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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
126846414 | from sklearn import cross_validation
from sklearn.metrics import confusion_matrix
from sklearn.metrics import precision_score
from sklearn.metrics import recall_score
from sklearn import metrics
from Evaluation import MyEvaluation
class Estimation(object):
def __init__(self):
return
def evaluate_test... | null | Estimation.py | Estimation.py | py | 3,574 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "sklearn.metrics.accuracy_score",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "sklearn.metrics",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "sklearn.metrics.precision_score",
"line_number": 16,
"usage_type": "call"
},
{
"ap... |
369563946 | def setup():
import json
#matches = json.load(open("matches.json"))
events = json.load(open("events.json"))
#juve_match = [match for match in matches if match["wyId"] == 2576302][0]
juve_events = [event for event in events if event["matchId"] == 2576302]
return juve_events
if __name__ == "__m... | null | esercizio15.py | esercizio15.py | py | 1,100 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "json.load",
"line_number": 5,
"usage_type": "call"
}
] |
259519256 | import socket
from PyQt5.QtCore import QSize
from PyQt5.QtCore import pyqtSignal
from PyQt5.QtGui import QColor
from PyQt5.QtGui import QIcon
from PyQt5.QtWidgets import QHBoxLayout
from PyQt5.QtWidgets import QVBoxLayout
from Source.GUI.Widgets.Label import MYLabel
from Source.GUI.Widgets.ModuleButton import MYButto... | null | GUI/Server/States.py | States.py | py | 7,022 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "Source.GUI.Widgets.Widget.MYWidget",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "PyQt5.QtCore.pyqtSignal",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "PyQt5.QtCore.pyqtSignal",
"line_number": 21,
"usage_type": "call"
},
{
... |
264195170 | # -*- coding: utf-8 -*-
"""
Created on Fri Mar 8 13:58:38 2019
@author: chonlatid.d
"""
# import the necessary packages
import requests
import base64
import json
import glob
import os
import time
import numpy as np
from PIL import Image
import io
# initialize the Keras REST API endpoint URL along wi... | null | 4connerwithsegment/rest_predict.py | rest_predict.py | py | 1,883 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "glob.glob",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "PIL.Image.open",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "PIL.Image",
"line_number": 28,
"usage_type": "name"
},
{
"api_name": "base64.b64encode",
"line_numbe... |
7882920 | import sys
import os
import random
pwd = os.path.dirname(os.path.realpath(__file__))
sys.path.append(pwd + "../")
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "django_app.settings")
import django
django.setup()
from goods.models import Goods
from users.models import UserProfile
from user_operation.... | null | db_tools/import_colection.py | import_colection.py | py | 1,063 | python | en | code | null | code-starcoder2 | 83 | [
{
"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.realpath",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "sys.path.append",
"lin... |
254563898 | import random
from matplotlib import pyplot as plt
import matplotlib
# windows和linux可以这样让其支持中文
font = {
'family': 'MicroSoft YaHei',
'weight': 'bold',
}
matplotlib.rc('font', **font)
# 如果列表a表示10点到12点的每一分钟的气温，绘制折线图观察每分钟气温的变化
# a = [random.randint(20, 35) for i in range(120)]
x = range(120)
y = [random.randint... | null | 01_data_analysis/matplotlib/02_matplotlib.py | 02_matplotlib.py | py | 1,115 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "matplotlib.rc",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "random.randint",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.figure",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "matplotlib.pypl... |
454620627 | import asyncio
from clock import clock, time
apple_num = 5
banana_num = 10
item = 5
@clock
async def load_apple(num):
await asyncio.sleep(num*0.1)
return num
async def buy_apple(num):
global apple_num
while num >= apple_num:
load_apple_num = await load_apple(5)
apple_num += load_apple... | null | FluentPython/深入理解异步编程/demo.py | demo.py | py | 1,475 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "asyncio.sleep",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "clock.clock",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "asyncio.sleep",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "asyncio.get_event_loop",
"... |
395587050 | import pytest
from rattlesnake.interval import Interval
from rattlesnake.note import Note
@pytest.mark.parametrize('bass_note, number, quality, expected_distance, expected_name, expected_note', [
(Note('C'), 1, Interval.perfect, 0, 'Perfect Unison', Note('C')),
(Note('C'), 1, Interval.augmented, 1, 'Augmented... | null | rattlesnake/tests/pytest_interval.py | pytest_interval.py | py | 3,192 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "rattlesnake.interval.Interval",
"line_number": 58,
"usage_type": "call"
},
{
"api_name": "pytest.mark.parametrize",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "pytest.mark",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "... |
76267419 | from flask import request
from init_app import socketio, db
from models import Status, Game
from general_handlers.deck_handler import draw
from general_handlers.game_handler import doubledown_valid
from general_handlers.balance_handler import sufficent_funds
from general_handlers.user_handler import identifier_to_st... | null | singleplayer/single_player_events.py | single_player_events.py | py | 2,810 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "init_app.db.session.query",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "models.Game",
"line_number": 22,
"usage_type": "argument"
},
{
"api_name": "init_app.db.session",
"line_number": 22,
"usage_type": "attribute"
},
{
"api_name": "in... |
108477520 | # -*-coding:utf-8-*-
import json
def per_map_to_pro(data):
per_map_pro_times = {}
for item in data:
per_map_pro_times[item['repo']['id']] = {}
for item in data:
per_map_pro_times[item['repo']['id']][item['actor']['id']] = {}
for item in data:
if item['type'] in ['P... | null | code.py | code.py | py | 3,751 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "json.loads",
"line_number": 54,
"usage_type": "call"
},
{
"api_name": "json.dump",
"line_number": 61,
"usage_type": "call"
}
] |
326771020 | from flask import Flask, render_template, request, redirect, session
app = Flask(__name__)
app.secret_key = "secret"
@app.route('/')
def count():
if len(session) == 0:
session['tally'] = 1
else:
session['tally'] += 1
return render_template("index.html", tally=session['tally'])
@app.route('... | null | Python/Flask/Counter/server.py | server.py | py | 411 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "flask.Flask",
"line_number": 2,
"usage_type": "call"
},
{
"api_name": "flask.session",
"line_number": 7,
"usage_type": "argument"
},
{
"api_name": "flask.session",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "flask.session",
"line_nu... |
123980717 | from multiprocessing import cpu_count
import click
variant_file = click.argument('variant_file',
type=click.File('rb'),
metavar='<vcf_file> or -')
outfile = click.option('-o', '--outfile',
type=click.File('w'),
help='Specify the path to a file where results should be stored.')
silent = click.option... | null | genmod/commands/utils.py | utils.py | py | 963 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "click.argument",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "click.File",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "click.option",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "click.File",
"line_number": 9... |
399779084 | import time
from collections import OrderedDict
from itertools import tee
from . import backends as be
from . import metrics as M
from . import schedules
from .models.model_utils import State
class Sampler(object):
"""Base class for the sequential Monte Carlo samplers"""
def __init__(self, model, **kwargs):
... | null | paysage/fit.py | fit.py | py | 19,119 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "models.model_utils.State.from_visible",
"line_number": 87,
"usage_type": "call"
},
{
"api_name": "models.model_utils.State",
"line_number": 87,
"usage_type": "name"
},
{
"api_name": "models.model_utils.State.from_visible",
"line_number": 88,
"usage_type": "... |
92703634 | from typing import Optional, Dict
import pandas as pd
from mykaggle.feature.base import Feature
from mykaggle.transform.groupby import BasicGroupByTransform
COLUMNS = [
'Platform',
'Year_of_Release',
'Genre',
'Rating'
]
class TE(Feature):
'''
Name 以外の全カテゴリのカウントエンコーディング
'''
def __init... | null | mykaggle/feature/te.py | te.py | py | 1,117 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "mykaggle.feature.base.Feature",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "pandas.DataFrame",
"line_number": 24,
"usage_type": "attribute"
},
{
"api_name": "typing.Optional",
"line_number": 25,
"usage_type": "name"
},
{
"api_name": "t... |
50953737 | """
TFTTool by Max Zuidberg
This Source Code Form is subject to the terms of the Mozilla Public
License, v. 2.0. If a copy of the MPL was not distributed with this
file, You can obtain one at http://mozilla.org/MPL/2.0/.
"""
import sys
import struct
import json
import string
import argparse
from pathlib import Path
... | null | TFTTool.py | TFTTool.py | py | 30,479 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "sys.tracebacklimit",
"line_number": 20,
"usage_type": "attribute"
},
{
"api_name": "json.dumps",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "struct.unpack",
"line_number": 149,
"usage_type": "call"
},
{
"api_name": "struct.unpack",
... |
92029190 | import os
os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'freelunch.settings')
from sys import exit
import django
django.setup()
import random
from flapp import models
from faker import Faker
fake = Faker()
sections = []
for i in models.Section:
sections.append(i[0])
author_designations = []
for i in models.A... | null | populate_site.py | populate_site.py | py | 3,310 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "os.environ.setdefault",
"line_number": 2,
"usage_type": "call"
},
{
"api_name": "os.environ",
"line_number": 2,
"usage_type": "attribute"
},
{
"api_name": "django.setup",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "faker.Faker",
"li... |
204213768 | #!/usr/bin/env python
#-*-coding:utf-8-*-
# @Time : 2020/6/3 14:05
# @Author : djc
# @File : db_operate.py 数据库相关操作
from flask import Blueprint
from app.models.models import db, User
db_operate = Blueprint('dboperate', __name__)
@db_operate.route('/create_db/')
def create_db():
"""
创建user表
:return... | null | flask/flask_00/app/views/db_operate.py | db_operate.py | py | 735 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "flask.Blueprint",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "app.models.models.db.create_all",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "app.models.models.db",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "a... |
157783748 | # -*- coding: utf-8 -*-
from django.utils.six import text_type
from rest_framework import exceptions
from rest_framework import HTTP_HEADER_ENCODING
from rest_framework.authentication import TokenAuthentication
def get_authorization_header(request):
"""
Return request's 'Authorization:' or 'x-authorization:' ... | null | conference/attendees/authentication.py | authentication.py | py | 1,583 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "django.utils.six.text_type",
"line_number": 17,
"usage_type": "argument"
},
{
"api_name": "rest_framework.HTTP_HEADER_ENCODING",
"line_number": 19,
"usage_type": "argument"
},
{
"api_name": "rest_framework.authentication.TokenAuthentication",
"line_number": 23,... |
387419713 | # uncompyle6 version 3.7.4
# Python bytecode 3.7 (3394)
# Decompiled from: Python 3.6.9 (default, Apr 18 2020, 01:56:04)
# [GCC 8.4.0]
# Embedded file name: build/bdist.macosx-10.15-x86_64/egg/foxylib/tools/database/mongodb/tests/test_foxylib_mongodb.py
# Compiled at: 2020-01-15 23:57:40
# Size of source mod 2**32: 10... | null | pycfiles/foxylib-0.3.96-py3.7/test_foxylib_mongodb.cpython-37.py | test_foxylib_mongodb.cpython-37.py | py | 1,351 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "unittest.TestCase",
"line_number": 16,
"usage_type": "name"
},
{
"api_name": "foxylib.tools.log.foxylib_logger.FoxylibLogger.attach_stderr2loggers",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "foxylib.tools.log.foxylib_logger.FoxylibLogger",
"line... |
331179964 | import bpy
import math
from math import pi
def run(origin):
#Add a single chain link to the scene
bpy.ops.mesh.primitive_torus_add(
#major_radius = 1,
#minor_radius = 0.25,
major_segment = 12,
minor_segment = 8,
abso_major_rad = 1,
abso_minor_rad = 0.6,
l... | null | chain.py | chain.py | py | 1,344 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "bpy.ops.mesh.primitive_torus_add",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "bpy.ops",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "bpy.context",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "bpy.ops.... |
14164871 | #!/usr/bin/env python
# <<BEGIN-copyright>>
# Copyright (c) 2016, Lawrence Livermore National Security, LLC.
# Produced at the Lawrence Livermore National Laboratory.
# Written by the LLNL Nuclear Data and Theory group
# (email: mattoon1@llnl.gov)
# LLNL-CODE-683960.
# All rights reserved.
#
# This file is par... | null | bin/XMLtoHDF.py | XMLtoHDF.py | py | 7,502 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "collections.Counter",
"line_number": 106,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 132,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 147,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"lin... |
391270564 | from datetime import datetime as dt
import numpy as np
import os
import pandas as pd
import re
import sys
sys.path.append(os.path.dirname(os.path.realpath(__file__)))
import smsclass
import volatile.memory as mem
import dynadb.db as db
#------------------------------------------------------------------------------
c... | null | gsm/smsparser2/subsurface.py | subsurface.py | py | 25,506 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "sys.path.append",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "os.path.dirname",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number... |
259632825 | # Initialize connection with rest of lib
from utils import *
from DL_ClassifierModel import *
import os
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from pathlib import Path
data = 'data/mtb/protcase_1a.txt'
model_path = 'pEmb_model_958.pkl'
#
# if data=="celegans" or data=="human":
# ... | null | predict_mtb.py | predict_mtb.py | py | 3,131 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "os.walk",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 33,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
"line_number": 3... |
339735720 | #! /usr/bin/python
# -*- coding: utf-8 -*-
from collections import ChainMap
from ..utils.constants import C
__author__ = 'fyabc'
class GameEntity:
"""The base class of all game entities."""
def __init__(self):
# oop(Order Of Play).
# All game entities have this attribute, and share the sam... | null | HearthStone2/HearthStone/game/game_entity.py | game_entity.py | py | 1,605 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "collections.ChainMap",
"line_number": 36,
"usage_type": "call"
},
{
"api_name": "utils.constants.C.Game",
"line_number": 39,
"usage_type": "attribute"
},
{
"api_name": "utils.constants.C",
"line_number": 39,
"usage_type": "name"
}
] |
36041535 | from flask import Flask, request
from crossdomain import crossdomain
import db
import config
import json
import logging
from daemonizer import Daemon
import time
conf = config.getConfig()
database = False
app = Flask(__name__)
secret=conf["karmaServer"]["secret"]
karmaWaiting = {}
karmaGivers = {}
karmaTickets = {}
... | null | src/dk.py | dk.py | py | 5,114 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "config.getConfig",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "flask.Flask",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "logging.debug",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "crossdomain.crossdomain",
... |
516428227 | # Author: R. C. Howell
# Python 2.7.10
# Generating GLJ textual encodings of board positions
# GLJ for the last names of Debasis Ganguly, Johannes Leveling, and Gareth J. F. Jones
# Textual encoding based upon their 'Retrieval of Similar Chess Positions' paper written at Dublin City University School of Computing
impo... | null | position_analysis/genGLJ.py | genGLJ.py | py | 2,689 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "chess.file_index",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "chess.rank_index",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "chess.file_index",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "chess.rank_index",... |
205602357 | # -*- coding:utf-8 -*-
from __future__ import division #除数可以显示为float
from six import StringIO #使用聚宽readfile函数
import time #使用time stamp
import datetime
import matplotlib.pyplot as plt
import math
import talib
import numpy as np
import pandas as pd
# 功能：从聚宽函数库中提取数据
# 输入：
# st... | null | Logit/QuantLib.py | QuantLib.py | py | 21,248 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "pandas.DataFrame",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame",
"line_number": 38,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 49,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line... |
422608195 | import dgl
import numpy as np
import torch as th
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
import torch.multiprocessing as mp
from torch.utils.data import DataLoader
import dgl.function as fn
import dgl.nn.pytorch as dglnn
import time
import math
import argparse
from _thread impo... | null | GNS_sampling_prob.py | GNS_sampling_prob.py | py | 22,810 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "math.log",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "torch.nn.Module",
"line_number": 28,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 28,
"usage_type": "name"
},
{
"api_name": "torch.nn.ModuleList",
"lin... |
106902593 | from django.shortcuts import render
from rest_framework import status
from rest_framework.response import Response
from shopify.models import Account, Products, Categories, AccountType, Vendor
from .serializers import AccountSerializer, ProductsSerializer, CategoriesSerializer, AccountTypeSerializer, VendorSerializer
f... | null | apis/views.py | views.py | py | 10,677 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "rest_framework.views.APIView",
"line_number": 22,
"usage_type": "name"
},
{
"api_name": "django.http.HttpResponse",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "json.dumps",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "merc... |
77266114 | from django.core.management.base import BaseCommand
from django.db import transaction
from guardian.shortcuts import assign_perm
import factory.random
from metaci import conftest as fact
from metaci.users.models import User
from metaci.testresults.models import TestResult
from django.contrib.auth.models import Grou... | null | metaci/db/management/commands/populate_db.py | populate_db.py | py | 2,980 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "django.core.management.base.BaseCommand",
"line_number": 19,
"usage_type": "name"
},
{
"api_name": "metaci.users.models.User.objects.count",
"line_number": 43,
"usage_type": "call"
},
{
"api_name": "metaci.users.models.User.objects",
"line_number": 43,
"usa... |
91058936 | class TwoSum(object):
def __init__(self):
from collections import Counter
self.num_counts = Counter()
def add(self, number):
self.num_counts[number] += 1
def find(self, value):
for num in self.num_counts:
comple = value - num
min_multiplicity = 2 if num == comple else 1
if (sel... | null | solutions/170/hash_table_linear_space.py | hash_table_linear_space.py | py | 525 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "collections.Counter",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "{'Counter': 'collections.Counter'}",
"line_number": 22,
"usage_type": "call"
}
] |
37594897 | # Copyright 2016 Mirantis, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ... | null | filesystems/vnx_rootfs_lxc_ubuntu64-16.04-v025-openstack-compute/rootfs/usr/lib/python2.7/dist-packages/oslo_messaging/_drivers/pika_driver/pika_connection.py | pika_connection.py | py | 19,484 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "oslo_utils.eventletutils.fetch_current_thread_functor",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "oslo_utils.eventletutils",
"line_number": 27,
"usage_type": "name"
},
{
"api_name": "logging.getLogger",
"line_number": 29,
"usage_type": "call... |
367854056 | import sys
import argparse
from sole import square_root
# Разбор входных параметров.
def argparser():
parser = argparse.ArgumentParser(description='Solving the systems of linear equations by square root method. Version 1.0.0.0.')
# разбор файлов
parser.add_argument('source', type=argparse.FileType(... | null | sole/test_sole_sqroot.py | test_sole_sqroot.py | py | 2,733 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "argparse.FileType",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "sole.square_root",
"line_number": 20,
"usage_type": "call"
}
] |
629156770 | from __future__ import annotations
from collections import defaultdict
from typing import Union, Collection, List, Dict, Tuple, Any
from functools import total_ordering
import networkx as nx
from dere.taskspec import TaskSpecification, SpanType, FrameType
from dere.corpus import Corpus, Instance, Frame, Span
_SFType... | null | dere/evaluation.py | evaluation.py | py | 14,192 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "typing.Union",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "dere.taskspec.SpanType",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "dere.taskspec.FrameType",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "typing.Li... |
262777599 | import pinocchio as pio
from example_robot_data import loadSolo
import hppfcl
import numpy as np
import matplotlib.pyplot as plt
import time
from numpy.linalg import norm
from solo12_legs_collisions_utils import initSolo, addCapsule
robot, rmodel, rdata, gmodel, gdata = initSolo()
robot_config = np.zeros(robot.q0.shap... | null | src/python/solo12_legs_collisions_main.py | solo12_legs_collisions_main.py | py | 3,370 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "solo12_legs_collisions_utils.initSolo",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 51,
"usage_type": "call"
},
{
"api_name": "numpy.a... |
508073139 | from selenium import webdriver
import os
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
import selenium.webdriver.support.expected_conditions as EC
from selenium.common.exceptions import TimeoutException
from selenium.common.exceptions import NoSuchElementException
f... | null | tools/LexScrape.py | LexScrape.py | py | 6,405 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "selenium.webdriver.Firefox",
"line_number": 36,
"usage_type": "call"
},
{
"api_name": "selenium.webdriver",
"line_number": 36,
"usage_type": "name"
},
{
"api_name": "os.system",
"line_number": 101,
"usage_type": "call"
},
{
"api_name": "selenium.web... |
73310669 | '''
committeeScrape.py is used to scrape the static DC Gov committee webpages for
the staff contact information.
Libraries Used: Requests, bs4
|Signature-------------------------------------------|
|Written for DC Policy Center by Michael Watson; 2017|
|www.DCPolicyCenter.org / DC-Policy-Center.github.io |
|github:M-... | null | committeeScrape.py | committeeScrape.py | py | 5,711 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "requests.get",
"line_number": 54,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 55,
"usage_type": "call"
}
] |
202433384 | # -*- coding: utf-8 -*-
from flask import Flask, render_template, request, abort, redirect, Response, url_for
import json
import requests
import base64
import re
from flask import stream_with_context
from user_agents import parse
from werkzeug.contrib.cache import SimpleCache
from NEMbox.api import NetEase, geturl_new... | null | app.py | app.py | py | 3,819 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "flask.Flask",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "NEMbox.api.NetEase",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "re.sub",
"line_number": 45,
"usage_type": "call"
},
{
"api_name": "NEMbox.api.geturl_new_api",
... |
240099866 | #!/venv/bin python
import os
from flask import Flask, Blueprint, current_app, render_template
from torch.nn.functional import softmax
from pnasnet import pnasnet5
from resnet import resnet50, resnet152
import utils
image_classifier = Blueprint('image_classifier', __name__)
app = Flask(__name__)
model_links = {
... | null | webapp/pytorch_classifier.py | pytorch_classifier.py | py | 3,747 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "flask.Blueprint",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "flask.Flask",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "pnasnet.pnasnet5",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "resnet.resnet152",
"... |
530982196 | """This module implements an abstract base class (ABC) 'BaseDataset' for datasets.
It also includes common transformation functions (e.g., get_transform, __scale_width), which can be later used in subclasses.
"""
import random
import numpy as np
import torch
import librosa
import audioread
import soundfile as sf
impo... | null | styletransfer/data/base_dataset.py | base_dataset.py | py | 4,198 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "torch.utils.data.Dataset",
"line_number": 22,
"usage_type": "attribute"
},
{
"api_name": "torch.utils.data",
"line_number": 22,
"usage_type": "name"
},
{
"api_name": "abc.ABC",
"line_number": 22,
"usage_type": "name"
},
{
"api_name": "abc.abstractme... |
295620701 | # Copyright 2020 CSIRO
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software
... | null | platipy/dicom/nifti_to_rtstruct/convert.py | convert.py | py | 3,517 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "loguru.logger.info",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "loguru.logger",
"line_number": 31,
"usage_type": "name"
},
{
"api_name": "loguru.logger.info",
"line_number": 44,
"usage_type": "call"
},
{
"api_name": "loguru.logger",
... |
476869485 | """mysite3 URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/2.2/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: path('', views.home, name='home')
Class-based... | null | 3-mouth04/day04/mysite3/mysite3/urls.py | urls.py | py | 1,227 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "django.urls.path",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "django.contrib.admin.site",
"line_number": 22,
"usage_type": "attribute"
},
{
"api_name": "django.contrib.admin",
"line_number": 22,
"usage_type": "name"
},
{
"api_name": "... |
284157046 | """
(VERSION 1) User creation, deletion, update and query tests
"""
import pytest
from unittest.mock import ANY
from falcon import HTTP_200, HTTP_204, HTTP_404, HTTP_422
from users.tests.test_api import BaseUserTestCase
VERSION_URL = 'v1'
PATH = '/{}/users'.format(VERSION_URL)
@pytest.mark.apiv1
class UserP... | null | api/users/tests/v1/test_api_v1.py | test_api_v1.py | py | 4,591 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "users.tests.test_api.BaseUserTestCase",
"line_number": 19,
"usage_type": "name"
},
{
"api_name": "falcon.HTTP_204",
"line_number": 29,
"usage_type": "name"
},
{
"api_name": "falcon.HTTP_200",
"line_number": 40,
"usage_type": "name"
},
{
"api_name": ... |
550089785 | # This program will take the data that is provided from the
# Government of Alberta and put the data into .db file.
# This data will later be used to create data visualizations.
import os
import sys
import requests
import sqlite3 as sql
import pandas as pd
def get_data_from_web(url):
# This function ... | null | Alberta/createCovidDB.py | createCovidDB.py | py | 6,009 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "os.path.exists",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 16,
"usage_type": "attribute"
},
{
"api_name": "os.remove",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number... |
421000478 | # -*- coding:utf-8 -*-
__author__ = 'yfj'
__date__ = '2019/5/22 23:07'
from matplotlib import pyplot as plt
import numpy as np
import mpl_toolkits.axisartist as axisartist
from matplotlib.ticker import MultipleLocator, FuncFormatter
import matplotlib.font_manager as fm
import pandas as pd
import math
import numpy as n... | null | DNN/DeepCA-2C/A_draw.py | A_draw.py | py | 1,516 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "matplotlib.font_manager.FontProperties",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "matplotlib.font_manager",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "pandas.read_csv",
"line_number": 17,
"usage_type": "call"
},
{
"ap... |
181700441 | from typing import Any, Callable, List, Dict, Union, Optional, Sequence, Tuple
from numpy import ndarray
from collections import OrderedDict
from scipy import sparse
import os
import sklearn
import numpy
import typing
# Custom import commands if any
import warnings
import numpy as np
from sklearn.utils import check_ar... | null | tods/detection_algorithm/PyodMoGaal.py | PyodMoGaal.py | py | 10,021 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "d3m.container.DataFrame",
"line_number": 40,
"usage_type": "name"
},
{
"api_name": "d3m.container.DataFrame",
"line_number": 41,
"usage_type": "name"
},
{
"api_name": "UODBasePrimitive.Params_ODBase",
"line_number": 45,
"usage_type": "name"
},
{
"ap... |
23465603 | import matplotlib.pyplot as plt
import numpy as np
data = np.genfromtxt('../Output/RF/RF_QuBit_AmpVSPhiBar_1.txt',delimiter=' ')
x=data[:,0]
y=data[:,1]
z=data[:,2]
x=np.unique(x)
y=np.unique(y)
X,Y = np.meshgrid(x,y)
Z=z.reshape(len(y),len(x))
plt.pcolormesh(X,Y,Z)
plt.show() | null | Legacy/src/plotting_Heatmap.py | plotting_Heatmap.py | py | 282 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "numpy.genfromtxt",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "numpy.unique",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "numpy.unique",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "numpy.meshgrid",
"line_... |
571650902 | import numpy as np
from sklearn import svm
from sklearn.metrics import roc_auc_score
from makeData import getCVData
# number of cross validation folds
n = 5
# params
kernels = ['linear', 'poly', 'rbf', 'sigmoid']
nus = np.round(np.arange(0.01,1.01,0.01),2) # create range from 0.01 to 1.00 with 0.01 step
for kernel ... | null | Homeworks/hw3/p1.py | p1.py | py | 1,350 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "numpy.round",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "numpy.arange",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "makeData.getCVData",
"line_n... |
246077739 | # -*- coding: utf-8 -*-
##############################################################################
#
# Author: Guewen Baconnier (Camptocamp)
# Author: Vincent Renaville
# Copyright 2012 Camptocamp SA
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the ... | null | __unported__/hr_timesheet_fulfill/wizard/timesheet_fulfill.py | timesheet_fulfill.py | py | 6,768 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "datetime.datetime.strptime",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 29,
"usage_type": "name"
},
{
"api_name": "datetime.datetime.strptime",
"line_number": 30,
"usage_type": "call"
},
{
"api_name"... |
62886221 | import pandas as pd
import pickle
from cili.util import *
from cili.cleanup import *
from os.path import isfile, join
from os import listdir
from pprint import pprint
from copy import deepcopy
import statistics as stat
from random import random
import matplotlib.pyplot as plt
import math
from scipy import stats
from sk... | null | Old_Files/EyeLinkReader_OLD.py | EyeLinkReader_OLD.py | py | 40,364 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "pandas.ExcelFile",
"line_number": 57,
"usage_type": "call"
},
{
"api_name": "os.path.isfile",
"line_number": 87,
"usage_type": "call"
},
{
"api_name": "pandas.ExcelFile",
"line_number": 91,
"usage_type": "call"
},
{
"api_name": "os.listdir",
"li... |
168823615 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import json
import sys
import string
from z3 import *
path = input()
with open(path, 'r') as f:
dieta = json.load(f)
s = Solver()
zmienne = []
for parametr in dieta["parametry"]:
zmienne.clear()
for skladnik in dieta[u"składniki"]:
ZS = [Int(skladnik... | null | Zad3/zad3.py | zad3.py | py | 1,617 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "json.load",
"line_number": 11,
"usage_type": "call"
}
] |
38891585 | # -*- coding: utf-8 -*-
from decimal import ROUND_DOWN
from marshmallow import Schema, fields, validate, EXCLUDE
class DIDSchema(Schema):
"""
Represents and handles a did interaction through api
"""
class Meta:
unknown = EXCLUDE
id = fields.UUID(dump_only=True)
value = fields.Strin... | null | app/modules/dids/schemas.py | schemas.py | py | 1,114 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "marshmallow.Schema",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "marshmallow.EXCLUDE",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "marshmallow.fields.UUID",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "marshma... |
46069114 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import os
import sys
import logging
import StringIO
import re
import locale
import cgi
import datetime
import oauth
import locale
import calendar
from email.utils import parseaddr
from google.appengine.ext.webapp import template
from google.appengine.ext import webapp
from ... | null | main.py | main.py | py | 11,197 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "os.path.dirname",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 28,
"usage_type": "attribute"
},
{
"api_name": "google.appengine.ext.db.Model",
"line_number": 34,
"usage_type": "attribute"
},
{
"api_name": "googl... |
388816882 | #%%
from matplotlib import use
from tensorflow.python.keras.layers.core import Dropout
from tensorflow.python.ops.gen_array_ops import Reshape
import get_dataset
from datetime import date
import numpy as np
from pandas import DataFrame
from sklearn.model_selection import train_test_split
device_keys_table = get_datase... | null | train.py | train.py | py | 3,966 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "get_dataset.get_device_keys_table",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "get_dataset.get_event_keys_table",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "get_dataset.get_XY_between_date",
"line_number": 17,
"usage_type": "ca... |
236096244 | import numpy as np
import scipy.optimize as spo
import scipy.stats as sps
from myquant.derivative import *
import time
class EGarch():
def __init__(self, x, ar = 0, ma = 0, beta = 1, omega = 1, mid = True,seed = 1000):
self.x = x
self.ar = ar
self.ma = ma
self.beta ... | null | myquant/egarch.py | egarch.py | py | 6,064 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "numpy.random.RandomState",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "numpy.random",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "numpy.std",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "numpy.max",
... |
399528535 | import RPi.GPIO as GPIO
import time
from itertools import cycle
from flask import Flask, render_template
app = Flask(__name__)
state_cycle = cycle(['on', 'off'])
GPIO.setmode(GPIO.BOARD)
GPIO.setup(12, GPIO.OUT)
@app.route('/')
def index():
return render_template('index.html')
@app.route('/<state>')
def updat... | null | app.py | app.py | py | 728 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "flask.Flask",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "itertools.cycle",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "RPi.GPIO.setmode",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "RPi.GPIO",
"line_numbe... |
221890537 | import sys
import time
import numpy as np
from optparse import OptionParser
from deep_sea_treasure import DeepSeaTreasure
from agent import DCRACSAgent, DCRACAgent, DCRACSEAgent, DCRAC0Agent, CNAgent, CN0Agent
from utils import mkdir_p, get_weights_from_json
from stats import rebuild_log, print_stats, compute_log
AGE... | null | main_dst.py | main_dst.py | py | 6,086 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "agent.DCRACAgent",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "agent.DCRACSAgent",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "agent.DCRACSEAgent",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "agent.DCRAC0Age... |
416307661 | import json
import platform
import tempfile
from distutils import dir_util
from pathlib import Path
from typing import Any, Dict, Optional
from docker.types import Mount
from lean.components.docker_manager import DockerManager
from lean.components.lean_config_manager import LeanConfigManager
from lean.components.logg... | null | lean/components/lean_runner.py | lean_runner.py | py | 10,331 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "lean.components.logger.Logger",
"line_number": 19,
"usage_type": "name"
},
{
"api_name": "lean.components.lean_config_manager.LeanConfigManager",
"line_number": 20,
"usage_type": "name"
},
{
"api_name": "lean.components.docker_manager.DockerManager",
"line_numb... |
554372236 | from src.utils import data_util
import matplotlib.pyplot as plt
util = data_util.DataUtil()
i = 0
batch_size = 8
batches = util.batches_for_gen_with_label(batch_size)
for batch in batches:
if i < 1:
for j in range(batch_size):
batch[0][j, :, :, :] += 1
batch[0][j, :, :, :] *= 127... | null | src/model/test_input.py | test_input.py | py | 732 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "src.utils.data_util.DataUtil",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "src.utils.data_util",
"line_number": 4,
"usage_type": "name"
},
{
"api_name": "matplotlib.pyplot.imshow",
"line_number": 21,
"usage_type": "call"
},
{
"api_name"... |
102955627 | #!/usr/bin/env pypy
# -*- coding: utf-8 -*-
# c.durr - swerc - 2017
""" Candy Stick ? (word_search)
dynamic programming in time O(N^3 L) where N is the length of the candy stick
and L is the total length over all words in the dictionary.
= Definitions =
A[i] = maximal score one can obtain from stick[i:] without nec... | null | SWERC/swerc2017/swerc/candychain/submissions/accepted/word_search.py | word_search.py | py | 4,153 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "sys.version_info",
"line_number": 89,
"usage_type": "attribute"
},
{
"api_name": "sys.version_info",
"line_number": 90,
"usage_type": "attribute"
},
{
"api_name": "collections.defaultdict",
"line_number": 128,
"usage_type": "call"
}
] |
245070938 | import requests
import json
import pandas as pd
from bs4 import BeautifulSoup
import numpy as np
otg_vendor_page = "http://offthegridsf.com/vendors#food"
event_request_limit = 1000
def get_all_vendor_names():
r_otg_vendors = requests.get(otg_vendor_page)
soup = BeautifulSoup(r_otg_vendors.text, 'html.parser... | null | foodtrucksite/foodtrucks/get_list_of_events.py | get_list_of_events.py | py | 1,701 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "requests.get",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_... |
540724663 | import scrapy
from ..items import RealityItem
import re
from .. import utils
class TalandaInvestSpider(scrapy.Spider):
name = 'talanda_invest'
start_urls = [
'https://www.talanda-invest.cz/nemovitosti?start=0&limit=30',
]
default_email = 'info@talanda-invest.cz'
def parse(self, response):... | null | reality/reality/spiders/talanda_invest_spider.py | talanda_invest_spider.py | py | 4,859 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "scrapy.Spider",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "items.RealityItem",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "scrapy.Request",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "re.sub",
"line... |
292741934 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from six.moves import xrange
import numpy as np
from util import log
from model import Model
from input_ops import create_input_ops, check_data_id
from PIL import Image
import tensorflow as tf
import time
im... | null | evaler.py | evaler.py | py | 16,606 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "numpy.sum",
"line_number": 36,
"usage_type": "call"
},
{
"api_name": "numpy.abs",
"line_number": 36,
"usage_type": "call"
},
{
"api_name": "numpy.prod",
"line_number": 36,
"usage_type": "call"
},
{
"api_name": "util.log.info",
"line_number": 39,... |
572214319 | #!/usr/bin/env python
from label_db import LabelDB
import os
os.chdir("/home/cam/Documents/PHS3350")
from utils import best_classifications
os.chdir("bnn_for_seals")
seal_db = LabelDB(label_db_file='seal_data/labels.db')
seal_db.create_if_required()
files = os.listdir("seal_data/all_images_seals")
# add each coord... | null | bnn_for_seals/seal_label_db.py | seal_label_db.py | py | 727 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "os.chdir",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "os.chdir",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "label_db.LabelDB",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "os.listdir",
"line_number": 12,
... |
288837107 | import logging
import os
import pathlib
import typing
import itertools
from graphql import (
GraphQLSchema,
GraphQLUnionType,
DocumentNode,
parse,
build_ast_schema,
extend_schema,
concat_ast,
is_type_extension_node,
is_type_system_extension_node,
is_type_definition_node,
)
LOG ... | null | cannula/schema.py | schema.py | py | 3,629 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "logging.getLogger",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "graphql.parse",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "graphql.parse",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "graphql.DocumentNode",
... |
405136826 | from pyspark.sql import SparkSession
from io import StringIO
import csv
import time
import sys
# Start counting execution time
start_time = time.time()
def split_complex(x):
return list(csv.reader(StringIO(x), delimiter=','))[0]
def split_year(x):
return x[3].split("-")[0]
def return_5years_period(year):... | null | deliverables/code/query_4_rdd.py | query_4_rdd.py | py | 2,117 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "time.time",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "csv.reader",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "io.StringIO",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "pyspark.sql.SparkSession.builder.appN... |
396336052 | import cv2
import numpy as np
#/*! 为了绘制一个圆形，我们使用 cv2.circle 函数。我们传递 x，y，半径大小，RGB 颜色，深 */
#/*! 度作为参数*/
img = cv2.imread("image.jpg")
print(img.shape)
# cv2.circle(img,(x,y),radius,(R,G,B),THICKNESS)
# x：距x轴的距离
# y：与y轴的距离
# radius：半径大小（整数）
# R，G，B：RGB形式的颜色（255,255,0）
# 厚度：矩形的厚度（整数）
cv2.circle(img, (200, 130), 90, (255... | null | 01_OpenCV常用的 7 个示例：从读取到人脸检测（Python版）/01_12_圆形/main.py | main.py | py | 534 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "cv2.imread",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "cv2.circle",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "cv2.imshow",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "cv2.waitKey",
"line_number": 20,
... |
103549835 | """Model Wrapper
"""
import json
import logging
import os
import threading
import time
import traceback
import cv2
import numpy as np
import onnxruntime
import requests
from shapely.geometry import Polygon
from exception_handler import PrintGetExceptionDetails
from object_detection import ObjectDetection
from onnxru... | null | factory-ai-vision/EdgeSolution/modules/PredictModule/model_wrapper.py | model_wrapper.py | py | 6,566 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "os.environ.get",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "os.environ",
"line_number": 28,
"usage_type": "attribute"
},
{
"api_name": "os.environ.get",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "os.environ",
"line_... |
218393524 | from argparse import Namespace
from helpers.checkpoint import Checkpoint
from helpers import st_gumbel_softmax
from torch.autograd import Variable
from helpers.initialization import weights_init_xavier
from helpers.logger import Logger
from helpers import data_loader
from datetime import datetime
import torch.nn as n... | null | src/models/dcggan/dcggan.py | dcggan.py | py | 7,418 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "os.path.abspath",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "os.getcwd",
"line_numbe... |
74834635 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice,
# this list of conditions and the following... | null | test/unit/test_plate.py | test_plate.py | py | 5,927 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "xml.etree.ElementTree.register_namespace",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "xml.etree.ElementTree",
"line_number": 31,
"usage_type": "name"
},
{
"api_name": "ome_model.experimental.Plate",
"line_number": 41,
"usage_type": "call"
}... |
546730984 | from datetime import datetime
import random
import string
import mysql.connector
class nodePresentSeeder:
def __init__(self, db_client, node_count_per_floor, floor_count):
self.db_client = db_client
self.cursor = db_client.cursor
self._node_count_per_floor = node_count_per_floor
sel... | null | python/seeder/nodePresentSeeder.py | nodePresentSeeder.py | py | 2,074 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "datetime.datetime.utcnow",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "random.choice",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "string.ascii... |
216766418 | import os
from PIL import Image
import boto3
from boto3.s3.transfer import S3Transfer
import tempfile
from boto3.session import Session
print("start")
session = Session(aws_access_key_id='',
aws_secret_access_key='', region_name='ap-northeast-1')
print("s3")
s3 = session.resource("s3")
print("images-f... | null | image_resize/function.py | function.py | py | 1,304 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "boto3.session.Session",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "boto3.client",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "boto3.s3.transfer.S3Transfer",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "tempfi... |
108059616 | #!/usr/bin/env python3
import zmq
from random import randint
import threading
SVR_ADDR = 'tcp://localhost:7150'
BACKEND_ADDR = 'inproc://backend'
def LOG(*args):
with open("async_dealer2router.log", 'a') as fd:
fd.write("%s: %s\n" % (threading.current_thread().name, str(args)))
def run_client():
g... | null | tests/py/async_dealer2router.py | async_dealer2router.py | py | 2,001 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "threading.current_thread",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "zmq.Context",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "zmq.DEALER",
"line_number": 20,
"usage_type": "attribute"
},
{
"api_name": "zmq.IDENTITY",
... |
141915038 | from __future__ import print_function
import ast
import datetime
import json
import glob
import locale
import logging
import operator as op
import os
import re
import socket
import select
import shlex
import sys
import time
from functools import wraps
from subprocess import Popen, PIPE
from itertools import chain
imp... | null | lib/rcUtilities.py | rcUtilities.py | py | 46,648 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "os.path.join",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 31,
"usage_type": "attribute"
},
{
"api_name": "rcGlobalEnv.rcEnv.paths",
"line_number": 31,
"usage_type": "attribute"
},
{
"api_name": "rcGlobalEnv.rc... |
87162835 | import enum
import asyncio
import websockets
import traceback
import pycommons.logger
import maxwell.protocol.maxwell_protocol_pb2 as protocol_types
import maxwell.protocol.maxwell_protocol as protocol
from maxwell.listenable import Listenable
logger = pycommons.logger.get_instance(__name__)
class Code(enum.Enum):
... | null | maxwell/connection.py | connection.py | py | 9,437 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "pycommons.logger.logger.get_instance",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "pycommons.logger.logger",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "pycommons.logger",
"line_number": 10,
"usage_type": "name"
},
{
... |
306859109 | import numpy as np
from textwrap import wrap
import matplotlib.pyplot as plt
import matplotlib.animation as animation
from mpl_toolkits.basemap import Basemap
from mpl_toolkits.axes_grid.inset_locator import inset_axes
plt.clf()
def dataloader(name = "signif.txt"):
data = np.genfromtxt(name, delimiter="\t", usecol... | null | Unit 1_Earthquakes/What Can You Do With Python/DemoAnimation.py | DemoAnimation.py | py | 2,458 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "matplotlib.pyplot.clf",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "numpy.genfromtxt",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "numpy.where",
... |
488535766 | import os
import sys
import xml.etree.ElementTree as et
def main():
filepath = 'save.txt'
if not os.path.exists(filepath):
print('Error: File does not exist')
sys.exit()
tree = et.parse('save.txt')
root = tree.getroot()
for item in root.findall('player/craftingRecip... | null | sv-crafting/crafting.py | crafting.py | py | 694 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "os.path.exists",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "sys.exit",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "xml.etree.ElementTree.parse",
... |
97575059 | #!/usr/bin/python3
import cv2
import imutils
img = cv2.imread("../tmp/3.png", cv2.IMREAD_COLOR)
cv2.imshow("before", img)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
cv2.imshow("gray", gray)
# 骨架化, size 为 结构元素内核大小
skeleton = imutils.skeletonize(gray, size=(3, 3))
cv2.imshow("after", skeleton)
cv2.wai... | null | basics_raspberry/5-learn.py | 5-learn.py | py | 378 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "cv2.imread",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "cv2.IMREAD_COLOR",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "cv2.imshow",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "cv2.cvtColor",
"line_num... |
426724202 | import base64
from mock import patch
import unittest
from stacker.lookups.handlers.kms import handler
class TestKMSHandler(unittest.TestCase):
def setUp(self):
patcher = patch("botocore.session")
self.addCleanup(patcher.stop)
self.session = patcher.start()
self.kms = self.session... | null | stacker/tests/lookups/handlers/test_kms.py | test_kms.py | py | 998 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "unittest.TestCase",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "mock.patch",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "base64.b64encode",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "stacker.lookups.han... |
594493367 | import cv2
import numpy as np
img = cv2.imread("imori.jpg")
img = img.astype(np.float32)
size = 8
for i in range(len(img)//size):
for j in range(len(img[i])//size):
s = np.array([0.0, 0.0, 0.0])
for k in range(size):
for l in range(size):
s += img[i*size+k, j*size+l]
... | null | Question_01_10/my_answer_07.py | my_answer_07.py | py | 451 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "cv2.imread",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "numpy.float32",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "numpy.array",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "numpy.uint8",
"line_numbe... |
489915240 | """
Copyright 2019 Amazon.com, Inc. or its affiliates. All Rights Reserved.
Permission is hereby granted, free of charge, to any person obtaining a copy of this
software and associated documentation files (the "Software"), to deal in the Software
without restriction, including without limitation the rights to ... | null | src/cfnlint/rules/resources/properties/ImageId.py | ImageId.py | py | 3,077 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "cfnlint.rules.CloudFormationLintRule",
"line_number": 21,
"usage_type": "name"
},
{
"api_name": "cfnlint.rules.RuleMatch",
"line_number": 56,
"usage_type": "call"
},
{
"api_name": "cfnlint.rules.RuleMatch",
"line_number": 60,
"usage_type": "call"
}
] |
495013759 | from mako.template import Template
import os
import subprocess
from django.db.models import ProtectedError
import configlet
from constants import *
import fabric
from ignite.settings import REPO_PATH
from models import Configlet, Profile
from pool.pool import allocate_pool_entry, update_pool_ref_count
from utils.exce... | null | config/profile.py | profile.py | py | 5,988 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "logging.getLogger",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "models.Profile.objects.filter",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "models.Profile.objects",
"line_number": 22,
"usage_type": "attribute"
},
{
"api_n... |
163102097 | #------------------Bombermans Team---------------------------------#
# Author : B3mB4m
# Concat : b3mb4m@protonmail.com
# Project : https://github.com/b3mb4m/Shellsploit
# LICENSE : https://github.com/b3mb4m/Shellsploit/blob/master/LICENSE
#------------------------------------------------------------------#
import ... | null | shell/control.py | control.py | py | 44,212 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "sys.version_info",
"line_number": 16,
"usage_type": "attribute"
},
{
"api_name": "lib.base.framework.ShellsploitFramework",
"line_number": 20,
"usage_type": "name"
},
{
"api_name": "lib.base.framework.ShellsploitFramework.__init__",
"line_number": 23,
"usag... |
16564188 | import time
import redis
class RedisLock(object):
def __init__(self, key):
# redis的连接，官方推荐ssshi用StrictRedis，而不是Redis
self.rdcon = redis.StrictRedis(host='127.0.0.1', port=6379, password="", db=1, decode_responses=True)
print(id(self.rdcon))
# False代表未加锁，True代表加锁了
self._lock... | null | python_redis_lock.py | python_redis_lock.py | py | 2,172 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "redis.StrictRedis",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "time.time",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "time.time",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "time.time",
"line_number": 2... |
224378750 | import streamlit as st
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import pandas_datareader as web
import datetime
from datetime import date
def annualized_return(Df, nb_of_year):
Df = Df[::-1].reset_index()
last_value = Df['Adj Close'][0]
first_value = Df['Adj... | null | streamlit_test.py | streamlit_test.py | py | 993 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "pandas.DataFrame",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "streamlit.number_input",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "datetime.datetime.now",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "datetim... |
472644700 | ##load dataset
from sklearn.datasets import load_digits
digits = load_digits()
data = digits.data
labels = digits.target
## split data
from sklearn.model_selection import train_test_split
x_train, x_test, y_train, y_test = train_test_split(data, labels, test_size=0.25, random_state=0)
##model
from sklearn.linear_mo... | null | machine_learning/logistic.py | logistic.py | py | 501 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "sklearn.datasets.load_digits",
"line_number": 3,
"usage_type": "call"
},
{
"api_name": "sklearn.model_selection.train_test_split",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "sklearn.linear_model.LogisticRegression",
"line_number": 14,
"usage_... |
365650328 | #
"""
If you want to make a picture using a name
"""
from wordcloud import STOPWORDS as EN_STOPWORDS
from wordcloud import ImageColorGenerator
from stopword_persian import stopword_persian as STOPWORDS
from wordcloud_fa import WordCloudFa
from hazm import Normalizer
##import nltk # Natural Language ToolK... | null | Twitter/Back Up/cloudword.py | cloudword.py | py | 3,489 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "os.path.dirname",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 29,
"usage_type": "name"
},
{
"api_name": "os.getcwd",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 3... |
75151630 | #!/usr/bin/python
from __future__ import print_function
from lxml import etree
import re
import os
import sys
# xml parser for wiki species, using Xpath
def xml_iter(context, func, f):
# Liza Daly: High-performance XML parsing in Python with lxml article on IBM.com
for event, node in context:
func(n... | null | species_parser.py | species_parser.py | py | 3,020 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "re.sub",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "re.findall",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "re.I",
"line_number": 34,
"usage_type": "attribute"
},
{
"api_name": "re.findall",
"line_number": 58,
"... |
323881295 | #!/usr/bin/env python
'''
@author David Stuebe <dstuebe@asasscience.com>
@file pystoch.py
@date 03/11/13
@description Main program to calculate probability grids for stochastic oil model results.
Max/Linux Command Line Examples (from the pystoch directory):
./pystoch_main.py -p ./trajectory_data/simap/3D_TEST1 -x 3D_T... | null | pystoch/pystoch/pystoch_main.py | pystoch_main.py | py | 3,227 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "logging.getLogger",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "pystoch.command_line_arguments.get_command_line_arguments",
"line_number": 52,
"usage_type": "call"
},
{
"api_name": "pystoch.config.Config",
"line_number": 55,
"usage_type": "cal... |
188478909 | """
ResNet50 (C2D) for spatiotemporal task. Only ResNet50 backbone structure was implemented here.
"""
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import math
from functools import partial
from models.non_local import NLBlockND
class Bottleneck(nn.Module):
... | null | 3D_experiment/models/resnet3D.py | resnet3D.py | py | 5,695 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "torch.nn.Module",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "torch.nn.Conv3d",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line_nu... |
351648220 | """Code for the book PySpark in Action, Chapter 4."""
# tag::relevant-imports[]
import os
import numpy as np
from pyspark.sql import SparkSession
import pyspark.sql.functions as F
spark = SparkSession.builder.getOrCreate()
# end::relevant-imports[]
# tag::ch04-grocery-list[]
my_grocery_list = [
["Banana", 2,... | null | code/Ch04/book_code.py | book_code.py | py | 10,967 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "pyspark.sql.SparkSession.builder.getOrCreate",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "pyspark.sql.SparkSession.builder",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "pyspark.sql.SparkSession",
"line_number": 11,
"usage_t... |
1393581 | '''
Created on January 31, 2021
@author: pashaa@mskcc.org
'''
import os, sys
import shutil
import requests
from pathlib import Path
from luna_core.common.config import ConfigSet
from luna_core.common.constants import DATA_CFG, CONFIG_LOCATION, PROJECT_LOCATION
from luna_pathology.common.slideviewer_client import get_s... | null | tests/luna_pathology/common/test_slideviewer_client.py | test_slideviewer_client.py | py | 5,539 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "luna_core.common.config.ConfigSet",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "luna_core.common.constants.DATA_CFG",
"line_number": 27,
"usage_type": "name"
},
{
"api_name": "luna_core.common.config.ConfigSet",
"line_number": 29,
"usage_type"... |
197404867 | # coding:utf-8
import json
import logging
import pandas as pd
import requests
from variable import Constant
"""
1. 查询股票代码和名称
"""
def getStockInfo():
"""
查询stockInfo表中股票的代码,名称.
:return: [('000001','平安银行'),...]
"""
stockInfo = []
try:
api = Constant.SERVER_ROOT + 'stockSymbolAndNameI... | null | database/operateTool.py | operateTool.py | py | 23,508 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "variable.Constant.SERVER_ROOT",
"line_number": 23,
"usage_type": "attribute"
},
{
"api_name": "variable.Constant",
"line_number": 23,
"usage_type": "name"
},
{
"api_name": "requests.get",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "var... |
160798868 | import boto3, datetime
def getClusters(region):
"""
:return:dictionary of clusters in this account
"""
awsClient = boto3.client('redshift',region_name=region)
clusters = awsClient.describe_clusters()
clustersIdentifire={}
for clusterIndex in range(len(clusters["Clusters"])):
if clu... | null | Redshift/Check Redshift Cluster Automated Snapshots.py | Check Redshift Cluster Automated Snapshots.py | py | 4,440 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "boto3.client",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "datetime.datetime.now",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 23,
"usage_type": "attribute"
},
{
"api_name": "datetime.tim... |
621602 | import numpy as np
import scipy as sp
import scipy.special
def correlation_matern(rho, rho0, nu=2.5):
"""
Return correlation as evaluated by the Matern correlation function.
https://en.wikipedia.org/wiki/Mat%C3%A9rn_covariance_function
If nu = 0.5 then the Matern correlation function is equivalent to... | null | multi_loc/covariance.py | covariance.py | py | 2,746 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "numpy.sqrt",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "numpy.abs",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "numpy.where",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "scipy.special.kv",
"line_number"... |
281282667 | import uuid
from django.db import models
from django.contrib.auth.models import User
from django.core.exceptions import ValidationError
class PizzaLover(models.Model):
numberOfVotes = models.IntegerField(default=0)
userID = models.ForeignKey(User, on_delete=models.CASCADE)
def vote(self):
... | null | pizzaloversproject/back/models.py | models.py | py | 955 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "django.db.models.Model",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "django.db.models",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "django.db.models.IntegerField",
"line_number": 10,
"usage_type": "call"
},
{
"api_name... |
399300603 | from django.conf.urls import include, url
from . import views
urlpatterns = [
url(r'^tasks$',views.list_tasks, name='list_tasks'),
url(r'^tasks/<pk>$',views.edit_tasks, name='edit_tasks'),
url(r'^tasks/add$',views.createTasks.as_view(), name='add_tasks'),
url(r'^states/add$',views.add_states, name='add_states'),
... | null | tasks/urls.py | urls.py | py | 1,663 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "django.conf.urls.url",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "django.conf.urls.url",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "django.conf.urls.url",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "django.co... |
344074181 | from torch.nn.init import xavier_uniform_
from torch.nn import Module, ModuleList, Linear, ReLU, Sigmoid, Tanh, BatchNorm1d
from torch.distributions import Normal
import torch
from GaussianLayer import GaussianLayer1 as GaussianLayer
def init_weights(m):
if type(m) == Linear:
xavier_uniform_(m.weight, gai... | null | rl/models.py | models.py | py | 4,154 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "torch.nn.Linear",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "torch.nn.init.xavier_uniform_",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "torch.nn.Module",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "torch.nn... |
576565368 | import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
# Importing dataset
dataset = pd.read_csv('diabetes.csv')
X= dataset.iloc[:,:-1].values
Y= dataset.iloc[:,-1].values
# splitting the dataset into training set and test set
from sklearn.model_selection import train_test_split
X_train,X_test,Y_trai... | null | diabetes_SVM_random.py | diabetes_SVM_random.py | py | 3,451 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "pandas.read_csv",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "sklearn.model_selection.train_test_split",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "sklearn.preprocessing.StandardScaler",
"line_number": 16,
"usage_type": "call"
... |
462789964 | # encoding: utf-8
"""
ROSE Lab's GTA ReID Dataset, v3 alpha. This is the train_long-full version, meaning that there is no separation between
training set, query set and gallery set. The training set consists of all annotated images available. This is to
facillitate cross domain experiments.
"""
from __future__ i... | null | idm/datasets/gta_long_2C_v2.py | gta_long_2C_v2.py | py | 9,676 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "utils.data.BaseImageDataset",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "os.path.join",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 28,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
... |
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