code stringlengths 22 1.05M | apis listlengths 1 3.31k | extract_api stringlengths 75 3.25M |
|---|---|---|
# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT!
import grpc
from grpc.framework.common import cardinality
from grpc.framework.interfaces.face import utilities as face_utilities
import google.cloud.proto.language.v1beta2.language_service_pb2 as google_dot_cloud_dot_proto_dot_language_dot_v1beta2_d... | [
"grpc.method_handlers_generic_handler",
"grpc.unary_unary_rpc_method_handler"
] | [((6783, 6894), 'grpc.method_handlers_generic_handler', 'grpc.method_handlers_generic_handler', (['"""google.cloud.language.v1beta2.LanguageService"""', 'rpc_method_handlers'], {}), "(\n 'google.cloud.language.v1beta2.LanguageService', rpc_method_handlers)\n", (6819, 6894), False, 'import grpc\n'), ((4753, 5118), 'g... |
import os
import numpy as np
import time
from multiprocessing import Pool
import psutil
import cv2
import matplotlib.pyplot as plt
import av #for better performance
##############################################################################
#For EPM, please select pionts from the OPEN arm to the CLOSE arm and press... | [
"os.mkdir",
"cv2.medianBlur",
"numpy.argmax",
"cv2.getPerspectiveTransform",
"numpy.isnan",
"cv2.ellipse",
"numpy.mean",
"cv2.rectangle",
"cv2.imshow",
"os.path.join",
"psutil.cpu_count",
"cv2.warpPerspective",
"cv2.cvtColor",
"cv2.fitEllipse",
"cv2.setMouseCallback",
"numpy.int32",
... | [((1349, 1372), 'psutil.cpu_count', 'psutil.cpu_count', (['(False)'], {}), '(False)\n', (1365, 1372), False, 'import psutil\n'), ((1793, 1839), 'numpy.zeros', 'np.zeros', ([], {'shape': '(w + h, w + h)', 'dtype': 'np.uint8'}), '(shape=(w + h, w + h), dtype=np.uint8)\n', (1801, 1839), True, 'import numpy as np\n'), ((72... |
from pathlib import Path
from .common import PathIsh, Visit, Source, last, Loc, Results, DbVisit, Context, Res
# add deprecation warning so eventually this may converted to a namespace package?
import warnings
warnings.warn("DEPRECATED! Please import directly from 'promnesia.common', e.g. 'from promnesia.common import... | [
"warnings.warn"
] | [((211, 376), 'warnings.warn', 'warnings.warn', (['"""DEPRECATED! Please import directly from \'promnesia.common\', e.g. \'from promnesia.common import Visit, Source, Results\'"""', 'DeprecationWarning'], {}), '(\n "DEPRECATED! Please import directly from \'promnesia.common\', e.g. \'from promnesia.common import Vis... |
# Inspired from this: https://www.data-blogger.com/2017/02/24/gathering-tweets-with-python/
import tweepy
import json
# Specify the account credentials in the following variables:
# TODO: Get them from an env varibale or secret file
consumer_key = 'INSERT CONSUMER KEY HERE'
consumer_secret = 'INSERT CONSUMER SECRET ... | [
"tweepy.OAuthHandler",
"json.loads",
"tweepy.Stream"
] | [((1039, 1089), 'tweepy.OAuthHandler', 'tweepy.OAuthHandler', (['consumer_key', 'consumer_secret'], {}), '(consumer_key, consumer_secret)\n', (1058, 1089), False, 'import tweepy\n'), ((1206, 1235), 'tweepy.Stream', 'tweepy.Stream', (['auth', 'listener'], {}), '(auth, listener)\n', (1219, 1235), False, 'import tweepy\n'... |
import psycopg2
HOSTNAME = '192.168.1.204'
USERNAME = 'postgres'
PASSWORD = '<PASSWORD>'
DATABASE_NAME = 'data_lake'
PORT = 5432
postgres_connection_string = "postgresql://{DB_USER}:{DB_PASS}@{DB_ADDR}:{PORT}/{DB_NAME}".format(
DB_USER=USERNAME,
DB_PASS=PASSWORD,
DB_ADDR=HOSTNAME,
PORT=PORT,
DB_NA... | [
"psycopg2.connect"
] | [((401, 505), 'psycopg2.connect', 'psycopg2.connect', ([], {'user': 'USERNAME', 'password': 'PASSWORD', 'host': 'HOSTNAME', 'port': 'PORT', 'database': 'DATABASE_NAME'}), '(user=USERNAME, password=PASSWORD, host=HOSTNAME, port=PORT,\n database=DATABASE_NAME)\n', (417, 505), False, 'import psycopg2\n')] |
"""add fortunki table
Revision ID: 567424e5046c
Revises: <PASSWORD>
Create Date: 2019-09-19 18:59:11.629057
"""
import sqlalchemy as sa
from alembic import op
# revision identifiers, used by Alembic.
revision = "567424e5046c"
down_revision = "f32a45256434"
branch_labels = None
depends_on = None
def upgrade():
... | [
"alembic.op.drop_table",
"sqlalchemy.Text",
"alembic.op.f",
"sqlalchemy.Integer"
] | [((795, 820), 'alembic.op.drop_table', 'op.drop_table', (['"""fortunki"""'], {}), "('fortunki')\n", (808, 820), False, 'from alembic import op\n'), ((447, 459), 'sqlalchemy.Integer', 'sa.Integer', ([], {}), '()\n', (457, 459), True, 'import sqlalchemy as sa\n'), ((504, 513), 'sqlalchemy.Text', 'sa.Text', ([], {}), '()\... |
import os
import re
from glob import glob
import pandas as pd
# enloc
#FILE_SUFFIX = '*.enloc.rst'
#FILE_PATTERN = '(?P<pheno>.+)__PM__(?P<tissue>.+)\.enloc\.rst'
# fastenloc
ALL_TISSUES = pd.read_csv('/mnt/phenomexcan/fastenloc/fastenloc_gtex_tissues.txt', header=None, squeeze=True).tolist()
FILE_PREFIX = 'fastenlo... | [
"os.makedirs",
"pandas.read_csv",
"os.system",
"re.escape",
"glob.glob",
"re.search",
"re.compile"
] | [((551, 568), 'glob.glob', 'glob', (['FILE_SUFFIX'], {}), '(FILE_SUFFIX)\n', (555, 568), False, 'from glob import glob\n'), ((607, 631), 're.compile', 're.compile', (['FILE_PATTERN'], {}), '(FILE_PATTERN)\n', (617, 631), False, 'import re\n'), ((948, 981), 'os.makedirs', 'os.makedirs', (['pheno'], {'exist_ok': '(True)'... |
from __future__ import absolute_import, division, print_function
import hashlib
import json
import logging
import subprocess
import tempfile
import time
import requests
from requests.utils import urlparse
__all__ = ['Kubernetes', "get_endpoint"]
logger = logging.getLogger(__name__)
resource_endpoints = {
"daemo... | [
"requests.utils.urlparse",
"tempfile.NamedTemporaryFile",
"json.loads",
"subprocess.check_output",
"json.dumps",
"time.sleep",
"requests.post",
"logging.getLogger"
] | [((258, 285), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (275, 285), False, 'import logging\n'), ((3372, 3393), 'json.loads', 'json.loads', (['self.body'], {}), '(self.body)\n', (3382, 3393), False, 'import json\n'), ((5370, 5399), 'tempfile.NamedTemporaryFile', 'tempfile.NamedTempora... |
from string import Template
const_base = "data/const/degree_order_{}_{}.pkl"
#LRF settings
N = 500
minc = 100
maxc = 100
mu = 0.3
k = 5
#k = 10
#maxk = 20
maxk = 50
t1 = 2
t2 = 1
name_tmp = Template("LRF_${N}_${k}_${maxk}_${minc}_${maxc}_${mu}")
lrf_data_label = name_tmp.substitute(N=N, k=k, maxk=maxk, minc=minc, ma... | [
"string.Template"
] | [((193, 248), 'string.Template', 'Template', (['"""LRF_${N}_${k}_${maxk}_${minc}_${maxc}_${mu}"""'], {}), "('LRF_${N}_${k}_${maxk}_${minc}_${maxc}_${mu}')\n", (201, 248), False, 'from string import Template\n')] |
"""Implement merge sort algorithm."""
from random import randint, shuffle
from timeit import timeit
def merge_sort(nums):
"""Merge list by merge sort."""
half = int(len(nums) // 2)
if len(nums) == 1:
return nums
if len(nums) == 2:
if nums[0] > nums[1]:
nums[0], nums[1] = ... | [
"random.shuffle",
"random.randint"
] | [((1308, 1322), 'random.randint', 'randint', (['(9)', '(50)'], {}), '(9, 50)\n', (1315, 1322), False, 'from random import randint, shuffle\n'), ((1691, 1705), 'random.randint', 'randint', (['(9)', '(50)'], {}), '(9, 50)\n', (1698, 1705), False, 'from random import randint, shuffle\n'), ((1761, 1778), 'random.shuffle', ... |
#!/usr/bin/python3
# Copyright 2017-2018 <NAME>
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice,
# this list of conditions and the followin... | [
"pandas.DataFrame",
"numpy.sum",
"numpy.average",
"numpy.log",
"os.path.basename",
"pandas.read_csv",
"os.path.isdir",
"os.walk",
"six.StringIO",
"multiprocessing.Pool",
"numpy.mean",
"os.path.normpath",
"pytablewriter.MarkdownTableWriter",
"glob.glob",
"pandas.concat"
] | [((1914, 1943), 'pandas.DataFrame', 'pd.DataFrame', ([], {'columns': 'columns'}), '(columns=columns)\n', (1926, 1943), True, 'import pandas as pd\n'), ((3874, 3909), 'pytablewriter.MarkdownTableWriter', 'pytablewriter.MarkdownTableWriter', ([], {}), '()\n', (3907, 3909), False, 'import pytablewriter\n'), ((3986, 4000),... |
import os
import shutil
def copy_file_path(source_path, target_path):
"""复制源文件目录下的所有目录到另一个文件目录下"""
for e, _, _ in os.walk(source_path):
path_name = os.path.splitdrive(e)[1]
file_path = os.path.join(target_path, path_name[len(source_path)-1:])
if not os.path.exists(file_path):
... | [
"os.path.splitdrive",
"os.makedirs",
"os.walk",
"os.path.exists",
"os.path.join",
"shutil.copy"
] | [((124, 144), 'os.walk', 'os.walk', (['source_path'], {}), '(source_path)\n', (131, 144), False, 'import os\n'), ((460, 480), 'os.walk', 'os.walk', (['source_path'], {}), '(source_path)\n', (467, 480), False, 'import os\n'), ((954, 967), 'os.walk', 'os.walk', (['path'], {}), '(path)\n', (961, 967), False, 'import os\n'... |
from __future__ import annotations
from abc import abstractmethod, abstractproperty
from typing import Any, Generic, TYPE_CHECKING, TypeVar, Union
import numpy as np
if TYPE_CHECKING:
from tanuki.data_store.column_alias import ColumnAlias
from tanuki.data_store.index.pandas_index import PandasIndex
C = Ty... | [
"typing.TypeVar"
] | [((318, 363), 'typing.TypeVar', 'TypeVar', (['"""C"""'], {'bound': "tuple['ColumnAlias', ...]"}), "('C', bound=tuple['ColumnAlias', ...])\n", (325, 363), False, 'from typing import Any, Generic, TYPE_CHECKING, TypeVar, Union\n')] |
#! /usr/bin/env python3
import logging
import sys
logging.basicConfig(stream=sys.stdout, level=logging.DEBUG, format='%(asctime)s(%(relativeCreated)6d)[%(threadName)s]%(message)s')
# example of an airborne survey where some of the flight lines get too close to each other
# when gridded, the output contains "tares" th... | [
"intrepid.mastertask_pb2.BatchJob",
"intrepid.utils.Executor.execute",
"logging.basicConfig"
] | [((51, 186), 'logging.basicConfig', 'logging.basicConfig', ([], {'stream': 'sys.stdout', 'level': 'logging.DEBUG', 'format': '"""%(asctime)s(%(relativeCreated)6d)[%(threadName)s]%(message)s"""'}), "(stream=sys.stdout, level=logging.DEBUG, format=\n '%(asctime)s(%(relativeCreated)6d)[%(threadName)s]%(message)s')\n", ... |
# si occupa della gestione delle regole e dei dati privati del server
from server.global_var import GlobalVar
from replicated.game_state import Fase
from server.player_private import PlayerPrivate
from server.deck import Deck, Card
from threading import Timer
from tcp_basics import safe_recv_var
from socket import tim... | [
"threading.Timer",
"server.deck.Card.contiene_carta",
"server.deck.Card",
"server.deck.Deck",
"server.deck.Card.del_carta",
"tcp_basics.safe_recv_var",
"server.deck.Card.carta_permessa"
] | [((769, 775), 'server.deck.Deck', 'Deck', ([], {}), '()\n', (773, 775), False, 'from server.deck import Deck, Card\n'), ((4445, 4504), 'server.deck.Card.contiene_carta', 'Card.contiene_carta', (['giocatore.player_state.mano.val', 'carta'], {}), '(giocatore.player_state.mano.val, carta)\n', (4464, 4504), False, 'from se... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
try:
from setuptools import setup
except ImportError:
from distutils.core import setup
import versioneer
versioneer.VCS = 'git'
versioneer.versionfile_source = 'shotgunCache/_version.py'
versioneer.versionfile_build = 'shotgunCache/_version.py'
versioneer.tag_pre... | [
"versioneer.get_version",
"versioneer.get_cmdclass"
] | [((560, 584), 'versioneer.get_version', 'versioneer.get_version', ([], {}), '()\n', (582, 584), False, 'import versioneer\n'), ((620, 645), 'versioneer.get_cmdclass', 'versioneer.get_cmdclass', ([], {}), '()\n', (643, 645), False, 'import versioneer\n')] |
import os
import sys
if __name__ == "__main__":
train_file = sys.argv[1]
dev_file = sys.argv[2]
test_folder = sys.argv[3]
folder = sys.argv[4]
param_file = sys.argv[5]
partition = sys.argv[6]
bash_script = os.path.join(folder, "parallel_eval_model.sh")
with open(bash_script, 'w+') as ... | [
"os.path.join"
] | [((236, 282), 'os.path.join', 'os.path.join', (['folder', '"""parallel_eval_model.sh"""'], {}), "(folder, 'parallel_eval_model.sh')\n", (248, 282), False, 'import os\n'), ((566, 600), 'os.path.join', 'os.path.join', (['folder_file', '"""error"""'], {}), "(folder_file, 'error')\n", (578, 600), False, 'import os\n'), ((6... |
import tensorflow.compat.v1 as tf
"""
I assume that each file represents a video.
All videos have minimal dimension equal to 256 and fps equal to 6.
Median video length is ~738 frames.
"""
NUM_FRAMES = 4 # must be greater or equal to 2
SIZE = 256 # must be less or equal to 256
class Pipeline:
def __init__(... | [
"tensorflow.compat.v1.stack",
"tensorflow.compat.v1.image.decode_png",
"tensorflow.compat.v1.parse_single_example",
"tensorflow.compat.v1.shape",
"tensorflow.compat.v1.image.crop_to_bounding_box",
"tensorflow.compat.v1.concat",
"tensorflow.compat.v1.random.uniform",
"tensorflow.compat.v1.data.TFRecord... | [((604, 649), 'tensorflow.compat.v1.data.Dataset.from_tensor_slices', 'tf.data.Dataset.from_tensor_slices', (['filenames'], {}), '(filenames)\n', (638, 649), True, 'import tensorflow.compat.v1 as tf\n'), ((2255, 2290), 'tensorflow.compat.v1.stack', 'tf.stack', (['images_and_labels'], {'axis': '(0)'}), '(images_and_labe... |
"""
This CLI plugin was auto-generated by using 'sonic-cli-gen' utility, BUT
it was manually modified to meet the PBH HLD requirements.
PBH HLD - https://github.com/Azure/SONiC/pull/773
CLI Auto-generation tool HLD - https://github.com/Azure/SONiC/pull/78
"""
import click
import json
import ipaddress
import re
import... | [
"click.argument",
"click.get_current_context",
"show.plugins.pbh.deserialize_pbh_counters",
"click.option",
"ipaddress.ip_address",
"click.Choice",
"click.group",
"click.secho",
"click.Abort"
] | [((17412, 17463), 'click.group', 'click.group', ([], {'name': '"""pbh"""', 'cls': 'clicommon.AliasedGroup'}), "(name='pbh', cls=clicommon.AliasedGroup)\n", (17423, 17463), False, 'import click\n'), ((17854, 17911), 'click.argument', 'click.argument', (['"""hash-field-name"""'], {'nargs': '(1)', 'required': '(True)'}), ... |
import sklearn
import pandas as pd
import seaborn as sns
import numpy as np
import matplotlib.pyplot as plt
from sklearn.metrics import classification_report
from sklearn.datasets import load_breast_cancer
from sklearn.model_selection import train_test_split
from sklearn.datasets import load_breast_cancer
from sklearn... | [
"matplotlib.pyplot.title",
"sklearn.model_selection.GridSearchCV",
"sklearn.preprocessing.StandardScaler",
"sklearn.model_selection.train_test_split",
"sklearn.tree.DecisionTreeClassifier",
"sklearn.metrics.classification_report",
"matplotlib.pyplot.figure",
"sklearn.externals.six.StringIO",
"numpy.... | [((998, 1018), 'sklearn.datasets.load_breast_cancer', 'load_breast_cancer', ([], {}), '()\n', (1016, 1018), False, 'from sklearn.datasets import load_breast_cancer\n'), ((1357, 1392), 'sklearn.datasets.load_breast_cancer', 'load_breast_cancer', ([], {'return_X_y': '(True)'}), '(return_X_y=True)\n', (1375, 1392), False,... |
import os
from pyautogui import *
import pyautogui
import time
import keyboard
import random
import win32api, win32con
#This program was written in a few hours, its purpose is to set the computer's power usage.
# Disclaimer: This is an awful way to do it, even the cmds, a better way would be NViAPI but I d... | [
"keyboard.press_and_release",
"win32api.SetCursorPos",
"time.sleep",
"pyautogui.pixel",
"win32api.mouse_event",
"os.startfile",
"win32api.GetCursorPos"
] | [((706, 735), 'win32api.SetCursorPos', 'win32api.SetCursorPos', (['(x, y)'], {}), '((x, y))\n', (727, 735), False, 'import win32api, win32con\n'), ((740, 797), 'win32api.mouse_event', 'win32api.mouse_event', (['win32con.MOUSEEVENTF_LEFTDOWN', '(0)', '(0)'], {}), '(win32con.MOUSEEVENTF_LEFTDOWN, 0, 0)\n', (760, 797), Fa... |
import boto3
import datetime
import argparse
import logging
import sys
from aws_interfaces.s3_interface import S3Interface
from boto3.dynamodb.conditions import Key, Attr
parser = argparse.ArgumentParser()
parser.add_argument("-r", "--region", action="store", required=True, dest="region", help="the region for uploadi... | [
"argparse.ArgumentParser",
"logging.basicConfig",
"boto3.client",
"boto3.dynamodb.conditions.Key",
"datetime.datetime.utcnow",
"aws_interfaces.s3_interface.S3Interface"
] | [((182, 207), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {}), '()\n', (205, 207), False, 'import argparse\n'), ((449, 507), 'logging.basicConfig', 'logging.basicConfig', ([], {'stream': 'sys.stdout', 'level': 'logging.INFO'}), '(stream=sys.stdout, level=logging.INFO)\n', (468, 507), False, 'import loggi... |
#!python
# -*- coding: UTF-8 -*-
'''
################################################################
# Multiprocessing based synchronization.
# @ Sync-stream
# Produced by
# <NAME> @ <EMAIL>,
# <EMAIL>.
# Requirements: (Pay attention to version)
# python 3.6+
# The base module for the message synchroniz... | [
"io.StringIO",
"multiprocessing.Manager",
"threading.Lock",
"multiprocessing.Queue",
"collections.deque"
] | [((1463, 1495), 'collections.deque', 'collections.deque', ([], {'maxlen': 'maxlen'}), '(maxlen=maxlen)\n', (1480, 1495), False, 'import collections\n'), ((1521, 1534), 'io.StringIO', 'io.StringIO', ([], {}), '()\n', (1532, 1534), False, 'import io\n'), ((1567, 1583), 'threading.Lock', 'threading.Lock', ([], {}), '()\n'... |
"""
OpenNEM AEMO facility closure dates parser.
"""
import logging
from datetime import datetime
from pathlib import Path
from typing import List, Optional, Union
from openpyxl import load_workbook
from pydantic import ValidationError
from pydantic.class_validators import validator
from opennem.core.normalizers imp... | [
"openpyxl.load_workbook",
"logging.getLogger",
"pydantic.class_validators.validator",
"pathlib.Path",
"pprint.pprint",
"opennem.core.normalizers.is_number"
] | [((403, 466), 'logging.getLogger', 'logging.getLogger', (['"""opennem.parsers.aemo_nem_facility_closures"""'], {}), "('opennem.parsers.aemo_nem_facility_closures')\n", (420, 466), False, 'import logging\n'), ((818, 841), 'opennem.core.normalizers.is_number', 'is_number', (['closure_year'], {}), '(closure_year)\n', (827... |
import os
import ssl
import smtplib
from typing import Callable
from email.mime.text import MIMEText
from email.mime.image import MIMEImage
from email.mime.multipart import MIMEMultipart
def send_mail(subject: str, log_path: str, img_path: str, get: Callable):
sender = get('email')
api_key = get('api_key')
... | [
"smtplib.SMTP_SSL",
"os.path.basename",
"email.mime.text.MIMEText",
"ssl.create_default_context",
"email.mime.multipart.MIMEMultipart"
] | [((369, 384), 'email.mime.multipart.MIMEMultipart', 'MIMEMultipart', ([], {}), '()\n', (382, 384), False, 'from email.mime.multipart import MIMEMultipart\n'), ((623, 636), 'email.mime.text.MIMEText', 'MIMEText', (['log'], {}), '(log)\n', (631, 636), False, 'from email.mime.text import MIMEText\n'), ((812, 840), 'ssl.cr... |
# MIT License
#
# Copyright (c) 2019 <NAME>
#
# 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,... | [
"os.environ.get",
"supporting.log",
"logging.getLogger"
] | [((1424, 1451), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (1441, 1451), False, 'import supporting, os, logging\n'), ((1700, 1758), 'supporting.log', 'supporting.log', (['logger', 'logging.DEBUG', 'thisproc', '"""started"""'], {}), "(logger, logging.DEBUG, thisproc, 'started')\n", (17... |
import argparse
import time
import os
import numpy as np
import json
import cv2
import random
import torch
from ACID_test import test
# Setup detectron2 logger
import detectron2
from detectron2.utils.logger import setup_logger
setup_logger()
# import some common detectron2 utilities
from detectron2.model_zoo import m... | [
"argparse.ArgumentParser",
"detectron2.data.DatasetCatalog.get",
"detectron2.utils.logger.setup_logger",
"detectron2.evaluation.COCOEvaluator",
"detectron2.data.datasets.register_coco_instances",
"detectron2.config.get_cfg",
"detectron2.model_zoo.model_zoo.get_config_file",
"detectron2.engine.DefaultT... | [((228, 242), 'detectron2.utils.logger.setup_logger', 'setup_logger', ([], {}), '()\n', (240, 242), False, 'from detectron2.utils.logger import setup_logger\n'), ((809, 875), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {'description': '"""ACID_Object_Detection_Train"""'}), "(description='ACID_Object_Dete... |
import django.core.validators
import django.utils.timezone
import model_utils.fields
from django.conf import settings
from django.db import migrations, models
from opaque_keys.edx.django.models import CourseKeyField
class Migration(migrations.Migration):
dependencies = [
migrations.swappable_dependency(s... | [
"django.db.models.TextField",
"django.db.migrations.swappable_dependency",
"django.db.models.CharField",
"opaque_keys.edx.django.models.CourseKeyField",
"django.db.models.ForeignKey",
"django.db.models.AutoField",
"django.db.migrations.AlterUniqueTogether"
] | [((287, 344), 'django.db.migrations.swappable_dependency', 'migrations.swappable_dependency', (['settings.AUTH_USER_MODEL'], {}), '(settings.AUTH_USER_MODEL)\n', (318, 344), False, 'from django.db import migrations, models\n'), ((2300, 2393), 'django.db.migrations.AlterUniqueTogether', 'migrations.AlterUniqueTogether',... |
import datetime as dt
from json import dumps as json_dumps
from django.urls import reverse
from rest_framework import status
from rest_framework.test import APITestCase
from registration.models import User
from events.models import SoloEvent
from event_registrations.models import SoloEventRegistration
from payments.mod... | [
"datetime.date",
"json.dumps",
"django.urls.reverse",
"datetime.time",
"event_registrations.models.SoloEventRegistration.objects.create",
"payments.models.Transaction.objects.create",
"registration.models.User.objects.create"
] | [((435, 558), 'registration.models.User.objects.create', 'User.objects.create', ([], {'username': '"""test_user1"""', 'first_name': '"""test"""', 'last_name': '"""user"""', 'email': '"""<EMAIL>"""', 'email_confirmed': '(True)'}), "(username='test_user1', first_name='test', last_name=\n 'user', email='<EMAIL>', email... |
import requests
image = {'image': open('data/test_photo.jpeg', 'rb').read()}
r1 = requests.get("http://0.0.0.0:5000/")
print(r1.text)
r2 = requests.post("http://localhost:5000/get_prob", files=image)
print(r2.text) # "Male" or "Female" | [
"requests.post",
"requests.get"
] | [((84, 120), 'requests.get', 'requests.get', (['"""http://0.0.0.0:5000/"""'], {}), "('http://0.0.0.0:5000/')\n", (96, 120), False, 'import requests\n'), ((142, 202), 'requests.post', 'requests.post', (['"""http://localhost:5000/get_prob"""'], {'files': 'image'}), "('http://localhost:5000/get_prob', files=image)\n", (15... |
#!/usr/bin/env python
# coding=utf-8
from PyQt4.QtCore import *
import requests
import re, os
from OCR import Image2txt
from PIL import Image
class backEnd(QThread):
finish_signal = pyqtSignal(str, bool)
def __init__(self, txt):
super(backEnd, self).__init__()
self.txt = txt
def run(self):
path = '../OCR/te... | [
"os.mkdir",
"os.path.exists",
"PIL.Image.open",
"re.findall",
"requests.get",
"OCR.Image2txt.picture_ocr"
] | [((829, 872), 're.findall', 're.findall', (['""""objURL":"(.*?)","""', 'html', 're.S'], {}), '(\'"objURL":"(.*?)",\', html, re.S)\n', (839, 872), False, 'import re, os\n'), ((337, 357), 'os.path.exists', 'os.path.exists', (['path'], {}), '(path)\n', (351, 357), False, 'import re, os\n'), ((362, 376), 'os.mkdir', 'os.mk... |
__source__ = 'https://leetcode.com/problems/bulb-switcher/description/'
# Time: O(1)
# Space: O(1)
#
# Description: Leetcode # 319. Bulb Switcher
#
# There are n bulbs that are initially off.
# You first turn on all the bulbs.
# Then, you turn off every second bulb.
# On the third round, you toggle every third bulb (t... | [
"unittest.main",
"math.sqrt"
] | [((1247, 1262), 'unittest.main', 'unittest.main', ([], {}), '()\n', (1260, 1262), False, 'import unittest\n'), ((1105, 1117), 'math.sqrt', 'math.sqrt', (['n'], {}), '(n)\n', (1114, 1117), False, 'import math\n')] |
from setuptools import setup
setup(
name='V16_API',
packages=['V16_API'],
include_package_data=True,
install_requires=[
'flask', 'flask-bootstrap', 'flask-nav', 'pyserial', 'flask_wtf', 'gunicorn'
],
)
| [
"setuptools.setup"
] | [((32, 207), 'setuptools.setup', 'setup', ([], {'name': '"""V16_API"""', 'packages': "['V16_API']", 'include_package_data': '(True)', 'install_requires': "['flask', 'flask-bootstrap', 'flask-nav', 'pyserial', 'flask_wtf', 'gunicorn']"}), "(name='V16_API', packages=['V16_API'], include_package_data=True,\n install_re... |
import torch.nn as nn
from matplotlib import pyplot as plt
def MLP(input_dim, out_dims):
"""
Creates an MLP for the models.
:param input_dim: Integer containing the dimensions of the input (= x_dim + y_dim).
:param out_dims: An iterable containing the output sizes of the layers of the MLP.
:retur... | [
"matplotlib.pyplot.show",
"torch.nn.ReLU",
"matplotlib.pyplot.plot",
"torch.nn.Sequential",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.yticks",
"torch.nn.Linear",
"matplotlib.pyplot.gca",
"matplotlib.pyplot.fill_between",
"matplotlib.pyplot.xticks",
"matplotlib.pyplot.savefig"
] | [((761, 783), 'torch.nn.Sequential', 'nn.Sequential', (['*layers'], {}), '(*layers)\n', (774, 783), True, 'import torch.nn as nn\n'), ((1939, 1996), 'matplotlib.pyplot.plot', 'plt.plot', (['target_x[0]', 'pred_y[0]', '"""tab:blue"""'], {'linewidth': '(2)'}), "(target_x[0], pred_y[0], 'tab:blue', linewidth=2)\n", (1947,... |
# -*- coding: utf-8 -*-
from __future__ import absolute_import
import numpy as np
from ..utils.generic_utils import get_uid
class Layer():
"""Abstract base layer class."""
def __init__(self, **kwargs):
self._trainable_weights = []
self._non_trainable_weights = []
self._grads = {} # (... | [
"numpy.zeros_like",
"numpy.expand_dims"
] | [((1652, 1682), 'numpy.expand_dims', 'np.expand_dims', (['weight'], {'axis': '(0)'}), '(weight, axis=0)\n', (1666, 1682), True, 'import numpy as np\n'), ((1727, 1748), 'numpy.zeros_like', 'np.zeros_like', (['weight'], {}), '(weight)\n', (1740, 1748), True, 'import numpy as np\n'), ((2777, 2802), 'numpy.zeros_like', 'np... |
# coding: utf-8
from django.test import TestCase
from djutils.testrunner import TearDownTestCaseMixin
from parkkeeper import models
from parkkeeper import factories
class BaseTaskTestCase(TearDownTestCaseMixin, TestCase):
def tearDown(self):
self.tearDownMongo()
def test_get_task_model_monit(self):... | [
"parkkeeper.factories.MonitTask",
"parkkeeper.models.BaseTask.get_task_model",
"parkkeeper.factories.WorkTask"
] | [((342, 363), 'parkkeeper.factories.MonitTask', 'factories.MonitTask', ([], {}), '()\n', (361, 363), False, 'from parkkeeper import factories\n'), ((432, 473), 'parkkeeper.models.BaseTask.get_task_model', 'models.BaseTask.get_task_model', (['task_type'], {}), '(task_type)\n', (462, 473), False, 'from parkkeeper import ... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Copyright (c) 2017 <NAME> <<EMAIL>>
from distutils.core import setup
setup(
name = 'sim-tree',
packages = ['sim_tree'], # this must be the same as the name above
install_requires = ['os', 'pandas', 'time', 'string'],
version = '0.6',
description = 'A module f... | [
"distutils.core.setup"
] | [((120, 548), 'distutils.core.setup', 'setup', ([], {'name': '"""sim-tree"""', 'packages': "['sim_tree']", 'install_requires': "['os', 'pandas', 'time', 'string']", 'version': '"""0.6"""', 'description': '"""A module for automating hierarchical simulation studies"""', 'author': '"""<NAME>"""', 'author_email': '"""<EMAI... |
from django.http.response import JsonResponse
from django.utils.translation import ugettext_lazy as _
from rest_framework import status
from jwt_devices import views
from jwt_devices.settings import api_settings
class PermittedHeadersMiddleware(object):
"""
Middleware used to disallow sending the permanent_t... | [
"django.utils.translation.ugettext_lazy"
] | [((1074, 1132), 'django.utils.translation.ugettext_lazy', '_', (['"""Using the Permanent-Token header is disallowed for {}"""'], {}), "('Using the Permanent-Token header is disallowed for {}')\n", (1075, 1132), True, 'from django.utils.translation import ugettext_lazy as _\n')] |
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [('reader', '0004_float_numbers')]
operations = [
migrations.CreateModel(
name='Category',
fields=[
('id', models.CharField(
auto_created=True, p... | [
"django.db.models.CharField",
"django.db.models.ManyToManyField"
] | [((1029, 1085), 'django.db.models.ManyToManyField', 'models.ManyToManyField', ([], {'blank': '(True)', 'to': '"""reader.Category"""'}), "(blank=True, to='reader.Category')\n", (1051, 1085), False, 'from django.db import migrations, models\n'), ((262, 351), 'django.db.models.CharField', 'models.CharField', ([], {'auto_c... |
from Constants import CONST_IDX, LINR_IDX, KAPPA_IDX, CALPHA_IDX, SQRTPLUS_IDX, EXACT_CUBIC_CONSTANT, STANDARD_IDXS, CUBIC_EXACT_IDXS, QUADRATIC_FORWARD_EXACT_IDXS, NOTORIGIN_IDXS
from LoewnerRun import LoewnerRun, ConstantLoewnerRun, LinearLoewnerRun, KappaLoewnerRun, CAlphaLoewnerRun, SqrtTPlusOneLoewnerRun
class Lo... | [
"LoewnerRun.KappaLoewnerRun",
"LoewnerRun.ConstantLoewnerRun",
"LoewnerRun.LinearLoewnerRun",
"LoewnerRun.CAlphaLoewnerRun",
"LoewnerRun.LoewnerRun",
"LoewnerRun.SqrtTPlusOneLoewnerRun"
] | [((2883, 3011), 'LoewnerRun.LoewnerRun', 'LoewnerRun', (['index', 'start_time', 'final_time', 'outer_points', 'inner_points', 'self.compile_modules', 'self.save_data', 'self.save_plot'], {}), '(index, start_time, final_time, outer_points, inner_points, self.\n compile_modules, self.save_data, self.save_plot)\n', (28... |
"""
Copyright 2010 <NAME>, <NAME>, and <NAME>
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing... | [
"django.contrib.admin.autodiscover"
] | [((680, 700), 'django.contrib.admin.autodiscover', 'admin.autodiscover', ([], {}), '()\n', (698, 700), False, 'from django.contrib import admin\n')] |
from serial import *
import serial.tools.list_ports
#import serial.tools.list_ports
import jsonConfig as j
import time
#connected_devices=[""]
def serialConnection(values,device):
print("hi ")
print("serialConnection()")
print("values: {} , port: {}".format(values,device))
#c_number=getDev... | [
"jsonConfig.getBindings",
"time.sleep"
] | [((496, 509), 'time.sleep', 'time.sleep', (['(3)'], {}), '(3)\n', (506, 509), False, 'import time\n'), ((759, 776), 'time.sleep', 'time.sleep', (['(0.001)'], {}), '(0.001)\n', (769, 776), False, 'import time\n'), ((633, 657), 'jsonConfig.getBindings', 'j.getBindings', (['i', 'values'], {}), '(i, values)\n', (646, 657),... |
# This file is part of Buildbot. Buildbot is free software: you can
# redistribute it and/or modify it under the terms of the GNU General Public
# License as published by the Free Software Foundation, version 2.
#
# This program is distributed in the hope that it will be useful, but WITHOUT
# ANY WARRANTY; without eve... | [
"twisted.internet.defer.returnValue",
"buildbot.process.results.worst_status"
] | [((1829, 1854), 'twisted.internet.defer.returnValue', 'defer.returnValue', (['result'], {}), '(result)\n', (1846, 1854), False, 'from twisted.internet import defer\n'), ((1992, 2014), 'twisted.internet.defer.returnValue', 'defer.returnValue', (['res'], {}), '(res)\n', (2009, 2014), False, 'from twisted.internet import ... |
from datetime import datetime
extensions = []
templates_path = ["_templates"]
source_suffix = ".rst"
master_doc = "index"
project = u"Opale"
year = datetime.now().year
copyright = u"%d <NAME> " % year
exclude_patterns = ["_build"]
html_theme = "opale"
html_sidebars = {
"**": [
"about.html",
"na... | [
"datetime.datetime.now"
] | [((151, 165), 'datetime.datetime.now', 'datetime.now', ([], {}), '()\n', (163, 165), False, 'from datetime import datetime\n')] |
# -*- coding: utf-8 -*-
"""
Created on Mon Aug 10 22:27:03 2020
@author: <NAME>
"""
import math
import tqdm
import torch
import torch.nn as nn
import pandas as pd
import numpy as np
import utils
from net import DCRNNModel
# import sys
# sys.path.append("./xlwang_version")
# from dcrnn_model import DCRNNModel
"""
H... | [
"tqdm.tqdm",
"math.exp",
"net.DCRNNModel",
"math.ceil",
"pandas.read_csv",
"utils.get_adjacency_matrix",
"utils.masked_mape_np",
"torch.cuda.max_memory_allocated",
"numpy.zeros",
"torch.FloatTensor",
"utils.load_dataset",
"utils.masked_mae_loss",
"utils.masked_mae_np",
"torch.cuda.is_avail... | [((1085, 1149), 'pandas.read_csv', 'pd.read_csv', (['sensor_distance'], {'dtype': "{'from': 'str', 'to': 'str'}"}), "(sensor_distance, dtype={'from': 'str', 'to': 'str'})\n", (1096, 1149), True, 'import pandas as pd\n'), ((1202, 1253), 'utils.get_adjacency_matrix', 'utils.get_adjacency_matrix', (['distance_df', 'sensor... |
"""
Task request/response classes for the registration job (discovering, validating and storing metadata for a dataset)
"""
# Copyright 2021 The Funnel Rocket Maintainers
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may ... | [
"enum.auto",
"dataclasses.dataclass"
] | [((1693, 1715), 'dataclasses.dataclass', 'dataclass', ([], {'frozen': '(True)'}), '(frozen=True)\n', (1702, 1715), False, 'from dataclasses import dataclass\n'), ((2130, 2152), 'dataclasses.dataclass', 'dataclass', ([], {'frozen': '(True)'}), '(frozen=True)\n', (2139, 2152), False, 'from dataclasses import dataclass\n'... |
import numpy as np
from rdkit.DataStructs.cDataStructs import ExplicitBitVect, SparseBitVect
from scipy.sparse import issparse, csr_matrix
from collections import defaultdict
from rdkit import DataStructs
from luna.util.exceptions import (BitsValueError, InvalidFingerprintType, IllegalArgumentError, FingerprintCountsE... | [
"scipy.sparse.issparse",
"collections.defaultdict",
"luna.util.exceptions.IllegalArgumentError",
"luna.util.exceptions.InvalidFingerprintType",
"numpy.unique",
"luna.util.exceptions.BitsValueError",
"numpy.intersect1d",
"numpy.union1d",
"numpy.log2",
"numpy.asarray",
"luna.util.exceptions.Finger... | [((390, 409), 'logging.getLogger', 'logging.getLogger', ([], {}), '()\n', (407, 409), False, 'import logging\n'), ((1543, 1577), 'numpy.asarray', 'np.asarray', (['indices'], {'dtype': 'np.long'}), '(indices, dtype=np.long)\n', (1553, 1577), True, 'import numpy as np\n'), ((1835, 1853), 'numpy.unique', 'np.unique', (['i... |
from pages.driver import Driver
from pages.login import LoginPage
from pages.addNewDevice import AddNewDevice
from pages.devicesvc import DeviceService
from pages.appsvc import AppService
from pages.scheduler import Scheduler
from pages.notification import Notification
from pages.config import Config
import time
if __... | [
"pages.login.LoginPage",
"time.sleep"
] | [((445, 456), 'pages.login.LoginPage', 'LoginPage', ([], {}), '()\n', (454, 456), False, 'from pages.login import LoginPage\n'), ((477, 490), 'time.sleep', 'time.sleep', (['(2)'], {}), '(2)\n', (487, 490), False, 'import time\n'), ((910, 923), 'time.sleep', 'time.sleep', (['(2)'], {}), '(2)\n', (920, 923), False, 'impo... |
import torch.optim as optim
from sklearn.metrics import roc_auc_score, f1_score, jaccard_score
from model_plus import createDeepLabv3Plus
import sys
print(sys.version, sys.platform, sys.executable)
from trainer_plus import train_model
import datahandler_plus
import argparse
import os
import torch
import numpy
torch.cu... | [
"trainer_plus.train_model",
"os.makedirs",
"argparse.ArgumentParser",
"datahandler_plus.get_dataloader_single_folder",
"torch.load",
"os.path.exists",
"model_plus.createDeepLabv3Plus",
"torch.nn.CrossEntropyLoss",
"torch.FloatTensor",
"numpy.array",
"torch.cuda.empty_cache",
"datahandler_plus.... | [((312, 336), 'torch.cuda.empty_cache', 'torch.cuda.empty_cache', ([], {}), '()\n', (334, 336), False, 'import torch\n'), ((460, 485), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {}), '()\n', (483, 485), False, 'import argparse\n'), ((3450, 3557), 'trainer_plus.train_model', 'train_model', (['model', 'cr... |
# coding: utf-8
from __future__ import absolute_import, division, print_function, unicode_literals
from typing import TYPE_CHECKING, Tuple
from feishu.exception import LarkInvalidArguments, OpenLarkException
if TYPE_CHECKING:
from feishu.api import OpenLark
# https://open.feishu.cn/document/ukTMukTMukTM/uIzMx... | [
"feishu.exception.LarkInvalidArguments",
"feishu.exception.OpenLarkException"
] | [((6357, 6443), 'feishu.exception.OpenLarkException', 'OpenLarkException', ([], {'msg': '"""[get_chat_id_between_user_bot] empty open_id and user_id"""'}), "(msg=\n '[get_chat_id_between_user_bot] empty open_id and user_id')\n", (6374, 6443), False, 'from feishu.exception import LarkInvalidArguments, OpenLarkExcepti... |
"""
====================================
Linear algebra (:mod:`scipy.linalg`)
====================================
.. currentmodule:: scipy.linalg
Linear algebra functions.
.. seealso::
`numpy.linalg` for more linear algebra functions. Note that
although `scipy.linalg` imports most of them, ident... | [
"numpy.dual.register_func",
"numpy.testing.Tester"
] | [((6396, 6424), 'numpy.dual.register_func', 'register_func', (['"""pinv"""', 'pinv2'], {}), "('pinv', pinv2)\n", (6409, 6424), False, 'from numpy.dual import register_func\n'), ((6523, 6531), 'numpy.testing.Tester', 'Tester', ([], {}), '()\n', (6529, 6531), False, 'from numpy.testing import Tester\n'), ((6546, 6554), '... |
from dependency_injector.providers import Singleton
def singleton_provider(obj):
def clb():
return obj
return Singleton(clb)
| [
"dependency_injector.providers.Singleton"
] | [((129, 143), 'dependency_injector.providers.Singleton', 'Singleton', (['clb'], {}), '(clb)\n', (138, 143), False, 'from dependency_injector.providers import Singleton\n')] |
import math
import itertools
class Solution:
def minimumIncompatibility(self, nums: List[int], k: int) -> int:
n = len(nums)
if k == n:
return 0
dp = [[math.inf] * n for _ in range(1 << n)]
nums.sort()
for i in range(n):
dp[1<<i][i] = 0
for m... | [
"itertools.combinations",
"itertools.permutations"
] | [((478, 513), 'itertools.permutations', 'itertools.permutations', (['n_z_bits', '(2)'], {}), '(n_z_bits, 2)\n', (500, 513), False, 'import itertools\n'), ((636, 671), 'itertools.combinations', 'itertools.combinations', (['n_z_bits', '(2)'], {}), '(n_z_bits, 2)\n', (658, 671), False, 'import itertools\n')] |
import sys
from typing import List
from unittest.mock import patch
import pytest
from poetry_pdf.cli import parse_cli
from poetry_pdf.exceptions import InvalidCommand, InvalidSourcePath
@pytest.mark.parametrize(
"argv",
[
["poetry-pdf", "tests/fixtures/the_raven.txt"],
[
"poetry-p... | [
"poetry_pdf.cli.parse_cli",
"pytest.mark.parametrize",
"pytest.raises",
"unittest.mock.patch.object"
] | [((190, 422), 'pytest.mark.parametrize', 'pytest.mark.parametrize', (['"""argv"""', "[['poetry-pdf', 'tests/fixtures/the_raven.txt'], ['poetry-pdf',\n 'tests/fixtures/the_raven.txt', '--output-dir', '.'], ['poetry-pdf',\n 'tests/fixtures/the_raven.txt', '--author', '<NAME>']]"], {}), "('argv', [['poetry-pdf',\n ... |
import sys
import shutil
import json
import subprocess
from typing import Union
from pathlib import Path
from jinja2 import Template
class UserModel():
"""Handles user-defined model described in python scripts.
"""
def __init__(self):
self.parent = Path(__file__).resolve().parent
self.dst... | [
"jinja2.Template",
"json.dump",
"json.load",
"pathlib.Path",
"shutil.copy",
"sys.exit"
] | [((810, 840), 'shutil.copy', 'shutil.copy', (['src_abs', 'self.dst'], {}), '(src_abs, self.dst)\n', (821, 840), False, 'import shutil\n'), ((6137, 6148), 'jinja2.Template', 'Template', (['s'], {}), '(s)\n', (6145, 6148), False, 'from jinja2 import Template\n'), ((6497, 6510), 'jinja2.Template', 'Template', (['tmp'], {}... |
# Generated by Django 3.2.7 on 2021-10-03 21:30
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
]
ope... | [
"django.db.models.URLField",
"django.db.models.TextField",
"django.db.migrations.swappable_dependency",
"django.db.models.BigAutoField",
"django.db.models.CharField",
"django.db.models.ForeignKey",
"django.db.models.BooleanField",
"django.db.models.DateTimeField"
] | [((247, 304), 'django.db.migrations.swappable_dependency', 'migrations.swappable_dependency', (['settings.AUTH_USER_MODEL'], {}), '(settings.AUTH_USER_MODEL)\n', (278, 304), False, 'from django.db import migrations, models\n'), ((474, 570), 'django.db.models.BigAutoField', 'models.BigAutoField', ([], {'auto_created': '... |
from django.http import HttpResponse
from rest_framework import permissions
from CRUDFilters.views import CRUDFilterModelViewSet
from .models import TestClass
from .serializers import TestClassSerializer
class TestClassViewset(CRUDFilterModelViewSet):
serializer_class = TestClassSerializer
crud_model = Test... | [
"django.http.HttpResponse"
] | [((440, 490), 'django.http.HttpResponse', 'HttpResponse', (['"""Everything\'s fine here"""'], {'status': '(200)'}), '("Everything\'s fine here", status=200)\n', (452, 490), False, 'from django.http import HttpResponse\n'), ((555, 605), 'django.http.HttpResponse', 'HttpResponse', (['"""Everything\'s fine here"""'], {'st... |
import os
from PIL import Image
from models.model import model
import argparse
import numpy as np
import tensorflow as tf
import shutil
def create(args):
if args.pre_trained == 'facenet':
from models.Face_recognition import FR_model
FR = FR_model()
Model = tf.keras.models.load_model(args.s... | [
"os.mkdir",
"tensorflow.keras.models.load_model",
"argparse.ArgumentParser",
"numpy.asarray",
"models.Face_recognition.FR_model",
"PIL.Image.open",
"shutil.move",
"os.listdir"
] | [((373, 389), 'os.listdir', 'os.listdir', (['path'], {}), '(path)\n', (383, 389), False, 'import os\n'), ((1063, 1083), 'os.mkdir', 'os.mkdir', (['"""Face-AHQ"""'], {}), "('Face-AHQ')\n", (1071, 1083), False, 'import os\n'), ((1618, 1643), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {}), '()\n', (1641, 1... |
# -*- coding: utf-8 -*-
"""
The node registry is a place to list the relationships between node types
and their views.
Nodular does *not* provide a global instance of :class:`NodeRegistry`. Since
the registry determines what is available in an app, registries should be
constructed as app-level globals.
"""
from insp... | [
"collections.OrderedDict",
"collections.defaultdict",
"inspect.isclass",
"werkzeug.routing.Map"
] | [((836, 849), 'collections.OrderedDict', 'OrderedDict', ([], {}), '()\n', (847, 849), False, 'from collections import OrderedDict, defaultdict\n'), ((881, 897), 'collections.defaultdict', 'defaultdict', (['set'], {}), '(set)\n', (892, 897), False, 'from collections import OrderedDict, defaultdict\n'), ((923, 940), 'col... |
#!/usr/bin/env python
# SPDX-FileCopyrightText: 2021 iteratec GmbH
#
# SPDX-License-Identifier: Apache-2.0
# -*- coding: utf-8 -*-
import pytest
from unittest.mock import MagicMock, Mock
from unittest import TestCase
from zapclient.configuration import ZapConfiguration
class ZapSpiderHttpTests(TestCase):
@py... | [
"zapclient.configuration.ZapConfiguration"
] | [((398, 490), 'zapclient.configuration.ZapConfiguration', 'ZapConfiguration', (['"""./tests/mocks/context-with-overlay/"""', '"""https://www.secureCodeBox.io/"""'], {}), "('./tests/mocks/context-with-overlay/',\n 'https://www.secureCodeBox.io/')\n", (414, 490), False, 'from zapclient.configuration import ZapConfigur... |
# -*- coding: utf-8 -*-
import sys
import os
UNITY_PATH = "/Applications/Unity/Hub/Editor/2019.4.18f1c1/Unity.app/Contents/MacOS/Unity"
class Unity(object):
# @staticmethod
# def SwitchPlatorm()
# @staticmethod
# def GeneratorWrapCode():
# Unity.ExecuteScript("CSObjectWrapEditor.Generator", "ClearAll")
# Un... | [
"os.system"
] | [((1087, 1140), 'os.system', 'os.system', (["('echo ' + cmd + ' >> ' + logFile + ' 2>&1')"], {}), "('echo ' + cmd + ' >> ' + logFile + ' 2>&1')\n", (1096, 1140), False, 'import os\n'), ((1135, 1178), 'os.system', 'os.system', (["(cmd + ' >> ' + logFile + ' 2>&1')"], {}), "(cmd + ' >> ' + logFile + ' 2>&1')\n", (1144, 1... |
# -*- coding: utf-8 -*-
from __future__ import absolute_import, division, print_function, unicode_literals
import six
import re
import operator
from utool import util_inject
print, rrr, profile = util_inject.inject2(__name__)
def modify_tags(tags_list, direct_map=None, regex_map=None, regex_aug=None,
... | [
"utool.dict_hist",
"utool.doctest_funcs",
"utool.compress",
"utool.ensure_iterable",
"utool.take_column",
"utool.flatten",
"utool.setdiff",
"utool.unique",
"re.match",
"six.text_type",
"utool.filter_Nones",
"utool.combinations",
"utool.odict",
"utool.build_alias_map",
"utool.alias_tags",... | [((196, 225), 'utool.util_inject.inject2', 'util_inject.inject2', (['__name__'], {}), '(__name__)\n', (215, 225), False, 'from utool import util_inject\n'), ((489, 499), 'utool.odict', 'ut.odict', ([], {}), '()\n', (497, 499), True, 'import utool as ut\n'), ((728, 767), 'utool.alias_tags', 'ut.alias_tags', (['new_tags_... |
import mcpi.minecraft as minecraft
from flask import render_template
from flask import Flask
from flask import jsonify
app = Flask(__name__)
@app.route('/')
def pyminemapIndex():
return render_template('index.html')
@app.route('/list')
def pyminemapList():
try:
positionstexte = []
mc = minecra... | [
"mcpi.minecraft.Minecraft.create",
"flask.jsonify",
"flask.Flask",
"flask.render_template"
] | [((125, 140), 'flask.Flask', 'Flask', (['__name__'], {}), '(__name__)\n', (130, 140), False, 'from flask import Flask\n'), ((191, 220), 'flask.render_template', 'render_template', (['"""index.html"""'], {}), "('index.html')\n", (206, 220), False, 'from flask import render_template\n'), ((851, 878), 'flask.render_templa... |
from __future__ import unicode_literals, print_function, division
from collections import Counter
from nltk.tokenize import TweetTokenizer
import cPickle as cp
import io
import numpy as np
PAD_TOKEN = 0
SOS_TOKEN = 1
EOS_TOKEN = 2
VOCAB_SIZE = 10000
class Lang(object):
def __init__(self, name, lowercase=True,... | [
"nltk.tokenize.TweetTokenizer",
"numpy.random.normal",
"io.open",
"collections.Counter",
"numpy.concatenate"
] | [((3179, 3221), 'numpy.random.normal', 'np.random.normal', (['(0)', '(1)', '(1, embedding_dim)'], {}), '(0, 1, (1, embedding_dim))\n', (3195, 3221), True, 'import numpy as np\n'), ((3245, 3287), 'numpy.random.normal', 'np.random.normal', (['(0)', '(1)', '(1, embedding_dim)'], {}), '(0, 1, (1, embedding_dim))\n', (3261,... |
# -*- coding: utf-8 -*-
"""
A program that carries out mini batch k-means clustering on Movielens datatset"""
from __future__ import print_function, division, absolute_import, unicode_literals
from decimal import *
#other stuff we need to import
import csv
import numpy as np
from sklearn.cluster import ... | [
"sklearn.cluster.MiniBatchKMeans",
"numpy.zeros"
] | [((1958, 2003), 'numpy.zeros', 'np.zeros', (['(number_of_users, number_of_movies)'], {}), '((number_of_users, number_of_movies))\n', (1966, 2003), True, 'import numpy as np\n'), ((2991, 3020), 'sklearn.cluster.MiniBatchKMeans', 'MiniBatchKMeans', ([], {'n_clusters': 'K'}), '(n_clusters=K)\n', (3006, 3020), False, 'from... |
from django.db import models
class Sale(models.Model):
created = models.DateTimeField()
def __str__(self):
return f'[{self.id}] {self.created:%Y-%m-%d}'
class SaleWithDrilldown(Sale):
"""
We will use this model in the admin to illustrate the difference
between date hierarchy with and wi... | [
"django.db.models.DateTimeField"
] | [((71, 93), 'django.db.models.DateTimeField', 'models.DateTimeField', ([], {}), '()\n', (91, 93), False, 'from django.db import models\n')] |
import json # note: ujson fails this test due to float equality
import copy
import numpy as np
import pytest
from gym.spaces import Tuple, Box, Discrete, MultiDiscrete, MultiBinary, Dict
@pytest.mark.parametrize(
"space",
[
Discrete(3),
Discrete(5, start=-2),
Box(low=0.0, high=np.in... | [
"gym.spaces.MultiBinary",
"copy.deepcopy",
"gym.spaces.Discrete",
"copy.copy",
"json.dumps",
"gym.spaces.MultiDiscrete",
"numpy.random.default_rng",
"pytest.raises",
"numpy.array",
"gym.spaces.Box",
"gym.spaces.Tuple",
"gym.spaces.Dict"
] | [((2604, 2620), 'copy.copy', 'copy.copy', (['space'], {}), '(space)\n', (2613, 2620), False, 'import copy\n'), ((6518, 6550), 'gym.spaces.Box', 'Box', ([], {'low': '(0)', 'high': '(1)', 'shape': '(3, 3)'}), '(low=0, high=1, shape=(3, 3))\n', (6521, 6550), False, 'from gym.spaces import Tuple, Box, Discrete, MultiDiscre... |
########
# Copyright (c) 2014 GigaSpaces Technologies Ltd. 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... | [
"integration_tests.tests.utils.get_resource",
"integration_tests.tests.utils.do_retries",
"integration_tests.framework.riemann.reset_data_and_restart"
] | [((1029, 1061), 'integration_tests.framework.riemann.reset_data_and_restart', 'riemann.reset_data_and_restart', ([], {}), '()\n', (1059, 1061), False, 'from integration_tests.framework import riemann\n'), ((2621, 2642), 'integration_tests.tests.utils.do_retries', 'do_retries', (['assertion'], {}), '(assertion)\n', (263... |
# -*- coding: utf-8 -*-
# Generated by Django 1.11.21 on 2019-09-02 07:59
from __future__ import unicode_literals
from django.db import migrations
import django.db.models.deletion
from apps.noclook.models import DEFAULT_ROLEGROUP_NAME, DEFAULT_ROLE_KEY, DEFAULT_ROLES
def init_default_roles(Role):
# and then get ... | [
"django.db.migrations.RunPython",
"apps.noclook.models.DEFAULT_ROLES.items"
] | [((393, 414), 'apps.noclook.models.DEFAULT_ROLES.items', 'DEFAULT_ROLES.items', ([], {}), '()\n', (412, 414), False, 'from apps.noclook.models import DEFAULT_ROLEGROUP_NAME, DEFAULT_ROLE_KEY, DEFAULT_ROLES\n'), ((1157, 1206), 'django.db.migrations.RunPython', 'migrations.RunPython', (['forwards_func', 'reverse_func'], ... |
import numpy as np
import tensorflow as tf
from lib.crf import crf_inference
from lib.CC_labeling_8 import CC_lab
def single_generate_seed_step(params):
"""Implemented seeded region growing
Parameters
----------
params : 3-tuple of numpy 4D arrays
(tag) : numpy 4D array (size: B x 1 x 1 x C),... | [
"tensorflow.contrib.layers.xavier_initializer",
"numpy.load",
"tensorflow.reduce_sum",
"numpy.sum",
"numpy.argmax",
"tensorflow.constant_initializer",
"tensorflow.Variable",
"tensorflow.nn.conv2d",
"tensorflow.reduce_max",
"lib.CC_labeling_8.CC_lab",
"tensorflow.get_variable",
"tensorflow.nn.r... | [((3106, 3133), 'numpy.expand_dims', 'np.expand_dims', (['cue'], {'axis': '(0)'}), '(cue, axis=0)\n', (3120, 3133), True, 'import numpy as np\n'), ((951, 983), 'numpy.argmax', 'np.argmax', (['existing_prob'], {'axis': '(2)'}), '(existing_prob, axis=2)\n', (960, 983), True, 'import numpy as np\n'), ((2213, 2232), 'numpy... |
# -*- coding: utf-8 -*-
"""
Created on Tue Feb 19 13:46:46 2019
Description:
Last update:
Version: 1.0
Author: <NAME> (NREL)
"""
import pandas as pd
class LoadConfig(object):
def __init__(self, config_file):
self.config_file = config_file
def str_to_bool(self, s):
if s == 'Tru... | [
"pandas.DataFrame"
] | [((542, 556), 'pandas.DataFrame', 'pd.DataFrame', ([], {}), '()\n', (554, 556), True, 'import pandas as pd\n')] |
import os
import shutil
from pathlib import PosixPath
from tempfile import TemporaryDirectory, mkdtemp
from urllib.error import URLError
import pytest
from jmanager.models.distribution import Architecture, Version, VersionType, Component
from jmanager.utils.fetch import HTTPFetcher
from test.globals import TEST_DISTR... | [
"jmanager.models.distribution.Version",
"tempfile.TemporaryDirectory",
"os.makedirs",
"pytest.raises",
"tempfile.mkdtemp",
"pathlib.PosixPath",
"shutil.rmtree"
] | [((508, 519), 'pathlib.PosixPath', 'PosixPath', ([], {}), '()\n', (517, 519), False, 'from pathlib import PosixPath\n'), ((568, 577), 'tempfile.mkdtemp', 'mkdtemp', ([], {}), '()\n', (575, 577), False, 'from tempfile import TemporaryDirectory, mkdtemp\n'), ((1032, 1079), 'shutil.rmtree', 'shutil.rmtree', (['self.tmp_di... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Sep 30 12:07:19 2018
@author: nn
"""
from collections import OrderedDict
import os
import cv2
from . import tf_metrics
def get_logger(arc_type, logger_params):
if arc_type == "sl":
logger = SlLogger(**logger_params)
elif arc_type == "ae":
... | [
"collections.OrderedDict",
"os.path.isdir",
"os.path.join",
"os.makedirs"
] | [((904, 917), 'collections.OrderedDict', 'OrderedDict', ([], {}), '()\n', (915, 917), False, 'from collections import OrderedDict\n'), ((2007, 2046), 'os.path.join', 'os.path.join', (['self.log_dir', 'self.sample'], {}), '(self.log_dir, self.sample)\n', (2019, 2046), False, 'import os\n'), ((2640, 2679), 'os.path.join'... |
from base64 import b64encode
import pytest
from asgi_webdav.constants import DAVPath, DAVUser
from asgi_webdav.config import update_config_from_obj, get_config
from asgi_webdav.auth import DAVPassword, DAVPasswordType, DAVAuth
from asgi_webdav.request import DAVRequest
USERNAME = "username"
PASSWORD = "password"
HAS... | [
"asgi_webdav.config.get_config",
"asgi_webdav.config.update_config_from_obj",
"asgi_webdav.constants.DAVUser",
"asgi_webdav.request.DAVRequest",
"asgi_webdav.auth.DAVPassword",
"asgi_webdav.constants.DAVPath"
] | [((695, 810), 'asgi_webdav.request.DAVRequest', 'DAVRequest', (["{'method': 'GET', 'headers': {b'authorization': b'placeholder'}, 'path': '/'}", 'fake_call', 'fake_call'], {}), "({'method': 'GET', 'headers': {b'authorization': b'placeholder'},\n 'path': '/'}, fake_call, fake_call)\n", (705, 810), False, 'from asgi_w... |
import os
import ndjson
import json
import time
from options import TestOptions
from framework import SketchModel
from utils import load_data
from writer import Writer
import numpy as np
from evalTool import *
def run_eval(opt=None, model=None, loader=None, dataset='test', write_result=False):
if opt is None:
... | [
"utils.load_data",
"numpy.average",
"ndjson.load",
"options.TestOptions",
"ndjson.dump",
"framework.SketchModel"
] | [((1682, 1702), 'numpy.average', 'np.average', (['lossList'], {}), '(lossList)\n', (1692, 1702), True, 'import numpy as np\n'), ((1718, 1743), 'numpy.average', 'np.average', (['p_metric_list'], {}), '(p_metric_list)\n', (1728, 1743), True, 'import numpy as np\n'), ((1759, 1784), 'numpy.average', 'np.average', (['c_metr... |
import sys
import time
import aiogram.types
from aiogram import types, Dispatcher, Bot
from aiogram.dispatcher import FSMContext
sys.path.append('bot')
from database.sess import get_users_by_link
from database.sess import create_new_user, check_on_off, switch_on_off, check_parse_channels, check_channel, \
add_chann... | [
"sys.path.append",
"database.sess.check_parse_channels",
"python.States.StatesClasses.Adding.first.set",
"database.sess.reemove_channels",
"database.sess.add_channels",
"database.sess.get_users_by_link",
"time.sleep",
"aiogram.Bot",
"database.sess.switch_on_off",
"database.sess.create_new_user",
... | [((129, 151), 'sys.path.append', 'sys.path.append', (['"""bot"""'], {}), "('bot')\n", (144, 151), False, 'import sys\n'), ((461, 478), 'aiogram.Bot', 'Bot', ([], {'token': 'bToken'}), '(token=bToken)\n', (464, 478), False, 'from aiogram import types, Dispatcher, Bot\n'), ((896, 967), 'database.sess.create_new_user', 'c... |
"""
Author: <NAME> (<EMAIL>)
Date: May 07, 2020
"""
from __future__ import print_function
import torch
import torch.nn as nn
import numpy as np
from itertools import combinations
class SupConLoss(nn.Module):
"""Supervised Contrastive Learning: https://arxiv.org/pdf/2004.11362.pdf.
It also supports the unsuper... | [
"numpy.triu",
"torch.eye",
"numpy.isnan",
"torch.arange",
"torch.device",
"numpy.unique",
"numpy.meshgrid",
"torch.diag",
"torch.exp",
"torch.triu",
"torch.unbind",
"torch.matmul",
"torch.log",
"itertools.combinations",
"torch.max",
"torch.sum",
"torch.ones_like",
"torch.eq",
"nu... | [((5136, 5159), 'itertools.combinations', 'combinations', (['nviews', '(2)'], {}), '(nviews, 2)\n', (5148, 5159), False, 'from itertools import combinations\n'), ((2896, 2947), 'torch.max', 'torch.max', (['anchor_dot_contrast'], {'dim': '(1)', 'keepdim': '(True)'}), '(anchor_dot_contrast, dim=1, keepdim=True)\n', (2905... |
# -*- coding: utf-8 -*-
from rete import Has, Filter, Rule
from rete.common import WME, Bind
from rete.network import Network
def test_filter_compare():
net = Network()
c0 = Has('spu:1', 'price', '$x')
f0 = Filter('$x>100')
f1 = Filter('$x<200')
f2 = Filter('$x>200 and $x<400')
f3 = Filter('$x... | [
"rete.Has",
"rete.common.Bind",
"rete.network.Network",
"rete.common.WME",
"rete.Rule",
"rete.Filter"
] | [((165, 174), 'rete.network.Network', 'Network', ([], {}), '()\n', (172, 174), False, 'from rete.network import Network\n'), ((184, 211), 'rete.Has', 'Has', (['"""spu:1"""', '"""price"""', '"""$x"""'], {}), "('spu:1', 'price', '$x')\n", (187, 211), False, 'from rete import Has, Filter, Rule\n'), ((221, 237), 'rete.Filt... |
from __future__ import print_function
import torch
import numpy as np
from PIL import Image
import os
import time
# Converts a Tensor into an image array (numpy)
# |imtype|: the desired type of the converted numpy array
def tensor2im(input_image, imtype=np.uint8):
if isinstance(input_image, torch.Tensor):
... | [
"os.makedirs",
"numpy.median",
"numpy.std",
"os.path.exists",
"numpy.transpose",
"numpy.clip",
"time.time",
"numpy.min",
"numpy.max",
"numpy.mean",
"numpy.tile",
"PIL.Image.fromarray",
"torch.abs"
] | [((772, 804), 'numpy.clip', 'np.clip', (['image_numpy', '(0.0)', '(255.0)'], {}), '(image_numpy, 0.0, 255.0)\n', (779, 804), True, 'import numpy as np\n'), ((1206, 1234), 'PIL.Image.fromarray', 'Image.fromarray', (['image_numpy'], {}), '(image_numpy)\n', (1221, 1234), False, 'from PIL import Image\n'), ((647, 678), 'nu... |
import subprocess
import shutil
import os
import time
from .interface import IsolateInterface
class IsolateSimple(IsolateInterface):
def isolate(self, files, command, parameters, envvariables, directories, allowmultiprocess, stdinfile, stdoutfile):
if os.path.isdir("/tmp/gradertools/isolation/"):
... | [
"os.makedirs",
"os.path.basename",
"os.path.isdir",
"time.perf_counter",
"shutil.rmtree"
] | [((267, 311), 'os.path.isdir', 'os.path.isdir', (['"""/tmp/gradertools/isolation/"""'], {}), "('/tmp/gradertools/isolation/')\n", (280, 311), False, 'import os\n'), ((378, 420), 'os.makedirs', 'os.makedirs', (['"""/tmp/gradertools/isolation/"""'], {}), "('/tmp/gradertools/isolation/')\n", (389, 420), False, 'import os\... |
import os, sys
sys.path.append( os.path.join(os.path.dirname(os.path.abspath(__file__)),'tts_websocketserver','src') )
from tts_websocketserver.tts_server import run
if __name__ == '__main__':
run() | [
"os.path.abspath",
"tts_websocketserver.tts_server.run"
] | [((203, 208), 'tts_websocketserver.tts_server.run', 'run', ([], {}), '()\n', (206, 208), False, 'from tts_websocketserver.tts_server import run\n'), ((62, 87), 'os.path.abspath', 'os.path.abspath', (['__file__'], {}), '(__file__)\n', (77, 87), False, 'import os, sys\n')] |
import re
import pytest
import rita
def load_rules(rules_path):
with open(rules_path, "r") as f:
return f.read()
def spacy_engine(rules, **kwargs):
spacy = pytest.importorskip("spacy", minversion="2.1")
patterns = rita.compile_string(rules, **kwargs)
nlp = spacy.load("en")
ruler = spacy... | [
"pytest.importorskip",
"rita.engine.translate_rust.load_lib",
"pytest.skip",
"rita.compile_string"
] | [((177, 223), 'pytest.importorskip', 'pytest.importorskip', (['"""spacy"""'], {'minversion': '"""2.1"""'}), "('spacy', minversion='2.1')\n", (196, 223), False, 'import pytest\n'), ((239, 275), 'rita.compile_string', 'rita.compile_string', (['rules'], {}), '(rules, **kwargs)\n', (258, 275), False, 'import rita\n'), ((62... |
from dataclasses import dataclass
from sailenv import Vector3
from sailenv.dynamics import Dynamic
@dataclass
class UniformMovementRandomBounce(Dynamic):
start_direction: Vector3 = Vector3(0, 0, 1)
speed: float = 5
angular_speed: float = 2
seed: int = 42
@staticmethod
def get_type():
... | [
"sailenv.Vector3"
] | [((188, 204), 'sailenv.Vector3', 'Vector3', (['(0)', '(0)', '(1)'], {}), '(0, 0, 1)\n', (195, 204), False, 'from sailenv import Vector3\n')] |
# -*- coding: utf-8 -*-
"""Core download functions."""
# Imports ---------------------------------------------------------------------
import datetime
import json
import numpy as np
import pandas as pd
import requests
from . import constants
from . import errors
from . import settings
# Functions -----------------... | [
"pandas.DataFrame",
"requests.post",
"datetime.datetime.strptime"
] | [((1134, 1181), 'requests.post', 'requests.post', (['url'], {'headers': 'headers', 'data': 'query'}), '(url, headers=headers, data=query)\n', (1147, 1181), False, 'import requests\n'), ((3046, 3086), 'pandas.DataFrame', 'pd.DataFrame', ([], {'data': 'rows', 'columns': 'headers'}), '(data=rows, columns=headers)\n', (305... |
# -*- coding: utf-8 -*-
"""
Created on Mon Jan 14 09:10:29 2021
Author: <NAME>
Functions for implementing the edge detection scheme first proposed by Zhang and Bao [1].
Modified for use with pywt's SWT2 transform and employs double thresholding similar to canny to improve noise resilience and revovery of wea... | [
"scipy.ndimage.generate_binary_structure",
"numpy.abs",
"numpy.sum",
"numpy.empty",
"numpy.ones",
"numpy.clip",
"pywt.swt2",
"numpy.arange",
"cv2.imshow",
"numpy.prod",
"numpy.max",
"cv2.destroyAllWindows",
"numpy.roll",
"cv2.waitKey",
"numpy.hypot",
"pywt.Wavelet",
"scipy.ndimage.bi... | [((2283, 2388), 'pywt.swt2', 'swt2', (['image'], {'wavelet': 'wavelet', 'level': 'max_level', 'start_level': 'start_level', 'norm': '(False)', 'trim_approx': '(True)'}), '(image, wavelet=wavelet, level=max_level, start_level=start_level, norm\n =False, trim_approx=True)\n', (2287, 2388), False, 'from pywt import swt... |
from flask import (
Blueprint, flash, g, redirect, render_template, request, url_for
)
from werkzeug.exceptions import abort
from flask_login import login_required, current_user
from flaskr.models import Post, db, PostComment, User
from flaskr import csrf
blog = Blueprint('blog', __name__)
@blog.route('/')
def i... | [
"flaskr.models.Post.query.order_by",
"flask.flash",
"flaskr.models.db.session.commit",
"flask.Blueprint",
"flask.redirect",
"flaskr.models.Post",
"flask_login.current_user.like_post",
"flaskr.models.PostComment",
"flaskr.models.Post.query.get",
"flask.url_for",
"flask_login.current_user.unlike_p... | [((269, 296), 'flask.Blueprint', 'Blueprint', (['"""blog"""', '__name__'], {}), "('blog', __name__)\n", (278, 296), False, 'from flask import Blueprint, flash, g, redirect, render_template, request, url_for\n'), ((391, 463), 'flask.render_template', 'render_template', (['"""blog/index.html"""'], {'posts': 'posts', 'get... |
from pyvmodule.develope import *
from pyvmodule.tools.modules.sram.dual import SRamR,SRamW
from pyvmodule.tools.modules.fifo import Fifo
from .common import AxiComponent,update_data_burst_addr,compute_address
class Axi2RamR(SRamR):
class FifoAR(Fifo):
def update_data_araddr(self,field):
return u... | [
"pyvmodule.tools.modules.sram.dual.SRamR.__init__",
"pyvmodule.tools.modules.sram.dual.SRamW.__init__",
"pyvmodule.tools.modules.fifo.Fifo"
] | [((420, 495), 'pyvmodule.tools.modules.sram.dual.SRamR.__init__', 'SRamR.__init__', (['self'], {'awidth': 'axi.awidth', 'bwidth': 'axi.bwidth', 'io': 'io'}), '(self, awidth=axi.awidth, bwidth=axi.bwidth, io=io, **kwargs)\n', (434, 495), False, 'from pyvmodule.tools.modules.sram.dual import SRamR, SRamW\n'), ((1970, 204... |
from typing import Dict, Iterable, List, Optional, Union
import attr
from attr.validators import instance_of
from ics.component import Component
from ics.event import Event
from ics.grammar.parse import Container, calendar_string_to_containers
from ics.parsers.icalendar_parser import CalendarParser
from ics.serialize... | [
"attr.validators.instance_of",
"ics.grammar.parse.calendar_string_to_containers",
"attr.ib",
"ics.timeline.Timeline"
] | [((703, 724), 'attr.ib', 'attr.ib', ([], {'default': 'None'}), '(default=None)\n', (710, 724), False, 'import attr\n'), ((753, 774), 'attr.ib', 'attr.ib', ([], {'default': 'None'}), '(default=None)\n', (760, 774), False, 'import attr\n'), ((819, 840), 'attr.ib', 'attr.ib', ([], {'factory': 'dict'}), '(factory=dict)\n',... |
from unittest import TestCase
from freezegun import freeze_time
from secret.utils import create_secret
class Utils(TestCase):
@freeze_time('2019-03-12 12:00:00')
def test_create_secret_key(self):
secret = create_secret()
self.assertEqual(secret, 'd3a4646728a9de9a74d8fc4c41966a42')
| [
"secret.utils.create_secret",
"freezegun.freeze_time"
] | [((135, 169), 'freezegun.freeze_time', 'freeze_time', (['"""2019-03-12 12:00:00"""'], {}), "('2019-03-12 12:00:00')\n", (146, 169), False, 'from freezegun import freeze_time\n'), ((225, 240), 'secret.utils.create_secret', 'create_secret', ([], {}), '()\n', (238, 240), False, 'from secret.utils import create_secret\n')] |
import unittest
from typing import List
import cadquery as cq
from cq_cam.utils import utils
class ProjectFaceTest(unittest.TestCase):
def setUp(self):
pass
def test_face_with_hole(self):
# This should create a projected face that is 2x4 (XY)
box = (
cq.Workplane('XZ')
... | [
"cadquery.Workplane",
"cq_cam.utils.utils.project_face",
"cadquery.Vector"
] | [((968, 1006), 'cq_cam.utils.utils.project_face', 'utils.project_face', (['face_wp.objects[0]'], {}), '(face_wp.objects[0])\n', (986, 1006), False, 'from cq_cam.utils import utils\n'), ((737, 762), 'cadquery.Vector', 'cq.Vector', (['(0.0)', '(-1.0)', '(0.0)'], {}), '(0.0, -1.0, 0.0)\n', (746, 762), True, 'import cadque... |
# -*- coding: utf-8 -*-
"""Test gui."""
#------------------------------------------------------------------------------
# Imports
#------------------------------------------------------------------------------
from pytest import raises
from ..qt import Qt, QApplication, QWidget, QMessageBox
from ..gui import (GUI, ... | [
"phy.utils._color._random_color",
"matplotlib.pyplot.Figure",
"pytest.raises",
"phy.utils.Bunch",
"vispy.app.Canvas"
] | [((812, 824), 'vispy.app.Canvas', 'app.Canvas', ([], {}), '()\n', (822, 824), False, 'from vispy import app\n'), ((839, 854), 'phy.utils._color._random_color', '_random_color', ([], {}), '()\n', (852, 854), False, 'from phy.utils._color import _random_color\n'), ((4447, 4468), 'phy.utils.Bunch', 'Bunch', ([], {'name': ... |
import os
import sys
from collections import OrderedDict
from absl import logging
import torch
import torch.nn.functional as F
import torch.optim as optim
import torchvision.transforms.functional as TF
import pytorch_lightning as pl
import e2cnn.gspaces
import e2cnn.nn
from .base import VariationalAutoEncoderModule
fro... | [
"torch.ones_like",
"torch.ones",
"torch.nn.Unflatten",
"torch.zeros_like",
"absl.logging.debug",
"torch.nn.functional.mse_loss",
"torch.zeros",
"torch.exp",
"torch.chunk",
"elm.nn.GConvTransposeNN",
"elm.nn.MLP",
"elm.nn.GConvNN",
"torch.nn.Flatten"
] | [((1296, 1353), 'absl.logging.debug', 'logging.debug', (['"""-------- GConv VAE ---------"""'], {}), "('-------- GConv VAE ---------')\n", (1309, 1353), False, 'from absl import logging\n'), ((1358, 1413), 'absl.logging.debug', 'logging.debug', (['"""-------- Trainable Variables ---------"""'], ... |
from ncbi.ncbi_taxonomy_parser import TaxonomyParser, Taxonomy
from common.database import *
from common.utils import get_data_dir
import os
# default strain for their species for organism searching
LMDB_SPECIES_MAPPING_STRAIN = ['367830','511145', '272563', '208964', '559292']
DATA_SOURCE = 'NCBI Taxonomy'
def write... | [
"ncbi.ncbi_taxonomy_parser.TaxonomyParser",
"os.path.join",
"common.utils.get_data_dir"
] | [((1163, 1187), 'ncbi.ncbi_taxonomy_parser.TaxonomyParser', 'TaxonomyParser', (['base_dir'], {}), '(base_dir)\n', (1177, 1187), False, 'from ncbi.ncbi_taxonomy_parser import TaxonomyParser, Taxonomy\n'), ((1235, 1290), 'os.path.join', 'os.path.join', (['parser.output_dir', '"""species_for_LMDB.tsv"""'], {}), "(parser.o... |
# -*- coding: utf-8 -*-
# @Time : 2020/11/15 13:49
# @Author : <NAME>
# @FileName: parse_uniprot_header.py
# @Usage:
# @Note:
# @E-mail: <EMAIL>
import pandas as pd
import re
class UniprotParse:
def __init__(self, _input_fasta):
self.input = _input_fasta
self.output = None
def parse(self):
... | [
"pandas.DataFrame",
"argparse.ArgumentParser",
"pandas.merge",
"re.match",
"pandas.read_table"
] | [((1221, 1362), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {'description': '"""This is the script to get Uniprot fasta header informationand use it intrepret BLAST results"""'}), "(description=\n 'This is the script to get Uniprot fasta header informationand use it intrepret BLAST results'\n )\n",... |
"""add site airtable
Revision ID: da6f10c8ebf4
Revises: 9<PASSWORD>e<PASSWORD>
Create Date: 2019-11-29 07:48:18.074193
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "da6f10c8ebf4"
down_revision = "aaae4ae18288"
branch_labels = None
depends_on = None
def upg... | [
"sqlalchemy.String",
"alembic.op.drop_column",
"sqlalchemy.Column"
] | [((697, 734), 'alembic.op.drop_column', 'op.drop_column', (['"""Site"""', '"""airtable_id"""'], {}), "('Site', 'airtable_id')\n", (711, 734), False, 'from alembic import op\n'), ((775, 807), 'sqlalchemy.Column', 'sa.Column', (['"""site_id"""', 'sa.Integer'], {}), "('site_id', sa.Integer)\n", (784, 807), True, 'import s... |
import pytest
import numpy as np
import xarray as xr
import dask.array as da
from xrspatial import curvature
from xrspatial.utils import doesnt_have_cuda
from xrspatial.tests.general_checks import general_output_checks
elevation = np.asarray([
[np.nan, np.nan, np.nan, np.nan, np.nan, np.nan],
... | [
"xrspatial.utils.doesnt_have_cuda",
"cupy.asarray",
"numpy.asarray",
"xrspatial.tests.general_checks.general_output_checks",
"numpy.array",
"xarray.DataArray",
"dask.array.from_array",
"xrspatial.curvature"
] | [((248, 756), 'numpy.asarray', 'np.asarray', (['[[np.nan, np.nan, np.nan, np.nan, np.nan, np.nan], [1584.8767, 1584.8767, \n 1585.0546, 1585.2324, 1585.2324, 1585.2324], [1585.0546, 1585.0546, \n 1585.2324, 1585.588, 1585.588, 1585.588], [1585.2324, 1585.4102, \n 1585.588, 1585.588, 1585.588, 1585.588], [1585.... |
# Copyright 2016 Recorded Future, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in... | [
"hmac.new",
"email.Utils.formatdate"
] | [((2402, 2426), 'email.Utils.formatdate', 'email.Utils.formatdate', ([], {}), '()\n', (2424, 2426), False, 'import email\n'), ((2802, 2851), 'hmac.new', 'hmac.new', (['self.userkey', 'hash_text', 'hashlib.sha256'], {}), '(self.userkey, hash_text, hashlib.sha256)\n', (2810, 2851), False, 'import hmac\n')] |
#!/usr/bin/env python3
"""
This script will run all jupyter notebooks in order to test for errors.
"""
import sys
import os
import nbformat
from nbconvert.preprocessors import ExecutePreprocessor
if os.path.dirname(sys.argv[0]) != '':
os.chdir(os.path.dirname(sys.argv[0]))
notebooks = ('grids-and-coefficients.ipy... | [
"nbformat.read",
"nbconvert.preprocessors.ExecutePreprocessor",
"os.path.dirname"
] | [((200, 228), 'os.path.dirname', 'os.path.dirname', (['sys.argv[0]'], {}), '(sys.argv[0])\n', (215, 228), False, 'import os\n'), ((249, 277), 'os.path.dirname', 'os.path.dirname', (['sys.argv[0]'], {}), '(sys.argv[0])\n', (264, 277), False, 'import os\n'), ((991, 1021), 'nbformat.read', 'nbformat.read', (['f'], {'as_ve... |
import unittest
import sys
sys.path.append('/pEigen/src/peigen')
import libpeigen as peigen
class DenseFactorizationTest(unittest.TestCase):
def setUp(self):
self.rows = 1000
self.cols = 1000
self.dense_matrix = peigen.denseMatrixDouble(self.rows, self.cols)
self.dense_matr... | [
"sys.path.append",
"unittest.main",
"libpeigen.denseDecomposition",
"libpeigen.denseMatrixDouble"
] | [((27, 64), 'sys.path.append', 'sys.path.append', (['"""/pEigen/src/peigen"""'], {}), "('/pEigen/src/peigen')\n", (42, 64), False, 'import sys\n'), ((1253, 1268), 'unittest.main', 'unittest.main', ([], {}), '()\n', (1266, 1268), False, 'import unittest\n'), ((250, 296), 'libpeigen.denseMatrixDouble', 'peigen.denseMatri... |
from typing import Optional
from prompt_toolkit import PromptSession
from prompt_toolkit import print_formatted_text as print_
from efb.validator import YesNoValidator
SESSION = PromptSession()
def make_decision(question: str, default: Optional[bool] = None) -> bool:
default_string = f'(default {"y" if default... | [
"efb.validator.YesNoValidator",
"prompt_toolkit.print_formatted_text",
"prompt_toolkit.PromptSession"
] | [((181, 196), 'prompt_toolkit.PromptSession', 'PromptSession', ([], {}), '()\n', (194, 196), False, 'from prompt_toolkit import PromptSession\n'), ((664, 725), 'prompt_toolkit.print_formatted_text', 'print_', (['f"""Please state your decision as y or n (not {answer}"""'], {}), "(f'Please state your decision as y or n (... |