seq_id string | text string | repo_name string | sub_path string | file_name string | file_ext string | file_size_in_byte int64 | program_lang string | lang string | doc_type string | stars int64 | dataset string | pt string | api list |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
73243352745 | import streamlit as st
import pytube as pt
import os
import subprocess
import re
from utils import logtime, load_ffmpeg
import whisper
from langchain.document_loaders import YoutubeLoader
from langchain.text_splitter import RecursiveCharacterTextSplitter
URL = 'URL'
TEXT = 'TEXT'
WHISPER = 'WHISPER'
PROCESSING = 'PROC... | olanigan/Youtube_Assistant | app.py | app.py | py | 4,825 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "streamlit.title",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "streamlit.session_state",
"line_number": 23,
"usage_type": "attribute"
},
{
"api_name": "streamlit.session_state",
"line_number": 24,
"usage_type": "attribute"
},
{
"api_nam... |
8714183178 | """
meclas.py
Package for running various laser utilities in MEC
Apologies on behalf of: Eric Cunningham (and others)
To load: use import meclas or use IPython's %run magic function
Class list and brief description:
LPL -- routines for LPL pulse shaping (with some aux functions), data acquisition, e... | efcunn/mecps | meclas.py | meclas.py | py | 349,079 | python | en | code | 2 | github-code | 36 | [
{
"api_name": "numpy.array",
"line_number": 232,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 263,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 292,
"usage_type": "call"
},
{
"api_name": "numpy.cumsum",
"line_numbe... |
27490420908 | import datetime
from FileBlackHolePy import FileBlackHole, initLib, destroyLib
from MigurdiaPy import Migurdia
from json import dumps, loads
from colors import log, bcolors
from PIL import Image
from credentials import __USERNAME__, __PASSWORD__, __TOKEN__
from os.path i... | iLikeTrioxin/PTMU | pixivToMigurdiaUploader.py | pixivToMigurdiaUploader.py | py | 6,744 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "datetime.datetime.now",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "PIL.Image.open",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "PIL.Image... |
21619772911 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import unittest
import apache_beam as beam
from apache_beam.runners.direct import direct_runner
from apache_beam.runners.interactive import cache_manager as cache
from apache_beam.runners.interactive import pi... | a0x8o/kafka | sdks/python/apache_beam/runners/interactive/pipeline_analyzer_test.py | pipeline_analyzer_test.py | py | 10,712 | python | en | code | 59 | github-code | 36 | [
{
"api_name": "apache_beam.pipeline.Pipeline.from_runner_api",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "apache_beam.pipeline",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "unittest.TestCase",
"line_number": 22,
"usage_type": "attribute"
... |
27898714417 | from datetime import datetime
def foo(n):
n = int(n)
global start_time
start_time = datetime.now()
list = []
i = 0
while len(list) < n:
flag = True
if i == 0 or i == 1:
i += 1
continue
for j in range(i+1):
if j == 0 or j == 1 or j == ... | stgolovin/js_hw | lesson2/task1.py | task1.py | py | 556 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "datetime.datetime.now",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "datetime.datetime.now",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "datetime.... |
8478439649 | #Python imports
import json
from uuid import UUID
from datetime import date
from datetime import datetime
from typing import Optional, List
#Pydantic imports
from pydantic import Field as FD
from pydantic import BaseModel as BMW
from pydantic import EmailStr
#FastAPI imports
from fastapi import FastAPI... | davidcordellatt/Twitter-Api-Fastapi-practice- | main.py | main.py | py | 13,686 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "fastapi.FastAPI",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "pydantic.BaseModel",
"line_number": 22,
"usage_type": "name"
},
{
"api_name": "uuid.UUID",
"line_number": 24,
"usage_type": "name"
},
{
"api_name": "pydantic.Field",
"li... |
16759793113 | import datetime
from ..command_system import Command
from ...models import Client, Schedule, Teacher, Subject
from ...utils import awesome_date
def next_lesson(domain):
client = Client.query.filter(Client.social_network == 'https://vk.com/'+ domain['domain']).first()
schedule = Schedule.query.filter((Schedule.c... | edukato/learning | app/home/commands/next_lesson.py | next_lesson.py | py | 1,707 | python | ru | code | 0 | github-code | 36 | [
{
"api_name": "models.Client.query.filter",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "models.Client.query",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "models.Client",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "models... |
6519049093 | from tkinter import*
import tkinter as tk
import cv2
import numpy as np
import webbrowser
#GRAY ONLY
def obj():
thres = 0.45
nms_threshold = 0.2
cap = cv2.VideoCapture(0)
className = []
classFile = 'coco.names'
with open(classFile, 'rt') as f:
className = f.read().rstrip('\n').split(... | jahin44/Python | pythonopencv/pro_gui.py | pro_gui.py | py | 6,916 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "cv2.VideoCapture",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "cv2.dnn_DetectionModel",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "cv2.dnn.NMSBoxes"... |
23306080113 | import streamlit as st
import plotting
def stats_view(dfmedicine, dfuniques, visualization_mode):
st.markdown("## Conteos generales del hospital respecto a los pacientes ingresados por trauma")
metric_values = zip(dfuniques.iloc[:, 0].values, dfuniques.iloc[:, 1].values)
metric_columns = st.colum... | SimonPGM/ds4adashboard | Dashboard/generalstatsvis.py | generalstatsvis.py | py | 937 | python | es | code | 0 | github-code | 36 | [
{
"api_name": "streamlit.markdown",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "streamlit.columns",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "plotting.group_comparisons_bar",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "str... |
4585824107 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Jun 30 20:16:19 2020
@author: Antonio Hickey
"""
#-------------------------------------------------------------------
# Importing Modules
from bs4 import BeautifulSoup as soup
from urllib.request import urlopen as uReq
import pandas as pd
import csv
#--... | antonio-hickey/Economics | Yeild Curve/Data Collection/Web_Crawler_Bot.py | Web_Crawler_Bot.py | py | 1,268 | python | en | code | 2 | github-code | 36 | [
{
"api_name": "urllib.request.urlopen",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "csv.writer",
"line_number": 42,
"usage_type": "call"
}
] |
7927334038 | from PyQt5.QtWidgets import (QWidget, QCalendarWidget,QLabel, QApplication, QVBoxLayout,QPushButton)
from PyQt5.QtCore import QDate
import sys
global ap
class Example(QWidget):
def __init__(self):
super().__init__()
self.initUI()
def initUI(self):
vbox = QVBoxLayout(self)
... | fernandezjared1/Vodafone-Idea---PS1 | cal.py | cal.py | py | 1,361 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "PyQt5.QtWidgets.QWidget",
"line_number": 5,
"usage_type": "name"
},
{
"api_name": "PyQt5.QtWidgets.QVBoxLayout",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "PyQt5.QtWidgets.QCalendarWidget",
"line_number": 12,
"usage_type": "call"
},
{
... |
27052806329 | from typing import List
class Solution:
def _fizzBuzz(self, number):
if number % 15 == 0:
return "FizzBuzz"
elif number % 5 == 0:
return "Buzz"
elif number % 3 == 0:
return "Fizz"
else:
return str(number)
def fizzBuzz(self, n: in... | ikedaosushi/leetcode | problems/python/fizzBuzz.py | fizzBuzz.py | py | 397 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "typing.List",
"line_number": 15,
"usage_type": "name"
}
] |
27878022936 | # First things, first. Import the wxPython package.
from concurrent.futures import thread
from tracemalloc import start
from turtle import pos
from numpy import size, true_divide
import wx
from wx.adv import *
from Utilities.media_utils import batchDownload, download, spotifyToSearches, ytFromLink
import misc
from spot... | missing-atabey/PyraTunes | main.py | main.py | py | 3,400 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "ctypes.windll.shcore.SetProcessDpiAwareness",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "ctypes.windll",
"line_number": 19,
"usage_type": "attribute"
},
{
"api_name": "wx.App",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": ... |
21600216675 | # -*- coding: utf-8 -*-
"""
ReferIt, UNC, UNC+ and GRef referring image segmentation PyTorch dataset.
Define and group batches of images, segmentations and queries.
Based on:
https://github.com/chenxi116/TF-phrasecut-public/blob/master/build_batches.py
"""
import os
import re
# import cv2
import sys
import json
impo... | djiajunustc/TransVG | datasets/data_loader.py | data_loader.py | py | 9,900 | python | en | code | 134 | github-code | 36 | [
{
"api_name": "sys.path.append",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 21,
"usage_type": "attribute"
},
{
"api_name": "re.match",
"line_number": 38,
"usage_type": "call"
},
{
"api_name": "torch.utils.data.Dataset",
... |
42843762688 | import pytest
import time
import json
import logging
from error_code.error_status import SignatureStatus
from automation_framework.utilities.workflow import submit_request
from automation_framework.work_order_get_result.work_order_get_result_params \
import WorkOrderGetResult
import avalon_client_sdk.worker.worker... | manojsalunke85/avalon0.6_automaiton | tests/validation_suite/automation_framework/work_order_get_result/work_order_get_result_utility.py | work_order_get_result_utility.py | py | 2,938 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "logging.getLogger",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "automation_framework.work_order_get_result.work_order_get_result_params.WorkOrderGetResult",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_number": 35,
... |
15827613862 | from __future__ import unicode_literals
from __future__ import print_function
from __future__ import division
from __future__ import absolute_import
from future import standard_library
standard_library.install_aliases()
from builtins import *
import logging
import pymongo
import emission.storage.timeseries.timequery a... | e-mission/e-mission-server | emission/storage/decorations/analysis_timeseries_queries.py | analysis_timeseries_queries.py | py | 4,240 | python | en | code | 22 | github-code | 36 | [
{
"api_name": "future.standard_library.install_aliases",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "future.standard_library",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "emission.storage.timeseries.abstract_timeseries.TimeSeries.get_aggregate_time_serie... |
13460739357 | import torch, torchvision
import os
class CNN(torch.nn.Module):
def __init__(self, network_type, dataset_name):
super(CNN, self).__init__()
self.network_type = network_type
if dataset_name == 'dogscats':
classes = 2
elif dataset_name == 'imagenet':
class... | burklight/Adversarial-Attacks-Pytorch | src/networks.py | networks.py | py | 943 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "torch.nn",
"line_number": 4,
"usage_type": "attribute"
},
{
"api_name": "torchvision.models.resnet18",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "torchvision.models",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "torc... |
5450602551 | from enum import Enum
import numpy as np
import pandas as pd
from dataclasses import dataclass
from copy import deepcopy
from typing import List, Union
class Direction(Enum):
UP = 'U'
DOWN = 'D'
LEFT = 'L'
RIGHT = 'R'
@dataclass
class Motion:
direction: Union[Direction, str]
steps: int
... | wbonna352/adventofcode2022 | day_09/main.py | main.py | py | 3,827 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "enum.Enum",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "typing.Union",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "dataclasses.dataclass",
"line_number": 16,
"usage_type": "name"
},
{
"api_name": "dataclasses.dataclass",
... |
41636716649 | import argparse
def create_parser():
parser = argparse.ArgumentParser(description='HR invetory software')
parser.add_argument('path', help='Path to file to be exported')
parser.add_argument('--export', action='store_true', help='Export current settings to json file')
return parser
def main():
from hr import use... | hamakohako/hr_inventory_test | src/hr/cli.py | cli.py | py | 510 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "hr.inventory.export_users",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "hr.inventory",
"line_number": 16,
"usage_type": "name"
},
{
"api_name": "hr.inve... |
9588027057 | """
A Jarvis plugin for listening music according
to your mood through Spotify's Web Player!
Jarvis asks for your mood and based on your choice it
opens a specific playlist of Spotify that fits
your mood.
"""
import webbrowser
from plugin import plugin
from plugin import require
from colorama import Fore
@require(n... | sukeesh/Jarvis | jarviscli/plugins/mood_music.py | mood_music.py | py | 3,509 | python | en | code | 2,765 | github-code | 36 | [
{
"api_name": "colorama.Fore.LIGHTCYAN_EX",
"line_number": 36,
"usage_type": "attribute"
},
{
"api_name": "colorama.Fore",
"line_number": 36,
"usage_type": "name"
},
{
"api_name": "colorama.Fore.CYAN",
"line_number": 38,
"usage_type": "attribute"
},
{
"api_name": ... |
1576881503 | from setuptools import setup, find_packages
with open('readme.md', encoding='utf-8') as f:
long_description = f.read()
setup(
packages = find_packages(),
name = 'pbat',
version = '0.0.16',
author = "Stanislav Doronin",
author_email = "mugisbrows@gmail.com",
url = 'https://github.com/mugise... | mugiseyebrows/pbat | setup.py | setup.py | py | 705 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "setuptools.setup",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "setuptools.find_packages",
"line_number": 7,
"usage_type": "call"
}
] |
39924563926 | from django.db import models
from django.utils import timezone
from . import Season
class SeasonPlayerManager(models.Manager):
def update_active(self, player, elo, wins, losses):
"""Update or create the season player instance for the active season."""
active_season = Season.objects.get_active()
... | dannymilsom/poolbot-server | src/core/models/season_player.py | season_player.py | py | 1,847 | python | en | code | 4 | github-code | 36 | [
{
"api_name": "django.db.models.Manager",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "django.db.models",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "django.db.models.Model",
"line_number": 32,
"usage_type": "attribute"
},
{
"api_name... |
4635120984 | #coding=utf-8
from confluent_kafka import Producer
import MySQLdb
import json
import time
import random
p = Producer({"bootstrap.servers": "118.24.53.99:9092"})
db = MySQLdb.connect("localhost", "root", "123456", "test_kafka", charset='utf8' )
cursor = db.cursor()
sql = "SELECT msg_body FROM order_kafka_msg;"
def ... | liu-xiaoran/demo | java/kafka/pd2.py | pd2.py | py | 1,018 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "confluent_kafka.Producer",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "MySQLdb.connect",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "json.dumps",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "json.loads",
"... |
5318351393 | import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import scipy
from scipy.misc import derivative
def fn_plot1d(fn, x_min, x_max, filename):
num_values = 1000
x = np.linspace(x_min, x_max, num_values)
fnv = np.vectorize(fn)
y = fnv(x)
Xlabel = "X axis"
Yl... | CS251-Fall-2020/outlab4-190050013-190070020 | task4/task4.py | task4.py | py | 2,230 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "numpy.linspace",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "numpy.vectorize",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.plot",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplo... |
16551248169 | import torch
import torch.nn as nn
class NegativeLabelLoss(nn.Module):
"""
https://www.desmos.com/calculator/9oaqcjayrw
"""
def __init__(self, ignore_index=-100, reduction='mean',alpha=1.0,beta=0.8):
super(NegativeLabelLoss, self).__init__()
self.softmax = nn.Softmax(dim=1)
self... | p208p2002/qgg-utils | qgg_utils/__init__.py | __init__.py | py | 897 | python | en | code | 2 | github-code | 36 | [
{
"api_name": "torch.nn.Module",
"line_number": 4,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 4,
"usage_type": "name"
},
{
"api_name": "torch.nn.Softmax",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line_num... |
19262690162 | from __future__ import print_function
import json
import logging
import os
import datetime
import calendar
import sys
from collections import OrderedDict
from pokemongo_bot.base_dir import _base_dir
from pokemongo_bot.services.item_recycle_worker import ItemRecycler
'''
Helper class for updating/retrieving Inventory ... | PokemonGoF/PokemonGo-Bot | pokemongo_bot/inventory.py | inventory.py | py | 53,475 | python | en | code | 3,815 | github-code | 36 | [
{
"api_name": "json.load",
"line_number": 43,
"usage_type": "call"
},
{
"api_name": "pokemongo_bot.services.item_recycle_worker.ItemRecycler",
"line_number": 227,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 254,
"usage_type": "call"
},
{
"... |
13097992788 | # !/usr/bin/env python
# -*- coding: utf-8 -*-
"""
@author: lishuang
@description: 利用 LSTM 预测股票价格
"""
import os
from itertools import chain
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from tensorflow.keras.layers import Dense, Dropout, LSTM
from tensorflow.keras.models import load_model, Se... | TatenLee/machine-learning | bi/core/l8/stock_lstm.py | stock_lstm.py | py | 4,659 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "pandas.DataFrame",
"line_number": 35,
"usage_type": "call"
},
{
"api_name": "pandas.concat",
"line_number": 51,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 67,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_nu... |
16964477743 | from bs4 import BeautifulSoup
import re
import requests
ENROLLMENT_BOUNDS = {
0: [0, 5000],
1: [5000, 15000],
2: [15000, 30000],
3: [30000, 10000000],
}
def get_college_basic(uni_id_list):
where_str = ''
order_by_str = 'ORDER BY (CASE'
counter = 1
for id in uni_id_list:
id_str... | michaelpri10/collegecalculator | query_schools.py | query_schools.py | py | 10,807 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "requests.get",
"line_number": 211,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 212,
"usage_type": "call"
},
{
"api_name": "re.compile",
"line_number": 216,
"usage_type": "call"
},
{
"api_name": "re.sub",
"line_numbe... |
34222275021 | from django.shortcuts import render, redirect
from django.contrib.auth.forms import UserCreationForm, AuthenticationForm
from django.contrib.auth import login as auth_login, logout as auth_logout
from django.views.decorators.http import require_http_methods
from .forms import CustomUserCreationForm
@require_http_metho... | kimhyunso/exampleCode | django/ONE_TO_MANY/accounts/views.py | views.py | py | 1,375 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "django.contrib.auth.forms.AuthenticationForm",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "django.contrib.auth.login",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "django.shortcuts.redirect",
"line_number": 16,
"usage_type": "call... |
39332540750 | from django.shortcuts import render
from abb.models import visitors
from abb.forms import visitorform
# Create your views here.
def show_data(request):
form=visitorform()
if request.method=='POST':
form=visitorform(request.POST)
if form.is_valid():
name=form.cleaned_data['name']
... | dhokanerahul13/4-11-22 | hotel/abb/views.py | views.py | py | 610 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "abb.forms.visitorform",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "abb.forms.visitorform",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "abb.models.visitors",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "abb.fo... |
17849902067 | from scripts.src.common.config import Color, Keywords, Direct, DataType
from common_and_plotting_functions.functions import check_and_mkdir_of_direct
from scripts.src.common.plotting_functions import multi_row_col_bar_plot
from scripts.data.common_functions import common_data_loader
from scripts.model.model_loader im... | LocasaleLab/Automated-MFA-2023 | scripts/src/experimental_data_analysis/specific_data_model_combination/renal_carcinoma_invivo_infusion.py | renal_carcinoma_invivo_infusion.py | py | 21,216 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "scripts.data.common_functions.common_data_loader",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "scripts.src.common.config.DataType.renal_carcinoma",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "scripts.src.common.config.DataType",
... |
17096720993 | # #############################################################################
# 本題參數設定，請勿更改
seed = 0 # 亂數種子數
# #############################################################################
import warnings
warnings.filterwarnings('ignore')
import numpy as np
import pandas as pd
evaluation = pd.DataFrame({'Model... | neochen2701/TQCPans | 機器學習Python 3答案檔/MLA305.py | MLA305.py | py | 5,623 | python | en | code | 4 | github-code | 36 | [
{
"api_name": "warnings.filterwarnings",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "pandas.get_du... |
16908305317 | # import package
import os, random, tweepy, time, schedule
def job():
folder=r"F:\mat\twitterbot\pics" # Set your folder here, twitter allows .jpg, .jpeg, .png, .gif and mp4 videos to be uploaded as media.
# Current limitations as of 18/07/2... | mdsmendes94/twitterdailybot | ttbot.pyw | ttbot.pyw | pyw | 1,988 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "random.choice",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "os.listdir",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "tweepy.OAuthHandler",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "tweepy.API",
"line_num... |
41473256040 | from PyQt5.QtWidgets import QLabel, QApplication, QDialog, QGridLayout, QHBoxLayout, QPushButton, QFormLayout, \
QWidget, \
QLineEdit
import sys
from PyQt5.QtCore import Qt
from PyQt5.QtGui import QIcon
class calculator_frame(QDialog):
def __init__(self):
super().__init__()
self.shower = Q... | siuwhat/calculator | calculator_frame.py | calculator_frame.py | py | 5,213 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "PyQt5.QtWidgets.QDialog",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "PyQt5.QtWidgets.QLineEdit",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "PyQt5.QtWidgets.QLabel",
"line_number": 13,
"usage_type": "call"
},
{
"api_name"... |
19686841128 | from argparse import ArgumentParser
import tabulate
argparser = ArgumentParser()
argparser.add_argument('--device', type=int, required=True, help='id of device to run training on.')
argparser.add_argument('--seed', type=int, required=True, help='random seed to use for training.')
argparser.add_argument('--dir', type=s... | ChaseDuncan/2dunet | train.py | train.py | py | 9,434 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "os.makedirs",
"line_number": 40,
"usage_type": "call"
},
{
"api_name": "os.makedirs",
"line_number": 41,
"usage_type": "call"
},
{
"api_name": "os.makedirs",
"lin... |
11677498007 | # This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful, but
... | blender-for-science/blendmsh | __init__.py | __init__.py | py | 2,626 | python | en | code | 28 | github-code | 36 | [
{
"api_name": "bpy.utils.register_class",
"line_number": 47,
"usage_type": "call"
},
{
"api_name": "preferences.BlendmshPreferences",
"line_number": 47,
"usage_type": "argument"
},
{
"api_name": "bpy.utils",
"line_number": 47,
"usage_type": "attribute"
},
{
"api_n... |
12303872667 | from albumentations.augmentations.transforms import Normalize
import torch
import torchvision
import albumentations
import albumentations.pytorch
from adamp import AdamP
import torch.nn as nn
from torch.utils.data import Dataset, DataLoader
from torchsummary import summary as summary_
from dataset import C... | taeyang916/kaggle_fruits | train.py | train.py | py | 2,350 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "torch.cuda.is_available",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "torch.cuda",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "albumentations.Compose",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "albume... |
42493495025 | from __future__ import absolute_import, print_function, division
import os
from string import Template
import numpy as np
import theano
from theano import Apply
from theano.tensor import as_tensor_variable
from theano.tensor.sort import TopKOp
from .basic_ops import (GpuKernelBase, Kernel, infer_context_name,
... | Theano/Theano | theano/gpuarray/sort.py | sort.py | py | 12,720 | python | en | code | 9,807 | github-code | 36 | [
{
"api_name": "basic_ops.GpuKernelBase",
"line_number": 26,
"usage_type": "name"
},
{
"api_name": "theano.tensor.sort.TopKOp",
"line_number": 26,
"usage_type": "name"
},
{
"api_name": "theano.tensor.sort.TopKOp.__props__",
"line_number": 33,
"usage_type": "attribute"
},... |
2364287539 | from PyQt5 import QtWidgets, uic,QtSql,QtCore
from rajon_1 import Ui_Dialog
import sqlite3 as sql
from vypocet import vypocty
from data import Databaze
from PyQt5.QtWidgets import QFileDialog
from cesta import path
import math
class Rajon(QtWidgets.QDialog,Ui_Dialog):
def __init__(self,cesta_projektu):
su... | ctu-yobp/2020-a | app/rajon_2.py | rajon_2.py | py | 4,041 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "PyQt5.QtWidgets.QDialog",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "PyQt5.QtWidgets",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "rajon_1.Ui_Dialog",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "data.D... |
33390403216 | from django.shortcuts import redirect, render
from animalprofile.models import Animal, Kind
from userprofile.models import UserAccount
from .forms import SearchAnimalsForm
def index(request):
if request.method == 'POST':
form = SearchAnimalsForm(request.POST)
if form.is_valid():
try: ... | manulovich/zoo-friend | zoofriends/animalprofiles/views.py | views.py | py | 1,839 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "forms.SearchAnimalsForm",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "animalprofile.models.Animal.objects.filter",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "animalprofile.models.Animal.objects",
"line_number": 23,
"usage_type": ... |
17079399924 | from operator import itemgetter
from typing import Dict, Iterable, List, Optional, Tuple
import typer
from lib.legiscan import BillDescriptor, download_and_extract
from lib.util import load_json
def wrangle_metadata(metadata: Dict) -> Tuple[BillDescriptor, Optional[str]]:
"""Get the stuff from a metadata blob th... | amy-langley/tracking-trans-hate-bills | lib/tasks/legiscan/retrieve_legislation.py | retrieve_legislation.py | py | 1,373 | python | en | code | 2 | github-code | 36 | [
{
"api_name": "typing.Dict",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "lib.legiscan.BillDescriptor",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "operator.itemgetter",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "typing.Tup... |
8567322626 | # coding: utf-8
#from PyInstaller.utils.hooks import copy_metadata, collect_data_files
#datas = copy_metadata('google-api-python-client')
#datas += collect_data_files('googleapiclient.discovery')
#datas += collect_data_files('PyInstaller.utils.hooks')
import os, sys, re
import pandas as PD
from datetime impo... | jameswhc/QUA | QUA_Classify.py | QUA_Classify.py | py | 19,830 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "re.compile",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "datetime.datetime.strptime",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 25,
"usage_type": "name"
},
{
"api_name": "datetime.date... |
17778652132 | from PyQt4.QtGui import *
from PyQt4.QtCore import *
import matplotlib.pyplot as plt
import matplotlib.backends.backend_qt4agg
import ReportDBOps as db
class ReportLogs(QWidget):
def __init__(self):
super(ReportLogs, self).__init__()
# Main Layout
self.mainGridLayout = QGridLayout()
... | subhamoykarmakar224/WindowsThreatAttackAnalyzer | ReportLogs.py | ReportLogs.py | py | 2,477 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "ReportDBOps.getUniqueReports",
"line_number": 45,
"usage_type": "call"
},
{
"api_name": "ReportDBOps.getReportCounts",
"line_number": 54,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.subplot2grid",
"line_number": 56,
"usage_type": "call"
},
... |
7114744218 | import numpy as np
import pandas as pd
from sklearn.preprocessing import Imputer
import keras
from keras.utils import np_utils
# Veri dosya üzerinden okunur.
data = pd.read_csv('spambase.data')
# PART 1 - DATAPREPROCESSING
# Okunan veri girdi ve çıktı olarak ayrıştırılır.
input_datas = np.array(data.iloc[:,:57])
out... | zekikus/Yapay-Sinir-Agi-Uygulamalari | SpamBase_ANN/SpamBase_ANN.py | SpamBase_ANN.py | py | 3,448 | python | tr | code | 8 | github-code | 36 | [
{
"api_name": "pandas.read_csv",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "sklearn.model_selection.train_... |
18647131917 | from django.http import HttpResponse
from django.template import RequestContext
from taikoexplorer_db.models import Video, Composer, Song, Group, SongStyle, ComposerSong, VideoSong, VideoGroup
from django.core import serializers
from django.forms.models import model_to_dict
from django.db.models import Count
import yo... | mitchfuku/taikoexplorer | taikoexplorer/data.py | data.py | py | 12,403 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "json.loads",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "taikoexplorer_db.models.Video.objects.get_or_create",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "taikoexplorer_db.models.Video.objects",
"line_number": 31,
"usage_type": "... |
9195540013 | import argparse
import pickle
import lmdb
import torch
from tqdm import tqdm
from torch.utils.data import DataLoader
from vq_text_gan.datasets import BPEDataset
from vq_text_gan.utils import get_default_device
def extract_codes(args):
device = get_default_device(args.device)
print('Loading model')
mode... | kklemon/text-gan-experiments | legacy/vq_text_gan/extract_latents.py | extract_latents.py | py | 1,643 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "vq_text_gan.utils.get_default_device",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "torch.load",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "vq_text_gan.datasets.BPEDataset",
"line_number": 20,
"usage_type": "call"
},
{
"a... |
8435375603 | from aiogram import types, Dispatcher
from config import bot, dp, ADMINS
import random
async def game(message: types.Message):
if message.text.startswith('game') and message.from_user.id in ADMINS:
list_emoji = ['⚽', '🏀', '🎰', '🎳', '🎯', '🎲']
emoji_random = random.choice(list_emoji)
awa... | kasi170703/bots | handlers/admin.py | admin.py | py | 577 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "aiogram.types.Message",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "aiogram.types",
"line_number": 5,
"usage_type": "name"
},
{
"api_name": "config.ADMINS",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "random.choice",
... |
24398919509 | import requests
from bs4 import BeautifulSoup
import config
## setup
url = 'https://eu4.paradoxwikis.com/Achievements'
page = requests.get(url)
soup = BeautifulSoup(page.content, 'html.parser')
table = soup.find('table')
def scrape():
table_dict = {}
headers = config.headers
url = 'https://e... | CarsenKennedy/EU4-flask-api | webscraper.py | webscraper.py | py | 1,608 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "requests.get",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "config.headers",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "requests.get",
"... |
72488882665 | from rest_framework import viewsets, views
from ..models import *
from .serializers import *
from rest_framework.permissions import *
from rest_framework.response import Response
from rest_framework.exceptions import NotFound, ValidationError
from rest_framework import mixins
from .custom_mixins import CreateListModelM... | artgas1/dlab_django | lab/lab_web/views/api.py | api.py | py | 18,206 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "rest_framework.viewsets.ModelViewSet",
"line_number": 31,
"usage_type": "attribute"
},
{
"api_name": "rest_framework.viewsets",
"line_number": 31,
"usage_type": "name"
},
{
"api_name": "rest_framework.viewsets.ModelViewSet",
"line_number": 45,
"usage_type":... |
42932594486 | import dash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Output, Input
import dash_bootstrap_components as dbc
import pandas as pd
import plotly.express as px
from plotly.graph_objs import *
def run_dash(bales_graph_file_path, pie_chart_file_path, bar_... | Tijzz/ComptencyAnalysisTool | Dash.py | Dash.py | py | 6,994 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "pandas.read_csv",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
... |
44007402888 | from django.urls import path
from .views import (
BasicInfoView,
ContactFormView,
FindProviderMedicationView,
GetFormOptionsView,
)
public_api_urlpatterns = [
path(
'options/',
GetFormOptionsView.as_view(),
),
path(
'find_providers/',
FindPro... | ninjadevtrack/medifiner-api | public/api_urls_v1.py | api_urls_v1.py | py | 521 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "django.urls.path",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "views.GetFormOptionsView.as_view",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "views.GetFormOptionsView",
"line_number": 13,
"usage_type": "name"
},
{
"api_na... |
28145554362 | from flask import Flask, request, jsonify
from urllib.request import urlopen
import json
app = Flask(__name__, static_folder='static')
@app.route('/')
def index():
return app.send_static_file('index.html')
@app.route('/api/submit', methods=['POST'])
def submit():
data = request.get_json()
message = data.... | coconnor07/WebsiteTest | __main__.py | __main__.py | py | 1,807 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "flask.Flask",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "flask.request.get_json",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "flask.request",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "flask.jsonify",
"... |
23452187462 | # coding=utf-8
import datetime
from OnlineClassroom.app.ext.plugins import db
from .curriculums import *
from .account import *
from .catalog import *
"""
购买记录
CREATE TABLE `shopping_carts` (
`aid` int DEFAULT NULL COMMENT '外键 用户id',
`cid` int DEFAULT NULL COMMENT '外键 课程id',
`number` int DEFAULT '1' COMMENT '课程... | z1421012325/flask_online_classroom | app/models/shopping_carts.py | shopping_carts.py | py | 5,125 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "OnlineClassroom.app.ext.plugins.db.Model",
"line_number": 25,
"usage_type": "attribute"
},
{
"api_name": "OnlineClassroom.app.ext.plugins.db",
"line_number": 25,
"usage_type": "name"
},
{
"api_name": "OnlineClassroom.app.ext.plugins.db.Column",
"line_number": 2... |
5023782942 | # -*- coding: utf-8 -*-
import os
import shutil
import torch
# from torch.utils.data import *
from torch.utils import data
from imutils import paths
import numpy as np
import random
from PIL import Image
from torchvision.transforms import transforms
import cv2
def cv_imread(path):
img = cv2.imdecode(... | stlyl/crack_detection | crack_detection_python/crack_dataset.py | crack_dataset.py | py | 2,601 | python | en | code | 2 | github-code | 36 | [
{
"api_name": "cv2.imdecode",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "numpy.fromfile",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "numpy.uint8",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "cv2.imencode",
"line... |
7582763868 | import urllib.request, urllib.parse, urllib.error
import twurl
import json
import ssl
# https://apps.twitter.com/
# Create App and get the four strings, put them in hidden.py
TWITTER_URL = 'https://api.twitter.com/1.1/friends/list.json'
# Ignore SSL certificate errors
ctx = ssl.create_default_context()
ctx.check_hos... | soliashuptar/LAB3 | twitter2.py | twitter2.py | py | 1,574 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "ssl.create_default_context",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "ssl.CERT_NONE",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "twurl.augment",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "urllib.re... |
27819397243 | import networkx as nx
import numpy as np
from params import args
class JobDAG(object):
def __init__(self, nodes, adj_mat, name):
# nodes: list of N nodes
# adj_mat: N by N 0-1 adjacency matrix, e_ij = 1 -> edge from i to j
assert len(nodes) == adj_mat.shape[0]
assert adj_mat.shap... | SpeedSchedulerProject/MDPA | spark_env/job_dag.py | job_dag.py | py | 3,725 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "numpy.inf",
"line_number": 48,
"usage_type": "attribute"
},
{
"api_name": "params.args.executor_data_point",
"line_number": 62,
"usage_type": "attribute"
},
{
"api_name": "params.args",
"line_number": 62,
"usage_type": "name"
},
{
"api_name": "param... |
20371505372 | import tensorflow as tf
gpus = tf.config.list_physical_devices('GPU')
if gpus:
tf.config.set_logical_device_configuration(gpus[0], [tf.config.LogicalDeviceConfiguration(memory_limit=5292)])
import keras
import matplotlib.pyplot as plt
import numpy as np
from keras import layers, optimizers, losses, metrics, Model... | Logann120/Logann120.github.io | img_gen/python_code/img_gen.py | img_gen.py | py | 7,935 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "tensorflow.config.list_physical_devices",
"line_number": 2,
"usage_type": "call"
},
{
"api_name": "tensorflow.config",
"line_number": 2,
"usage_type": "attribute"
},
{
"api_name": "tensorflow.config.set_logical_device_configuration",
"line_number": 4,
"usag... |
24916190530 | #encoding:utf-8
import os
import requests
class MyRequests():
def get_url(self, url, headers):
re = self.request(url, headers)
return re
def request(self, url, headers):
re = requests.get(url, headers=headers)
return re
def main():
url = "https://www.baidu.com"
he... | fanpengcs/python | my_requests.py | my_requests.py | py | 1,750 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "requests.get",
"line_number": 12,
"usage_type": "call"
}
] |
36901679046 | import logging
from math import sqrt
from typing import Optional
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
import torch
from tqdm import trange
from ..common import HistoricalData, get_device
from ..exceptions import SimulationException
from . import Simulations
log... | ethanlee928/pyfmc | pyfmc/simulations/gbm.py | gbm.py | py | 5,015 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "logging.getLogger",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "torch.Tensor",
"line_number": 20,
"usage_type": "attribute"
},
{
"api_name": "matplotlib.pyplot.subplots",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "matplo... |
41550884221 | import math
import warnings
from typing import Sequence
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torchmetrics.functional import pairwise_cosine_similarity
from mmcv.cnn import (build_activation_layer, build_conv_layer,
build_norm_layer, xavier_ini... | parkyongjun1/rotated_deformabledetr | AO2-DETR/mmrotate/models/utils/rotated_transformer.py | rotated_transformer.py | py | 59,187 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "warnings.warn",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "torch.autograd.set_detect_anomaly",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "torch.autograd",
"line_number": 37,
"usage_type": "attribute"
},
{
"api_name": "f... |
6797208641 | # app imports
import random
from django.utils.translation import ugettext_lazy as _
from django.conf import settings
from utils.faker_factory import faker
from ..mails import BaseMailView
class InvitationConsultantProjectMailView(BaseMailView):
template_name = 'mails/invitation_consultant_project.html'
man... | tomasgarzon/exo-services | service-exo-mail/mail/mailviews/invitation_consultant_project.py | invitation_consultant_project.py | py | 1,281 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "mails.BaseMailView",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "django.utils.translation.ugettext_lazy",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "django.conf.settings.BRAND_NAME",
"line_number": 19,
"usage_type": "attribute"
... |
35512038562 | import json
import shutil
import unittest
from src import SDF3dData, train_sdf
from src.train_utils import *
class SDFTrainTest(unittest.TestCase):
@staticmethod
def get_abs_path():
path = os.path.abspath(__file__)
parent_dir = os.path.split(path)[0]
return parent_dir
def get_data... | amaleki2/graph_sdf | test/test_train.py | test_train.py | py | 2,349 | python | en | code | 2 | github-code | 36 | [
{
"api_name": "unittest.TestCase",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "json.load",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "src.SDF3dData",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "json.load",
"line_n... |
33215612402 | import os
import torch
import cflearn
import numpy as np
# for reproduction
np.random.seed(142857)
torch.manual_seed(142857)
# preparation
data_config = {"label_name": "Survived"}
file_folder = os.path.dirname(__file__)
train_file = os.path.join(file_folder, "train.csv")
test_file = os.path.join(file_folder, "test.c... | TrendingTechnology/carefree-learn | examples/titanic/titanic.py | titanic.py | py | 1,421 | python | en | code | null | github-code | 36 | [
{
"api_name": "numpy.random.seed",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "numpy.random",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "torch.manual_seed",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "os.path.dirname",
... |
74840516263 | import glob
import os, shutil
import numpy as np
import xml.etree.ElementTree as ET
from skimage import io, transform
from PIL import Image
import cv2
class BatchPcik():
'''
批量判断图片维度，并挑出不符合的文件至error文件夹
！！！error文件夹如果没有可以新建功能！！！
'''
def __init__(self):
self.imgdir_path = "F:/Fruit_dataset/... | CGump/dataset-tools | pick_img.py | pick_img.py | py | 11,355 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "os.listdir",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "os.path.isdir",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 32,
"usage_type": "attribute"
},
{
"api_name": "glob.glob",
"line_number": ... |
14381362201 | # 1099
from typing import List
def twoSumLessThanK(nums: List[int], k: int) -> int:
nums = sorted(nums)
ans = -1
i = 0
j = len(nums) - 1
while i < j:
if nums[i] + nums[j] >= k:
j -= 1
else:
ans = max(ans, nums[i] + nums[j])
... | jithindmathew/LeetCode | two-sum-less-than-k.py | two-sum-less-than-k.py | py | 455 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "typing.List",
"line_number": 5,
"usage_type": "name"
}
] |
13998551053 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import unittest
from os import path, listdir, curdir, remove
import uproot as ur
from astropy.io import fits
from km3net_testdata import data_path
from km3irf import build_irf
class TestBuild_IRF(unittest.TestCase):
def setUp(self):
self.testdata = data_path... | KM3NeT/km3irf | tests/test_main.py | test_main.py | py | 2,400 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "unittest.TestCase",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "km3net_testdata.data_path",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "km3irf.build_irf.DataContainer",
"line_number": 15,
"usage_type": "call"
},
{
"a... |
24369652375 | from django.shortcuts import render, HttpResponseRedirect
from django.contrib.auth import login, authenticate
from .forms import SignUpForm, LoginForm, PostForm
from django.contrib.auth import authenticate, login, logout
from .models import Post
# Create your views here.
def Home(request):
return render(request,... | SurajLodh/TaskProduct | User/views.py | views.py | py | 2,617 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "django.shortcuts.render",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "forms.SignUpForm",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "django.shortcuts.HttpResponseRedirect",
"line_number": 19,
"usage_type": "call"
},
{
"ap... |
2014305094 | import speech_recognition as sr
import pyttsx3
def SpeakText(command):
engine = pyttsx3.init()
engine.say(command)
engine.runAndWait()
def CollectText(x, gram):
recognizer = sr.Recognizer()
microphone = sr.Microphone()
with microphone as source:
recognizer.adjust_for_ambient_noise(sour... | Dorito-Dog/Python_Ktane_Bot | solvers/solverSpeech.py | solverSpeech.py | py | 488 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "pyttsx3.init",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "speech_recognition.Recognizer",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "speech_recognition.Microphone",
"line_number": 11,
"usage_type": "call"
}
] |
43844905296 | import argparse
from dataclasses import dataclass
from decimal import *
import re
import sys
from typing import Dict, List
int_re = re.compile('[-+]?[0-9]+')
float_re = re.compile('[-+]?[0-9]+(\.[0-9]+)?')
def extract_int(l: str) -> (int, str):
m = int_re.match(l)
assert m
s = m.group()
return int(... | brouhaha/gridcheck | gridcheck.py | gridcheck.py | py | 4,133 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "re.compile",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "re.compile",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "dataclasses.dataclass",
"line_number": 28,
"usage_type": "name"
},
{
"api_name": "dataclasses.dataclass",
... |
20515420312 | import os
import PyPDF2
import openai
from flask import Flask, redirect, render_template, request, url_for
app = Flask(__name__)
# Set your API key directly
os.environ["OPENAI_API_KEY"] = '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'
openai.api_key = os.getenv("OPENAI_API_KEY")
@app.route("/", methods=["GET"... | OUABSL/Congreso | app.py | app.py | py | 1,642 | python | es | code | 0 | github-code | 36 | [
{
"api_name": "flask.Flask",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "os.environ",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "openai.api_key",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "os.getenv",
"line_n... |
8445360878 | import operator
import warnings
import numpy
try:
import scipy.sparse
_scipy_available = True
except ImportError:
_scipy_available = False
import cupy
from cupy._core import _accelerator
from cupy.cuda import cub
from cupy.cuda import runtime
from cupyx.scipy.sparse import _base
from cupyx.scipy.sparse i... | cupy/cupy | cupyx/scipy/sparse/_csr.py | _csr.py | py | 42,419 | python | en | code | 7,341 | github-code | 36 | [
{
"api_name": "cupyx.scipy.sparse._compressed._compressed_sparse_matrix",
"line_number": 23,
"usage_type": "attribute"
},
{
"api_name": "cupyx.scipy.sparse._compressed",
"line_number": 23,
"usage_type": "name"
},
{
"api_name": "scipy.sparse.sparse.csr_matrix",
"line_number": ... |
73491948585 | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from utils.models import BaseModel, models
from utils import constants as Constants, get_choices, get_kyc_upload_path
from django.contrib.contenttypes.models import ContentType
from django.db.models.signals import post_save
from django.utils.timezone imp... | anjali-rao/backend-app-1 | crm/models.py | models.py | py | 8,059 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "utils.models.BaseModel",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "utils.models.models.ForeignKey",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "utils.models.models",
"line_number": 15,
"usage_type": "name"
},
{
"api_nam... |
35420476348 | from PIL import Image
import numpy as np
import matplotlib.pyplot as plt
path_gotowe = "kolos_1/obrazy/"
path = "kolos_1/"
def szary(w, h):
t = (h, w)
tab = np.zeros(t, dtype=np.uint8)
for i in range(0, h, 1):
for j in range(0, w, 1):
tab[i, j] = (i + 3*j) % 256
return tab
obraz... | AdrianAlbrecht/WdGM | kolos_1/zad7.py | zad7.py | py | 910 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "numpy.zeros",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "numpy.uint8",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "PIL.Image.open",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "PIL.Image",
"line_num... |
38875856666 | import sys
sys.path.append('.')
from contextlib import contextmanager
import time
import torch
import graphnet as GNN
num_iters = 100000
NN = 128*1024
D = 128
DT = torch.float16
dev = torch.device('cuda:0')
is_cuda = dev.type == 'cuda'
#net = GNN.Mlp(3 * D, [D, D, D], layernorm=False).to(DT).to(dev)
net = torch.... | medav/meshgraphnets-torch | test/test_torch_mlp.py | test_torch_mlp.py | py | 555 | python | en | code | 6 | github-code | 36 | [
{
"api_name": "sys.path.append",
"line_number": 2,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 2,
"usage_type": "attribute"
},
{
"api_name": "torch.float16",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "torch.device",
"li... |
4511356839 | import openpyxl
from collections import Counter
from difflib import SequenceMatcher
from collections import OrderedDict
import time
import numpy
import sys
path = "F:\\Book1.xlsx"
wb_obj = openpyxl.load_workbook(path)
sheet_base = wb_obj.worksheets[0]
sheet_area_1 = wb_obj.worksheets[1]
sheet_area_2 = wb_obj.workshe... | ChinhTheHugger/vscode_python | excel.py | excel.py | py | 1,448 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "openpyxl.load_workbook",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "time.time",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "time.strftime",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "time.gmtime",
"lin... |
19417305890 | import requests
class Player:
def __init__(self, dict):
self.name = dict['name']
self.nationality = dict['nationality']
self.team = dict['team']
self.goals = dict['goals']
self.assists = dict['assists']
self.points = self.goals + self.assists
def __str__(self):... | alannesanni/palautusrepositorio | viikko2/nhl-reader/src/player.py | player.py | py | 1,119 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "requests.get",
"line_number": 21,
"usage_type": "call"
}
] |
30781006442 | # -*- coding: utf-8 -*-
import oss2
from oss2.credentials import EnvironmentVariableCredentialsProvider
import os
# 这里填写你的 OSS_ACCESS_KEY_ID 和 OSS_ACCESS_KEY_SECRET
os.environ['OSS_ACCESS_KEY_ID'] = ''
os.environ['OSS_ACCESS_KEY_SECRET'] = ''
auth = oss2.ProviderAuth(EnvironmentVariableCredentialsProvider())
# 这里改成你... | source-dream/AliyunOSS-DownloadTool | main.py | main.py | py | 1,190 | python | zh | code | 0 | github-code | 36 | [
{
"api_name": "os.environ",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "os.environ",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "oss2.ProviderAuth",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "oss2.credentials.Envi... |
73744223785 | # -*- coding: utf-8 -*-
from __future__ import print_function
import os
import logging
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
VERSION = "1.0"
# Application definition
INSTALLED_APPS = (
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'... | lingdb/CoBL-public | ielex/settings.py | settings.py | py | 5,555 | python | en | code | 3 | github-code | 36 | [
{
"api_name": "os.path.dirname",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "os.path.abspath",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_nu... |
38875732926 |
import torch
import torch.nn as nn
from torch.utils.cpp_extension import load
import os
import time
import random
import math
cur_path = os.path.dirname(os.path.realpath(__file__))
if torch.cuda.is_available():
scatter_concat_cuda = load('scatter_concat_cuda',
[f'{cur_path}/scatter_concat.cu'],
ex... | medav/meshgraphnets-torch | kernels/scatter_concat/kernel.py | kernel.py | py | 1,699 | python | en | code | 6 | github-code | 36 | [
{
"api_name": "os.path.dirname",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "os.path.realpath",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "torch.cuda.is_available... |
43082790642 | import numpy as np
from matplotlib import pyplot as plt
def smooth(data, box_pts):
box = np.ones(box_pts)/box_pts
data_smooth = np.convolve(data, box, mode='same')
return data_smooth
filename = 'limited'
ignore_lines = True
x_min = np.inf
x_max = -np.inf
y_min = np.inf
y_max = -np.inf
z_min =... | dlech97/master-thesis | process_log.py | process_log.py | py | 3,749 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "numpy.ones",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "numpy.convolve",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "numpy.inf",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "numpy.inf",
"line_number":... |
11841445530 | import torch
from torch import nn
from spdnet.spd import Normalize
class GBMS_RNN(nn.Module):
def __init__(self, bandwidth=0.1, normalize=True):
super(GBMS_RNN, self).__init__()
self.bandwidth = nn.Parameter(torch.tensor(bandwidth))
self.normalize = None
if normalize:
... | Dandy5721/CPD-Net | MICCAI-2021/mean_shift/mean_shift.py | mean_shift.py | py | 1,419 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "torch.nn.Module",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "torch.nn.Parameter",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line_nu... |
17930873755 | #!/usr/bin/python
import os
import sys
myPath = os.path.dirname(os.path.abspath(__file__))
sys.path.insert(0, os.path.dirname(myPath))
import pytest
import src.pre_commit as pre_commit
import subprocess
from mock import patch
commit_is_ready_params = [
(["test/foo.py"], []),
(["test/clean.c"], []),
("... | aws/amazon-freertos | tools/git/hooks/test/test_pre_commit.py | test_pre_commit.py | py | 5,105 | python | en | code | 2,543 | github-code | 36 | [
{
"api_name": "os.path.dirname",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "os.path.abspath",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "sys.path.insert",
"line... |
22805925879 | import fiftyone as fo
import fiftyone.zoo as foz
dataset = foz.load_zoo_dataset("quickstart")
# Create a custom App config
app_config = fo.AppConfig()
app_config.show_confidence = True
app_config.show_attributes = True
session = fo.launch_app(dataset, config=app_config, port=5151)
session.wait() | patharanordev/ds51vis | sample.py | sample.py | py | 300 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "fiftyone.zoo.load_zoo_dataset",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "fiftyone.zoo",
"line_number": 4,
"usage_type": "name"
},
{
"api_name": "fiftyone.AppConfig",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "fiftyone.l... |
10759107890 | import unittest
import sys
import time
sys.path.append("..")
from deltarest import DeltaRESTAdapter, DeltaRESTService
from pyspark.sql import SparkSession
class Test(unittest.TestCase):
root_dir: str = f"/tmp/delta_rest_test_{int(time.time())}"
spark: SparkSession = None
dra: DeltaRESTAdapter
@... | bonnal-enzo/delta-rest | test/test.py | test.py | py | 3,975 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "sys.path.append",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "unittest.TestCase",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "time.time",
"l... |
31071015439 | from core_algo.SGA import SGA
import alarm
import sys
import json
import time
from tabulate import tabulate
def average_res(ga, cal_times=100, **params):
cost_sum = 0
runtime_sum = 0
gen_sum = 0
speed_sum = 0
for _ in range(cal_times):
# solve the question
res, runtime, last_gen =... | UTP-project/core-algo | exp_compare.py | exp_compare.py | py | 7,044 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "tabulate.tabulate",
"line_number": 36,
"usage_type": "call"
},
{
"api_name": "json.load",
"line_number": 49,
"usage_type": "call"
},
{
"api_name": "time.time",
"line_number": 55,
"usage_type": "call"
},
{
"api_name": "core_algo.SGA.SGA",
"line_n... |
8272041392 | """
Test the OOD DiscDist2 scorer. It disentangle the feature into discriminative space and the residual space
"""
import pdb
import numpy as np
import matplotlib.pyplot as plt
import os
import argparse
import torch
from tqdm import tqdm
import torch.backends.cudnn as cudnn
from ood_scores.get_scorers ... | ivalab/WDiscOOD | test_feat_disc.py | test_feat_disc.py | py | 5,166 | python | en | code | 4 | github-code | 36 | [
{
"api_name": "numpy.random.seed",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "numpy.random",
"line_number": 23,
"usage_type": "attribute"
},
{
"api_name": "utils.argparser.OODArgs",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "ood_score... |
25969718175 | # -*- coding: utf-8 -*-
from django.http import HttpResponse
from django.template import RequestContext, Template
from django.views.decorators.csrf import csrf_exempt
from django.utils.encoding import smart_str, smart_unicode
import xml.etree.ElementTree as ET
import urllib, urllib2, time, hashlib
@csrf_exempt
def ... | wqh872081365/weixin0324 | weixin0324/views1.py | views1.py | py | 2,306 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "django.http.HttpResponse",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "django.http.HttpResponse",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "django.http.HttpResponse",
"line_number": 21,
"usage_type": "call"
},
{
"api_na... |
22355151722 | # coding: utf-8
import tkinter as tk
from tkinter import messagebox, filedialog
import os
from PIL import Image, ImageTk
from detector import PlateDetector
from util import resized_size
class LPRGUI:
max_image_width = 600
max_image_height = 600
def __init__(self):
self.detector = PlateDetector(... | QQQQQby/Car-Plate-Recognition | start_gui.py | start_gui.py | py | 3,908 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "detector.PlateDetector",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "tkinter.Tk",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "tkinter.StringVar",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "tkinter.Canvas",
... |
506681210 | """
Resample Raster Files
"""
def match_cellsize_and_clip(rstBands, refRaster, outFolder,
clipgeo=None, isint=None, ws=None):
"""
Resample images to make them with the same resolution and clip
Good to resample Sentinel bands with more than 10 meters.
Dependencies:... | jasp382/glass | glass/rst/rmp.py | rmp.py | py | 4,165 | python | en | code | 2 | github-code | 36 | [
{
"api_name": "os.path.exists",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 26,
"usage_type": "attribute"
},
{
"api_name": "glass.pys.oss.mkdir",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "glass.prop.prj.rst_ep... |
24985603198 | import pygame
from settings import BOSSTELEPORTINGSOUND, ENEMYHITSOUND, importFolder, bossPositions
from random import randint
from os import path
class Boss(pygame.sprite.Sprite):
def __init__(self, pos, surface, level):
super().__init__()
#animation
self.displaySurface = surface
s... | Maltoros/Project-Pygame | boss.py | boss.py | py | 8,327 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "pygame.sprite",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "pygame.Rect",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "pygame.time.get_ticks",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "pygame.time",
... |
37326026549 | from zipline.pipeline.factors import CustomFactor
from zipline.pipeline.data import USEquityPricing
import numpy as np
import warnings
def recurs_sum(arr):
arr_sum = np.zeros(arr.shape)
arr_sum[0] = arr[0]
for i in range(1, len(arr)):
arr_sum[i] = arr_sum[i-1]+arr[i]
return arr_sum
class A... | ahmad-emanuel/quant_trading_system | Indicators/chaikin_oscilator.py | chaikin_oscilator.py | py | 1,745 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "numpy.zeros",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "zipline.pipeline.factors.CustomFactor",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "zipline.pipeline.data.USEquityPricing.close",
"line_number": 29,
"usage_type": "attribut... |
40926602467 | from discord.ext.commands import bot, has_permissions
import discord.ext
from discord.ext import commands
from config import *
import asyncio
import random
# noinspection PyPackageRequirements
intents = discord.Intents.default()
intents.message_content = True
bot = commands.Bot(command_prefix=PREFIX, intents=intents, ... | Juilfsjc/SeniorDesign | main.py | main.py | py | 16,345 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "discord.ext.commands.Intents.default",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "discord.ext.commands.Intents",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "discord.ext.commands",
"line_number": 9,
"usage_type": "name"
},
... |
18252823651 | import bisect
from typing import List
class Solution:
def maxEnvelopes(self, envelopes: List[List[int]]) -> int:
items = sorted(envelopes, key=lambda x: (x[0], -x[1]))
piles = []
for item in items:
v = item[1]
i = bisect.bisect_left(piles, v)
if i == len... | hujienan/Jet-Algorithm | leetcode/354. Russian Doll Envelopes/index.py | index.py | py | 554 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "typing.List",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "bisect.bisect_left",
"line_number": 11,
"usage_type": "call"
}
] |
10840945598 | import os
import requests
from bs4 import BeautifulSoup
#os.system("clear")
def crawl():
url = "https://www.iban.com/currency-codes"
iban_result = requests.get(url)
iban_soup = BeautifulSoup(iban_result.text, "html.parser")
table = iban_soup.find("table", {"class": "table table-bordered downloads t... | cheonjiwan/python_challenge | assignment/Day5.py | Day5.py | py | 1,568 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "requests.get",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 12,
"usage_type": "call"
}
] |
15744786007 | import errno
import filecmp
import glob
import os
import platform
import random
import re
import shutil
import stat
import subprocess
import sys
import tarfile
import tempfile
import time
from typing import List, NamedTuple
import urllib.parse
from color import Coloring
from error import DownloadError
from error impor... | GerritCodeReview/git-repo | project.py | project.py | py | 160,523 | python | en | code | 267 | github-code | 36 | [
{
"api_name": "repo_logging.RepoLogger",
"line_number": 49,
"usage_type": "call"
},
{
"api_name": "typing.NamedTuple",
"line_number": 52,
"usage_type": "name"
},
{
"api_name": "error.RepoError",
"line_number": 66,
"usage_type": "name"
},
{
"api_name": "error.RepoE... |
40174507966 | # 访问链接
import requests
# 进度条
from tqdm import tqdm
# 定义一个类来构造方法
class Music:
def __init__(self):
"""
通过用户输入的歌曲名搜索对应的音乐列表
:return: 歌曲列表链接
"""
a = input('请输入想要下载的歌曲名称：')
__url = f'http://www.kuwo.cn/api/www/search/searchMusicBykeyWord?key={a}&pn=1&rn=20&http... | UIGNB123/kuwo | 面向对象式酷我音乐爬虫，引入init方法和私有方法.py | 面向对象式酷我音乐爬虫，引入init方法和私有方法.py | py | 3,171 | python | zh | code | 1 | github-code | 36 | [
{
"api_name": "requests.get",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 51,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 54,
"usage_type": "call"
},
{
"api_name": "tqdm.tqdm",
"line_number":... |
31772755575 | # coding=utf-8
import os
import logging
from bs4 import UnicodeDammit
from subliminal.api import io, defaultdict
from subliminal_patch.patch_provider_pool import PatchedProviderPool
logger = logging.getLogger(__name__)
def download_subtitles(subtitles, **kwargs):
"""Download :attr:`~subliminal.subtitl... | luboslavgerliczy/SubZero | Contents/Libraries/Shared/subliminal_patch/patch_api.py | patch_api.py | py | 5,965 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "logging.getLogger",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "subliminal_patch.patch_provider_pool.PatchedProviderPool",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "subliminal.api.defaultdict",
"line_number": 41,
"usage_type": "... |
69815035624 | import os
from pyspark.sql import DataFrame
from pyspark.sql import types as t, functions as f
from pyspark.sql import SparkSession
from consts import COVID_DATE_FORMAT
def get_dataframe(name: str, session: SparkSession,
cols: list[str], type_mapping: dict,
date_format: str = COV... | volodymyrkir/pyspark_ml | utils.py | utils.py | py | 2,410 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "pyspark.sql.SparkSession",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "consts.COVID_DATE_FORMAT",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "os.path.join",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "os.pat... |
36867704347 | import spacy
nlp = spacy.load('en_core_web_md')
############
word1 = nlp("cat")
word2 = nlp("monkey")
word3 = nlp("banana")
print(word1.similarity(word2))
print(word3.similarity(word2))
print(word3.similarity(word1))
#############
tokens = nlp('cat apple monkey banana')
for token1 in tokens:
for token2 in toke... | rauldesor/T38 | semantic.py | semantic.py | py | 1,163 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "spacy.load",
"line_number": 2,
"usage_type": "call"
}
] |
17190663769 | import PySimpleGUI as sg
class GameGui:
def __init__(self,
box_size=15,
title = 'Japanese Crossword Puzzle!',
puzzle_size=500,
coor_sys_height=130
):
self.box_size = box_size
self.rows = 8
self.... | chengcj-upenn/jp_crossword_puzzle | frontend.py | frontend.py | py | 7,549 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "PySimpleGUI.theme",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "PySimpleGUI.Text",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "PySimpleGUI.Graph",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "PySimpleGUI.Text... |
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