code stringlengths 22 1.05M | apis listlengths 1 3.31k | extract_api stringlengths 75 3.25M |
|---|---|---|
import asyncio
from aiocouch import CouchDB
async def main_with():
async with CouchDB(
"http://localhost:5984", user="admin", password="<PASSWORD>"
) as couchdb:
database = await couchdb["config"]
async for doc in database.docs(["db-hta"]):
print(doc)
if __name__ == "_... | [
"asyncio.get_event_loop",
"aiocouch.CouchDB"
] | [((341, 365), 'asyncio.get_event_loop', 'asyncio.get_event_loop', ([], {}), '()\n', (363, 365), False, 'import asyncio\n'), ((85, 154), 'aiocouch.CouchDB', 'CouchDB', (['"""http://localhost:5984"""'], {'user': '"""admin"""', 'password': '"""<PASSWORD>"""'}), "('http://localhost:5984', user='admin', password='<PASSWORD>... |
import pandas as pd
import numpy as np
dataset_name = "Caltech"
relative = "../../../"
df = pd.read_csv(relative + "datasets/" + dataset_name + '/'+ dataset_name + '.csv', sep=";", header=None)
df = df.drop(0, 1)
print(df.describe())
print(df.nunique())
print(df.head())
print(df.shape)
df[11] = pd.Categorical... | [
"matplotlib.pyplot.show",
"pandas.read_csv",
"matplotlib.pyplot.scatter",
"numpy.savetxt",
"umap.UMAP",
"pandas.Categorical"
] | [((96, 202), 'pandas.read_csv', 'pd.read_csv', (["(relative + 'datasets/' + dataset_name + '/' + dataset_name + '.csv')"], {'sep': '""";"""', 'header': 'None'}), "(relative + 'datasets/' + dataset_name + '/' + dataset_name +\n '.csv', sep=';', header=None)\n", (107, 202), True, 'import pandas as pd\n'), ((306, 328),... |
# Generated by Django 2.2.13 on 2020-07-07 17:18
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
(
"samlidp",
"0003_samlapplication_allow_access_by_email_suffix_squashed_0004_auto_20200420_1246",
... | [
"django.db.models.ForeignKey",
"django.db.models.AutoField"
] | [((557, 650), '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", (573, 650), False, 'from django.db import migrations, models\... |
"""Tree Practice
=== Module description ===
- Task 1, which contains one Tree method to implement.
- Task 2, which asks you to implement two operations that allow you
to convert between trees and nested lists.
- Task 3, which asks you to learn about and use a more restricted form of
trees known as *binary t... | [
"python_ta.check_all"
] | [((7577, 7598), 'python_ta.check_all', 'python_ta.check_all', ([], {}), '()\n', (7596, 7598), False, 'import python_ta\n')] |
import string
import itertools
from operator import add
import argparse
import json
parser = argparse.ArgumentParser()
parser.add_argument("--l1", default="en", help="name of language 1")
parser.add_argument("--l2", default="sp", help="name of language 2")
parser.add_argument("--probs_l1", default="../../da... | [
"json.load",
"argparse.ArgumentParser"
] | [((102, 127), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {}), '()\n', (125, 127), False, 'import argparse\n'), ((6251, 6263), 'json.load', 'json.load', (['f'], {}), '(f)\n', (6260, 6263), False, 'import json\n')] |
# -- Path setup --------------------------------------------------------------
import os
import sys
sys.path.insert(0, os.path.abspath("../../src"))
import sphinx_gallery
# -- Project information -----------------------------------------------------
project = "SPFlow"
copyright = "2020, <NAME>, <NAME>, <NAME>, <NAME>... | [
"os.path.abspath",
"os.path.join"
] | [((120, 148), 'os.path.abspath', 'os.path.abspath', (['"""../../src"""'], {}), "('../../src')\n", (135, 148), False, 'import os\n'), ((2681, 2706), 'os.path.join', 'os.path.join', (['"""generated"""'], {}), "('generated')\n", (2693, 2706), False, 'import os\n')] |
"""Tests for views of applications."""
from django.test import TestCase
from django.core.urlresolvers import reverse
from django.contrib.auth.models import AnonymousUser
from django.http import HttpResponseRedirect
from nose.tools import raises
from oauth2_provider.models import AccessToken
from rest_framework.test ... | [
"django.contrib.auth.models.AnonymousUser",
"django.core.urlresolvers.reverse",
"oauth2_provider.models.AccessToken.objects.get",
"rest_framework.test.APIRequestFactory",
"geokey.projects.tests.model_factories.UserFactory.create",
"oauth2_provider.models.AccessToken.objects.create",
"django.contrib.mess... | [((2399, 2431), 'nose.tools.raises', 'raises', (['AccessToken.DoesNotExist'], {}), '(AccessToken.DoesNotExist)\n', (2405, 2431), False, 'from nose.tools import raises\n'), ((783, 812), 'django.core.urlresolvers.reverse', 'reverse', (['"""admin:app_overview"""'], {}), "('admin:app_overview')\n", (790, 812), False, 'from... |
#!/usr/bin/env python3
from ev3dev2.motor import MoveSteering, MediumMotor, OUTPUT_A, OUTPUT_B, OUTPUT_C
from ev3dev2.sensor.lego import TouchSensor
from time import sleep
ts = TouchSensor()
steer_pair = MoveSteering(OUTPUT_A, OUTPUT_B)
mm = MediumMotor(OUTPUT_C)
mm.on(speed=100)
#teer_pair.on_for_rotations(steering=... | [
"ev3dev2.motor.MediumMotor",
"ev3dev2.sensor.lego.TouchSensor",
"time.sleep",
"ev3dev2.motor.MoveSteering"
] | [((178, 191), 'ev3dev2.sensor.lego.TouchSensor', 'TouchSensor', ([], {}), '()\n', (189, 191), False, 'from ev3dev2.sensor.lego import TouchSensor\n'), ((205, 237), 'ev3dev2.motor.MoveSteering', 'MoveSteering', (['OUTPUT_A', 'OUTPUT_B'], {}), '(OUTPUT_A, OUTPUT_B)\n', (217, 237), False, 'from ev3dev2.motor import MoveSt... |
import re
import math
from collections import Counter
import numpy as np
text1 = '<NAME> mangé du singe'
text2 = 'Nicole a mangé du rat'
class Similarity():
def compute_cosine_similarity(self, string1, string2):
# intersects the words that are common
# in the set of the two words
intersec... | [
"collections.Counter",
"math.sqrt",
"re.compile"
] | [((994, 1012), 're.compile', 're.compile', (['"""\\\\w+"""'], {}), "('\\\\w+')\n", (1004, 1012), False, 'import re\n'), ((1063, 1077), 'collections.Counter', 'Counter', (['words'], {}), '(words)\n', (1070, 1077), False, 'from collections import Counter\n'), ((783, 798), 'math.sqrt', 'math.sqrt', (['sum1'], {}), '(sum1)... |
import data
import numpy as np
# TODO: split tests 1 test per assert statement
# TODO: move repeating constants out of functions
class TestHAPT:
def test_get_train_data(self):
d = data.HAPT()
assert d._train_attrs is None
d.get_train_data()
assert len(d._train_attrs) > 0
a... | [
"data.HAPT",
"numpy.array"
] | [((195, 206), 'data.HAPT', 'data.HAPT', ([], {}), '()\n', (204, 206), False, 'import data\n'), ((404, 415), 'data.HAPT', 'data.HAPT', ([], {}), '()\n', (413, 415), False, 'import data\n'), ((616, 627), 'data.HAPT', 'data.HAPT', ([], {}), '()\n', (625, 627), False, 'import data\n'), ((820, 831), 'data.HAPT', 'data.HAPT'... |
import pytest
from auto_deprecator import deprecate
__version__ = "2.0.0"
@deprecate(
expiry="2.1.0",
version_module="tests.function.test_deprecate_version_module",
)
def simple_deprecate():
pass
@deprecate(
expiry="2.1.0", version_module="tests.function.conftest",
)
def failed_to_locate_version(... | [
"pytest.warns",
"auto_deprecator.deprecate",
"pytest.raises"
] | [((80, 173), 'auto_deprecator.deprecate', 'deprecate', ([], {'expiry': '"""2.1.0"""', 'version_module': '"""tests.function.test_deprecate_version_module"""'}), "(expiry='2.1.0', version_module=\n 'tests.function.test_deprecate_version_module')\n", (89, 173), False, 'from auto_deprecator import deprecate\n'), ((216, ... |
from urllib import request
url="http://www.renren.com/970973463"
headers={
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:66.0) Gecko/20100101 Firefox/66.0',
'Cookie':'anonymid=jw6ali52-qw6ldx; depovince=GUZ; _r01_=1; JSESSIONID=abcv45u4hL5Z0cQdde5Rw; ick_login=99f8241c-bfc0-4cda-9ed9-a... | [
"urllib.request.Request",
"urllib.request.urlopen"
] | [((698, 735), 'urllib.request.Request', 'request.Request', (['url'], {'headers': 'headers'}), '(url, headers=headers)\n', (713, 735), False, 'from urllib import request\n'), ((741, 761), 'urllib.request.urlopen', 'request.urlopen', (['req'], {}), '(req)\n', (756, 761), False, 'from urllib import request\n')] |
import math
from math import sqrt
import cmath
print("Module math imported")
print(math.floor(32.9))
print(int(32.9))
print(math.ceil(32.3))
print(math.ceil(32))
print(sqrt(9))
print(sqrt(2))
#cmath and Complex Numbers
##print(sqrt(-1)) This will trigger a ValueError: math domain error
print(cmath.sqrt(-1))
prin... | [
"cmath.sqrt",
"math.floor",
"math.sqrt",
"math.ceil"
] | [((84, 100), 'math.floor', 'math.floor', (['(32.9)'], {}), '(32.9)\n', (94, 100), False, 'import math\n'), ((127, 142), 'math.ceil', 'math.ceil', (['(32.3)'], {}), '(32.3)\n', (136, 142), False, 'import math\n'), ((150, 163), 'math.ceil', 'math.ceil', (['(32)'], {}), '(32)\n', (159, 163), False, 'import math\n'), ((173... |
from flask import Flask, jsonify, request
app = Flask(__name__) # Gives a unique name
stores = [
{
'name': 'MyStore',
'items': [
{
'name': 'My Item',
'price': 15.99
}
]
}
]
"""
@app.route('/') # Route of the endpoint 'http://www.google.com/'
def home():
return "Hello, world!... | [
"flask.jsonify",
"flask.Flask",
"flask.request.get_json"
] | [((49, 64), 'flask.Flask', 'Flask', (['__name__'], {}), '(__name__)\n', (54, 64), False, 'from flask import Flask, jsonify, request\n'), ((435, 453), 'flask.request.get_json', 'request.get_json', ([], {}), '()\n', (451, 453), False, 'from flask import Flask, jsonify, request\n'), ((554, 572), 'flask.jsonify', 'jsonify'... |
#!/usr/bin/env python
"""fq2vcf
"""
from __future__ import division, print_function
import os
import glob
from setuptools import setup, find_packages
VERSION = '0.0.0'
scripts = ['scripts/fq2vcf']
scripts.extend(glob.glob('scripts/*.sh'))
scripts.extend(glob.glob('scripts/*.py'))
print(scripts)
def read(fname):
... | [
"os.path.dirname",
"setuptools.find_packages",
"glob.glob"
] | [((217, 242), 'glob.glob', 'glob.glob', (['"""scripts/*.sh"""'], {}), "('scripts/*.sh')\n", (226, 242), False, 'import glob\n'), ((259, 284), 'glob.glob', 'glob.glob', (['"""scripts/*.py"""'], {}), "('scripts/*.py')\n", (268, 284), False, 'import glob\n'), ((432, 447), 'setuptools.find_packages', 'find_packages', ([], ... |
import numpy as np
from collections import namedtuple
from util import (
vec3d_to_array,
quat_to_array,
array_to_vec3d_pb,
array_to_quat_pb,
)
from radar_data_streamer import RadarData
from data_pb2 import Image
Extrinsic = namedtuple('Extrinsic', ['position', 'attitude'])
class RadarImage(RadarData)... | [
"util.array_to_quat_pb",
"util.quat_to_array",
"data_pb2.Image",
"numpy.frombuffer",
"util.vec3d_to_array",
"numpy.linalg.norm",
"collections.namedtuple",
"util.array_to_vec3d_pb"
] | [((241, 290), 'collections.namedtuple', 'namedtuple', (['"""Extrinsic"""', "['position', 'attitude']"], {}), "('Extrinsic', ['position', 'attitude'])\n", (251, 290), False, 'from collections import namedtuple\n'), ((1371, 1431), 'numpy.frombuffer', 'np.frombuffer', (['image_pb.cartesian.data.data'], {'dtype': 'np.uint3... |
import pygame
import Levels
from Sprites import *
is_fever = False
class Fever():
global fever_score
def __init__(self):
self.is_fever = False
def feverTime(self,hero_sprites,ghost_sprites):
pygame.sprite.groupcollide(hero_sprites, ghost_sprites, False, False)
return True
| [
"pygame.sprite.groupcollide"
] | [((223, 292), 'pygame.sprite.groupcollide', 'pygame.sprite.groupcollide', (['hero_sprites', 'ghost_sprites', '(False)', '(False)'], {}), '(hero_sprites, ghost_sprites, False, False)\n', (249, 292), False, 'import pygame\n')] |
"""Get top N rated movies from MovieLens
This script allows user to get information about films.
This file can also be imported as a module and contains the following
functions:
* display_movies - Print data in csv format
* get_arguments - Construct the argument parser and get the arguments
* main - the ... | [
"logging.exception",
"logging.error",
"logging.debug",
"argparse.ArgumentParser",
"time.perf_counter",
"mysql.connector.connection.MySQLConnection",
"logging.info",
"logging.getLevelName"
] | [((1296, 1323), 'logging.info', 'log.info', (['"""fetching movies"""'], {}), "('fetching movies')\n", (1304, 1323), True, 'import logging as log\n'), ((3682, 3726), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {'description': '__doc__'}), '(description=__doc__)\n', (3705, 3726), False, 'import argparse\n'... |
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
import logging
import os
import sys
import settings
from datetime import datetime
class Logger(object):
def __init__(self):
log = logging.getLogger('')
log.setLevel(logging.INFO)
filename = datetime.utcnow().strftime('%Y.%m.... | [
"os.makedirs",
"os.path.isdir",
"logging.StreamHandler",
"logging.Formatter",
"datetime.datetime.utcnow",
"os.path.join",
"logging.getLogger"
] | [((1114, 1135), 'logging.getLogger', 'logging.getLogger', (['""""""'], {}), "('')\n", (1131, 1135), False, 'import logging\n'), ((209, 230), 'logging.getLogger', 'logging.getLogger', (['""""""'], {}), "('')\n", (226, 230), False, 'import logging\n'), ((599, 672), 'logging.Formatter', 'logging.Formatter', (['"""%(asctim... |
import csv
import cv2
from datetime import datetime
import numpy as np
import matplotlib.pyplot as plt
import sklearn
from sklearn.utils import shuffle
from sklearn.model_selection import train_test_split
from keras.models import Sequential
from keras.layers import Convolution2D,Flatten,Dense,Lambda
from keras import o... | [
"matplotlib.pyplot.title",
"keras.regularizers.l2",
"csv.reader",
"sklearn.model_selection.train_test_split",
"csv.Sniffer",
"matplotlib.pyplot.figure",
"keras.layers.Flatten",
"numpy.max",
"datetime.datetime.now",
"cv2.resize",
"matplotlib.pyplot.show",
"matplotlib.pyplot.legend",
"keras.op... | [((1728, 1755), 'matplotlib.pyplot.figure', 'plt.figure', ([], {'figsize': '(14, 7)'}), '(figsize=(14, 7))\n', (1738, 1755), True, 'import matplotlib.pyplot as plt\n'), ((1759, 1778), 'matplotlib.pyplot.ylabel', 'plt.ylabel', (['"""Count"""'], {}), "('Count')\n", (1769, 1778), True, 'import matplotlib.pyplot as plt\n')... |
import functools
import pathlib
import queue
import re
import sys
import time
import typing
from .line_timestamper import LineTimestamper
from .non_blocking_read_thread import stdin_read_thread
class LogLine:
def __init__(self, raw_text=None, raw_text_lines=None,
log_file=None, read_... | [
"time.time",
"time.sleep",
"pathlib.Path",
"re.findall",
"typing.TypeVar",
"functools.lru_cache",
"re.compile"
] | [((4138, 4170), 'functools.lru_cache', 'functools.lru_cache', ([], {'maxsize': '(100)'}), '(maxsize=100)\n', (4157, 4170), False, 'import functools\n'), ((4223, 4248), 'typing.TypeVar', 'typing.TypeVar', (['"""LogLine"""'], {}), "('LogLine')\n", (4237, 4248), False, 'import typing\n'), ((5181, 5241), 're.compile', 're.... |
# Copyright 2021 <NAME>. 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 ag... | [
"kernel.components.binning.vertfeaturebinning.param.TransformParam"
] | [((1780, 1796), 'kernel.components.binning.vertfeaturebinning.param.TransformParam', 'TransformParam', ([], {}), '()\n', (1794, 1796), False, 'from kernel.components.binning.vertfeaturebinning.param import FeatureBinningParam, TransformParam\n')] |
import os
import sys
import torch
try:
import torchchimera
except:
# attempts to import local module
sys.path.append(os.path.join(os.path.dirname(os.path.abspath(__file__)), '..'))
import torchchimera
from torchchimera.datasets import FolderTuple
from torchchimera.metrics import eval_snr
from torchchi... | [
"torch.ones_like",
"torchchimera.datasets.FolderTuple",
"os.path.abspath",
"torch.utils.data.DataLoader",
"os.path.isdir",
"torchchimera.metrics.eval_si_sdr",
"torchchimera.metrics.eval_snr",
"os.path.isfile",
"_model_io.load_model",
"torchchimera.metrics.permutation_free",
"torch.no_grad",
"t... | [((1518, 1576), 'torchchimera.datasets.FolderTuple', 'FolderTuple', (['args.data_dir', 'args.sr', 'args.segment_duration'], {}), '(args.data_dir, args.sr, args.segment_duration)\n', (1529, 1576), False, 'from torchchimera.datasets import FolderTuple\n'), ((1590, 1669), 'torch.utils.data.DataLoader', 'torch.utils.data.D... |
import glob
import os
# files = glob.glob("./finall/*")
# files = sorted(files)
# print(files)
import codecs
with open("result.txt",'w') as wf:
for num in range(1,401):
file = "./finall/入院记录现病史-"+str(num)+".txt"
with codecs.open(file,'r',encoding='utf-8') as rf:
for i,line in e... | [
"codecs.open",
"os.path.basename"
] | [((246, 286), 'codecs.open', 'codecs.open', (['file', '"""r"""'], {'encoding': '"""utf-8"""'}), "(file, 'r', encoding='utf-8')\n", (257, 286), False, 'import codecs\n'), ((387, 409), 'os.path.basename', 'os.path.basename', (['file'], {}), '(file)\n', (403, 409), False, 'import os\n')] |
from keras.models import Sequential, load_model
from keras.callbacks import History, EarlyStopping, Callback
from keras.layers.recurrent import LSTM
from keras.layers import Bidirectional
from keras.losses import mse, binary_crossentropy,cosine
from keras.layers.core import Dense, Activation, Dropout
import numpy as np... | [
"keras.layers.core.Dense",
"keras.callbacks.History",
"keras.layers.core.Activation",
"tensorflow.keras.losses.CosineSimilarity",
"numpy.append",
"keras.callbacks.EarlyStopping",
"keras.layers.core.Dropout",
"keras.layers.recurrent.LSTM",
"keras.models.Sequential"
] | [((887, 899), 'keras.models.Sequential', 'Sequential', ([], {}), '()\n', (897, 899), False, 'from keras.models import Sequential, load_model\n'), ((2012, 2024), 'keras.models.Sequential', 'Sequential', ([], {}), '()\n', (2022, 2024), False, 'from keras.models import Sequential, load_model\n'), ((784, 793), 'keras.callb... |
import asyncio
import json
from typing import Any, Dict, Generator, List, Optional, cast
import pytest
from robotcode.jsonrpc2.protocol import (
JsonRPCError,
JsonRPCErrorObject,
JsonRPCErrors,
JsonRPCMessage,
JsonRPCProtocol,
JsonRPCRequest,
JsonRPCResponse,
)
from robotcode.jsonrpc2.serv... | [
"robotcode.language_server.common.types.MessageActionItem.parse_obj",
"robotcode.language_server.common.types.MessageActionItem",
"asyncio.sleep",
"typing.cast",
"robotcode.jsonrpc2.protocol.JsonRPCResponse",
"pytest.fixture",
"robotcode.jsonrpc2.protocol.JsonRPCRequest",
"robotcode.jsonrpc2.protocol.... | [((1092, 1122), 'pytest.fixture', 'pytest.fixture', ([], {'scope': '"""module"""'}), "(scope='module')\n", (1106, 1122), False, 'import pytest\n'), ((1204, 1228), 'asyncio.new_event_loop', 'asyncio.new_event_loop', ([], {}), '()\n', (1226, 1228), False, 'import asyncio\n'), ((1405, 1458), 'robotcode.jsonrpc2.protocol.J... |
from __future__ import annotations
import ast
import inspect
import os
import sys
import traceback
from typing import Optional, Any, Callable
from collections.abc import Iterable
from subtypes import Str
from pathmagic import Dir
def is_running_in_ipython() -> bool:
"""Returns True if run from within a jupyter ... | [
"os.path.abspath",
"inspect.getsourcelines",
"pathmagic.Dir.from_home",
"winsound.Beep",
"subtypes.Str",
"os.linesep.join",
"ast.parse",
"ast.walk"
] | [((2453, 2475), 'ast.parse', 'ast.parse', (['source_text'], {}), '(source_text)\n', (2462, 2475), False, 'import ast\n'), ((768, 783), 'pathmagic.Dir.from_home', 'Dir.from_home', ([], {}), '()\n', (781, 783), False, 'from pathmagic import Dir\n'), ((786, 811), 'os.path.abspath', 'os.path.abspath', (['main_dir'], {}), '... |
import argparse
import logging
import sys
from typing import Dict
import pandas as pd
from analysis.src.python.data_analysis.model.column_name import IssuesColumns, SubmissionColumns
from analysis.src.python.data_analysis.utils.df_utils import read_df, write_df
from analysis.src.python.data_analysis.utils.parsing_uti... | [
"analysis.src.python.data_analysis.utils.df_utils.read_df",
"argparse.ArgumentParser",
"analysis.src.python.data_analysis.model.column_name.SubmissionColumns",
"logging.info",
"analysis.src.python.data_analysis.utils.parsing_utils.str_to_dict"
] | [((546, 565), 'analysis.src.python.data_analysis.utils.parsing_utils.str_to_dict', 'str_to_dict', (['issues'], {}), '(issues)\n', (557, 565), False, 'from analysis.src.python.data_analysis.utils.parsing_utils import str_to_dict\n'), ((1036, 1126), 'logging.info', 'logging.info', (['f"""Reading submissions with issues f... |
"""Module containing the CLI programs for histoprint."""
import numpy as np
import click
from histoprint import *
import histoprint.formatter as formatter
@click.command()
@click.argument("infile", type=click.Path(exists=True, dir_okay=False, allow_dash=True))
@click.option(
"-b",
"--bins",
type=str,
... | [
"click.version_option",
"click.option",
"click.echo",
"numpy.nanmin",
"click.command",
"click.open_file",
"numpy.histogram",
"numpy.linspace",
"click.Path",
"uproot.open",
"numpy.nanmax"
] | [((159, 174), 'click.command', 'click.command', ([], {}), '()\n', (172, 174), False, 'import click\n'), ((265, 375), 'click.option', 'click.option', (['"""-b"""', '"""--bins"""'], {'type': 'str', 'default': '"""10"""', 'help': '"""Number of bins or space-separated bin edges."""'}), "('-b', '--bins', type=str, default='... |
# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT!
"""Client and server classes corresponding to protobuf-defined services."""
import grpc
import proto_pb2 as proto__pb2
class EdgeDeviceStub(object):
"""Missing associated documentation comment in .proto file."""
def __init__(self, channel... | [
"grpc.method_handlers_generic_handler",
"grpc.stream_stream_rpc_method_handler",
"grpc.experimental.stream_stream"
] | [((1408, 1486), 'grpc.method_handlers_generic_handler', 'grpc.method_handlers_generic_handler', (['"""aranya.EdgeDevice"""', 'rpc_method_handlers'], {}), "('aranya.EdgeDevice', rpc_method_handlers)\n", (1444, 1486), False, 'import grpc\n'), ((1149, 1313), 'grpc.stream_stream_rpc_method_handler', 'grpc.stream_stream_rpc... |
from django.conf.urls import url
from django.urls import path, include
from . import views
from django.conf import settings
from django.conf.urls.static import static
urlpatterns = [
url('^$', views.home, name='home'),
path('account/', include('django.contrib.auth.urls')),
path('profile/<id>/', views.profi... | [
"django.urls.path",
"django.conf.urls.static.static",
"django.conf.urls.url",
"django.urls.include"
] | [((188, 222), 'django.conf.urls.url', 'url', (['"""^$"""', 'views.home'], {'name': '"""home"""'}), "('^$', views.home, name='home')\n", (191, 222), False, 'from django.conf.urls import url\n'), ((287, 339), 'django.urls.path', 'path', (['"""profile/<id>/"""', 'views.profile'], {'name': '"""profile"""'}), "('profile/<id... |
from extutils.logger import LoggerSkeleton
logger = LoggerSkeleton("sys.handle", logger_name_env="EVT_HANDLER")
| [
"extutils.logger.LoggerSkeleton"
] | [((54, 113), 'extutils.logger.LoggerSkeleton', 'LoggerSkeleton', (['"""sys.handle"""'], {'logger_name_env': '"""EVT_HANDLER"""'}), "('sys.handle', logger_name_env='EVT_HANDLER')\n", (68, 113), False, 'from extutils.logger import LoggerSkeleton\n')] |
from typing import List, Dict
from injecta.service.argument.ArgumentInterface import ArgumentInterface
from injecta.service.class_.InspectedArgument import InspectedArgument
from injecta.service.resolved.ResolvedArgument import ResolvedArgument
from injecta.service.argument.validator.ArgumentsValidator import Arguments... | [
"injecta.service.resolved.ResolvedArgument.ResolvedArgument",
"injecta.service.argument.validator.ArgumentsValidator.ArgumentsValidator",
"injecta.service.class_.InspectedArgumentsResolver.InspectedArgumentsResolver"
] | [((521, 549), 'injecta.service.class_.InspectedArgumentsResolver.InspectedArgumentsResolver', 'InspectedArgumentsResolver', ([], {}), '()\n', (547, 549), False, 'from injecta.service.class_.InspectedArgumentsResolver import InspectedArgumentsResolver\n'), ((587, 607), 'injecta.service.argument.validator.ArgumentsValida... |
import unittest
import libpysal
from libpysal.common import pandas, RTOL, ATOL
from esda.geary_local_mv import Geary_Local_MV
import numpy as np
PANDAS_EXTINCT = pandas is None
class Geary_Local_MV_Tester(unittest.TestCase):
def setUp(self):
np.random.seed(100)
self.w = libpysal.io.open(libpysal.e... | [
"numpy.random.seed",
"unittest.TextTestRunner",
"unittest.TestSuite",
"esda.geary_local_mv.Geary_Local_MV",
"numpy.array",
"unittest.TestLoader",
"libpysal.examples.get_path"
] | [((803, 823), 'unittest.TestSuite', 'unittest.TestSuite', ([], {}), '()\n', (821, 823), False, 'import unittest\n'), ((1009, 1034), 'unittest.TextTestRunner', 'unittest.TextTestRunner', ([], {}), '()\n', (1032, 1034), False, 'import unittest\n'), ((256, 275), 'numpy.random.seed', 'np.random.seed', (['(100)'], {}), '(10... |
'''
Module that makes timeline graphs from csv data.
'''
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
def plot_timeline(file_name):
'''
Makes timeline graphs from csv data.
'''
# data frame from rounded data file
df = pd.read_csv(file_name)
# find all par for graphs... | [
"pandas.read_csv",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.show"
] | [((267, 289), 'pandas.read_csv', 'pd.read_csv', (['file_name'], {}), '(file_name)\n', (278, 289), True, 'import pandas as pd\n'), ((466, 484), 'matplotlib.pyplot.subplots', 'plt.subplots', (['(8)', '(1)'], {}), '(8, 1)\n', (478, 484), True, 'import matplotlib.pyplot as plt\n'), ((1191, 1201), 'matplotlib.pyplot.show', ... |
import pytorch_lightning as pl
import torch
import torch.nn as nn
import numpy as np
import matplotlib.pyplot as plt
from typing import List, Tuple, Dict, Any, Union, Iterable
try:
import genomics_gans
except:
exec(open('__init__.py').read())
import genomics_gans
from genomics_gans.prepare_data.data_module... | [
"pytorch_lightning.metrics.functional.classification.multiclass_auroc",
"matplotlib.pyplot.show",
"numpy.abs",
"torch.argmax",
"pytorch_lightning.metrics.functional.f1",
"pytorch_lightning.metrics.functional.accuracy",
"torch.nn.NLLLoss",
"torch.Tensor",
"numpy.arange",
"torch.zeros",
"matplotli... | [((917, 929), 'torch.nn.NLLLoss', 'nn.NLLLoss', ([], {}), '()\n', (927, 929), True, 'import torch.nn as nn\n'), ((7044, 7077), 'torch.argmax', 'torch.argmax', ([], {'input': 'logits', 'dim': '(1)'}), '(input=logits, dim=1)\n', (7056, 7077), False, 'import torch\n'), ((7707, 7751), 'pytorch_lightning.metrics.functional.... |
import json
import os
import pathlib
from typing import Any, Dict, List, Union, cast
JSONData = Union[List[Any], Dict[str, Any]]
# Splitting this out for testing with no side effects
def mkdir(directory: str) -> None:
return pathlib.Path(directory).mkdir(parents=True, exist_ok=True)
# Splitting this out for te... | [
"json.dump",
"os.remove",
"json.load",
"pathlib.Path",
"os.path.join"
] | [((393, 412), 'os.remove', 'os.remove', (['filename'], {}), '(filename)\n', (402, 412), False, 'import os\n'), ((521, 554), 'os.path.join', 'os.path.join', (['directory', 'filename'], {}), '(directory, filename)\n', (533, 554), False, 'import os\n'), ((603, 629), 'json.dump', 'json.dump', (['data', 'json_file'], {}), '... |
#!/usr/bin/python3
"""
Script for generating the data set (128b, 256b, 1kB, 1MB, 100MB, 1GB).
Context : Projet BCS - Master 2 SSI - Istic (Univ. Rennes1)
Authors : <NAME> and <NAME>
This script also executes the time measurement into 4 contexts
=> Sequential encryption
=> Sequential decryption
=> Parallel encry... | [
"pygal.Line",
"time.time",
"subprocess.call",
"collections.OrderedDict",
"os.urandom"
] | [((679, 801), 'collections.OrderedDict', 'OrderedDict', (["[('128b', 16), ('256b', 32), ('1kB', 1000), ('1MB', 1000000), ('100MB', \n 100000000), ('1GB', 1000000000)]"], {}), "([('128b', 16), ('256b', 32), ('1kB', 1000), ('1MB', 1000000), (\n '100MB', 100000000), ('1GB', 1000000000)])\n", (690, 801), False, 'from... |
#!/usr/bin/env python
# Copyright 2009 Google Inc. All Rights Reserved.
"""Tests for finding sensitive strings."""
__author__ = '<EMAIL> (<NAME>)'
from google.apputils import resources
from google.apputils import basetest
from moe import config_utils
from moe.scrubber import sensitive_string_scrubber
import test_ut... | [
"test_util.TestResourceName",
"google.apputils.basetest.main",
"moe.scrubber.sensitive_string_scrubber.SensitiveReScrubber",
"moe.scrubber.sensitive_string_scrubber.SensitiveWordScrubber"
] | [((377, 429), 'test_util.TestResourceName', 'test_util.TestResourceName', (['"""sensitive_strings.json"""'], {}), "('sensitive_strings.json')\n", (403, 429), False, 'import test_util\n'), ((3304, 3319), 'google.apputils.basetest.main', 'basetest.main', ([], {}), '()\n', (3317, 3319), False, 'from google.apputils import... |
from torch.utils.data import Dataset
from torchvision import transforms
import torch
class HypertrophyDataset(Dataset):
def __init__(self, images, targets, device):
self.images = images
self.targets = targets
self.device = device
self.augmenter = transforms.Compose([
tr... | [
"torchvision.transforms.RandomAffine",
"torchvision.transforms.ToPILImage",
"torchvision.transforms.ToTensor",
"torchvision.transforms.CenterCrop",
"torch.tensor",
"torchvision.transforms.Resize"
] | [((812, 871), 'torch.tensor', 'torch.tensor', (['image_'], {'dtype': 'torch.float', 'device': 'self.device'}), '(image_, dtype=torch.float, device=self.device)\n', (824, 871), False, 'import torch\n'), ((895, 966), 'torch.tensor', 'torch.tensor', (['self.targets[index]'], {'dtype': 'torch.long', 'device': 'self.device'... |
# -*- encoding=utf-8 -*-
"""
# **********************************************************************************
# Copyright (c) Huawei Technologies Co., Ltd. 2020-2020. All rights reserved.
# [oecp] is licensed under the Mulan PSL v1.
# You can use this software according to the terms and conditions of the Mulan PSL ... | [
"oecp.proxy.rpm_proxy.RPMProxy.rpm_n_v_r_d_a",
"json.load",
"logging.getLogger"
] | [((922, 947), 'logging.getLogger', 'logging.getLogger', (['"""oecp"""'], {}), "('oecp')\n", (939, 947), False, 'import logging\n'), ((1965, 1977), 'json.load', 'json.load', (['f'], {}), '(f)\n', (1974, 1977), False, 'import json\n'), ((2206, 2262), 'oecp.proxy.rpm_proxy.RPMProxy.rpm_n_v_r_d_a', 'RPMProxy.rpm_n_v_r_d_a'... |
#!/usr/bin/env python3
from pathlib import Path
from sqlite3 import Connection
from bleanser.core import logger
from bleanser.core.utils import get_tables
from bleanser.core.sqlite import SqliteNormaliser, Tool
class Normaliser(SqliteNormaliser):
DELETE_DOMINATED = True
MULTIWAY = True
def __init__(sel... | [
"bleanser.core.utils.get_tables",
"bleanser.core.main",
"bleanser.core.sqlite.Tool"
] | [((2951, 2978), 'bleanser.core.main', 'main', ([], {'Normaliser': 'Normaliser'}), '(Normaliser=Normaliser)\n', (2955, 2978), False, 'from bleanser.core import main\n'), ((805, 812), 'bleanser.core.sqlite.Tool', 'Tool', (['c'], {}), '(c)\n', (809, 812), False, 'from bleanser.core.sqlite import SqliteNormaliser, Tool\n')... |
import requests
import json
class CovidData:
__data = [{}]
__province = ''
__population = -1
def __init__(self, province):
self.__province = province.upper()
reports = json.loads(
requests.get(
'https://api.covid19tracker.ca/reports/province/' +
... | [
"requests.get"
] | [((226, 312), 'requests.get', 'requests.get', (["('https://api.covid19tracker.ca/reports/province/' + self.__province)"], {}), "('https://api.covid19tracker.ca/reports/province/' + self.\n __province)\n", (238, 312), False, 'import requests\n'), ((458, 513), 'requests.get', 'requests.get', (['"""https://api.covid19t... |
from typing import Dict
import requests
import helpscout.exceptions as exc
class Endpoint:
"""Base endpoint class."""
def __init__(self, client, base_url: str):
"""
Params:
client: helpscout client with credentials
base_url: url for endpoint
"""
self.... | [
"requests.patch",
"requests.delete",
"requests.get",
"requests.put",
"requests.post"
] | [((1313, 1423), 'requests.get', 'requests.get', (['base_url'], {'headers': "{'Authorization': f'Bearer {self.client.access_token}'}", 'params': '{**kwargs}'}), "(base_url, headers={'Authorization':\n f'Bearer {self.client.access_token}'}, params={**kwargs})\n", (1325, 1423), False, 'import requests\n'), ((1593, 1756... |
#!/usr/bin/env python
# __BEGIN_LICENSE__
#Copyright (c) 2015, United States Government, as represented by the
#Administrator of the National Aeronautics and Space Administration.
#All rights reserved.
# __END_LICENSE__
import os
import logging
import stat
from glob import glob
import shutil
import itertools
from g... | [
"geocamUtil.Builder.Builder",
"os.unlink",
"glob.glob",
"os.path.join",
"shutil.copy",
"os.path.lexists",
"os.path.dirname",
"os.path.exists",
"stat.S_ISDIR",
"stat.S_ISREG",
"os.stat",
"os.path.basename",
"os.path.realpath",
"os.system",
"os.listdir",
"logging.debug",
"os.makedirs",... | [((871, 885), 'os.system', 'os.system', (['cmd'], {}), '(cmd)\n', (880, 885), False, 'import os\n'), ((1275, 1297), 'stat.S_ISREG', 'stat.S_ISREG', (['pathMode'], {}), '(pathMode)\n', (1287, 1297), False, 'import stat\n'), ((1677, 1695), 'os.path.isdir', 'os.path.isdir', (['src'], {}), '(src)\n', (1690, 1695), False, '... |
#from models.baseline_net import BaseNet
import torch
from data_loaders import *
from image_dataloaders import get_dataloaders
from loss import compute_ADD_L1_loss, compute_disentangled_ADD_L1_loss, compute_scaled_disentl_ADD_L1_loss
from rotation_representation import calculate_T_CO_pred
#from models.efficient_net im... | [
"loss.compute_ADD_L1_loss",
"pickle.dump",
"loss.compute_disentangled_ADD_L1_loss",
"loss.compute_scaled_disentl_ADD_L1_loss",
"torch.autograd.set_detect_anomaly",
"os.path.join",
"matplotlib.pyplot.close",
"image_dataloaders.get_dataloaders",
"datetime.timedelta",
"matplotlib.pyplot.subplots",
... | [((636, 675), 'torch.autograd.set_detect_anomaly', 'torch.autograd.set_detect_anomaly', (['(True)'], {}), '(True)\n', (669, 675), False, 'import torch\n'), ((732, 768), 'os.path.join', 'os.path.join', (['logdir', '"""log_dict.pkl"""'], {}), "(logdir, 'log_dict.pkl')\n", (744, 768), False, 'import os\n'), ((946, 957), '... |
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import seaborn as sns
import numpy as np
from misc import set_size
from scipy import stats
from scipy.interpolate import interp1d
from pandas.plotting import table
import statsmodels.api as sm
df_knolls_grund = pd.read_csv("data-set... | [
"seaborn.set_theme",
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.ylim",
"pandas.read_csv",
"statsmodels.api.OLS",
"misc.set_size",
"matplotlib.pyplot.subplots",
"matplotlib.dates.WeekdayLocator",
"matplotlib.dates.DateFormatter",
"seaborn.boxplot",
"matplotlib.pyplot.ylabel",
"pandas.... | [((299, 468), 'pandas.read_csv', 'pd.read_csv', (['"""data-set\\\\knolls_grund.csv"""'], {'sep': '""";"""', 'parse_dates': "['Datum Tid (UTC)']", 'index_col': '"""Datum Tid (UTC)"""', 'usecols': "['Datum Tid (UTC)', 'Havstemperatur']"}), "('data-set\\\\knolls_grund.csv', sep=';', parse_dates=[\n 'Datum Tid (UTC)'], ... |
mat = [
'сука', "блять", "пиздец", "нахуй", "<NAME>", "епта"]
import random
import re
# strong_emotions = re.sub('[^а-я]', ' ', open('strong_emotions').read().lower()).split()
def process(txt, ch):
words = txt.split(" ")
nxt = words[0] + ' '
i = 1
while i < len(words) - 1:
if words[i - 1... | [
"random.random",
"random.choice"
] | [((337, 352), 'random.random', 'random.random', ([], {}), '()\n', (350, 352), False, 'import random\n'), ((378, 396), 'random.choice', 'random.choice', (['mat'], {}), '(mat)\n', (391, 396), False, 'import random\n')] |
import fnmatch
import executePythonResources
import writeEndPointsFile
import executeResources
import changeLogGenerator
import sys
import os
import shutil
from datetime import datetime
import json
import git # if git module is not found, use 'pip install gitpython'
resource_dict = {
'FC Networks': 'fc_net... | [
"fnmatch.filter",
"json.load",
"executeResources.executeResources",
"writeEndPointsFile.writeEndpointsFile",
"os.getcwd",
"changeLogGenerator.changeLogGenerator",
"json.dumps",
"os.path.join",
"os.chdir"
] | [((3830, 3849), 'json.load', 'json.load', (['jsonFile'], {}), '(jsonFile)\n', (3839, 3849), False, 'import json\n'), ((4719, 4779), 'executeResources.executeResources', 'executeResources.executeResources', (['selected_sdk', 'api_version'], {}), '(selected_sdk, api_version)\n', (4752, 4779), False, 'import executeResour... |
from django.conf import settings
from openpersonen.features.country_code_and_omschrijving.models import (
CountryCodeAndOmschrijving,
)
from openpersonen.features.gemeente_code_and_omschrijving.models import (
GemeenteCodeAndOmschrijving,
)
from openpersonen.utils.helpers import is_valid_date_format
def conv... | [
"openpersonen.utils.helpers.is_valid_date_format",
"openpersonen.features.country_code_and_omschrijving.models.CountryCodeAndOmschrijving.get_omschrijving_from_code",
"openpersonen.features.gemeente_code_and_omschrijving.models.GemeenteCodeAndOmschrijving.get_omschrijving_from_code"
] | [((4974, 5053), 'openpersonen.features.country_code_and_omschrijving.models.CountryCodeAndOmschrijving.get_omschrijving_from_code', 'CountryCodeAndOmschrijving.get_omschrijving_from_code', (['ouder.geboorteland_ouder'], {}), '(ouder.geboorteland_ouder)\n', (5027, 5053), False, 'from openpersonen.features.country_code_a... |
from flask.ext.wtf import Form
from wtforms import BooleanField, TextField, PasswordField, validators
from wtforms.validators import DataRequired
from flask_wtf.file import FileField
class LoginForm(Form):
first_name = TextField('first_name', validators=[DataRequired()])
last_name = TextField('first_name', val... | [
"wtforms.validators.Length",
"wtforms.BooleanField",
"wtforms.validators.required",
"flask_wtf.file.FileField",
"wtforms.validators.DataRequired"
] | [((456, 467), 'flask_wtf.file.FileField', 'FileField', ([], {}), '()\n', (465, 467), False, 'from flask_wtf.file import FileField\n'), ((486, 528), 'wtforms.BooleanField', 'BooleanField', (['"""remember_me"""'], {'default': '(False)'}), "('remember_me', default=False)\n", (498, 528), False, 'from wtforms import Boolean... |
#!/usr/bin/python
# -*- coding: utf-8 -*-
from flask import Blueprint, render_template
from flask_login import login_required
from vhoops.modules.teams.api.controllers import get_all_teams_func
from vhoops.modules.on_call.forms.new_on_call import NewOnCallSchedule
on_call_router = Blueprint("on_call_router", __name... | [
"vhoops.modules.teams.api.controllers.get_all_teams_func",
"vhoops.modules.on_call.forms.new_on_call.NewOnCallSchedule",
"flask.Blueprint",
"flask.render_template"
] | [((286, 323), 'flask.Blueprint', 'Blueprint', (['"""on_call_router"""', '__name__'], {}), "('on_call_router', __name__)\n", (295, 323), False, 'from flask import Blueprint, render_template\n'), ((443, 477), 'vhoops.modules.teams.api.controllers.get_all_teams_func', 'get_all_teams_func', ([], {'as_object': '(True)'}), '... |
import os
import pickle
from collections import defaultdict
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import scipy.stats
def add_capitals(dico):
return {**dico, **{key[0].capitalize() + key[1:]: item for key, item in dico.items()}}
COLORS = {
'causal': 'blue',
'anti': 'red',
... | [
"collections.defaultdict",
"os.path.isfile",
"pickle.load",
"numpy.arange",
"os.path.join",
"matplotlib.pyplot.hlines",
"os.path.abspath",
"numpy.set_printoptions",
"matplotlib.pyplot.close",
"os.path.dirname",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.ylim",
"numpy.percentile",
"ma... | [((3201, 3248), 'matplotlib.pyplot.subplots', 'plt.subplots', ([], {'nrows': '(1)', 'ncols': '(1)', 'figsize': 'figsize'}), '(nrows=1, ncols=1, figsize=figsize)\n', (3213, 3248), True, 'import matplotlib.pyplot as plt\n'), ((4291, 4338), 'matplotlib.pyplot.subplots', 'plt.subplots', ([], {'nrows': '(1)', 'ncols': '(1)'... |
from tests.v1tests import BaseTestCase
import json
class OfficeEndpointsTestCase(BaseTestCase):
def test_create_office(self):
"""Tests valid data POST Http method request on /offices endpoint"""
# Post, uses office specification model
response = self.client.post('api/v1/offices', data=jso... | [
"json.dumps"
] | [((317, 340), 'json.dumps', 'json.dumps', (['self.office'], {}), '(self.office)\n', (327, 340), False, 'import json\n'), ((2178, 2201), 'json.dumps', 'json.dumps', (['self.office'], {}), '(self.office)\n', (2188, 2201), False, 'import json\n'), ((3284, 3307), 'json.dumps', 'json.dumps', (['self.office'], {}), '(self.of... |
from rest_framework import serializers
class ValidateSerializer(serializers.Serializer):
class_label = serializers.IntegerField()
confidence = serializers.FloatField() | [
"rest_framework.serializers.IntegerField",
"rest_framework.serializers.FloatField"
] | [((108, 134), 'rest_framework.serializers.IntegerField', 'serializers.IntegerField', ([], {}), '()\n', (132, 134), False, 'from rest_framework import serializers\n'), ((152, 176), 'rest_framework.serializers.FloatField', 'serializers.FloatField', ([], {}), '()\n', (174, 176), False, 'from rest_framework import serializ... |
"""
Copyright 2018 Inmanta
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 ... | [
"jinja2.PackageLoader",
"typing.TypeVar",
"os.path.dirname",
"re.compile"
] | [((1916, 1963), 'typing.TypeVar', 'TypeVar', (['"""Explainable"""'], {'bound': 'CompilerException'}), "('Explainable', bound=CompilerException)\n", (1923, 1963), False, 'from typing import Generic, List, Mapping, Optional, Sequence, Set, Type, TypeVar\n'), ((6623, 6670), 're.compile', 're.compile', (['"""(\\\\x9B|\\\\x... |
# -*- coding: utf-8 -*-
"""
CW, FGSM, and IFGSM Attack CNN
"""
import torch._utils
try:
torch._utils._rebuild_tensor_v2
except AttributeError:
def _rebuild_tensor_v2(storage, storage_offset, size, stride, requires_grad, backward_hooks):
tensor = torch._utils._rebuild_tensor(storage, storage_offset, size... | [
"argparse.ArgumentParser",
"torch.utils.data.DataLoader",
"torch.autograd.Variable",
"torch.load",
"torch.nn.Conv2d",
"os.path.dirname",
"torch.nn.CrossEntropyLoss",
"torch._utils._rebuild_tensor",
"torch.cuda.FloatTensor",
"os.path.isfile",
"torch.clamp",
"numpy.array",
"torch.optim.Adam",
... | [((1203, 1255), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {'description': '"""Fool EnResNet"""'}), "(description='Fool EnResNet')\n", (1226, 1255), False, 'import argparse\n'), ((3100, 3189), 'torch.nn.Conv2d', 'nn.Conv2d', (['in_planes', 'out_planes'], {'kernel_size': '(3)', 'stride': 'stride', 'paddi... |
# Write a Python program to get the name of the host on which the routine is running.
import socket
host_name = socket.gethostname()
print("Host name:", host_name)
| [
"socket.gethostname"
] | [((113, 133), 'socket.gethostname', 'socket.gethostname', ([], {}), '()\n', (131, 133), False, 'import socket\n')] |
# encoding: utf-8
__author__ = "<NAME>"
# Parts of the code have been taken from https://github.com/facebookresearch/fastMRI
import numpy as np
import pytest
import torch
from tests.collections.reconstruction.fastmri.create_temp_data import create_temp_data
# these are really slow - skip by default
SKIP_INTEGRATION... | [
"numpy.product",
"tests.collections.reconstruction.fastmri.create_temp_data.create_temp_data",
"pytest.fixture",
"torch.from_numpy"
] | [((632, 663), 'pytest.fixture', 'pytest.fixture', ([], {'scope': '"""session"""'}), "(scope='session')\n", (646, 663), False, 'import pytest\n'), ((927, 949), 'tests.collections.reconstruction.fastmri.create_temp_data.create_temp_data', 'create_temp_data', (['path'], {}), '(path)\n', (943, 949), False, 'from tests.coll... |
import discord
from discord import Forbidden
from discord.ext import commands
from discord.http import Route
from utils import checks
MUTED_ROLE = "316134780976758786"
class Moderation:
def __init__(self, bot):
self.bot = bot
self.no_ban_logs = set()
@commands.command(hidden=True, pass_cont... | [
"discord.utils.get",
"discord.ext.commands.command",
"discord.Embed",
"utils.checks.mod_or_permissions",
"discord.http.Route"
] | [((281, 341), 'discord.ext.commands.command', 'commands.command', ([], {'hidden': '(True)', 'pass_context': '(True)', 'no_pm': '(True)'}), '(hidden=True, pass_context=True, no_pm=True)\n', (297, 341), False, 'from discord.ext import commands\n'), ((347, 394), 'utils.checks.mod_or_permissions', 'checks.mod_or_permission... |
"""Tibber custom"""
import logging
import homeassistant.helpers.config_validation as cv
import voluptuous as vol
from homeassistant.const import EVENT_HOMEASSISTANT_START
from homeassistant.helpers import discovery
DOMAIN = "tibber_custom"
CONF_USE_DARK_MODE = "use_dark_mode"
CONFIG_SCHEMA = vol.Schema({
DOMAI... | [
"homeassistant.helpers.discovery.load_platform",
"voluptuous.Optional",
"logging.getLogger"
] | [((477, 504), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (494, 504), False, 'import logging\n'), ((647, 706), 'homeassistant.helpers.discovery.load_platform', 'discovery.load_platform', (['hass', '"""camera"""', 'DOMAIN', '{}', 'config'], {}), "(hass, 'camera', DOMAIN, {}, config)\n",... |
# coding=utf-8
# *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from .. import... | [
"pulumi.get",
"pulumi.getter",
"pulumi.ResourceOptions",
"pulumi.set"
] | [((1477, 1508), 'pulumi.getter', 'pulumi.getter', ([], {'name': '"""cidrBlock"""'}), "(name='cidrBlock')\n", (1490, 1508), False, 'import pulumi\n'), ((1812, 1849), 'pulumi.getter', 'pulumi.getter', ([], {'name': '"""reservationType"""'}), "(name='reservationType')\n", (1825, 1849), False, 'import pulumi\n'), ((2217, 2... |
import os
def complier():
print("If ur using this ur so dumb on god just read the install instructions!\n"
"PLEASE HAVE THE requirements.txt FILE IN THE SAME DIRECTORY!!!!")
os.system("pip install -r requirements.txt")
def cleanup():
cmds = ["RD __pycache__ /Q /S",
... | [
"os.getcwd",
"os.system"
] | [((198, 242), 'os.system', 'os.system', (['"""pip install -r requirements.txt"""'], {}), "('pip install -r requirements.txt')\n", (207, 242), False, 'import os\n'), ((434, 453), 'os.system', 'os.system', (['commands'], {}), '(commands)\n', (443, 453), False, 'import os\n'), ((799, 814), 'os.system', 'os.system', (['arg... |
# 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 agreed to in writing, ... | [
"multitest_transport.models.ndb_models.GetPrivateNodeConfig",
"os.path.dirname",
"flask.Flask",
"flask.render_template",
"flask.send_from_directory",
"os.path.join"
] | [((732, 757), 'os.path.dirname', 'os.path.dirname', (['__file__'], {}), '(__file__)\n', (747, 757), False, 'import os\n'), ((772, 805), 'os.path.join', 'os.path.join', (['ROOT_PATH', '"""static"""'], {}), "(ROOT_PATH, 'static')\n", (784, 805), False, 'import os\n'), ((813, 906), 'flask.Flask', 'flask.Flask', (['__name_... |
# -*- coding: utf-8 -*-
# Generated by Django 1.11.7 on 2019-01-10 07:01
from __future__ import unicode_literals
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('app', '0003_auto_20190110_1037'),
]
operations = [
migrations.RenameModel(
... | [
"django.db.migrations.RenameModel"
] | [((288, 359), 'django.db.migrations.RenameModel', 'migrations.RenameModel', ([], {'old_name': '"""Meeting_room"""', 'new_name': '"""MeetingRoom"""'}), "(old_name='Meeting_room', new_name='MeetingRoom')\n", (310, 359), False, 'from django.db import migrations\n'), ((404, 481), 'django.db.migrations.RenameModel', 'migrat... |
'''
async fetching of urls.
Assumes robots checks have already been done.
Supports server mocking; proxies are not yet implemented.
Success returns response object and response bytes (which were already
read in order to shake out all potential network-related exceptions.)
Failure returns enough details for the call... | [
"traceback.print_exc",
"urllib.parse.urlunsplit",
"time.time",
"collections.namedtuple",
"aiohttp.ProxyConnector",
"logging.getLogger"
] | [((705, 732), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (722, 732), False, 'import logging\n'), ((2800, 2941), 'collections.namedtuple', 'namedtuple', (['"""FetcherResponse"""', "['response', 'body_bytes', 'req_headers', 't_first_byte', 't_last_byte',\n 'is_truncated', 'last_excep... |
# Copyright 2021 The Brax Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed t... | [
"brax.physics.base.take",
"brax.Config",
"brax.physics.bodies.Body.from_config",
"jax.numpy.reshape",
"jax.random.uniform",
"jax.numpy.where",
"jax.numpy.linalg.norm",
"jax.numpy.sin",
"brax.envs.env.State",
"jax.numpy.sum",
"jax.vmap",
"jax.numpy.square",
"jax.lax.scan",
"jax.numpy.concat... | [((2031, 2060), 'jax.numpy.array', 'jnp.array', (['[2, 6, 10, 13, 16]'], {}), '([2, 6, 10, 13, 16])\n', (2040, 2060), True, 'import jax.numpy as jnp\n'), ((2095, 2134), 'jax.numpy.array', 'jnp.array', (['[[0, 1], [11, 12], [14, 15]]'], {}), '([[0, 1], [11, 12], [14, 15]])\n', (2104, 2134), True, 'import jax.numpy as jn... |
# TODOS
#--------------------------------------
# imports
import matplotlib.pyplot as plt
from atalaia.atalaia import Atalaia
import numpy as np
import networkx as nx
class Explore:
"""Explore is used for text exploratory tasks.
"""
def __init__(self, language:str):
"""
Parameters
... | [
"matplotlib.pyplot.show",
"matplotlib.pyplot.hist",
"matplotlib.pyplot.boxplot",
"matplotlib.pyplot.bar",
"atalaia.atalaia.Atalaia",
"numpy.percentile",
"matplotlib.pyplot.figure",
"numpy.array",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.xlabel"
] | [((585, 607), 'atalaia.atalaia.Atalaia', 'Atalaia', (['self.language'], {}), '(self.language)\n', (592, 607), False, 'from atalaia.atalaia import Atalaia\n'), ((1116, 1133), 'numpy.array', 'np.array', (['lengths'], {}), '(lengths)\n', (1124, 1133), True, 'import numpy as np\n'), ((1854, 1890), 'matplotlib.pyplot.hist',... |
"""Test I/O related functionality."""
import tempfile
import os
import pathlib
def test_cache_dir():
"""Test getting cache directory."""
from sattools.io import get_cache_dir
with tempfile.TemporaryDirectory() as tmpdir:
d = get_cache_dir(tmpdir, "tofu")
assert str(d.parent) == tmpdir
... | [
"sattools.io.get_cache_dir",
"tempfile.TemporaryDirectory",
"sattools.io.plotdir",
"os.environ.copy",
"os.environ.clear",
"os.environ.get",
"sattools.io.nas_data_out",
"pathlib.Path",
"os.environ.pop",
"os.environ.update"
] | [((1315, 1336), 'sattools.io.plotdir', 'plotdir', ([], {'create': '(False)'}), '(create=False)\n', (1322, 1336), False, 'from sattools.io import plotdir\n'), ((1446, 1485), 'sattools.io.plotdir', 'plotdir', ([], {'create': '(False)', 'basedir': 'tmp_path'}), '(create=False, basedir=tmp_path)\n', (1453, 1485), False, 'f... |
'''
gather redshift info across all observations for a given target type; for now from a single tile
'''
#test
#standard python
import sys
import os
import shutil
import unittest
from datetime import datetime
import json
import numpy as np
import fitsio
import glob
import argparse
from astropy.table import Table,join... | [
"os.mkdir",
"argparse.ArgumentParser",
"os.walk",
"os.path.exists",
"astropy.table.join",
"astropy.table.vstack",
"fitsio.read",
"numpy.unique"
] | [((383, 408), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {}), '()\n', (406, 408), False, 'import argparse\n'), ((1314, 1354), 'os.path.exists', 'os.path.exists', (["(svdir + 'redshift_comps')"], {}), "(svdir + 'redshift_comps')\n", (1328, 1354), False, 'import os\n'), ((1358, 1392), 'os.mkdir', 'os.mkdi... |
import cv2
import numpy as np
cap = cv2.VideoCapture('grace4.mp4')
def make_360p():
cap.set(3, 480)
cap.set(4, 360)
def rescale_frame(frame):
percent = 25;
width = int(frame.shape[1] * percent/100)
height = int(frame.shape[0] * percent/100)
dim = (width, height)
return cv2.resize(frame, d... | [
"cv2.boundingRect",
"cv2.createBackgroundSubtractorMOG2",
"cv2.findContours",
"cv2.contourArea",
"cv2.waitKey",
"cv2.imshow",
"cv2.transpose",
"cv2.VideoCapture",
"cv2.rectangle",
"cv2.flip",
"cv2.destroyAllWindows",
"cv2.resize"
] | [((37, 67), 'cv2.VideoCapture', 'cv2.VideoCapture', (['"""grace4.mp4"""'], {}), "('grace4.mp4')\n", (53, 67), False, 'import cv2\n'), ((370, 406), 'cv2.createBackgroundSubtractorMOG2', 'cv2.createBackgroundSubtractorMOG2', ([], {}), '()\n', (404, 406), False, 'import cv2\n'), ((1072, 1095), 'cv2.destroyAllWindows', 'cv... |
#!/usr/bin/env python
# $Id$
"""74 solutions"""
import puzzler
from puzzler.puzzles.hexiamonds import Hexiamonds4x9
puzzler.run(Hexiamonds4x9)
| [
"puzzler.run"
] | [((119, 145), 'puzzler.run', 'puzzler.run', (['Hexiamonds4x9'], {}), '(Hexiamonds4x9)\n', (130, 145), False, 'import puzzler\n')] |
"""
This module constructs network of streets.
"""
import numpy as np
import json
# Adobe flat UI colour scheme
DARK_BLUE = "#2C3E50"
MEDIUM_BLUE = "#2980B9"
LIGHT_BLUE = "#3498DB"
RED = "#E74C3C"
WHITE = "#ECF0F1"
# Colour parameters
STROKE_COLOUR = DARK_BLUE
STREET_COLOUR = DARK_BLUE
JUNCTION_COLOUR = MEDIUM_BLUE
... | [
"json.dump",
"numpy.zeros",
"numpy.array",
"numpy.log10",
"numpy.delete"
] | [((2673, 2725), 'numpy.zeros', 'np.zeros', (['(self.__nodes, self.__nodes)'], {'dtype': 'np.int'}), '((self.__nodes, self.__nodes), dtype=np.int)\n', (2681, 2725), True, 'import numpy as np\n'), ((3291, 3318), 'numpy.zeros', 'np.zeros', (['(self.__nodes, 2)'], {}), '((self.__nodes, 2))\n', (3299, 3318), True, 'import n... |
# _*_ coding: utf-8 _*_
import re
__author__ = "andan"
__data__ = "2018/9/22 12:44"
from django import forms
from operation.models import UserAsk
class UserAskForm(forms.ModelForm):
class Meta:
model = UserAsk
fields = ['name', 'moblie', 'course_name']
def clean_moblie(self):
moblie... | [
"django.forms.ValidationError",
"re.compile"
] | [((405, 429), 're.compile', 're.compile', (['REGEX_MOBILE'], {}), '(REGEX_MOBILE)\n', (415, 429), False, 'import re\n'), ((516, 570), 'django.forms.ValidationError', 'forms.ValidationError', (['"""手机号码非法"""'], {'code': '"""mobile_invaild"""'}), "('手机号码非法', code='mobile_invaild')\n", (537, 570), False, 'from django impo... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#This script scores results from each student
#Drawn images are downloaded from a .csv file, converted from string base64 encoding,
#and scored against machine learning models saved to disk
import csv
import os
#import file
import cv2
import re
import base64
import nump... | [
"os.remove",
"csv.reader",
"csv.writer",
"tkinter.Button",
"csv.field_size_limit",
"tkinter.filedialog.askopenfilename",
"base64.b64decode",
"tkinter.filedialog.askdirectory",
"tkinter.simpledialog.askstring",
"cv2.imread",
"keras.models.model_from_json",
"numpy.array",
"numpy.amax",
"re.f... | [((741, 770), 'csv.field_size_limit', 'csv.field_size_limit', (['(2 ** 30)'], {}), '(2 ** 30)\n', (761, 770), False, 'import csv\n'), ((10354, 10361), 'tkinter.Tk', 'tk.Tk', ([], {}), '()\n', (10359, 10361), True, 'import tkinter as tk\n'), ((10412, 10481), 'tkinter.Button', 'tk.Button', (['root'], {'text': '"""Select ... |
from typing import Tuple, Union, Dict, Optional, Any
import re
from mandarin.core import ELEMENTS
class NodeHasNoValueError(Exception):
pass
class Parser:
def __init__(self):
pass
@staticmethod
def remove_white_space(value: str) -> str:
cleaned_val = value.lstrip()
# TODO ... | [
"re.split"
] | [((1959, 1987), 're.split', 're.split', (['"""\\\\(|\\\\)"""', 'element'], {}), "('\\\\(|\\\\)', element)\n", (1967, 1987), False, 'import re\n')] |
import math
import os
import sys
import pprint
def count_sort_func(data,maxdata,index):
maxdata +=1
count_list = [0]*(maxdata)
count_dict = data
for n in data:
count_list[n[index]] +=1
i = 0
count = 0
for n in range(len(count_list)):
print(n)
while(count_list[n]>0):
for... | [
"pprint.pprint"
] | [((441, 466), 'pprint.pprint', 'pprint.pprint', (['count_dict'], {}), '(count_dict)\n', (454, 466), False, 'import pprint\n')] |
'''
Root task (Crunchbase)
========================
Luigi routine to collect all data from the Crunchbase data dump and load it to MySQL.
'''
import luigi
import datetime
import logging
from nesta.core.routines.datasets.crunchbase.crunchbase_parent_id_collect_task import ParentIdCollectTask
from nesta.core.routines.... | [
"nesta.core.orms.orm_utils.get_class_by_tablename",
"nesta.core.luigihacks.misctools.find_filepath_from_pathstub",
"datetime.date.today",
"luigi.Parameter",
"nesta.core.routines.datasets.crunchbase.crunchbase_parent_id_collect_task.ParentIdCollectTask",
"nesta.core.routines.datasets.crunchbase.crunchbase_... | [((1091, 1125), 'luigi.BoolParameter', 'luigi.BoolParameter', ([], {'default': '(False)'}), '(default=False)\n', (1110, 1125), False, 'import luigi\n'), ((1150, 1181), 'luigi.IntParameter', 'luigi.IntParameter', ([], {'default': '(500)'}), '(default=500)\n', (1168, 1181), False, 'import luigi\n'), ((1270, 1304), 'luigi... |
from flask import Blueprint, Flask, render_template, request
blueprint = Blueprint(__name__, __name__, url_prefix='/auth')
@blueprint.route('/login', methods=['GET', 'POST'])
def login():
if request.method != 'POST':
return render_template("login_start.jinja")
print(request.form)
return 'You "log... | [
"flask.Blueprint",
"flask.render_template"
] | [((74, 123), 'flask.Blueprint', 'Blueprint', (['__name__', '__name__'], {'url_prefix': '"""/auth"""'}), "(__name__, __name__, url_prefix='/auth')\n", (83, 123), False, 'from flask import Blueprint, Flask, render_template, request\n'), ((239, 275), 'flask.render_template', 'render_template', (['"""login_start.jinja"""']... |
import struct
import itertools
polys = [
[ (1.0, 2.5), (3.5, 4.0), (2.5, 1.5) ],
[ (7.0, 1.2), (5.1, 3.0), (0.5, 7.5), (0.8, 9.0) ],
[ (3.4, 6.3), (1.2, 0.5), (4.6, 9.2) ],
]
def write_polys(filename, polys):
# Determine bounding box
flattened = list(itertools.chain(*... | [
"struct.pack",
"itertools.chain",
"struct.calcsize"
] | [((303, 326), 'itertools.chain', 'itertools.chain', (['*polys'], {}), '(*polys)\n', (318, 326), False, 'import itertools\n'), ((796, 818), 'struct.calcsize', 'struct.calcsize', (['"""<dd"""'], {}), "('<dd')\n", (811, 818), False, 'import struct\n'), ((839, 866), 'struct.pack', 'struct.pack', (['"""<i"""', '(size + 4)']... |
from glob import glob
import os
import os.path as op
from shutil import copyfile
from nose.tools import assert_raises
import numpy as np
from numpy.testing import assert_array_almost_equal
import mne
from mne.datasets import testing
from mne.transforms import (Transform, apply_trans, rotation, translation,
... | [
"mne.coreg.fit_matched_points",
"os.remove",
"mne.utils._TempDir",
"mne.utils.run_tests_if_main",
"mne.setup_volume_source_space",
"mne.coreg.coregister_fiducials",
"glob.glob",
"numpy.testing.assert_array_almost_equal",
"os.path.join",
"mne.read_source_spaces",
"mne.source_space.write_source_sp... | [((6417, 6436), 'mne.utils.run_tests_if_main', 'run_tests_if_main', ([], {}), '()\n', (6434, 6436), False, 'from mne.utils import _TempDir, run_tests_if_main\n'), ((950, 1084), 'numpy.array', 'np.array', (['[[-0.08061612, -0.02908875, -0.04131077], [0.00146763, 0.08506715, -\n 0.03483611], [0.08436285, -0.02850276, ... |
import util
import pygame
import math
import images
class Particles(util.Block):
lifetime = 100
def __init__(self, x, y, n=10, lifetime=10, imgname=images.particleDefault):
super().__init__(x, y, imgname)
self.particles_xyd = list() # координаты и скорости частицы (x, y, dx, dy)
spd =... | [
"math.cos",
"math.sin"
] | [((464, 493), 'math.cos', 'math.cos', (['(i * 2 * math.pi / n)'], {}), '(i * 2 * math.pi / n)\n', (472, 493), False, 'import math\n'), ((518, 547), 'math.sin', 'math.sin', (['(i * 2 * math.pi / n)'], {}), '(i * 2 * math.pi / n)\n', (526, 547), False, 'import math\n')] |
"""HTTP module for CFEngine"""
import os
import urllib
import urllib.request
import ssl
import json
from cfengine import PromiseModule, ValidationError, Result
_SUPPORTED_METHODS = {"GET", "POST", "PUT", "DELETE", "PATCH"}
class HTTPPromiseModule(PromiseModule):
def __init__(self, *args, **kwargs):
su... | [
"os.path.isabs",
"ssl.SSLContext",
"urllib.request.Request",
"os.path.getsize",
"urllib.request.urlopen",
"json.dumps",
"cfengine.ValidationError"
] | [((5342, 5419), 'urllib.request.Request', 'urllib.request.Request', ([], {'url': 'url', 'data': 'payload', 'method': 'method', 'headers': 'headers'}), '(url=url, data=payload, method=method, headers=headers)\n', (5364, 5419), False, 'import urllib\n'), ((562, 603), 'cfengine.ValidationError', 'ValidationError', (['"""\... |
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import sys
from pycket import impersonators as imp
from pycket import values, values_string
from pycket.hash.base import W_HashTable, W_ImmutableHashTable, w_missing
from pycket.hash.simple import (
W_EqvMutableHashTable, W_EqMutableHashTa... | [
"pycket.values.Values._make2",
"pycket.hash.simple.make_simple_immutable_table",
"pycket.interpreter.check_one_val",
"pycket.prims.expose.expose",
"pycket.hash.simple.make_simple_mutable_table_assocs",
"pycket.interpreter.return_value",
"pycket.prims.expose.define_nyi",
"pycket.values.W_Fixnum",
"py... | [((1430, 1459), 'rpython.rlib.objectmodel.specialize.arg', 'objectmodel.specialize.arg', (['(4)'], {}), '(4)\n', (1456, 1459), False, 'from rpython.rlib import jit, objectmodel\n'), ((7113, 7127), 'pycket.prims.expose.expose', 'expose', (['"""hash"""'], {}), "('hash')\n", (7119, 7127), False, 'from pycket.prims.expose ... |
import sys
try:
from PIL import Image, ImageFilter
except ImportError:
print("error:", sys.argv[0], "requires Pillow - install it via 'pip install Pillow'")
sys.exit(2)
if len(sys.argv) != 3:
print("error - usage:", sys.argv[0], "input_file output_file")
sys.exit(2)
input_filename = sys.argv[1]
... | [
"sys.exit",
"PIL.Image.open"
] | [((278, 289), 'sys.exit', 'sys.exit', (['(2)'], {}), '(2)\n', (286, 289), False, 'import sys\n'), ((377, 403), 'PIL.Image.open', 'Image.open', (['input_filename'], {}), '(input_filename)\n', (387, 403), False, 'from PIL import Image, ImageFilter\n'), ((170, 181), 'sys.exit', 'sys.exit', (['(2)'], {}), '(2)\n', (178, 18... |
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('vendors', '0028_auto_20180211_1350'),
('contracts', '0024_auto_20180205_0342'),
]
operations = [
migrations.RunSQL("... | [
"django.db.migrations.RunSQL"
] | [((301, 416), 'django.db.migrations.RunSQL', 'migrations.RunSQL', (['"""UPDATE django_content_type SET app_label = \'contracts\' WHERE app_label = \'contract\';"""'], {}), '(\n "UPDATE django_content_type SET app_label = \'contracts\' WHERE app_label = \'contract\';"\n )\n', (318, 416), False, 'from django.db imp... |
from enum import Enum, auto
class State(Enum):
USR_START = auto()
#
# SYS_GENRE = auto()
# USR_GENRE = auto()
# SYS_WEEKDAY = auto()
USR_WHAT_FAV = auto()
SYS_CHECK_POSITIVE = auto()
SYS_CHECK_NEGATIVE = auto()
SYS_CHECK_NEUTRAL = auto()
SYS_GET_REASON = auto()
USR_REPEAT =... | [
"enum.auto"
] | [((65, 71), 'enum.auto', 'auto', ([], {}), '()\n', (69, 71), False, 'from enum import Enum, auto\n'), ((174, 180), 'enum.auto', 'auto', ([], {}), '()\n', (178, 180), False, 'from enum import Enum, auto\n'), ((206, 212), 'enum.auto', 'auto', ([], {}), '()\n', (210, 212), False, 'from enum import Enum, auto\n'), ((238, 2... |
# -*- coding: utf-8 -*-
"""Class for tests of pysiaalarm."""
import json
import logging
import random
import socket
import threading
import time
import pytest
from mock import patch
from pysiaalarm import InvalidAccountFormatError
from pysiaalarm import InvalidAccountLengthError
from pysiaalarm import InvalidKeyFormat... | [
"threading.Thread",
"json.load",
"time.sleep",
"pysiaalarm.SIAAccount",
"pytest.mark.parametrize",
"pysiaalarm.SIAEvent",
"logging.getLogger"
] | [((574, 601), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (591, 601), False, 'import logging\n'), ((800, 1116), 'pytest.mark.parametrize', 'pytest.mark.parametrize', (['"""line, account, type, code"""', '[(\n \'98100078"*SIA-DCS"5994L0#AAA[5AB718E008C616BF16F6468033A11326B0F7546CAB2... |
import json
from requests_html import HTMLSession
from helpers import compare_trees, get_content_tree
MAIN_URL = r'http://docente.ifrn.edu.br/abrahaolopes/2017.1-integrado/2.02401.1v-poo'
def main():
session = HTMLSession()
current_tree = get_content_tree(MAIN_URL, session)
with open('storage/tree.json... | [
"json.load",
"helpers.compare_trees",
"json.dumps",
"helpers.get_content_tree",
"requests_html.HTMLSession"
] | [((219, 232), 'requests_html.HTMLSession', 'HTMLSession', ([], {}), '()\n', (230, 232), False, 'from requests_html import HTMLSession\n'), ((252, 287), 'helpers.get_content_tree', 'get_content_tree', (['MAIN_URL', 'session'], {}), '(MAIN_URL, session)\n', (268, 287), False, 'from helpers import compare_trees, get_conte... |
import sys
from io import StringIO
def zen_of_python() -> list[str]:
"""
Dump the Zen of Python into a variable
https://stackoverflow.com/a/23794519
"""
zen = StringIO()
old_stdout = sys.stdout
sys.stdout = zen
import this # noqa F401
sys.stdout = old_stdout
return zen.getval... | [
"io.StringIO",
"pyperclip.copy"
] | [((181, 191), 'io.StringIO', 'StringIO', ([], {}), '()\n', (189, 191), False, 'from io import StringIO\n'), ((415, 434), 'pyperclip.copy', 'pyperclip.copy', (['zen'], {}), '(zen)\n', (429, 434), False, 'import pyperclip\n')] |
import unittest
from exceptions import RangeValidationException
from weight_calculator import calculate_weights, validate_rages, validate_grades_and_ranges
class WeightCalculatorTest(unittest.TestCase):
def range_validation_tests(self):
self.assertFalse(validate_rages({
"Final": [50, 60],
... | [
"weight_calculator.validate_grades_and_ranges",
"weight_calculator.calculate_weights",
"weight_calculator.validate_rages"
] | [((2751, 2784), 'weight_calculator.calculate_weights', 'calculate_weights', (['grades', 'ranges'], {}), '(grades, ranges)\n', (2768, 2784), False, 'from weight_calculator import calculate_weights, validate_rages, validate_grades_and_ranges\n'), ((270, 355), 'weight_calculator.validate_rages', 'validate_rages', (["{'Fin... |
import torch
import torch.nn.functional as F
from torch.nn import Parameter
from .metrics import Beta_divergence
from .base import Base
from tqdm import tqdm
def _mu_update(param, pos, gamma, l1_reg, l2_reg, constant_rows=None):
if param.grad is None:
return
# prevent negative term, very likely to hap... | [
"tqdm.tqdm",
"torch.rand",
"torch.nn.functional.conv2d",
"torch.nn.functional.conv3d",
"torch.nn.functional.conv1d",
"torch.nn.functional.relu",
"torch.no_grad",
"torch.tensor"
] | [((373, 411), 'torch.nn.functional.relu', 'F.relu', (['(pos - param.grad)'], {'inplace': '(True)'}), '(pos - param.grad, inplace=True)\n', (379, 411), True, 'import torch.nn.functional as F\n'), ((2867, 2908), 'tqdm.tqdm', 'tqdm', ([], {'total': 'max_iter', 'disable': '(not verbose)'}), '(total=max_iter, disable=not ve... |
from gensim.models import KeyedVectors
import pprint
import json
PATH_DATA = '../data/sake_dataset_v1.json'
def preprocessing(sake_data):
return sake_data.strip().replace(' ', '_')
def fix_data(data):
fixed_data = []
for k, v in sorted(data.items(), key=lambda x:x[0]):
if 'mean' in v:
... | [
"json.load",
"gensim.models.KeyedVectors.load_word2vec_format"
] | [((806, 845), 'gensim.models.KeyedVectors.load_word2vec_format', 'KeyedVectors.load_word2vec_format', (['path'], {}), '(path)\n', (839, 845), False, 'from gensim.models import KeyedVectors\n'), ((730, 742), 'json.load', 'json.load', (['f'], {}), '(f)\n', (739, 742), False, 'import json\n')] |
"""Psychopy ElementArrayStim with flexible pedestal luminance.
Psychopy authors have said on record that this functionality should exist in
Psychopy itself. Future users of this code should double check as to whether
that has been implemented and if this code can be excised.
Note however that we have also added some ... | [
"psychopy._shadersPyglet.compileProgram",
"ctypes.POINTER"
] | [((4092, 4158), 'psychopy._shadersPyglet.compileProgram', 'shaders.compileProgram', (['shaders.vertSimple', 'fragSignedColorTexMask'], {}), '(shaders.vertSimple, fragSignedColorTexMask)\n', (4114, 4158), True, 'from psychopy import _shadersPyglet as shaders\n'), ((5402, 5433), 'ctypes.POINTER', 'ctypes.POINTER', (['cty... |
#!/usr/bin/env python
import json
import yaml
sharesFilename = 'simple-exports.json'
with open(sharesFilename, 'r') as f:
shares = json.load(f)
### For Loop to write out playbook for each cluster
for cluster in shares['clusters']:
playbookFilename = 'playbook-simple-exports-%s.yml' % cluster['name']
wit... | [
"json.load",
"yaml.safe_dump"
] | [((138, 150), 'json.load', 'json.load', (['f'], {}), '(f)\n', (147, 150), False, 'import json\n'), ((2747, 2803), 'yaml.safe_dump', 'yaml.safe_dump', (['play', 'playbook'], {'default_flow_style': '(False)'}), '(play, playbook, default_flow_style=False)\n', (2761, 2803), False, 'import yaml\n')] |
from flask import request, Blueprint, send_file
from sasukekun_flask.utils import v1, format_response
from sasukekun_flask.config import API_IMAGE
from .models import PasteFile
ONE_MONTH = 60 * 60 * 24 * 30
upload = Blueprint('upload', __name__)
@upload.route(v1('/upload/'), methods=['GET', 'POST'])
def upload_file(... | [
"flask.Blueprint",
"sasukekun_flask.utils.format_response",
"sasukekun_flask.utils.v1",
"flask.request.form.get"
] | [((218, 247), 'flask.Blueprint', 'Blueprint', (['"""upload"""', '__name__'], {}), "('upload', __name__)\n", (227, 247), False, 'from flask import request, Blueprint, send_file\n'), ((263, 277), 'sasukekun_flask.utils.v1', 'v1', (['"""/upload/"""'], {}), "('/upload/')\n", (265, 277), False, 'from sasukekun_flask.utils i... |
from uuid import uuid4
from datetime import datetime
from time import time
import boto3
from boto3 import Session
from botocore.credentials import RefreshableCredentials
from botocore.session import get_session
from botocore.credentials import InstanceMetadataFetcher
from storages.utils import setting
import logging
... | [
"boto3.session.Session",
"uuid.uuid4",
"logging.debug",
"boto3.Session",
"storages.utils.setting",
"botocore.credentials.RefreshableCredentials.create_from_metadata",
"botocore.session.get_session"
] | [((2028, 2103), 'logging.debug', 'logging.debug', (['"""Found credentials from IAM Role: %s"""', "metadata['role_name']"], {}), "('Found credentials from IAM Role: %s', metadata['role_name'])\n", (2041, 2103), False, 'import logging\n'), ((2323, 2453), 'botocore.credentials.RefreshableCredentials.create_from_metadata',... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
#########
Reporting
#########
*Created on Thu Jun 8 14:40 2017 by <NAME>*
Tools for creating HTML Reports."""
import time
import base64
import os
import gc
import os.path as op
from string import Template
from io import BytesIO as IO
import pandas as pd
from rdkit... | [
"PIL.ImageChops.difference",
"cellpainting2.tools.load_config",
"PIL.Image.new",
"matplotlib.pyplot.clf",
"matplotlib.pyplot.bar",
"IPython.core.display.HTML",
"gc.collect",
"os.path.isfile",
"matplotlib.pyplot.style.use",
"numpy.arange",
"cellpainting2.tools.parameters_from_act_profile_by_val",... | [((607, 632), 'cellpainting2.tools.load_config', 'cpt.load_config', (['"""config"""'], {}), "('config')\n", (622, 632), True, 'from cellpainting2 import tools as cpt\n'), ((684, 712), 'cellpainting2.tools.is_interactive_ipython', 'cpt.is_interactive_ipython', ([], {}), '()\n', (710, 712), True, 'from cellpainting2 impo... |
# -*- coding: utf-8 -*-
# Generated by Django 1.10.4 on 2017-01-01 01:05
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('api_v2', '0007_auto_20170101_0101'),
]
operations = [
migrations.AlterField... | [
"django.db.models.FloatField"
] | [((407, 511), 'django.db.models.FloatField', 'models.FloatField', ([], {'blank': '(True)', 'help_text': '"""Percentage Coefficient - all"""', 'null': '(True)', 'verbose_name': '"""P"""'}), "(blank=True, help_text='Percentage Coefficient - all',\n null=True, verbose_name='P')\n", (424, 511), False, 'from django.db im... |
import numpy as np
import torch
# https://github.com/sfujim/TD3/blob/ade6260da88864d1ab0ed592588e090d3d97d679/utils.py
class ReplayBuffer(object):
def __init__(self, state_dim, action_dim, max_size=int(1e6)):
self.max_size = max_size
self.ptr = 0
self.size = 0
self.state = np.zero... | [
"numpy.load",
"numpy.save",
"numpy.float32",
"numpy.zeros",
"numpy.random.randint",
"torch.cuda.is_available",
"torch.from_numpy"
] | [((313, 344), 'numpy.zeros', 'np.zeros', (['(max_size, state_dim)'], {}), '((max_size, state_dim))\n', (321, 344), True, 'import numpy as np\n'), ((367, 399), 'numpy.zeros', 'np.zeros', (['(max_size, action_dim)'], {}), '((max_size, action_dim))\n', (375, 399), True, 'import numpy as np\n'), ((426, 457), 'numpy.zeros',... |