_ALPHABET = 'abcdefghjkmnprstuvwxyz0123456789'
ENCODE_TRANS = str.maketrans(STANDARD_ALPHABET, CUSTOM_ALPHABET)
DECODE_TRANS = str.maketrans(CUSTOM_ALPHABET, STANDARD_ALPHABET)
PADDING_LETTER = '='
def encode(buffer):
assert type(buffer) ... | [
"base64.b32encode"
] | [((399, 423), 'base64.b32encode', 'base64.b32encode', (['buffer'], {}), '(buffer)\n', (415, 423), False, 'import base64\n')] |
"""
A* grid planning
author: <NAME>(@Atsushi_twi)
<NAME> (<EMAIL>)
See Wikipedia article (https://en.wikipedia.org/wiki/A*_search_algorithm)
"""
import math
from node import Node
from obstacle_map import Position
class AStarPlanner:
def __init__(self, obstacle_map):
"""
Initialize gr... | [
"obstacle_map.Position",
"math.hypot",
"node.Node",
"math.sqrt"
] | [((698, 732), 'node.Node', 'Node', (['*args'], {'parent': 'self'}), '(*args, parent=self, **kwargs)\n', (702, 732), False, 'from node import Node\n'), ((3874, 3922), 'math.hypot', 'math.hypot', (['(pos_1.x - pos_2.x)', '(pos_1.y - pos_2.y)'], {}), '(pos_1.x - pos_2.x, pos_1.y - pos_2.y)\n', (3884, 3922), False, 'import... |
import datetime as dt
import pytest
from cuenca_validations.types import (
EntryType,
SavingCategory,
TransactionStatus,
WalletTransactionType,
)
from cuenca import BalanceEntry, Saving, WalletTransaction
@pytest.mark.vcr
def test_create_wallet_transaction():
wallet_id = 'LAvWUDH6OpQk-ber3E_zUEi... | [
"cuenca.WalletTransaction.retrieve",
"datetime.datetime.now",
"cuenca.WalletTransaction.all",
"datetime.timedelta",
"cuenca.WalletTransaction.create",
"cuenca.BalanceEntry.all"
] | [((337, 463), 'cuenca.WalletTransaction.create', 'WalletTransaction.create', ([], {'wallet_uri': 'f"""/savings/{wallet_id}"""', 'transaction_type': 'WalletTransactionType.deposit', 'amount': '(10000)'}), "(wallet_uri=f'/savings/{wallet_id}',\n transaction_type=WalletTransactionType.deposit, amount=10000)\n", (361, 4... |
'''
XlPy/inputs
___________
Validates input file selection, configurations, and matches file types.
:copyright: (c) 2015 The Regents of the University of California.
:license: GNU GPL, see licenses/GNU GPLv3.txt for more details.
'''
# load modules
import operator as op
from xldlib.onstart.main ... | [
"xldlib.xlpy.wrappers.threadmessage",
"xldlib.utils.logger.call",
"operator.attrgetter"
] | [((421, 449), 'xldlib.utils.logger.call', 'logger.call', (['"""xlpy"""', '"""debug"""'], {}), "('xlpy', 'debug')\n", (432, 449), False, 'from xldlib.utils import logger\n'), ((513, 557), 'xldlib.xlpy.wrappers.threadmessage', 'wrappers.threadmessage', (['"""Checking inputs..."""'], {}), "('Checking inputs...')\n", (535,... |
#!/usr/bin/env python
import rospy
from std_msgs.msg import Int32
from geometry_msgs.msg import PoseStamped, Pose
from styx_msgs.msg import TrafficLightArray, TrafficLight
from styx_msgs.msg import Lane
from sensor_msgs.msg import Image
from scipy.spatial import KDTree
import cv2
import yaml
import math
import numpy as... | [
"rospy.logerr",
"rospy.Subscriber",
"rospy.init_node",
"rospy.get_param",
"scipy.spatial.KDTree",
"std_msgs.msg.Int32",
"yaml.load",
"rospy.spin",
"geometry_msgs.msg.Pose",
"rospy.Publisher"
] | [((450, 480), 'rospy.init_node', 'rospy.init_node', (['"""tl_detector"""'], {}), "('tl_detector')\n", (465, 480), False, 'import rospy\n'), ((729, 769), 'rospy.get_param', 'rospy.get_param', (['"""/traffic_light_config"""'], {}), "('/traffic_light_config')\n", (744, 769), False, 'import rospy\n'), ((792, 816), 'yaml.lo... |
# Generated by Django 2.1.7 on 2019-03-29 20:19
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('e_secretary', '0009_profile'),
]
operations = [
migrations.AlterModelOptions(
name='professor',
options={'ordering':... | [
"django.db.models.EmailField",
"django.db.migrations.DeleteModel",
"django.db.models.BooleanField",
"django.db.migrations.AlterModelOptions",
"django.db.migrations.RemoveField",
"django.db.models.CharField"
] | [((228, 307), 'django.db.migrations.AlterModelOptions', 'migrations.AlterModelOptions', ([], {'name': '"""professor"""', 'options': "{'ordering': ['title']}"}), "(name='professor', options={'ordering': ['title']})\n", (256, 307), False, 'from django.db import migrations, models\n'), ((352, 412), 'django.db.migrations.R... |
"""
Implements Pseudo-outcome based Two-step Nets, namely the DR-learner, the PW-learner and the
RA-learner.
"""
# Author: <NAME>
from typing import Callable, Optional, Tuple
import jax.numpy as jnp
import numpy as onp
import pandas as pd
from sklearn.model_selection import StratifiedKFold
import catenets.logger as l... | [
"catenets.logger.debug",
"catenets.models.jax.model_utils.check_shape_1d_data",
"numpy.ones",
"catenets.models.jax.transformation_utils._get_transformation_function",
"sklearn.model_selection.StratifiedKFold",
"numpy.zeros",
"numpy.std",
"catenets.models.jax.base.train_output_net_only",
"numpy.round... | [((18080, 18124), 'catenets.models.jax.transformation_utils._get_transformation_function', '_get_transformation_function', (['transformation'], {}), '(transformation)\n', (18108, 18124), False, 'from catenets.models.jax.transformation_utils import DR_TRANSFORMATION, PW_TRANSFORMATION, RA_TRANSFORMATION, _get_transforma... |
import random
from plotting_utils import plot_spectrogram_to_numpy, image_for_logger, plot_to_image
import numpy as np
import tensorflow as tf
class GParrotLogger():
def __init__(self, logdir, ali_path='ali'):
# super(ParrotLogger, self).__init__(logdir)
self.writer = tf.summary.create_file_write... | [
"tensorflow.summary.scalar",
"tensorflow.summary.create_file_writer"
] | [((292, 329), 'tensorflow.summary.create_file_writer', 'tf.summary.create_file_writer', (['logdir'], {}), '(logdir)\n', (321, 329), True, 'import tensorflow as tf\n'), ((729, 786), 'tensorflow.summary.scalar', 'tf.summary.scalar', (['"""training.loss"""', 'train_loss', 'iteration'], {}), "('training.loss', train_loss, ... |
import pyspiel
game = pyspiel.load_game('bridge(use_double_dummy_result=false)')
line = '30 32 10 35 50 45 21 7 1 42 39 43 0 16 40 20 36 15 22 44 26 6 4 51 47 46 25 14 29 5 34 11 49 31 37 9 41 13 24 8 28 17 48 23 33 18 3 19 38 2 27 12 56 57 52 63 52 52 52 0 32 48 8 3 51 47 15 44 28 16 4 14 50 2 10 49 5 37 9 36 31 24 2... | [
"pyspiel.load_game"
] | [((22, 80), 'pyspiel.load_game', 'pyspiel.load_game', (['"""bridge(use_double_dummy_result=false)"""'], {}), "('bridge(use_double_dummy_result=false)')\n", (39, 80), False, 'import pyspiel\n')] |
import pytest
from gorgona.stages.cleaners import NumberCleaner
@pytest.fixture()
def setup_number_cleaner():
nc = NumberCleaner(
'',
'',
)
return nc
def test_positive_integer_single_digit_single_digit(setup_number_cleaner):
assert setup_number_cleaner("7") == ""
def test_positiv... | [
"pytest.fixture",
"gorgona.stages.cleaners.NumberCleaner"
] | [((68, 84), 'pytest.fixture', 'pytest.fixture', ([], {}), '()\n', (82, 84), False, 'import pytest\n'), ((122, 143), 'gorgona.stages.cleaners.NumberCleaner', 'NumberCleaner', (['""""""', '""""""'], {}), "('', '')\n", (135, 143), False, 'from gorgona.stages.cleaners import NumberCleaner\n')] |
#! /usr/bin/env python3
import argparse
import atexit
import json
import os
import subprocess
import sys
import time
import unittest
from test_device import (
Bitcoind,
DeviceEmulator,
DeviceTestCase,
TestDeviceConnect,
TestGetKeypool,
TestGetDescriptors,
TestSignTx,
)
from hwilib.devices... | [
"unittest.TestSuite",
"argparse.ArgumentParser",
"test_device.DeviceTestCase.parameterize",
"test_device.Bitcoind.create",
"json.dumps",
"unittest.TextTestRunner",
"time.sleep",
"hwilib.devices.digitalbitbox.send_plain",
"os.path.dirname",
"hwilib.devices.digitalbitbox.BitboxSimulator",
"os.unli... | [((7871, 7891), 'unittest.TestSuite', 'unittest.TestSuite', ([], {}), '()\n', (7889, 7891), False, 'import unittest\n'), ((8978, 9051), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {'description': '"""Test Digital Bitbox implementation"""'}), "(description='Test Digital Bitbox implementation')\n", (9001, ... |
import os
on_rtd = os.environ.get('READTHEDOCS', None) == 'True'
extensions = []
templates_path = ['_templates']
source_suffix = ['.rst', '.md']
master_doc = 'index'
project = u'fiubar'
copyright = u'2008-2018, <NAME>'
version = '2.0.0'
release = '2.0.0'
exclude_trees = ['_build']
pygments_style = 'sphinx'
html_stati... | [
"sphinx_rtd_theme.get_html_theme_path",
"os.environ.get"
] | [((20, 55), 'os.environ.get', 'os.environ.get', (['"""READTHEDOCS"""', 'None'], {}), "('READTHEDOCS', None)\n", (34, 55), False, 'import os\n'), ((443, 481), 'sphinx_rtd_theme.get_html_theme_path', 'sphinx_rtd_theme.get_html_theme_path', ([], {}), '()\n', (479, 481), False, 'import sphinx_rtd_theme\n')] |
from io import StringIO
import itertools
import numpy as np
import numpy.ma as ma
inputfile = './input/day9.txt'
# inputfile = StringIO('''2199943210
# 3987894921
# 9856789892
# 8767896789
# 9899965678''')
def neighbors(ar, i, j):
return {ar[i-1,j],
ar[i+1,j],
ar[i,j-1],
ar[i... | [
"numpy.pad",
"numpy.genfromtxt"
] | [((333, 381), 'numpy.genfromtxt', 'np.genfromtxt', (['inputfile'], {'dtype': '"""i"""', 'delimiter': '(1)'}), "(inputfile, dtype='i', delimiter=1)\n", (346, 381), True, 'import numpy as np\n'), ((409, 456), 'numpy.pad', 'np.pad', (['a', '((1, 1), (1, 1))'], {'constant_values': '(10)'}), '(a, ((1, 1), (1, 1)), constant_... |
"""
Copyright 2019 BBC. Licensed under the terms of the Apache License 2.0.
"""
from unittest.mock import Mock
import pytest
from google.cloud.bigquery import Client
from foxglove.connectors.bigquery import BigQueryConnector
@pytest.fixture
def fake_bq_client():
return Mock(spec=Client(project='test_project')... | [
"foxglove.connectors.bigquery.BigQueryConnector",
"google.cloud.bigquery.Client"
] | [((406, 472), 'foxglove.connectors.bigquery.BigQueryConnector', 'BigQueryConnector', (['"""test_dataset_id"""', '"""test_table_id"""', '"""test_role"""'], {}), "('test_dataset_id', 'test_table_id', 'test_role')\n", (423, 472), False, 'from foxglove.connectors.bigquery import BigQueryConnector\n'), ((697, 763), 'foxglov... |
import sys
#"splchar":["!","@","#","$",".",",",":","%","^","*"]
splchar=[chr(i) for i in range(33,48)]#ASCII spl charecter range from 33-48 and58-65#and i here is the mapping expression ie the thing thet is executed evry iteration
splchar1=[chr(i) for i in range(58,65)]#Instead of explicit declaration of for loop ... | [
"sys.stdin.read"
] | [((733, 749), 'sys.stdin.read', 'sys.stdin.read', ([], {}), '()\n', (747, 749), False, 'import sys\n')] |
__author__ = 'ashvinder'
import re
import os
import gc
import logger
import time
from TestInput import TestInputSingleton
from backup.backup_base import BackupBaseTest
from remote.remote_util import RemoteMachineShellConnection
from couchbase_helper.documentgenerator import BlobGenerator
from couchbase_helper.documentg... | [
"re.search",
"view.spatialquerytests.SimpleDataSet",
"couchbase_helper.cluster.Cluster",
"memcached.helper.kvstore.KVStore",
"membase.helper.spatial_helper.SpatialHelper",
"remote.remote_util.RemoteMachineShellConnection",
"time.sleep",
"logger.Logger.get_logger",
"couchbase_helper.documentgenerator... | [((1093, 1168), 'couchbase_helper.documentgenerator.BlobGenerator', 'BlobGenerator', (['"""testdata"""', '"""testdata-"""', 'self.value_size'], {'end': 'self.num_items'}), "('testdata', 'testdata-', self.value_size, end=self.num_items)\n", (1106, 1168), False, 'from couchbase_helper.documentgenerator import BlobGenerat... |
"""Check the feasibility of a bipartite graph by using SSLAP's feasibility module"""
import numpy as np
from sslap import hopcroft_solve
# All 3 methods will use the same input bipartite graph:
# i = 0 connects to j = 0, 1
# i = 1 connects to j = 1, 2
# i = 2 connects to j = 1, 4
# i = 3 connects to j = 2
# i = 4 con... | [
"numpy.array",
"numpy.ones",
"sslap.hopcroft_solve"
] | [((494, 523), 'sslap.hopcroft_solve', 'hopcroft_solve', ([], {'lookup': 'lookup'}), '(lookup=lookup)\n', (508, 523), False, 'from sslap import hopcroft_solve\n'), ((690, 713), 'sslap.hopcroft_solve', 'hopcroft_solve', ([], {'mat': 'mat'}), '(mat=mat)\n', (704, 713), False, 'from sslap import hopcroft_solve\n'), ((752, ... |
from django.db import models
# Create your models here.
class HeadlineListing(models.Model):
headline_text = models.CharField(max_length=500)
accessed = models.DateTimeField()
source_url = models.CharField(max_length=200)
author = models.CharField(default="", max_length=200)
source = models.CharFie... | [
"django.db.models.DateTimeField",
"django.db.models.CharField"
] | [((114, 146), 'django.db.models.CharField', 'models.CharField', ([], {'max_length': '(500)'}), '(max_length=500)\n', (130, 146), False, 'from django.db import models\n'), ((162, 184), 'django.db.models.DateTimeField', 'models.DateTimeField', ([], {}), '()\n', (182, 184), False, 'from django.db import models\n'), ((202,... |
import matplotlib.pyplot as plt
import pandas as pd
def main():
times = [ 1, 100, 365, 365*20, 365*100, 100000]
df = pd.read_csv('tmp.csv')
df_ini = pd.read_csv("initial_value.csv")
xan_measured = (df_ini["distance"], df_ini["XAn"])
df_m = pd.read_csv('measured_value.csv')
measured_da... | [
"matplotlib.pyplot.figure",
"pandas.read_csv"
] | [((126, 148), 'pandas.read_csv', 'pd.read_csv', (['"""tmp.csv"""'], {}), "('tmp.csv')\n", (137, 148), True, 'import pandas as pd\n'), ((167, 199), 'pandas.read_csv', 'pd.read_csv', (['"""initial_value.csv"""'], {}), "('initial_value.csv')\n", (178, 199), True, 'import pandas as pd\n'), ((271, 304), 'pandas.read_csv', '... |
import os
import re
import csv
import sys
import json
import yaml
import time
import socket
import connexion
import postgresql as psql
from flask import current_app
from urllib.parse import urlencode
from hashlib import md5
from bokeh.embed import server_document
from .processes import fetch_process, is_running, proce... | [
"csv.DictReader",
"re.compile",
"subprocess.run",
"json.dumps",
"os.path.splitext",
"postgresql.open",
"os.path.basename",
"json.load"
] | [((378, 405), 're.compile', 're.compile', (['"""^\\\\d*\\\\.\\\\d+$"""'], {}), "('^\\\\d*\\\\.\\\\d+$')\n", (388, 405), False, 'import re\n'), ((418, 440), 're.compile', 're.compile', (['"""^-?\\\\d+$"""'], {}), "('^-?\\\\d+$')\n", (428, 440), False, 'import re\n'), ((454, 472), 're.compile', 're.compile', (['"""^NA$""... |
import numpy as np
import chainer
from chainer import cuda, Function, gradient_check, Variable
from chainer import optimizers, serializers, utils
from chainer import Link, Chain, ChainList
import chainer.functions as F
import chainer.links as L
class normalNN(Chain):
def __init__(self, dim):
super().__ini... | [
"chainer.links.BatchNormalization",
"chainer.links.Linear",
"chainer.links.Convolution2D"
] | [((340, 358), 'chainer.links.Linear', 'L.Linear', (['dim', '(100)'], {}), '(dim, 100)\n', (348, 358), True, 'import chainer.links as L\n'), ((375, 391), 'chainer.links.Linear', 'L.Linear', (['(100)', '(1)'], {}), '(100, 1)\n', (383, 391), True, 'import chainer.links as L\n'), ((674, 705), 'chainer.links.Linear', 'L.Lin... |
""" This script is needed to convert gdb scripts from commands to documentation
"""
import os
def convert_commands_to_docs():
commands_dir = os.getcwd() + "/numba_dppy/examples/debug/commands"
examples = os.listdir(commands_dir)
os.chdir(commands_dir + "/docs")
for file in examples:
if file !=... | [
"os.path.exists",
"os.listdir",
"os.getcwd",
"os.chdir",
"os.remove"
] | [((214, 238), 'os.listdir', 'os.listdir', (['commands_dir'], {}), '(commands_dir)\n', (224, 238), False, 'import os\n'), ((243, 275), 'os.chdir', 'os.chdir', (["(commands_dir + '/docs')"], {}), "(commands_dir + '/docs')\n", (251, 275), False, 'import os\n'), ((147, 158), 'os.getcwd', 'os.getcwd', ([], {}), '()\n', (156... |
import json
import requests
from typing import List
from konlpy.tag import Okt
from requests.models import Response
class OktTokenizer:
"""
A POS-tagger based tokenizer functor. Note that these are just examples. The `phrases` function usually gives a better result than an ordinary POS tokenizer.
... | [
"konlpy.tag.Okt",
"json.loads",
"requests.post"
] | [((467, 472), 'konlpy.tag.Okt', 'Okt', ([], {}), '()\n', (470, 472), False, 'from konlpy.tag import Okt\n'), ((1098, 1137), 'requests.post', 'requests.post', (['self.endpoint'], {'data': 'body'}), '(self.endpoint, data=body)\n', (1111, 1137), False, 'import requests\n'), ((1166, 1186), 'json.loads', 'json.loads', (['re... |
from .alexnet import alexnet_V2
import tensorflow.compat.v1 as tf
import tensorflow.contrib.slim as slim
from utils import montage_tf
from .lci_nets import patch_inpainter, patch_discriminator
import tensorflow.contrib as contrib
# Average pooling params for imagenet linear classifier experiments
AVG_POOL_PARAMS = {'... | [
"tensorflow.compat.v1.ones_like",
"tensorflow.compat.v1.shape",
"tensorflow.compat.v1.pad",
"tensorflow.contrib.layers.variance_scaling_initializer",
"tensorflow.compat.v1.losses.mean_squared_error",
"tensorflow.compat.v1.concat",
"tensorflow.compat.v1.nn.relu",
"tensorflow.compat.v1.split",
"tensor... | [((7919, 7980), 'tensorflow.compat.v1.ones', 'tf.ones', (['[im_shape[0], patch_sz[0], patch_sz[1], im_shape[3]]'], {}), '([im_shape[0], patch_sz[0], patch_sz[1], im_shape[3]])\n', (7926, 7980), True, 'import tensorflow.compat.v1 as tf\n'), ((7998, 8106), 'tensorflow.compat.v1.pad', 'tf.pad', (['patch_mask', '[[0, 0], [... |
#!/usr/bin/env python
# -*- coding:utf-8 -*-
"""
Author: pirogue
Purpose: 白名单端口表操作
Site: http://pirogue.org
Created: 2018-08-03 17:32:54
"""
from dbs.initdb import DBSession
from dbs.models.Whiteport import Whiteport
from sqlalchemy import desc,asc
from sqlalchemy.exc import InvalidRequestError
# import s... | [
"dbs.models.Whiteport.Whiteport"
] | [((884, 912), 'dbs.models.Whiteport.Whiteport', 'Whiteport', ([], {'dst_port': 'dst_port'}), '(dst_port=dst_port)\n', (893, 912), False, 'from dbs.models.Whiteport import Whiteport\n')] |
#
# Copyright (C) 2018 <NAME> <<EMAIL>>
# License: MIT
#
r"""Singleton class
.. versionadded:: 0.9.8
- Add to make a kind of manager instancne later to manage plugins.
"""
from __future__ import absolute_import
import threading
class Singleton(object):
"""Singleton utilizes __new__ special method.
.. no... | [
"threading.RLock"
] | [((428, 445), 'threading.RLock', 'threading.RLock', ([], {}), '()\n', (443, 445), False, 'import threading\n')] |
import tvm
from functools import reduce
from ..utils import to_int, to_int_or_None
def get_need_tile(need_tile):
return [True if x.value == 1 else False for x in need_tile]
def get_factors(split_factor_entities):
return [[x.value for x in factors.factors] for factors in split_factor_entities]
def tile_axis(st... | [
"functools.reduce"
] | [((3933, 3982), 'functools.reduce', 'reduce', (['(lambda x, y: x + y)', 'leveled_axes[:-1]', '[]'], {}), '(lambda x, y: x + y, leveled_axes[:-1], [])\n', (3939, 3982), False, 'from functools import reduce\n'), ((4008, 4059), 'functools.reduce', 'reduce', (['(lambda x, y: x + y)', 'reduce_leveled_axes', '[]'], {}), '(la... |
"""
mcpython - a minecraft clone written in python licenced under the MIT-licence
(https://github.com/mcpython4-coding/core)
Contributors: uuk, xkcdjerry (inactive)
Based on the game of fogleman (https://github.com/fogleman/Minecraft), licenced under the MIT-licence
Original game "minecraft" by Mojang Studios (www.m... | [
"mcpython.engine.ResourceLoader.read_image",
"mcpython.engine.logger.print_exception",
"asyncio.get_event_loop"
] | [((4030, 4091), 'mcpython.engine.logger.print_exception', 'logger.print_exception', (['"""failed to add alpha composite layer"""'], {}), "('failed to add alpha composite layer')\n", (4052, 4091), False, 'from mcpython.engine import logger\n'), ((2844, 2888), 'mcpython.engine.ResourceLoader.read_image', 'ResourceLoader.... |
from setuptools import setup
setup(name='goofy',
version='0.1',
description='A goofy ebay bot.',
url='github.com/elcolumbio/goofy',
author='<NAME>',
author_email='<EMAIL>',
license='Apache License, Version 2.0 (the "License")',
packages=['goofy'])
| [
"setuptools.setup"
] | [((30, 257), 'setuptools.setup', 'setup', ([], {'name': '"""goofy"""', 'version': '"""0.1"""', 'description': '"""A goofy ebay bot."""', 'url': '"""github.com/elcolumbio/goofy"""', 'author': '"""<NAME>"""', 'author_email': '"""<EMAIL>"""', 'license': '"""Apache License, Version 2.0 (the "License")"""', 'packages': "['g... |
import unittest
import translator
class TestEnglishToFrench(unittest.TestCase):
def test_love(self):
self.assertEqual(translator.english_to_french('Love'), 'Amour')
def test_sun(self):
self.assertEqual(translator.english_to_french('Sun'), 'Soleil')
def test_null(self):
self.as... | [
"unittest.main",
"translator.french_to_english",
"translator.english_to_french"
] | [((972, 987), 'unittest.main', 'unittest.main', ([], {}), '()\n', (985, 987), False, 'import unittest\n'), ((131, 167), 'translator.english_to_french', 'translator.english_to_french', (['"""Love"""'], {}), "('Love')\n", (159, 167), False, 'import translator\n'), ((228, 263), 'translator.english_to_french', 'translator.... |
from flask import (Flask, jsonify)
from gevent import (pywsgi, sleep)
from geventwebsocket.handler import WebSocketHandler
from . import __version__
from .logs import logger
class FlaskApp(object):
def __init__(self, host='', port=8080):
self.app = Flask(__name__)
self._register_routes()
... | [
"flask.jsonify",
"gevent.sleep",
"gevent.pywsgi.WSGIServer",
"flask.Flask"
] | [((264, 279), 'flask.Flask', 'Flask', (['__name__'], {}), '(__name__)\n', (269, 279), False, 'from flask import Flask, jsonify\n'), ((419, 509), 'gevent.pywsgi.WSGIServer', 'pywsgi.WSGIServer', (['(self._host, self._port)', 'self.app'], {'handler_class': 'WebSocketHandler'}), '((self._host, self._port), self.app, handl... |
from django.views.generic import ListView, CreateView, UpdateView
from django.utils.decorators import method_decorator
from django.contrib.admin.views.decorators import staff_member_required
from django.shortcuts import get_object_or_404, redirect, reverse
from django.urls import reverse_lazy
from django.contrib import... | [
"django.http.JsonResponse",
"django.contrib.messages.warning",
"django.shortcuts.get_object_or_404",
"product.models.Product.objects.filter",
"django.utils.decorators.method_decorator",
"product.models.Product.broswer.active",
"datetime.datetime.now",
"django.shortcuts.reverse",
"django_tables2.Requ... | [((716, 772), 'django.utils.decorators.method_decorator', 'method_decorator', (['staff_member_required'], {'name': '"""dispatch"""'}), "(staff_member_required, name='dispatch')\n", (732, 772), False, 'from django.utils.decorators import method_decorator\n'), ((2079, 2135), 'django.utils.decorators.method_decorator', 'm... |
import caffe
import torch
import numpy as np
import argparse
from collections import OrderedDict
from torch.autograd import Variable
import torch.nn as nn
def arg_parse():
parser = argparse.ArgumentParser()
parser.add_argument('--model', '-m', default='alexnet')
parser.add_argument('--decimal', '-d', defa... | [
"numpy.prod",
"collections.OrderedDict",
"torchvision.models.inception.inception_v3",
"argparse.ArgumentParser",
"torchvision.models.resnet.resnet18",
"torch.Tensor",
"numpy.testing.assert_almost_equal",
"caffe.Net",
"torchvision.models.alexnet.alexnet"
] | [((187, 212), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {}), '()\n', (210, 212), False, 'import argparse\n'), ((836, 849), 'collections.OrderedDict', 'OrderedDict', ([], {}), '()\n', (847, 849), False, 'from collections import OrderedDict\n'), ((1695, 1708), 'collections.OrderedDict', 'OrderedDict', ([... |
# coding=utf-8
import logging
import numpy as np
import pandas as pd
from sklearn import metrics
from sklearn.linear_model import LogisticRegression
from sklearn.multiclass import OneVsRestClassifier
from sklearn.preprocessing import LabelBinarizer
from sklearn.utils import shuffle
logging.basicConfig(format='%(level... | [
"logging.basicConfig",
"sklearn.preprocessing.LabelBinarizer",
"pandas.read_csv",
"numpy.where",
"sklearn.utils.shuffle",
"numpy.argmax",
"numpy.isin",
"sklearn.linear_model.LogisticRegression",
"numpy.array",
"numpy.linalg.norm"
] | [((285, 361), 'logging.basicConfig', 'logging.basicConfig', ([], {'format': '"""%(levelname)s:%(message)s"""', 'level': 'logging.ERROR'}), "(format='%(levelname)s:%(message)s', level=logging.ERROR)\n", (304, 361), False, 'import logging\n'), ((538, 581), 'pandas.read_csv', 'pd.read_csv', (['lbl_path'], {'header': 'None... |
import os
import glob
import argparse as ap
import shutil as sh
import re
def main():
parser = ap.ArgumentParser(description="""Uses minimum basis term file to extract the data for a
simulation that used the minimum number of basis terms for each frequency""")
parser.add_argument('min_file',type=str,help="... | [
"argparse.ArgumentParser",
"os.makedirs",
"os.path.join",
"os.path.isfile",
"shutil.copytree",
"os.path.isdir",
"os.path.basename",
"os.path.abspath",
"glob.glob",
"re.search"
] | [((100, 279), 'argparse.ArgumentParser', 'ap.ArgumentParser', ([], {'description': '"""Uses minimum basis term file to extract the data for a\n simulation that used the minimum number of basis terms for each frequency"""'}), '(description=\n """Uses minimum basis term file to extract the data for a\n simulatio... |
# turingmachine.py - implementation of the Turing machine model
#
# Copyright 2014 <NAME>.
#
# This file is part of turingmachine.
#
# turingmachine is free software: you can redistribute it and/or modify it
# under the terms of the GNU General Public License as published by the
# Free Software Foundation, either versi... | [
"logging.getLogger",
"logging.Formatter",
"logging.StreamHandler"
] | [((951, 978), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (968, 978), False, 'import logging\n'), ((989, 1012), 'logging.StreamHandler', 'logging.StreamHandler', ([], {}), '()\n', (1010, 1012), False, 'import logging\n'), ((1025, 1073), 'logging.Formatter', 'logging.Formatter', (['"""[... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Jul 5 23:04:10 2020
@author: y3
749e8aa818a63c61c31acd7ee948d6d8
"""
import requests
api_address = "https://api.openweathermap.org/data/2.5/weather?q="
api_key_url = "&APPID=749e8aa818a63c61c31acd7ee948d6d8"
city_name = "Bet shemesh,IL"
weather_data... | [
"requests.get"
] | [((323, 374), 'requests.get', 'requests.get', (['(api_address + city_name + api_key_url)'], {}), '(api_address + city_name + api_key_url)\n', (335, 374), False, 'import requests\n')] |
#!/usr/bin/python3
import os
import click
import sys
import csv
import time
import pandas as pd
import country_converter as coco
import hashlib
import phonenumbers
from tqdm import tqdm
from uszipcode import SearchEngine
HEADER_TRANSLATIONS = {
"email1": "Email",
"phone1": "Phone",
"person_country": "Count... | [
"csv.DictReader",
"pandas.read_csv",
"country_converter.convert",
"csv.Sniffer",
"sys.exit",
"os.path.exists",
"tqdm.tqdm.write",
"click.option",
"click.command",
"click.argument",
"hashlib.sha256",
"click.confirm",
"uszipcode.SearchEngine",
"os.path.isfile",
"os.path.dirname",
"phonen... | [((14903, 15046), 'click.command', 'click.command', ([], {'help': '"""Generates a Google Ads Customer Match compliant CSV file from a (potentially large) CSV file in another format."""'}), "(help=\n 'Generates a Google Ads Customer Match compliant CSV file from a (potentially large) CSV file in another format.'\n ... |
import io
from PIL import Image
from torchvision import models
import torch
import torchvision.transforms as transforms
import torch.nn as nn
import torch.nn.functional as F
import urllib
import os
def get_model_from_global_agent():
global_model = models.squeezenet1_1(pretrained=True)
global_model.classifier[1... | [
"torchvision.transforms.CenterCrop",
"torch.device",
"urllib.request.urlretrieve",
"io.BytesIO",
"torch.nn.Conv2d",
"torchvision.transforms.Normalize",
"torchvision.transforms.Resize",
"torchvision.transforms.ToTensor",
"torchvision.models.squeezenet1_1",
"os.remove"
] | [((253, 290), 'torchvision.models.squeezenet1_1', 'models.squeezenet1_1', ([], {'pretrained': '(True)'}), '(pretrained=True)\n', (273, 290), False, 'from torchvision import models\n'), ((324, 376), 'torch.nn.Conv2d', 'nn.Conv2d', (['(512)', '(5)'], {'kernel_size': '(1, 1)', 'stride': '(1, 1)'}), '(512, 5, kernel_size=(... |
"""
main(terminal).py
Author: <NAME>
"""
from solver import print_grid, solve
def main():
sudoku_grid = [ [0,8,0, 0,0,0, 2,0,0],
[0,0,0, 0,8,4, 0,9,0],
[0,0,6, 3,2,0, 0,1,0],
[0,9,7, 0,0,0, 0,8,0],
... | [
"solver.solve",
"solver.print_grid"
] | [((872, 895), 'solver.print_grid', 'print_grid', (['sudoku_grid'], {}), '(sudoku_grid)\n', (882, 895), False, 'from solver import print_grid, solve\n'), ((973, 987), 'solver.solve', 'solve', (['copy', '(9)'], {}), '(copy, 9)\n', (978, 987), False, 'from solver import print_grid, solve\n'), ((992, 1008), 'solver.print_g... |
import subprocess
import os
import requests
import pyttsx3
from bs4 import BeautifulSoup
class Commander:
def __init__(self):
self.confirm = ["yes", "ok", "go on", "sure", "do it", "yeah", "yaa", "Imm", "confirm", "of course"]
self.cancel = ["nope", "no", "noo", "not yet", "don't", "do not", "stop... | [
"pyttsx3.init",
"bs4.BeautifulSoup",
"requests.get"
] | [((2034, 2048), 'pyttsx3.init', 'pyttsx3.init', ([], {}), '()\n', (2046, 2048), False, 'import pyttsx3\n'), ((1282, 1299), 'requests.get', 'requests.get', (['URL'], {}), '(URL)\n', (1294, 1299), False, 'import requests\n'), ((1319, 1361), 'bs4.BeautifulSoup', 'BeautifulSoup', (['content.text', '"""html.parser"""'], {})... |
# Generated by Django 2.2.12 on 2020-04-29 18:42
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('cmsplugin_remote_form', '0004_remoteform_notification_emails'),
]
operations = [
migrations.AlterField(
model_name='extrafield'... | [
"django.db.models.CharField"
] | [((370, 1138), 'django.db.models.CharField', 'models.CharField', ([], {'choices': "[('CharField', 'CharField'), ('BooleanField', 'BooleanField'), (\n 'EmailField', 'EmailField'), ('DecimalField', 'DecimalField'), (\n 'FloatField', 'FloatField'), ('IntegerField', 'IntegerField'), (\n 'FileField', 'FileField'), ... |
import csv
import cv2
import numpy as np
import pandas as pd
import sys
from datetime import datetime
from numpy.random import RandomState
import keras
import tensorflow as tf
from keras.models import Sequential
from keras.callbacks import ModelCheckpoint
from keras.layers import Flatten, Dense, Lambda, Cropping2D, C... | [
"keras.optimizers.Adam",
"keras.layers.Conv2D",
"keras.layers.Flatten",
"pandas.read_csv",
"cv2.flip",
"keras.layers.Lambda",
"tensorflow.multiply",
"keras.callbacks.TensorBoard",
"keras.models.Sequential",
"numpy.array",
"keras.layers.Dropout",
"keras.layers.Dense",
"keras.layers.MaxPool2D"... | [((14357, 14369), 'keras.models.Sequential', 'Sequential', ([], {}), '()\n', (14367, 14369), False, 'from keras.models import Sequential\n'), ((15282, 15386), 'pandas.read_csv', 'pd.read_csv', (['"""data/driving_log.csv"""'], {'names': "['center', 'left', 'right', 'measurement', '1', '2', '3']"}), "('data/driving_log.c... |
import torch
from torch import nn
from configs import ANCHOR_SIZES
class PostRes(nn.Module):
def __init__(self, n_in, n_out, stride=1):
super(PostRes, self).__init__()
self.conv1 = nn.Conv3d(n_in, n_out, kernel_size=3, stride=stride, padding=1)
self.bn1 = nn.BatchNorm3d(n_out)
self... | [
"torch.nn.ReLU",
"torch.nn.BatchNorm3d",
"torch.nn.ConvTranspose3d",
"torch.nn.Dropout3d",
"torch.nn.Sequential",
"torch.nn.MaxPool3d",
"torch.nn.MaxUnpool3d",
"torch.cat",
"torch.nn.Conv3d"
] | [((203, 266), 'torch.nn.Conv3d', 'nn.Conv3d', (['n_in', 'n_out'], {'kernel_size': '(3)', 'stride': 'stride', 'padding': '(1)'}), '(n_in, n_out, kernel_size=3, stride=stride, padding=1)\n', (212, 266), False, 'from torch import nn\n'), ((286, 307), 'torch.nn.BatchNorm3d', 'nn.BatchNorm3d', (['n_out'], {}), '(n_out)\n', ... |
from django.urls import path
from rest_framework_simplejwt.views import (
TokenObtainPairView,
TokenRefreshView,
TokenVerifyView,
)
from . views import *
urlpatterns = [
path('register/', UserRegisterView.as_view()),
path('logout/', LogoutView.as_view()),
path('token/', TokenObtainPairView.as_... | [
"rest_framework_simplejwt.views.TokenVerifyView.as_view",
"rest_framework_simplejwt.views.TokenObtainPairView.as_view",
"rest_framework_simplejwt.views.TokenRefreshView.as_view"
] | [((297, 326), 'rest_framework_simplejwt.views.TokenObtainPairView.as_view', 'TokenObtainPairView.as_view', ([], {}), '()\n', (324, 326), False, 'from rest_framework_simplejwt.views import TokenObtainPairView, TokenRefreshView, TokenVerifyView\n'), ((382, 408), 'rest_framework_simplejwt.views.TokenRefreshView.as_view', ... |
from __future__ import print_function
import os
import argparse
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.utils.data import DataLoader, Dataset
from collections import OrderedDict
import numpy as np
from edgeml_pytorch.trainer.drocc_trainer import DROCCTra... | [
"numpy.mean",
"edgeml_pytorch.trainer.drocc_trainer.DROCCTrainer",
"torch.nn.ReLU",
"os.path.exists",
"numpy.ones",
"torch.set_printoptions",
"argparse.ArgumentParser",
"os.makedirs",
"numpy.std",
"os.path.join",
"torch.from_numpy",
"torch.is_tensor",
"torch.tensor",
"torch.cuda.is_availab... | [((2779, 2807), 'numpy.ones', 'np.ones', (['train_data.shape[0]'], {}), '(train_data.shape[0])\n', (2786, 2807), True, 'import numpy as np\n'), ((3052, 3074), 'numpy.mean', 'np.mean', (['train_data', '(0)'], {}), '(train_data, 0)\n', (3059, 3074), True, 'import numpy as np\n'), ((3082, 3103), 'numpy.std', 'np.std', (['... |
from django import forms
class ContactForm(forms.Form):
user_name = forms.CharField(max_length=60, label='', required=True, widget=forms.TextInput(attrs={'placeholder': '<NAME>'}))
user_email = forms.EmailField(label='', required=True)
message = forms.CharField(label='', required=True, widget=forms.Texta... | [
"django.forms.Textarea",
"django.forms.EmailField",
"django.forms.TextInput"
] | [((205, 246), 'django.forms.EmailField', 'forms.EmailField', ([], {'label': '""""""', 'required': '(True)'}), "(label='', required=True)\n", (221, 246), False, 'from django import forms\n'), ((138, 186), 'django.forms.TextInput', 'forms.TextInput', ([], {'attrs': "{'placeholder': '<NAME>'}"}), "(attrs={'placeholder': '... |
#coding:utf-8
import ftplib
import os
from ...core import constants
from . import base
class Configurer(base.Configurer):
def __init__(self,config):
self._config = config
self._key = constants.KEY_CONFIGURER_INSTANCES
self._results = {}
self.instance = ftplib.FTP()
self.inst... | [
"os.path.exists",
"os.listdir",
"ftplib.FTP",
"os.makedirs",
"os.path.join",
"os.path.isdir"
] | [((290, 302), 'ftplib.FTP', 'ftplib.FTP', ([], {}), '()\n', (300, 302), False, 'import ftplib\n'), ((1235, 1259), 'os.path.isdir', 'os.path.isdir', (['localpath'], {}), '(localpath)\n', (1248, 1259), False, 'import os\n'), ((1282, 1303), 'os.listdir', 'os.listdir', (['localpath'], {}), '(localpath)\n', (1292, 1303), Fa... |
# Name: load.py
# Date: June 2019
# Function: goes trough a bookmark file checking the status of each URL
# Input: bookmark file in json format
# Output: new text and json files including those URLs according with their status
import os
import ast
try:
import requests
except:
sys.stderr.write("%s: Please inst... | [
"simplejson.load",
"requests.head",
"os.mkdir"
] | [((915, 940), 'simplejson.load', 'json.load', (['input_filename'], {}), '(input_filename)\n', (924, 940), True, 'import simplejson as json\n'), ((1172, 1189), 'os.mkdir', 'os.mkdir', (['DIRNAME'], {}), '(DIRNAME)\n', (1180, 1189), False, 'import os\n'), ((2281, 2311), 'requests.head', 'requests.head', (['url'], {'timeo... |
from tir import Webapp
import unittest
from tir.technologies.apw_internal import ApwInternal
import datetime
import time
DateSystem = datetime.datetime.today().strftime('%d/%m/%Y')
DateVal = datetime.datetime(2120, 5, 17)
"""-------------------------------------------------------------------
/*/{Protheus.doc} PLSA809T... | [
"datetime.datetime",
"unittest.main",
"time.sleep",
"tir.Webapp",
"datetime.datetime.today"
] | [((192, 222), 'datetime.datetime', 'datetime.datetime', (['(2120)', '(5)', '(17)'], {}), '(2120, 5, 17)\n', (209, 222), False, 'import datetime\n'), ((4574, 4589), 'unittest.main', 'unittest.main', ([], {}), '()\n', (4587, 4589), False, 'import unittest\n'), ((135, 160), 'datetime.datetime.today', 'datetime.datetime.to... |
from __future__ import print_function
from P13pt.mascril.measurement import MeasurementBase
from P13pt.mascril.parameter import Sweep, String, Folder, Boolean
from P13pt.drivers.bilt import Bilt, BiltVoltageSource, BiltVoltMeter
from P13pt.drivers.zilockin import ZILockin
import time
import numpy as np
import os
clas... | [
"P13pt.mascril.parameter.Folder",
"P13pt.mascril.parameter.String",
"P13pt.drivers.zilockin.ZILockin",
"P13pt.mascril.parameter.Sweep",
"time.strftime",
"os.path.join",
"time.sleep",
"P13pt.mascril.parameter.Boolean",
"P13pt.drivers.bilt.Bilt",
"P13pt.drivers.bilt.BiltVoltageSource",
"P13pt.driv... | [((383, 395), 'P13pt.mascril.parameter.Sweep', 'Sweep', (['[0.0]'], {}), '([0.0])\n', (388, 395), False, 'from P13pt.mascril.parameter import Sweep, String, Folder, Boolean\n'), ((413, 425), 'P13pt.mascril.parameter.Sweep', 'Sweep', (['[0.0]'], {}), '([0.0])\n', (418, 425), False, 'from P13pt.mascril.parameter import S... |
# NOTE: Following example requires boto3 package.
import boto3
from InquirerPy import prompt
from InquirerPy.exceptions import InvalidArgument
from InquirerPy.validator import PathValidator
client = boto3.client("s3")
def get_bucket(_):
return [bucket["Name"] for bucket in client.list_buckets()["Buckets"]]
de... | [
"InquirerPy.prompt",
"InquirerPy.validator.PathValidator",
"boto3.client"
] | [((201, 219), 'boto3.client', 'boto3.client', (['"""s3"""'], {}), "('s3')\n", (213, 219), False, 'import boto3\n'), ((1646, 1677), 'InquirerPy.prompt', 'prompt', (['questions'], {'vi_mode': '(True)'}), '(questions, vi_mode=True)\n', (1652, 1677), False, 'from InquirerPy import prompt\n'), ((911, 926), 'InquirerPy.valid... |
#!/bin/sh
''''[ ! -z $VIRTUAL_ENV ] && exec python -u -- "$0" ${1+"$@"}; command -v python3 > /dev/null && exec python3 -u -- "$0" ${1+"$@"}; exec python2 -u -- "$0" ${1+"$@"} # '''
import sys
import os
import argparse
HERE = os.path.dirname(__file__)
ROOT = os.path.abspath(os.path.join(HERE, ".."))
sys.path.insert(0... | [
"sys.path.insert",
"argparse.ArgumentParser",
"os.path.join",
"os.path.dirname",
"paella.Setup.__init__"
] | [((228, 253), 'os.path.dirname', 'os.path.dirname', (['__file__'], {}), '(__file__)\n', (243, 253), False, 'import os\n'), ((303, 327), 'sys.path.insert', 'sys.path.insert', (['(0)', 'ROOT'], {}), '(0, ROOT)\n', (318, 327), False, 'import sys\n'), ((1104, 1167), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([]... |
import pyHook
from threading import Timer
import win32gui
import logging
class blockInput():
def OnKeyboardEvent(self,event):
return False
def OnMouseEvent(self,event):
return False
def unblock(self):
logging.info(" -- Unblock!")
if self.t.is_alive():
... | [
"logging.basicConfig",
"win32gui.PumpWaitingMessages",
"threading.Timer",
"pyHook.HookManager",
"logging.info",
"time.sleep",
"time.time"
] | [((992, 1031), 'logging.basicConfig', 'logging.basicConfig', ([], {'level': 'logging.INFO'}), '(level=logging.INFO)\n', (1011, 1031), False, 'import logging\n'), ((1108, 1119), 'time.time', 'time.time', ([], {}), '()\n', (1117, 1119), False, 'import time\n'), ((1238, 1259), 'logging.info', 'logging.info', (['"""Done.""... |
"""
This python code demonstrates an edge-based active contour model as an application of the
Distance Regularized Level Set Evolution (DRLSE) formulation in the following paper:
<NAME>, <NAME>, <NAME>, <NAME>, "Distance Regularized Level Set Evolution and Its Application to Image Segmentation",
IEEE Trans. Ima... | [
"numpy.ones",
"numpy.max",
"skimage.io.imread",
"lv_set.find_lsf.find_lsf",
"numpy.min",
"lv_set.show_fig.draw_all"
] | [((2340, 2358), 'lv_set.find_lsf.find_lsf', 'find_lsf', ([], {}), '(**params)\n', (2348, 2358), False, 'from lv_set.find_lsf import find_lsf\n'), ((2387, 2419), 'lv_set.show_fig.draw_all', 'draw_all', (['phi', "params['img']", '(10)'], {}), "(phi, params['img'], 10)\n", (2395, 2419), False, 'from lv_set.show_fig import... |
#!/usr/bin/python
# vim: set fileencoding=utf-8 :
# Copyright 2019 Google Inc. All rights reserved.
#
# 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/LIC... | [
"sys.path.insert",
"distutils.dir_util.copy_tree",
"zipfile.ZipFile",
"yt_api.remove_uploaded_videos",
"time.sleep",
"yt_api.start_video_upload",
"bottle.get",
"os.walk",
"os.path.exists",
"os.listdir",
"argparse.ArgumentParser",
"bottle.post",
"json.dumps",
"os.path.split",
"os.path.isd... | [((931, 987), 'sys.path.insert', 'sys.path.insert', (['(0)', "(program_dir + '/third_party/bottle/')"], {}), "(0, program_dir + '/third_party/bottle/')\n", (946, 987), False, 'import sys\n'), ((1611, 1652), 'bottle.post', 'post', (['"""/api/youtube_auth/get_device_code"""'], {}), "('/api/youtube_auth/get_device_code')\... |
#!/usr/bin/env python
# coding: utf-8
# # Lab 02
#
# ## Solving a system of nonlinear equations
#
# ### <NAME>, Б01-818
#
# IV.12.7.д
# $$\begin{cases} x^7 - 5x^2y^4 + 1510 = 0 \\ y^3 - 3x^4y - 105 = 0 \end{cases}$$
# $$\begin{cases} x_{n+1} = \sqrt{\frac{x_n^7 + 1510}{5y_n^4}} \\ y_{n+1} = \sqrt[3]{3x_{n}^4y_{n}... | [
"logging.getLogger",
"numpy.abs",
"numpy.sqrt",
"pandas.DataFrame",
"numpy.cbrt"
] | [((3476, 3495), 'logging.getLogger', 'logging.getLogger', ([], {}), '()\n', (3493, 3495), False, 'import logging\n'), ((3984, 4097), 'pandas.DataFrame', 'pd.DataFrame', (["{'Начальное приближение': x_init_vec_fpi, 'Результат': fpi_results,\n 'Итераций': fpi_iterations}"], {}), "({'Начальное приближение': x_init_vec_... |
#!/usr/bin/env python3
"""PenIn setup script."""
from setuptools import setup, find_packages
from penin.core.version import get_version
VERSION = get_version()
readme_file = open("README.md", "r")
LONG_DESCRIPTION = readme_file.read()
readme_file.close()
setup(
name="penin",
version=VERSION,
description=... | [
"setuptools.find_packages",
"penin.core.version.get_version"
] | [((147, 160), 'penin.core.version.get_version', 'get_version', ([], {}), '()\n', (158, 160), False, 'from penin.core.version import get_version\n'), ((600, 645), 'setuptools.find_packages', 'find_packages', ([], {'exclude': "['ez_setup', 'tests*']"}), "(exclude=['ez_setup', 'tests*'])\n", (613, 645), False, 'from setup... |
# -*- coding: utf-8 -*-
"""
Copyright (c) 2012 University of Oxford
Permission is hereby granted, free of charge, to any person obtaining
a copy of this software and associated documentation files (the
"Software"), to deal in the Software without restriction, including
without limitation the rights to use, copy, modif... | [
"ConfigParser.ConfigParser",
"repoze.who.classifiers.default_request_classifier",
"pylons.config.has_key"
] | [((1530, 1565), 'repoze.who.classifiers.default_request_classifier', 'default_request_classifier', (['environ'], {}), '(environ)\n', (1556, 1565), False, 'from repoze.who.classifiers import default_request_classifier\n'), ((1834, 1867), 'pylons.config.has_key', 'config.has_key', (['"""who.config_file"""'], {}), "('who.... |
#!/usr/bin/env python3
#------------------------------------------------------------------------------#
# Filename: apod_linux_config.py / \ #
# Project : APOD_Linux | () | #
# Date : 06/23/2021 ... | [
"logging.debug",
"gi.repository.Gtk.Grid",
"gi.repository.Gtk.Button",
"gi.repository.Gtk.Adjustment",
"gi.repository.Gtk.main",
"os.path.exists",
"gi.repository.Gtk.Stack",
"gi.repository.Gtk.SpinButton",
"subprocess.Popen",
"gi.repository.Gtk.Window.__init__",
"os.path.expanduser",
"gi.requi... | [((607, 639), 'gi.require_version', 'gi.require_version', (['"""Gtk"""', '"""3.0"""'], {}), "('Gtk', '3.0')\n", (625, 639), False, 'import gi\n'), ((778, 801), 'os.path.expanduser', 'os.path.expanduser', (['"""~"""'], {}), "('~')\n", (796, 801), False, 'import os\n'), ((812, 855), 'os.path.join', 'os.path.join', (['hom... |
import vtk
class Scene(object):
def __init__(self):
self.sceneSources = list()
self.sceneMappers = list()
self.sceneActors = list()
self.sceneLights = list()
self.sceneSources.append(vtk.vtkCubeSource())
self.sceneSources[-1].SetXLength(50000)
self.sceneSou... | [
"vtk.vtkJPEGReader",
"vtk.vtkTexture",
"vtk.vtkPolyDataMapper",
"vtk.vtkActor",
"vtk.vtkLight",
"vtk.vtkCubeSource",
"vtk.vtkTextureMapToPlane"
] | [((561, 580), 'vtk.vtkJPEGReader', 'vtk.vtkJPEGReader', ([], {}), '()\n', (578, 580), False, 'import vtk\n'), ((722, 738), 'vtk.vtkTexture', 'vtk.vtkTexture', ([], {}), '()\n', (736, 738), False, 'import vtk\n'), ((882, 908), 'vtk.vtkTextureMapToPlane', 'vtk.vtkTextureMapToPlane', ([], {}), '()\n', (906, 908), False, '... |
import sys
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import random
from cobras_ts.querier import Querier
from IPython import display
def _query_yes_no(question, default="yes"):
"""Ask a yes/no question via raw_input() and return their answer.
"question" is a string that is presented t... | [
"matplotlib.pyplot.imshow",
"random.sample",
"matplotlib.pyplot.gcf",
"matplotlib.image.imread",
"matplotlib.pyplot.clf",
"IPython.display.clear_output",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.subplots_adjust",
"sys.stdout.write"
] | [((990, 1025), 'sys.stdout.write', 'sys.stdout.write', (['(question + prompt)'], {}), '(question + prompt)\n', (1006, 1025), False, 'import sys\n'), ((1490, 1518), 'matplotlib.pyplot.figure', 'plt.figure', ([], {'figsize': '(20, 20)'}), '(figsize=(20, 20))\n', (1500, 1518), True, 'import matplotlib.pyplot as plt\n'), (... |
import os
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from dataclasses import dataclass
from argparse import ArgumentParser
from tqdm import tqdm
from torch.utils.data import DataLoader
from data import VCTKAudio
from model import WaveNet
def set_option():
parse... | [
"data.VCTKAudio",
"os.makedirs",
"argparse.ArgumentParser",
"torch.nn.CrossEntropyLoss",
"os.path.join",
"torch.utils.data.DataLoader",
"model.WaveNet"
] | [((324, 340), 'argparse.ArgumentParser', 'ArgumentParser', ([], {}), '()\n', (338, 340), False, 'from argparse import ArgumentParser\n'), ((2195, 2235), 'os.makedirs', 'os.makedirs', (['opt.ckpt_dir'], {'exist_ok': '(True)'}), '(opt.ckpt_dir, exist_ok=True)\n', (2206, 2235), False, 'import os\n'), ((2288, 2356), 'data.... |
import os
def remove_comments_and_crlf(inp_path, comment_string=';', overwrite=False):
tmpfilename = os.path.splitext(os.path.basename(inp_path))[0] + '_mod.inp'
tmpfilepath = os.path.join(os.path.dirname(inp_path), tmpfilename)
with open (inp_path) as oldf:
with open(tmpfilepath, 'w') as newf:
... | [
"os.path.dirname",
"os.rename",
"os.path.basename",
"os.remove"
] | [((199, 224), 'os.path.dirname', 'os.path.dirname', (['inp_path'], {}), '(inp_path)\n', (214, 224), False, 'import os\n'), ((916, 935), 'os.remove', 'os.remove', (['inp_path'], {}), '(inp_path)\n', (925, 935), False, 'import os\n'), ((944, 976), 'os.rename', 'os.rename', (['tmpfilepath', 'inp_path'], {}), '(tmpfilepath... |
import re
import pprint
pp = pprint.PrettyPrinter(indent=4)
from sys import version_info # py3, for checking type of input
def combine_messages(messages):
""" Combines messages that have one or more integers in them, such as
"trial001" "trial002", into a single message like "trial# (#=1-2)".
Thi... | [
"re.sub",
"re.findall",
"pprint.PrettyPrinter"
] | [((29, 59), 'pprint.PrettyPrinter', 'pprint.PrettyPrinter', ([], {'indent': '(4)'}), '(indent=4)\n', (49, 59), False, 'import pprint\n'), ((2601, 2624), 're.findall', 're.findall', (['"""\\\\d+"""', 'msg'], {}), "('\\\\d+', msg)\n", (2611, 2624), False, 'import re\n'), ((2959, 2984), 're.sub', 're.sub', (['pattern', '"... |
# Generated by Django 3.0.1 on 2020-01-02 22:21
from django.db import migrations, models
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='CustomerProfile',
fields=[
('id', models.Au... | [
"django.db.models.AutoField",
"django.db.models.CharField",
"django.db.models.BinaryField"
] | [((311, 404), 'django.db.models.AutoField', 'models.AutoField', ([], {'auto_created': '(True)', 'primary_key': '(True)', 'serialize': '(False)', 'verbose_name': '"""ID"""'}), "(auto_created=True, primary_key=True, serialize=False,\n verbose_name='ID')\n", (327, 404), False, 'from django.db import migrations, models\... |
import logging
logging.basicConfig(level=logging.INFO)
from flask import Flask
from application.config import Config
app = Flask(__name__)
app.config.from_object(Config)
from application.models.classifiers.CNNClassifier import CNNClassifier
from application.models.classifiers.MLPClassifier import MLPClassifier
fro... | [
"logging.basicConfig",
"application.utils.get_urls_list",
"flask.Flask",
"application.models.classifiers.MLPClassifier.MLPClassifier",
"application.models.classifiers.CNNClassifier.CNNClassifier",
"application.models.detectors.CasClasDetector.CasClasDetector",
"application.models.classifiers.NaiveBayesC... | [((15, 54), 'logging.basicConfig', 'logging.basicConfig', ([], {'level': 'logging.INFO'}), '(level=logging.INFO)\n', (34, 54), False, 'import logging\n'), ((127, 142), 'flask.Flask', 'Flask', (['__name__'], {}), '(__name__)\n', (132, 142), False, 'from flask import Flask\n'), ((661, 694), 'logging.info', 'logging.info'... |
import numpy as np
import unittest
from itertools import product
from ml_techniques.svm import *
class PermutationDataTest(unittest.TestCase):
def testpropershape(self):
data = np.random.random((10, 4))
labels = np.random.randint(0, 2, 10)*2-1
data_per = permut_data(data)
self.a... | [
"numpy.random.random",
"itertools.product",
"numpy.random.randint",
"numpy.random.randn",
"numpy.random.permutation"
] | [((193, 218), 'numpy.random.random', 'np.random.random', (['(10, 4)'], {}), '((10, 4))\n', (209, 218), True, 'import numpy as np\n'), ((3285, 3315), 'numpy.random.random', 'np.random.random', (['(n, n_feats)'], {}), '((n, n_feats))\n', (3301, 3315), True, 'import numpy as np\n'), ((5136, 5166), 'numpy.random.random', '... |
import collections
from numpy.core.defchararray import lower
import streamlit as st
import numpy as np
import pandas as pd
from pages import utils
def app():
st.title("Data Storyteller Application")
st.markdown("## Data Upload")
# Upload the dataset and save as csv
st.markdown("### Upload ... | [
"streamlit.markdown",
"pandas.read_csv",
"streamlit.file_uploader",
"streamlit.write",
"streamlit.button",
"streamlit.dataframe",
"pandas.read_excel",
"pandas.DataFrame",
"streamlit.set_option",
"pages.utils.genMetaData",
"streamlit.title"
] | [((173, 213), 'streamlit.title', 'st.title', (['"""Data Storyteller Application"""'], {}), "('Data Storyteller Application')\n", (181, 213), True, 'import streamlit as st\n'), ((219, 248), 'streamlit.markdown', 'st.markdown', (['"""## Data Upload"""'], {}), "('## Data Upload')\n", (230, 248), True, 'import streamlit as... |
# -*- coding:utf-8 -*-
import paddle.fluid as fluid
def cnn_net(data,
dict_dim,
emb_dim=128,
hid_dim=128,
hid_dim2=96,
class_dim=2,
win_size=3):
"""
Conv net
"""
# embedding layer
emb = fluid.layers.embedding(
input=da... | [
"paddle.fluid.ParamAttr"
] | [((377, 431), 'paddle.fluid.ParamAttr', 'fluid.ParamAttr', ([], {'name': '"""@HUB_senta_cnn@embedding_0.w_0"""'}), "(name='@HUB_senta_cnn@embedding_0.w_0')\n", (392, 431), True, 'import paddle.fluid as fluid\n'), ((644, 702), 'paddle.fluid.ParamAttr', 'fluid.ParamAttr', ([], {'name': '"""@HUB_senta_cnn@sequence_conv_0.... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import runpy
import os
import pytest
import glob
THIS_FILES_DIR_PATH = os.path.realpath(os.path.dirname(__file__))
def get_paths_of_scripts():
exclude_sub_strings = ["do_not_execute"]
plot_script_paths = glob.glob(
os.path.join(
os.path.dirna... | [
"os.path.dirname",
"runpy.run_path"
] | [((136, 161), 'os.path.dirname', 'os.path.dirname', (['__file__'], {}), '(__file__)\n', (151, 161), False, 'import os\n'), ((878, 943), 'runpy.run_path', 'runpy.run_path', (['path_script'], {'init_globals': '{}', 'run_name': '"""__main__"""'}), "(path_script, init_globals={}, run_name='__main__')\n", (892, 943), False,... |
# -*- coding: utf-8 -*-
"""
Inspired by:
* https://gist.github.com/shirriff/c9fb5d98e6da79d9a772#file-merkle-py
* https://github.com/richardkiss/pycoin
"""
from __future__ import absolute_import, division, unicode_literals
from builtins import range
import binascii
import hashlib
def merkleroot(hashes):
... | [
"hashlib.sha256"
] | [((773, 814), 'hashlib.sha256', 'hashlib.sha256', (['(hashes[i] + hashes[i + 1])'], {}), '(hashes[i] + hashes[i + 1])\n', (787, 814), False, 'import hashlib\n'), ((850, 882), 'hashlib.sha256', 'hashlib.sha256', (['first_round_hash'], {}), '(first_round_hash)\n', (864, 882), False, 'import hashlib\n')] |
from django.contrib import admin
from simple_history.admin import SimpleHistoryAdmin
from .models import MainMetadata
# Register your models here.
admin.site.register(MainMetadata, SimpleHistoryAdmin) | [
"django.contrib.admin.site.register"
] | [((149, 202), 'django.contrib.admin.site.register', 'admin.site.register', (['MainMetadata', 'SimpleHistoryAdmin'], {}), '(MainMetadata, SimpleHistoryAdmin)\n', (168, 202), False, 'from django.contrib import admin\n')] |
"""
The CPTPState class and supporting functionality.
"""
#***************************************************************************************************
# Copyright 2015, 2019 National Technology & Engineering Solutions of Sandia, LLC (NTESS).
# Under the terms of Contract DE-NA0003525 with NTESS, the U.S. Govern... | [
"numpy.trace",
"numpy.sqrt",
"pygsti.modelmembers.states.densestate.DenseState.__init__",
"numpy.rollaxis",
"numpy.array",
"numpy.einsum",
"numpy.imag",
"numpy.take",
"numpy.real",
"numpy.dot",
"numpy.empty",
"pygsti.evotypes.Evotype.cast",
"pygsti.modelmembers.states.state.State._to_vector"... | [((2705, 2727), 'pygsti.modelmembers.states.state.State._to_vector', '_State._to_vector', (['vec'], {}), '(vec)\n', (2722, 2727), True, 'from pygsti.modelmembers.states.state import State as _State\n'), ((2903, 2937), 'numpy.rollaxis', '_np.rollaxis', (['self.basis_mxs', '(0)', '(3)'], {}), '(self.basis_mxs, 0, 3)\n', ... |
# -*- coding: utf-8 -*-
"""
Created on Fri Apr 30 11:58:20 2021
@author: <NAME>
"""
import sys
sys.path.append("...")
import macheval as me
class IMSettingsHandler(me.SettingsHandler):
def getSettings(x):
return NotImplementedError #TODO Implement settings functionality
| [
"sys.path.append"
] | [((97, 119), 'sys.path.append', 'sys.path.append', (['"""..."""'], {}), "('...')\n", (112, 119), False, 'import sys\n')] |
import datetime as dt
import json
import os
import pandas as pd
from sqlalchemy import Column, Integer, String, Float, DateTime, Boolean, func
from iotfunctions.preprocessor import BaseTransformer
from iotfunctions.bif import IoTExpression
from iotfunctions.metadata import EntityType, make_sample_entity
from iotfunctio... | [
"iotfunctions.db.Database",
"iotfunctions.estimator.SimpleAnomaly",
"iotfunctions.metadata.make_sample_entity",
"iotfunctions.bif.IoTExpression"
] | [((652, 685), 'iotfunctions.db.Database', 'Database', ([], {'credentials': 'credentials'}), '(credentials=credentials)\n', (660, 685), False, 'from iotfunctions.db import Database\n'), ((799, 906), 'iotfunctions.metadata.make_sample_entity', 'make_sample_entity', ([], {'db': 'db', 'schema': 'db_schema', 'float_cols': '... |
# Copyright 2017 Red Hat, Inc. <http://www.redhat.com>
#
# 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 b... | [
"rally.task.validation.add",
"rally_openstack.task.scenario.configure"
] | [((875, 945), 'rally.task.validation.add', 'validation.add', (['"""required_services"""'], {'services': '[consts.Service.GNOCCHI]'}), "('required_services', services=[consts.Service.GNOCCHI])\n", (889, 945), False, 'from rally.task import validation\n'), ((947, 1016), 'rally.task.validation.add', 'validation.add', (['"... |
import queue
import textwrap
import threading
import time
import urllib.parse
import pychromecast
def create_notify_url(text: str, lang: str, ttsspeed: float):
payload = {
"ie": "UTF-8",
"q": text,
"tl": lang,
"total": 1,
"idx": 0,
"textlen": ... | [
"time.sleep",
"pychromecast.get_chromecasts",
"textwrap.wrap",
"threading.Thread",
"queue.Queue",
"time.time"
] | [((684, 729), 'textwrap.wrap', 'textwrap.wrap', (['text'], {'width': 'max_split_text_len'}), '(text, width=max_split_text_len)\n', (697, 729), False, 'import textwrap\n'), ((3656, 3712), 'pychromecast.get_chromecasts', 'pychromecast.get_chromecasts', (['tries', 'retry_wait', 'timeout'], {}), '(tries, retry_wait, timeou... |
from taurex.log import Logger
class LinesReader:
def __init__(self, lines):
self._lines = lines
self._count = 0
def skip(self, num=1):
self._count += num
def read_int(self, skip=1):
val = int(self._lines[self._count])
self.skip(skip)
return val
... | [
"re.findall",
"os.path.join"
] | [((1800, 1844), 'os.path.join', 'os.path.join', (['broadener_path', 'self._filename'], {}), '(broadener_path, self._filename)\n', (1812, 1844), False, 'import os\n'), ((6644, 6668), 're.findall', 're.findall', (['"""\\\\d+"""', 'form'], {}), "('\\\\d+', form)\n", (6654, 6668), False, 'import re\n')] |
import os
import json
from flask_sqlalchemy import SQLAlchemy
from flask import Flask, request, jsonify
from flask.views import MethodView
from flask.ext.cors import CORS
from database import ElasticStorage, RedisClient
from article import Article as ESArticle
app = Flask(__name__)
CORS(app)
#sql_config = json.loads(... | [
"os.getenv",
"flask.Flask",
"database.RedisClient.get_instance",
"flask.ext.cors.CORS",
"flask.request.data.decode",
"database.ElasticStorage.get_instance",
"article.Article.get",
"flask_sqlalchemy.SQLAlchemy",
"flask.jsonify"
] | [((268, 283), 'flask.Flask', 'Flask', (['__name__'], {}), '(__name__)\n', (273, 283), False, 'from flask import Flask, request, jsonify\n'), ((284, 293), 'flask.ext.cors.CORS', 'CORS', (['app'], {}), '(app)\n', (288, 293), False, 'from flask.ext.cors import CORS\n'), ((534, 549), 'flask_sqlalchemy.SQLAlchemy', 'SQLAlch... |
import os
from qaviton.utils import filer
from qaviton.utils import path
from qaviton.utils.operating_system import s
from qaviton.version import __version__
cwd = os.getcwd()
examples = path.of(__file__)('examples')
def initial_msg(f):
def dec(*args, **kwargs):
print("""
QAVITON VERSION {}
... | [
"qaviton.utils.filer.find_replace",
"qaviton.utils.path.of",
"os.getcwd",
"qaviton.utils.filer.os.path.exists",
"os.system",
"qaviton.utils.filer.copy_directory"
] | [((165, 176), 'os.getcwd', 'os.getcwd', ([], {}), '()\n', (174, 176), False, 'import os\n'), ((188, 205), 'qaviton.utils.path.of', 'path.of', (['__file__'], {}), '(__file__)\n', (195, 205), False, 'from qaviton.utils import path\n'), ((4869, 4913), 'qaviton.utils.filer.os.path.exists', 'filer.os.path.exists', (["(cwd +... |
"""
Tests for the reference loader for Buyback Authorizations.
"""
from functools import partial
from unittest import TestCase
import blaze as bz
from blaze.compute.core import swap_resources_into_scope
from contextlib2 import ExitStack
import pandas as pd
from six import iteritems
from zipline.pipeline.common import... | [
"zipline.pipeline.factors.events.BusinessDaysSinceCashBuybackAuth",
"zipline.utils.test_utils.tmp_asset_finder",
"blaze.compute.core.swap_resources_into_scope",
"contextlib2.ExitStack",
"zipline.pipeline.factors.events.BusinessDaysSinceShareBuybackAuth",
"functools.partial",
"pandas.DataFrame",
"six.i... | [((1243, 1317), 'pandas.DataFrame', 'pd.DataFrame', (['{SHARE_COUNT_FIELD_NAME: [1, 15], CASH_FIELD_NAME: [10, 20]}'], {}), '({SHARE_COUNT_FIELD_NAME: [1, 15], CASH_FIELD_NAME: [10, 20]})\n', (1255, 1317), True, 'import pandas as pd\n'), ((1367, 1441), 'pandas.DataFrame', 'pd.DataFrame', (['{SHARE_COUNT_FIELD_NAME: [7,... |
import pymongo
from bson.objectid import ObjectId
# mongo 增加
def main():
client = pymongo.MongoClient(host='172.16.17.32', port=27017)
db = client.test
collection = db.students
# 插入一条数据
student = {
'id': '20170101',
'name': 'Kevin',
'age': 20,
'gender': 'male'
... | [
"pymongo.MongoClient"
] | [((89, 141), 'pymongo.MongoClient', 'pymongo.MongoClient', ([], {'host': '"""172.16.17.32"""', 'port': '(27017)'}), "(host='172.16.17.32', port=27017)\n", (108, 141), False, 'import pymongo\n')] |
#
# Copyright (C) 2014 Red Hat, 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 wr... | [
"gerrymander.model.ModelEvent.from_json",
"gerrymander.model.ModelChange.from_json"
] | [((3660, 3687), 'gerrymander.model.ModelChange.from_json', 'ModelChange.from_json', (['line'], {}), '(line)\n', (3681, 3687), False, 'from gerrymander.model import ModelChange\n'), ((4476, 4502), 'gerrymander.model.ModelEvent.from_json', 'ModelEvent.from_json', (['line'], {}), '(line)\n', (4496, 4502), False, 'from ger... |
import rospy
import numpy as np
import cv2
class ScalarStable(object):
"""Represents a stabilized scalar"""
def __init__(self,
x=.0,
vx=.0,
p_cov=.03, m_cov=.01,
time=None):
"""ScalarStabilized constructor"""
self.x = x
... | [
"numpy.array",
"rospy.Time",
"numpy.float32",
"cv2.KalmanFilter"
] | [((411, 433), 'cv2.KalmanFilter', 'cv2.KalmanFilter', (['(2)', '(1)'], {}), '(2, 1)\n', (427, 433), False, 'import cv2\n'), ((522, 552), 'numpy.array', 'np.array', (['[[1, 1]]', 'np.float32'], {}), '([[1, 1]], np.float32)\n', (530, 552), True, 'import numpy as np\n'), ((1073, 1116), 'numpy.array', 'np.array', (['[[self... |
#!/usr/bin/env python
import os
import sys
import sqlite3
import pandas as pd
import numpy as np
from scraper import create_data_folder, read_config
from collections import OrderedDict
def main():
"""
Mainly for debugging purposes.
"""
config_file = read_config()
# Pick a file
try:
c... | [
"pandas.read_sql_query",
"scraper.read_config",
"collections.OrderedDict",
"os.listdir",
"sqlite3.connect",
"pandas.read_csv",
"os.path.join",
"pandas.set_option",
"sys.exc_info",
"scraper.create_data_folder",
"numpy.savetxt",
"pandas.DataFrame"
] | [((269, 282), 'scraper.read_config', 'read_config', ([], {}), '()\n', (280, 282), False, 'from scraper import create_data_folder, read_config\n'), ((701, 755), 'scraper.create_data_folder', 'create_data_folder', (["config_file['extracted_data_path']"], {}), "(config_file['extracted_data_path'])\n", (719, 755), False, '... |
import nengo
import pytest
from nengo_spinnaker.builder import Model
from nengo_spinnaker.builder.ports import OutputPort, InputPort
from nengo_spinnaker.node_io import ethernet as ethernet_io
from nengo_spinnaker.operators import SDPReceiver, SDPTransmitter
@pytest.mark.parametrize("transmission_period", [0.001, 0.... | [
"nengo.Network",
"nengo_spinnaker.node_io.ethernet.Ethernet",
"nengo.Ensemble",
"nengo_spinnaker.builder.Model",
"nengo.Node",
"pytest.mark.parametrize",
"nengo.Connection"
] | [((263, 325), 'pytest.mark.parametrize', 'pytest.mark.parametrize', (['"""transmission_period"""', '[0.001, 0.002]'], {}), "('transmission_period', [0.001, 0.002])\n", (286, 325), False, 'import pytest\n'), ((518, 579), 'nengo_spinnaker.node_io.ethernet.Ethernet', 'ethernet_io.Ethernet', ([], {'transmission_period': 't... |
from rest_framework import serializers
from api.model.foodComment import FoodComment
from api.model.food import Food
from django.contrib.auth.models import User
from api.serializer.user import UserSerializer
class FoodCommentSerializer(serializers.ModelSerializer):
comment = serializers.CharField(max_length=255... | [
"api.model.food.Food.objects.all",
"rest_framework.serializers.CharField",
"django.contrib.auth.models.User.objects.all",
"api.serializer.user.UserSerializer"
] | [((284, 321), 'rest_framework.serializers.CharField', 'serializers.CharField', ([], {'max_length': '(255)'}), '(max_length=255)\n', (305, 321), False, 'from rest_framework import serializers\n'), ((334, 404), 'rest_framework.serializers.CharField', 'serializers.CharField', ([], {'max_length': '(255)', 'allow_null': '(T... |