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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
67546195 | import cv2 # for reading and writing or showing image
import numpy as np
import matplotlib.pyplot as plt
from keras.models import load_model
import keras
import tensorflow as tf
from keras.preprocessing import image
from keras.models import load_model
# from net import Net
from resnet_build import Net
import sys
# fro... | null | ocr_reinforce/CharClassification2/CharClassification_git/mp.py | mp.py | py | 2,525 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "keras.preprocessing.image.load_img",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "keras.preprocessing.image",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "matplotlib.pyplot.imshow",
"line_number": 20,
"usage_type": "call"
},
{
... |
54669744 | # Copyright 2015 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | null | tensorflow/python/keras/_impl/keras/engine/sequential.py | sequential.py | py | 38,139 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "tensorflow.python.keras._impl.keras.engine.training.Model",
"line_number": 45,
"usage_type": "name"
},
{
"api_name": "tensorflow.python.keras._impl.keras.backend.get_uid",
"line_number": 101,
"usage_type": "call"
},
{
"api_name": "tensorflow.python.keras._impl.kera... |
129136539 | # -*- coding: utf-8 -*-
"""
account.forms
:copyright: (c) 2013 by Openlabs Technologies & Consulting (P) Limited
:license: see LICENSE for more details.
"""
from django import forms
from account.models import UserProfile, TrainingProfile, StudentProfile, \
GovernmentProfile, IndustryProfile
__all__ = ... | null | pursuite/django-pursuite/apps/account/forms.py | forms.py | py | 1,535 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.forms.Form",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "django.forms",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "django.forms.CharField",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "django.for... |
544515252 | import os.path
import csv
import datetime
from django.contrib.auth import get_user_model
from django.core.management.base import BaseCommand
from django.utils import timezone
from hub.apps.content.models import Website
from hub.apps.metadata.models import (
Organization,
SustainabilityTopic,
AcademicDisci... | null | hub/apps/content/management/commands/import_academic_programs.py | import_academic_programs.py | py | 4,069 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.contrib.auth.get_user_model",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "django.core.management.base.BaseCommand",
"line_number": 22,
"usage_type": "name"
},
{
"api_name": "datetime.datetime.now",
"line_number": 29,
"usage_type": "call... |
437178078 | from math import inf, floor
from typing import Union, Optional, List, Dict
from num import Num
from options import options
from row import Row
from sym import Sym
from utils import copy
class Range:
def __init__(self, at, txt, lo, hi=None):
self.at = at
self.txt = txt
self.lo = lo
... | null | src/HW6/discretization.py | discretization.py | py | 5,242 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "sym.Sym",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "typing.Union",
"line_number": 28,
"usage_type": "name"
},
{
"api_name": "sym.Sym",
"line_number": 28,
"usage_type": "name"
},
{
"api_name": "num.Num",
"line_number": 28,
"us... |
130753459 |
import requests
import time
import sys
# You will need to register for a Wunderground API key and set it below
#
API_KEY = 'Your API key here'
def get_weather(date, location):
""" Return the json response as a Python dictionary"""
base_url = "http://api.wunderground.com/api/{api_key}/histo... | null | Exercises/solutions/Ex2a_source(solution).py | Ex2a_source(solution).py | py | 1,054 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "requests.get",
"line_number": 24,
"usage_type": "call"
}
] |
392611694 | from abc import abstractmethod
import trio
from async_service import background_trio_service
from lahja import EndpointAPI
from asyncio_run_in_process import open_in_process_with_trio
from trinity._utils.logging import child_process_logging, get_logger
from trinity._utils.profiling import profiler
from trinity.even... | null | trinity/extensibility/trio.py | trio.py | py | 3,503 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "component.BaseComponent",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "component.BaseIsolatedComponent",
"line_number": 26,
"usage_type": "name"
},
{
"api_name": "trinity._utils.logging.get_logger",
"line_number": 27,
"usage_type": "call"
},
... |
253024831 | import os
import numpy as np
import pyqtgraph as pg
import qtawesome as qta
from qtpy.QtWidgets import QMainWindow, QMdiSubWindow, QListWidget, QAction
from qtpy.QtCore import Signal, QObject, Property
from qtpy.uic import loadUi
from ..core.models import PlotProxyModel
from ..utils import UI_PATH
class PlotWindow(... | null | specviz/widgets/plotting.py | plotting.py | py | 4,115 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "qtpy.QtWidgets.QMdiSubWindow",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "qtpy.QtWidgets.QMainWindow",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "qtpy.uic.loadUi",
"line_number": 23,
"usage_type": "call"
},
{
"api_name"... |
498538400 | import random
import datetime
from candidate import Candidate
from project import Project
from experience import Experience
class DataGenerator:
__first_names = ["Alene", "Alessandra", "Aleta", "Alethea", "Alex", "Alexa", "Alexandra",
"Deedee", "Deena", "Deerdre", "Deeyn", "Dehlia", "Deidre"... | null | FlaskAPI_ENV/scripts/Section 1/Video 1.4/source_code/datagenerator.py | datagenerator.py | py | 3,421 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "random.randint",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "candidate.Candidate",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "random.randint",
"line_number": 46,
"usage_type": "call"
},
{
"api_name": "random.randint",
... |
392836180 | import base64
from flask import g
from service.auth import SimpleAuth
from service import db
from models.user import User
from app import app
basic_auth = SimpleAuth(auth_type="Basic")
@basic_auth.post_authentication
def check_confirmed():
return g.user.confirmed
@basic_auth.auth_error_handler
def basic_error... | null | service/auth_config.py | auth_config.py | py | 2,541 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "service.auth.SimpleAuth",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "flask.g.user",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "flask.g",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "base64.b64decode",
... |
376084962 | #!/usr/bin/python
# Importando modulo de leitura de planilhas
import datetime
import xlrd
import xlsxwriter
import sys
import os
# ----------------------------------INICIO DO CODIGO DE LEITURA DO PIPELINE -----------------------------------------#
print('Iniciando leitura das Planilhas PIPELINE, GSA e Textile....\n\n... | null | main_pipe.py | main_pipe.py | py | 3,986 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "xlrd.open_workbook",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "xlrd.open_workbook",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "xlrd.open_workbook",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "xlrd.xldate_... |
355507046 | import re
import xml.etree.ElementTree as metree
import random
INPUT_FILENAME = "./GKfiles/GKvocab_n4_raw.xml"
DICT_FILENAME = "/tools/dict/JMdict_e"
OUTPUT_FILENAME = "./GKvocab_n4_updated.xml"
pos_switch = {
"Godan verb with `bu' ending": {"VERB_5_BU"},
"Godan verb with `gu' ending": {"VERB_5_GU"},
"Godan verb with... | null | update_vocabulary.py | update_vocabulary.py | py | 13,348 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "xml.etree.ElementTree.parse",
"line_number": 98,
"usage_type": "call"
},
{
"api_name": "xml.etree.ElementTree",
"line_number": 98,
"usage_type": "name"
},
{
"api_name": "xml.etree.ElementTree.parse",
"line_number": 99,
"usage_type": "call"
},
{
"api... |
1194269 | import time
import subprocess
import digitalio
import board
from PIL import Image, ImageDraw, ImageFont
import adafruit_rgb_display.st7789 as st7789
# Configuration for CS and DC pins (these are FeatherWing defaults on M0/M4):
cs_pin = digitalio.DigitalInOut(board.CE0)
dc_pin = digitalio.DigitalInOut(board.D25)
reset_... | null | Lab 2/screen_clock.py | screen_clock.py | py | 3,338 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "digitalio.DigitalInOut",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "board.CE0",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "digitalio.DigitalInOut",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "board.D25"... |
455454861 | # coding=utf-8
"""
repl Plugin for DecoraterBot.
"""
import traceback
import inspect
from contextlib import redirect_stdout
import io
import discord
from discord.ext import commands
from DecoraterBotUtils.utils import *
class REPL:
"""
repl Plugin class.
"""
def __init__(self):
self.sessions... | null | repl.py | repl.py | py | 4,425 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "io.StringIO",
"line_number": 97,
"usage_type": "call"
},
{
"api_name": "contextlib.redirect_stdout",
"line_number": 100,
"usage_type": "call"
},
{
"api_name": "inspect.isawaitable",
"line_number": 102,
"usage_type": "call"
},
{
"api_name": "tracebac... |
10090221 | import json
from db import db, Faculty, Class, Research
from flask import Flask, request
app = Flask(__name__)
db_filename = 'todo.db'
#Class.students.append(user)
app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///%s' % db_filename
app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False
app.config['SQLALCHEMY_ECHO'] = T... | null | app.py | app.py | py | 4,316 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "flask.Flask",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "db.db.init_app",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "db.db",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "db.db.create_all",
"line_number":... |
214237525 | #-*- coding: utf-8 -*-
import os
import pickle
import maya.cmds as rig
import maya.OpenMaya as om
import maya.OpenMayaAnim as omAnim
from RIG.simulation.simulationMain import SM_warning
from RIG.commonly.base import SK_getSkinCluster
from RIG.tools.IOWeights.IOgetOptionUI import SK_IOgetOptionUI
def IO_newFile(allPoly... | null | OLD/COMMON/set/RIG/tools/IOWeights/IOFile.py | IOFile.py | py | 4,891 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "maya.cmds.fileDialog",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "maya.cmds",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "maya.cmds.ls",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "maya.cmds",
"line_num... |
368279820 | import numpy as np
from numpy.linalg import pinv
from ex2c import X_train, X_cv, X_test, Y_train, Y_cv, Y_test
import matplotlib
matplotlib.use('Qt4Agg')
import matplotlib.pyplot as plt
train_errors = []
num_train_errors = []
cv_errors = []
num_cv_errors = []
reg_parameters = [
0.00001,
0.00003,
0.0001... | null | list_2/ex2d.py | ex2d.py | py | 3,810 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "matplotlib.use",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "numpy.random.rand",
"line_number": 41,
"usage_type": "call"
},
{
"api_name": "numpy.random",
"line_number": 41,
"usage_type": "attribute"
},
{
"api_name": "numpy.exp",
"li... |
482261541 | # coding: utf-8
# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------... | null | sdk/formrecognizer/azure-ai-formrecognizer/samples/v3.2_and_later/sample_compose_model.py | sample_compose_model.py | py | 6,031 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.environ",
"line_number": 49,
"usage_type": "attribute"
},
{
"api_name": "os.environ",
"line_number": 50,
"usage_type": "attribute"
},
{
"api_name": "os.environ",
"line_number": 51,
"usage_type": "attribute"
},
{
"api_name": "os.environ",
"lin... |
452918870 | """Display a graph of the corona virus spread"""
import pandas as pd
import plotly.graph_objs as go
URL = (f"https://docs.google.com/"
f"spreadsheets/d/18X1VM1671d99V_yd-cnUI1j8oSG2ZgfU_q1HfOizErA/"
f"export?format=csv&id")
class CoronaVirusGrapher():
"""
Visualize cases of the corona virus
... | null | main.py | main.py | py | 5,275 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "pandas.read_csv",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "plotly.graph_objs.Figure",
"line_number": 64,
"usage_type": "call"
},
{
"api_name": "plotly.graph_objs",
"line_number": 64,
"usage_type": "name"
},
{
"api_name": "plotly.gra... |
371644456 | #!/usr/bin/env python
# encoding: utf-8
import redis
import sys
import os
sys.path.append(os.getcwd())
from sina.settings import LOCAL_REDIS_HOST, LOCAL_REDIS_PORT, PROXY_BASEURL
import urllib.parse
from sina.spiders.utils import get_random_proxy
r = redis.Redis(host=LOCAL_REDIS_HOST, port=LOCAL_REDIS_PORT)
#delete... | null | crawl_search/sina/redis_init.py | redis_init.py | py | 1,366 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "sys.path.append",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "os.getcwd",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "redis.Redis",
"line_number":... |
409999360 | import numpy as np
import networkx as nx
from networkx import is_strongly_connected, is_strongly_connected_dev
from garageofcode.common import benchmarking
from garageofcode.probing.utils import get_random_graph
def is_strongly_connected_v001(G):
N = len(G)
u = next(iter(G))
#return len(reachable_from(G,... | null | garageofcode/networkx/networkx_scc.py | networkx_scc.py | py | 2,235 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "networkx.descendants",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "networkx.ancestors",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "numpy.random.seed",
"line_number": 36,
"usage_type": "call"
},
{
"api_name": "numpy.rando... |
68470369 | from flask import Flask
# StatsD: https://statsd.readthedocs.io/en/v3.2.1/timing.html
from statsd import StatsClient
import time
import random
app = Flask(__name__)
statsd = StatsClient(host='localhost',
port=8126,
prefix='services',
maxudpsize=512)
@app.... | null | python3.8/app/main.py | main.py | py | 624 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "flask.Flask",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "statsd.StatsClient",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "time.sleep",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "random.uniform",
"line_nu... |
111099353 | import numpy as np
from modules.entity import Entity
from modules.ray import Ray
from utils import normalize
class Sphere(Entity):
def __init__(self, params, materials):
super().__init__(params, materials)
self.center = np.array(params[0:3], dtype=float)
self.radius = float(params[3])
... | null | modules/sphere.py | sphere.py | py | 1,090 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "modules.entity.Entity",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "numpy.array",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "numpy.sum",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "numpy.full",
"line_num... |
304992800 | from django.urls import path
from . import views
urlpatterns = [
path('', views.index_view, name="home_view"),
path('register/', views.register_view, name="register_view"),
path('login/', views.login_view, name="login_view"),
path('profile/', views.profile_view, name="profile_view"),
path('log-out/... | null | login_reg_proj/login_reg_app/urls.py | urls.py | py | 519 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.urls.path",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
... |
77563310 | from django.core.management.base import BaseCommand, CommandError
from django.core.management import call_command
from django.conf import settings
ECOMMERCE_FIXTURES = [
'categories.json',
'products.json',
]
class Command(BaseCommand):
def handle(self, *args, **options):
for fixture in ECOMMERCE_... | null | ecommerce_projec/ecommerce/management/commands/eccomerce_fixtures.py | eccomerce_fixtures.py | py | 542 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.core.management.base.BaseCommand",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "django.core.management.call_command",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "django.conf.settings.DJANGO_ROOT",
"line_number": 15,
"usage_... |
585718932 | # univariate multi-step lstm
from math import sqrt
import numpy
import pandas as pd
from numpy import array
from pandas import read_csv
from pandas import DataFrame
from pandas import concat
from sklearn.metrics import mean_absolute_error
from sklearn.metrics import mean_squared_error
from matplotlib import pyplot
fro... | null | time-serials/LSTM_Attention_multi2one.py | LSTM_Attention_multi2one.py | py | 6,962 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "pandas.DataFrame",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "pandas.concat",
"line_number": 35,
"usage_type": "call"
},
{
"api_name": "keras.models.Sequential",
"line_number": 47,
"usage_type": "call"
},
{
"api_name": "keras.layers.L... |
1485268 | """
Author: Rehman Ali RA
dated=25 auguest 2020
A Program which gives covid 19 notifiction
"""
from plyer import notification # module for notifiction
import requests
from bs4 import BeautifulSoup # beautify all the html data
import time
def notif_me(title,message): # notifiction function which igave notif... | null | Covid out break notifiction Project.py | Covid out break notifiction Project.py | py | 1,899 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "plyer.notification.notify",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "plyer.notification",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "requests.get",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "bs4.Beautif... |
548932499 | import datetime
import os
import pickle
import re
from typing import Union, List
from .. import params
from .. import util, settings
from ..api.defaultclient import DefaultAPIClient, DefaultAPIUser
from ..exceptions import ReqException, LoginError, APIUserError
__all__ = ['WebAPIClient']
class BaseClient:
_logi... | null | pikax/api/webclient.py | webclient.py | py | 13,841 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "exceptions.ReqException",
"line_number": 26,
"usage_type": "name"
},
{
"api_name": "os.path.isfile",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 32,
"usage_type": "attribute"
},
{
"api_name": "pickle.dump",
... |
487378033 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Mar 10 09:56:11 2021
"""
import json
from Lookup import LookupTable
# Load periodic table info from file
table_path = "Put json file path here"
with open(table_path, 'r') as data:
periodic_table = json.load(data)
table = LookupTable(periodic_table... | null | main.py | main.py | py | 1,137 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "json.load",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "Lookup.LookupTable",
"line_number": 15,
"usage_type": "call"
}
] |
65099084 | #airlines sentiment anaysis
#Importing libraries
import pandas as pd
import numpy as np
import matplotlib.pyplot as pt
import re
from html.parser import HTMLParser
from nltk.corpus import stopwords
#from nltk.stem.porter import PorterStemmer
from nltk.stem.wordnet import WordNetLemmatizer
import string
from nltk import... | null | airlines_sentiment_anlyse.py | airlines_sentiment_anlyse.py | py | 6,451 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "pandas.read_csv",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "html.parser.HTMLParser",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "re.compile",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "re.DOTALL",
"li... |
371162937 | # -*- coding: utf-8 -*-
__author__ = 'wangli'
__date__ = '2020-02-10 16:12'
# 导入相关扩展类库
from flask_bootstrap import Bootstrap
# 邮件
from flask_mail import Mail
# 时间
from flask_moment import Moment
# 数据库
from flask_sqlalchemy import SQLAlchemy
# 登录
from flask_login import LoginManager
# 上传文件
from flask_uploads import Up... | null | app/extensions.py | extensions.py | py | 1,395 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "flask_bootstrap.Bootstrap",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "flask_mail.Mail",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "flask_moment.Moment",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "flask_s... |
635653304 | import argparse
import json
import logging
import os
import random
from io import open
import numpy as np
from tensorboardX import SummaryWriter
from tqdm import tqdm
from bisect import bisect
import yaml
from easydict import EasyDict as edict
import pdb
import sys
import torch
import torch.nn.functional as F
import ... | null | train_cider.py | train_cider.py | py | 15,155 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "numpy.random.seed",
"line_number": 41,
"usage_type": "call"
},
{
"api_name": "numpy.random",
"line_number": 41,
"usage_type": "attribute"
},
{
"api_name": "torch.manual_seed",
"line_number": 42,
"usage_type": "call"
},
{
"api_name": "torch.cuda.manu... |
497969526 | # -*- coding: utf-8 -*-
import paddle
class Merger(paddle.nn.Layer):
def __init__(self, cfg):
super(Merger, self).__init__()
self.cfg = cfg
# Layer Definition
self.layer1 = paddle.nn.Sequential(
paddle.nn.Conv3D(9, 16, kernel_size=3, padding=1, weight_attr=paddle.nn.i... | null | Pix2Vox-F/models/merger.py | merger.py | py | 3,958 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "paddle.nn",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "paddle.nn.Sequential",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "paddle.nn",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "paddle.nn.Conv3D",
... |
494668208 | '''
The exercises and classes are configured in json/yaml.
Each directory inside exercises/ holding an index.json/yaml is a course.
'''
from django.conf import settings
import os, time, json, yaml, re
import logging
import copy
from util.dict import iterate_kvp_with_dfs, get_rst_as_html
from util.importer import impor... | null | access/config.py | config.py | py | 14,312 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.path.join",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "django.conf.settings.BASE_DIR",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "django.c... |
391547726 | """
@Description: This python collects data from YouTube Videos
@ such as views, likes, dislikes, etc
@
@Author: Ken Zeng
"""
import requests
from lxml import html
from datetime import datetime
import csv
class Collector(object):
"""
A collector that takes a list of url... | null | collector.py | collector.py | py | 7,941 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "datetime.datetime.now",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 26,
"usage_type": "name"
},
{
"api_name": "requests.get",
"line_number": 90,
"usage_type": "call"
},
{
"api_name": "lxml.html.fromst... |
108506728 | import numpy as np
import cv2
img = cv2.imread('/home/meghnadixit38/Pictures/tiger.jpg',0)
cv2.imshow('image',img)
k = cv2.waitKey(0)
if k == 27:
cv2.destroyAllWindows()
elif k == ord('s'):
cv2.imwrite('tigergray.jpg',img)
cv2.destroyAllWindows()
| null | OpenCV/Assignment_1.1.py | Assignment_1.1.py | py | 271 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "cv2.imread",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "cv2.imshow",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "cv2.waitKey",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "cv2.destroyAllWindows",
"line_numb... |
601633915 | import multiprocessing
from abc import ABCMeta, abstractmethod
from multiprocessing import Process
from typing import Dict, List
from datetime import datetime
from ...base_crawler import BaseCrawler
from ..api import TWEEPY_API
class KeywordCrawler(BaseCrawler):
def __init__(
self,
keywords: Lis... | null | fin_app/crawler/twitter/singleshot/tweepy_keyword_crawler.py | tweepy_keyword_crawler.py | py | 3,365 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "base_crawler.BaseCrawler",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "typing.List",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "multiprocessing.cpu_count",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "typing... |
616097075 | from urllib.request import urlretrieve
import os
import zipfile
if __name__ == '__main__':
os.system('sudo apt install python3-pip')
os.system('sudo -H pip3 install selenium')
urlretrieve('https://chromedriver.storage.googleapis.com/2.35/chromedriver_linux64.zip', 'chromedriver_linux64.zip')
zip_ref =... | null | setup.py | setup.py | py | 649 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.system",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "os.system",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "urllib.request.urlretrieve",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "zipfile.ZipFile",
"li... |
403732331 | import matplotlib.pyplot as plt
import numpy as np
cupcakes = open('CupcakeInvoices.csv')
print("---------------PROBLEM 3---------------")
# print(cupcakes)
# for line in cupcakes:
# print(line)
print("---------------PROBLEM 4---------------")
# for flavor in cupcakes:
# flavor = flavor.strip('\r\n').split(',... | null | Labs/data-python-lab/data_presenter.py | data_presenter.py | py | 2,143 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "matplotlib.pyplot.bar",
"line_number": 67,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 67,
"usage_type": "name"
},
{
"api_name": "matplotlib.pyplot.xlabel",
"line_number": 70,
"usage_type": "call"
},
{
"api_name": "matp... |
292234049 | import boto3
import json
import os
# configurations from file
config_filename = "_src/configs.json"
if os.path.isfile(config_filename):
with open(config_filename) as f:
all_configs = json.loads(f.read())
environment = all_configs['environment'] if 'environment' in all_configs.keys() else "dev"
region = all... | null | work/insta-spike/FeedBearBot/create_kms_key.py | create_kms_key.py | py | 3,037 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.path.isfile",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "json.loads",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "boto3.client",
"line_number":... |
360290964 | #! /usr/bin/env python
import Tkinter as tk
import tkFileDialog
from datetime import datetime
import os
class ConvertMe(object):
"""Docstring"""
buttonfont = ("Arial", 10)
def __init__(self, master):
self.master = master
# frame which will contain buttons and entry field
self.t... | null | ConvertMe/convertme.py | convertme.py | py | 8,891 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "Tkinter.Frame",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "Tkinter.Frame",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "Tkinter.Button",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "Tkinter.Button",
"line... |
429321530 | import scrapy
from spiders.items import SpidersItem
class MoviewSpider(scrapy.Spider):
name = 'moview'
allowed_domains = ['https://maoyan.com/']
start_urls = ['https://maoyan.com/films?showType=3']
def parse(self, response):
moview = SpidersItem()
dl = response.xpath('//div[@class="mo... | null | week01/work2/spiders/spiders/spiders/moview.py | moview.py | py | 786 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "scrapy.Spider",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "spiders.items.SpidersItem",
"line_number": 11,
"usage_type": "call"
}
] |
45175480 | import pickle
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.utils import shuffle
from datetime import datetime
from sortedcontainers import SortedList
with open('user2movie.json','rb') as f:
user2movie = pickle.load(f)
with open('movie2user.json','rb') as f:
movie2user = ... | null | usercollab.py | usercollab.py | py | 4,117 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "pickle.load",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "pickle.load",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "pickle.load",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "pickle.load",
"line_number": ... |
383170368 | # this is the ellipse bluff body grid generator script
# developed by ramkumar
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from copy import copy as cp
# geometric parameters
a1 = 0.2
b1 = 0.1
a2 = 1.0
b2 = 0.5
nx = 101
ny = 51
theta1 = 3*np.pi/2.0
theta2 = np.pi/2.0
# computing the mes... | null | fortran/bluff_body/old_files/geometry_codes/ellipse_creator.py | ellipse_creator.py | py | 1,207 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "numpy.pi",
"line_number": 19,
"usage_type": "attribute"
},
{
"api_name": "numpy.pi",
"line_number": 20,
"usage_type": "attribute"
},
{
"api_name": "numpy.sqrt",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "numpy.sqrt",
"line_number"... |
115380059 | #!/usr/bin/env python3
from elasticsearch import Elasticsearch
from elasticsearch import helpers
from elasticsearch.connection import create_ssl_context
from error import send_jira_event, send_ms_teams_message
import ssl
from itertools import islice
import sys
import os
import re
import json
from config impo... | null | es.py | es.py | py | 24,103 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "urllib3.disable_warnings",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "urllib3.exceptions",
"line_number": 16,
"usage_type": "attribute"
},
{
"api_name": "re.search",
"line_number": 98,
"usage_type": "call"
},
{
"api_name": "re.search"... |
432371789 | # -*- coding: utf-8 -*-
import os.path
import tornado.escape
import tornado.httpserver
import tornado.ioloop
import tornado.options
import tornado.web
import markdown
from tornado.options import define, options
from django_settings import *
import re
import unicodedata
import markdown
define("port", default=8888, help... | null | tornado_app/server.py | server.py | py | 5,311 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "tornado.options.define",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "tornado.escape.web",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "tornado.escape",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "os.path... |
30837663 | # -*- coding: utf8 -*-
import sys, os
import time
import datetime
import json
import configparser
import threading
import psycopg2
import psycopg2.extras
sys.path.append('C:\\Python34\\mysite\\tcb_bank_gate_way\\')
import FXDP
import FXSE
#path = "C:\\Python34\\mysite\\tcb_bank_gate_way\\"
path = ""
#程式執行時間序log
def wr... | null | tcb_bank_gw.py | tcb_bank_gw.py | py | 8,256 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "sys.path.append",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "os.path.isdir",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_numbe... |
383983000 | # -*- coding: utf-8 -*-
"""
Created on Tue Nov 24 16:28:49 2020
@author: user
"""
import librosa
import matplotlib.pyplot as plt
import numpy as np
y , sr = librosa.load( 'audio_files/ah_2.wav' , 44100 )
# plt.plot( np.arange(y.size) , y )
# select a window size
w_size = 2048
# take a segment number of samples a ... | null | dsp_meeting_0.py | dsp_meeting_0.py | py | 750 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "librosa.load",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "numpy.fft.fft",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "numpy.fft",
"line_number": 25,
"usage_type": "attribute"
},
{
"api_name": "numpy.sqrt",
"line_numb... |
174940863 | import logging
import collections
import datetime
from google.appengine.ext import ndb
from consts.event_type import EventType
from models.event import Event
from models.match import Match
from models.team import Team
CHAMPIONSHIP_EVENTS = set(['arc', 'cur', 'gal', 'new', 'ein', 'cmp'])
CHAMPIONSHIP_EVENTS_LABEL = ... | null | helpers/event_helper.py | event_helper.py | py | 6,620 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "collections.OrderedDict",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "datetime.timedelta",
"line_number": 50,
"usage_type": "call"
},
{
"api_name": "datetime.timedelta",
"line_number": 52,
"usage_type": "call"
},
{
"api_name": "datetim... |
233811846 | import logging
from linebot.models import (
TextMessage, ImageMessage, VideoMessage, AudioMessage, LocationMessage, StickerMessage, FileMessage
)
from flags import MessageType
from extline import LINE, ExtraKey, event_dest_fmt
from ..error import handle_error
from .text import handle_text
from .image import handl... | null | extline/handler/message/main.py | main.py | py | 1,789 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "flags.MessageType.UNKNOWN",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "flags.MessageType",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "flags.MessageType.TEXT",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_... |
525924555 | import io
import cv2
from splitWavProcess import *
def get_img_from_fig(fig, dpi=100):
buf = io.BytesIO()
fig.savefig(buf, format="png", dpi=dpi)
buf.seek(0)
img_arr = np.frombuffer(buf.getvalue(), dtype=np.uint8)
buf.close()
img = cv2.imdecode(img_arr, 1)
img = cv2.cvtColor(img, cv2.COLOR_... | null | 2-Preprocessing/preProcessing.py | preProcessing.py | py | 3,064 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "io.BytesIO",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "cv2.imdecode",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "cv2.cvtColor",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "cv2.COLOR_BGR2RGB",
"line_num... |
302475870 | from queue import Queue
from collections import defaultdict
class Node:
def __init__(self, i, connects):
self.i = i
self.colour = None
self.connects = connects
def inject_intersections(self, inter):
self.inter = inter
def get_neigh_colours(self):
cols = set()
... | null | basincity.py | basincity.py | py | 1,585 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "queue.Queue",
"line_number": 39,
"usage_type": "call"
},
{
"api_name": "collections.defaultdict",
"line_number": 41,
"usage_type": "call"
}
] |
305699815 | import meshio
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.animation as animation
mesh = meshio.read("circle-2d-drag_1000.vtu")
cells=mesh.cells_dict
pointData=mesh.point_data
Velocity=pointData['Pressure']
points=mesh.points
data=points[:,[0,1]]
plt.figure(1)
a=plt.scatter(data[:,0],data... | null | 2. interpolating on structured grid (worked)/extract.py | extract.py | py | 1,093 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "meshio.read",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.figure",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "matplotlib.pypl... |
577838647 | import torch
from IPython import display
import matplotlib.pyplot as plt
import torchvision
from torchvision import transforms
from torch.utils import data
def synthetic_data(w, b, num_examples): #@save
"""Generate y = Xw + b + noise."""
X = torch.normal(0, 1, (num_examples, len(w)))
y = torch.matmul(X, w... | null | torch/Chapter3/func.py | func.py | py | 7,087 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "torch.normal",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "torch.matmul",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "torch.normal",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "torch.reshape",
"line_numb... |
269591779 | #!/usr/bin/env python3
import datetime
from click import prompt
from jinja2 import Template
from mena import mena_kc
from ares import firma_info
parameter_sablony = dict()
today = datetime.date.today()
print("Odběratel", "=" * 80)
parameter_sablony["odberatel"] = firma_info(prompt("IČ"))
print("Faktura", "=" * 80)
... | null | faktura.py | faktura.py | py | 2,087 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "datetime.date.today",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "datetime.date",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "ares.firma_info",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "click.prompt",... |
244794242 | #!/usr/bin/env python3
import os
from setuptools import setup, find_packages
import sys
sys.path.append(os.getcwd())
import build_cffi
def add_pkg_data_dirs(pkg, dirs):
pkg_data = []
for d in dirs:
for root, _, files in os.walk(os.path.join(pkg, d)):
r = os.path.relpath(root, pkg)
pkg_data.extend([os.path.j... | null | setup.py | setup.py | py | 1,002 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "sys.path.append",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "os.getcwd",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "os.walk",
"line_number": 12,... |
608590408 | import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
row_labels = ['Self', 'Other', 'News', 'Irrelevant', 'Other Relevant']
column_labels = ['7/13/14', '7/20/14', '7/27/14', '8/3/14', '8/10/14', '8/17/14', '8/24/14', '8/31/14', '9/7/14', '9/14/14', '9/21/14', '9/28/12', '10/5/14', '10/12/14', '10/19... | null | heatmap.py | heatmap.py | py | 903 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "pandas.read_csv",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.subplots",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "matplotli... |
77817499 | from django.urls import path
from . import views
urlpatterns = [
#### following followers 목록
# path('follows/<username>/',views.follows),
#### 회원등급을 올려주는 거 (admin 계정만 올수 있다.)
path('grade/<username>/',views.grade),
#### 해당 회원의 좋아하는 게시글들 ####
path('like_article/<username>/',views.like_article),
... | null | last_pjt/backend/accounts/urls.py | urls.py | py | 810 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.urls.path",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
... |
356586096 | import http.client as http_client
import datetime
from drift.test_helpers.systesthelper import uuid_string
from driftbase.systesthelper import DriftBaseTestCase
from tests import has_key
from unittest import mock
class UserIdentitiesTest(DriftBaseTestCase):
def test_identities_missing_user(self):
# authen... | null | tests/test_useridentities.py | test_useridentities.py | py | 8,457 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "driftbase.systesthelper.DriftBaseTestCase",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "drift.test_helpers.systesthelper.uuid_string",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "drift.test_helpers.systesthelper.uuid_string",
"line_nu... |
118738954 | """
896. Monotonic Array
====================
Easy
An array is monotonic if it is either monotone increasing or monotone
decreasing.
An array A is monotone increasing if for all i <= j, A[i] <= A[j]. An array A
is monotone decreasing if for all i <= j, A[i] >= A[j].
Return true if and only if the given array A is... | null | src/arr/monotonic_array.py | monotonic_array.py | py | 1,254 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "typing.List",
"line_number": 58,
"usage_type": "name"
},
{
"api_name": "src.decorator.decorator.register",
"line_number": 57,
"usage_type": "call"
},
{
"api_name": "typing.List",
"line_number": 76,
"usage_type": "name"
},
{
"api_name": "src.decorato... |
485362978 | # Version March 15, 2018
# Created by Dan Reichert at Sumo Logic
from newrelic_api import Applications
from datetime import datetime, timedelta
import sys
import json
import time
import requests
time_pattern='%Y-%m-%dT%H:%M:%S+00:00'
configfilename='newrelic.conf'
if len(sys.argv) > 1:
configfilename=sys.argv[... | null | NewRelic/NewRelicAPMToSumo/newrelictosumo.py | newrelictosumo.py | py | 2,707 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "sys.argv",
"line_number": 16,
"usage_type": "attribute"
},
{
"api_name": "sys.argv",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "newrelic_api.Applications",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "time.time",
... |
447749034 | from django.conf.urls import patterns, include, url
from django.contrib import admin
from django.contrib.auth.views import login, logout
from django.views.generic.base import RedirectView
urlpatterns = patterns('',
url( r'^admin/', include( admin.site.urls ) ),
# URLS de sistema de login
url( r'^$' ,... | null | canto/canto/urls.py | urls.py | py | 1,405 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.conf.urls.patterns",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "django.conf.urls.url",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "django.conf.urls.include",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "... |
501321743 | # coding:UTF-8
from sklearn import datasets
from sklearn import svm
# Irisの測定データの読み込み
iris = datasets.load_iris()
# データの形式を確認
# print(iris.data)
# print(iris.data.shape)
# データの数
n = len(iris.data)
# 線形サポートベクターマシン
clf = svm.LinearSVC()
# サポートベクターマシンによる訓練
clf.fit(iris.data, iris.target)
# 品種を判定する
print(clf.predict... | null | scikit-learn/practice.py | practice.py | py | 511 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "sklearn.datasets.load_iris",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "sklearn.datasets",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "sklearn.svm.LinearSVC",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "sklea... |
174847067 | import logging
from django.http import HttpResponse
from uuid import uuid4
import requests
from django.contrib import auth, messages
from django.contrib.auth.decorators import login_required
from django.db import transaction
from django.http import HttpResponseForbidden
from django.shortcuts import get_object_or_404,... | null | saleor/order/views.py | views.py | py | 12,991 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "logging.getLogger",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "django.views.generic.detail.DetailView",
"line_number": 39,
"usage_type": "name"
},
{
"api_name": "models.Order",
"line_number": 40,
"usage_type": "name"
},
{
"api_name": ... |
125202541 | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import csv
import datetime
from collections import defaultdict
import numpy as np
import torch
import torchvision
from te... | null | third_party/drqv2/logger.py | logger.py | py | 6,044 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "collections.defaultdict",
"line_number": 44,
"usage_type": "call"
},
{
"api_name": "csv.DictReader",
"line_number": 65,
"usage_type": "call"
},
{
"api_name": "csv.DictWriter",
"line_number": 74,
"usage_type": "call"
},
{
"api_name": "csv.DictWriter"... |
45295598 | #use: make aug folder with 2 subfolders named images and xmls.
# edit images path: line 134
# edit anotations files path: 137
# edit line 158 : range(5)--- how many images do you need from each image?
import os
import numpy as np
import cv2
import glob
import xml.etree.ElementTree as ET
from xml.dom import minidom
... | null | Python-Projects/codes/augmentations_with_bbox.py | augmentations_with_bbox.py | py | 5,204 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "cv2.imread",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "xml.etree.ElementTree.split",
"line_number": 38,
"usage_type": "call"
},
{
"api_name": "xml.etree.ElementTree",
"line_number": 38,
"usage_type": "name"
},
{
"api_name": "xml.etre... |
114681790 | #! /usr/bin/env python
'''
File:
espa-framework.py
Purpose:
Implements a Mesos Framework for processing data through ESPA.
License:
NASA Open Source Agreement 1.3
'''
import os
import sys
import json
import uuid
import copy
import logging
import signal
from argparse import ArgumentParser
from threading... | null | espa-framework/espa-framework.py | espa-framework.py | py | 27,990 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "logging.Filter",
"line_number": 42,
"usage_type": "attribute"
},
{
"api_name": "logging.Formatter",
"line_number": 55,
"usage_type": "attribute"
},
{
"api_name": "logging.INFO",
"line_number": 90,
"usage_type": "attribute"
},
{
"api_name": "logging.... |
315629031 | __author__ = 'leonardo'
from scrapy.http import Request
from alascrapy.spiders.base_spiders.bazaarvoice_spider import BazaarVoiceSpider
from alascrapy.items import CategoryItem, ProductIdItem
from alascrapy.lib.generic import get_full_url
class JohnLewisSpider(BazaarVoiceSpider):
name = 'johnlewis'
start_url... | null | alascrapy/spiders/johnlewis.py | johnlewis.py | py | 6,379 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "alascrapy.spiders.base_spiders.bazaarvoice_spider.BazaarVoiceSpider",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "alascrapy.lib.generic.get_full_url",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "scrapy.http.Request",
"line_number": 31... |
640074513 | from flask import Flask, redirect, url_for, render_template, request, make_response
import datetime
import os
import json
import pandas as pd
import matplotlib
# Path for test image
photo_folder = os.path.join('static')
full_filename = os.path.join(photo_folder, 'sample.png')
app = Flask(__name__)
app.config["CACHE... | null | simple_session.py | simple_session.py | py | 4,752 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.path.join",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 1... |
616330523 | # https://archive.ics.uci.edu/ml/index.php
import tensorflow as tf
import pandas as pd
import numpy as np
from sklearn import preprocessing, model_selection
import collections
# 문제
# wdbc 데이터에 대해 70%로 학습하고 30%에 대해 정확도를 구하세요
def get_data():
# 1. Sample code number id number
# 2. Clump Thicknes... | null | Keras - DeepLearning/9. KerasBreastCancer.py | 9. KerasBreastCancer.py | py | 5,850 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "pandas.read_csv",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "numpy.newaxis",
"line_number": 65,
"usage_type": "attribute"
},
{
"api_name": "numpy.hstack",
"line_number": 71,
"usage_type": "call"
},
{
"api_name": "numpy.float32",
"... |
39993877 | from django.urls import path
from . import views
app_name = 'todo'
urlpatterns = [
path('', views.index, name='index'),
path('new-task/', views.new_task, name='new_task'),
path('complete-task/', views.complete_task, name='complete_task'),
] | null | Assignments/pete/django/django-vue/todo/django/todo/urls.py | urls.py | py | 255 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.urls.path",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
"line_number": 10,
"usage_type": "call"
}
] |
407565638 | import datetime
import os
import sys
import xbmc
import xbmcaddon
__addon__ = xbmcaddon.Addon()
__addondir__ = xbmc.translatePath(__addon__.getAddonInfo('profile'))
__cwd__ = __addon__.getAddonInfo('path')
__resource__ = xbmc.translatePath(os.path.join(__cwd__, 'resources', 'lib'))
sys.path.append(__resource__)
fro... | null | default.py | default.py | py | 12,738 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "xbmcaddon.Addon",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "xbmc.translatePath",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "xbmc.translatePath",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "os.path.join",
... |
159439670 | from django.conf.urls.defaults import *
from django.contrib.auth.decorators import login_required
from django.views.generic.date_based import archive_year, archive_month
from mousedb.animal.models import Animal
@login_required
def limited_archive_year(*args, **kwargs):
return archive_year(*args, **kwargs)
@login_re... | null | src/mousedb/animal/urls/date.py | date.py | py | 927 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.views.generic.date_based.archive_year",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "django.contrib.auth.decorators.login_required",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "django.views.generic.date_based.archive_month",
"lin... |
195318071 | # -*- coding: utf-8 -*-
import pymysql
class MysqlDb():
def __init__(self):
conn = pymysql.connect(
host="47.244.242.187",
port=3306,
user="lilei",
passwd="BLkj_123123",
db="amazondb",
charset='utf8mb4',
cursorclass=pymysq... | null | mysql_utils/mysql_db.py | mysql_db.py | py | 1,381 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "pymysql.connect",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "pymysql.cursors",
"line_number": 14,
"usage_type": "attribute"
}
] |
519632341 | '''
NOTE: USE IN A CONTEXT MANAGER!!!
There seems to be an issue with webdriver.quit() being called
when the program is ending. So this class is intended to be used
in a context manager instead to ensure that the webdriver is always
properly closed without issue.
NOTE: It's quite possible that either the web... | null | fire_eye/scraper/scraper.py | scraper.py | py | 5,558 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.path.join",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 34,
"usage_type": "attribute"
},
{
"api_name": "os.path.dirname",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "os.path.isfile",
"line_... |
409028775 | import os,shutil,smtplib
from email.mime.base import MIMEBase
from email.mime.multipart import MIMEMultipart
from mimetypes import guess_type
from email.encoders import encode_base64
from email.mime.text import MIMEText
name = os.getenv('username')
path = "C:/Users/"+name+"/AppData/Local/Google/Chrome/User Data/... | null | CS-Chrome-Password-Stealer.py | CS-Chrome-Password-Stealer.py | py | 1,270 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.getenv",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "os.mkdir",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "shutil.copy",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "os.chdir",
"line_number": 13,
"... |
371731470 | from django.contrib.auth.backends import ModelBackend
from django.http import Http404
from .models import UserComponent, Protection, TravelProtection
from .constants import ProtectionType, TravelLoginType
class SpiderAuthBackend(ModelBackend):
def authenticate(self, request, username=None,
... | null | spkcspider/apps/spider/auth.py | auth.py | py | 2,476 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.contrib.auth.backends.ModelBackend",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "models.TravelProtection.objects.get_active",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "models.TravelProtection.objects",
"line_number": 17,
... |
263165511 | from collections import defaultdict, Counter
from contextlib import suppress
from functools import lru_cache
from itertools import islice, cycle, groupby, product
from types import SimpleNamespace
from typing import List, NamedTuple, Tuple, Dict, Optional, Callable, Iterable, Set, Union, Any
from PIL import Image
fro... | null | lifxlan3/routines/tile/tile_utils.py | tile_utils.py | py | 16,188 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "lifxlan3.init_log",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "lifxlan3.Colors.OFF",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "lifxlan3.Colors",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "typing.Tup... |
625000243 | import numpy as np
import cv2
k = 2
win_size = 52
color=cv2.imread("lips2.jpg",1)
height,width,channels=color.shape
color = cv2.resize(color, (int(width/k), int(height/k)))
height,width,channels=color.shape
h_z = height+win_size
gray = cv2.cvtColor(color,cv2.COLOR_BGR2GRAY)
cv2.imshow("Image",gray)
cv2.moveWindo... | null | lips_px_gray.py | lips_px_gray.py | py | 521 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "cv2.imread",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "cv2.resize",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "cv2.cvtColor",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "cv2.COLOR_BGR2GRAY",
"line_numb... |
103520206 | import numpy as np
from skimage.measure import compare_psnr as psnr
from skimage.measure import compare_ssim as ssim
def calc_metrics(out, y):
# swap axes, move to cpu, break gradient and cast to numpy array for metric calculation
y = np.moveaxis(y.cpu().detach().numpy(), 1, -1)
out = np.moveaxis(out.cpu(... | null | utils/.ipynb_checkpoints/metrics-checkpoint.py | metrics-checkpoint.py | py | 598 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "numpy.moveaxis",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "numpy.moveaxis",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "skimage.measure.compare_ssim",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "skimage.meas... |
509123770 | import argparse
from functools import cmp_to_key
def my_cmp(a, b):
if len(a[0]) != len(b[0]):
return len(a[0]) - len(b[0])
for i in range(len(a[0])):
if a[0][i] != b[0][i]:
return a[0][i] - b[0][i]
def n_round(v):
return int(v * 10000 + 0.50000001) / 10000.
if __name__ == '__m... | null | Assignment-2/tools/spmf2hw_out.py | spmf2hw_out.py | py | 1,197 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "functools.cmp_to_key",
"line_number": 25,
"usage_type": "call"
}
] |
17350370 | from bs4 import BeautifulSoup
import re
from nltk.corpus import stopwords
import nltk.data
import numpy as np
from wordcloud import WordCloud
from matplotlib import pyplot as plt
class preprocessing():
sent_detector = nltk.data.load('tokenizers/punkt/english.pickle')
def return_averaged_vector_review(sel... | null | MasterProject/data_Preprocessing/Datasets/preprocessing.py | preprocessing.py | py | 2,918 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "nltk.corpus.data.load",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "nltk.corpus.data",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "nltk.corpus",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "numpy.zeros",... |
481062983 | # -*- coding: utf-8 -*-
"""
Doctor Daily
Created: 7 Dec 2019
Last up: 8 Dec 2019
"""
from __future__ import print_function
#import collections
from openerp import models, fields, api
from openerp.addons.openhealth.models.order import ord_vars
import datetime
class DoctorDaily(models.Model):
"""
For ... | null | models/management/doctor_daily/doctor_daily.py | doctor_daily.py | py | 3,732 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "openerp.models.Model",
"line_number": 19,
"usage_type": "attribute"
},
{
"api_name": "openerp.models",
"line_number": 19,
"usage_type": "name"
},
{
"api_name": "openerp.fields.Many2one",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "open... |
295173676 | import random
import json
def getopts(argv):
opts = {}
while argv:
if argv[0][0] == '-':
opts[argv[0]] = argv[1]
argv = argv[1:]
return opts
if __name__ == '__main__':
from sys import argv
myargs = getopts(argv)
from time import sleep
#sleep(100)
results = {"i": myargs['--i']... | null | code/MLAPI/Scripts/train.py | train.py | py | 462 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "sys.argv",
"line_number": 13,
"usage_type": "argument"
},
{
"api_name": "random.random",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "json.dumps",
"line_number": 17,
"usage_type": "call"
}
] |
549800552 | import os
import tempfile
from collections import OrderedDict
from pathlib import Path
import pytest
import xncml
here = os.path.abspath(os.path.dirname(__file__))
input_file = os.path.join(here, 'exercise1.ncml')
def test_ncml_dataset_constructor():
nc = xncml.Dataset(input_file)
expected = OrderedDict(
... | null | tests/test_core.py | test_core.py | py | 7,472 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.path.abspath",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "os.path.dirname",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line... |
273515467 | # from ansible import utils
# import ansible.constants as C
# import ansible.utils.template as template
# from ansible import errors
# from ansible.runner.return_data import ReturnData
from ansible.errors import AnsibleError, AnsibleAction, _AnsibleActionDone
import os
import tempfile
from ansible.plugins.action imp... | null | action_plugins/jcliff.py | jcliff.py | py | 3,201 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "ansible.plugins.action.ActionBase",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "tempfile.NamedTemporaryFile",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "os.environ",
"line_number": 29,
"usage_type": "attribute"
},
{
"api... |
336414347 | #!/usr/bin/python
################################################################################
# NASTRAN BOOTSTRAP SCRIPT
# D. Everhart
# 10 FEB 2016
################################################################################
# The MIT License (MIT)
#
# Copyright (c) 2016 Daniel Everhart
#
# Permission is he... | null | sbin/nastran.py | nastran.py | py | 8,758 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.path.path.abspath",
"line_number": 46,
"usage_type": "call"
},
{
"api_name": "os.path.path",
"line_number": 46,
"usage_type": "attribute"
},
{
"api_name": "os.path",
"line_number": 46,
"usage_type": "name"
},
{
"api_name": "os.path.curdir",
"... |
362998087 | """
DOES NOT WORK WITHOUT ORTOOLS
DOWNLOAD HERE: https://developers.google.com/optimization/installing
"""
from __future__ import print_function
from ortools.graph import pywrapgraph
def dataRoute(resource, server, network):
numOfRows = len(network)
numOfCols = len(network[0])
# Instantiate a SimpleMaxFl... | null | companyBots/sigmaBot/maxNetworkFlow1.py | maxNetworkFlow1.py | py | 1,126 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "ortools.graph.pywrapgraph.SimpleMaxFlow",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "ortools.graph.pywrapgraph",
"line_number": 14,
"usage_type": "name"
}
] |
265268943 | import requests
import random
import json
import sqlite3
from datetime import datetime
from dateutil import relativedelta
from abc import ABC, abstractmethod
class CommandBase(ABC):
def __init__(self, bot):
self.bot = bot
@property
@abstractmethod
def command_name(self):
raise NotImp... | null | command.py | command.py | py | 10,126 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "abc.ABC",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "abc.abstractmethod",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "abc.abstractmethod",
"line_number": 20,
"usage_type": "name"
},
{
"api_name": "sqlite3.connect",
"l... |
619234315 | """Driver() test. Runs with "python". (pytest not needed)."""
from seleniumbase import Driver
from seleniumbase import js_utils
from seleniumbase import page_actions
# Example with options. (Also accepts command-line options.)
driver = Driver(browser="chrome", headless=False)
try:
driver.get("https://selen... | null | examples/raw_browser_launcher.py | raw_browser_launcher.py | py | 1,062 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "seleniumbase.Driver",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "seleniumbase.page_actions.wait_for_element",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "seleniumbase.page_actions",
"line_number": 10,
"usage_type": "name"
},
... |
568591797 | """
This crawler collects 15 main news from rbk.ru
- url, title, modification date and body
"""
import requests
from bs4 import BeautifulSoup
from re import compile
from itertools import chain, zip_longest
name_of_collected_items = ('title', 'url', 'data_modification', 'body')
patterns = {
# pattern... | null | crawler.py | crawler.py | py | 1,827 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "re.compile",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "re.compile",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "re.compile",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 26... |
412777803 | import requests
from bs4 import BeautifulSoup
if __name__ == "__main__":
response = requests.get("https://s.weibo.com/top/summary?Refer=top_hot&topnav=1&wvr=6")
bs = BeautifulSoup(response.content.decode(),'lxml')
i = 1
print("===========微博热搜榜===========")
for keyword in bs.select("#pl_top_realtime... | null | Week-04/0401/Exercise-0401-彭高杲.py | Exercise-0401-彭高杲.py | py | 473 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "requests.get",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 6,
"usage_type": "call"
}
] |
149688806 | import warnings
from civis.futures import CivisFuture
class SubscribableResult(CivisFuture):
def __init__(self, *args, **kwargs):
warnings.warn('This class was deprecated in version 1.3 in favor of '
'civis.futures.CivisFuture. This will be removed in '
'versio... | null | civis/pubnub.py | pubnub.py | py | 413 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "civis.futures.CivisFuture",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "warnings.warn",
"line_number": 8,
"usage_type": "call"
}
] |
374263026 | # -*- coding: utf-8 -*-
import numpy as np
import logging
log = logging.getLogger(__name__)
from qulab.Driver import visaDriver, QList, QOption, QReal
class Driver(visaDriver):
__log__=log
support_models = ['AWG70001A', 'AWG70002A']
CHs=[1,2]
quants = [
# Sample Rate set_cmd is block cmd
... | null | qulab/Driver/drivers/TekAWG70000A.py | TekAWG70000A.py | py | 14,164 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "logging.getLogger",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "qulab.Driver.visaDriver",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "qulab.Driver.QReal",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "qulab.Driv... |
82038322 | import pytoshop, os
import numpy as np
from PIL import Image
from pytoshop.user import nested_layers as nl
from pytoshop.enums import *
#img_layer_conf = dict(
# name = 'layer_added',
# channels = channels,
# visible = True,
# opacity = 255,
# group_id = 0,
# blend_mode = BlendMode.normal,
# top ... | null | modules/test_pytoshop_m.py | test_pytoshop_m.py | py | 1,990 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.path.splitext",
"line_number": 35,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 35,
"usage_type": "attribute"
},
{
"api_name": "os.path.splitext",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_nu... |
201779015 | import requests
from bs4 import BeautifulSoup
data = requests.get("https://www.monster.com/jobs/search/?q=Software-Developer&where=Australia")
soup = BeautifulSoup(data.content, 'html.parser')
results = soup.find(id='SearchResults',class_='mux-card mux-job-card')
title_elem = results.find('h2', class_='title')
company... | null | pythonBackend/webscraping/webscraping.py | webscraping.py | py | 907 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "requests.get",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 5,
"usage_type": "call"
}
] |
534607684 | import collections
import logging
from base64 import b64encode
from django.conf import settings
from kubernetes import client, config
from django.utils.functional import cached_property
from awx.main.utils.common import parse_yaml_or_json
from awx.main.utils.execution_environments import get_default_pod_spec
logger ... | null | awx/main/scheduler/kubernetes.py | kubernetes.py | py | 4,562 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "logging.getLogger",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "collections.namedtuple",
"line_number": 38,
"usage_type": "call"
},
{
"api_name": "django.conf.settings.INSTALL_UUID",
"line_number": 42,
"usage_type": "attribute"
},
{
"a... |
212219202 | #!/usr/bin/env python
import random
import sys
import pickle
import pdb
from spacegame.Universe import Universe, Sector
import code, traceback, signal
import networkx as nx
major_types = ['Cluster', 'Nebula', 'Formation']
proper_names = [ 'Ursa', 'Lupus', 'Taurus', 'Virgo', 'Libra', 'Scorpio', 'Scylla', 'Charybdis', ... | null | scripts/make_map.py | make_map.py | py | 4,961 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "random.randint",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "random.randint",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "random.randint",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "code.InteractiveConsole"... |
544803168 | from __future__ import annotations
from bevy import Bevy
from typing import Awaitable, Callable, Generic, Type, TypeAlias, TypeVar
from .policies import FormatPolicy, ValidationPolicy, ViewPolicy, ChangePolicy
T = TypeVar("T")
FormatFunction: TypeAlias = Callable[[T, "Field[T]"], Awaitable[T]]
ValidationFunction: T... | null | wordlette/databases/models.py | models.py | py | 3,155 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "typing.TypeVar",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "typing.TypeAlias",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "typing.Callable",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "typing.Awaitable",
... |
344182464 | import torch
import torch.nn as nn
class DnCNN(nn.Module):
"""
Define the DnCNN neural network which takes noisy image image y and
output the residual image v such that the estimation for the ground
truth is y - v.
"""
def __init__(self, depth=17, n_channels=64,
img_channel=1,... | null | NLL/model.py | model.py | py | 4,037 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "torch.nn.Module",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 5,
"usage_type": "name"
},
{
"api_name": "torch.nn.Conv2d",
"line_number": 42,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line_numb... |
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