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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
40134161700 | import gevent.monkey
# If gevent is installed, it needs to monkey-patch the python sockets to cooperate (see documentation or this
# github issue https://github.com/gevent/gevent/issues/941).
gevent.monkey.patch_all()
import requests
import json
import urllib.parse as urlparse
from urllib.parse import parse_qs
"""
Bas... | NHSDigital/gp-connect-access-record-fhir-api | mediation_service/tests/performance/common/auth.py | auth.py | py | 3,435 | python | en | code | 2 | github-code | 7 | [
{
"api_name": "gevent.monkey.monkey.patch_all",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "gevent.monkey.monkey",
"line_number": 4,
"usage_type": "attribute"
},
{
"api_name": "gevent.monkey",
"line_number": 4,
"usage_type": "name"
},
{
"api_name": "r... |
5282760959 | """
通用工具函数
"""
import subprocess
import functools
import os
def _filepath_(surf: str = None):
"""
将参数名中带 path 的参数都换成据对路径
检查 outpath 的后缀名是不是 surf
:param surf: 后缀名字符串 ".mp4", ".m3u8", ".mov" 等
:return: 函数装饰器
"""
def ck_surf(fn):
"""
本装饰器的作用就是将函数中使用的路径变为绝对路径
"""
... | i-crux/x264codec | x264codec/_models/utils/utils_common.py | utils_common.py | py | 4,018 | python | zh | code | 35 | github-code | 7 | [
{
"api_name": "os.path.abspath",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 27,
"usage_type": "attribute"
},
{
"api_name": "os.path.abspath",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_numb... |
40131584587 | """This script implements a simplified map reduce solution for the purpose of comparing performance between
using threads and multiprocessing"""
def map_func(x):
""" Simple occurrence mapper """
return x, 1
def shuffle(mapper_out):
""" Organise the mapped values by key """
data = {}
for k, v in ... | hilariie/MapReduce | src/simple.py | simple.py | py | 2,889 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "os.path.dirname",
"line_number": 44,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 44,
"usage_type": "attribute"
},
{
"api_name": "os.path.abspath",
"line_number": 44,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line... |
72719244062 | import pandas as pd
import scipy.stats as ss
import sklearn.metrics as skmet
import numpy as np
def get_explanatory_indices(index, min_lag, max_lag):
# In append mode, the start index can always be 0
if max_lag is None:
start_idx = 0
else:
start_idx = max(index-max_lag, ... | jiawu/Roller | Swing/util/utility_module.py | utility_module.py | py | 6,107 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "numpy.setdiff1d",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "sklearn.metrics.explained_variance_score",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "sklearn.metrics",
"line_number": 33,
"usage_type": "name"
},
{
"api_name... |
71570731743 | import re
from orderedset import OrderedSet
from flask import Markup
from notifications_utils.columns import Columns
from notifications_utils.formatters import (
unescaped_formatted_list,
strip_html,
escape_html,
strip_dvla_markup,
)
class Placeholder:
def __init__(self, body):
# body sh... | govau/notify | utils/notifications_utils/field.py | field.py | py | 5,378 | python | en | code | 17 | github-code | 7 | [
{
"api_name": "re.compile",
"line_number": 52,
"usage_type": "call"
},
{
"api_name": "notifications_utils.formatters.strip_html",
"line_number": 77,
"usage_type": "name"
},
{
"api_name": "notifications_utils.formatters.escape_html",
"line_number": 78,
"usage_type": "name"... |
3611208466 | import psycopg2
from app.db_handler.db_setup import Database_handler
#create insatnce of the Database_handler
db = Database_handler()
class Text:
"""
This will help in the saving of text
"""
def __init__(self, text, sentiment):
"""
Initialize text and it's sentiment
"""
... | peterwade153/sniffy | app/db_handler/db_helper.py | db_helper.py | py | 740 | python | en | code | 1 | github-code | 7 | [
{
"api_name": "app.db_handler.db_setup.Database_handler",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "psycopg2.Error",
"line_number": 29,
"usage_type": "attribute"
}
] |
1875625937 | from flask import escape
def view_the_log() -> str:
with open('vsearch.log') as log:
contents = log.read()
four_strings = contents.split('|')
list_test= []
for i in range(4):
list_test.append(four_strings[i])
return print(escape(list_test))
view_the_log() | niceasitaka/vsearch-by-flask | webapp/test.py | test.py | py | 272 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "flask.escape",
"line_number": 10,
"usage_type": "call"
}
] |
72910837982 | #Boa:Frame:wxAtomClient
__author__ = "Joe Gregorio <http://bitworking.org/>"
__version__ = "Revision: 1.00"
__copyright__ = "Copyright (c) 2003 Joe Gregorio"
__license__ = """All Rights Reserved"""
from wxPython.wx import *
import atomClientAPI
import libxml2
from xml.sax.saxutils import escape
import St... | cdent/st-clients | atom/pyatom/wxAtomClientFrame.py | wxAtomClientFrame.py | py | 6,293 | python | en | code | 4 | github-code | 7 | [
{
"api_name": "atomClientAPI.interface",
"line_number": 85,
"usage_type": "call"
},
{
"api_name": "xml.sax.saxutils",
"line_number": 110,
"usage_type": "name"
},
{
"api_name": "xml.sax.saxutils.escape",
"line_number": 117,
"usage_type": "call"
},
{
"api_name": "xm... |
27179479378 | import requests
import pandas as pd
START_DATE = "2022-04-15"
END_DATE = "2023-01-01"
from yahoo_fin.stock_info import get_data as get_stock_data
from yahoo_fin.stock_info import tickers_sp500 as get_sp500
def collect_api(url, is_stock = False):
# Make a get request.
response = requests.get(url)
response_d = r... | galmercado/AnotherStockInTheWall | BackEnd/src/stockApi.py | stockApi.py | py | 4,383 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "requests.get",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "pandas.read_json",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "yahoo_fin.stock_info.g... |
34149390371 | import itertools
from AF import AF
class AFND(AF):
"""
Uma classe usada para representar autômatos finitos não-determinísticos
Extends
----------
classe AF
Attributes
----------
vertices: list
lista com os estados do autômato
transitions: dict
dicionário de transições do autômato
initial:... | Bredstone/Linguagens-Formais | src/AFND.py | AFND.py | py | 3,552 | python | pt | code | 2 | github-code | 7 | [
{
"api_name": "AF.AF",
"line_number": 4,
"usage_type": "name"
},
{
"api_name": "AF.AF.vertices",
"line_number": 32,
"usage_type": "attribute"
},
{
"api_name": "AF.AF",
"line_number": 32,
"usage_type": "name"
},
{
"api_name": "AF.AF.transitions",
"line_number":... |
43296057635 | from tkinter import *
import PIL
from PIL import Image, ImageDraw
import numpy as np
import cv2
from feed_forward import feed_forward_two
CIRCLE = 0
EGG = 1
HOUSE = 2
MICKEY = 3
QUESTION = 4
SAD = 5
SMILEY = 6
SQUARE = 7
TREE = 8
TRIANGLE = 9
types = ['circulo', 'huevo', 'casa', 'mickey', 'signo', 'triste', 'feliz'... | jav-ram/RN | canvas.py | canvas.py | py | 2,113 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "PIL.Image.open",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "PIL.Image",
"line_number": 29,
"usage_type": "name"
},
{
"api_name": "PIL.Image",
"line_number": 32,
"usage_type": "attribute"
},
{
"api_name": "numpy.asarray",
"line_num... |
71314552542 | from itertools import permutations
def solution(expression):
answer = 0
opers = ["+", "-", "*"]
priorities = [*map(list, permutations(opers))]
for priority in priorities:
first = expression.split(priority[0])
tmp = []
for item in first:
second = item.split(priorit... | ddb8036631/algorithm | src/프로그래머스_Level2/programmers_67257.py | programmers_67257.py | py | 607 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "itertools.permutations",
"line_number": 7,
"usage_type": "call"
}
] |
21561648346 | """
评估确定性策略π：若总点数之和>=20时不再要牌，即选择action=0；在总点数<20时要牌，即选择action=1
"""
import gym
from collections import defaultdict
import numpy as np
import sys
sys.path.append('..')
from utils import ob2state, plot_blackjack_values
env = gym.make('Blackjack-v1')
def generate_episode_from_policy(env, policy):
"""
执行以下策略π生成e... | hongliw/Reinforcement-Learning | Machine_Learning_Book/Chapter_16-4_model-free/16-4-1_monte_carlo/on-policy/monte_carlo_evaluate.py | monte_carlo_evaluate.py | py | 1,989 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "sys.path.append",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "gym.make",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "utils.ob2state",
"line_numbe... |
29396111949 | import typing
from sqlalchemy import (
create_engine,
MetaData
)
from databases import Database, DatabaseURL
metadata = MetaData()
class CustomDatabase(Database):
def __init__(self, url: typing.Union[str, "DatabaseURL"], *, force_rollback: bool = False, **options: typing.Any):
super().__init__(... | Mansur-Ashrapov/bot_for_dudes_on_sport | app/database/db.py | db.py | py | 560 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "sqlalchemy.MetaData",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "databases.Database",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "typing.Union",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "typing.Any",... |
73861589984 | #We will create a bot that opens Zoom at the time of our meeting
#pip3 install schedule
# If you have buttons to click on the screen, you jave to leverage another module that we have to import with "pyautogui"
import schedule
import time
import webbrowser
def open_link(link):
webbrowser.open(link)
def intro_to_... | debbycosoi/Zoombot | Zoombot.py | Zoombot.py | py | 818 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "webbrowser.open",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "webbrowser.open",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "webbrowser.open",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "schedule.every",
... |
18565190156 | """@package docstring
Model file that corresponds to all the data related logic
"""
from app import db
from sqlalchemy.dialects.postgresql import JSON
import enum
# Owner of datamap can be a farm or a user
class OwnerType(enum.Enum):
FARM = "farm"
USER = "user"
class EquipmentModel(db.Model):
id = db.Co... | dassico/StripeFarm | MappingService/app/models.py | models.py | py | 4,660 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "enum.Enum",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "app.db.Model",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "app.db",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "app.db.Column",
"line_num... |
31224491649 | from sklearn.metrics import accuracy_score, f1_score, precision_score, recall_score, roc_auc_score
from sklearn.svm import SVC
from preprocess import preprocess
X,Y = preprocess(dataset='lucene', do_smote = True)
sv1 = SVC(kernel='rbf')
sv1.fit(X['train'],Y['train'])
Y_predict = sv1.predict(X['test'])
print("F1 score... | gurudarshan266/FSS-HW-Group-P | Project/code/order.py | order.py | py | 808 | python | en | code | 1 | github-code | 7 | [
{
"api_name": "preprocess.preprocess",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "sklearn.svm.SVC",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "sklearn.metrics.f1_score",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "sklearn.... |
18327786899 | import streamlit as st
from pymongo import MongoClient
from descriptions.reindex_descr import ReindexDescr
__version__ = 'v2.2'
class AddWidgetsRu():
'''
Создание Streamlit-интерфейса.
'''
def __init__(self, version, authors):
with st.form(key='reindex'):
st.header(... | PlatonB/high-perf-bio | gui_streamlit/reindex_gui.py | reindex_gui.py | py | 3,176 | python | ru | code | 8 | github-code | 7 | [
{
"api_name": "streamlit.form",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "streamlit.header",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "streamlit.expander",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "streamlit.text",
... |
5679514496 | import datetime
import ipaddress
import json
import os
import requests
import signal
import sys
import time
import calculate_acf as myacf
import trans
import detect_abnormal as ab
import utils
# from pprint import pprint
class Blocking():
def __init__(self, ip):
self.path_all_json = "./all.json"
s... | taka8poyo/ssh_attack_firewall | firewall/blocking.py | blocking.py | py | 8,374 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "trans.transform_log",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "trans.sys_trans_dict",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "datetime.datetime.now",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "dateti... |
5117554669 | import logging
import os
import pytest
import sdk_cmd
import sdk_tasks
import sdk_utils
import spark_utils as utils
from tests.integration.fixture_kafka import KERBERIZED_KAFKA, KAFKA_PACKAGE_NAME, KAFKA_SERVICE_NAME, KEYTAB_SECRET
from tests.integration.fixture_kafka import get_kerberized_kafka_spark_conf, upload_jaa... | mesosphere/spark-build | tests/integration/test_kafka.py | test_kafka.py | py | 3,496 | python | en | code | 53 | github-code | 7 | [
{
"api_name": "logging.getLogger",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "os.path.dirname",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "os.path.abspath",
... |
267979566 | import pandas as pd
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression
from sklearn.tree import DecisionTreeRegressor
from sklearn.ensemble import RandomForestRegressor
from sklearn.svm import SVR
from sklearn.metrics import r2_score, mean_squared_e... | samyakkhatua/intelliSunBackend | newMain.py | newMain.py | py | 2,085 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "pandas.read_csv",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "sklearn.model_selection.train_test_split",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "sklearn.linear_model.LinearRegression",
"line_number": 21,
"usage_type": "call"
... |
15269550107 | import networkx as nx
import pandas as pd
import numpy as np
from active_semi_clustering.exceptions import EmptyClustersException
class AHCC:
def __init__(self, n_clusters=2):
self.n_clusters = n_clusters
def fit(self, X, y=None, ml=[], cl=[]):
if isinstance(X, pd.DataFrame):
... | heriosousa/active-constrained-clustering | active_semi_clustering/semi_supervised/pairwise_constraints/ahcc.py | ahcc.py | py | 3,403 | python | en | code | null | github-code | 7 | [
{
"api_name": "pandas.DataFrame",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "active_semi_clustering.exceptions.EmptyClustersException",
"line_number": 22,
"usage_type": "name"
},
{
"api_name": "networkx.number_connected_components",
"line_number": 25,
... |
8864127426 |
import loguru
from dataclasses import dataclass
from typing import Any, Callable, Optional, Tuple, TypeVar, Self
from autoboot.args import get_env_name
from autoboot.logging import Logging
from autoboot.plugin import AppPlugin
from autoboot.process import load_env_file, load_yaml_file
from autoboot.event import Applic... | yizzuide/autoboot | autoboot/applications.py | applications.py | py | 4,339 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "typing.TypeVar",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "typing.TypeVar",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "dataclasses.dataclass",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "typing.Optional",... |
32808557323 | # (c) AlenPaulVarghese
# -*- coding: utf-8 -*-
from pathlib import Path
from typing import Set
import fitz
from tools.scaffold import AbstractTask
class Extractor(AbstractTask):
def __init__(self, chat_id: int, message_id: int):
super().__init__(chat_id, message_id)
self.input_file: Path
... | alenpaulvarghese/pdf_bot | pdf_bot/tools/extractor.py | extractor.py | py | 1,248 | python | en | code | 1 | github-code | 7 | [
{
"api_name": "tools.scaffold.AbstractTask",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "pathlib.Path",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "typing.Set",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "pathlib.Path",
... |
1203803671 | import requests
import json
followers_file = open("followers.txt", "w+", encoding="utf-8")
following_file = open("following.txt", "w+", encoding="utf-8")
brief_dict = {}
cookie = '' #Here Paste Your Twitter Cookie
authorization = '' #Here Paste your Authoriaztion Token
csrf_token = '' #Here Paste you... | Samarth-2561/Twitter-Follower-Following-Scraper | twitter_data.py | twitter_data.py | py | 7,667 | python | en | code | 1 | github-code | 7 | [
{
"api_name": "json.dumps",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "json.dumps",
"line_number": 39,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 63,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": ... |
20306451363 | # tif to png convert
from PIL import Image
import glob
import os
Image.MAX_IMAGE_PIXELS = None
for name in glob.glob('*.tif'):
im = Image.open(name)
region = im.crop((0, 0, 16304, 16304))
name = str(name).rstrip(".tif")
region.save(name + '.png', 'PNG')
def crop_to_selection(src, dst, na... | nayemabs/keras_segmentation | utils/resize_img.py | resize_img.py | py | 515 | python | en | code | 1 | github-code | 7 | [
{
"api_name": "PIL.Image.MAX_IMAGE_PIXELS",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "PIL.Image",
"line_number": 5,
"usage_type": "name"
},
{
"api_name": "glob.glob",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "PIL.Image.open",
... |
7818782725 | from flask import Flask, render_template, request
from flask_sqlalchemy import SQLAlchemy
from datetime import datetime
app = Flask(__name__)
number = 0
@app.get('/')
def index():
return render_template('index.html')
@app.route('/submit', methods=['POST', 'GET'])
def submit():
number = request.form... | RonnieJohnston/Flask-Exercises | exercise-02/app.py | app.py | py | 557 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "flask.Flask",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "flask.render_template",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "flask.request.form.get",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "flask.request... |
15567639770 | # -*- coding: utf-8 -*-
"""
Created on 20190612
@author: dell
"""
"""========================
1. 将同一个Excel中的不同的sheet页，汇总到一个新的表格中
================================"""
import os
def file_name(file_dir):
file_name_lst=[]
for root,dirs,files in os.walk(file_dir):
file_name_lst.extend(files)
return fi... | shanggeshihun/prw | 合并工作表及工作簿.py | 合并工作表及工作簿.py | py | 1,342 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "os.walk",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "xlrd.open_workbook",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "xlsxwriter.Workbook",
"line_number": 44,
"usage_type": "call"
}
] |
74415646944 | import random
from myhdl import StopSimulation, block, enum, always, instance, Signal, intbv, delay
from mux import mux
random.seed(5)
randrange = random.randrange
t_state = enum('0', '1')
@block
def test_mux():
a = Signal(intbv(4))
b = Signal(intbv(6))
z = Signal(intbv(0))
sel = Signal(intbv(0))
... | JoseK21/HLS_MyHDL | _Project/MUX2x1/test_mux.py | test_mux.py | py | 978 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "random.seed",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "random.randrange",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "myhdl.enum",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "myhdl.Signal",
"line_nu... |
16072560783 | import logging as log
import ming
import argparse
import madsenlab.axelrod.utils as utils
import madsenlab.axelrod.data as data
import madsenlab.axelrod.analysis as analysis
import madsenlab.axelrod.rules as rules
import uuid
def setup():
global args, simconfig
parser = argparse.ArgumentParser()
parse... | mmadsen/axelrod-ct | simulations/sim-extensible-single.py | sim-extensible-single.py | py | 4,184 | python | en | code | 5 | github-code | 7 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "madsenlab.axelrod.utils.AxelrodExtensibleConfiguration",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "madsenlab.axelrod.utils",
"line_number": 34,
"usage_type":... |
34874006579 | import logging
import os
import torch
logger = logging.getLogger(__name__)
class Checkpointer:
"""A simple pytorch checkpointer.
Parameters
----------
model : torch.nn.Module
Network model, eventually loaded from a checkpointed file
optimizer : :py:mod:`torch.optim`, Optional
... | bioidiap/bob.ip.binseg | src/deepdraw/utils/checkpointer.py | checkpointer.py | py | 2,899 | python | en | code | 1 | github-code | 7 | [
{
"api_name": "logging.getLogger",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "os.path.realpath",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 32,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
"li... |
33090178804 | import re
import helper
# Sample public reports as a single string
reports = "Critical water shortage in our town demands immediate attention. Ministry of Environment, we need assistance night safety street"
# Define ministry agencies and their associated keywords
ministries = {
"Kementerian Pendidikan, Kebudayaa... | fmaulll/natural_language_processing | nlp.py | nlp.py | py | 2,355 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "helper.generate_keyword",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "helper.generate_keyword",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "helper.generate_keyword",
"line_number": 11,
"usage_type": "call"
},
{
"api_name":... |
3622129954 | from cursor.path import Path
from cursor.position import Position
from cursor.collection import Collection
from cursor.bb import BoundingBox
def test_bb_center():
bb = BoundingBox(100, 200, 300, 400)
cx, cy = bb.center()
assert cx == 200
assert cy == 300
def test_bb_center2():
bb = BoundingBox(-... | schwittlick/cursor | cursor/tests/test_bb.py | test_bb.py | py | 1,808 | python | en | code | 4 | github-code | 7 | [
{
"api_name": "cursor.bb.BoundingBox",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "cursor.bb.BoundingBox",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "cursor.bb.BoundingBox",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "curs... |
38552691719 | import pathlib
import zipfile
from io import BytesIO
import pandas as pd
import requests
from disentanglement_lib.config.unsupervised_study_v1.sweep import get_config
configs = get_config()
def get_model_info():
"""Retrieve information about the pre-trained models of "Challenging Common Assumptions in the Unsup... | bonheml/tc_study | tc_study/utils/models.py | models.py | py | 2,669 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "disentanglement_lib.config.unsupervised_study_v1.sweep.get_config",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame.from_dict",
"line_number": 29,
"usage_... |
13365761782 | import requests
from bs4 import BeautifulSoup
import time
import csv
import Sendmail
from datetime import date
urls = ["https://finance.yahoo.com/quote/AAPL?p=AAPL", "https://finance.yahoo.com/quote/AMZN?p=AMZN&ncid=yahooproperties_peoplealso_km0o32z3jzm" , "https://finance.yahoo.com/quote/GOOG?p=GOOG&ncid=yahooproper... | Prathamesh-Rathi/Web-Scrape-Bot | Scrape.py | Scrape.py | py | 1,632 | python | en | code | 2 | github-code | 7 | [
{
"api_name": "datetime.date.today",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "datetime.date",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "csv.writer",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line... |
4609082800 | from django.urls import path
from .views import (
index,
CarListView,
CarDetailView,
CarCreateView,
CarUpdateView,
CarDeleteView,
assign_user_to_car,
delete_user_from_car,
DriverListView,
DriverDetailView,
DriverCreateView,
ManufacturerListView,
ManufacturerCreateVie... | Y-Havryliv/taxi-service | taxi/urls.py | urls.py | py | 2,012 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "django.urls.path",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "views.index",
"line_number": 24,
"usage_type": "argument"
},
{
"api_name": "django.urls.path",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "views.ManufacturerL... |
42831591389 | import json
ds = ['ganesh', {'k1': {'k2': [1,2,3]}}, 'a', 13.4, 15]
print(json.dumps(ds)) # Dump as a string to screen
# Dump the DataStructure to a File
with open('json_out.json', 'w') as fh:
json.dump(ds, fh)
# Load the json from the File to Memory
ds1 = None
with open('json_out.json') as fh:
ds1 = json.l... | kvsrsastry/Docs_and_Code | Python/python_session_consolidated_scripts/json_play.py | json_play.py | py | 659 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "json.dumps",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "json.dump",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "json.load",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_number": 20,
... |
14099464757 | #!/usr/bin/env python3
import minimalmodbus
import config
import signal
import sys
import paho.mqtt.client as mqtt
import time
import binascii
import RPi.GPIO as GPIO
import serial
def signal_handler(sig, frame):
client.loop_stop() #stop the loop
print(time.strftime("%y%m%d%H%M%S") + "by, by...")
sys.exit... | sgersing73/Home-Automation | Powerstation/Scripts/Epever_ModbusToMqtt.py | Epever_ModbusToMqtt.py | py | 7,360 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "time.strftime",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "sys.exit",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "time.sleep",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "time.strftime",
"line_number": ... |
17102607562 | '''
File used to extract members of UNEP FI. From the extracted list, this file will determine whether a company is a member of UNEP FI
'''
# Install Relevant Libraries
# pip install openpyxl --upgrade --pre
# pip install fuzzywuzzy
# Import Libraries and UNEP FI data
import requests
import fuzzywuzzy as fw
fro... | putridar/esg-dashboard | Scripts/unep_fi.py | unep_fi.py | py | 1,330 | python | en | code | 12 | github-code | 7 | [
{
"api_name": "requests.get",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "fuzzywuzzy.fuzz.partial_ratio",
"line_number": 50,
"usage_type": "call"
},
{
"api_name": "fuzzywuz... |
7268427646 | # -*- coding: utf-8 -*-
"""
Input nom de jeu
"""
import tkinter as tk
import numpy as n
import pygame as p
import pygame.mixer as pm
import pygame.mixer_music as pmm
global Lmap
Lmap=[]
Map_dispo=10
# # Fonctions pour les menus # #
def Menu_principal():
global Menu
Menu = tk.Tk()
Menu.geometry("800x500")... | bperreyon/Projets-perso | Python/Escaping Game/Jeuv9.py | Jeuv9.py | py | 49,256 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "tkinter.Tk",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "tkinter.Frame",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "tkinter.GROOVE",
"line_number": 25,
"usage_type": "attribute"
},
{
"api_name": "tkinter.TOP",
"line_... |
6326298188 | import numpy as np
np.random.seed(0)
from bokeh.io import curdoc
from bokeh.layouts import widgetbox, row, column, gridplot
from bokeh.models import ColumnDataSource, Select, Slider
from bokeh.plotting import figure
from bokeh.palettes import Greys256
from bokeh.models.callbacks import CustomJS
from skimage.feature i... | holmgroup/BokehAppDemo | Flask_parameter_update/main.py | main.py | py | 5,662 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "numpy.random.seed",
"line_number": 2,
"usage_type": "call"
},
{
"api_name": "numpy.random",
"line_number": 2,
"usage_type": "attribute"
},
{
"api_name": "skimage.io.imread",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "skimage.color.rgb... |
72859249182 | import argparse
import logging
import os
import sys
from pathlib import Path
import numpy as np
import torch
sys.path.append(".")
from config import cfg
from train_ctl_model import CTLModel
from inference_utils import (
ImageDataset,
ImageFolderWithPaths,
calculate_centroids,
create_pid_path_index,
... | Ascend/ModelZoo-PyTorch | PyTorch/contrib/cv/classification/Centroids-reid/inference/create_embeddings.py | create_embeddings.py | py | 3,057 | python | en | code | 31 | github-code | 7 | [
{
"api_name": "sys.path.append",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "logging.basicConfig",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "os.environ.get",
... |
73911081182 | from collections import deque
from typing import List
class Solution:
def removeStones(self, stones: List[List[int]]) -> int:
visited = set()
points_by_row = {}
points_by_col = {}
for stone in stones:
points_by_row.setdefault(stone[0], set()).add(tuple(stone))
... | cs-cordero/interview-prep | leetcode/0947_most_stones_removed_with_same_row_or_column.py | 0947_most_stones_removed_with_same_row_or_column.py | py | 1,266 | python | en | code | 9 | github-code | 7 | [
{
"api_name": "typing.List",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "collections.deque",
"line_number": 22,
"usage_type": "call"
}
] |
72685155424 | from typing import List
from itertools import combinations, product
class Solution:
def beautifulSubsets(self, nums: List[int], k: int) -> int:
answer = len(nums)
for i in range(2, len(nums) + 1):
for comb in combinations(nums, i):
is_beautiful = True
fo... | daviddwlee84/LeetCode | Contest/LeetCodeWeeklyContest/WeeklyContest337/3/Naive_TLE.py | Naive_TLE.py | py | 614 | python | en | code | 15 | github-code | 7 | [
{
"api_name": "typing.List",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "itertools.combinations",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "itertools.product",
"line_number": 11,
"usage_type": "call"
}
] |
5986158358 | from flask import Flask, render_template, redirect, request
from flask_wtf import FlaskForm
from wtforms import StringField, SubmitField, SelectField, RadioField
from wtforms.validators import DataRequired
from datetime import datetime
app = Flask(__name__)
app.config["SECRET_KEY"] = '1234'
class q1Form(FlaskForm):
... | NCNU-Project/FlaskHW | exam_1.py | exam_1.py | py | 7,575 | python | zh | code | 0 | github-code | 7 | [
{
"api_name": "flask.Flask",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "flask_wtf.FlaskForm",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "wtforms.RadioField",
"line_number": 90,
"usage_type": "call"
},
{
"api_name": "wtforms.RadioField"... |
15850544373 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# @Time : 2021/3/8 18:37
# @Author : hzy
# @File : 14_最长公共前缀.py
# @Software: PyCharm
"""
编写一个函数来查找字符串数组中的最长公共前缀。
如果不存在公共前缀，返回空字符串""。
示例 1：
输入：strs = ["flower","flow","flight"]
输出："fl"
示例 2：
输入：strs = ["dog","racecar","car"]
输出：""
解释：输入不存在公共前缀。
提示：
0 <= str... | hzy0809/leetcode | leetcode/14_最长公共前缀.py | 14_最长公共前缀.py | py | 1,180 | python | zh | code | 0 | github-code | 7 | [
{
"api_name": "typing.List",
"line_number": 38,
"usage_type": "name"
}
] |
71667059103 | import requests
from bs4 import BeautifulSoup
import codecs
headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 5.1; rv:47.0) Gecko/20100101 Firefox/47.0',
'Accept':'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8'}
session = requests.Session()
urls = []
jobs = []
def get_html(url):
req = ses... | amyard/Django-Tests | Job_Parsing/scripts_parsing/work.py | work.py | py | 1,437 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "requests.Session",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 30,
"usage_type": "call"
}
] |
73171140384 | from django.urls import path
from . import views
urlpatterns = [
path('test/', views.Test, name='test'),
path('sign-up/', views.SignUp, name='signup'),
path('login/', views.Login, name='login'),
path('logout/', views.Logout, name='logout'),
path('donar-list/', views.DonorList, name='donor-list... | tayson13/BloodNet | project/urls.py | urls.py | py | 326 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "django.urls.path",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
... |
22023811869 | import math
import pandas as pd
import matplotlib.pyplot as plt
import networkx as nx
import numpy as np
from data_manager import DataManager
JRCODE = 11
class JRMap:
def __init__(self):
self.data_manager = DataManager(JRCODE)
self.graph = nx.Graph()
self.construct_graph()
def constru... | Njima1572/bluespring18 | scripts/jrmap.py | jrmap.py | py | 3,997 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "data_manager.DataManager",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "networkx.Graph",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.scatter",
"line_number": 48,
"usage_type": "call"
},
{
"api_name": "mat... |
25888822760 | #!/usr/bin/python3
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import argparse
import pandas as pd
import os
import sys
if __name__=="__main__":
parser = argparse.ArgumentParser(description='Filter for value stocks.')
parser.add_argument('stock... | alessandroferrari/StockCrawler | filter_bargains.py | filter_bargains.py | py | 2,688 | python | en | code | 2 | github-code | 7 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "os.path.expanduser",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 31,
"usage_type": "attribute"
},
{
"api_name": "os.path.exist... |
70959818782 | import threading
import json
import logging
# see https://stackoverflow.com/a/2390997
class SafeFileDict(dict): # dicts take a mapping or iterable as their optional first argument
def __init__(self, *args, **kwargs):
self.lock = threading.Lock()
self.update(*args, **kwargs)
self.doJournal = False
se... | bhautikj/jobChomper | jobChomper/safeFileDict.py | safeFileDict.py | py | 1,895 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "threading.Lock",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "logging.info",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "logging.warning",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "json.dumps",
"line_num... |
5155158178 | import numpy as np
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.feature_extraction.text import TfidfTransformer, CountVectorizer
from sklearn.linear_model import LinearRegression
from sklearn.preprocessing import PolynomialFeatures
from sklearn.pipeline import Pipeline
import pi... | SergeyZinkovich/rucode5 | main.py | main.py | py | 2,484 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "sklearn.pipeline.Pipeline",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "sklearn.feature_extraction.text.CountVectorizer",
"line_number": 31,
"usage_type": "call"
},
... |
26331731255 | import pandas as pd
import numpy as np
import matplotlib
import random
from matplotlib import pyplot as plt
matplotlib.use("Agg")
np.random.seed(42)
class Scaler():
def __call__(self,features, is_train=False):
'''
Arguments : features N X D all are numeric
'''
min=features.min(0)
ptp=features.ptp(0)
feat... | NihalSargaiya9/FML | LR.py | LR.py | py | 6,330 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "matplotlib.use",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "numpy.random.seed",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "numpy.random",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "numpy.power",
"li... |
16970114396 | import datetime
from models import Record
from settings import celery, db
from utils import get_response_status, parse_yml_files
@celery.on_after_configure.connect
def setup_periodic_tasks(sender, **kwargs):
for parsed_data in parse_yml_files()['urls']:
sender.add_periodic_task(parsed_data['delay'],
... | fiddlest1ck/Grabby | grabby.py | grabby.py | py | 615 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "utils.parse_yml_files",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "settings.celery.on_after_configure",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "settings.celery",
"line_number": 7,
"usage_type": "name"
},
{
"api_na... |
11754820317 | # -*- coding: utf-8 -*-
import os
import cv2
import shutil
import copy
import json
from mbhk_get_eye import get_label
from PIL import Image,ImageDraw
import numpy as np
labelDst = {"close_eyes": "闭眼", "yawn": "打哈欠", "phone": "打电话", "smoking": "吸烟", "sunglasses_block": "红外阻断",
"drink_water": "喝水", "toothpick... | 124451/eye_copen_close_other | show_label_on_image.py | show_label_on_image.py | py | 20,338 | python | en | code | 1 | github-code | 7 | [
{
"api_name": "os.walk",
"line_number": 71,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 73,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 73,
"usage_type": "attribute"
},
{
"api_name": "os.path.splitext",
"line_number... |
20298938200 | from functools import partial
from front.crude import Crudifier
mall = dict(
a=dict(one=1, two=2), b=dict(three=3, four=4), foo_output=dict(), bar_output=dict(),
)
crudifier = partial(Crudifier, mall=mall, include_stores_attribute=True)
@crudifier(param_to_mall_map=['a', 'b'], output_store='foo_output')
def foo(... | otosense/plunk | plunk/vf/extrude/crude/__init__.py | __init__.py | py | 546 | python | en | code | 1 | github-code | 7 | [
{
"api_name": "functools.partial",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "front.crude.Crudifier",
"line_number": 7,
"usage_type": "argument"
}
] |
12659187644 | import pytest
from .factories import NotificationFactory
pytestmark = pytest.mark.django_db
def test_user_can_query_notifications_unread_count(django_user_client, graphql_user_client):
NotificationFactory(recipient=django_user_client.user)
response = graphql_user_client("query { me { notificationsUnreadCou... | silverlogic/baseapp-backend | baseapp-notifications/baseapp_notifications/tests/test_graphql_queries.py | test_graphql_queries.py | py | 1,098 | python | en | code | 2 | github-code | 7 | [
{
"api_name": "pytest.mark",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "factories.NotificationFactory",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "factories.NotificationFactory",
"line_number": 17,
"usage_type": "call"
},
{
"api_na... |
70745109023 | '''
NGram Language Model
'''
from collections import Counter
from math import log10
from os import linesep
from itertools import product
import re
import random
class NGram(object):
'''
Implements an n-gram language model. Arguments:
-N: the size of the word tuple
-trainingdata: the file-like ... | mreese3/ngrams | ngram-master/NGram/NGram.py | NGram.py | py | 9,647 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "collections.Counter",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "collections.Counter",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "re.compile",
"line_number": 46,
"usage_type": "call"
},
{
"api_name": "re.findall",
"... |
17709818575 | import urllib
import webapp2
import jinja2
import os
import datetime
from google.appengine.ext import ndb
from google.appengine.api import users
from google.appengine.api import search
jinja_environment = jinja2.Environment(
loader=jinja2.FileSystemLoader(os.path.dirname(__file__) + "/templates"))
# This part fo... | jials/RollingGo | rollinggo.py | rollinggo.py | py | 8,538 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "jinja2.Environment",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "jinja2.FileSystemLoader",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "os.path.dirname",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "os.path",
... |
43049901021 | """
URL configuration for CaclPy project.
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/4.2/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'... | Bishesh-Khanal/CalcPy | CaclPy/urls.py | urls.py | py | 1,302 | python | en | code | 1 | github-code | 7 | [
{
"api_name": "django.urls.path",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "django.contrib.admin.site",
"line_number": 21,
"usage_type": "attribute"
},
{
"api_name": "django.contrib.admin",
"line_number": 21,
"usage_type": "name"
},
{
"api_name": "... |
23080594563 | import time
from copy import deepcopy
import tqdm
import torch
from torch import nn, optim
from torch.nn import functional as F
from cope import CoPE
from model_utils import *
from eval_utils import *
def train_one_epoch(model, optimizer, train_dl, delta_coef=1e-5, tbptt_len=20,
va... | FDUDSDE/CoPE | trainer.py | trainer.py | py | 3,524 | python | en | code | 5 | github-code | 7 | [
{
"api_name": "tqdm.tqdm",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "torch.no_grad",
"line_number": 68,
"usage_type": "call"
},
{
"api_name": "tqdm.tqdm",
"line_number": 69,
"usage_type": "call"
},
{
"api_name": "cope.CoPE",
"line_number": 77,
... |
12944566910 | # this is a correlation analysis using python to show how corrlation between two numerical values is done
import pandas as pd
import seaborn as sns
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
plt.style.use('ggplot')
from matplotlib.pyplot import figure
matplotlib.rcParams[... | holdendata/Data_analyst_project | correlation_in_python.py | correlation_in_python.py | py | 2,850 | python | en | code | 1 | github-code | 7 | [
{
"api_name": "matplotlib.pyplot.style.use",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.style",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 11,
"usage_type": "name"
},
{
"api_na... |
257833041 | #coding: utf-8
#Salut Jean-Hugues! J'ai choisi de "moissonner" la page de la Chambre des communes du Canada, qui contient les informations des 338 députés fédéraux.
#Je chercherai à obtenir quatre (parfois cinq) informations pour chacun de ces 338 députés : leur nom, parti politique, circonscription et la provincipe d... | sandrinevieira/edm4466-devoir3 | devoir3.py | devoir3.py | py | 3,473 | python | fr | code | 0 | github-code | 7 | [
{
"api_name": "requests.get",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "csv.writer",
"line_number": 64,
"usage_type": "call"
}
] |
72868390622 | from torchvision import datasets, transforms
import torch
import numpy as np
from torchvision import transforms
import os
from PIL import Image, ImageOps
import torch.npu
import os
NPU_CALCULATE_DEVICE = 0
if os.getenv('NPU_CALCULATE_DEVICE') and str.isdigit(os.getenv('NPU_CALCULATE_DEVICE')):
NPU_CALCULATE_DEVICE ... | Ascend/ModelZoo-PyTorch | PyTorch/dev/cv/image_classification/CDAR_ID2747_for_PyTorch/data_loader.py | data_loader.py | py | 2,069 | python | en | code | 31 | github-code | 7 | [
{
"api_name": "os.getenv",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "os.getenv",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "torch.npu.current_device",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "torch.npu",
"line_nu... |
39056286616 | from flask import Flask, render_template, request
from settings import Common
from flask_mail import Mail, Message
from smtplib import SMTPException
import yaml, os, re
import stripe
application = Flask(__name__)
application.config.from_object(Common)
mail = Mail(application)
stripe.api_key = application.config['STRI... | abdallahsoliman/FRN | app.py | app.py | py | 3,946 | python | en | code | 2 | github-code | 7 | [
{
"api_name": "flask.Flask",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "settings.Common",
"line_number": 9,
"usage_type": "argument"
},
{
"api_name": "flask_mail.Mail",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "stripe.api_key",
"l... |
7152967374 | import csv
import sys
from statistics import mean
input_file = sys.argv[1] # customer_finance.csv
output_file = sys.argv[2] # output_files/2_output_p.csv
packages = {} # structuring formatted data to dictionary
counters = {}
mean_value_package = {}
header_for_dict = ['소득', '금융자산', '부채', '순자산']
with open(input_f... | Meengkko/bigdata_python2019 | 04_bigdata/02_Standardization_Analysis/4.APP/2_calculate_statistic_by_category_v1.01.py | 2_calculate_statistic_by_category_v1.01.py | py | 2,972 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "sys.argv",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "sys.argv",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "csv.reader",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "statistics.mean",
"line_numb... |
74736372381 | import sys
from tqdm import tqdm
import math
import torch
import numpy as np
import matplotlib.pyplot as plt
import torch.cuda
#from sklearn.preprocessing import StandardScaler
from torch import nn
from torchvision.datasets import CIFAR10
from torch.utils.tensorboard import SummaryWriter
from ResNet_ import *
from clr... | theNNAx/Projects | ResNet50/main.py | main.py | py | 4,647 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "math.ceil",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "torch.utils.tensorboard.SummaryWriter",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "torch.device",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "tqdm.tqd... |
38156979270 | import mysql.connector
import yaml
import threading
from datetime import datetime
from transaction_state_enum import TransactionState
db = yaml.safe_load(open("yamls/db.yaml"))
class TransactionTable:
def __init__(self):
self.lock = threading.Lock()
transactions_db = mysql.connector.connect(
... | nikolaJov2605/DRS_CryptoMenjacnica | CryptoMenjacnica/transactions_db.py | transactions_db.py | py | 3,166 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "yaml.safe_load",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "threading.Lock",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "mysql.connector.connector.connect",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "mysql.... |
40058688271 | # Sanjay Santokee 81600051
from random import randrange, getrandbits
from socket import *
from itertools import repeat
def serverSetup():
c = socket(AF_INET, SOCK_STREAM)
host = gethostbyname('127.0.0.1')
port = 12346
host_addr = (host, port)
c.bind(host_addr)
c.listen(10)
pri... | SanjaySantokee/EncryptionAlgorithms | Miller-Rabin/Bob_Server.py | Bob_Server.py | py | 2,845 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "itertools.repeat",
"line_number": 42,
"usage_type": "call"
},
{
"api_name": "random.randrange",
"line_number": 43,
"usage_type": "call"
},
{
"api_name": "random.getrandbits",
"line_number": 47,
"usage_type": "call"
},
{
"api_name": "random.getrandbi... |
3762472635 | import multiprocessing
import queue
def worker_func(worker_index, input_queue, output_queue):
import time
while True:
try:
input = input_queue.get(timeout=5)
print("worker_index:" + str(worker_index) + " ")
print(input)
output_queue.put((worker_inde... | projectmayuki/AI | Sample/SimpleMultiProcess/SimpleMultiProcess.py | SimpleMultiProcess.py | py | 1,802 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "time.sleep",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "queue.Empty",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "multiprocessing.Manager",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "multiprocessing.P... |
74447289183 | # -*- coding: utf-8 -*-
"""
Created on Tue Nov 10 13:57:18 2020
@author: NCJ
"""
import numpy as np
import pandas as pd
from matplotlib import pyplot as plt
from sklearn.datasets.samples_generator import make_blobs
from sklearn.cluster import KMeans
import struct
import cv2
def intensity(img):
... | DGJonna97/Median_Cut_Algorithm | Python/test.py | test.py | py | 2,292 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "numpy.shape",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "numpy.shape",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "cv2.imread",
"line_number": 40,
"usage_type": "call"
},
{
"api_name": "cv2.IMREAD_COLOR",
"line_numbe... |
14345349500 | from flask import Flask, request, jsonify
from pymongo import MongoClient
import pandas as pd
from flask_cors import CORS
import analytics
app = Flask(__name__)
CORS(app)
# Configure MongoDB connection
client = MongoClient('MONGO_URL')
db = client['MichiganTeachers']
collection = db['FormTeachers']
collection1 = db['... | harshitakalva/TeacherSalaryAnalytics | my-app/backend/app.py | app.py | py | 3,501 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "flask.Flask",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "flask_cors.CORS",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "pymongo.MongoClient",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "flask.request.get_json"... |
21971136345 | import gradio as gr
import numpy as np
import torch
import requests
import random
import os
import sys
import pickle
from PIL import Image
from tqdm.auto import tqdm
from datetime import datetime
import diffusers
from diffusers import DDIMScheduler
from transformers import CLIPTextModel, CLIPTokenizer
import torch.n... | naver-ai/DenseDiffusion | gradio_app.py | gradio_app.py | py | 14,628 | python | en | code | 364 | github-code | 7 | [
{
"api_name": "diffusers.__version__",
"line_number": 25,
"usage_type": "attribute"
},
{
"api_name": "sys.exit",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "diffusers.StableDiffusionPipeline.from_pretrained",
"line_number": 79,
"usage_type": "call"
},
{
... |
33984568833 | from django.contrib.auth.models import AbstractUser
from django.db import models
from django.utils.translation import gettext_lazy as _
class User(AbstractUser):
class Role_choices(models.TextChoices):
USER = 'user', _('Пользователь')
ADMINISTRATOR = 'admin', _('Администратор')
username = mode... | Osolodkov1/foodgram-project-react | backend/foodgram/users/models.py | models.py | py | 1,234 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "django.contrib.auth.models.AbstractUser",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "django.db.models.TextChoices",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "django.db.models",
"line_number": 7,
"usage_type": "name"
},
... |
74465653024 | """
This file is a part of the 'Unnamed' source code.
The source code is distributed under the MIT license.
"""
from typing import Callable, Optional
import pygame
class FadeTransition:
def __init__(self, fade_in: bool, fade_speed: float, size: tuple[int, int]):
self.fade_in = fade_in
self.init_... | blankRiot96/pglib | pglib/transition.py | transition.py | py | 1,787 | python | en | code | 3 | github-code | 7 | [
{
"api_name": "pygame.Surface",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "typing.Optional",
"line_number": 41,
"usage_type": "name"
},
{
"api_name": "typing.Callable",
"line_number": 41,
"usage_type": "name"
},
{
"api_name": "pygame.Surface",
"... |
41349514454 |
"""
Title: Timeseries classification from scratch
Author: [hfawaz](https://github.com/hfawaz/)
Date created: 2020/07/21
Last modified: 2020/08/21
Description: Training a timeseries classifier from scratch on the FordA dataset from the UCR/UEA archive.
"""
"""
## Introduction
This example shows how to do timeseries cl... | Snaags/HPO-keras | TEPS-processing.py | TEPS-processing.py | py | 4,392 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "numpy.load",
"line_number": 55,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 56,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 57,
"usage_type": "call"
},
{
"api_name": "numpy.load",
"line_number": 60... |
34068440343 | import scrapy
from datetime import datetime
import locale
locale.setlocale(locale.LC_ALL, 'esp_esp')
class MalditaBulosSpdier(scrapy.Spider):
name = 'malditaBulosSpider'
start_urls = [
'https://maldita.es/malditobulo/1'
]
def parse(self, response):
for titularbulo in response.xpath(... | georgicacristianciobanoiu/Analisis-de-tendencias-y-opiniones-en-redes-sociales | tfg_python/spiders/spiders/spiders/malditabulos.py | malditabulos.py | py | 1,748 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "locale.setlocale",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "locale.LC_ALL",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "scrapy.Spider",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "scrapy.Request",
... |
2332993189 | import torch
import torch.nn.functional as F
from explaignn.heterogeneous_answering.graph_neural_network.answering.answering_factory import (
AnsweringFactory,
)
from explaignn.heterogeneous_answering.graph_neural_network.encoders.encoder_factory import (
EncoderFactory,
)
class HeterogeneousGNN(torch.nn.Mod... | saitouhao/srtp-gnn-explain | EXPLAIGNN-main/explaignn/heterogeneous_answering/graph_neural_network/hgnn.py | hgnn.py | py | 6,229 | python | en | code | 1 | github-code | 7 | [
{
"api_name": "torch.nn",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "explaignn.heterogeneous_answering.graph_neural_network.encoders.encoder_factory.EncoderFactory.get_encoder",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "explaignn.heterogeneous_... |
7096375247 | import sqlite3
data = [('Yphe', 'Yphe@compote.com', 0),
('Zirak', 'Zirak34@hibou.fr', 100),
('Tikal', 'twouini@music.fr', 50),
('Nyse', 'Niz@patate.com', 0)]
def main():
conn = sqlite3.connect('baseDonnees.db')
cur = conn.cursor()
cur.execute(
"CREATE TABLE IF NOT EXISTS J... | ARKANYOTA/Cours2022Git | notes/Nsi/TP3/main.py | main.py | py | 1,721 | python | en | code | 1 | github-code | 7 | [
{
"api_name": "sqlite3.connect",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "sqlite3.connect",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "sqlite3.connect",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "sqlite3.connect",
... |
6312670557 | import logging
from utils import logger
from PyInquirer import prompt
from FeatureExtraction.main import featureExtractor
from FramesExtraction.frameExtractor import frameExtractor
modules = ['Frame Extraction', 'Visual Features Extraction']
def getUserInput():
questions = [
{
'type': 'list',... | RecSys-lab/Multimodal-music-recommender | main.py | main.py | py | 892 | python | en | code | 3 | github-code | 7 | [
{
"api_name": "PyInquirer.prompt",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "logging.basicConfig",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "logging.INFO",
"line_number": 25,
"usage_type": "attribute"
},
{
"api_name": "utils.logger"... |
45357810677 | from django.urls import path
from posts import views
urlpatterns = [
path('',views.post_list),
path('login/', views.login),
path('posts/', views.post_list),
path('posts/<int:pk>/', views.post_detail),
path('posts/create', views.post_create),
path('posts/update', views.post_update),
path('po... | pirogramming/4th-assignment-saturday | posts/urls.py | urls.py | py | 500 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "django.urls.path",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "posts.views.post_list",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "posts.views",
"line_number": 5,
"usage_type": "name"
},
{
"api_name": "django.urls.path... |
71039913823 | import numpy
from .skimage import compare_ssim
import sys
## ======================= ##
##
class MetricSSIM:
## ======================= ##
##
@staticmethod
def compute_metrics(image1, image2):
image1 = image1.convert("RGB")
image2 = image2.convert("RGB")
np_... | golemfactory/clay | apps/blender/resources/images/entrypoints/scripts/verifier_tools/ssim.py | ssim.py | py | 920 | python | en | code | 2,915 | github-code | 7 | [
{
"api_name": "numpy.array",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "skimage.compare_ssim",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "sys.argv",
"line_num... |
5442135385 | import cv2
import keyboard
# haar files (face and smile)
face_detector_file = r"haarcascade_frontalface_default.xml"
face_detector = cv2.CascadeClassifier(face_detector_file)
smile_detector_file = r"haarcascade_smile.xml"
smile_detector = cv2.CascadeClassifier(smile_detector_file)
# access the webcam.
webcam= cv2.V... | Himanshu584/smile_detector | detector.py | detector.py | py | 1,775 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "cv2.CascadeClassifier",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "cv2.CascadeClassifier",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "cv2.VideoCapture",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "cv2.CAP_DS... |
16209565170 | """
Tests SparkML StringIndexer converter.
"""
import unittest
from pyspark.ml.feature import VectorAssembler
from onnxmltools import convert_sparkml
from onnxmltools.convert.common.data_types import FloatTensorType
from onnxmltools.utils import dump_data_and_sparkml_model
from sparkml import SparkMlTestCase
class Te... | Riponsayf/onnxmltools | tests/sparkml/test_vector_assembler.py | test_vector_assembler.py | py | 1,591 | python | en | code | null | github-code | 7 | [
{
"api_name": "sparkml.SparkMlTestCase",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "pyspark.ml.feature.VectorAssembler",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "onnxmltools.convert_sparkml",
"line_number": 19,
"usage_type": "call"
},
{... |
9418219068 | #coding:utf-8
'''
创建者：liu
作用：从jmeter脚本中提取url，头文件，发送的json数据，发送的方法等
使用方法：实例化的时候传入jmeter脚本。
创建日期：2017/7/20
'''
import os
import re
import json
import sys
from log import *
import logging
reload(sys)
sys.setdefaultencoding('utf8')
__dir__ = os.path.dirname(os.path.abspath(__file__))
jmeter_path = __dir__+... | liuchang6/API-test | AnalysisJmeter.py | AnalysisJmeter.py | py | 3,463 | python | en | code | 1 | github-code | 7 | [
{
"api_name": "sys.setdefaultencoding",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "os.path.dirname",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "os.path.abspath",... |
1990695923 | import torch
import os
class Policy(torch.nn.Module):
def __init__(self):
super().__init__()
self.hidden1 = torch.nn.Sequential(
torch.nn.Linear(in_features=110, out_features=256, bias=True),
torch.nn.Tanh()
)
self.hidden2 = torch.nn.Sequential(
... | navidmdn/f1tenth_rl | scripts/custom_policy.py | custom_policy.py | py | 1,400 | python | en | code | 2 | github-code | 7 | [
{
"api_name": "torch.nn",
"line_number": 4,
"usage_type": "attribute"
},
{
"api_name": "torch.nn.Sequential",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "torch.nn.Linear",
"l... |
32354544363 | from datetime import datetime
from flask import Flask, render_template, request, redirect
from flask_sqlalchemy import SQLAlchemy
from app.commands import add, subtract, multiply, divide
from app.validations import validate_number
app = Flask(__name__)
app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///database/calc... | Marius-prog/calculator | app/program.py | program.py | py | 2,642 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "app.commands",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "flask.Flask",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "app.commands.config",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "app.commands",
"l... |
2668210231 | from dataclasses import dataclass
from os.path import relpath, abspath
from .const import (
LIMITED,
NORMAL,
FULL,
)
from .utils import formatted_current_time, File, Directory
class Colors:
DARK_GRAY = "\x1b[38;5;8m"
LIGHT_GRAY = "\x1b[38;5;249m"
GREEN = "\x1b[38;5;40m"
YELLOW = "\x1b[38;... | michalpokusa/file-directory-watcher | src/file_directory_watcher/cli.py | cli.py | py | 4,097 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "dataclasses.dataclass",
"line_number": 32,
"usage_type": "name"
},
{
"api_name": "utils.formatted_current_time",
"line_number": 49,
"usage_type": "call"
},
{
"api_name": "utils.File",
"line_number": 54,
"usage_type": "name"
},
{
"api_name": "utils.D... |
30308226536 | import dash_bootstrap_components as dbc
import dash
import json
import pandas as pd
import requests
import datetime
import plotly.express as px
from dash import html, dcc, Input, Output, callback, State, no_update, dash_table
from auth import authenticate_user, validate_login_session
from flask import session
# Info ... | DMGochoa/final_prog102 | UI_web/pages/reports.py | reports.py | py | 6,190 | python | en | code | 2 | github-code | 7 | [
{
"api_name": "utils.data.Data_carrier",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "dash.html.Div",
"line_number": 48,
"usage_type": "call"
},
{
"api_name": "dash.html",
"line_number": 48,
"usage_type": "name"
},
{
"api_name": "dash.html.H2",
"l... |
25833809509 | # 1.keywords 3个都有, 2.按长度排序
import re
import scrapy
from copy import deepcopy
import tldextract
from scrapy.linkextractors import LinkExtractor
import xlrd
import io,sys
class SchoolspiderSpider(scrapy.Spider):
name = 'schoolspider'
allowed_domains = ['']
# sys.stdout = io.TextIOWrapper(sys.stdout.buffe... | zbuhui/anjuke | school_518/school/spiders/schoolspider.py | schoolspider.py | py | 14,419 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "scrapy.Spider",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "xlrd.open_workbook",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "scrapy.Request",
"line_number": 63,
"usage_type": "call"
},
{
"api_name": "copy.deepcopy",
... |
26176854597 | import pytest
import torch
from torch.utils.data import DataLoader
from torchvision import transforms
from torchvision.datasets import CIFAR10
from modeling.diffusion import DiffusionModel
from modeling.training import train_step
from modeling.unet import UnetModel
@pytest.fixture
def train_dataset():
tf = trans... | mryab/efficient-dl-systems | week02_management_and_testing/homework/tests/test_pipeline.py | test_pipeline.py | py | 1,296 | python | en | code | 467 | github-code | 7 | [
{
"api_name": "torchvision.transforms.Compose",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "torchvision.transforms",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "torchvision.transforms.ToTensor",
"line_number": 14,
"usage_type": "call"
},
{
... |
17129825080 | import os
import time
import json
from google.cloud import datastore
os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "./firstdemo-a214cb88e8b0.json"
dbclient = datastore.Client(project='firstdemo-207206')
kind = "Books"
def get_data(id):
'''Get data by Id'''
key = dbclient.key(kind, str(id))
return (dbc... | SouravAggarwal/gc_appengine | firebase_datastore/gcdatastore.py | gcdatastore.py | py | 667 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "os.environ",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "google.cloud.datastore.Client",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "google.cloud.datastore",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "g... |
14367897020 | import pytest
pytestmark = pytest.mark.asyncio
async def test_webhook_flow(test_cli_user):
guild = await test_cli_user.create_guild()
channel = await test_cli_user.create_guild_channel(guild_id=guild.id)
resp = await test_cli_user.post(
f"/api/v6/channels/{channel.id}/webhooks", json={"name": "a... | dolfies/patchcord | tests/test_webhooks.py | test_webhooks.py | py | 1,018 | python | en | code | 39 | github-code | 7 | [
{
"api_name": "pytest.mark",
"line_number": 3,
"usage_type": "attribute"
}
] |
75026562143 | def applyRegexsToDirOfXML(directoryPath,stringPhraseList,fieldsSelect,caseSensitive=False):
"""
Applies a regex search to the list of inputTexts and a dictionary wherein the keys are a tuple of the string phrase and the file name and the values are booleans indicating whether the string phrase was found in the ... | DanNBullock/USG_grants_crawl | src/daskFuncs.py | daskFuncs.py | py | 19,126 | python | en | code | 1 | github-code | 7 | [
{
"api_name": "os.listdir",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "dask.bag.from_sequence",
"line_number": 39,
"usage_type": "call"
},
{
"api_name": "dask.bag",
"line_number": 39,
"usage_type": "name"
},
{
"api_name": "os.path.join",
"line_n... |
41345218528 | #!/usr/bin/env python3
"""
Usage:
git-cloner [ -n ] [ --workspace <folder> ] <url>
Options:
--workspace <folder> The default folder we extract sites to [default: ~/projects]
-n Dry run - show what you would do
"""
# ~/.gitconfig
# [alias]
# cloner = !~/bin/git-cloner.py
import s... | rbuckland/workstation | HOME/bin/git-cloner.py | git-cloner.py | py | 1,269 | python | en | code | 0 | github-code | 7 | [
{
"api_name": "urllib.parse.urlparse",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "urllib.parse.urlparse",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "os.path.dirname",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "os.path",... |
14131602097 | #######################################################################
## (C)Copyright 2023 Hewlett Packard Enterprise Development LP
## 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
##... | HewlettPackard/swarm-learning | lib/src/python-client/swarmlearning/com/bridge.py | bridge.py | py | 9,747 | python | en | code | 286 | github-code | 7 | [
{
"api_name": "typing.Union",
"line_number": 29,
"usage_type": "name"
},
{
"api_name": "swarmlearning.com.swifrpc_pb2.Status",
"line_number": 30,
"usage_type": "attribute"
},
{
"api_name": "swarmlearning.com.swifrpc_pb2",
"line_number": 30,
"usage_type": "name"
},
{
... |
72869771742 | from torch import nn
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from tensormask import _C
class _SwapAlign2Nat(Function):
@staticmethod
def forward(ctx, X, lambda_val, pad_val):
ctx.lambda_val = lambda_val
ctx.input_shape = X.size()
Y ... | Ascend/ModelZoo-PyTorch | PyTorch/dev/cv/image_classification/SlowFast_ID0646_for_PyTorch/detectron2/projects/TensorMask/tensormask/layers/swap_align2nat.py | swap_align2nat.py | py | 2,032 | python | en | code | 31 | github-code | 7 | [
{
"api_name": "torch.autograd.Function",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "tensormask._C.swap_align2nat_forward",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "tensormask._C",
"line_number": 14,
"usage_type": "name"
},
{
"api_nam... |
2644067387 | # -*- coding: utf-8 -*-
# Define your item pipelines here
#
# Don't forget to add your pipeline to the ITEM_PIPELINES setting
# See: https://doc.scrapy.org/en/latest/topics/item-pipeline.html
from pymongo import MongoClient
client = MongoClient()
collection = client["douban"]["movie"]
class DoubanPipeline(object):... | Xiao-X-Qiang/Python_Coding | Spider/douban_work/douban/pipelines.py | pipelines.py | py | 491 | python | en | code | 2 | github-code | 7 | [
{
"api_name": "pymongo.MongoClient",
"line_number": 10,
"usage_type": "call"
}
] |
36759247256 | #!/usr/bin/env python3
# -*- coding: UTF-8 -*-
from utils import connection_util
class DataCollection(object):
def __init__(self):
self._target_url = 'https://www.scrapingbee.com/blog/'
self._init_connection = connection_util.ProcessConnection()
def main(self):
# 连接目标网站，获取内容
... | sycct/Scrape_1_1 | data_collection.py | data_collection.py | py | 1,302 | python | en | code | 4 | github-code | 7 | [
{
"api_name": "utils.connection_util.ProcessConnection",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "utils.connection_util",
"line_number": 10,
"usage_type": "name"
}
] |
28901170930 | import data
import question_model
import quiz_brain
question_bank = []
for question in data.question_data:
q = question_model.Question(question["question"], question["correct_answer"])
question_bank.append(q)
quiz = quiz_brain.QuizBrain(question_bank)
while quiz.still_has_questions():
quiz.next_questio... | arsovskidev/100-days-of-code | day-017/project/main.py | main.py | py | 422 | python | en | code | 4 | github-code | 7 | [
{
"api_name": "data.question_data",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "question_model.Question",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "quiz_brain.QuizBrain",
"line_number": 11,
"usage_type": "call"
}
] |
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