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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
8983073054 | from datetime import datetime
from typing import Optional, Union
class Poll:
"""
Slot class for each Pool object.
"""
MAX_OPTIONS = 10
MIN_OPTIONS = 2
__slots__ = [
"_message_id",
"_channel_id",
"_question",
"_options",
"_date_created_at",
"_us... | TheXer/Jachym | src/ui/poll.py | poll.py | py | 1,559 | python | en | code | 11 | github-code | 36 | [
{
"api_name": "typing.Optional",
"line_number": 28,
"usage_type": "name"
},
{
"api_name": "typing.Optional",
"line_number": 29,
"usage_type": "name"
},
{
"api_name": "typing.Union",
"line_number": 29,
"usage_type": "name"
},
{
"api_name": "datetime.datetime",
... |
73224987304 | # views.py
from django.shortcuts import get_object_or_404
from rest_framework import status
from rest_framework.decorators import api_view
from rest_framework.response import Response
from calculator.models import Report
from calculator.serializers import ReportSerializer, ReportCalculationSerializer
import pandas as p... | StefKal/superdupertax | superdupertax/calculator/views.py | views.py | py | 2,749 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "calculator.models.Report.objects.all",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "calculator.models.Report.objects",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "calculator.models.Report",
"line_number": 18,
"usage_type": "n... |
8086245877 | #!/usr/bin/env python
"""
The file contains the class and methods for loading and aligning datasets
"""
from __future__ import print_function, division
import pickle
import numpy as np
from scipy.io import loadmat
import pandas as pd
from .utils import p2fa_phonemes
import warnings
from collections import OrderedDict
f... | codeislife99/Multimodal_Emotion_Analysis | mmdata/dataset.py | dataset.py | py | 29,605 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "sys.version_info",
"line_number": 23,
"usage_type": "attribute"
},
{
"api_name": "utils.p2fa_phonemes",
"line_number": 45,
"usage_type": "name"
},
{
"api_name": "pickle.load",
"line_number": 70,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv... |
34594770015 | """OpenAPI schema utility functions."""
from io import StringIO
_DEFAULT_EXAMPLES = {
"string": "string",
"integer": 1,
"number": 1.0,
"boolean": True,
"array": [],
}
_DEFAULT_STRING_EXAMPLES = {
"date": "2020-01-01",
"date-time": "2020-01-01T01:01:01Z",
"password": "********",
... | sphinx-contrib/openapi | sphinxcontrib/openapi/schema_utils.py | schema_utils.py | py | 4,446 | python | en | code | 103 | github-code | 36 | [
{
"api_name": "io.StringIO",
"line_number": 119,
"usage_type": "call"
}
] |
33006855107 | import csv
import io
from nltk.tokenize import word_tokenize
import sys
reload(sys)
sys.setdefaultencoding('ISO-8859-1')
def findLowest(topWords):
result = topWords.keys()[0]
for word in topWords:
if(topWords[word] < topWords[result]):
result = word
return result
with io.open("old_tweets.csv", encoding = "IS... | Temirlan97/WhatTwitterFeels | wordBag/countWords.py | countWords.py | py | 1,230 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "sys.setdefaultencoding",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "io.open",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "csv.reader",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "nltk.tokenize.word_tokenize"... |
25615151962 | #!/usr/bin/env python
# -*- coding:utf-8 -*-
import os
import pandas as pd
from datetime import datetime
from txt_table import txt_table
import re
# 将txt文件转化为csv
def transfer_data(folder):
#建立使用文件列表
filenames=[]
filelist=[]
filexlsx=[]
#遍历文件寻找txt
files=os.walk(folder)
... | hellboy1990/qixiang_explore | qixiang_check_v2.py | qixiang_check_v2.py | py | 7,538 | python | en | code | 5 | github-code | 36 | [
{
"api_name": "os.walk",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "re.match",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 28,
"u... |
73692412265 | import copy
import mock
import testtools
from stackalytics.processor import default_data_processor
from stackalytics.processor import normalizer
from stackalytics.tests.unit import test_data
class TestDefaultDataProcessor(testtools.TestCase):
def setUp(self):
super(TestDefaultDataProcessor, self).setUp(... | Mirantis/stackalytics | stackalytics/tests/unit/test_default_data_processor.py | test_default_data_processor.py | py | 7,360 | python | en | code | 12 | github-code | 36 | [
{
"api_name": "testtools.TestCase",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "mock.Mock",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "stackalytics.tests.unit.test_data.USERS",
"line_number": 16,
"usage_type": "attribute"
},
{
"ap... |
40974261041 | #Import libraries
import numpy as np
import sqlalchemy
from sqlalchemy.ext.automap import automap_base
from sqlalchemy.orm import Session
from sqlalchemy import create_engine, func
from flask import Flask, jsonify
#Database Connection
engine = create_engine("sqlite:///Resources/hawaii.sqlite")
#Map database
Base = au... | AJ-Paine/10-Hawaii-Temperature-Exploration | app.py | app.py | py | 3,710 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "sqlalchemy.create_engine",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "sqlalchemy.ext.automap.automap_base",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "flask.Flask",
"line_number": 21,
"usage_type": "call"
},
{
"api_name... |
323607876 | """added Client Favourite and product views
Revision ID: bcc08ae9bed7
Revises: 399549c08a2a
Create Date: 2020-01-24 22:55:04.098191
"""
from alembic import op
import sqlalchemy as sa
import sqlalchemy_utils
# revision identifiers, used by Alembic.
revision = 'bcc08ae9bed7'
down_revision = '399549c08a2a'
branch_labe... | Dsthdragon/kizito_bookstore | migrations/versions/bcc08ae9bed7_added_client_favourite_and_product_views.py | bcc08ae9bed7_added_client_favourite_and_product_views.py | py | 1,741 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "alembic.op.create_table",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "alembic.op",
"line_number": 22,
"usage_type": "name"
},
{
"api_name": "sqlalchemy.Column",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "sqlalchemy.Integ... |
20885862962 | # flake8: noqa
import nltk
nltk.download("brown")
nltk.download("names")
import numpy as np
import multiprocessing as mp
import string
import spacy
import os
os.system("python -m spacy download en_core_web_sm")
from sklearn.base import TransformerMixin, BaseEstimator
from normalise import normalise
import pandas as ... | Lolik-Bolik/Hashing_Algorithms | utils/process_book.py | process_book.py | py | 2,868 | python | en | code | 2 | github-code | 36 | [
{
"api_name": "nltk.download",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "nltk.download",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "os.system",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "sklearn.base.BaseEstimator",
... |
7147825929 | #!/usr/bin/env python3
import re
import sys
import linecache
from pathlib import Path
regex = re.compile('#?(.*)\s?=\s?(.*)')
data = ''
try:
fpath = str(sys.argv[1])
if not Path(fpath).is_file():
raise Exception("file path is invalid or not a file")
except:
print("Error: file not provided or inval... | japtain-cack/docker-marid | files/configToRemco.py | configToRemco.py | py | 1,338 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "re.compile",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "sys.argv",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "pathlib.Path",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "sys.exit",
"line_number": 16... |
14049615322 | from django.shortcuts import render
from admin_dashboard.models import Review, Package
from django.contrib import messages
def home(request):
reviews = Review.objects.all()
packages = Package.objects.all()
return render(request, 'index.html', {
'title': 'Home',
'reviews': reviews,
... | aniatki/pro-dad | homepage/views.py | views.py | py | 709 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "admin_dashboard.models.Review.objects.all",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "admin_dashboard.models.Review.objects",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "admin_dashboard.models.Review",
"line_number": 6,
"usa... |
534546914 | import pygame as p
from Chess import ChessEngine, SmartMoveFinder, DataToLearn, VisualizData
import time
import xml.etree.ElementTree as gfg
import os.path
from Chess.DataTree import TreeNode
WIDTH = HEIGHT = 512
DIMENSION = 8
SQ_SIZE = HEIGHT // DIMENSION
MAX_FPS = 15
IMAGES = {}
WHITE_PIECE_CAPTUED = []
BLACK_PIECE... | KaiBaeuerle/chessAI | Chess/ChessMain.py | ChessMain.py | py | 16,775 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "pygame.Rect",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "pygame.transform.scale",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "pygame.transform",
"line_number": 26,
"usage_type": "attribute"
},
{
"api_name": "pygame.image... |
33865589189 | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import migrations, models
import datetime
class Migration(migrations.Migration):
dependencies = [
('bot', '0007_bot_logo'),
]
operations = [
migrations.CreateModel(
name='Chat',
fields... | DenerRodrigues/Chatterbot | bot/migrations/0008_chat.py | 0008_chat.py | py | 681 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "django.db.migrations.Migration",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "django.db.migrations",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "django.db.migrations.CreateModel",
"line_number": 15,
"usage_type": "call"
},
... |
40568030755 | from __future__ import annotations
import random
from datetime import timedelta
from typing import Type
from game.theater import FrontLine
from game.utils import Distance, Speed, feet
from .capbuilder import CapBuilder
from .invalidobjectivelocation import InvalidObjectiveLocation
from .patrolling import PatrollingFl... | dcs-liberation/dcs_liberation | game/ato/flightplans/barcap.py | barcap.py | py | 2,444 | python | en | code | 647 | github-code | 36 | [
{
"api_name": "patrolling.PatrollingFlightPlan",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "patrolling.PatrollingLayout",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "typing.Type",
"line_number": 17,
"usage_type": "name"
},
{
"api_name"... |
7704128693 | # -*- coding:utf-8 -*-
"""
Evluate the performance of embedding via different methods.
"""
import math
import numpy as np
from sklearn import metrics
from sklearn import utils as sktools
from sklearn.cluster import AgglomerativeClustering
from sklearn.cluster import SpectralClustering
from sklearn.linear_model impor... | Sngunfei/HSD | tools/evaluate.py | evaluate.py | py | 5,117 | python | en | code | 3 | github-code | 36 | [
{
"api_name": "sklearn.cluster.AgglomerativeClustering",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "sklearn.metrics.homogeneity_completeness_v_measure",
"line_number": 35,
"usage_type": "call"
},
{
"api_name": "sklearn.metrics",
"line_number": 35,
"usage_ty... |
21393775413 | """
5 element API Client
"""
from typing import Optional, Tuple
from bgd.constants import FIFTHELEMENT
from bgd.responses import GameSearchResult, Price
from bgd.services.abc import GameSearchResultFactory
from bgd.services.api_clients import GameSearcher, JsonHttpApiClient
from bgd.services.base import CurrencyExchan... | ar0ne/bg_deal | bgd/services/apis/fifth_element.py | fifth_element.py | py | 3,213 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "bgd.services.api_clients.JsonHttpApiClient",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "typing.Optional",
"line_number": 20,
"usage_type": "name"
},
{
"api_name": "bgd.services.constants.GET",
"line_number": 24,
"usage_type": "argument"
},
... |
262396930 | from bs4 import BeautifulSoup
import requests
import requests # request img from web
import shutil # save img locally
URL1 = 'http://localhost'
page = requests.get(URL1)
soup = BeautifulSoup(page.content, 'html.parser')
print(soup.prettify())
image_tags = soup.find_all('img')
for image_tag in image_tags:
url = im... | FukudaYoshiro/singo | saudi/import image.py | import image.py | py | 555 | python | en | code | 4 | github-code | 36 | [
{
"api_name": "requests.get",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "shutil.copyfileobj",
"l... |
16858290153 | # Enter your code here. Read input from STDIN. Print output to STDOUT
from collections import deque
deq = deque()
for i in range(int(input())):
command = input().split()
if command[0] == 'append':
deq.append(command[1])
elif command[0] == 'appendleft':
deq.appendleft(command[1])
elif c... | polemeest/daily_practice | hackerrank_deque.py | hackerrank_deque.py | py | 490 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "collections.deque",
"line_number": 4,
"usage_type": "call"
}
] |
7136369222 | # -*- coding: utf-8 -*-
# ***************************************************
# * File : timefeatures.py
# * Author : Zhefeng Wang
# * Email : wangzhefengr@163.com
# * Date : 2023-04-19
# * Version : 0.1.041901
# * Description : description
# * Link : link
# * Requirement : 相关模块版本需求... | wangzhefeng/tsproj | utils/timefeatures.py | timefeatures.py | py | 17,505 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "os.getcwd",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "sys.path.append",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number":... |
28297076587 | #!/bin/python3
"""
Creates new training data for all language directions (META_LANGS) according to META_RECIPES.
This may take some time, but is written in a functional way, so the files are not loaded into memory
in larger pieces.
"""
import file_utils
from recipes import META_RECIPES
import os
import argparse
par... | zouharvi/reference-mt-distill | src/create_data.py | create_data.py | py | 1,805 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "recipes.META_RECIPES.items",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "recipes.META_RECIPES",
"line_number": 34,
"usage_type": "name"
},
{
"api_name"... |
42218937553 | import os
import pandas as pd
import time
from pathlib import Path
import shutil
from bs4 import BeautifulSoup
#loading all the files in the memory and parsing it using beautiful soap to get key financials
#problem in reading coal india.
#due to unrecognized encoding, it throws error
#we add encoding="utf8"
d... | santoshjsh/invest | nse_7.py | nse_7.py | py | 2,312 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "pandas.read_csv",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "pathlib.Path",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "pathlib.Path",
"lin... |
44675601513 | import pysubs2
import pysrt
archivo = 'subtitle.ass'
subs = pysubs2.load(archivo, encoding='utf-8')
for line in subs:
print(line.text)
textoplano = line.text
texto = open('textoplano.txt', 'a')
texto.write(textoplano)
texto.close()
| FukurOwl/subtitles_translate | load_files.py | load_files.py | py | 260 | python | es | code | 0 | github-code | 36 | [
{
"api_name": "pysubs2.load",
"line_number": 4,
"usage_type": "call"
}
] |
17795055591 | from typing import List
class Solution:
def highFive(self, items: List[List[int]]) -> List[List[int]]:
items.sort(key=lambda x: (x[0], x[1]))
ans = list()
for i in range(len(items)):
if i == len(items) - 1 or items[i][0] != items[i + 1][0]:
temp = list()
... | fastso/learning-python | leetcode_cn/solved/pg_1086.py | pg_1086.py | py | 569 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "typing.List",
"line_number": 5,
"usage_type": "name"
}
] |
72908308584 | """
Чтобы решить данную задачу, можно воспользоваться алгоритмом поиска в ширину (BFS),
так как он позволяет находить кратчайшие пути в графе с невзвешенными ребрами.
В нашем случае города и дороги между ними образуют граф без весов на ребрах.
"""
from collections import deque
# Функция для вычисления расстояния ме... | TatsianaPoto/yandex | ML & Programming/6_find_shortest_path.py | 6_find_shortest_path.py | py | 4,858 | python | ru | code | 0 | github-code | 36 | [
{
"api_name": "collections.deque",
"line_number": 16,
"usage_type": "call"
}
] |
43301216014 | import py
from rpython.flowspace.model import Constant
from rpython.rtyper.lltypesystem import lltype
from rpython.jit.codewriter.flatten import SSARepr, Label, TLabel, Register
from rpython.jit.codewriter.flatten import ListOfKind, IndirectCallTargets
from rpython.jit.codewriter.jitcode import SwitchDictDescr
from rpy... | mozillazg/pypy | rpython/jit/codewriter/format.py | format.py | py | 6,680 | python | en | code | 430 | github-code | 36 | [
{
"api_name": "rpython.jit.codewriter.flatten.Register",
"line_number": 15,
"usage_type": "argument"
},
{
"api_name": "rpython.flowspace.model.Constant",
"line_number": 17,
"usage_type": "argument"
},
{
"api_name": "rpython.rtyper.lltypesystem.lltype.Ptr",
"line_number": 18,
... |
14365200747 | #Import dependencies
import json
import pandas as pd
import numpy as np
import re
from sqlalchemy import create_engine
import psycopg2
from config import db_password
import time
#Set file directory
file_dir = '/Users/mariacarter/Desktop/Berkeley-Bootcamp/Analysis-Projects/Movies-ETL/Resources/'
def process_ETL(wiki_m... | mcarter-00/Movies-ETL | challenge.py | challenge.py | py | 15,363 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "json.load",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame",
"lin... |
3733422218 | from argparse import Namespace
from pandas.core.frame import DataFrame
from app.command.sub_command import SubCommand
from app.error.column_already_exists_error import ColumnAlreadyExistsError
from app.error.column_not_found_error import ColumnNotFoundError
class Add(SubCommand):
def __init__(self, args: Namesp... | takenoco82/alter_csv | src/app/command/add.py | add.py | py | 1,355 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "app.command.sub_command.SubCommand",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "argparse.Namespace",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "pandas.core.frame.DataFrame",
"line_number": 18,
"usage_type": "name"
},
{
... |
71551407784 | import matplotlib.pyplot as plt
from sklearn.manifold import TSNE
from textClustringAnalysis.feature.common import dict2Array, myTFIDF
from textClustringAnalysis.feature.main import TC, TC_PCA, PCA
from textClustringAnalysis.preprocessor.dataInfo import getWordCount
if __name__ == '__main__':
"""
当我们想要对高维数据进行... | bearbro/TextClusteringAnalysis | textClustringAnalysis/showdatafirst.py | showdatafirst.py | py | 2,127 | python | en | code | 3 | github-code | 36 | [
{
"api_name": "textClustringAnalysis.preprocessor.dataInfo.getWordCount",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "textClustringAnalysis.feature.main.TC_PCA",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "sklearn.manifold.TSNE",
"line_number": 21,... |
35206645553 | from django.contrib import admin
from .models import *
class CostInline(admin.TabularInline):
model = Cost
extra = 0
class CoordinatesAdmin(admin.ModelAdmin):
list_display = ('latitude', 'longitude')
class LanguageAdmin(admin.ModelAdmin):
list_display = ('name', 'population')
class CountryAdmin(admin.... | borisovodov/np | app/admin.py | admin.py | py | 4,586 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "django.contrib.admin.TabularInline",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "django.contrib.admin",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "django.contrib.admin.ModelAdmin",
"line_number": 10,
"usage_type": "attribute"... |
35809219103 | #! python2
# -*- coding: utf-8 -*-
import scrapy
import csv
import time
from sys import exit
import os
import logging
from scrapy import signals
from . import wikimallbottodbmy
import re
#from scrapy.utils.log import configure_logging
class WikimallbotSpider(scrapy.Spider):
name = 'wikimallbot'
allowed_do... | rizanurhadi/webscraping1 | spiders/wikimallbot.py | wikimallbot.py | py | 7,971 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "scrapy.Spider",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "os.path.dirname",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 19,
"usage_type": "attribute"
},
{
"api_name": "os.path.realpath",
... |
69845996905 | #!/usr/bin/env python
import pika
from pika.adapters import BlockingConnection
from pika import BasicProperties
#connection = BlockingConnection('172.20.14.192')
connection = pika.BlockingConnection(pika.ConnectionParameters('172.20.14.192'))
channel = connection.channel()
client_params = {"x-ha-policy": "all"}
exch... | appop/simple-test | createmessage/createqueue.py | createqueue.py | py | 654 | python | en | code | 2 | github-code | 36 | [
{
"api_name": "pika.BlockingConnection",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "pika.ConnectionParameters",
"line_number": 7,
"usage_type": "call"
}
] |
6435166822 | from collections import Counter
def maketemp(l,h):
templist = []
for i in range(l,h+1):
templist.append(i)
return templist
def themode(lst):
n = len(lst)
data = Counter(lst)
get_mode = dict(data)
mode = [k for k, v in get_mode.items() if v == max(list(data.values()))]
if len(mo... | DongjiY/Kattis | src/airconditioned.py | airconditioned.py | py | 1,012 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "collections.Counter",
"line_number": 11,
"usage_type": "call"
}
] |
30134924939 | import numpy as np
import datetime as dt
import sqlalchemy
from sqlalchemy.ext.automap import automap_base
from sqlalchemy.orm import Session
from sqlalchemy import create_engine, func, and_
from flask import Flask, jsonify
engine = create_engine("sqlite:///hawaii.sqlite")
base = automap_base()
base.prepare(engine,... | Emziicles/sqlalchemy-challenge | app.py | app.py | py | 2,364 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "sqlalchemy.create_engine",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "sqlalchemy.ext.automap.automap_base",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "flask.Flask",
"line_number": 19,
"usage_type": "call"
},
{
"api_name... |
2503764043 | #!/usr/bin/env python
# *********************
# webcam video stream
# *********************
import time
import cv2
# 0 - Dell Webcam
# cap = cv2.VideoCapture('filename.avi')
cap = cv2.VideoCapture(0)
pTime = 0
while (cap.isOpened()):
cTime = time.time()
ret, frame = cap.read()
if ret == True:
fp... | ammarajmal/cam_pose_pkg | script/webcam.py | webcam.py | py | 640 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "cv2.VideoCapture",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "time.time",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "cv2.putText",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "cv2.FONT_HERSHEY_PLAIN",
"... |
4877559988 |
import os
from fuzzywuzzy import fuzz
from fuzzywuzzy import process
import pandas
data = pandas.read_csv('C:\\Users\\aruny\\Downloads\\ezyzip\\MusicApp\\songs.csv')
data = data.to_dict('records')
song_names = [i['name'] for i in data]
dir = 'C:\playlist songs\Malayalam_sad_songs'
files = os.listdir(dir)
for song in ... | chmson/MusicApp_website | MusicApp/give_id.py | give_id.py | py | 1,094 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "pandas.read_csv",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "os.listdir",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "fuzzywuzzy.fuzz.ratio",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "fuzzywuzzy.fuzz",
... |
10603730701 | import argparse
import time , datetime
from pythonosc import udp_client
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--ip", default="127.0.0.1",
help="The ip of the OSC server")
parser.add_argument("--port", type=int, default=9000,
help="The port the OSC server... | kakuchrome/OSCscript | timer.py | timer.py | py | 968 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "pythonosc.udp_client.SimpleUDPClient",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "pythonosc.udp_client",
"line_number": 14,
"usage_type": "name"
},
{
"... |
7410224509 | from bs4 import BeautifulSoup
import requests
from selenium import webdriver
import re
import timeit
url = "https://www.investing.com/equities/trending-stocks"
driver = webdriver.Chrome(r"C:\Program Files\chromedriver.exe")
driver.get(url)
# x, stockPopularityData
page = driver.page_source
soup = BeautifulSoup(page, ... | SRI-VISHVA/WebScrapping | scrapping_73.py | scrapping_73.py | py | 1,915 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "selenium.webdriver.Chrome",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "selenium.webdriver",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "re.finda... |
1355556431 | import pygame
import os
import time
import random
x = 100
y = 50
os.environ['SDL_VIDEO_WINDOW_POS'] = "%d,%d" % (x,y)
width = 1640
height = 980
pygame.init()
screen = pygame.display.set_mode((width, height))
white = (255, 255, 255)
black = (0, 0, 0)
random_color = (random.randint(0, 255), random.ra... | MagicLuxa/Python-Projects | sorting algorithms visualized.py | sorting algorithms visualized.py | py | 4,028 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "os.environ",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "pygame.init",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "pygame.display.set_mode",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "pygame.display",
... |
37914230085 | from pathlib import Path
import json
import plotly.express as px
import numpy as np
# Read data as a string and convert to a Python object.
path = Path("eq_data/eq_data.geojson")
contents = path.read_text(encoding="utf-8")
all_eq_data = json.loads(contents)
# Examine all the earthquakes in dataset
all_eq_dicts = all... | hharpreetk/python-earthquake-data-viz | eq_explore_data.py | eq_explore_data.py | py | 1,615 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "pathlib.Path",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "numpy.min",
"line_number": 28,... |
23413820054 | # -*- coding: utf-8 -*-
"""
Create doc tree if you follows
:ref:`Sanhe Sphinx standard <en_sphinx_doc_style_guide>`.
"""
from __future__ import print_function
import json
from pathlib_mate import PathCls as Path
from .template import TC
from .pkg import textfile
class ArticleFolder(object):
"""
Represent... | MacHu-GWU/docfly-project | docfly/doctree.py | doctree.py | py | 5,328 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "pathlib_mate.PathCls",
"line_number": 44,
"usage_type": "call"
},
{
"api_name": "pathlib_mate.PathCls",
"line_number": 51,
"usage_type": "call"
},
{
"api_name": "pathlib_mate.PathCls",
"line_number": 58,
"usage_type": "call"
},
{
"api_name": "pathli... |
16567280409 | import tensorflow as tf
import keras
import numpy as np
import matplotlib.pyplot as plt
from keras.layers import Input, Dense, Lambda, InputLayer, concatenate, Dropout
from keras.models import Model, Sequential
from keras import backend as K
from keras import metrics
from keras.datasets import mnist
from keras.utils i... | tirthasheshpatel/Generative-Models | vae.py | vae.py | py | 3,413 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "tensorflow.InteractiveSession",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "keras.backend.set_session",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "keras.backend",
"line_number": 16,
"usage_type": "name"
},
{
"api_name": ... |
17079421444 | from glob import glob
from itertools import chain
import logging
from lib.language import canonicalize_tokens, clean_text, clean_tokens, tokenize_text
from lib.language.types import TokenStream
from lib.util import chain as chain_calls, extract_text
logger = logging.getLogger(__name__)
def tokenize_corpus(globby_p... | amy-langley/tracking-trans-hate-bills | lib/tasks/tokenize_corpus.py | tokenize_corpus.py | py | 752 | python | en | code | 2 | github-code | 36 | [
{
"api_name": "logging.getLogger",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "itertools.chain.from_iterable",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "itertools.chain",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "lib.u... |
34922299042 | """
shared dataloader for multiple issues
must gurantee that a batch only has data from same issue
but the batches can be shuffled
"""
import collections
from more_itertools import more
from numpy.core import overrides
import torch
from torch import tensor
import torch.nn as nn
import numpy as np
from torch.utils.data... | xymou/Frame_Detection | myprompt/myprompt/data/share_dataloader.py | share_dataloader.py | py | 7,930 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "random.shuffle",
"line_number": 40,
"usage_type": "call"
},
{
"api_name": "torch.utils.data.dataset.Dataset",
"line_number": 48,
"usage_type": "name"
},
{
"api_name": "torch.utils.data.sampler.Sampler",
"line_number": 60,
"usage_type": "name"
},
{
"... |
3327955898 | import argparse
import re
_re_pattern_value_unit = r"^\s*(-?\d+(?:.\d+)?)\s*([a-zA-Z]*?[\/a-zA-Z]*)$"
# this regex captures the following example normal(3s,1ms) with/without spaces between parenthesis and comma(s)
# it's also able to capture the sample duration specified after the distribution e.g., normal(3s,1ms) H 2... | connets/tod-carla | src/args_parse/parser_utils.py | parser_utils.py | py | 7,994 | python | en | code | 3 | github-code | 36 | [
{
"api_name": "re.compile",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "re.compile",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "re.compile",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "re.compile",
"line_number": 15,
... |
35198885002 | # -*- coding: utf-8 -*-
"""
Test to check api calls in in varonis assignment
"""
import json
import pytest
import requests
URL = "http://localhost:8000"
data = {
"data": [{"key": "key1", "val": "val1", "valType": "str"}]
}
credentials_data = {
"username": "test",
"password": "1234"
}
wron... | eldar101/EldarRep | Python/Varonis/api_assignment/test_api.py | test_api.py | py | 2,627 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "requests.post",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 52,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_number": 53,
"usage_type": "call"
},
{
"api_name": "requests.post",
"line_numbe... |
2769961219 | from weixin_api_two.api.contact.get_wework_token import WeworkToken
from weixin_api_two.uitls.get_data import GetData
import loguru
class Tag(WeworkToken):
def __init__(self):
self.baseurl=GetData()
self.log= loguru.logger
self.tagurl=self.baseurl.get_UrlData('url','tag')
self.add... | liwanli123/HogwartProjectPractice | weixin_api_two/api/externalcontact/tag_api.py | tag_api.py | py | 2,429 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "weixin_api_two.api.contact.get_wework_token.WeworkToken",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "weixin_api_two.uitls.get_data.GetData",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "loguru.logger",
"line_number": 10,
"usage_typ... |
73520719463 | from Functions import Functions
from log import Log
from webdriver import WebDriver
import PySimpleGUI as sg
import json
class Main:
def __init__(self):
self.ind = 0 # Indice utilizado para acessar o json.
self.log = Log() # Log de registro.
self.url = Functions().Json('Collector', 'ur... | LucasAmorimDC/SeleniumCollector | Selenium_Collector/Main.py | Main.py | py | 4,318 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "log.Log",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "Functions.Functions",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "webdriver.WebDriver",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "Functions.Functions",... |
38440361902 | import requests
from decouple import config
from django.contrib.auth.decorators import login_required
from django.shortcuts import render
@login_required(login_url='/accounts/login/')
def home(request):
disk = requests.get(config("API") + 'disk_space._')
load = requests.get(config("API") + 'system.load')
... | carlos-moreno/dashboard | dashboard/core/views.py | views.py | py | 950 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "requests.get",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "decouple.config",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "decouple.config",
"line_n... |
28984839741 | #! /usr/bin/env python
import argparse
import re
import numpy as np
def to_binary_string(value):
"""
Converts F or L to zeros, and B or R to 1 and interprets the string as a binary value
>>> to_binary_string("FBFBBFF")
('0101100', 44)
>>> to_binary_string("RLR")
('101', 5)
:param value:... | SocialFinanceDigitalLabs/AdventOfCode | solutions/2020/kws/day_05.py | day_05.py | py | 1,856 | python | en | code | 2 | github-code | 36 | [
{
"api_name": "re.sub",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "re.sub",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "argparse.ArgumentParser",
"line_number": 48,
"usage_type": "call"
},
{
"api_name": "argparse.FileType",
"line_n... |
12514324819 | import torch
from torchtext.datasets import AG_NEWS
from torchtext.data.utils import get_tokenizer
from torchtext.vocab import build_vocab_from_iterator
from torch.utils.data import DataLoader
UNK = '<unk>'
tok = get_tokenizer('basic_english')
train_iter = AG_NEWS(split='train')
def yield_tokens(data_iter, tokenizer... | moon0331/TorchTutorial | seq2seq.py | seq2seq.py | py | 1,590 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "torchtext.data.utils.get_tokenizer",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "torchtext.datasets.AG_NEWS",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "torchtext.vocab.build_vocab_from_iterator",
"line_number": 16,
"usage_type":... |
2346859029 | import numpy as np
from PIL import Image
# Goal: convert an image file from normal pixels to ANSI art made of dots "."
# of same color with canvas-like color background
# ANSI foreground color (n, 0-255) based on 256-bit -> \033[38;5;nm
# ANSI background color (n, 0-255) based on 256-bit -> \033[48;5;nm
# end with \0... | jakecharris/pointillism | source.py | source.py | py | 2,172 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "PIL.Image.open",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "PIL.Image",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "numpy.array",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "numpy.uint8",
"line_number":... |
15771336312 | import ctypes
import typing as t
from . import sdk
from .enum import Result
from .event import bind_events
from .exception import get_exception
from .model import UserAchievement
class AchievementManager:
_internal: sdk.IDiscordAchievementManager = None
_garbage: t.List[t.Any]
_events: sdk.IDiscordAchiev... | Maselkov/GW2RPC | gw2rpc/lib/discordsdk/achievement.py | achievement.py | py | 3,610 | python | en | code | 47 | github-code | 36 | [
{
"api_name": "typing.List",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "typing.Any",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "event.bind_events",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "model.UserAchievem... |
18665738715 | import os, requests
index_file_path = input("Enter Index file path with extension m3u8 : ")
index_file = open(index_file_path,'r')
indexes = index_file.read()
index_file.close()
output_file_path = input("Enter output file path : ")
output_file = open(output_file_path,'wb')
folder_path = input("Enter folder path ... | nkpro2000sr/m3u8ToVideo | m3u8tovideo.py | m3u8tovideo.py | py | 952 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "requests.get",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 37,
"usage_type": "attribute"
}
] |
36749002781 | import cv2
thres = 0.45 # Threshold to detect object
# hog = cv2.HOGDescriptor()
# hog.setSVMDetector(cv2.HOGDescriptor_getDefaultPeopleDetector())
#
# cv2.startWindowThread()
cap = cv2.VideoCapture(0)
### for IP CAM
# cap = cv2.VideoCapture('rtsp://admin:admin@192.168.1.108/',apiPreference=cv2.CAP_FFMPEG)
cap.set(... | Quant1766/detectObjects | main.py | main.py | py | 1,420 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "cv2.VideoCapture",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "cv2.dnn_DetectionModel",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "cv2.rectangle",
"line_number": 39,
"usage_type": "call"
},
{
"api_name": "cv2.putText",
... |
30055768931 | import argparse
import numpy as np
from Data import Data
from Experiment import Experiment
from FrameStackExperiment import FrameStackExperiment
if __name__=='__main__':
parser = argparse.ArgumentParser(description='Evaluate termination classifier performance')
parser.add_argument('filepath', type=str, help=... | jwnicholas99/option-term-classifier | run.py | run.py | py | 5,905 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "Data.Data",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "numpy.arange",
"line_number": 50,
"usage_type": "call"
},
{
"api_name": "FrameStackExperiment.Fr... |
17613252101 | import plotly.plotly as py
import plotly.graph_objs as go
from pymongo import MongoClient
import sys
import networkx as nx
import matplotlib.pyplot as plt
import matplotlib
from networkx.algorithms import approximation as approx
from nxpd import draw
from networkx.drawing.nx_agraph import graphviz_layout
client = Mongo... | diaaahmed850/snaproject | diaa.py | diaa.py | py | 5,831 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "pymongo.MongoClient",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "pymongo.MongoClient",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "plotly.plotly.sign_in",
"line_number": 52,
"usage_type": "call"
},
{
"api_name": "plotly.... |
24486912101 | """ Clean up of hail endpoint column in three steps:
- remove unused staging column
- remove now obsolete testing column
- make hail_endpoint_production non null
Revision ID: aa6d3d875f28
Revises: 8bd62cba881a
Create Date: 2020-11-17 09:28:10.910999
"""
from alembic import op
import sqlalchemy as sa
from sqlalchemy.d... | openmaraude/APITaxi | APITaxi_models2/migrations/versions/20201117_09:28:10_aa6d3d875f28_clean_hail_endpoints.py | 20201117_09:28:10_aa6d3d875f28_clean_hail_endpoints.py | py | 1,214 | python | en | code | 24 | github-code | 36 | [
{
"api_name": "alembic.op.drop_column",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "alembic.op",
"line_number": 23,
"usage_type": "name"
},
{
"api_name": "alembic.op.drop_column",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "alembic.op",... |
15098306537 | #
#
#
import pandas as pd
import geopandas as gpd
from zipfile import ZipFile
from pathlib import Path
import sys,time
def Read_Glob_Bldg( country_geojson ):
CACHE = './PICKLE'
DIR = Path( '/home/phisan/GeoData/GlobML_BldgFP' )
GEOJSON = DIR.joinpath( country_geojson )
STEM = GEOJSON.stem
PICKLE ... | phisan-chula/Thai_Bldg_Model | BreakProv_Bldg.py | BreakProv_Bldg.py | py | 2,944 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "pathlib.Path",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "pandas.read_pickle",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "geopandas.read_file",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "geopandas.read_fi... |
73456512104 | # -*- coding: utf-8 -*-
# Time : 2023/10/5 22:53
# Author : QIN2DIM
# GitHub : https://github.com/QIN2DIM
# Description:
import csv
from dataclasses import dataclass, field
from pathlib import Path
from typing import List
class Level:
first = 1
second = 2
third = 3
fourth = 4
fifth =... | QIN2DIM/hysterical_ticket | hysterical_ticket/component/bingo_ssq.py | bingo_ssq.py | py | 3,044 | python | en | code | 3 | github-code | 36 | [
{
"api_name": "typing.List",
"line_number": 58,
"usage_type": "name"
},
{
"api_name": "dataclasses.field",
"line_number": 72,
"usage_type": "call"
},
{
"api_name": "dataclasses.field",
"line_number": 73,
"usage_type": "call"
},
{
"api_name": "dataclasses.field",
... |
5511991110 |
import os
from re import M, search
from unicodedata import category
import requests
import json
import psycopg2
import itertools
from flask import Flask, render_template, request, flash, redirect, session, g, jsonify,url_for,abort
from sqlalchemy.exc import IntegrityError
from forms import LoginForm, UserAddForm, P... | MITHIRI1/Capstone-Project-1 | app.py | app.py | py | 8,123 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "flask.Flask",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "os.environ.get",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "os.environ",
"line_number": 22,
"usage_type": "attribute"
},
{
"api_name": "os.environ.get",
"line... |
32058791507 | from datetime import datetime
from binance_functions.client_functions.binance_client import CreateClient
from decouple import config
from settings.bot_settings import *
from multiprocessing import Pool
import timeit
import json
class HistoricalData:
def __init__(self):
if config('API_KEY') != None and con... | turancan-p/binance-trade-bot | collecting_functions/historical_data.py | historical_data.py | py | 2,183 | python | en | code | 25 | github-code | 36 | [
{
"api_name": "decouple.config",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "decouple.config",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "decouple.config",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "binance_functions.cli... |
6318280878 | # -*- coding: utf-8 -*-
"""
Created on Tue Jan 15 12:38:24 2019
@author: MHozayen
Simple Linear Regression
Weighted Linear Regression is commented out
"""
# Importing the libraries
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
def predict(x, y, pred):
#degree is u... | mohamedhozayen/Diabetes-Analytics-Engine | Joe_Deliverable/LR.py | LR.py | py | 772 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "numpy.ones",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "numpy.flip",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "sklearn.linear_model.LinearRegression",
"line_number": 29,
"usage_type": "call"
}
] |
3465936756 | import json, requests, subprocess, sys, yaml
from pip._vendor.distlib.compat import raw_input
class JiraClient():
board_status_to_env = {"Ready to Deploy": "QAX",
"QAX Done": "STGX",
"StgX Done": "PROD-EU",
"Prod EU Done": "PROD-US"... | mulesoft-labs/popeye | JiraClient.py | JiraClient.py | py | 9,957 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "requests.post",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "json.dumps",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 40,
"usage_type": "call"
},
{
"api_name": "requests.post",
"line_numbe... |
6637403650 | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.shortcuts import render, HttpResponse
# Create your views here.
def home_view(request):
if request.user.is_authenticated():
context = {
'isim': 'Emine'
}
else:
context = {
'isim': 'Gues... | emineksknc/veterinerim | home/views.py | views.py | py | 382 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "django.shortcuts.render",
"line_number": 17,
"usage_type": "call"
}
] |
34647682320 | from pathlib import Path
from uuid import uuid4
from django.core.validators import FileExtensionValidator
from django.db.models import (
CASCADE,
CharField,
DateField,
FileField,
ForeignKey,
IntegerChoices,
IntegerField,
Model,
TextField,
URLField,
)
from django.utils.translatio... | cuducos/fio-de-ariadne | web/core/models.py | models.py | py | 2,873 | python | en | code | 78 | github-code | 36 | [
{
"api_name": "uuid.uuid4",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "pathlib.Path",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "django.db.models.Model",
"line_number": 25,
"usage_type": "name"
},
{
"api_name": "django.db.models.Integ... |
25353856217 | import http.server
import socketserver
import cgi
import pymongo
import json
import bcrypt
import secrets
import hashlib
import base64
from datetime import datetime, timedelta
import helperFunction as helper
SOCKET_GUID = b'258EAFA5-E914-47DA-95CA-C5AB0DC85B11'
TEXT_FRAME = 1
OPCODE_MASK = 0b00001111
PAYLOAD_LEN_MASK ... | jackyzhu209/312-Project | website/httpserver.py | httpserver.py | py | 27,742 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "pymongo.MongoClient",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "helperFunction.gen_project_post_html_asbytes",
"line_number": 48,
"usage_type": "call"
},
{
"api_name": "helperFunction.get_mimetype",
"line_number": 95,
"usage_type": "call"
... |
36402183870 | from datetime import datetime, timedelta
date_format = "%d.%m.%Y"
print("Laenukalkulaator")
amount = None
while amount is None:
try:
amount = int(input("laenusumma (täisarv): "))
if amount <= 0:
print("Sisestatud väärtus peab olema suurem kui 0")
amount = None
except ... | marianntoots/Programmeerimine_2021 | laenukalkulaator.py | laenukalkulaator.py | py | 3,000 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "datetime.datetime.strptime",
"line_number": 47,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 47,
"usage_type": "name"
},
{
"api_name": "datetime.datetime",
"line_number": 68,
"usage_type": "call"
},
{
"api_name": "dateti... |
2909760362 | import streamlit as st
import leafmap.kepler as leafmap
import geopandas as gpd
def app():
st.title("Kaavoitetut rakennukset tyypeittäin")
st.markdown(
"""
Väritä, visualisoi ja filtteröi aineistoa kartan vasemmasta yläkulmasta avautuvan työkalupakin avulla.
"""
)
m = leafmap.Map(ce... | SanttuVP/SpatialPlanning_vizualization_streamlit | apps/rakennustyypit.py | rakennustyypit.py | py | 1,216 | python | fi | code | 0 | github-code | 36 | [
{
"api_name": "streamlit.title",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "streamlit.markdown",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "leafmap.kepler.Map",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "leafmap.kepler",
... |
20484377775 | from collections import Counter
# initializing string
test_str = "aabbbccde"
# using collections.Counter() to get
# count of each element in string
res = Counter(test_str)
# valuesList = list(res.values())
# # printing result
# str1 = str(res)
print(res)
keysList = list(res.keys())
print(keysList)
# pri... | prathammodi333/python-programs | pr1.py | pr1.py | py | 407 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "collections.Counter",
"line_number": 8,
"usage_type": "call"
}
] |
34987945802 | import sqlite3
import re
from gcpTalent import create_company
def sanitize_company_name(input_string):
# Replace spaces with underscores
sanitized_string = input_string.replace(' ', '_')
# Remove special characters using regular expression
sanitized_string = re.sub(r'[^a-zA-Z0-9_]', '', sanitized... | LoganOneal/job-scraper | gcp-talent/createCompanies.py | createCompanies.py | py | 1,099 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "re.sub",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "sqlite3.connect",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "gcpTalent.create_company",
"line_number": 40,
"usage_type": "call"
}
] |
70606642025 | import os
import sys
# 在linux会识别不了包 所以要加临时搜索目录
curPath = os.path.abspath(os.path.dirname(__file__))
rootPath = os.path.split(curPath)[0]
sys.path.append(rootPath)
import pandas as pd
import pymysql
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from clickhouse_sqlalchemy import make_sessio... | cgyPension/pythonstudy_space | 05_quantitative_trading_hive/util/DBUtils.py | DBUtils.py | py | 6,392 | python | en | code | 7 | github-code | 36 | [
{
"api_name": "os.path.abspath",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 4,
"usage_type": "attribute"
},
{
"api_name": "os.path.dirname",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "os.path.split",
"line_n... |
30222648461 | import torch.nn as nn
class RPN(nn.Module):
def __init__(self, input_channels, anchor_count):
super(RPN, self).__init__()
self.ContainsObjectClassifier = nn.Conv2d(
in_channels = input_channels,
out_channels = 2*anchor_count,
kernel_size = 1,
stride = 1,
padding = 0)
self.RegionRegressor = n... | jday96314/Kuzushiji | ImageProcessing/DualNetworkApproach/RegionProposal/RPN.py | RPN.py | py | 1,450 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "torch.nn.Module",
"line_number": 3,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 3,
"usage_type": "name"
},
{
"api_name": "torch.nn.Conv2d",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line_numbe... |
20736597554 | import random
import datetime
st = datetime.datetime.now()
tai_moji = 10 # 対象文字数
ke_moji = 2 # 欠損文字数
chance = 2 # 試行回数
def shutudai(alh):
moji = random.sample(alh, tai_moji)
print("対象文字", end = " ")
for i in moji:
print(i, end = " ")
print()
nai_moji = random.sample(moji, ke_moji)
p... | c0b2108596/ProjExD | ex01/alphabet.py | alphabet.py | py | 1,363 | python | ja | code | 0 | github-code | 36 | [
{
"api_name": "datetime.datetime.now",
"line_number": 3,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 3,
"usage_type": "attribute"
},
{
"api_name": "random.sample",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "random.sample... |
20715607582 | # HAPPY NEW YEAR... or something.
import re
from collections import defaultdict
from itertools import repeat
DIRECTIONS = {
'se': (.5, 1),
'sw': (-.5, 1),
'nw': (-.5, -1),
'ne': (.5, -1),
'e': (1, 0),
'w': (-1, 0),
}
def find_tile(reference):
reference = re.findall('se|sw|nw|ne|e|w', refer... | jonassjoh/AdventOfCode | 2020/24/day24.py | day24.py | py | 1,682 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "re.findall",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "itertools.repeat",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "collections.defaultdict",
"line_number": 30,
"usage_type": "call"
}
] |
22840825846 | import cv2
from skimage.measure import ransac
from skimage.transform import ProjectiveTransform, AffineTransform
import numpy as np
class FeatureExtractor(object):
def __init__(self, orbParam):
self.kpData = []
self.orb = cv2.ORB_create(orbParam)
def computeKpData(self, img):
kp, des ... | naurunnahansa/SLAM_implementation | featureExtractor.py | featureExtractor.py | py | 1,856 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "cv2.ORB_create",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "cv2.BFMatcher",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "cv2.NORM_HAMMING",
"line_number": 22,
"usage_type": "attribute"
},
{
"api_name": "numpy.float32",
... |
44649010863 | #!/usr/bin/env python
# coding: utf-8
import warnings
warnings.filterwarnings("ignore")
import numpy as np
import os
import pandas as pd
from divexplorer_generalized.FP_Divergence import FP_Divergence
DATASET_DIRECTORY = os.path.join(os.path.curdir, "datasets")
# # Import data
def abbreviateValue(value, abbrevia... | elianap/h-divexplorer | run_experiments_pruning.py | run_experiments_pruning.py | py | 11,632 | python | en | code | 2 | github-code | 36 | [
{
"api_name": "warnings.filterwarnings",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "import_process_datas... |
20112154408 | import argparse
import tflearn
import numpy as np
from processsing import Processing
from training import Training
class Prediction():
def __init__(self):
# Construct the Neural Network classifier and start the learning phase
training = Training()
net = training.buildNN()
self.mod... | Pierre-Assemat/DeepPoseIdentification | predictions/WorkInProgress/prediction_tflearn.py | prediction_tflearn.py | py | 1,534 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "training.Training",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "training.buildNN",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "tflearn.DNN",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"lin... |
17364039643 | # Imports from Third Party Modules
from bs4 import BeautifulSoup
from urllib2 import urlopen
BASE_URL = "http://www.portlandhikersfieldguide.org"
REGIONS = ['Gorge', 'Mount Hood', 'Central OR', 'OR Coast', 'East OR',
'South OR', 'Portland', 'SW WA', 'WA Coast']
REGION_INDEXS = [
'http://www.portlandhike... | RAINSoftwareTech/hiketheplanet | backend/datascrape.py | datascrape.py | py | 5,124 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "urllib2.urlopen",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 30,
"usage_type": "call"
}
] |
74332806822 | from time import sleep
import traceback
from django.forms import model_to_dict
from django.shortcuts import redirect, render
from .models import Transaction
from .form.CreateTransactionForm import CreateTransactionForm
from django.http import JsonResponse
from django.views.decorators.csrf import csrf_exempt
from F... | edwinlowxh/CZ3002---Advanced-Software-Engineering | FinApp/Transaction/views.py | views.py | py | 12,542 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "constants.START_DATE_QUERY_PARAM",
"line_number": 48,
"usage_type": "argument"
},
{
"api_name": "constants.END_DATE_QUERY_PARAM",
"line_number": 49,
"usage_type": "argument"
},
{
"api_name": "constants.INCOME_TABLE_HEADER",
"line_number": 50,
"usage_type": ... |
34116401936 | '''
Detects a grid.
'''
import ujson
import cv2
from math import floor
from operator import itemgetter
from argparse import ArgumentParser
from pytesseract import image_to_string
parser = ArgumentParser(description = 'Detect grid.')
parser.add_argument(
"-f",
"--filename",
dest = "filename",
help = "filename prefi... | pumpncode/mimoai | read-game.py | read-game.py | py | 12,747 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "cv2.imread",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "cv2.cvtColor",
"line_number": 38,
"usage_type": "call"
},
{
"api_name": "cv2.COLOR_BGR2GRAY",
... |
74172105702 | import math
import centrosome.outline
import numpy
import numpy.testing
import pytest
import skimage.measure
import skimage.segmentation
import cellprofiler_core.image
import cellprofiler_core.measurement
from cellprofiler_core.constants.measurement import (
EXPERIMENT,
COLTYPE_FLOAT,
C_LOCATION,
)
impo... | BodenmillerGroup/ImcPluginsCP | tests/test_measureobjectintensitymultichannel.py | test_measureobjectintensitymultichannel.py | py | 20,306 | python | en | code | 10 | github-code | 36 | [
{
"api_name": "cellprofiler_core.image.preferences.set_headless",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "cellprofiler_core.image.preferences",
"line_number": 24,
"usage_type": "attribute"
},
{
"api_name": "cellprofiler_core.image",
"line_number": 24,
"u... |
198052217 | from django.views import generic
from digifarming.models import User, Staff, Rating, \
RequestType, Commodity, Supply, \
Order, OrderItem, UserTrackingMovements, HarvestDispatch,FacilityType, Facility, \
JobTitle, JobShift, ArrivalView, DepartureView, CancellationView, \
TransportCategory, TransportTyp... | gatirobi/digifarming | digifarming/digifarming/views.py | views.py | py | 53,254 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "django.views.generic.ListView",
"line_number": 59,
"usage_type": "attribute"
},
{
"api_name": "django.views.generic",
"line_number": 59,
"usage_type": "name"
},
{
"api_name": "digifarming.models.ArrivalView",
"line_number": 62,
"usage_type": "name"
},
{... |
19288984909 | import tensorflow as tf
import numpy as np
from dataset import get_dataset, get_rotation_augmentor, get_translation_augmentor
from model import build_model
AUTOTUNE = tf.data.experimental.AUTOTUNE
dataset, num_classes = get_dataset()
model = build_model(num_classes)
model.load_weights('./saved_weights/weights')
rn... | wdecay/ShapeClassification | test_model.py | test_model.py | py | 640 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "tensorflow.data",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "dataset.get_dataset",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "model.build_model",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "model.load_w... |
6163296593 | '''
Classe wordCloudGenerator que a partir de um conjunto de token gera uma nuvem de palavra
Argumentos:
text: lista de token (preferencilmente geradas pela classe pdfReader) (OBRIGATORIO)
max_font_size: tamanho maximo das palavras na nuvem
max_words: numero maximo de palavras na nuvem
background_color: color de fundo... | InfoEduc/Automatizando-Pesquisas-Bibliometricas | wordCloudGenerator.py | wordCloudGenerator.py | py | 1,515 | python | pt | code | 1 | github-code | 36 | [
{
"api_name": "wordcloud.WordCloud",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.imshow",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 24,
"usage_type": "name"
},
{
"api_name": "matplo... |
18518883640 | import random
from multiprocessing import Pool
from ai_player import Ai_player
from deck import Deck
class Population:
"""
blackjack Ai player population
"""
POPULATION_SIZE = 400
BJ_ROUNDS = 50000
PARENT_SIZE = 5
MAX_THREADS = 40 # most efficient
def __init__(self):
def... | BenPVandenberg/blackjack-ai | Dustin_Marks/population.py | population.py | py | 2,112 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "ai_player.Ai_player",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "random.choices",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "ai_player.Ai_player",
"line_number": 39,
"usage_type": "call"
},
{
"api_name": "ai_player.Ai_p... |
38608858024 | # -*- coding: utf-8 -*-
"""
Created on Sun Feb 11 22:34:18 2018
@author: Roshan Zameer Syed
ID : 99999-2920
Description : Multivariate linear regression and backward elimination
"""
# Reading the dataset
import pandas as pd
data = pd.read_csv('Advertising.csv')
# Feature and response matrix
X = data.iloc[:,[1,2,3]].... | syedroshanzameer/Machine-Learning | Multi-variate Linear Regression/multiRegression.py | multiRegression.py | py | 1,600 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "pandas.read_csv",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "sklearn.model_selection.train_test_split",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "sklearn.linear_model.LinearRegression",
"line_number": 23,
"usage_type": "call"
... |
42245347977 | #!/usr/bin/python
# noinspection PyUnresolvedReferences
import json
import requests
from yoctopuce.yocto_api import *
from yoctopuce.yocto_display import *
from yoctopuce.yocto_anbutton import *
display_list = []
class SimpleXMBC(object):
def __init__(self, host, port, user, password):
self._password = ... | yoctopuce-examples/xbmc_remote | xbmc_remote.py | xbmc_remote.py | py | 6,386 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "requests.post",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "json.dumps",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_number": 76,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_number": 8... |
10167749049 | from socket_webserver import Socketserver
import json
# Creating server instance
server = Socketserver()
# Configuring host and port
server.host = '127.0.0.1'
server.port = 8080
""" Two example functions to return response. Upper one returns simple json response and lower one returns html response
You could cre... | miikalehtonen/pywebserver | main.py | main.py | py | 963 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "socket_webserver.Socketserver",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "json.dumps",
"line_number": 31,
"usage_type": "call"
}
] |
10625869502 | from typing import List
from eth_vertigo.incremental.store import MutationRecord, IncrementalMutationStore
from eth_vertigo.core import Mutation
class IncrementalRecorder:
def record(self, mutations: List[Mutation]) -> IncrementalMutationStore:
store = IncrementalMutationStore()
store.known_mutat... | JoranHonig/vertigo | eth_vertigo/incremental/record.py | record.py | py | 958 | python | en | code | 180 | github-code | 36 | [
{
"api_name": "typing.List",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "eth_vertigo.core.Mutation",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "eth_vertigo.incremental.store.IncrementalMutationStore",
"line_number": 9,
"usage_type": "call"
},
... |
6301592120 | # !/user/bin/env python
# -*- coding: utf-8 -*-
# @Time : 2020/5/12 21:11
# @Author : chineseluo
# @Email : 848257135@qq.com
# @File : run.py
# @Software: PyCharm
import os
from Common.publicMethod import PubMethod
import logging
from selenium.webdriver.common.by import By
from Base.baseBy import BaseBy
pub_... | chineseluo/app_auto_frame_v1 | ActivityObject/elemParams.py | elemParams.py | py | 5,248 | python | en | code | 11 | github-code | 36 | [
{
"api_name": "Common.publicMethod.PubMethod",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "os.path.dirname",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 16,
"usage_type": "attribute"
},
{
"api_name": "os.path.jo... |
24300694321 | from pyspark import SparkContext, SparkConf
from pyspark.sql import SQLContext, DataFrame
from pyspark.sql.functions import lit
from pyspark.sql.functions import split, explode, monotonically_increasing_id
import numpy as np
from numpy import linalg as LA
from scipy.sparse import csr_matrix
import json
import datetim... | SebasAndres/Recomendadores | src/sar/models/sar.py | sar.py | py | 8,299 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "sar.models.elastic.ElasticHelper",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "tqdm.notebook.trange",
"line_number": 48,
"usage_type": "call"
},
{
"api_name": "tqdm.notebook.trange",
"line_number": 78,
"usage_type": "call"
},
{
"api_na... |
22771811138 | # -*- coding: utf-8 -*-
# This file is part of CFVVDS.
#
# CFVVDS is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# (at your option) any later version.
#
# ... | swak/cardfight-vanguard-vds | printer.py | printer.py | py | 3,420 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "wx.Printout",
"line_number": 22,
"usage_type": "attribute"
},
{
"api_name": "wx.Printout.__init__",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "wx.Printout",
"line_number": 24,
"usage_type": "attribute"
},
{
"api_name": "wx.Font",
... |
31141721992 | '''
Analyse observation basket
'''
import argparse
import joblib
import pandas as pd
import apriori
import helpers
from rules import RuleGenerator
parser = argparse.ArgumentParser(description='Convert Halias RDF dataset for data mining')
parser.add_argument('minsup', help='Minimum support', nargs='?', type=float, de... | razz0/DataMiningProject | src/observation_basket_analysis.py | observation_basket_analysis.py | py | 1,225 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "apriori.NUM_CORES",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "helpers.read_observation_basket",
"line_number": 22,
"usage_type": "call"
},
{
"ap... |
36808206999 | import os
import copy
from typing import Dict, Union
from torch.utils.data import Dataset
import torchio as tio
from .subject_loaders import SubjectLoader
from .subject_filters import SubjectFilter, ComposeFilters
class SubjectFolder(Dataset):
""" A PyTorch Dataset for 3D medical data.
Args:
root: ... | efirdc/Segmentation-Pipeline | segmentation_pipeline/data_processing/subject_folder.py | subject_folder.py | py | 9,208 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "torch.utils.data.Dataset",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "subject_loaders.SubjectLoader",
"line_number": 38,
"usage_type": "name"
},
{
"api_name": "typing.Dict",
"line_number": 39,
"usage_type": "name"
},
{
"api_name": "su... |
38406688388 | import pandas as pd
import matplotlib.pyplot as plt
import re # regular expression
df = pd.read_csv('./csv/Travel details dataset.csv')
# drop the rows with missing values
df = df.dropna()
# [OPTIONAL] pick country name only after the comma
df['Destination'] = df['Destination'].apply(lambda x: x.split(', ')[1] if ',... | mbenkzz/pyt11kelompok13 | functions.py | functions.py | py | 4,955 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "pandas.read_csv",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "pandas.to_datetime",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "pandas.to_datetime",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "re.compile",
... |
19150508999 | import tensorflow as tf
from .util.datasetUtil import dataset , filelength
from tensorflow.keras.applications import VGG16,VGG19 ,InceptionV3
from .util.Callbacks import CustomCallback
import datetime
class inference_load():
def __init__(self,params,csvPath):
print(params)
self.csvPath = './dataset... | kococo-code/Tensorflow_Automatic_Training | server/api/inference/model.py | model.py | py | 4,512 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "datetime.datetime.now",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 23,
"usage_type": "attribute"
},
{
"api_name": "tensorflow.keras.applications.VGG16",
"line_number": 30,
"usage_type": "call"
},
{
"... |
4822893898 | import base64
import sys
from github import Github
ACCESS_TOKEN = ''
REPO_NAME = ''
ACCESS_TOKEN = sys.argv[1]
REPO_NAME = sys.argv[2]
g = Github(ACCESS_TOKEN)
repo = g.get_repo(REPO_NAME)
contents = repo.get_contents("/README.md")
contents_bkp = repo.get_contents("/docs/README.md")
base = contents.content
base = b... | BobAnkh/LinuxBeginner | scripts/sync.py | sync.py | py | 697 | python | en | code | 6 | github-code | 36 | [
{
"api_name": "sys.argv",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "sys.argv",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "github.Github",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "base64.b64decode",
"line_... |
16921327452 | #!/usr/bin/env python3
"""
Advent of Code 2022 - Elf Rucksack Reorganization
A given rucksack always has the same number of items in each of its two compartments
Lowercase item types a through z have priorities 1 through 26.
Uppercase item types A through Z have priorities 27 through 52.
Find the item type that appe... | CristiGuijarro/NN-aoc-2022 | scripts/elf_rucksack_priorities.py | elf_rucksack_priorities.py | py | 3,390 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "typing.List",
"line_number": 55,
"usage_type": "name"
},
{
"api_name": "argparse.ArgumentParser",
"line_number": 70,
"usage_type": "call"
}
] |
26409439119 |
class Solution:
def topKFrequent(self, words: List[str], k: int) -> List[str]:
dict = {}
res = []
lista = []
#哈哈！这个是我自己写的hash table计算单词出现的频率 牛逼吧
#但是性能没下面的好嘻嘻
'''
for i in words:
dict[i]=len([x for x in words if x == i])
'''
... | lpjjj1222/leetcode-notebook | 692. Top K Frequent Words.py | 692. Top K Frequent Words.py | py | 1,460 | python | zh | code | 0 | github-code | 36 | [
{
"api_name": "collections.Counter",
"line_number": 19,
"usage_type": "call"
}
] |
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