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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
20644437454 | import numpy as np
import open3d as o3d
import os
import torch
import torch.nn as nn
import torch.nn.functional as F
import sys
BASE_DIR = os.path.dirname(os.path.abspath(__file__))
ROOR_DIR = os.path.dirname(BASE_DIR)
sys.path.append(ROOR_DIR)
from utils import batch_transform, angle
from models import gather_points... | zhulf0804/ROPNet | src/models/TFMR.py | TFMR.py | py | 10,333 | python | en | code | 51 | github-code | 1 | [
{
"api_name": "os.path.dirname",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "os.path.abspath",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "os.path.dirname",
"line... |
71109526434 | import numbers
import datetime as dt
def get_sample_count(profileDict):
"""
Gets the number of samples taken from a dictionary representing data from an
Arm MAP file
Args:
profileDict (dict): Dictionary from which to obtain the count of samples
Returns:
The number of samples taken... | arm-hpc/allinea_json_analysis | MAP_JSON_Scripts/map_json_common.py | map_json_common.py | py | 19,968 | python | en | code | 3 | github-code | 1 | [
{
"api_name": "numbers.Number",
"line_number": 480,
"usage_type": "attribute"
},
{
"api_name": "datetime.datetime.strptime",
"line_number": 557,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 557,
"usage_type": "attribute"
},
{
"api_name... |
15654363718 | import gzip
import pickle
import tensorflow as tf
import numpy as np
# Translate a list of labels into an array of 0's and one 1.
# i.e.: 4 -> [0,0,0,0,1,0,0,0,0,0]
def one_hot(x, n):
"""
:param x: label (int)
:param n: number of bits
:return: one hot code
"""
if type(x) == list:
x = ... | adrianmesa93/practica2-fsi | nn_mnist.py | nn_mnist.py | py | 3,885 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "numpy.array",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "numpy.arange",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "gzip.open",
"line_number": 2... |
36261614433 | from setuptools import setup
with open("README.md") as file:
long_description = file.read()
setup(
include_package_data=True,
name='ginz',
version='1.1',
license="MIT",
description='Ginz is a command-line utility that simplifies the process of cloning multiple repositories from GitHub by allow... | happer64bit/ginz-cli | setup.py | setup.py | py | 726 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "setuptools.setup",
"line_number": 6,
"usage_type": "call"
}
] |
74363230754 | import base64
import json
import requests
class VisionUtils:
def __init__(self):
self.endpoint_url = 'https://vision.googleapis.com/v1/images:annotate'
self.api_key = 'AIzaSyCSqfhtZXwEy8JxJRtUYm31YWLC1aACUMg'
def __make_request(self, img_path, feature_type):
request_list = []
... | drimyus/GoogleCloudAPI | vision_utils.py | vision_utils.py | py | 2,022 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "base64.b64encode",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "json.dumps",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "requests.post",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_numb... |
20597467269 | #!/usr/bin/env python3
#
# Project homepage: https://github.com/mwoolweaver
# Licence: <http://unlicense.org/>
# Created by Michael Woolweaver <m.woolweaver@icloud.com>
# ================================================================================
import os
from inspect import getframeinfo, stack
from sqlite3 impo... | mwoolweaver/listManager.py | lib/debug.py | debug.py | py | 3,700 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "os.system",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "os.path.isdir",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 19,
"usage_type": "attribute"
},
{
"api_name": "argparse.ArgumentParser",
"l... |
20179427993 | import codecs
import atexit
from flask import Flask,render_template
import urllib3
import requests
import csv
from flask_crontab import Crontab
import pandas as pd
app = Flask(__name__)
cron=Crontab(app)
class LocationsData:
def __init__(self,state='NA',country='NA',latestCount=0,prevDayCount=0):
self.s... | ayush0407/Corona-Stats | app.py | app.py | py | 1,661 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "flask.Flask",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "flask_crontab.Crontab",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "csv.DictReader",
"... |
32198374896 | from django.urls import path
from response.slack import views
urlpatterns = [
path("slash_command", views.slash_command, name="slash_command"),
path("action", views.action, name="action"),
path("event", views.event, name="event"),
path("cron_minute", views.cron_minute, name="cron_minute"),
path("c... | monzo/response | response/slack/urls.py | urls.py | py | 372 | python | en | code | 1,487 | github-code | 1 | [
{
"api_name": "django.urls.path",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "response.slack.views.slash_command",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "response.slack.views",
"line_number": 6,
"usage_type": "name"
},
{
"api_na... |
26741822791 | # A library for streamlining ML processes
# by Matthew Mauer
# last editted 2020-05-10
'''
EDITS TO COME:
- more exception handling!!!
- more Grid Parameters in SupervisedLearner
- an UnsupervervisedLearner...
'''
import pandas as pd
import numpy as np
import datetime
import matplotlib.pyp... | mrmauer/pipelines | Python/supervised_pipeline.py | supervised_pipeline.py | py | 13,284 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "pandas.read_csv",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "numpy.nan",
"line_number": 41,
"usage_type": "attribute"
},
{
"api_name": "seaborn.pairplot",
"line_number": 52,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.fig... |
4484391480 | import requests
import os
config_path = os.path.join(os.getcwd() + '\Config\\token.md')
def getHeaders():
'''获取headers'''
return { 'Parkingwang-Client-Source': 'ParkingWangAPIClientWeb',
'Authorization': getToken()}
def login(url,params):
try:
url = "http://dykttest.zsyky.cn:9999" +... | wfamzing/Test_API | config/gettoken.py | gettoken.py | py | 1,404 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "os.path.join",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "os.getcwd",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "requests.post",
"line_number": 1... |
959248874 | '''LiteMobileNet in PyTorch.
See the paper "MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications"
for more details.
'''
from torch.nn import init
import torch.nn as nn
import math
import torch
import collections
import torch.nn.functional as F
class Block(nn.Module):
'''Depthwise co... | AlexanderParkin/CASIA-SURF_CeFA | rgb_track/models/architectures/lite_mobilenet.py | lite_mobilenet.py | py | 3,585 | python | en | code | 149 | github-code | 1 | [
{
"api_name": "torch.nn.Module",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "torch.nn.Conv2d",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line_nu... |
23167920981 | import os
import tensorflow as tf
from scipy import misc
import numpy as np
import random
import sys
import io
def to_rgb(img):
if img.ndim < 3:
h, w = img.shape
ret = np.empty((h, w, 3), dtype=np.uint8)
ret[:, :, 0] = ret[:, :, 1] = ret[:, :, 2] = img
return ret
else:
... | luckycallor/InsightFace-tensorflow | data/classificationDataTool.py | classificationDataTool.py | py | 4,902 | python | en | code | 246 | github-code | 1 | [
{
"api_name": "numpy.empty",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "numpy.uint8",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "tensorflow.shape",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "tensorflow.image.random... |
16779028414 | import numpy as np
import cv2
import math
def calculate_hs_histogram(img, bin_size):
height, width, _ = img.shape
img_hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
max_h = 179
max_s = 255
hs_hist = np.zeros((math.ceil((max_h+1)/bin_size), math.ceil((max_s+1)/bin_size)))
for i in range(he... | Tano-Coppoletta/Computer_vision | color_segmentation/main.py | main.py | py | 1,453 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "cv2.cvtColor",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "cv2.COLOR_BGR2HSV",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "numpy.zeros",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "math.ceil",
"line_n... |
19448146036 | from string import Template
import smtplib
import os
from os.path import basename
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
from email.mime.application import MIMEApplication
SMTP_SERVER = "smtp.gmail.com"
SMTP_PORT = 465
EMAIL_ADDRESS = os.environ.get('EMAIL_USER')
EMAIL_PAS... | jakobOB/Automate-Email | main.py | main.py | py | 2,430 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "os.environ.get",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "os.environ",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "os.environ.get",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "os.environ",
"line_... |
20041132401 | import sys
import matplotlib.pyplot as plt
import pickle
from scapy.all import rdpcap
from math import log
import numpy as np
broadcast_address = 'ff:ff:ff:ff:ff:ff'
def dict_add(dic, key):
if key in dic:
dic[key] += 1
else:
dic[key] = 1
def tipo(n):
if str(n) in types:
return typ... | alejandroFerrante/TP_Redes_Wiretapping | plot_entropia_s1.py | plot_entropia_s1.py | py | 1,461 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "pickle.load",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "scapy.all.rdpcap",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "sys.argv",
"line_number": 24,
"usage_type": "attribute"
},
{
"api_name": "math.log",
"line_numbe... |
32396192117 | import asyncio
from websockets import server
from threading import Thread
import logging
from datetime import datetime
import numpy as np
logging.basicConfig(filename='controlador.log',
# w -> sobrescreve o arquivo a cada log
# a -> não sobrescreve o arquivo
... | felipe-junior/ExclusaoMutuaDistribuida | app.py | app.py | py | 3,536 | python | pt | code | 1 | github-code | 1 | [
{
"api_name": "logging.basicConfig",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "logging.INFO",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "logging.getLogger",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
... |
73872794272 | import json
import pandas as pd
import requests
from common.utils import *
from tushare_client.base import AbstractDataRetriever
from tushare_client.stock_calendar import StockCalendar
stock_index_map = {
's50': ('stock_index_s50', '000016'),
'h300': ('stock_index_h300', '000300'),
'z500': ('stock_index_... | xiekeng/tushare-client | tushare_client/stock_index.py | stock_index.py | py | 2,526 | python | en | code | 6 | github-code | 1 | [
{
"api_name": "tushare_client.base.AbstractDataRetriever",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "tushare_client.stock_calendar.StockCalendar",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "requests.post",
"line_number": 48,
"usage_type": "c... |
28097719889 | import logging
import pathlib
from unittest.mock import patch
from rest_framework.test import APITestCase
logger = logging.getLogger(__name__)
class TestTemplates(APITestCase):
def test_when_get_then_response(self):
ret_value = pathlib.Path(
"src/human_lambdas/templates_handler/tests/t.json"... | Human-Lambdas/human-lambdas | src/human_lambdas/templates_handler/tests/test_templates.py | test_templates.py | py | 1,465 | python | en | code | 32 | github-code | 1 | [
{
"api_name": "logging.getLogger",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "rest_framework.test.APITestCase",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "pathlib.Path",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "unittes... |
74152330592 | import praw
import sys
import pickle
import operator
import json
from datetime import datetime
AGENT='windows:blood_bender.reddit-data:v1.0.1 (by /u/blood_bender)'
reddit = praw.Reddit(user_agent=AGENT)
def main():
print("Warning: this takes a tooonnnnn of time, sorry")
if (len(sys.argv) != 2):
print("Must p... | jgr3go/reddit_ar | artopcommenters.py | artopcommenters.py | py | 2,168 | python | en | code | 3 | github-code | 1 | [
{
"api_name": "praw.Reddit",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "sys.argv",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "sys.exit",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "sys.argv",
"line_number": 18,
... |
5928117169 | import math
from typing import Dict, Union
import numpy as np
import torch
from scipy.special import binom
from ocpmodels.common.typing import assert_is_instance
from ocpmodels.modules.scaling import ScaleFactor
class PolynomialEnvelope(torch.nn.Module):
"""
Polynomial envelope function that ensures a smoot... | Open-Catalyst-Project/ocp | ocpmodels/models/gemnet_oc/layers/radial_basis.py | radial_basis.py | py | 7,484 | python | en | code | 518 | github-code | 1 | [
{
"api_name": "torch.nn",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "torch.Tensor",
"line_number": 30,
"usage_type": "attribute"
},
{
"api_name": "torch.where",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "torch.zeros_like",
"l... |
18253543936 | from django.core.cache import cache
from config.settings import CACHE_ENABLED
from blog.models import Post
def get_cached_posts():
"""Получить список постов из кеша, если необходимо, то из БД."""
if CACHE_ENABLED:
key = 'blog_posts_list'
queryset = cache.get(key)
if queryset is None:... | RomanBogdanov5111/Coursework_6 | blog/services.py | services.py | py | 540 | python | ru | code | 0 | github-code | 1 | [
{
"api_name": "config.settings.CACHE_ENABLED",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "django.core.cache.cache.get",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "django.core.cache.cache",
"line_number": 12,
"usage_type": "name"
},
{
... |
12990749826 | import os
import sys
import unittest
_PARENT_DIR = os.path.abspath(os.path.join(os.getcwd(), os.pardir))
_PYLINT_PATH = os.path.join(_PARENT_DIR, 'oppia_tools', 'pylint-1.7.1')
sys.path.insert(0, _PYLINT_PATH)
# Since these module needs to be imported after adding Pylint path,
# we need to disable isort for the below... | shouri007/oppia | scripts/custom_lint_checks_test.py | custom_lint_checks_test.py | py | 2,269 | python | en | code | null | github-code | 1 | [
{
"api_name": "os.path.abspath",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "os.getcwd",
"line_number":... |
13857045676 | import asyncio
from discord.ext import commands
from utils.moduleloader import get_module_loader
class MemeBot:
bot: commands.Bot
command_prefix: str
async def loadModules(self, bot):
#def __ainit__(self, config: dict, bot: commands.Bot):
print( await self.moduleLoader.reload_all_cogs())
... | JeppeLovstad/Discord-Meme-Delivery-Bot | memebot.py | memebot.py | py | 1,980 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "discord.ext.commands.Bot",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "discord.ext.commands",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "discord.ext.commands.Bot",
"line_number": 14,
"usage_type": "attribute"
},
{
"ap... |
8410126543 | import matplotlib.pyplot as plt
def f(x):
return (7*x) % 1729
x = []
y = []
for i in range(0, 2000):
x.append(i)
y.append(f(i))
plt.plot(x, y)
plt.show()
| hermanholmoy/TDT4109 | Oppgaver/plotmod.py | plotmod.py | py | 173 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "matplotlib.pyplot.plot",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 16,
"usage_type": "name"
},
{
"api_name": "matplotlib.pyplot.show",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "matpl... |
7594669007 | from keras.models import load_model
from keras.preprocessing.image import img_to_array
import cv2
import numpy as np
import webbrowser
from tkinter import *
face_classifier = cv2.CascadeClassifier(
r'D:\EMOTION BASED MUSIC PLAYER\haarcascade_frontalface_default.xml')
classifier = load_model(r'D:\EMOTION... | anuragx18/EMOTION-BASED-MUSIC-PLAYER | main(1).py | main(1).py | py | 2,631 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "cv2.CascadeClassifier",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "keras.models.load_model",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "cv2.VideoCapture",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "cv2.cvt... |
33715367939 | import argparse
import datetime
import random
import sys
from pathlib import Path
from pprint import pprint
from typing import Dict
from tqdm import tqdm
import numpy as np
import torch
from torch.utils.tensorboard import SummaryWriter
from cal_angle import *
base_dir = str(Path(__file__).resolve().parent.parent)
sys.p... | w4ngzI/MARL-olympic-running | olympic_running_algo&reward/rl_trainer/main_reward.py | main_reward.py | py | 11,843 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "pathlib.Path",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "sys.path.append",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "rl_trainer.algo.ppo.PPO",
... |
35947564914 | # -*- coding: utf-8 -*-
import re
import csv
import matplotlib.pyplot as plt
"""
This script is for plotting each node# (force/RMSE & TC(300K) diff from 112.1)
with classified color of each data#
"""
if __name__ == '__main__':
datagrp=["2","10","20","40","60"]
dlabels=['70','350','700','1400','2100']
no... | s-okugawa/HDNNP-tools | tools/Lmps-MD/plotRMSETCdata-all4.py | plotRMSETCdata-all4.py | py | 3,341 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "csv.reader",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "re.split",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.figure",
"line_number": 38,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
... |
40517490417 | import bpy, mathutils
class RenderManager():
files = None
camera = None
dummyObject = None
zAxis = (0,0,1)
blenderFilesDir = "."
radius = 6378137
def __init__(self, **kwargs):
for k in kwargs:
setattr(self, k, kwargs[k])
def getBoundingBox(self):
# perform context.scene.update(), otherwise o.mat... | vvoovv/blender-2.5dmaps | render_manager.py | render_manager.py | py | 808 | python | en | code | 10 | github-code | 1 | [
{
"api_name": "bpy.context.scene.update",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "bpy.context",
"line_number": 20,
"usage_type": "attribute"
},
{
"api_name": "bpy.context",
"line_number": 25,
"usage_type": "attribute"
},
{
"api_name": "mathutils.... |
24845698363 | #!/usr/bin/env python
# WS server that sends messages at random intervals
import asyncio
import datetime
import random
import websockets
async def time(websocket, path):
print('Start... Loop előtt')
while True:
now = datetime.datetime.utcnow().isoformat() + 'Z'
print(now)
await websock... | cogitoergoread/em-simul | minta/ws_server_tine.py | ws_server_tine.py | py | 665 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "datetime.datetime.utcnow",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "asyncio.sleep",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "random.... |
36850304791 | """ 此文件用于解析rsl.out.0000文件 """
from datetime import datetime
# import matplotlib.pyplot as plt
class rslOutParser:
""" 此类用于解析rsl.out.0000文件 """
def __init__(self, rslFilePath):
self.rslFilePath = rslFilePath
self.dataLines = []
def tryParse(self):
""" a """
print('aaaaa')
... | the-1000th-summer/wrfViewerDjango | wrfViewer/app1/parser.py | parser.py | py | 3,362 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "datetime.datetime.strptime",
"line_number": 92,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 92,
"usage_type": "name"
}
] |
27514299411 | from base import Screen
import curses
from math import sin, cos, pi
from time import sleep, strftime
from datetime import datetime
from threading import Lock, Thread
class TimeClock(Screen):
name = '时钟'
used_pairs = (
(curses.COLOR_BLACK, curses.COLOR_WHITE),
(curses.COLOR_YELLOW, -1),
... | xiaohehao2009/lib | py/clock/builtin_components/timeclock.py | timeclock.py | py | 8,622 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "base.Screen",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "curses.COLOR_BLACK",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "curses.COLOR_WHITE",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "curses.COL... |
10663353857 | from transformers import AutoTokenizer
from optimum.onnxruntime import ORTModelForSeq2SeqLM
from optimum.pipelines import pipeline
from pathlib import Path
class OptimizedM100Model:
def __init__(self, model_path, src_lang, tgt_lang):
model_path = Path(model_path)
assert model_path.exists(), "Model... | dsfsi/masakhane-web | src/m_to_m_models/model_handlers.py | model_handlers.py | py | 1,404 | python | en | code | 34 | github-code | 1 | [
{
"api_name": "pathlib.Path",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "optimum.onnxruntime.ORTModelForSeq2SeqLM.from_pretrained",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "optimum.onnxruntime.ORTModelForSeq2SeqLM",
"line_number": 12,
"usage... |
8430419909 | import torch
import torch.nn as nn
from torch import optim
import torch.nn.functional as F
from torch.autograd import Variable
import numpy as np
import matplotlib.pyplot as plt
train_data = np.load("E:\\quant_research\\train the rank of ten points\\RNN_point\\data\\train_data_10num.npy")
train_aim = np.loa... | 00wuweimin/rank-ten-types-of-stocks-using-pointer-network | pointer_network.py | pointer_network.py | py | 7,979 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "numpy.load",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "numpy.load",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "torch.from_numpy",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "torch.FloatTensor",
"line_... |
16557727585 | # 10 그래프 이론 - 커리큘럼
# Solved Date: 22.07.17.
import sys
from collections import deque
import heapq
read = sys.stdin.readline
# 위상정렬하고, 더 오래 걸리는 값을 항상 저장해줌
def book_topological_sort(indegrees, graph, costs):
answer = [cost for cost in costs]
queue = deque()
for node, indegree in enumerate(indegrees):
... | imn00133/algorithm | ItIsCodingTest/chap10/04.curriculum.py | 04.curriculum.py | py | 2,018 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "sys.stdin",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "collections.deque",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "heapq.heappush",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "heapq.heappop",
"l... |
70199258594 | # -*- coding: utf-8 -*-
import json
import logging
import traceback
from datetime import datetime, timedelta
import odoo
from odoo import _, models, fields, api
from odoo.api import Environment
from odoo.tools import DEFAULT_SERVER_DATETIME_FORMAT as DATETIME_FORMAT
from ..api import AsyncDB
_logger = logging.getLo... | oejia/task_queue | models/task_task.py | task_task.py | py | 3,503 | python | en | code | 15 | github-code | 1 | [
{
"api_name": "logging.getLogger",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "odoo.models.AbstractModel",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "odoo.models",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "odoo.fie... |
70506253795 | import logging
import typing
from flask import render_template
import api
import api_types
from soda_api import client, LICENSE_DATASET
log = logging.getLogger(__name__)
def license_lookup(license: str) -> str:
if license:
try:
results = client.get(
LICENSE_DATASET, limit=1... | OrcaCollective/1-312-hows-my-driving | src/dataset.py | dataset.py | py | 2,722 | python | en | code | 3 | github-code | 1 | [
{
"api_name": "logging.getLogger",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "soda_api.client.get",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "soda_api.LICENSE_DATASET",
"line_number": 18,
"usage_type": "argument"
},
{
"api_name": "so... |
10576800492 | from pymongo import MongoClient
# Create a pymongo client
client = MongoClient("localhost", 27017)
# Get the database instance
db = client["mydb"]
# db collection
pytech = db["PyTech"]
# insert 3 students
records = [
{
"student_id": "1007",
"first_name": "Fred",
"last_name": "Jones"
... | taj1395/Python | csd_310/module_5/pytech_insert.py | pytech_insert.py | py | 829 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "pymongo.MongoClient",
"line_number": 4,
"usage_type": "call"
}
] |
74419552994 | import os
import pickle
import argparse
import numpy as np
import torch
import utils
import attacks
class TargetedIndexedDataset():
def __init__(self, dataset, classes):
self.dataset = dataset
self.classes = classes
def __getitem__(self, idx):
x, y, ii = self.dataset[idx]
y +... | fshp971/robust-unlearnable-examples | generate_tap.py | generate_tap.py | py | 5,798 | python | en | code | 35 | github-code | 1 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "utils.add_shared_args",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "torch.save",
"line_number": 58,
"usage_type": "call"
},
{
"api_name": "utils.get_mo... |
16967247888 | from tqdm import tqdm
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from pyflann import FLANN
from scipy.stats import gaussian_kde
from sklearn.neighbors import KernelDensity
import tool
class Coverage:
def __init__(self, model, layer_size_dict, hyper=None... | Yuanyuan-Yuan/NeuraL-Coverage | coverage.py | coverage.py | py | 34,661 | python | en | code | 243 | github-code | 1 | [
{
"api_name": "torch.device",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "torch.cuda.is_available",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "torch.cuda",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "tqdm.tqdm",
... |
32958159929 | import sys
import signal
import socket
import gym
import json
import numpy as np
import cv2
import tqdm
from itertools import product
from time import sleep
from utils.virtual_controller import VirtualKeyboard
from utils.img import ImageCapture
from utils.utils import changeWindowName, kill_process, kill_steam, run_ga... | Seladus/The-RL-of-Isaac | isaac_env.py | isaac_env.py | py | 10,300 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "gym.logger.set_level",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "gym.logger",
"line_number": 19,
"usage_type": "attribute"
},
{
"api_name": "gym.Env",
"line_number": 24,
"usage_type": "attribute"
},
{
"api_name": "itertools.product",... |
7954580347 | # -*- coding: utf-8 -*-
import select
import socket as sk
import logging
import common
import terminal
import commands.client
import commands.command
MAX_LOOP_TIME = 0.1 # s
server_ip = ("localhost", 23456)
class Client(common.Client):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kw... | Unprex/python-server | client.py | client.py | py | 3,792 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "common.Client",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "commands.client.client",
"line_number": 21,
"usage_type": "attribute"
},
{
"api_name": "commands.client",
"line_number": 21,
"usage_type": "name"
},
{
"api_name": "comman... |
26139386529 | import numpy as np
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.tree import DecisionTreeClassifier
from sklearn.metrics import accuracy_score
import category_encoders as ce
import warnings
import sys
import os
import logging
import mlflow
import mlflow.sklearn
import dvc.ap... | nshutijean/DVC-Mlflow-pipeline | train.py | train.py | py | 3,607 | python | en | code | 2 | github-code | 1 | [
{
"api_name": "logging.basicConfig",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "logging.WARN",
"line_number": 20,
"usage_type": "attribute"
},
{
"api_name": "logging.getLogger",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "dvc.api.api.g... |
8975814633 | import os
from re import L
import sys
import numpy as np
from numpy import asarray
import PIL
from PIL import Image, ImageDraw, ImageFont
from PIL.ExifTags import TAGS
np.set_printoptions(threshold=sys.maxsize)
def addition_decode_algo(stego_path):
stego_image = Image.open(stego_path, 'r')
stego_array = np.... | PoornaHegde20/stegWebApp | algo/addition.py | addition.py | py | 4,609 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "numpy.set_printoptions",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "sys.maxsize",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "PIL.Image.open",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "PIL.Image",
... |
72551170595 | """Module test for the multi-agent action model learning."""
from pddl_plus_parser.models import Domain, MultiAgentObservation, ActionCall, MultiAgentComponent, \
GroundedPredicate
from pytest import fixture
from sam_learning.core import LiteralCNF
from sam_learning.learners import MultiAgentSAM
from tests.consts ... | argaman-aloni/sam_learning | tests/multi_agent_sam_test.py | multi_agent_sam_test.py | py | 14,700 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "pddl_plus_parser.models.Domain",
"line_number": 16,
"usage_type": "name"
},
{
"api_name": "sam_learning.learners.MultiAgentSAM",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "pytest.fixture",
"line_number": 15,
"usage_type": "call"
},
{
... |
36214270512 | import click
import joblib
import pandas as pd
import numpy as np
import sklearn
from sklearn.pipeline import Pipeline
from sklearn.compose import ColumnTransformer
from sklearn.preprocessing import OrdinalEncoder
from sklearn.impute import KNNImputer
from sklearn.tree import DecisionTreeClassifier
import src
CAT_F... | mikhailmartin/Breast-Cancer | src/models/train_decision_tree_pipe.py | train_decision_tree_pipe.py | py | 2,200 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "src.constants",
"line_number": 16,
"usage_type": "attribute"
},
{
"api_name": "src.constants",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "src.constants",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "src.constant... |
36891714649 | from typing import List
def print_array(array: List[List]):
for i in range(0, len(array)):
print(" ".join([str(num) if num >= 10 else '0%s' % num for num in array[i]]))
def spiral(n: int) -> List[List]:
if n == 1:
return [[1]]
start, end = (0, n)
array = [[-1 for i in range(0, n)] fo... | peterehik/scripts | src/spiral.py | spiral.py | py | 2,015 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "typing.List",
"line_number": 4,
"usage_type": "name"
},
{
"api_name": "typing.List",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "typing.List",
"line_number": 22,
"usage_type": "name"
},
{
"api_name": "typing.List",
"line_number": 56... |
18270633501 | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torchvision import datasets, transforms
# Load the data
train = torch.utils.data.DataLoader(
datasets.MNIST('../data', train=True, download=True,
transform=transforms.Compose([transforms.ToT... | bencarletonn/Intro-to-Deep-Learning | pytorchMNISTmodel.py | pytorchMNISTmodel.py | py | 2,007 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "torch.utils.data.DataLoader",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "torch.utils",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "torchvision.datasets.MNIST",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": ... |
20567820784 | import etl
import boto3
import io
ny_url = "data/ETL_data.csv"
jh_url = "data/ETL_recovery.csv"
ACCESS_KEY_ID = 'YOUR_ACCESS_KEY_ID'
SECRET_ACCESS_KEY = 'YOUR_SECRET_ACCESS_ID'
filename = 'MyPandasData.'
bucketName = 'mypyfile'
s3_client = boto3.client(
"s3",
aws_access_key_id=ACCESS_KEY_ID,
aws_secret_a... | Gayathrimahe/ETL-aws-cloud-project | lamda.py | lamda.py | py | 861 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "boto3.client",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "etl.extract_transform",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "io.StringIO",
"line_number": 21,
"usage_type": "call"
}
] |
20798569158 | import sys
import cv2
import numpy as np
class VideoWriter(object):
def __init__(self, save_path='./video.mp4', fps=25, imsize=(224, 224)):
# encoder(for mp4)
#imsize must be tuplle object
fourcc = cv2.VideoWriter_fourcc('m', 'p', '4', 'v')
# output file name, encoder, fps, size(fi... | WeLoveKiraboshi/DeepTiltedDepthEstimation | utils/VideoWriter.py | VideoWriter.py | py | 1,247 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "cv2.VideoWriter_fourcc",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "numpy.ndarray",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "cv2.VideoWriter",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "sys.exit",
... |
36365978443 | import os
import glob
import shutil
import sys
import re
import string
import argparse
import unicodedata
import six.moves.configparser as ConfigParser
from os.path import expanduser
import h5py
import automo.util as util
import subprocess
from distutils.dir_util import mkpath
import logging
# logger = logging.getLog... | decarlof/automo | automo/robo.py | robo.py | py | 8,424 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "os.path.expanduser",
"line_number": 45,
"usage_type": "call"
},
{
"api_name": "os.path.dirname",
"line_number": 46,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 46,
"usage_type": "attribute"
},
{
"api_name": "os.path.abspath",
... |
18248847095 | import requests
from bs4 import BeautifulSoup
import time
# 爬取美女壁纸
url = 'https://pic.netbian.com/4kmeinv/'
resp = requests.get(url)
resp.encoding = 'gbk'
tags = BeautifulSoup(resp.text, 'html.parser')
imgs = tags.find('ul', class_='clearfix').find_all('img')
for img in imgs:
imgUrl = url[0:-9] + img.get('src')
... | xshxsh/pythonProject | 美女壁纸-bs4.py | 美女壁纸-bs4.py | py | 585 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "requests.get",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 15,
"usage_type": "call"
}
] |
31636756521 | from StringIO import StringIO
from lxml import etree
import requests
#NLM DTD is at http://dtd.nlm.nih.gov/archiving/3.0/archivearticle3.dtd
r = requests.get('http://dtd.nlm.nih.gov/archiving/3.0/archivearticle3.dtd')
NLM_DTD = r.text
dtd = etree.DTD(StringIO(NLM_DTD))
root = etree.XML("<foo/>")
print(dtd.validate... | elifesciences/elife-poa-xml-generation | validate.py | validate.py | py | 1,009 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "requests.get",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "lxml.etree.DTD",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "lxml.etree",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "StringIO.StringIO",
"line_num... |
71015525475 | #!/usr/bin/env python3
"""Get the minimum distance ** 2 among the given points.
>>> main("testcases/test_100000_1")
0
>>> main("testcases/test_10000_1")
144
>>> main("testcases/test_1000_1")
200
>>> main("testcases/test_uniform")
3969
"""
import math
import fileinput
from collections import defaultdict... | yskang/AlgorithmPractice | baekjoon/python/closest_two_point_2261.py | closest_two_point_2261.py | py | 3,400 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "fileinput.input",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "math.hypot",
"line_number": 56,
"usage_type": "call"
},
{
"api_name": "math.floor",
"line_number": 57,
"usage_type": "call"
},
{
"api_name": "math.sqrt",
"line_number": ... |
17329945888 | """
bid_frame.py represents the abstract frame for different types of auctions.
"""
__author__ = "Max Chan, Nick Chua"
# Library import
from tkinter import *
from datetime import datetime
from abc import ABC
# File import
from Controller.bid_controller import BidController
from View.abstract_frames import AbstractFr... | itsMoxMox/fit3077 | View/abstract_frames/bid_frame.py | bid_frame.py | py | 5,282 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "View.abstract_frames.AbstractFrame",
"line_number": 19,
"usage_type": "name"
},
{
"api_name": "abc.ABC",
"line_number": 19,
"usage_type": "name"
},
{
"api_name": "View.abstract_frames.AbstractFrame.__init__",
"line_number": 25,
"usage_type": "call"
},
{... |
29262785888 | import pygame
from pygame.sprite import Sprite
class Alien(Sprite):
"""a single alien class"""
def __init__(self, ai_settings, screen):
"""init alien set"""
super(Alien, self).__init__()
self.screen = screen
self.ai_settings = ai_settings
#load alien image, set it as r... | miasen939/alien_invasion | alien.py | alien.py | py | 745 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "pygame.sprite.Sprite",
"line_number": 4,
"usage_type": "name"
},
{
"api_name": "pygame.image.load",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "pygame.image",
"line_number": 14,
"usage_type": "attribute"
}
] |
19609182885 | #!/usr/bin/python3
'''This module contains one class, HBNBCommand'''
import cmd
import sys
import models
import json
from models.engine.file_storage import FileStorage
from models.amenity import Amenity
from models.base_model import BaseModel
from models.city import City
from models.place import Place
from models.revi... | komerela/AirBnB_clone_v1 | console.py | console.py | py | 5,397 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "cmd.Cmd",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "json.loads",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "models.base_model.BaseModel",
"line_number": 73,
"usage_type": "argument"
},
{
"api_name": "models.storag... |
12828599322 | #!/usr/bin/python
# -*- coding: utf-8 -*-
'''
4.11 同时迭代多个序列
Created on 2016年9月2日
@author: wang
'''
xpts = [1, 5, 4, 2, 10, 7]
ypts = [101, 78, 37, 15, 62, 99]
for x, y in zip(xpts, ypts):
print(x, y)
a = [1, 2, 3]
b = ['w', 'y', 'z', 'x']
for x, y in zip(a, b):
print(x, y)
from itertoo... | hejiawang/PythonCookbook | src/four/11.py | 11.py | py | 555 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "itertools.zip_longest",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "itertools.zip_longest",
"line_number": 23,
"usage_type": "call"
}
] |
467656577 | import spotipy
import sys
import pandas as pd
import numpy as np
from spotipy.oauth2 import SpotifyClientCredentials
from get_data import get_audio_features, get_songs, get_playlist_ID, preprocess_data
from model import separate_features, split_data, kNN_model, rf_model, logreg_model, mlp_model
import argparse
import s... | prathik-naidu/Spotify-Music-Analytics | predict.py | predict.py | py | 2,747 | python | en | code | 6 | github-code | 1 | [
{
"api_name": "spotipy.oauth2.SpotifyClientCredentials",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "spotipy.Spotify",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "spotipy.util.prompt_for_user_token",
"line_number": 23,
"usage_type": "call"
},... |
26212538295 | # -*- coding: utf-8 -*-
from odoo import api, fields, models, _
from odoo.exceptions import ValidationError
from datetime import datetime
class AflowzSchoolPolling(models.Model):
_name = 'aflowz.school.polling'
_description = 'Aflowz School Polling'
_inherit = ['mail.thread']
name = fields.Char(requi... | FRFirdaus/aflowz_school | aflowz_school/models/aflowz_school_polling.py | aflowz_school_polling.py | py | 5,583 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "odoo.models.Model",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "odoo.models",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "odoo.fields.Char",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "odoo.fields",
"... |
36066718460 | # -*- coding: utf-8 -*-
"""
Created on Wed Jun 21 11:23:57 2023
@author: athar
"""
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
path = r"C:\Users\athar\OneDrive\Desktop\Machine learning\Projects\SimpleLinearRegressionDataset\HtWt.csv"
df = pd.read_csv(path)
X = df['Height']... | atharvakalele/Machine_Learning | Projects/SImpleLinearRegression_4.py | SImpleLinearRegression_4.py | py | 1,299 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "pandas.read_csv",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.scatter",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 21,
"usage_type": "name"
},
{
"api_name": "matplotli... |
13387915055 | from fixture import DataSet
from datetime import datetime, date, time
class UserData(DataSet):
class LoggedInUser:
id = 101
username = "test_public"
first_name = "TestPublic"
last_name = "Public",
email = "test.public@parthenonsoftware.com"
raw_password = "password"... | fenriz07/flask-hippooks | hipcooks/fixtures.py | fixtures.py | py | 7,044 | python | en | code | 2 | github-code | 1 | [
{
"api_name": "fixture.DataSet",
"line_number": 5,
"usage_type": "name"
},
{
"api_name": "fixture.DataSet",
"line_number": 56,
"usage_type": "name"
},
{
"api_name": "fixture.DataSet",
"line_number": 72,
"usage_type": "name"
},
{
"api_name": "fixture.DataSet",
... |
34091916829 | from math import cos, radians
import matplotlib.pyplot as plt
import numpy as np
def finger_path(phase):
"""
If you plot this function it is a graph of the motion of each finger
phase: 0-259, phase the finger is in
returns:
angle: offset angle from finger's step start position
z: heigh... | neutronztar/Pivot | MicroPython/testing/bunga.py | bunga.py | py | 876 | python | en | code | 5 | github-code | 1 | [
{
"api_name": "math.cos",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "math.radians",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.xlim",
"line_number": 38,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
... |
12062159317 | #!/usr/bin/env python
import warnings
warnings.simplefilter(action='ignore', category=FutureWarning)
import numpy as np
import pandas as pd
#warnings.resetwarnings()
import re
import os
import time
import argparse
import prob_dist as prob
import fano_calc as fc
import resfuncRead as rfr
import time
from argparse impor... | villano-lab/nrFano_paper2019 | python/sig_diff.py | sig_diff.py | py | 6,154 | python | en | code | 2 | github-code | 1 | [
{
"api_name": "warnings.simplefilter",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "argparse.ArgumentParser",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 44,
"usage_type": "call"
},
{
"api_name": "pandas.r... |
30079951396 | import time
import requests
import pandas as pd
from bs4 import BeautifulSoup
from selenium import webdriver
from selenium.webdriver.firefox.options import Options
import json
import os
print("Opening web browser ")
url = "https://www.fifa.com/fifa-world-ranking/men"
option = Options()
option.headless = True
driver =... | mnluan/web_scrapping | rankingFIFA.py | rankingFIFA.py | py | 1,677 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "selenium.webdriver.firefox.options.Options",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "selenium.webdriver.Firefox",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "selenium.webdriver",
"line_number": 15,
"usage_type": "name"
},
... |
74736765474 | import json
from typing import TYPE_CHECKING, Optional, Iterable
from boxsdk.object.base_object import BaseObject
from ..pagination.marker_based_object_collection import MarkerBasedObjectCollection
from ..util.api_call_decorator import api_call
if TYPE_CHECKING:
from boxsdk.object.user import User
from boxsdk... | box/box-python-sdk | boxsdk/object/task.py | task.py | py | 2,694 | python | en | code | 395 | github-code | 1 | [
{
"api_name": "typing.TYPE_CHECKING",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "boxsdk.object.base_object.BaseObject",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "json.dumps",
"line_number": 38,
"usage_type": "call"
},
{
"api_name": "u... |
10563716155 | from pathlib import Path
import pytest
import time
import json
import platform
from usb_audio_test_utils import (
check_analyzer_output,
get_xtag_dut,
XrunDut,
XsigInput,
)
from conftest import list_configs, get_config_features
def OS_uncollect(features, board, config):
if (
platform.syst... | xmos/sw_usb_audio | tests/test_loopback.py | test_loopback.py | py | 2,914 | python | en | code | 16 | github-code | 1 | [
{
"api_name": "platform.system",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "conftest.get_config_features",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "usb_audio_test_utils.get_xtag_dut",
"line_number": 28,
"usage_type": "call"
},
{
"ap... |
32205008255 | import librosa
import joblib
import numpy as np
import pandas as pd
from typing import List
# Load the StandardScaler used during training
scaler = joblib.load("./resources/standard_scaler_pytorch_model_last.pkl")
def audio_to_csv(audio) -> List[pd.DataFrame]:
dfs = []
segments = get_3sec_sample(audio)
... | Pindice/Music | modules/preprocessing.py | preprocessing.py | py | 4,246 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "joblib.load",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame",
"line_number": 84,
"usage_type": "call"
},
{
"api_name": "typing.List",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "pandas.DataFrame",
"line... |
20643232235 | import sys
import os
import math
from random import randint
import networkx as nx
# import matplotlib.pyplot as plt
import random
from networkx.readwrite import json_graph
# 0 ≤ β ≤ 1 0\leq \beta \leq 1 and N ≫ K ≫ ln N ≫ 1 {\displaystyle N\gg K\gg \ln N\gg 1}
# num_nodes = 1024
# k = 50
# num_nodes = 512
# k = 28... | shishirrraic/LB-Spiral | network_generator.py | network_generator.py | py | 6,044 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "random.randint",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "networkx.shortest_path_length",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "networkx.eccentricity",
"line_number": 38,
"usage_type": "call"
},
{
"api_name": "ne... |
10001371754 | import cv2
import numpy as np
from IMP_SD import computeHOGs,get_svm_detector
if __name__ == '__main__':
# 第一步计算HOG特征
gradien_list = []
labels = []
hard_neg_list = []
# 正样本以及label导入
# pos_num, gradien_list_pos = computeHOGs('C:\\Users\\SLJ\\Desktop\\OCR_Project\\sample_R')
pos_num, gradi... | SWSWswswZJU/OCR_Relative | TrainHOG.py | TrainHOG.py | py | 2,567 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "IMP_SD.computeHOGs",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "IMP_SD.computeHOGs",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "cv2.ml.SVM_create",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "cv2.ml",
... |
26406619282 | import json
import os
import datetime
import tarfile
import torch
import warnings
import copy
import yaml
from . import constants
from ... import utils
from . import datasets
from . import training
from . import compilation
from .params import init_params
from . import descriptions
class ModelRunner():
@classmet... | TexasInstruments/edgeai-modelmaker | edgeai_modelmaker/ai_modules/vision/runner.py | runner.py | py | 11,088 | python | en | code | 9 | github-code | 1 | [
{
"api_name": "params.init_params",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "torch.hub.set_dir",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "torch.hub",
"line_number": 25,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
... |
26809118520 | #!/bin/env python
import time
from datetime import datetime
import numpy as np
import pandas as pd
from sportsipy.nfl.boxscore import Boxscore, Boxscores
from definitions import (
AGG_DROP_COLS,
AGG_MERGE_ON,
AGG_RENAME_AWAY,
AGG_RENAME_HOME,
AWAY_STATS,
AWAY_STATS_DROP,
ELO_DATA_URL,
... | mitch-avis/nfl-predictor | src/data_collection.py | data_collection.py | py | 17,657 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "datetime.datetime.strptime",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 30,
"usage_type": "name"
},
{
"api_name": "datetime.datetime.strptime",
"line_number": 32,
"usage_type": "call"
},
{
"api_name"... |
33160864962 | import asyncio
import copy
import json
import re
import uuid
from datetime import datetime
from async_generator import aclosing
from jupyterhub.utils import maybe_future
from jupyterhub.utils import url_path_join
from traitlets import Callable
from traitlets import Dict
from traitlets import Union
from .backendspawne... | kreuzert/jupyterhub-backendspawner | backendspawner/eventspawner.py | eventspawner.py | py | 10,280 | python | en | code | 2 | github-code | 1 | [
{
"api_name": "backendspawner.BackendSpawner",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "copy.deepcopy",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "datetime.datetime.strptime",
"line_number": 38,
"usage_type": "call"
},
{
"api_name":... |
25206615587 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Jun 26 08:24:46 2019
"Brown Corpus Analysis"
@author: Singh Gagan Deep
The Brown Corpus was the first million-word electronic corpus of English,
created in 1961 at Brown University.
This corpus contains text from 500 sources,
and the sources have been... | Gagan40/NLP_Learn | brown_Corpus_Analysis.py | brown_Corpus_Analysis.py | py | 2,217 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "nltk.corpus.brown.categories",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "nltk.corpus.brown",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "nltk.corpus.brown.words",
"line_number": 26,
"usage_type": "call"
},
{
"api_name":... |
26064580319 | import argparse
import os
import random
import shutil
import time
import warnings
from tqdm import tqdm
from typing import Callable, Optional
import faiss
import torch
import torch.nn as nn
import torch.nn.parallel
import torch.backends.cudnn as cudnn
import torch.optim
import torch.utils.data
from torch.utils.data im... | UCDvision/low-budget-al | sampler.py | sampler.py | py | 15,075 | python | en | code | 13 | github-code | 1 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "os.path.exists",
"line_number": 69,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 69,
"usage_type": "attribute"
},
{
"api_name": "os.makedirs",
... |
36930660381 | from django.shortcuts import render, redirect
from django.contrib.auth import authenticate, login, logout
from django.contrib.auth.decorators import login_required
from . import servise
from .forms import *
def login_required_decorator(f):
return login_required(f, login_url="login")
# @login_required_decorator
... | islombek-boboyorov/burger | mysite/spicyo/views.py | views.py | py | 2,340 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "django.contrib.auth.decorators.login_required",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "django.shortcuts.render",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "django.contrib.auth.authenticate",
"line_number": 31,
"usage_type": ... |
10805770602 | from data import question_data
from quiz_brain import QuizBrain
import random
class Main:
def __init__(self, index):
self.index = index
def play(self):
self.index = random.randint(0, len(question_data) - 1)
quiz = QuizBrain(self.index)
return quiz.check_answer()
while True:
... | krasenHristov/pythonL | OOP/quiz_game/main.py | main.py | py | 625 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "random.randint",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "data.question_data",
"line_number": 11,
"usage_type": "argument"
},
{
"api_name": "quiz_brain.QuizBrain",
"line_number": 12,
"usage_type": "call"
}
] |
2737478756 | import scrapy
import time
limit = False
infty = 1000000
class Player(scrapy.Item):
name = scrapy.Field()
team = scrapy.Field()
passport = scrapy.Field()
birth_date = scrapy.Field()
height = scrapy.Field()
position = scrapy.Field()
class NewSpider(scrapy.Spider):
name = 'players'
def ... | handedeemirci/Webscraping-PolishBasketballLeague-UW2023 | scrapy/suzuki/spiders/players.py | players.py | py | 1,326 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "scrapy.Item",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "scrapy.Field",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "scrapy.Field",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "scrapy.Field",
"line_numb... |
9748320846 | '''
READ THIS!
caption have been exracted into the variable 'caption'
'''
import os
import shutil
from instaloader import Post
import instaloader
url = 'https://www.instagram.com/reel/Ce85ucDFx_F/?utm_source=ig_web_copy_link'
k = url.split("/")
url =... | AnsahMohammad/Hackmanthan | InstaPost.py | InstaPost.py | py | 796 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "instaloader.Instaloader",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "instaloader.Post.from_shortcode",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "instaloader.Post",
"line_number": 19,
"usage_type": "name"
},
{
"api_name... |
4966719236 | from setuptools import setup, find_packages
version = '0.0.1'
setup(name="helga-naked-ping",
version=version,
description=('annoy users who insist (or have no idea) on naked pings'),
classifiers=['Development Status :: 1 - Beta',
'Environment :: IRC',
'Intended ... | alfredodeza/helga-naked-ping | setup.py | setup.py | py | 1,022 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "setuptools.setup",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "setuptools.find_packages",
"line_number": 21,
"usage_type": "call"
}
] |
2556952859 | import vcf
import numpy as np
def get_all_gt(records: vcf.Reader) -> list:
"""
Receiving all genotype values from vcf.Reader records
:param records: vcf.Reader records
:return: list with all genotype values
"""
all_gt_values = list()
for row in records:
samples = row.samples
... | Mil-m/bioinf-VAF_profile-barcode-mutations | calculate_VAF.py | calculate_VAF.py | py | 4,016 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "vcf.Reader",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "vcf.Reader",
"line_number": 23,
"usage_type": "attribute"
},
{
"api_name": "numpy.matrix",
"line_number": 82,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_n... |
16854851533 | """
Pre-Processing
1. The JSON file is processed to extract raw data and store it.
2. Raw data is converted to a data frame and processed to filter non-English characters.
3. Messages containing SHIB and DODGE are kept.
"""
# Libraries
from tqdm import tqdm
import json
import argparse
import pandas as pd
# Creates an... | paritoshsinghrahar/telegram_crawler | preprocessing.py | preprocessing.py | py | 2,447 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "pandas.DataFrame",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "tqdm.tqdm",
"line_number": 45,
"usage_type": "call"
},
{
"api_name": "tqdm.tqdm",
"line_number": 59,
"usage_type": "call"
},
{
"api_name": "argparse.ArgumentParser",
"l... |
18355212386 | from datetime import datetime
import argparse
import kudu
from kudu.client import Partitioning
# Parse arguments
parser = argparse.ArgumentParser(description='Basic Example for Kudu Python.')
parser.add_argument('--masters', '-m', nargs='+', default='localhost',
help='The master address(es) to co... | apache/kudu | examples/python/basic-python-example/basic_example.py | basic_example.py | py | 2,191 | python | en | code | 1,762 | github-code | 1 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "kudu.connect",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "kudu.schema_builder",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "kudu.int64",
... |
28522705093 | from BaseUserHandler import *
import datetime as dt
class ResaveExercisesHandler(BaseUserHandler):
async def get(self, course_id, assignment_id):
try:
if self.is_administrator or await self.is_instructor_for_course(course_id) or await self.is_assistant_for_course(course_id):
cou... | srp33/CodeBuddy | front_end/server/handlers/ResaveExercisesHandler.py | ResaveExercisesHandler.py | py | 1,945 | python | en | code | 8 | github-code | 1 | [
{
"api_name": "datetime.datetime.utcnow",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 17,
"usage_type": "attribute"
}
] |
36068249065 | from django import forms
from django.contrib.auth import get_user_model
from django.contrib.auth.forms import UserCreationForm
from django.forms import TextInput, EmailInput, PasswordInput
from cloudinary.forms import cl_init_js_callbacks
class SignupForm(UserCreationForm):
class Meta(UserCreationForm.Meta):... | clara-lancelle/shareyourplate | authentication/forms.py | forms.py | py | 832 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "django.contrib.auth.forms.UserCreationForm",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "django.contrib.auth.forms.UserCreationForm.Meta",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "django.contrib.auth.forms.UserCreationForm",
"l... |
20191142944 | import datetime as dt
import pytz
import json
import os
from typing import Any, List, Tuple
from operator import attrgetter, itemgetter
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import pandas_datareader as web
import seaborn as sns
from functools import wraps
from dotenv import load_dotenv... | raphtlw/crypto-price-predictor | src/telegram-bot.py | telegram-bot.py | py | 9,734 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "dotenv.load_dotenv",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "pytz.timezone",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "telegram.ext.callbackcontext.CallbackContext",
"line_number": 40,
"usage_type": "name"
},
{
"api... |
42643117573 | import shodan
import socket
from pprint import pprint as pp
import json
from openpyxl import Workbook
from openpyxl import styles
import argparse
import sys
from dotenv import load_dotenv
import os
from tqdm import tqdm
parser = argparse.ArgumentParser(
prog='shodanscanner',
description='Simple script to bul... | aerodiduch/shodanscanner | shodanscanner.py | shodanscanner.py | py | 4,339 | python | en | code | 2 | github-code | 1 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "openpyxl.Workbook",
"line_number": 52,
"usage_type": "name"
},
{
"api_name": "openpyxl.styles.Font",
"line_number": 79,
"usage_type": "call"
},
{
"api_name": "openpy... |
36170356261 | from typing import Any, Callable, Iterable, List
from volatility3.framework import interfaces, renderers
from volatility3.framework.configuration import requirements
from volatility3.framework.objects import utility
from volatility3.framework.renderers import format_hints
from volatility3.framework.symbols import inte... | volatilityfoundation/volatility3 | volatility3/framework/plugins/linux/pslist.py | pslist.py | py | 7,386 | python | en | code | 1,879 | github-code | 1 | [
{
"api_name": "volatility3.framework.interfaces.plugins",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "volatility3.framework.interfaces",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "volatility3.framework.configuration.requirements.ModuleRequirement... |
25650715659 | from django.contrib import admin
from repairshop.models import SubCategory
# Class to control how to display SubCategory on admin page
class SubCategoriesAdmin(admin.ModelAdmin):
list_display = ["name", "url", "position", "image", "blank"]
list_display_links = ["name"]
list_editable = ["position"]
se... | bmyronov/eremont | repairshop/admin/sub_category.py | sub_category.py | py | 482 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "django.contrib.admin.ModelAdmin",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "django.contrib.admin",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "django.contrib.admin.site.register",
"line_number": 16,
"usage_type": "call"
},... |
39571750898 | import json
class json_setting:
def __init__(self, file:str) -> None:
self.file = file
def loging(self, massage) -> None:
with open('history.txt', 'a+') as file:
file.write(f'{massage}\n')
def get_json(self) -> dict:
with open(f"{self.file}", "r+") as json_file:
... | KASSAS20/learn_python | inventory_JSON/main.py | main.py | py | 2,219 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "json.load",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "json.dumps",
"line_number": 17,
"usage_type": "call"
}
] |
10110617943 | #!/usr/bin/env python3
"""
Download JENDL data from JAEA and convert it to a HDF5 library for
use with OpenMC.
"""
import argparse
import ssl
from multiprocessing import Pool
from pathlib import Path
from urllib.parse import urljoin
import openmc.data
from openmc_data import download, extract, process_neutron, state... | openmc-data-storage/openmc_data | src/openmc_data/generate/generate_jendl.py | generate_jendl.py | py | 4,581 | python | en | code | null | github-code | 1 | [
{
"api_name": "argparse.ArgumentDefaultsHelpFormatter",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "argparse.RawDescriptionHelpFormatter",
"line_number": 19,
"usage_type": "attribute"
},
{
"api_name": "argparse.ArgumentParser",
"line_number": 23,
"usage... |
11479906122 | from flask import Flask, request
import argparse
import boto3
import json
from tqdm import tqdm
# Set up the Flask app
app = Flask(__name__)
# Set the values of the configuration, destination, and files variables
config = ""
dest = ""
files = []
@app.route("/", methods=["GET", "POST"])
def index():
if request.me... | OrShmuel22/boto3_searchfile | s3_search.py | s3_search.py | py | 2,531 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "flask.Flask",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "flask.request.method",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "flask.request",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "flask.request.form... |
24808861508 | # https://github.com/rdegges/pelican-minify
# Not used anymore, see gulpfile.js at root
import os
import htmlmin
import rcssmin
import jsmin
import pelican
def minify_html(filename):
with open(filename, 'r') as f:
# Read file to minify
uncompressed = f.read()
with open(filename, 'w') as f:
... | lucas-santoni/blog.geographer.fr | plugins/minify/minify.py | minify.py | py | 1,909 | python | en | code | 4 | github-code | 1 | [
{
"api_name": "htmlmin.minify",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "rcssmin.cssmin",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "jsmin.jsmin",
"line_number": 40,
"usage_type": "call"
},
{
"api_name": "os.walk",
"line_number"... |
74149748832 | # -*- coding: utf-8 -*-
"""
Created on Mon Feb 21 14:18:27 2022
@author: mamun
Face Recognition
Face recognition problems commonly fall into one of two categories:
Face Verification "Is this the claimed person?" For example, at some airports,
you can pass through customs by letting a system scan your passport an... | mamunrushdi/face_recognition | face_recognition.py | face_recognition.py | py | 18,244 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "tensorflow.keras.backend.set_image_data_format",
"line_number": 49,
"usage_type": "call"
},
{
"api_name": "tensorflow.keras.backend",
"line_number": 49,
"usage_type": "name"
},
{
"api_name": "tensorflow.keras.models.model_from_json",
"line_number": 87,
"usa... |
36810385194 | import argparse
import sys
import os
import TitaniaTest
def parse_args() -> argparse.Namespace:
# parse command line argument
parser = argparse.ArgumentParser(description="Titania Testing")
parser.add_argument('--output', type=str, default=".", help="\
Folderpath to store test results. \n \
... | i3drobotics/titania-testing | run.py | run.py | py | 7,169 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "argparse.Namespace",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "TitaniaTest.enableCameraEmulation",
"line_number": 87,
"usage_type": "call"
},
{
"a... |
74726793312 | from lib.cohort import Cohort
from lib.student import Student
class CohortRepository():
def __init__(self, connection):
self.connection = connection
def find_with_students(self, cohort_id):
rows = self.connection.execute(
"SELECT cohorts.id, cohorts.name, cohorts.start_date, stude... | TomMazzag/Makers-Learning | Week 5 - Databases/Find_with/lib/cohort_repository.py | cohort_repository.py | py | 826 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "lib.student.Student",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "lib.cohort.Cohort",
"line_number": 21,
"usage_type": "call"
}
] |
32185064776 | import argparse
import datetime
import random
import socket
import struct
from binascii import hexlify
from copy import copy
from impacket.krb5 import constants
from impacket.krb5.asn1 import AS_REQ, KERB_PA_PAC_REQUEST, seq_set, seq_set_iter, KRB_ERROR, AS_REP, METHOD_DATA, \
ETYPE_INFO2, ETYPE_INFO, PA_ENC_TS_EN... | Amulab/CAudit | plugins/AD/Plugin_AD_Exploit_ASRepRoasting.py | Plugin_AD_Exploit_ASRepRoasting.py | py | 14,610 | python | en | code | 250 | github-code | 1 | [
{
"api_name": "plugins.AD.PluginAdExploitBase",
"line_number": 27,
"usage_type": "name"
},
{
"api_name": "utils.consts.AllPluginTypes.Exploit",
"line_number": 30,
"usage_type": "attribute"
},
{
"api_name": "utils.consts.AllPluginTypes",
"line_number": 30,
"usage_type": "n... |
37272849998 | import datetime
import time
import typing
import boto3
import pytest
DEFAULT_WAIT_UNTIL_TIMEOUT_SECONDS = 60*10
DEFAULT_WAIT_UNTIL_INTERVAL_SECONDS = 15
DEFAULT_WAIT_UNTIL_DELETED_TIMEOUT_SECONDS = 60*10
DEFAULT_WAIT_UNTIL_DELETED_INTERVAL_SECONDS = 15
ProxyMatchFunc = typing.NewType(
'ProxyMatchFunc',
typin... | aws-controllers-k8s/rds-controller | test/e2e/db_proxy.py | db_proxy.py | py | 3,439 | python | en | code | 58 | github-code | 1 | [
{
"api_name": "typing.NewType",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "typing.Callable",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "datetime.datetime.now",
"line_number": 50,
"usage_type": "call"
},
{
"api_name": "datetime.da... |
22801704554 | import pygame,sys,math,time,copy,datetime,json
import numpy as np
SCREEN_WIDTH = 500
SCREEN_HEIGHT = 500
WHITE = (255, 255, 255)
ORANGE = (255, 127, 0)
BLACK = (0, 0, 0)
G = 6.673 * 1e-11
M_SUN = 1.98892e+30
M_EARTH = 5.9722e+24
camSize = 1
def add_h(arg):
h = 1e-6
return int(arg/(camSize+h))
def addTwo... | unknownbox-collab/gargantua | main.py | main.py | py | 8,166 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "numpy.array",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "math.cos",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "math.radians",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "math.sin",
"line_number": 20,
... |
17617829594 | import cv2
import numpy as np
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
from utils import detect_faces, predict_face, StatsStore, emotions, overlay_emoji
cap = cv2.VideoCapture(0)
stats = StatsStore({emot:0 for emot in emotions})
ret, frame = cap.read()
while (ret == True):
ret, frame = cap.read()
... | Core9nvidia/behavioural-assessment | code/emotion_detect.py | emotion_detect.py | py | 1,507 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "os.environ",
"line_number": 4,
"usage_type": "attribute"
},
{
"api_name": "cv2.VideoCapture",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "utils.StatsStore",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "utils.emotions",
... |
30209391413 | import numpy as np
import torch
from botorch.acquisition.cost_aware import InverseCostWeightedUtility
from botorch.acquisition import PosteriorMean
from botorch.acquisition.knowledge_gradient import qMultiFidelityKnowledgeGradient
from botorch.acquisition.fixed_feature import FixedFeatureAcquisitionFunction
from botorc... | yiping514/LMGP | lmgp_pytorch/bayesian_optimizations/bo_steps.py | bo_steps.py | py | 6,790 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "lmgp_pytorch.optim.fit_model_scipy",
"line_number": 42,
"usage_type": "call"
},
{
"api_name": "botorch.models.gp_regression_fidelity.SingleTaskMultiFidelityGP",
"line_number": 66,
"usage_type": "call"
},
{
"api_name": "botorch.models.transforms.outcome.Standardize"... |
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