code stringlengths 22 1.05M | apis listlengths 1 3.31k | extract_api stringlengths 75 3.25M |
|---|---|---|
import app.ai.model as model
from app.ai.genetic import Genetic
import app.ai.plot as plot
import time
import datetime
import numpy as np
import torch as t
import threading
import sys
class Service():
def __init__(self, inputs=1, outputs=1, main_service=False):
self.main_service = main_serv... | [
"numpy.float",
"torch.stack",
"datetime.datetime.now",
"numpy.array",
"app.ai.plot.linear",
"app.ai.genetic.Genetic",
"app.ai.model.Model_deep",
"numpy.int",
"torch.FloatTensor"
] | [((960, 1003), 'app.ai.model.Model_deep', 'model.Model_deep', (['self.inputs', 'self.outputs'], {}), '(self.inputs, self.outputs)\n', (976, 1003), True, 'import app.ai.model as model\n'), ((1271, 1295), 'app.ai.plot.linear', 'plot.linear', (['self.losses'], {}), '(self.losses)\n', (1282, 1295), True, 'import app.ai.plo... |
# Generated by Django 3.1.1 on 2021-12-26 10:44
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
('question', '0005_auto_20211226_1036'),
]
operations = [
migrations.CreateModel(
... | [
"django.db.models.ForeignKey",
"django.db.models.AutoField",
"django.db.models.DateTimeField",
"django.db.models.FilePathField",
"django.db.models.CharField"
] | [((388, 481), '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", (404, 481), False, 'from django.db import migrations, models\... |
#!/usr/bin/env python3
import yaml
def load_config(filepath):
# Loads YAML config file
with open(filepath, "r") as f:
return yaml.load(f, Loader=yaml.FullLoader)
| [
"yaml.load"
] | [((143, 179), 'yaml.load', 'yaml.load', (['f'], {'Loader': 'yaml.FullLoader'}), '(f, Loader=yaml.FullLoader)\n', (152, 179), False, 'import yaml\n')] |
"""
This file exports the big_endian and little_endian decorators,
They are used to convert a BinaryStruct endiannes
"""
import logging
from copy import deepcopy
from binary_structs.utils import *
from binary_structs.binary_struct import binary_struct, _is_binary_struct
def _convert_primitive_type_endianness(kind: ... | [
"binary_structs.binary_struct._is_binary_struct",
"logging.debug",
"binary_structs.binary_struct.binary_struct"
] | [((997, 1048), 'logging.debug', 'logging.debug', (['f"""Converting {kind} into {new_kind}"""'], {}), "(f'Converting {kind} into {new_kind}')\n", (1010, 1048), False, 'import logging\n'), ((2371, 2420), 'logging.debug', 'logging.debug', (['f"""Converting endianness for {cls}"""'], {}), "(f'Converting endianness for {cls... |
from transformers import pipeline
import pandas as pd
import os
import mlflow
from mlflow import log_artifact
from mlflow.models import ModelSignature
import json
import subprocess
# Example invocation:
# curl -X POST -H "Content-Type:application/json; format=pandas-split"
# --data '{"columns":["text"],"data":[["T... | [
"mlflow.start_run",
"json.dumps",
"mlflow.models.ModelSignature.from_dict",
"os.system",
"transformers.pipeline"
] | [((1171, 1214), 'os.system', 'os.system', (['"""conda env export -f conda.yaml"""'], {}), "('conda env export -f conda.yaml')\n", (1180, 1214), False, 'import os\n'), ((1334, 1382), 'json.dumps', 'json.dumps', (["[{'name': 'text', 'type': 'string'}]"], {}), "([{'name': 'text', 'type': 'string'}])\n", (1344, 1382), Fals... |
import itertools
from .. import DSPCircuit
from ..device.RZ6 import split_atten, atten_to_bits
if __name__ == '__main__':
circuit = DSPCircuit('debug_RZ6_audio_out', 'RZ6')
circuit.start()
for a, b in itertools.permutations((0, 20, 40, 60), 2):
circuit.set_tag('attA', a)
circui... | [
"itertools.permutations"
] | [((225, 267), 'itertools.permutations', 'itertools.permutations', (['(0, 20, 40, 60)', '(2)'], {}), '((0, 20, 40, 60), 2)\n', (247, 267), False, 'import itertools\n')] |
from invoke import Collection, Config
from sys import platform
import os
import yaml
from . import nrfconnect, nrf5
def parse_platform_specific(cfg, is_linux):
"""Recursive function that will parse platform specific config
This will move all children of matching platform keys to its parent
I.e. if cu... | [
"os.path.abspath",
"os.path.join",
"invoke.Collection"
] | [((1534, 1546), 'invoke.Collection', 'Collection', ([], {}), '()\n', (1544, 1546), False, 'from invoke import Collection, Config\n'), ((1153, 1178), 'os.path.abspath', 'os.path.abspath', (['__file__'], {}), '(__file__)\n', (1168, 1178), False, 'import os\n'), ((1209, 1238), 'os.path.join', 'os.path.join', (['tasks_dir'... |
"""Integration tests for the pyWriter project.
Test the odt brief synopsis.
For further information see https://github.com/peter88213/PyWriter
Published under the MIT License (https://opensource.org/licenses/mit-license.php)
"""
from pywriter.odt.odt_brief_synopsis import OdtBriefSynopsis
from pywriter.test.e... | [
"unittest.main"
] | [((709, 724), 'unittest.main', 'unittest.main', ([], {}), '()\n', (722, 724), False, 'import unittest\n')] |
import frameworks.tc_scikit.features.bag_of_words as bag_of_words
import frameworks.tc_scikit.features.character_embeddings as character_embeddings
import frameworks.tc_scikit.features.character_ngrams as character_ngrams
import frameworks.tc_scikit.features.dependency_distribution_spacy as dependency_distribution_spac... | [
"frameworks.tc_scikit.features.sentiws_average_polarity_feature.build",
"frameworks.tc_scikit.features.bag_of_words.build",
"frameworks.tc_scikit.features.character_ngrams.build",
"frameworks.tc_scikit.features.pos_distribution_spacy.build",
"frameworks.tc_scikit.features.textdepth_feature.build",
"framew... | [((1281, 1319), 'frameworks.tc_scikit.features.bag_of_words.build', 'bag_of_words.build', ([], {'ngram_range': '(1, 1)'}), '(ngram_range=(1, 1))\n', (1299, 1319), True, 'import frameworks.tc_scikit.features.bag_of_words as bag_of_words\n'), ((1480, 1534), 'frameworks.tc_scikit.features.bag_of_words.build', 'bag_of_word... |
#!/usr/bin/env python
# -*- coding:utf-8 -*-
# Copyright 2019 Huawei Technologies Co.,Ltd.
# Licensed under the Apache License, Version 2.0 (the "License"); you may not use
# this file except in compliance with the License. You may obtain a copy of the
# License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unle... | [
"obs.util.to_int",
"threading.Lock",
"threading.Thread",
"queue.Queue",
"threading.Condition"
] | [((994, 1017), 'queue.Queue', 'queue.Queue', (['queue_size'], {}), '(queue_size)\n', (1005, 1017), False, 'import queue\n'), ((1104, 1120), 'threading.Lock', 'threading.Lock', ([], {}), '()\n', (1118, 1120), False, 'import threading\n'), ((2839, 2860), 'threading.Condition', 'threading.Condition', ([], {}), '()\n', (28... |
import os
import django
BASE_PATH = os.path.dirname(__file__)
if django.VERSION[:2] >= (1, 3):
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.sqlite3',
'NAME': ':memory:',
}
}
else:
DATABASE_ENGINE = 'sqlite3'
DATABASE_NAME = ':memory:'
SITE_ID = 1
... | [
"os.path.dirname",
"os.path.join"
] | [((38, 63), 'os.path.dirname', 'os.path.dirname', (['__file__'], {}), '(__file__)\n', (53, 63), False, 'import os\n'), ((576, 611), 'os.path.join', 'os.path.join', (['BASE_PATH', '"""coverage"""'], {}), "(BASE_PATH, 'coverage')\n", (588, 611), False, 'import os\n')] |
import yaml
import sys
import os
import pathlib
import zipfile
import shutil
import tarfile
import errno
# Read YAML file
def main(argv):
command_name = 'mkisofs'
target_directory = 'target'
if sys.version_info[0] != 3 or sys.version_info[1] < 6:
print("This script requires Python version 3.6+")
... | [
"os.path.exists",
"tarfile.open",
"distutils.spawn.find_executable",
"zipfile.ZipFile",
"os.makedirs",
"shutil.copy2",
"pathlib.Path",
"tarfile.is_tarfile",
"yaml.safe_load",
"os.path.isdir",
"sys.exit",
"os.system",
"zipfile.is_zipfile"
] | [((5700, 5720), 'os.path.exists', 'os.path.exists', (['name'], {}), '(name)\n', (5714, 5720), False, 'import os\n'), ((5923, 5954), 'zipfile.ZipFile', 'zipfile.ZipFile', (['file_name', '"""r"""'], {}), "(file_name, 'r')\n", (5938, 5954), False, 'import zipfile\n'), ((328, 339), 'sys.exit', 'sys.exit', (['(1)'], {}), '(... |
"""
Reinforcement Learning Using Q-learning, Double Q-learning, and Dyna-Q.
Copyright (c) 2020 <NAME>
References
----------
- Based on project 7 in the Georgia Tech Spring 2020 course "Machine Learning
for Trading" by Prof. <NAME>.
- Course: http://quantsoftware.gatech.edu/CS7646_Spring_2020
- Project: http://quant... | [
"numpy.mean",
"numpy.median",
"QLearner.QLearner",
"robot.robot",
"numpy.std",
"numpy.array",
"numpy.random.seed",
"sys.exit",
"numpy.loadtxt"
] | [((4817, 4859), 'numpy.array', 'np.array', (['[-1.0, -1.0, -1.0, +1.0, -100.0]'], {}), '([-1.0, -1.0, -1.0, +1.0, -100.0])\n', (4825, 4859), True, 'import numpy as np\n'), ((5097, 5143), 'numpy.array', 'np.array', (['[[-1, 0], [0, +1], [+1, 0], [0, -1]]'], {}), '([[-1, 0], [0, +1], [+1, 0], [0, -1]])\n', (5105, 5143), ... |
#!/usr/bin/env python
#
# Copyright 2014 Quantopian, 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 ... | [
"zipline.api.get_datetime",
"zipline.api.time_rules.market_close",
"zipline.api.record",
"matplotlib.pyplot.gcf",
"zipline.api.symbols",
"zipline.algorithm.TradingAlgorithm",
"zipline.api.date_rules.every_day",
"datetime.date",
"zipline.utils.factory.load_from_yahoo",
"zipline.api.set_symbol_looku... | [((1164, 1200), 'zipline.api.set_symbol_lookup_date', 'set_symbol_lookup_date', (['"""2015-02-08"""'], {}), "('2015-02-08')\n", (1186, 1200), False, 'from zipline.api import order, order_target_percent, record, symbol, symbols, set_symbol_lookup_date, history, get_datetime, schedule_function, date_rules, time_rules, ge... |
import torch
from torch.utils.data import Dataset
import os
from PIL import Image
import numpy as np
import PIL
import torch.nn as nn
from config import opt
import pandas as pd
import matplotlib.pyplot as plt
from pathlib import Path
import random
import math
class TextureDataset(Dataset):
"""Dataset wrapping ima... | [
"torch.nn.ReLU",
"pandas.read_csv",
"torch.nn.Sequential",
"torch.sin",
"numpy.array",
"torch.cuda.is_available",
"torch.arange",
"os.listdir",
"pathlib.Path",
"torch.nn.Flatten",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.close",
"matplotlib.pyplot.title",
... | [((6041, 6067), 'matplotlib.pyplot.figure', 'plt.figure', ([], {'figsize': '(5, 5)'}), '(figsize=(5, 5))\n', (6051, 6067), True, 'import matplotlib.pyplot as plt\n'), ((6153, 6190), 'pandas.read_csv', 'pd.read_csv', (['csv_path'], {'index_col': 'None'}), '(csv_path, index_col=None)\n', (6164, 6190), True, 'import panda... |
"""
Created on Tuesday Dec 4 18:00 2018
@author: <EMAIL>
Partially based on the BSc Thesis of <NAME> (TUM, Statik 2018)
"""
from node2d import Node2D
from geometric_utilities import get_line_coefficients, get_magnitude_and_direction, get_length, get_midpoint
class Segment2D(object):
def __init__(self, id, nod... | [
"geometric_utilities.get_magnitude_and_direction",
"geometric_utilities.get_line_coefficients",
"node2d.Node2D",
"geometric_utilities.get_length",
"geometric_utilities.get_midpoint"
] | [((3969, 4037), 'geometric_utilities.get_midpoint', 'get_midpoint', (['[self.nodes[0].coordinates, self.nodes[1].coordinates]'], {}), '([self.nodes[0].coordinates, self.nodes[1].coordinates])\n', (3981, 4037), False, 'from geometric_utilities import get_line_coefficients, get_magnitude_and_direction, get_length, get_mi... |
# -*- coding: utf-8 -*-
#
# test_place.py
# cjktools
#
from __future__ import unicode_literals
import unittest
import os
import tempfile
from cjktools.resources import place
def suite():
test_suite = unittest.TestSuite((
unittest.makeSuite(PlaceTestCase)
))
return test_suite
class PlaceTestC... | [
"os.path.exists",
"os.close",
"unittest.makeSuite",
"cjktools.resources.place.Place.from_file",
"cjktools.resources.place.Place",
"tempfile.mkstemp",
"unittest.TextTestRunner",
"os.remove"
] | [((239, 272), 'unittest.makeSuite', 'unittest.makeSuite', (['PlaceTestCase'], {}), '(PlaceTestCase)\n', (257, 272), False, 'import unittest\n'), ((385, 418), 'cjktools.resources.place.Place', 'place.Place', (['"""Melbourne"""', '"""メルボルン"""'], {}), "('Melbourne', 'メルボルン')\n", (396, 418), False, 'from cjktools.resources... |
import pytest
from drink_partners.contrib.samples import (
partner_adega_cerveja,
partner_adega_ze_ambev,
partner_bar_legal
)
@pytest.fixture
def url():
return '/partner/1/'
@pytest.fixture
def partner_with_str_id_url():
return '/partner/id-str/'
@pytest.fixture
def partner_search_with_str_co... | [
"drink_partners.contrib.samples.partner_bar_legal",
"drink_partners.contrib.samples.partner_adega_ze_ambev",
"drink_partners.contrib.samples.partner_adega_cerveja"
] | [((835, 858), 'drink_partners.contrib.samples.partner_adega_cerveja', 'partner_adega_cerveja', ([], {}), '()\n', (856, 858), False, 'from drink_partners.contrib.samples import partner_adega_cerveja, partner_adega_ze_ambev, partner_bar_legal\n'), ((918, 941), 'drink_partners.contrib.samples.partner_adega_cerveja', 'part... |
import asyncio
import usb1
from select import POLLIN, POLLOUT
from weakref import finalize
from . import descriptor
__all__ = ["Context"]
class ContextNotifier:
"""
Object used for binding libusb1 into Asyncio's event loop.
This is an implementation detail (i.e. no API stability).
"""
def __init__... | [
"weakref.finalize",
"asyncio.get_running_loop",
"asyncio.Event",
"usb1.USBContext"
] | [((485, 500), 'asyncio.Event', 'asyncio.Event', ([], {}), '()\n', (498, 500), False, 'import asyncio\n'), ((521, 536), 'asyncio.Event', 'asyncio.Event', ([], {}), '()\n', (534, 536), False, 'import asyncio\n'), ((2468, 2485), 'usb1.USBContext', 'usb1.USBContext', ([], {}), '()\n', (2483, 2485), False, 'import usb1\n'),... |
# coding: utf-8
# Unless explicitly stated otherwise all files in this repository are licensed under the Apache-2.0 License.
# This product includes software developed at Datadog (https://www.datadoghq.com/).
# Copyright 2019-Present Datadog, Inc.
import sys
import unittest
import datadog_api_client.v2
from datadog... | [
"unittest.main"
] | [((1225, 1240), 'unittest.main', 'unittest.main', ([], {}), '()\n', (1238, 1240), False, 'import unittest\n')] |
from PIL import Image, ImageDraw
import sys
import math, random
from itertools import product
from utils.ufarray import *
import numpy as np
def perform_dws(dws_energy, class_map, bbox_map,cutoff=0,min_ccoponent_size=0, return_ccomp_img = False):
bbox_list = []
dws_energy = np.squeeze(dws_energy)
class_m... | [
"numpy.amax",
"numpy.average",
"PIL.Image.new",
"numpy.asanyarray",
"numpy.squeeze",
"numpy.transpose",
"numpy.bincount",
"random.randint",
"numpy.round"
] | [((286, 308), 'numpy.squeeze', 'np.squeeze', (['dws_energy'], {}), '(dws_energy)\n', (296, 308), True, 'import numpy as np\n'), ((325, 346), 'numpy.squeeze', 'np.squeeze', (['class_map'], {}), '(class_map)\n', (335, 346), True, 'import numpy as np\n'), ((362, 382), 'numpy.squeeze', 'np.squeeze', (['bbox_map'], {}), '(b... |
"""
Turning radar PPIs into Cartesian grids. Processing the Australian
National archive.
@creator: <NAME> <<EMAIL>>
@institution: Monash University and Bureau of Meteorology
@date: 12/04/2021
.. autosummary::
:toctree: generated/
buffer
check_rid
extract_zip
get_radar_archive_file
mkdir
r... | [
"radar_grids.标准映射",
"os.path.exists",
"zipfile.ZipFile",
"argparse.ArgumentParser",
"warnings.catch_warnings",
"os.path.join",
"os.mkdir",
"dask.bag.from_sequence",
"sys.exit",
"warnings.simplefilter",
"traceback.print_exc",
"time.time",
"pandas.date_range",
"os.remove"
] | [((1664, 1685), 'os.path.exists', 'os.path.exists', (['indir'], {}), '(indir)\n', (1678, 1685), False, 'import os\n'), ((4575, 4630), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {'description': 'parser_description'}), '(description=parser_description)\n', (4598, 4630), False, 'import argparse\n'), ((683,... |
import itertools
import requests
from geosolver import settings
import networkx as nx
__author__ = 'minjoon'
class SyntaxParse(object):
def __init__(self, words, directed, undirected, rank, score):
self.words = words
self.directed = directed
self.undirected = undirected
self.rank =... | [
"networkx.DiGraph",
"networkx.shortest_path",
"networkx.shortest_path_length",
"requests.get"
] | [((1677, 1708), 'networkx.shortest_path', 'nx.shortest_path', (['graph', 'i0', 'i1'], {}), '(graph, i0, i1)\n', (1693, 1708), True, 'import networkx as nx\n'), ((2385, 2423), 'networkx.shortest_path_length', 'nx.shortest_path_length', (['graph', 'i0', 'i1'], {}), '(graph, i0, i1)\n', (2408, 2423), True, 'import network... |
import setuptools
with open("README.md", "r") as fh:
long_description = fh.read()
setuptools.setup(
name='movies_organizer',
version='1.0.4',
scripts=['movies_organizer'] ,
author="<NAME>",
author_email="<EMAIL>",
description="Tool for organizing movies by IMDB rating.",
long... | [
"setuptools.find_packages"
] | [((477, 503), 'setuptools.find_packages', 'setuptools.find_packages', ([], {}), '()\n', (501, 503), False, 'import setuptools\n')] |
import re
from collections import Counter
from re import split
from os import chdir, environ
from os.path import join, dirname
import sys
def pyinstaller_get_full_path(filename):
""" If bundling files in onefile with pyinstaller, use thise to get the temp directory where file actually resides """
if hasattr(s... | [
"os.path.dirname",
"os.path.join",
"re.split"
] | [((414, 442), 'os.path.join', 'join', (['sys._MEIPASS', 'filename'], {}), '(sys._MEIPASS, filename)\n', (418, 442), False, 'from os.path import join, dirname\n'), ((581, 617), 'os.path.join', 'join', (["environ['_MEIPASS2']", 'filename'], {}), "(environ['_MEIPASS2'], filename)\n", (585, 617), False, 'from os.path impor... |
# -*- coding: utf-8 -*-
# Copyright 2019 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agr... | [
"parameterized.parameterized.expand",
"o2a.utils.el_utils.extract_evaluate_properties",
"o2a.o2a_libs.property_utils.PropertySet",
"o2a.utils.el_utils.escape_string_with_python_escapes",
"tempfile.NamedTemporaryFile"
] | [((3306, 3623), 'parameterized.parameterized.expand', 'parameterized.expand', (["[('${nameNode}/examples/output-data/demo/pig-node',\n '/examples/output-data/demo/pig-node'), (\n '${nameNode}/examples/output-data/demo/pig-node2',\n '/examples/output-data/demo/pig-node2'), (\n 'hdfs:///examples/output-data/d... |
from typing import Dict, Set, Tuple
from automaton import abstract
__all__ = ["NDFA"]
class NonDetTransitions:
"""Transitions is a wrapper for a graph of moves over non-deterministic state machine."""
def __init__(self, d: Dict[int, Dict[chr, Set[int]]] = None):
"""Constructor for a non-determinist... | [
"automaton.abstract.map"
] | [((5035, 5100), 'automaton.abstract.map', 'abstract.map', (['self.T', 'new_trans', '(lambda x: x + n)', '(lambda x: x + n)'], {}), '(self.T, new_trans, lambda x: x + n, lambda x: x + n)\n', (5047, 5100), False, 'from automaton import abstract\n')] |
import numpy as np
import tensorflow as tf
def upsample_nearest(inputs, scale):
shape = tf.shape(input=inputs)
n, h, w, c = shape[0], shape[1], shape[2], shape[3]
return tf.image.resize(inputs, tf.stack([h*scale, w*scale]), method=tf.image.ResizeMethod.NEAREST_NEIGHBOR) | [
"tensorflow.shape",
"tensorflow.stack"
] | [((94, 116), 'tensorflow.shape', 'tf.shape', ([], {'input': 'inputs'}), '(input=inputs)\n', (102, 116), True, 'import tensorflow as tf\n'), ((208, 240), 'tensorflow.stack', 'tf.stack', (['[h * scale, w * scale]'], {}), '([h * scale, w * scale])\n', (216, 240), True, 'import tensorflow as tf\n')] |
"""
Django settings for securedblog project.
Generated by 'django-admin startproject' using Django 3.1.4.
For more information on this file, see
https://docs.djangoproject.com/en/3.1/topics/settings/
For the full list of settings and their values, see
https://docs.djangoproject.com/en/3.1/ref/settings/
"""
from pat... | [
"os.path.join",
"environ.Env",
"environ.Env.read_env",
"pathlib.Path"
] | [((390, 422), 'environ.Env', 'environ.Env', ([], {'DEBUG': '(bool, False)'}), '(DEBUG=(bool, False))\n', (401, 422), False, 'import environ\n'), ((482, 504), 'environ.Env.read_env', 'environ.Env.read_env', ([], {}), '()\n', (502, 504), False, 'import environ\n'), ((3966, 4003), 'os.path.join', 'os.path.join', (['BASE_D... |
from random import randint
from sympy import expand, sqrt
from cartesian import *
def tangent(x0, y0):
x, y = symbols('x, y')
return Eq(x0*x + y0*y, 1)
def sub_y(x, y):
return y, (1 - randint(0, 1)*2)*sqrt(1 - x**2)
def main():
# A hexagon ABCDEF circumscribed about a unit circle with tangent points ... | [
"random.randint",
"sympy.sqrt"
] | [((215, 231), 'sympy.sqrt', 'sqrt', (['(1 - x ** 2)'], {}), '(1 - x ** 2)\n', (219, 231), False, 'from sympy import expand, sqrt\n'), ((198, 211), 'random.randint', 'randint', (['(0)', '(1)'], {}), '(0, 1)\n', (205, 211), False, 'from random import randint\n')] |
#!/usr/bin/env python3
from csv import reader
from math import pi, sqrt, exp
from random import randrange
class NaiveBayesClassifier:
"""
Implementation of a Naive Bayes Classifier algorithm.
The implementation consists of the following steps:\n
1. Dataset values separation by class\n
2. Calcu... | [
"math.exp",
"math.sqrt",
"csv.reader"
] | [((4097, 4111), 'math.sqrt', 'sqrt', (['variance'], {}), '(variance)\n', (4101, 4111), False, 'from math import pi, sqrt, exp\n'), ((5864, 5908), 'math.exp', 'exp', (['(-((x - mean) ** 2 / (2 * std_dev ** 2)))'], {}), '(-((x - mean) ** 2 / (2 * std_dev ** 2)))\n', (5867, 5908), False, 'from math import pi, sqrt, exp\n'... |
import os
from pytorch3dunet.unet3d import utils
from argparse import ArgumentParser
import yaml
from pathlib import Path
from pytorch3dunet.datasets.utils_pdb import processPdb
import prody as pr
from shutil import copyfile
logger = utils.get_logger('DataGen')
def procName(arg):
output, name, dataFol... | [
"os.makedirs",
"argparse.ArgumentParser",
"pathlib.Path",
"pytorch3dunet.unet3d.utils.get_logger",
"pytorch3dunet.datasets.utils_pdb.processPdb",
"shutil.copyfile",
"prody.parsePDB",
"prody.writePDB"
] | [((244, 271), 'pytorch3dunet.unet3d.utils.get_logger', 'utils.get_logger', (['"""DataGen"""'], {}), "('DataGen')\n", (260, 271), False, 'from pytorch3dunet.unet3d import utils\n'), ((380, 418), 'os.makedirs', 'os.makedirs', (['output_dir'], {'exist_ok': '(True)'}), '(output_dir, exist_ok=True)\n', (391, 418), False, 'i... |
#!/usr/bin/python2.5
#
# Copyright 2008 the Melange 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... | [
"django.utils.translation.ugettext",
"google.appengine.ext.db.ReferenceProperty",
"google.appengine.ext.db.DateTimeProperty"
] | [((1426, 1532), 'google.appengine.ext.db.ReferenceProperty', 'db.ReferenceProperty', ([], {'reference_class': 'soc.models.user.User', 'required': '(True)', 'collection_name': '"""commented"""'}), "(reference_class=soc.models.user.User, required=True,\n collection_name='commented')\n", (1446, 1532), False, 'from goog... |
# Copyright 2010-2018 Amazon.com, Inc. or its 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. A copy of
# the License is located at
#
# http://aws.amazon.com/apache2.0/
#
# or in the "license" file ac... | [
"boto3.client"
] | [((630, 649), 'boto3.client', 'boto3.client', (['"""sts"""'], {}), "('sts')\n", (642, 649), False, 'import boto3\n'), ((1016, 1173), 'boto3.client', 'boto3.client', (['"""sts"""'], {'aws_access_key_id': "creds['AccessKeyId']", 'aws_secret_access_key': "creds['SecretAccessKey']", 'aws_session_token': "creds['SessionToke... |
"""
Code to extract a box-like region, typically for another modeler to use
as a boundary contition. In cases where it gets velocity in addition to
the rho-grid variables the grid limits mimic the standard ROMS organization,
with the outermost corners being on the rho-grid.
Job definitions are in LO_user/extract/box/... | [
"sys.exit",
"job_definitions.get_box",
"lo_tools.Lfun.make_dir",
"numpy.mod",
"lo_tools.Lfun.Lstart",
"lo_tools.zrfun.get_z",
"argparse.ArgumentParser",
"subprocess.Popen",
"os.getpid",
"sys.stdout.flush",
"lo_tools.Lfun.get_fn_list",
"numpy.ones",
"numpy.isnan",
"xarray.open_dataset",
"... | [((1163, 1174), 'os.getpid', 'os.getpid', ([], {}), '()\n', (1172, 1174), False, 'import os\n'), ((1288, 1313), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {}), '()\n', (1311, 1313), False, 'import argparse\n'), ((2719, 2775), 'lo_tools.Lfun.Lstart', 'Lfun.Lstart', ([], {'gridname': 'gridname', 'tag': 't... |
from torch import nn
from constants import Const
from simple_lstm import SimpleLSTM
from crf import CRF
# or try the vectorized version:
# from crf_vectorized import CRF
class BiLSTM_CRF(nn.Module):
def __init__(self, vocab_size, nb_labels, emb_dim=5, hidden_dim=4):
super().__init__()
self.lstm =... | [
"crf.CRF",
"simple_lstm.SimpleLSTM"
] | [((321, 394), 'simple_lstm.SimpleLSTM', 'SimpleLSTM', (['vocab_size', 'nb_labels'], {'emb_dim': 'emb_dim', 'hidden_dim': 'hidden_dim'}), '(vocab_size, nb_labels, emb_dim=emb_dim, hidden_dim=hidden_dim)\n', (331, 394), False, 'from simple_lstm import SimpleLSTM\n'), ((436, 538), 'crf.CRF', 'CRF', (['nb_labels', 'Const.B... |
import scipy
import matplotlib.pyplot as plt
filename = 'cyclic_test_data.txt'
data = scipy.loadtxt(filename,delimiter=',')
t = data[:,0]
v = data[:,1]
figsize = 12, 8
xlim = t.min(), t.max()
ylim = -0.2, 1.2
linewidth = 2
fig = plt.figure(1,figsize=figsize)
vpos_arrow_low = -0.15
# Quiet time fill
plt.fill([0.0... | [
"matplotlib.pyplot.text",
"scipy.loadtxt",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.title",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.fill",
"matplotlib.pyplot.figtext",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.figure",
"mat... | [((88, 126), 'scipy.loadtxt', 'scipy.loadtxt', (['filename'], {'delimiter': '""","""'}), "(filename, delimiter=',')\n", (101, 126), False, 'import scipy\n'), ((234, 264), 'matplotlib.pyplot.figure', 'plt.figure', (['(1)'], {'figsize': 'figsize'}), '(1, figsize=figsize)\n', (244, 264), True, 'import matplotlib.pyplot as... |
import numpy as np
import torch.nn as nn
import torch
import math
import time
from visualDet3D.networks.backbones import resnet
class YoloMono3DCore(nn.Module):
"""Some Information about YoloMono3DCore"""
def __init__(self, backbone_arguments=dict()):
super(YoloMono3DCore, self).__init__()
sel... | [
"visualDet3D.networks.backbones.resnet"
] | [((332, 360), 'visualDet3D.networks.backbones.resnet', 'resnet', ([], {}), '(**backbone_arguments)\n', (338, 360), False, 'from visualDet3D.networks.backbones import resnet\n')] |
'''
Created on 2016年8月4日
@author: Administrator
pickling序列化, 反序列化即unpickling
'''
import pickle
d = dict(name='Bob', age=20, score=88)
# 把任意对象序列化成一个bytes
print(pickle.dumps(d))
# 序列化
with open('dump.txt', 'wb') as f:
pickle.dump(d, f)
# 反序列化
with open('dump.txt', 'rb') as f:
d = pickle.load(f)
print... | [
"pickle.dumps",
"pickle.load",
"pickle.dump"
] | [((162, 177), 'pickle.dumps', 'pickle.dumps', (['d'], {}), '(d)\n', (174, 177), False, 'import pickle\n'), ((224, 241), 'pickle.dump', 'pickle.dump', (['d', 'f'], {}), '(d, f)\n', (235, 241), False, 'import pickle\n'), ((296, 310), 'pickle.load', 'pickle.load', (['f'], {}), '(f)\n', (307, 310), False, 'import pickle\n'... |
# https://www.tweepy.org/
# https://developer.twitter.com/en/portal/dashboard
import tweepy
import time
consumer_key = 'UhGZOyvUbcV2AdP6qKO0JVyO5'
consumer_secret = '<KEY>'
access_token = '<KEY>'
access_token_secret = '<KEY>'
auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
auth.set_access_token... | [
"tweepy.Cursor",
"tweepy.API",
"time.sleep",
"tweepy.OAuthHandler"
] | [((247, 297), 'tweepy.OAuthHandler', 'tweepy.OAuthHandler', (['consumer_key', 'consumer_secret'], {}), '(consumer_key, consumer_secret)\n', (266, 297), False, 'import tweepy\n'), ((363, 379), 'tweepy.API', 'tweepy.API', (['auth'], {}), '(auth)\n', (373, 379), False, 'import tweepy\n'), ((1046, 1079), 'tweepy.Cursor', '... |
"""
Solution to https://adventofcode.com/2020/day/17
"""
from collections import namedtuple
from itertools import product
class Array:
"""
A simple array that you can add and multiply with other arrays and scalars.
"""
def __init__(self, *args):
self._vals = tuple(args)
def __len__(self... | [
"collections.namedtuple"
] | [((1468, 1509), 'collections.namedtuple', 'namedtuple', (['"""Cube"""', "['position', 'state']"], {}), "('Cube', ['position', 'state'])\n", (1478, 1509), False, 'from collections import namedtuple\n')] |
import argparse
import os
import random
from envs import MappingEnvironment, LocalISM
import numpy as np
parser = argparse.ArgumentParser()
# General Stuff
parser.add_argument('--experiment', default='runs/myopic', help='folder to put results of experiment in')
# Environment
parser.add_argument('--N', type=int, de... | [
"numpy.ones",
"os.makedirs",
"argparse.ArgumentParser",
"envs.LocalISM",
"os.path.join",
"random.seed",
"envs.MappingEnvironment",
"numpy.sum",
"numpy.random.seed",
"random.random",
"random.randint"
] | [((117, 142), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {}), '()\n', (140, 142), False, 'import argparse\n'), ((1040, 1061), 'random.seed', 'random.seed', (['opt.seed'], {}), '(opt.seed)\n', (1051, 1061), False, 'import random\n'), ((1062, 1086), 'numpy.random.seed', 'np.random.seed', (['opt.seed'], {}... |
#!/usr/bin/env python3
# This sample script demonstrates how to
# 1. get a list of flow regex properties
# 2. create a new flow regex property
# 3. get a flow regex property by id
# 4. update an existing flow regex property
# 5. start a find dependents task and check results when completed
# 6. start a deletion task to... | [
"importlib.import_module",
"json.dumps",
"os.path.realpath",
"taskManager.TaskManager",
"sys.exit"
] | [((514, 554), 'importlib.import_module', 'importlib.import_module', (['"""RestApiClient"""'], {}), "('RestApiClient')\n", (537, 554), False, 'import importlib\n'), ((573, 615), 'importlib.import_module', 'importlib.import_module', (['"""SampleUtilities"""'], {}), "('SampleUtilities')\n", (596, 615), False, 'import impo... |
import psycopg2
import time
q1 = """SELECT DISTINCT "visc", "dens", "kxx", "kyy", "kzz", "mmodel", "mesh" FROM "scc2-edgecfd"."oedgecfdpre" , "scc2-edgecfd"."dl_mat" WHERE mesh = 'cavp.2' OR mesh = 'cavp.3' OR mesh = 'cavp.4' AND "oedgecfdpre"."dl_matid" = "dl_mat"."rid" """
q2 = """SELECT DISTINCT dat FROM "scc2-... | [
"psycopg2.connect",
"time.time"
] | [((1076, 1154), 'psycopg2.connect', 'psycopg2.connect', (['"""dbname=edgecfd-program-p user=postgres password=<PASSWORD>"""'], {}), "('dbname=edgecfd-program-p user=postgres password=<PASSWORD>')\n", (1092, 1154), False, 'import psycopg2\n'), ((1220, 1231), 'time.time', 'time.time', ([], {}), '()\n', (1229, 1231), Fals... |
from omnibus import lang
from omnibus import dataclasses as dc
import pytest
from .. import nodes as no
from ... import types
def test_cache():
qn = no.QualifiedNameNode.of(['hi', 'there'])
assert qn.name == types.QualifiedName(('hi', 'there'))
def test_sealed():
with pytest.raises(lang.SealedException... | [
"pytest.raises"
] | [((286, 321), 'pytest.raises', 'pytest.raises', (['lang.SealedException'], {}), '(lang.SealedException)\n', (299, 321), False, 'import pytest\n'), ((523, 555), 'pytest.raises', 'pytest.raises', (['dc.CheckException'], {}), '(dc.CheckException)\n', (536, 555), False, 'import pytest\n')] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Meeko hydrate molecule
#
import numpy as np
from .utils import geomutils
from .utils import obutils
class HydrateMoleculeLegacy:
def __init__(self, distance=3.0, charge=0, atom_type="W"):
"""Initialize the legacy hydrate typer for AutoDock 4.2.x
... | [
"numpy.radians",
"numpy.array"
] | [((1867, 1887), 'numpy.array', 'np.array', (['[position]'], {}), '([position])\n', (1875, 1887), True, 'import numpy as np\n'), ((2190, 2210), 'numpy.array', 'np.array', (['[position]'], {}), '([position])\n', (2198, 2210), True, 'import numpy as np\n'), ((2993, 3012), 'numpy.array', 'np.array', (['positions'], {}), '(... |
# Copyright (c) 2021 elParaguayo
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distrib... | [
"pytest.mark.parametrize"
] | [((2423, 2856), 'pytest.mark.parametrize', 'pytest.mark.parametrize', (['"""params,expected"""', "[({'location': 'London'}, 'London: 7.0 °C 81% light intensity drizzle'), ({\n 'location': 'London', 'format': '{location_city}: {sunrise} {sunset}'},\n 'London: 07:40 16:47'), ({'location': 'London', 'format':\n '... |
import streamlit as st
import json
from joblib import dump, load
import numpy as np
import glob
with open('params.json') as f:
config = json.load(f)
features = config['feature_names']
models = glob.glob('artifacts/*.joblib')+glob.glob('artifacts/*.pkl')
if len(models)>0:
model = load(models[0])
st.title('Welcome ... | [
"numpy.array",
"joblib.load",
"json.load",
"glob.glob",
"streamlit.title"
] | [((302, 324), 'streamlit.title', 'st.title', (['"""Welcome to"""'], {}), "('Welcome to')\n", (310, 324), True, 'import streamlit as st\n'), ((325, 355), 'streamlit.title', 'st.title', (["config['model_name']"], {}), "(config['model_name'])\n", (333, 355), True, 'import streamlit as st\n'), ((138, 150), 'json.load', 'js... |
"""
PSoC bootloader command line tool
This Python file encompasses the command line utility cyflash.
If you need to use this package in your own program, then use bootload.py
"""
import argparse
import codecs
import time
import six
import sys
import logging
import logging.config
from builtins import input
from cyfl... | [
"logging.basicConfig",
"cyflash.cyacd.BootloaderData.read",
"argparse.FileType",
"logging.getLogger",
"builtins.input",
"argparse.ArgumentParser",
"time.clock",
"can.interface.Bus",
"cyflash.protocol.SerialTransport",
"cyflash.bootload.BootloaderHost",
"argparse.ArgumentTypeError",
"time.perf_... | [((446, 525), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {'description': '"""Bootloader tool for Cypress PSoC devices"""'}), "(description='Bootloader tool for Cypress PSoC devices')\n", (469, 525), False, 'import argparse\n'), ((7829, 7869), 'logging.basicConfig', 'logging.basicConfig', ([], {'level': ... |
###############################################################################
# Copyright 2018 The AnPyLar Team. All Rights Reserved.
# Use of this source code is governed by an MIT-style license that
# can be found in the LICENSE file at http://anpylar.com/mit-license
################################################... | [
"anpylar.html.a",
"anpylar.html.span",
"anpylar.html.txt",
"anpylar.html.li"
] | [((832, 841), 'anpylar.html.li', 'html.li', ([], {}), '()\n', (839, 841), False, 'from anpylar import Component, html\n'), ((943, 989), 'anpylar.html.a', 'html.a', ([], {'routerlink': "('', {'did': disaster.did})"}), "(routerlink=('', {'did': disaster.did}))\n", (949, 989), False, 'from anpylar import Component, html\n... |
import sys,os
import torch
import torch.nn as nn
import config
import numpy as np
from .smpl import SMPL
sys.path.append(os.path.abspath(__file__).replace('models/smpl_regressor.py',''))
from config import args
class SMPLR(nn.Module):
def __init__(self, use_gender=False):
super(SMPLR, self).__init__()
... | [
"os.path.abspath",
"config.args",
"torch.from_numpy"
] | [((122, 147), 'os.path.abspath', 'os.path.abspath', (['__file__'], {}), '(__file__)\n', (137, 147), False, 'import sys, os\n'), ((338, 344), 'config.args', 'args', ([], {}), '()\n', (342, 344), False, 'from config import args\n'), ((388, 394), 'config.args', 'args', ([], {}), '()\n', (392, 394), False, 'from config imp... |
import pendulum
from .. import types
# https://github.com/sdispater/pendulum/issues/97
DEFAULT_TIMEZONE = "utc"
class DateTime(types.DateTime):
python_type = pendulum.Pendulum
def __init__(self, timezone=DEFAULT_TIMEZONE):
self.timezone = timezone
super().__init__()
def dynamo_dump(se... | [
"pendulum.instance"
] | [((703, 724), 'pendulum.instance', 'pendulum.instance', (['dt'], {}), '(dt)\n', (720, 724), False, 'import pendulum\n'), ((1342, 1363), 'pendulum.instance', 'pendulum.instance', (['dt'], {}), '(dt)\n', (1359, 1363), False, 'import pendulum\n')] |
import unittest
from assertpy import assert_that
from nose_parameterized import parameterized
from implementation.converter import RomanToArabic
from implementation.exceptions import IllegalArgumentError
from tests.method_conversion import as_function
class RomanToArabicTests(unittest.TestCase):
def setUp(self)... | [
"nose_parameterized.parameterized.expand",
"assertpy.assert_that",
"implementation.converter.RomanToArabic",
"tests.method_conversion.as_function"
] | [((366, 421), 'nose_parameterized.parameterized.expand', 'parameterized.expand', (["[('I', 1), ('II', 2), ('III', 3)]"], {}), "([('I', 1), ('II', 2), ('III', 3)])\n", (386, 421), False, 'from nose_parameterized import parameterized\n'), ((953, 996), 'nose_parameterized.parameterized.expand', 'parameterized.expand', (["... |
import numpy as np
import requests
import random
import pandas as pd
import time
import multiprocessing
url = 'https://raw.githubusercontent.com/dwyl/english-words/master/words_alpha.txt'
existingWords = requests.get(url)
existingWords = existingWords.text.split()
existingWords = [word for word in existingWo... | [
"random.choice",
"pandas.DataFrame",
"multiprocessing.Process",
"requests.get",
"numpy.array",
"multiprocessing.Manager",
"time.time"
] | [((213, 230), 'requests.get', 'requests.get', (['url'], {}), '(url)\n', (225, 230), False, 'import requests\n'), ((460, 483), 'random.choice', 'random.choice', (['alphabet'], {}), '(alphabet)\n', (473, 483), False, 'import random\n'), ((4981, 4992), 'time.time', 'time.time', ([], {}), '()\n', (4990, 4992), False, 'impo... |
import logging
from homeassistant.components.media_player.const import (
MEDIA_TYPE_MUSIC,
SUPPORT_PAUSE,
SUPPORT_PLAY,
SUPPORT_PLAY_MEDIA,
SUPPORT_SELECT_SOURCE,
SUPPORT_VOLUME_MUTE,
SUPPORT_VOLUME_SET,
)
from homeassistant.const import (
STATE_OFF,
STATE_PAUSED,
STATE_PLAYING,... | [
"logging.getLogger",
"datetime.timedelta"
] | [((494, 521), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (511, 521), False, 'import logging\n'), ((539, 559), 'datetime.timedelta', 'timedelta', ([], {'seconds': '(5)'}), '(seconds=5)\n', (548, 559), False, 'from datetime import timedelta\n')] |
from .Role import Role
import strings as s
class Derek(Role):
"""Derek muore. Quando gli pare."""
icon = s.derek_icon
team = "Good"
name = s.derek_name
powerdesc = s.derek_power_description
def __init__(self, player):
super().__init__(player)
# Per qualche motivo assurdo ho dec... | [
"strings.derek_deathwish_successful.format"
] | [((847, 910), 'strings.derek_deathwish_successful.format', 's.derek_deathwish_successful.format', ([], {'name': 'self.player.tusername'}), '(name=self.player.tusername)\n', (882, 910), True, 'import strings as s\n')] |
# -*- coding: utf-8 -*-
from yawf import get_workflow_by_instance
def get_allowed(sender, obj):
workflow = get_workflow_by_instance(obj)
obj_state = getattr(obj, workflow.state_attr_name)
check_result = dict(
(c, c(obj, sender))
for c in workflow.get_checkers_by_state(obj_state))
me... | [
"yawf.get_workflow_by_instance"
] | [((113, 142), 'yawf.get_workflow_by_instance', 'get_workflow_by_instance', (['obj'], {}), '(obj)\n', (137, 142), False, 'from yawf import get_workflow_by_instance\n')] |
from django import template
from django.core.exceptions import ImproperlyConfigured
from django.utils.safestring import mark_safe
from django.conf import settings
from bilderfee.bilderfee import Ext
from bilderfee.bilderfee import url
from bilderfee.bilderfee import BASE_URL as BF_BASE_URL
LAZY_LOADING = getattr(sett... | [
"bilderfee.bilderfee.url",
"django.utils.safestring.mark_safe",
"django.template.Library",
"django.conf.settings.STATIC_URL.endswith",
"django.core.exceptions.ImproperlyConfigured"
] | [((530, 548), 'django.template.Library', 'template.Library', ([], {}), '()\n', (546, 548), False, 'from django import template\n'), ((455, 517), 'django.core.exceptions.ImproperlyConfigured', 'ImproperlyConfigured', (['"""Please provide your BILDERFEE_BASE_URL"""'], {}), "('Please provide your BILDERFEE_BASE_URL')\n", ... |
# Generated by Django 2.0.5 on 2018-05-26 15:31
import django.db.models.deletion
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('sunless_web', '0023_entity_translated'),
]
operations = [
migrations.CreateModel(
name='Answer',... | [
"django.db.models.AutoField",
"django.db.models.CharField",
"django.db.models.ForeignKey"
] | [((1222, 1363), 'django.db.models.ForeignKey', 'models.ForeignKey', ([], {'on_delete': 'django.db.models.deletion.CASCADE', 'related_name': '"""answers"""', 'to': '"""sunless_web.Conversation"""', 'verbose_name': '"""대화"""'}), "(on_delete=django.db.models.deletion.CASCADE, related_name\n ='answers', to='sunless_web.... |
import snap7
import threading
import time
import struct
from utils import int2bitarray
import ctypes
from snap7.common import check_error
from snap7.snap7types import S7DataItem, S7AreaDB, S7WLByte
import logging
logger = logging.getLogger(__name__)
class Siemens_s7(snap7.client.Client):
def __init__(self):
... | [
"logging.getLogger",
"utils.int2bitarray",
"snap7.common.check_error",
"ctypes.c_int32",
"ctypes.POINTER",
"snap7.util.set_bool",
"struct.pack",
"ctypes.create_string_buffer",
"struct.unpack",
"ctypes.pointer"
] | [((223, 250), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (240, 250), False, 'import logging\n'), ((5853, 5877), 'ctypes.c_int32', 'ctypes.c_int32', (['S7AreaDB'], {}), '(S7AreaDB)\n', (5867, 5877), False, 'import ctypes\n'), ((5910, 5934), 'ctypes.c_int32', 'ctypes.c_int32', (['S7WLBy... |
#!/usr/bin/env python
"""
This filename contains a health monitoring plugin which is still
being developed and is still in the alpha testing stage.
----------------------------------------------------------------
check-l3-resources
DESCRIPTION
OUTPUT
plain text
PLATFORMS:
Cumulus Linux Hardware Switc... | [
"subprocess.check_output",
"argparse.ArgumentParser"
] | [((2787, 2896), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {'description': "('Check Cumulus L3 Resources. ' + 'Found in cl-resource-query output')"}), "(description='Check Cumulus L3 Resources. ' +\n 'Found in cl-resource-query output')\n", (2810, 2896), False, 'import argparse\n'), ((1194, 1222), 's... |
"""
Visualize mel spectrogram input data.
Copyright 2021. <NAME>.
"""
from os import path
from matplotlib import pyplot as plt # type: ignore
from seaborn import heatmap # type: ignore
from click import command, option # type: ignore
import tensorflow as tf # type: ignore
from util import ARTIFACT_DIR, hyperparams... | [
"util.hyperparams",
"matplotlib.pyplot.savefig",
"tensorflow.transpose",
"click.option",
"os.path.join",
"preprocess.load_accents",
"matplotlib.pyplot.close",
"matplotlib.pyplot.figure",
"click.command"
] | [((401, 410), 'click.command', 'command', ([], {}), '()\n', (408, 410), False, 'from click import command, option\n'), ((412, 502), 'click.option', 'option', (['"""--num"""', '"""-n"""'], {'type': 'int', 'required': '(True)', 'help': '"""The number of plots to create."""'}), "('--num', '-n', type=int, required=True, he... |
import MeCab
import mojimoji
import re
import pandas as pd
import numpy as np
tagger = MeCab.Tagger("-Owakati -d /usr/lib/x86_64-linux-gnu/mecab/dic/mecab-ipadic-neologd")
def make_wakati(sentence):
# MeCabで分かち書き
sentence = sentence.lower()
sentence = tagger.parse(sentence)
sentence = mojimoji.zen_to_h... | [
"MeCab.Tagger",
"re.sub",
"mojimoji.zen_to_han",
"re.compile"
] | [((88, 177), 'MeCab.Tagger', 'MeCab.Tagger', (['"""-Owakati -d /usr/lib/x86_64-linux-gnu/mecab/dic/mecab-ipadic-neologd"""'], {}), "(\n '-Owakati -d /usr/lib/x86_64-linux-gnu/mecab/dic/mecab-ipadic-neologd')\n", (100, 177), False, 'import MeCab\n'), ((303, 332), 'mojimoji.zen_to_han', 'mojimoji.zen_to_han', (['sente... |
from django_sqlalchemy.test import *
from django_sqlalchemy.backend import metadata
from django.db import models
# An example of a custom manager called "objects".
class PersonManager(models.Manager):
def get_fun_people(self):
return self.filter(fun=True)
class Person(models.Model):
first_name = mode... | [
"django.db.models.Manager",
"django.db.models.IntegerField",
"django.db.models.ManyToManyField",
"django.db.models.BooleanField",
"django.db.models.CharField",
"django_sqlalchemy.backend.metadata.create_all"
] | [((1591, 1612), 'django_sqlalchemy.backend.metadata.create_all', 'metadata.create_all', ([], {}), '()\n', (1610, 1612), False, 'from django_sqlalchemy.backend import metadata\n'), ((316, 347), 'django.db.models.CharField', 'models.CharField', ([], {'max_length': '(30)'}), '(max_length=30)\n', (332, 347), False, 'from d... |
#
# Progression of infection within individuals
#
import random
import numpy as np
import pyEpiabm as pe
from pyEpiabm.core import Person
from pyEpiabm.property import InfectionStatus
from pyEpiabm.utility import StateTransitionMatrix, TransitionTimeMatrix
from .abstract_sweep import AbstractSweep
class HostProgre... | [
"pyEpiabm.Parameters.instance",
"pyEpiabm.property.InfectionStatus",
"pyEpiabm.utility.TransitionTimeMatrix",
"numpy.floor",
"random.choices",
"numpy.random.gamma",
"pyEpiabm.utility.StateTransitionMatrix"
] | [((1116, 1139), 'pyEpiabm.utility.StateTransitionMatrix', 'StateTransitionMatrix', ([], {}), '()\n', (1137, 1139), False, 'from pyEpiabm.utility import StateTransitionMatrix, TransitionTimeMatrix\n'), ((1555, 1577), 'pyEpiabm.utility.TransitionTimeMatrix', 'TransitionTimeMatrix', ([], {}), '()\n', (1575, 1577), False, ... |
import asyncio
import platform
import telegram_helper
if platform.system() == "Windows":
# otherwise some "RuntimeError: Event loop is closed" occur
asyncio.set_event_loop_policy(asyncio.WindowsSelectorEventLoopPolicy())
telegram_helper.run_bot()
| [
"telegram_helper.run_bot",
"platform.system",
"asyncio.WindowsSelectorEventLoopPolicy"
] | [((232, 257), 'telegram_helper.run_bot', 'telegram_helper.run_bot', ([], {}), '()\n', (255, 257), False, 'import telegram_helper\n'), ((59, 76), 'platform.system', 'platform.system', ([], {}), '()\n', (74, 76), False, 'import platform\n'), ((189, 229), 'asyncio.WindowsSelectorEventLoopPolicy', 'asyncio.WindowsSelectorE... |
import streamlit as st
import requests
import json
from PIL import Image
import ipywidgets as widgets
import matplotlib.pyplot as plt
import deviantart
import numpy as np
import argparse
import sys
from IPython.display import display
from ipywidgets import interact, interact_manual
def app():
st.title('Recommendat... | [
"streamlit.form",
"streamlit.caption",
"streamlit.markdown",
"PIL.Image.open",
"deviantart.Api",
"streamlit.number_input",
"streamlit.expander",
"streamlit.write",
"requests.get",
"streamlit.container",
"streamlit.header",
"streamlit.form_submit_button",
"streamlit.title"
] | [((299, 342), 'streamlit.title', 'st.title', (['"""Recommendation from Deviant Art"""'], {}), "('Recommendation from Deviant Art')\n", (307, 342), True, 'import streamlit as st\n'), ((347, 385), 'streamlit.write', 'st.write', (['"""Welcome to Recommendations"""'], {}), "('Welcome to Recommendations')\n", (355, 385), Tr... |
"""A minimal API for defining ACL protected resources and querying permissions"""
import functools
import typing
import flask
class AclResource:
def __init__(self,
name: str,
rank: int = 1,
children: typing.Optional[typing.List['AclResource']] = None):
... | [
"flask.abort",
"functools.update_wrapper"
] | [((3584, 3620), 'functools.update_wrapper', 'functools.update_wrapper', (['wrapper', 'f'], {}), '(wrapper, f)\n', (3608, 3620), False, 'import functools\n'), ((3384, 3415), 'flask.abort', 'flask.abort', (['(403)', 'abort_message'], {}), '(403, abort_message)\n', (3395, 3415), False, 'import flask\n')] |
from fastapi import APIRouter, Depends, Path, HTTPException
from fastapi.responses import Response
from kubernetes.client import CoreV1Api, StorageV1Api
from starlette.status import (
HTTP_201_CREATED,
HTTP_204_NO_CONTENT,
HTTP_400_BAD_REQUEST,
HTTP_404_NOT_FOUND,
HTTP_422_UNPROCESSABLE_ENTITY,
)
... | [
"app.crud.user.delete_user",
"fastapi.HTTPException",
"app.core.jwt.get_current_user_authorizer",
"app.crud.user.get_user_by_user_id",
"app.core.permission.check_permission_with_exception",
"app.crud.user.crud_get_many_user",
"fastapi.APIRouter",
"fastapi.Path",
"fastapi.Depends",
"fastapi.respons... | [((1091, 1102), 'fastapi.APIRouter', 'APIRouter', ([], {}), '()\n', (1100, 1102), False, 'from fastapi import APIRouter, Depends, Path, HTTPException\n'), ((1312, 1333), 'fastapi.Depends', 'Depends', (['get_database'], {}), '(get_database)\n', (1319, 1333), False, 'from fastapi import APIRouter, Depends, Path, HTTPExce... |
import os
import sys
sys.path.append('../../../')
sys.path.append('../../../python_parser')
from run_parser import get_identifiers, get_code_tokens
from parser_folder import remove_comments_and_docstrings
def preprocess_gcjpy(split_portion):
'''
预处理文件.
需要将结果分成train和valid
'''
data_name = "gcjpy"
... | [
"os.path.exists",
"os.listdir",
"run_parser.get_code_tokens",
"os.path.join",
"os.mkdir",
"run_parser.get_identifiers",
"sys.path.append"
] | [((21, 49), 'sys.path.append', 'sys.path.append', (['"""../../../"""'], {}), "('../../../')\n", (36, 49), False, 'import sys\n'), ((50, 91), 'sys.path.append', 'sys.path.append', (['"""../../../python_parser"""'], {}), "('../../../python_parser')\n", (65, 91), False, 'import sys\n'), ((330, 370), 'os.path.join', 'os.pa... |
import torch
import torch.nn as nn
class Actor(nn.Module):
def __init__(self, state_size, action_size, args):
super(Actor, self).__init__()
self.fc1 = nn.Linear(state_size, args.hidden_size)
self.fc2 = nn.Linear(args.hidden_size, args.hidden_size)
self.fc3 = nn.Linear(args.hidden_si... | [
"torch.cat",
"torch.nn.Linear"
] | [((172, 211), 'torch.nn.Linear', 'nn.Linear', (['state_size', 'args.hidden_size'], {}), '(state_size, args.hidden_size)\n', (181, 211), True, 'import torch.nn as nn\n'), ((231, 276), 'torch.nn.Linear', 'nn.Linear', (['args.hidden_size', 'args.hidden_size'], {}), '(args.hidden_size, args.hidden_size)\n', (240, 276), Tru... |
from flask import Flask, jsonify, request
import logging
logging.basicConfig(level=logging.DEBUG)
app = Flask(__name__)
@app.route("/")
def get_header():
default = {"Client IP": "0.0.0.0", "Host": "", "User-Agent": "",
"Accept": ""}
try:
r = request.headers.__dict__
#print r
logging.d... | [
"logging.basicConfig",
"flask.jsonify",
"logging.debug",
"flask.Flask"
] | [((57, 97), 'logging.basicConfig', 'logging.basicConfig', ([], {'level': 'logging.DEBUG'}), '(level=logging.DEBUG)\n', (76, 97), False, 'import logging\n'), ((105, 120), 'flask.Flask', 'Flask', (['__name__'], {}), '(__name__)\n', (110, 120), False, 'from flask import Flask, jsonify, request\n'), ((580, 596), 'flask.jso... |
"""
Implementation of F-cooper maxout fusing.
"""
import torch
import torch.nn as nn
class SpatialFusion(nn.Module):
def __init__(self):
super(SpatialFusion, self).__init__()
def regroup(self, x, record_len):
cum_sum_len = torch.cumsum(record_len, dim=0)
split_x = torch.tensor_split(x... | [
"torch.max",
"torch.cumsum",
"torch.cat"
] | [((250, 281), 'torch.cumsum', 'torch.cumsum', (['record_len'], {'dim': '(0)'}), '(record_len, dim=0)\n', (262, 281), False, 'import torch\n'), ((660, 681), 'torch.cat', 'torch.cat', (['out'], {'dim': '(0)'}), '(out, dim=0)\n', (669, 681), False, 'import torch\n'), ((580, 614), 'torch.max', 'torch.max', (['xx'], {'dim':... |
import torch
import torch.nn as nn
from network.gated_conv import GatedConv2d, GatedDeConv2d
class CoarseNetwork(nn.Module):
def __init__(self, in_channels: int = 4, out_channels: int = 3, latent_channels: int = 48, padding_type: str = 'zero', activation: str = 'lrelu', norm: str = 'none'):
super().__init... | [
"network.gated_conv.GatedDeConv2d",
"torch.nn.Tanh",
"torch.cat",
"network.gated_conv.GatedConv2d"
] | [((3008, 3044), 'torch.cat', 'torch.cat', (['(img_masked, mask)'], {'dim': '(1)'}), '((img_masked, mask), dim=1)\n', (3017, 3044), False, 'import torch\n'), ((397, 513), 'network.gated_conv.GatedConv2d', 'GatedConv2d', (['in_channels', 'latent_channels', '(5)', '(1)', '(2)'], {'padding_type': 'padding_type', 'activatio... |
import os
import json
path = "P2S2/"
example = {}
example["labels"] = ["Background","Vegetation","Organ","Don't know"]
example["models"] = []
dirs = [item for item in os.listdir(path) if os.path.isdir(os.path.join(path,item))]
print(dirs)
for dir_ in dirs:
if dir_ == "images":
example["imageURLs"] = ["data/im... | [
"os.listdir",
"os.path.join",
"json.dump"
] | [((665, 687), 'json.dump', 'json.dump', (['example', 'fp'], {}), '(example, fp)\n', (674, 687), False, 'import json\n'), ((171, 187), 'os.listdir', 'os.listdir', (['path'], {}), '(path)\n', (181, 187), False, 'import os\n'), ((205, 229), 'os.path.join', 'os.path.join', (['path', 'item'], {}), '(path, item)\n', (217, 22... |
# Copyright (c) [2022] Huawei Technologies Co.,Ltd.ALL rights reserved.
# This program is licensed under Mulan PSL v2.
# You can use it according to the terms and conditions of the Mulan PSL v2.
# http://license.coscl.org.cn/MulanPSL2
# THIS PROGRAM IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KI... | [
"json.loads",
"os.path.isfile",
"shlex.quote",
"copy.deepcopy",
"re.search"
] | [((939, 962), 'shlex.quote', 'shlex.quote', (['machine.ip'], {}), '(machine.ip)\n', (950, 962), False, 'import shlex\n'), ((972, 1001), 'shlex.quote', 'shlex.quote', (['machine.password'], {}), '(machine.password)\n', (983, 1001), False, 'import shlex\n'), ((1051, 1076), 'shlex.quote', 'shlex.quote', (['machine.user'],... |
from flask import Flask
app = Flask(__name__)
import lachesis.views
from lachesis.models.database import init_db, clear_db
if __name__ == '__main__':
app.run(debug=True)
| [
"flask.Flask"
] | [((32, 47), 'flask.Flask', 'Flask', (['__name__'], {}), '(__name__)\n', (37, 47), False, 'from flask import Flask\n')] |
import jwe
import jwt
class Strategy2:
def __init__(self, signature_public_key, signature_algorithm,
encryption_private_key, encryption_algorithm, encryption_method,
logging_enabled=False):
# The library we use, PyJWE, only supports the 'A256GCM' encryption algorithm
... | [
"jwt.decode",
"logging.exception"
] | [((1417, 1538), 'jwt.decode', 'jwt.decode', (['decrypted_payload', 'self.signature_public_key'], {'audience': '"""OpenStax"""', 'algorithms': '[self.signature_algorithm]'}), "(decrypted_payload, self.signature_public_key, audience=\n 'OpenStax', algorithms=[self.signature_algorithm])\n", (1427, 1538), False, 'import... |
from django.shortcuts import render, redirect
from django.contrib.auth.decorators import login_required
from chinese.models import *
from language.views_common import *
import datetime
import json
def choose_language (request):
return render(request, 'russian/home.html')
def time(request):
#print(get_time_step(requ... | [
"django.shortcuts.render",
"datetime.timedelta"
] | [((237, 273), 'django.shortcuts.render', 'render', (['request', '"""russian/home.html"""'], {}), "(request, 'russian/home.html')\n", (243, 273), False, 'from django.shortcuts import render, redirect\n'), ((1615, 1660), 'django.shortcuts.render', 'render', (['request', '"""russian/time.html"""', 'context'], {}), "(reque... |
# -*- coding: utf-8 -*-
# File: vgg_model.py
import tensorflow as tf
from tensorpack import *
from tensorpack.tfutils.scope_utils import auto_reuse_variable_scope
from tensorpack.tfutils.argscope import argscope, get_arg_scope
from tensorpack.tfutils.summary import *
from tensorpack.models import (
Conv2D, MaxPoo... | [
"tensorpack.tfutils.argscope.argscope",
"tensorflow.variance_scaling_initializer",
"tensorpack.models.MaxPooling",
"tensorflow.random_normal_initializer",
"tensorpack.tfutils.tower.get_current_tower_context",
"tensorflow.summary.histogram",
"tensorpack.models.GlobalAvgPooling"
] | [((565, 592), 'tensorpack.tfutils.tower.get_current_tower_context', 'get_current_tower_context', ([], {}), '()\n', (590, 592), False, 'from tensorpack.tfutils.tower import get_current_tower_context\n'), ((754, 848), 'tensorpack.tfutils.argscope.argscope', 'argscope', (['[Conv2D, MaxPooling, BatchNorm, GlobalAvgPooling]... |
####################
# ES-DOC CIM Questionnaire
# Copyright (c) 2017 ES-DOC. All rights reserved.
#
# University of Colorado, Boulder
# http://cires.colorado.edu/
#
# This project is distributed according to the terms of the MIT license [http://www.opensource.org/licenses/MIT].
####################
from Q.qu... | [
"Q.questionnaire.models.models_ontologies.registered_ontology_signal.connect"
] | [((1050, 1161), 'Q.questionnaire.models.models_ontologies.registered_ontology_signal.connect', 'registered_ontology_signal.connect', (['registered_ontology_handler'], {'dispatch_uid': '"""registered_ontology_handler"""'}), "(registered_ontology_handler,\n dispatch_uid='registered_ontology_handler')\n", (1084, 1161),... |
#!/usr/bin/env python3
import numpy as np
#############################################################
class Person():
def __init__(self, _id, pos, moveinterval, destiny):
self.id = _id
self.destiny = destiny
self.pos = pos
self.moveinterval = moveinterval
self.path = np.... | [
"numpy.array"
] | [((317, 345), 'numpy.array', 'np.array', (['[]'], {'dtype': 'np.int64'}), '([], dtype=np.int64)\n', (325, 345), True, 'import numpy as np\n')] |
from typing import Optional, Tuple
from sqlalchemy.orm import Session
from sqlalchemy import func
from amcat4annotator.models import Unit, User, Annotation, CodingJob, JobSetUnits
from amcat4annotator.crud import crud_codingjob
class ValidationError(Exception):
pass
class RuleSet:
"""
A Rule set encodes... | [
"sqlalchemy.func.count",
"amcat4annotator.crud.crud_codingjob.get_jobset",
"amcat4annotator.models.JobSetUnits.unit_id.not_in"
] | [((3666, 3730), 'amcat4annotator.crud.crud_codingjob.get_jobset', 'crud_codingjob.get_jobset', (['self.db', 'job.id', 'coder.id', 'assign_set'], {}), '(self.db, job.id, coder.id, assign_set)\n', (3691, 3730), False, 'from amcat4annotator.crud import crud_codingjob\n'), ((7591, 7649), 'amcat4annotator.crud.crud_codingjo... |
#!/usr/bin/env python
# We use addstr() instead of printw()
import curses
try:
# message to be appeared on the screen
mesg = "Enter a string: "
# start the curses mode
stdscr = curses.initscr()
# get the number of rows and columns
row, col = stdscr.getmaxyx()
# print the message at the ... | [
"curses.endwin",
"curses.initscr"
] | [((198, 214), 'curses.initscr', 'curses.initscr', ([], {}), '()\n', (212, 214), False, 'import curses\n'), ((536, 551), 'curses.endwin', 'curses.endwin', ([], {}), '()\n', (549, 551), False, 'import curses\n')] |
from flask import Flask
from flask_sqlalchemy import SQLAlchemy
from flask_migrate import Migrate
from flask_login import LoginManager
from config import config_options
from flask_bootstrap import Bootstrap
db = SQLAlchemy()
migrate = Migrate()
login = LoginManager()
login.login_view = 'auth.login'
login.login_message... | [
"flask_login.LoginManager",
"flask.Flask",
"flask_migrate.Migrate",
"flask_bootstrap.Bootstrap",
"flask_sqlalchemy.SQLAlchemy"
] | [((213, 225), 'flask_sqlalchemy.SQLAlchemy', 'SQLAlchemy', ([], {}), '()\n', (223, 225), False, 'from flask_sqlalchemy import SQLAlchemy\n'), ((236, 245), 'flask_migrate.Migrate', 'Migrate', ([], {}), '()\n', (243, 245), False, 'from flask_migrate import Migrate\n'), ((254, 268), 'flask_login.LoginManager', 'LoginManag... |
# Copyright 2004-2008 <NAME>.
# Distributed under the Boost Software License, Version 1.0. (See
# accompanying file LICENSE_1_0.txt or copy at
# http://www.boost.org/LICENSE_1_0.txt)
import os
import compound
import code_creator
import ctypes_formatter
import declaration_based
from pygccxml import declaratio... | [
"os.linesep.join",
"ctypes_formatter.as_ctype",
"code_creator.code_creator_t.__init__",
"declaration_based.declaration_based_t.__init__",
"pygccxml.declarations.is_void"
] | [((975, 1017), 'code_creator.code_creator_t.__init__', 'code_creator.code_creator_t.__init__', (['self'], {}), '(self)\n', (1011, 1017), False, 'import code_creator\n'), ((1027, 1087), 'declaration_based.declaration_based_t.__init__', 'declaration_based.declaration_based_t.__init__', (['self', 'class_'], {}), '(self, c... |
"""evaluate.py
This script is used to evalute trained ImageNet models.
"""
import sys
import argparse
import tensorflow as tf
from config import config
from utils.utils import config_keras_backend, clear_keras_session
from utils.dataset import get_dataset
from models.adamw import AdamW
DESCRIPTION = """For examp... | [
"utils.utils.config_keras_backend",
"argparse.ArgumentParser",
"utils.utils.clear_keras_session",
"tensorflow.keras.models.load_model",
"sys.exit",
"utils.dataset.get_dataset"
] | [((524, 572), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {'description': 'DESCRIPTION'}), '(description=DESCRIPTION)\n', (547, 572), False, 'import argparse\n'), ((886, 908), 'utils.utils.config_keras_backend', 'config_keras_backend', ([], {}), '()\n', (906, 908), False, 'from utils.utils import config_... |
# -*- coding: UTF-8 -*-
from twisted.internet.defer import inlineCallbacks
from autobahn.twisted.util import sleep
from Adafruit_LED_Backpack.HT16K33 import HT16K33
# Digit value to bitmask map.
#
REPLACEMENT = 0x00
DIGIT_VALUES = {
' ': 0x00,
'!': 0x82,
'"': 0x21,
'\'': 0x02,
'{': 0x39,
'... | [
"time.sleep"
] | [((3704, 3712), 'time.sleep', 'sleep', (['(2)'], {}), '(2)\n', (3709, 3712), False, 'from time import sleep\n'), ((3802, 3810), 'time.sleep', 'sleep', (['(1)'], {}), '(1)\n', (3807, 3810), False, 'from time import sleep\n'), ((3987, 3997), 'time.sleep', 'sleep', (['(0.1)'], {}), '(0.1)\n', (3992, 3997), False, 'from ti... |
# -*- coding: utf-8 -*-
"""
Tencent is pleased to support the open source community by making BK-BASE 蓝鲸基础平台 available.
Copyright (C) 2021 THL A29 Limited, a Tencent company. All rights reserved.
BK-BASE 蓝鲸基础平台 is licensed under the MIT License.
License for BK-BASE 蓝鲸基础平台:
---------------------------------------------... | [
"json.dumps"
] | [((1636, 1768), 'json.dumps', 'json.dumps', (["{'bkdata_authentication_method': 'inner', 'bk_app_code': APP_ID,\n 'bk_app_secret': APP_TOKEN, 'bk_username': 'admin'}"], {}), "({'bkdata_authentication_method': 'inner', 'bk_app_code': APP_ID,\n 'bk_app_secret': APP_TOKEN, 'bk_username': 'admin'})\n", (1646, 1768), ... |
import numpy as np
import cv2
import operator
import numpy as np
from matplotlib import pyplot as plt
def plot_many_images(images, titles, rows=1, columns=2):
"""Plots each image in a given list as a grid structure. using Matplotlib."""
for i, image in enumerate(images):
plt.subplot(rows, columns, i+1)
plt.imsh... | [
"numpy.sqrt",
"numpy.array",
"operator.itemgetter",
"matplotlib.pyplot.imshow",
"cv2.__version__.split",
"numpy.mean",
"matplotlib.pyplot.yticks",
"numpy.concatenate",
"cv2.drawContours",
"matplotlib.pyplot.xticks",
"cv2.getPerspectiveTransform",
"cv2.floodFill",
"cv2.cvtColor",
"matplotli... | [((414, 424), 'matplotlib.pyplot.show', 'plt.show', ([], {}), '()\n', (422, 424), True, 'from matplotlib import pyplot as plt\n'), ((2470, 2524), 'cv2.drawContours', 'cv2.drawContours', (['img', 'contours', '(-1)', 'colour', 'thickness'], {}), '(img, contours, -1, colour, thickness)\n', (2486, 2524), False, 'import cv2... |
from ..tools.velocity_embedding import quiver_autoscale, velocity_embedding
from ..tools.utils import groups_to_bool
from .utils import *
from .scatter import scatter
from .docs import doc_scatter, doc_params
from sklearn.neighbors import NearestNeighbors
from scipy.stats import norm as normal
from matplotlib import r... | [
"numpy.mean",
"numpy.abs",
"numpy.unique",
"matplotlib.pyplot.plot",
"numpy.max",
"numpy.array",
"matplotlib.pyplot.figure",
"scipy.stats.norm.pdf",
"numpy.vstack",
"sklearn.neighbors.NearestNeighbors",
"numpy.min",
"numpy.percentile",
"numpy.meshgrid",
"numpy.maximum",
"matplotlib.pyplo... | [((1146, 1163), 'numpy.meshgrid', 'np.meshgrid', (['*grs'], {}), '(*grs)\n', (1157, 1163), True, 'import numpy as np\n'), ((1328, 1380), 'sklearn.neighbors.NearestNeighbors', 'NearestNeighbors', ([], {'n_neighbors': 'n_neighbors', 'n_jobs': '(-1)'}), '(n_neighbors=n_neighbors, n_jobs=-1)\n', (1344, 1380), False, 'from ... |
from django.conf.urls import url
from timepiece.entries import views
urlpatterns = [
url(r'^time/$',
views.Dashboard.as_view(),
name='dashboard'),
# Active entry
url(r'^entry/clock_in/$',
views.clock_in,
name='clock_in'),
url(r'^entry/clock_out/$',
views.clock_... | [
"timepiece.entries.views.TodoAdminListView.as_view",
"django.conf.urls.url",
"timepiece.entries.views.TodoCompletedListView.as_view",
"timepiece.entries.views.Dashboard.as_view"
] | [((193, 250), 'django.conf.urls.url', 'url', (['"""^entry/clock_in/$"""', 'views.clock_in'], {'name': '"""clock_in"""'}), "('^entry/clock_in/$', views.clock_in, name='clock_in')\n", (196, 250), False, 'from django.conf.urls import url\n'), ((273, 333), 'django.conf.urls.url', 'url', (['"""^entry/clock_out/$"""', 'views... |
import json
import sys
import datetime
from os import getenv
from dotenv import load_dotenv
from notion import NotionHelper
from rabbit import RabbitHelper
load_dotenv()
notion_helper = NotionHelper()
# get discord id to notion id list
result = notion_helper.get_discord_list(getenv('NOTION_ID_LIST'))
discord_to_noti... | [
"rabbit.RabbitHelper",
"os.getenv",
"notion.NotionHelper",
"dotenv.load_dotenv",
"json.JSONEncoder",
"sys.exit",
"datetime.date.today"
] | [((158, 171), 'dotenv.load_dotenv', 'load_dotenv', ([], {}), '()\n', (169, 171), False, 'from dotenv import load_dotenv\n'), ((189, 203), 'notion.NotionHelper', 'NotionHelper', ([], {}), '()\n', (201, 203), False, 'from notion import NotionHelper\n'), ((517, 531), 'rabbit.RabbitHelper', 'RabbitHelper', ([], {}), '()\n'... |
import os
from django.db import models
from django.contrib.auth.models import User
from django.core.validators import MinValueValidator, MaxValueValidator
from ecantina_project import constants
from api.models.ec.organization import Organization
from api.models.ec.store import Store
from api.models.ec.employee import E... | [
"django.core.validators.MinValueValidator",
"django.core.validators.MaxValueValidator",
"django.db.models.TextField",
"django.db.models.ForeignKey",
"django.db.models.ManyToManyField",
"django.db.models.BooleanField",
"django.db.models.ImageField",
"django.db.models.AutoField",
"django.db.models.Dat... | [((1108, 1142), 'django.db.models.AutoField', 'models.AutoField', ([], {'primary_key': '(True)'}), '(primary_key=True)\n', (1124, 1142), False, 'from django.db import models\n'), ((1409, 1479), 'django.db.models.CharField', 'models.CharField', ([], {'max_length': '(511)', 'null': '(True)', 'blank': '(True)', 'db_index'... |
import tkinter
from tkinter import ttk
import random
import time
import tkinter.messagebox
class SortingVisualizer:
"""
Main GUI
"""
def __init__(self, main):
"""
Init GUI
:param main: tkinter.Tk()
"""
self.FINISHED_SORTING = False
self.box_color = "#... | [
"tkinter.messagebox.showwarning",
"tkinter.ttk.Separator",
"tkinter.Button",
"time.sleep",
"tkinter.Canvas",
"tkinter.StringVar",
"tkinter.Tk",
"tkinter.Scrollbar",
"tkinter.Label",
"tkinter.PhotoImage",
"tkinter.messagebox.showinfo",
"tkinter.Frame",
"random.randint"
] | [((24122, 24134), 'tkinter.Tk', 'tkinter.Tk', ([], {}), '()\n', (24132, 24134), False, 'import tkinter\n'), ((1018, 1082), 'tkinter.PhotoImage', 'tkinter.PhotoImage', ([], {'file': '"""icons/icons8-ascending-sorting-48.png"""'}), "(file='icons/icons8-ascending-sorting-48.png')\n", (1036, 1082), False, 'import tkinter\n... |
import ezdxf
from ezdxf.tools.standards import linetypes
data = {
'circles': (
(5, (13, 2)),
(19, (15, 15)),
(19, (12, 4)),
(8, (8, 13)),
(3, (29, 29)),
(2, (8, 11)),
(1, (2, 6)),
),
'lines': (
((12, 3), (18, 2), 'CONTINUOUS', 'B'),
((... | [
"ezdxf.tools.standards.linetypes",
"ezdxf.new"
] | [((596, 615), 'ezdxf.new', 'ezdxf.new', (['"""AC1027"""'], {}), "('AC1027')\n", (605, 615), False, 'import ezdxf\n'), ((683, 694), 'ezdxf.tools.standards.linetypes', 'linetypes', ([], {}), '()\n', (692, 694), False, 'from ezdxf.tools.standards import linetypes\n')] |
# Copyright 2012 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/LICENSE-2.0
#
# Unless required by applicable law or ... | [
"traceback.format_exc",
"google.appengine.ext.db.TextProperty",
"google.appengine.ext.db.IntegerProperty",
"json.dumps",
"google.appengine.ext.deferred.defer",
"logging.info",
"google.appengine.ext.db.DateTimeProperty",
"google.appengine.api.namespace_manager.get_namespace",
"google.appengine.ext.db... | [((2920, 2953), 'google.appengine.ext.db.DateTimeProperty', 'db.DateTimeProperty', ([], {'indexed': '(True)'}), '(indexed=True)\n', (2939, 2953), False, 'from google.appengine.ext import db\n'), ((2979, 3012), 'google.appengine.ext.db.IntegerProperty', 'db.IntegerProperty', ([], {'indexed': '(False)'}), '(indexed=False... |
import numpy as np
np.random.seed(0)
import torch
torch.manual_seed(0)
from torch.utils.data import Dataset, DataLoader, ConcatDataset, RandomSampler
import torchvision
import imageio
import importlib
import random
import glob
import os
import transforms_3d
class patch_DS(Dataset):
"""Implementation of torch... | [
"torch.utils.data.ConcatDataset",
"torch.manual_seed",
"numpy.mean",
"importlib.import_module",
"numpy.std",
"random.seed",
"numpy.max",
"numpy.array",
"numpy.zeros",
"numpy.random.seed",
"numpy.min",
"imageio.imread",
"torchvision.transforms.ToTensor",
"transforms_3d.get_transformer",
"... | [((19, 36), 'numpy.random.seed', 'np.random.seed', (['(0)'], {}), '(0)\n', (33, 36), True, 'import numpy as np\n'), ((50, 70), 'torch.manual_seed', 'torch.manual_seed', (['(0)'], {}), '(0)\n', (67, 70), False, 'import torch\n'), ((8191, 8228), 'importlib.import_module', 'importlib.import_module', (['"""dataloader"""'],... |
import numpy as np
import pandas as pd
import pytest
from pandas.testing import assert_index_equal
from evalml.pipelines import RegressionPipeline
def test_regression_init():
clf = RegressionPipeline(
component_graph=["Imputer", "One Hot Encoder", "Random Forest Regressor"]
)
assert clf.parameter... | [
"pandas.Series",
"evalml.pipelines.RegressionPipeline",
"numpy.arange",
"pandas.testing.assert_index_equal",
"pytest.mark.parametrize",
"pytest.raises",
"pandas.date_range"
] | [((1943, 2013), 'pytest.mark.parametrize', 'pytest.mark.parametrize', (['"""target_type"""', "['category', 'string', 'bool']"], {}), "('target_type', ['category', 'string', 'bool'])\n", (1966, 2013), False, 'import pytest\n'), ((188, 285), 'evalml.pipelines.RegressionPipeline', 'RegressionPipeline', ([], {'component_gr... |
from io import BytesIO
import PIL.Image
import PIL.ImageColor
import PIL.ImageDraw
import zeit.cms.browser.view
import zeit.content.image.interfaces
import zeit.imp.mask
def parse_filter_args(request, crop):
for key, value in request.form.items():
if key.startswith('filter.'):
filter_type = ke... | [
"io.BytesIO"
] | [((1064, 1073), 'io.BytesIO', 'BytesIO', ([], {}), '()\n', (1071, 1073), False, 'from io import BytesIO\n')] |