added stringdate 2024-11-18 17:59:49 2024-11-19 03:44:43 | created int64 0 2,086B | id stringlengths 40 40 | int_score int64 2 5 | metadata dict | score float64 2.31 5.5 | source stringclasses 1
value | text stringlengths 258 23.4k | num_lines int64 16 649 | avg_line_length float64 15 61 | max_line_length int64 31 179 | ast_depth int64 8 40 | length int64 101 3.8k | lang stringclasses 1
value | sast_codeql_findings stringlengths 2 265k | sast_codeql_findings_count int64 0 45 | sast_codeql_success bool 1
class | sast_codeql_error stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2024-11-18T20:59:39.844810+00:00 | 1,625,282,800,000 | 89ebee1cff643237caa06db58c2e361ba4ee4022 | 3 | {
"blob_id": "89ebee1cff643237caa06db58c2e361ba4ee4022",
"branch_name": "refs/heads/main",
"committer_date": 1625282800000,
"content_id": "613a191cf77f9186626e54ff5f8e280751d66fa2",
"detected_licenses": [
"MIT",
"Python-2.0"
],
"directory_id": "4d6d00c7ee7f0f4f5085d4af00fdaeee1e4efeb2",
"extensi... | 2.578125 | stackv2 | # web_app/routes/movie_routes.py
from flask import Blueprint, request, render_template, redirect, jsonify, flash
from app.movie_reco_web import new_movie
from app.movie_reco_web import new_movie
movie_routes = Blueprint("movie_routes", __name__)
@movie_routes.route("/movie/form")
def movie_form():
print("MOVI... | 37 | 33.38 | 122 | 13 | 297 | python | [] | 0 | true | |
2024-11-18T20:59:39.897223+00:00 | 1,534,507,667,000 | 353b1cf15fa537366e9c1f390a2c62f1fcf2c4dd | 3 | {
"blob_id": "353b1cf15fa537366e9c1f390a2c62f1fcf2c4dd",
"branch_name": "refs/heads/master",
"committer_date": 1534507667000,
"content_id": "9329315889037689e0da0c59dc0b0600b7cb1479",
"detected_licenses": [
"MIT"
],
"directory_id": "41a4768b6373d9775e9a9497941602a09f3397ac",
"extension": "py",
"fi... | 2.546875 | stackv2 | import torch
import torch.nn as nn
import torch.nn.functional as F
import math
from torchlite.torch.models import Flatten
class Generator(nn.Module):
def __init__(self, scale_factor, res_blocks_count=4):
upsample_block_num = int(math.log(scale_factor, 2))
super(Generator, self).__init__()
... | 206 | 27.73 | 97 | 15 | 1,657 | python | [] | 0 | true | |
2024-11-18T20:59:40.190357+00:00 | 1,658,182,382,000 | 31189e30b4ab752d8a3377b191929f751af08567 | 3 | {
"blob_id": "31189e30b4ab752d8a3377b191929f751af08567",
"branch_name": "refs/heads/master",
"committer_date": 1658182382000,
"content_id": "2ca5ee6dce09fbfd7ac993be4b31357f743c7d46",
"detected_licenses": [
"MIT"
],
"directory_id": "84922a6f22f75185df8acb2b54e757063a46666c",
"extension": "py",
"fi... | 2.859375 | stackv2 | """
Convert SNP information to gene, rsid, or other useful annotations
"""
import struct
import typing as ty
import lmdb
import msgpack
from . import assets, exceptions
class SnpToRsid:
"""Convert SNP coordinates to RSID information"""
def __init__(self, path_or_build: str, *, num_chroms: int = 25, test=Fal... | 74 | 37.93 | 113 | 17 | 675 | python | [] | 0 | true | |
2024-11-18T20:59:40.512706+00:00 | 1,551,110,770,000 | 38b74b918d6cb492d6443d38cb9d81843e777fc0 | 3 | {
"blob_id": "38b74b918d6cb492d6443d38cb9d81843e777fc0",
"branch_name": "refs/heads/master",
"committer_date": 1551110770000,
"content_id": "3dd18bfa982352bf100959a2ab3ac45475e1acc7",
"detected_licenses": [
"Unlicense"
],
"directory_id": "0ece56ea9df32ec03c0d5bfdb8abf95958939095",
"extension": "py",... | 2.84375 | stackv2 | # -*- coding: utf-8 -*-
"""
Created on Mon Mar 12 10:47:40 2018
@author: arlan
"""
import numpy as np
from taqm import taqm
from scipy.stats import linregress
from beinf import beinf
import matplotlib.pyplot as plt
import os
# Change directory to where the data is stored and load data
os.chdir('Data')
X = np.load('M... | 77 | 28.79 | 101 | 10 | 777 | python | [] | 0 | true | |
2024-11-18T20:59:40.563713+00:00 | 1,273,530,098,000 | 90be8fcf7d5cf629c99c3160dfc2e4712e231abc | 2 | {
"blob_id": "90be8fcf7d5cf629c99c3160dfc2e4712e231abc",
"branch_name": "refs/heads/master",
"committer_date": 1273530098000,
"content_id": "a3c20ceeda975f8e6c4c299ac1da8c2c86f4993c",
"detected_licenses": [
"BSD-3-Clause"
],
"directory_id": "8a591ba502b67d960a04a72872a1a8b6a9dc66ad",
"extension": "p... | 2.453125 | stackv2 | import mimeparse
def determine_format(request, serializer, default_format='application/json'):
# First, check if they forced the format.
if request.GET.get('format'):
if request.GET['format'] in serializer.formats:
return serializer.get_mime_for_format(request.GET['format'])
# If call... | 29 | 32.31 | 101 | 13 | 210 | python | [] | 0 | true | |
2024-11-18T20:59:40.624776+00:00 | 1,635,234,531,000 | 10229c050f9741186b63eb798af08789fc9a1829 | 3 | {
"blob_id": "10229c050f9741186b63eb798af08789fc9a1829",
"branch_name": "refs/heads/main",
"committer_date": 1635234531000,
"content_id": "eb054e5c54dc013ed4185f42276be329c603bbcf",
"detected_licenses": [
"MIT"
],
"directory_id": "6ebe332acd4a714f80e511f8a6765d989b3d9395",
"extension": "py",
"file... | 2.75 | stackv2 | from pprint import pprint
import click
from rich import print
from rich.tree import Tree
from rich.live import Live
from rich.padding import Padding
from solution_2_ip_and_hostname import parse_cdp, connect_ssh
def generate_tree_from_schema(schema):
"""
Функция рисует дерево топологии на основе словаря sche... | 124 | 28.69 | 87 | 17 | 894 | python | [] | 0 | true | |
2024-11-18T20:59:40.672924+00:00 | 1,583,961,397,000 | da5ad81579e601e42427ad5d0746fcd0a15f2394 | 3 | {
"blob_id": "da5ad81579e601e42427ad5d0746fcd0a15f2394",
"branch_name": "refs/heads/master",
"committer_date": 1583961397000,
"content_id": "e705bf5e89f181cdad740a74dd5b9e3e18551a78",
"detected_licenses": [
"MIT"
],
"directory_id": "e0451d4e580d9b5c1327dc9103dfff801f6fb91b",
"extension": "py",
"fi... | 2.515625 | stackv2 | # To add a new cell, type '#%%'
# To add a new markdown cell, type '#%% [markdown]'
#%% Change working directory from the workspace root to the ipynb file location. Turn this addition off with the DataScience.changeDirOnImportExport setting
# ms-python.python added
import os
try:
os.chdir(os.path.join(os.getcwd(), ... | 129 | 22.85 | 156 | 14 | 888 | python | [] | 0 | true | |
2024-11-18T20:59:40.778243+00:00 | 1,540,472,874,000 | 08fd417856419883d96a055cc3185ffacb740a48 | 2 | {
"blob_id": "08fd417856419883d96a055cc3185ffacb740a48",
"branch_name": "refs/heads/master",
"committer_date": 1540472874000,
"content_id": "41768371fb9ebe8223d3e3dfef8e235095db8005",
"detected_licenses": [
"MIT"
],
"directory_id": "0b7a105e8b708d85f5c08c75507dbb4447ccf172",
"extension": "py",
"fi... | 2.328125 | stackv2 | class FPGA_config(object):
def __init__(self, ddr2fpga_nb, fpga2ddr_nb, iter_nb, mem_nb, mem_depth, add_nb, mul_nb):
self.func_layout = {'add': add_nb, 'mul': mul_nb}
func_nb = sum(self.func_layout.values())
self.config = {
'ddr2fpga_nb': ddr2fpga_nb,
'fpga2dd... | 18 | 39.39 | 93 | 13 | 205 | python | [] | 0 | true | |
2024-11-18T20:59:40.934542+00:00 | 1,509,702,219,000 | 08f77172d6d8c97ef2fe380f355eac92aec3d81b | 3 | {
"blob_id": "08f77172d6d8c97ef2fe380f355eac92aec3d81b",
"branch_name": "refs/heads/master",
"committer_date": 1509702219000,
"content_id": "13e4ca228547d4af884c3b1bed675d5109974a49",
"detected_licenses": [
"MIT"
],
"directory_id": "8f547afd2996c32336362002785f26a1c5f714cc",
"extension": "py",
"fi... | 3.296875 | stackv2 | import numpy as np
import matplotlib.pyplot as plt
from skimage import io, img_as_float
from skimage.color import rgb2gray
###############################################################################
# all functions ###############################################################
####################################... | 112 | 36.54 | 123 | 21 | 857 | python | [] | 0 | true | |
2024-11-18T20:59:41.286933+00:00 | 1,591,178,665,000 | a34de0b1b9646e966538b5d25ce3dd069bbefd19 | 3 | {
"blob_id": "a34de0b1b9646e966538b5d25ce3dd069bbefd19",
"branch_name": "refs/heads/master",
"committer_date": 1591178665000,
"content_id": "aeed6e07ec0def521ba6582647d4ee1ecbc6b645",
"detected_licenses": [
"MIT-0"
],
"directory_id": "7de00574899fe8a83281349d9e17248cc4dcbc75",
"extension": "py",
"... | 2.5625 | stackv2 | """
Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
SPDX-License-Identifier: MIT-0
"""
from cfnlint.rules import CloudFormationLintRule
from cfnlint.rules.limits import approaching_name_limit
class LimitName(CloudFormationLintRule):
"""Check maximum Resource name size limit"""
id = 'I3011'
... | 19 | 37.42 | 108 | 10 | 163 | python | [] | 0 | true | |
2024-11-18T20:59:41.763943+00:00 | 1,493,782,843,000 | ceebabb5cede862687ec23662fc98a22cb1e1378 | 2 | {
"blob_id": "ceebabb5cede862687ec23662fc98a22cb1e1378",
"branch_name": "refs/heads/master",
"committer_date": 1493782843000,
"content_id": "3ed133288ef112cb01573848e62c36fb4d628cbf",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "76e5545d49f7dccebf82280d3556c18df074463a",
"extension": "py"... | 2.46875 | stackv2 | __author__ = 'Leandra'
import pandas as pd
import os
import numpy as np
import math
from pyAudioAnalysis import audioAnalysis
def load_df(path_name, file_name):
file_path = os.path.join(path_name, file_name)
df = pd.read_csv(file_path)
return df
def xy_centroid_to_num(x, y):
scale_factor = 10.0 #3840... | 150 | 34.45 | 101 | 18 | 1,360 | python | [] | 0 | true | |
2024-11-18T20:59:41.966237+00:00 | 1,228,672,351,000 | 94db704e8f722ac148b7bf2b612fdb3ecd9d4622 | 3 | {
"blob_id": "94db704e8f722ac148b7bf2b612fdb3ecd9d4622",
"branch_name": "refs/heads/master",
"committer_date": 1228672351000,
"content_id": "9c43dd1daf82ec638afdc189955b8a58e477699b",
"detected_licenses": [
"BSD-2-Clause",
"BSD-3-Clause"
],
"directory_id": "7565d9b7762706bf67adc27f43700d54f04d2f0d... | 2.515625 | stackv2 | # Copyright 2008 Owen Taylor
#
# This file is part of Reinteract and distributed under the terms
# of the BSD license. See the file COPYING in the Reinteract
# distribution for full details.
#
########################################################################
import gtk
import os
from window_builder import Wind... | 36 | 32.94 | 94 | 16 | 255 | python | [] | 0 | true | |
2024-11-18T20:59:42.098620+00:00 | 1,693,470,539,000 | 8554b72740fa7d1c9705475a685d8bf6ddb298dd | 2 | {
"blob_id": "8554b72740fa7d1c9705475a685d8bf6ddb298dd",
"branch_name": "refs/heads/master",
"committer_date": 1693470539000,
"content_id": "6c440ed22440b3d92b5d30b76941157059b49441",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "f9d564f1aa83eca45872dab7fbaa26dd48210d08",
"extension": "py"... | 2.34375 | stackv2 | # coding: utf-8
import six
from huaweicloudsdkcore.utils.http_utils import sanitize_for_serialization
class EquipmentDnsItem:
"""
Attributes:
openapi_types (dict): The key is attribute name
and the value is attribute type.
attribute_map (dict): The key is attribute n... | 144 | 25.53 | 79 | 23 | 849 | python | [] | 0 | true | |
2024-11-18T20:59:42.708888+00:00 | 1,452,104,924,000 | 229afc122a79193e1f6065450db8ed4dc1747f51 | 3 | {
"blob_id": "229afc122a79193e1f6065450db8ed4dc1747f51",
"branch_name": "refs/heads/master",
"committer_date": 1452104946000,
"content_id": "65882ed4686fc757550c4e1da9d851dabe3fa8ce",
"detected_licenses": [
"MIT"
],
"directory_id": "6da0ce25795eeff42de4a23edee323f259386df2",
"extension": "py",
"fi... | 2.8125 | stackv2 | import sys
import json
import pyexiv2
from pyexiv2.utils import make_fraction
from lib.geo import decimal_to_dms
'''
A class for edit EXIF using pyexiv2
'''
class ExifEdit(object):
def __init__(self, filename, precision=1000):
self.filename = filename
self.metadata = pyexiv2.ImageMetadata(filenam... | 86 | 36.72 | 134 | 15 | 835 | python | [] | 0 | true | |
2024-11-18T20:59:42.842811+00:00 | 1,594,039,186,000 | 982e5a5c95dd147c914f985655edd28567ca2796 | 3 | {
"blob_id": "982e5a5c95dd147c914f985655edd28567ca2796",
"branch_name": "refs/heads/master",
"committer_date": 1594039186000,
"content_id": "9091e9825df2732e03d5a045ad6818a8ca2af818",
"detected_licenses": [
"MIT"
],
"directory_id": "36ca14e66b6d6b99f7dba6394a5a6445196a5283",
"extension": "py",
"fi... | 3.234375 | stackv2 | import os
from string import ascii_uppercase
from random import choice
import pygame
import pygame.freetype
# Tutorial = https://www.youtube.com/watch?v=UEO1B_llDnc
# init
pygame.init()
WIDTH = 800
HEIGHT = 500
win = pygame.display.set_mode((WIDTH, HEIGHT))
pygame.display.set_caption("Hangman The Game")
GAME_FONT = p... | 129 | 24.57 | 76 | 18 | 958 | python | [] | 0 | true | |
2024-11-18T20:59:43.175671+00:00 | 1,594,524,129,000 | ce04a17f03e815e7c573c4126b3e3f4d573e2e66 | 3 | {
"blob_id": "ce04a17f03e815e7c573c4126b3e3f4d573e2e66",
"branch_name": "refs/heads/master",
"committer_date": 1594524129000,
"content_id": "0e28bc6658aed5d9007e5b562722b7cd261efb7a",
"detected_licenses": [
"MIT"
],
"directory_id": "661fb342f8ec023306143cfe15a665b208e01c47",
"extension": "py",
"fi... | 2.96875 | stackv2 | ''' Another example of loading a pre-trained NFSP model on Leduc Hold'em
Here, we directly load the model from model zoo
'''
import rlcard
from rlcard.agents import RandomAgent
from rlcard.utils import set_global_seed, tournament
from rlcard import models
# Make environment
env = rlcard.make('leduc-holdem', config... | 24 | 30.17 | 72 | 10 | 186 | python | [] | 0 | true | |
2024-11-18T20:59:43.260795+00:00 | 1,604,064,574,000 | bd14c5cb0f1f8c99989da4097eff7f4a66171fc4 | 2 | {
"blob_id": "bd14c5cb0f1f8c99989da4097eff7f4a66171fc4",
"branch_name": "refs/heads/master",
"committer_date": 1604064574000,
"content_id": "25b6147b80ff8d04c55d53a528dc82defee03a99",
"detected_licenses": [
"MIT"
],
"directory_id": "5188016e2be50005f23e10f7d1e80158e7baa89b",
"extension": "py",
"fi... | 2.328125 | stackv2 | import json
import requests
headers = {
"Authorization": "Bearer " + 'accessToken',
}
temperature = 36.5
Mask = 76
message_description = '해당인원 온도 :' +str(temperature) + '\n마스크 미착용 확률 : ' + str(Mask) +'%'
template = {
"object_type": "feed",
"content": {
"image_url": "IMAGE_URL, 클라이언트의 사진을 가져오거... | 54 | 25.87 | 108 | 13 | 417 | python | [] | 0 | true | |
2024-11-18T20:59:43.331982+00:00 | 1,584,219,605,000 | 6ed99ef52ad5531e7aeac24adbaa22b392291398 | 3 | {
"blob_id": "6ed99ef52ad5531e7aeac24adbaa22b392291398",
"branch_name": "refs/heads/master",
"committer_date": 1584219605000,
"content_id": "4e6f463d29633f1a19554f57362436b7cef102b8",
"detected_licenses": [
"MIT"
],
"directory_id": "981daa78d19cacbcdaaed167d017594b8dbce198",
"extension": "py",
"fi... | 2.78125 | stackv2 | from collections import defaultdict
from slugify import slugify
from itertools import chain
from utils.date import date_to_str
from utils.locale import is_brazil
from utils.amount import amount_to_str
from utils.file import get_files_of_data_folder, get_file_content
file_contents = None
def _get_file_contents():
... | 121 | 28.24 | 84 | 15 | 744 | python | [] | 0 | true | |
2024-11-18T20:59:43.397678+00:00 | 1,614,264,552,000 | a64dc6faef140f70e99645929ebbff0c82d4a5b4 | 3 | {
"blob_id": "a64dc6faef140f70e99645929ebbff0c82d4a5b4",
"branch_name": "refs/heads/main",
"committer_date": 1614264552000,
"content_id": "3a1195d5eb934306e547c9cdcebe316380653f05",
"detected_licenses": [
"MIT"
],
"directory_id": "157b4b54236b98b4bb8edfec96afc9193947e93e",
"extension": "py",
"file... | 2.546875 | stackv2 | #!/usr/bin/env python
import sys
import os
import cv2
import numpy as np
import math
from cv_bridge import CvBridge, CvBridgeError
import rospy
import rospkg
import std_msgs.msg
from sensor_msgs.msg import Image
IMAGES_DIR = '/path/to/img' #change this
# DEPTH_TIMESTAMP_FILE = "path/to/timestampsdepth.txt"
# COLOR_T... | 107 | 33.39 | 107 | 16 | 835 | python | [] | 0 | true | |
2024-11-18T20:59:43.518639+00:00 | 1,528,445,722,000 | a8e1f4d55e7f450d5b35be5e3d4da66bd392ccc7 | 3 | {
"blob_id": "a8e1f4d55e7f450d5b35be5e3d4da66bd392ccc7",
"branch_name": "refs/heads/master",
"committer_date": 1528445722000,
"content_id": "01e229d799ca2ab80d2ba631d96c35eedc44a324",
"detected_licenses": [
"MIT"
],
"directory_id": "6db646e1f78d580003b6a37e8f722b28cc9ceae8",
"extension": "py",
"fi... | 2.59375 | stackv2 | from base import *
from ofxparse import OfxParser
import codecs, re
class OFXAdapter(BankAdapter):
name = 'OFX'
def parse_ofx(self):
if not getattr(self, 'ofx', None):
with codecs.open(self.filename) as f:
self.ofx = OfxParser.parse(f)
return self.ofx
def get_... | 40 | 34 | 105 | 17 | 289 | python | [] | 0 | true | |
2024-11-18T20:59:43.578816+00:00 | 1,579,228,607,000 | 606a74ca64b228fb088f449a2fc05e5fabd1ce44 | 2 | {
"blob_id": "606a74ca64b228fb088f449a2fc05e5fabd1ce44",
"branch_name": "refs/heads/master",
"committer_date": 1579228607000,
"content_id": "19907053b925f6dc602aadf31904ad3c78f41dae",
"detected_licenses": [
"MIT"
],
"directory_id": "3f6088cf1aaaddc18ca1c6f2d5bfc69590941d60",
"extension": "py",
"fi... | 2.5 | stackv2 | import matplotlib.pyplot as plt
from pylab import mpl
mpl.rcParams['font.sans-serif'] = ['FangSong'] # 指定默认字体
mpl.rcParams['axes.unicode_minus'] = False # 解决保存图像是负号'-'显示为方块的问题
plt.rcParams['font.size']=10
import pandas as pd
import numpy as np
import os
root_path = os.path.dirname(os.path.abspath('__file__'))
# root_pa... | 186 | 32.56 | 139 | 9 | 2,162 | python | [] | 0 | true | |
2024-11-18T20:59:44.052347+00:00 | 1,472,155,503,000 | 5b430ff94b536c55b3b8dd1cba2a81e8c425385a | 4 | {
"blob_id": "5b430ff94b536c55b3b8dd1cba2a81e8c425385a",
"branch_name": "refs/heads/master",
"committer_date": 1472155503000,
"content_id": "16091ce662efbba9785b7a578bbcc8f6851a3c21",
"detected_licenses": [
"MIT"
],
"directory_id": "22a2a26a9fe0a4ba3c11e3115168849945f87d53",
"extension": "py",
"fi... | 3.5 | stackv2 | """
THis is a paranthesis checker
"""
import os
import sys
os.system("clear")
#reading the path to file
if len(sys.argv) <= 1:
print "Please input the codefile to be checked for paranthesis"
print "USAGE : paranthesisChecker.py <path to file>"
sys.exit();
filename=sys.argv[1]
try:
readme=open(filename,"r")... | 125 | 22.22 | 77 | 18 | 780 | python | [] | 0 | true | |
2024-11-18T20:59:44.203998+00:00 | 1,590,760,271,000 | 5bd24b4e2b662e1b444cd2684fe9583cbdf1880a | 3 | {
"blob_id": "5bd24b4e2b662e1b444cd2684fe9583cbdf1880a",
"branch_name": "refs/heads/master",
"committer_date": 1590760271000,
"content_id": "5426897b4e636ae6b4c31f576eafc95138a15900",
"detected_licenses": [
"MIT"
],
"directory_id": "bb273d6ced49e7c4ddc41f8d2e5257e5a5097e34",
"extension": "py",
"fi... | 2.984375 | stackv2 | # TASK - 1 : To build a Subjective-Objective classifier, by using 5000+5000 dataset
# TASK - 2 : Constructing a function that performs mincut for a given file
# TASK - 3 : Calling the function over all the 2000 files and creating new modified reviews
from sklearn.feature_extraction.text import CountVectorizer
from skl... | 119 | 30.57 | 92 | 17 | 931 | python | [] | 0 | true | |
2024-11-18T20:59:44.266257+00:00 | 1,568,556,471,000 | 8eca00957123033b0f193a1c0f0c556c73893588 | 3 | {
"blob_id": "8eca00957123033b0f193a1c0f0c556c73893588",
"branch_name": "refs/heads/master",
"committer_date": 1568556471000,
"content_id": "e72bdd515ed7cc0d2bfc14fe816888006045ef02",
"detected_licenses": [
"MIT"
],
"directory_id": "73f10c7c7aedb08670cd03304603bd92f964a77a",
"extension": "py",
"fi... | 3.4375 | stackv2 | # https://docs.python.org/3/library/unittest.mock-examples.html
import unittest
from unittest.mock import patch
class SomeClass(object):
attribute = 'someclass_someclass'
function = 'function'
# def function(cls):
# return 'function'
class Sentinel(object):
attribute = 'sentinel_sentinel'
d... | 105 | 23.11 | 103 | 12 | 621 | python | [] | 0 | true | |
2024-11-18T20:59:44.323622+00:00 | 1,473,594,415,000 | 3a4572b310764eef429c9c55de6676bf46ac64ed | 3 | {
"blob_id": "3a4572b310764eef429c9c55de6676bf46ac64ed",
"branch_name": "refs/heads/master",
"committer_date": 1473594415000,
"content_id": "c558d0db8b6c88aa55d2b496d64a47852676b8d7",
"detected_licenses": [
"MIT"
],
"directory_id": "97a642a2b5737c614d31b555cc9ac7f98d364150",
"extension": "py",
"fi... | 2.984375 | stackv2 |
class SnippetSyntaxError(Exception):
"""Base class for snippets syntax errors"""
def __init__(self):
self.language = None
def set_language(self, language):
self.language = language
class EndSnippetSyntaxError(SnippetSyntaxError):
"""Ending snippet syntax error"""
def __init__(s... | 54 | 30.43 | 105 | 10 | 350 | python | [] | 0 | true | |
2024-11-18T20:59:44.373660+00:00 | 1,623,528,450,000 | e77aeb20e082e6037faa6d552a02195f81aa45c6 | 3 | {
"blob_id": "e77aeb20e082e6037faa6d552a02195f81aa45c6",
"branch_name": "refs/heads/master",
"committer_date": 1623528450000,
"content_id": "d1708574297a0944952999afed547472bb5dc9e8",
"detected_licenses": [
"MIT"
],
"directory_id": "5cf7fba21ae7999cb5e3a0e9ce5e44f51b21389d",
"extension": "py",
"fi... | 2.640625 | stackv2 | # COMMAND ----------
#PySpark Functions
from pyspark.sql.functions import col, when, lead, expr
from pyspark.sql.window import Window
# COMMAND ----------
######## Load DF from blob storage ##############
df = spark.read.format("csv") \
.options(header='true', delimiter = ',') \
.schema(customSchema) \
.load("/mnt/fi... | 28 | 23.82 | 55 | 13 | 155 | python | [] | 0 | true | |
2024-11-18T20:59:44.436745+00:00 | 1,567,944,662,000 | 70d368a82f0db8b99240b93473867b275fc0a4d4 | 4 | {
"blob_id": "70d368a82f0db8b99240b93473867b275fc0a4d4",
"branch_name": "refs/heads/master",
"committer_date": 1567944662000,
"content_id": "3a8f670f2b573a75d2343ff9b5a3be4ee389586a",
"detected_licenses": [
"MIT"
],
"directory_id": "6eadd5fbf819c055e494b77aeb5378e76b975a9e",
"extension": "py",
"fi... | 4.375 | stackv2 | # Given an array of integers, find the first missing positive integer in
# linear time and constant space. In other words, find the lowest positive
# integer that does not exist in the array. The array can contain duplicates
# and negative numbers as well.
# For example, the input [3, 4, -1, 1] should give 2. The inpu... | 47 | 25.74 | 88 | 12 | 360 | python | [] | 0 | true | |
2024-11-18T20:59:44.653774+00:00 | 1,608,472,956,000 | 9d856acabc20d75f69476058b5cad3c0ab31ab4e | 4 | {
"blob_id": "9d856acabc20d75f69476058b5cad3c0ab31ab4e",
"branch_name": "refs/heads/master",
"committer_date": 1608472956000,
"content_id": "5bed5f068d30a77b2a82f5f99c84d2c0a98755c7",
"detected_licenses": [
"MIT"
],
"directory_id": "9818262abff066b528a4c24333f40bdbe0ae9e21",
"extension": "py",
"fi... | 4.09375 | stackv2 | '''
Digit Problem
This time your task is simple.
Given two integers X and K, find the largest number that can be formed by changing digits at atmost K places in the number X.
Input:
First line of the input contains two integers X and K separated by a single space.
Output:
Print the largest number formed in a single... | 32 | 19.78 | 125 | 11 | 171 | python | [] | 0 | true | |
2024-11-18T20:59:44.798834+00:00 | 1,686,120,388,000 | 7804eadd716365f2328e26d5c058d87ae79e01a8 | 3 | {
"blob_id": "7804eadd716365f2328e26d5c058d87ae79e01a8",
"branch_name": "refs/heads/master",
"committer_date": 1686120388000,
"content_id": "93dc7009bcac9159202736858d96d2a7a183a777",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "d48d076fb07c1faf04b81b24f86c4cf2c48ecf29",
"extension": "py"... | 2.5625 | stackv2 | #!/usr/bin/python
# -*- coding:utf-8 -*-
SKIP_VERIFY_ATTR_TYPE = False
def _verify_attr_type(value, allowedAttrType):
if isinstance(allowedAttrType, list):
for t in allowedAttrType:
if isinstance(value, t):
return True
return False
return isinstance(value, allowedAt... | 51 | 33.08 | 94 | 18 | 388 | python | [] | 0 | true | |
2024-11-18T20:59:44.853280+00:00 | 1,595,068,024,000 | d2d1e77263bbe8975298a57a964c5129b4190e8d | 3 | {
"blob_id": "d2d1e77263bbe8975298a57a964c5129b4190e8d",
"branch_name": "refs/heads/master",
"committer_date": 1595068024000,
"content_id": "b9272e85cdf98c822d04c4d711483bf33401675c",
"detected_licenses": [
"BSD-3-Clause"
],
"directory_id": "4cbb866848c57fa103d198a27767bd817a9ab287",
"extension": "p... | 2.78125 | stackv2 | #!/usr/bin/env python3
import os
import sys
from bs4 import BeautifulSoup
SCRIPT_TAG = "script"
JQUERY_ADDRESS = "https://ajax.googleapis.com/ajax/libs/" \
"jquery/3.4.1/jquery.min.js"
INDEX_HTML_SCRIPT_NAME = "processRefs.js"
OTHER_HTML_SCRIPT_NAME = "script.js"
OTHER_HTML_FUNC_CALL = "colorReferenc... | 60 | 26.63 | 76 | 17 | 372 | python | [] | 0 | true | |
2024-11-18T20:59:45.168031+00:00 | 1,600,946,955,000 | e23f3dc4c8ddc4ea0a809d00e6052643d80e3453 | 3 | {
"blob_id": "e23f3dc4c8ddc4ea0a809d00e6052643d80e3453",
"branch_name": "refs/heads/master",
"committer_date": 1600946955000,
"content_id": "a00337d3f68c0f5113011222a2d8f3a4778715f6",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "778606229e2d14fa76acb5dff7070692ead1a7d6",
"extension": "py"... | 2.890625 | stackv2 | import requests
import json
import re
class Round_plan():
"""一个关于调用百度地图API全方式路径规划功能的类"""
def __init__(self, transit_mode):
self.transit_mode = transit_mode
def stod(self, slat, slng, dlat, dlng, waypoints='', route_type=''): # 输入：起点纬度、起点经度、终点纬度、终点经度
self.slat=slat
self.slng=slng
... | 115 | 47.53 | 121 | 28 | 1,567 | python | [] | 0 | true | |
2024-11-18T20:59:45.386387+00:00 | 1,647,289,971,000 | b3ff8fa901590ca9d2ecedba94c31be4eaaa49f3 | 3 | {
"blob_id": "b3ff8fa901590ca9d2ecedba94c31be4eaaa49f3",
"branch_name": "refs/heads/master",
"committer_date": 1647289971000,
"content_id": "626951e3832893e5c1f75e6bde36330bd081c87e",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "3102aa91e2b5d2f7ff0821d33639651585797081",
"extension": "py"... | 2.65625 | stackv2 | import RPi.GPIO as GPIO
import json
class on_off_range :
def __init__(self, on_string , off_string):
self.on_string= on_string
self.off_string= off_string
class actuator:
def __init__(self,name, port):
GPIO.setmode(GPIO.BCM)
GPIO.setup(port, GPIO.OUT)
self.name=name
... | 79 | 21.39 | 62 | 12 | 384 | python | [] | 0 | true | |
2024-11-18T20:59:45.493436+00:00 | 1,573,148,949,000 | 58da9c43e10fba440647b5d0a6039fb6ed106ec5 | 3 | {
"blob_id": "58da9c43e10fba440647b5d0a6039fb6ed106ec5",
"branch_name": "refs/heads/master",
"committer_date": 1573148949000,
"content_id": "ab703d17d833d65ae68d1cd4bd9a88bfd05c1178",
"detected_licenses": [
"MIT"
],
"directory_id": "308ff3931781ba97355e610f20356f7df5a684bc",
"extension": "py",
"fi... | 2.90625 | stackv2 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Helper functions for plotting modules
"""
import collections
import numpy as np
from matplotlib import ticker
from tunacell.base import Colony, Lineage
MIN_SEP = 20
MAX_XTICKS = 6
def _set_axis_limits(ax, values, which='x', pad=.1, force_range=(None, None)):
"... | 133 | 26.74 | 116 | 18 | 955 | python | [] | 0 | true | |
2024-11-18T20:59:46.873084+00:00 | 1,473,943,081,000 | 6704746b0a9cf54c42b42f33ec4c08808e41379d | 3 | {
"blob_id": "6704746b0a9cf54c42b42f33ec4c08808e41379d",
"branch_name": "refs/heads/master",
"committer_date": 1473943081000,
"content_id": "9db62c5b745f78937726dd81dbcedeac1817ed4b",
"detected_licenses": [
"MIT"
],
"directory_id": "de8599411de3f1b53c0026a635a15470b4d22854",
"extension": "py",
"fi... | 2.921875 | stackv2 | import os
import argparse
import glob
from tankbuster.engine import bust
# Set up the argument parser
ap = argparse.ArgumentParser()
# Add argument for input
ap.add_argument("-i", "--input", required=True, help="The image or directory to be analysed.")
# Parse the arguments
args = vars(ap.parse_args())
# Assign arg... | 29 | 20.9 | 94 | 10 | 149 | python | [] | 0 | true | |
2024-11-18T20:59:47.186567+00:00 | 1,458,625,179,000 | c231e096ce27326847130c768abf679f41eb71bd | 3 | {
"blob_id": "c231e096ce27326847130c768abf679f41eb71bd",
"branch_name": "refs/heads/master",
"committer_date": 1458625179000,
"content_id": "d5462af09a0493dc1f3e01a35dd3ef8df5f03eee",
"detected_licenses": [
"MIT"
],
"directory_id": "c2caf7c60c1d1cef84e96144e73bb6941388a6ea",
"extension": "py",
"fi... | 3.0625 | stackv2 | import datetime
import dateutil.tz
import pytz
import calendar
LOCAL_TIMEZONE = dateutil.tz.tzlocal()
def to_utc(dt):
if dt.tzinfo is None:
dt = dt.replace(tzinfo=LOCAL_TIMEZONE)
if dt.tzinfo != pytz.UTC:
return dt.astimezone(tz=pytz.UTC)
return dt
def to_timestamp(dt):
return calenda... | 37 | 23.51 | 69 | 11 | 249 | python | [] | 0 | true | |
2024-11-18T20:59:47.254755+00:00 | 1,586,791,373,000 | 780128fc234764de7f428e073414c915e6114f34 | 3 | {
"blob_id": "780128fc234764de7f428e073414c915e6114f34",
"branch_name": "refs/heads/master",
"committer_date": 1586791373000,
"content_id": "d7ecf552dad415c9a1c25ccb1feca1a1199735f8",
"detected_licenses": [
"MIT",
"Apache-2.0"
],
"directory_id": "429a2fac32015d4460e98f61c90ee85d961d5f9b",
"exten... | 3.234375 | stackv2 | # -*- coding: UTF-8 -*-
from __future__ import unicode_literals
from functools import wraps
import jscaller
def object2result(obj):
""" Object 转 Result。"""
return Result(obj.__parent__, obj.__name__, True)
def object2expr(obj):
""" Object 转 Express。"""
return Express(obj.__parent__, object2result(ob... | 455 | 27.65 | 105 | 20 | 3,284 | python | [] | 0 | true | |
2024-11-18T20:59:47.468520+00:00 | 1,512,040,608,000 | 4e4146455582f56d1db789c7ded76e9d964b247a | 3 | {
"blob_id": "4e4146455582f56d1db789c7ded76e9d964b247a",
"branch_name": "refs/heads/master",
"committer_date": 1512040608000,
"content_id": "af4f0cbf581bc85afc4e56a920064f5ed3e03c91",
"detected_licenses": [
"BSD-2-Clause"
],
"directory_id": "123cdb1d6a6956586dd91c86d02e0d1bacdcebae",
"extension": "p... | 2.765625 | stackv2 | #!/Users/jcb/anaconda/bin/python3
import sys
import pprint
from pddl import PDDL_Parser
from action import Durative_Action
class VRP:
'''Represent a parsed Pandora PDDL file and output a VRP formatted
for input into the CP solver.
This is a domain specific implementation, assuming that we are
... | 381 | 34.54 | 137 | 20 | 3,094 | python | [] | 0 | true | |
2024-11-18T20:59:47.598677+00:00 | 1,599,267,401,000 | de092e5bf752977b832288e93a93df331b33acc3 | 3 | {
"blob_id": "de092e5bf752977b832288e93a93df331b33acc3",
"branch_name": "refs/heads/master",
"committer_date": 1599267401000,
"content_id": "eb7f1e7ec9417c6e24b2509e6b95f04fc4f480af",
"detected_licenses": [
"MIT"
],
"directory_id": "ffe15d571ddc21b2f8ac22ba1122ad7ce27d3c02",
"extension": "py",
"fi... | 3.03125 | stackv2 | if __name__ == "__main__":
set=0
dingdong = list(map(int, input().split()))
if(dingdong[0]==1):
for i in range(0, 8):
if(dingdong[i]!=i+1):
print("mixed")
set=1
break
if(set==0):
print("ascending")
elif(dingdon... | 24 | 22.75 | 46 | 15 | 152 | python | [] | 0 | true | |
2024-11-18T20:59:47.665668+00:00 | 1,522,472,683,000 | 98bd57fd0c0907acc35b97b1128f93353d9c89f0 | 2 | {
"blob_id": "98bd57fd0c0907acc35b97b1128f93353d9c89f0",
"branch_name": "refs/heads/master",
"committer_date": 1522472683000,
"content_id": "17b791612ee3653527b50b9c5be93d3380f20b13",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "6639761e05e3b0aae3f6ce53558e99149e11a09e",
"extension": "py"... | 2.328125 | stackv2 | #!/usr/bin/env python
from stanza.research import config
config.redirect_output()
import datetime
from stanza.monitoring import progress
from stanza.research import evaluate, output
import metrics
import learners
import datasets
parser = config.get_options_parser()
parser.add_argument('--learner', default='Baseline... | 86 | 46.02 | 92 | 16 | 772 | python | [] | 0 | true | |
2024-11-18T20:59:47.764832+00:00 | 1,619,049,051,000 | 2c278159d4f63e2772a4bf1cd2bcb6eb94ca912d | 3 | {
"blob_id": "2c278159d4f63e2772a4bf1cd2bcb6eb94ca912d",
"branch_name": "refs/heads/master",
"committer_date": 1619049051000,
"content_id": "d5b6e0cd57c95c808dd96ca2784525d8c1988873",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "5bd05b2b6b9b01f6f2c58bfb7a14b0b45ea20999",
"extension": "py"... | 3.0625 | stackv2 | from __future__ import print_function
from copy import copy
font = Glyphs.font
def glyph_exists(gname):
glyph_existence = False
if gname in font.glyphs:
glyph_existence = True
return glyph_existence
def _duplicate_glyph(glyph, suffix=".alt"):
new_glyph = glyph.copy()
new_glyph.name = gl... | 50 | 23.54 | 84 | 14 | 338 | python | [] | 0 | true | |
2024-11-18T20:59:47.810098+00:00 | 1,396,988,968,000 | 261c8a5159c28e872d2b6889f40456d68b3abdda | 3 | {
"blob_id": "261c8a5159c28e872d2b6889f40456d68b3abdda",
"branch_name": "refs/heads/master",
"committer_date": 1396988968000,
"content_id": "8b087899b63a6f143c5cce32fb6d29ce1b3bd4f4",
"detected_licenses": [
"MIT"
],
"directory_id": "0f5b9c9ebb32e6878630b5ff7a52b84daa1d23c3",
"extension": "py",
"fi... | 2.90625 | stackv2 | # encoding=utf-8
from PyQt4.QtGui import *
from PyQt4.QtCore import *
from loginwindow import LoginWindow
from messagewindow import MessageWindow
from clientthread import ClientThread
from PyQt4 import QtGui
import socket
import sys
class Client(QtGui.QMainWindow):
def __init__(self,application, parent = None):
QtGu... | 128 | 32.16 | 157 | 15 | 1,040 | python | [] | 0 | true | |
2024-11-18T20:59:47.881039+00:00 | 1,576,936,802,000 | 5cdf5fadaecac300a4de2ef717cf0f367b493096 | 3 | {
"blob_id": "5cdf5fadaecac300a4de2ef717cf0f367b493096",
"branch_name": "refs/heads/master",
"committer_date": 1576936802000,
"content_id": "9a77186f94e2aaa3f98b7b5e80519ec08d677e34",
"detected_licenses": [
"MIT"
],
"directory_id": "984062ef926f8ebf16610688bc79053c7a4cd8b5",
"extension": "py",
"fi... | 3.09375 | stackv2 | from collections import OrderedDict
import time
class GeoDistributedLRUCache(object):
"""Using Dictionary to hold Cache"""
def __init__(self, cacheSize=1024):
self.cacheSize = cacheSize
self.__values = {}
self.__access_times = OrderedDict()
self.access_iter = 0
def size(sel... | 49 | 26.78 | 52 | 13 | 307 | python | [] | 0 | true | |
2024-11-18T20:59:58.229813+00:00 | 1,514,461,011,000 | 1cc20e21eb80e2cd654bbb9a4c31c7a5abce4eb7 | 3 | {
"blob_id": "1cc20e21eb80e2cd654bbb9a4c31c7a5abce4eb7",
"branch_name": "refs/heads/master",
"committer_date": 1514461011000,
"content_id": "6aa2cfb153c3906b54f135975b6f92842cafa4dd",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "1e0cc26234a06f0d0ee25888ad817cb7f3e5a256",
"extension": "py"... | 2.578125 | stackv2 | # -*- coding: utf-8 -*-
"""
Created on Sat Jul 23 22:21:47 2016
@author: nebula
"""
import os
# import Image, ImageDraw
from PIL import Image
# from PIL import ImageDraw
import matplotlib.pyplot as plt
def makeHist(inpath, outfile):
img = Image.open(inpath)
print(img.size)
rawimage = img.getdata()
h... | 62 | 31.16 | 100 | 14 | 624 | python | [] | 0 | true | |
2024-11-18T20:59:58.496034+00:00 | 1,494,863,758,000 | d9aef5ba4a6c0004176d610c0ae68fd6d55874a9 | 3 | {
"blob_id": "d9aef5ba4a6c0004176d610c0ae68fd6d55874a9",
"branch_name": "refs/heads/master",
"committer_date": 1494863758000,
"content_id": "75f208b38a2bf4dd7dbcc72ab9b704d7b471f98d",
"detected_licenses": [
"MIT"
],
"directory_id": "b7aa0a823da3bb99eb161bb92b3d53122c534ced",
"extension": "py",
"fi... | 2.640625 | stackv2 | from __future__ import absolute_import
from werkzeug.http import parse_options_header
from . import exceptions
class Negotiator(object):
"""The class used to select the proper parser and renderer."""
def select_parser(self, parser_classes, content_type):
"""Select the proper parser class.
... | 51 | 35.41 | 71 | 14 | 340 | python | [] | 0 | true | |
2024-11-18T21:00:00.205259+00:00 | 1,614,181,199,000 | 9f473b3cfe6a2ad7f129142f0e8f9d047a0600fc | 4 | {
"blob_id": "9f473b3cfe6a2ad7f129142f0e8f9d047a0600fc",
"branch_name": "refs/heads/master",
"committer_date": 1614181199000,
"content_id": "8f56266eda7eac8ed9e35115d15d0f9e09e24ecb",
"detected_licenses": [
"Python-2.0",
"MIT"
],
"directory_id": "50008b3b7fb7e14f793e92f5b27bf302112a3cb4",
"exten... | 3.78125 | stackv2 | class groupcount(object):
"""Accept a (possibly infinite) iterable and yield a succession
of sub-iterators from it, each of which will yield N values.
>>> gc = groupcount('abcdefghij', 3)
>>> for subgroup in gc:
... for item in subgroup:
... print item,
... print
...... | 30 | 21.93 | 67 | 13 | 181 | python | [] | 0 | true | |
2024-11-18T21:00:00.313323+00:00 | 1,587,651,002,000 | 709f460ec188b60df6c323f74ea384c5e35b6000 | 2 | {
"blob_id": "709f460ec188b60df6c323f74ea384c5e35b6000",
"branch_name": "refs/heads/master",
"committer_date": 1587651002000,
"content_id": "100fc72d7662a30b910796bcf0a0c745423956d9",
"detected_licenses": [
"MIT"
],
"directory_id": "a298b34be474fe8826152830f2ef641ac68b720e",
"extension": "py",
"fi... | 2.3125 | stackv2 | # -*- coding: utf-8 -*-
# Copyright (c) 2020 Ricardo Bartels. All rights reserved.
#
# check_redfish.py
#
# This work is licensed under the terms of the MIT license.
# For a copy, see file LICENSE.txt included in this
# repository or visit: <https://opensource.org/licenses/MIT>.
from cr_module.classes.inventory i... | 150 | 37.44 | 120 | 17 | 1,267 | python | [] | 0 | true | |
2024-11-18T21:00:00.416813+00:00 | 1,595,172,405,000 | f2e4706703b1bd229a00e3a224760a2655fcb6d4 | 3 | {
"blob_id": "f2e4706703b1bd229a00e3a224760a2655fcb6d4",
"branch_name": "refs/heads/master",
"committer_date": 1595172405000,
"content_id": "76cdb1bd8a4c6dfae0aec240b18c31a9bca5a97c",
"detected_licenses": [
"MIT"
],
"directory_id": "2052a12f0ab7a827d6427b5533b6ae29847dcc3b",
"extension": "py",
"fi... | 2.96875 | stackv2 | class Solution:
def exist(self, board: List[List[str]], word: str) -> bool:
if not word:
return True
def h(board, i, j, cur, target, used):
ret = False
if board[i][j] == target[len(cur)]:
cur += board[i][j]
if cur == target:
... | 43 | 31.81 | 72 | 18 | 347 | python | [] | 0 | true | |
2024-11-18T21:00:00.598903+00:00 | 1,540,991,658,000 | 4df5b924cfac73bd81a15d1cc21e59268d054917 | 3 | {
"blob_id": "4df5b924cfac73bd81a15d1cc21e59268d054917",
"branch_name": "refs/heads/master",
"committer_date": 1540991658000,
"content_id": "ce0863050e67db5e3c8e91b0739549fd44ff0ec9",
"detected_licenses": [
"MIT"
],
"directory_id": "6934faf01429e38412c5efc6e11882f8b4cbd7a6",
"extension": "py",
"fi... | 2.65625 | stackv2 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Detect faces in images.
"""
#
# This script detects faces in images.
# https://docs.opencv.org/3.1.0/d7/d8b/tutorial_py_face_detection.html
# Input is a folder with image files.
# Output is a csv-file listing number of detected faces, genre, hashes and filenames.
#
... | 125 | 27.52 | 107 | 12 | 895 | python | [] | 0 | true | |
2024-11-18T21:00:00.731617+00:00 | 1,612,691,220,000 | afc470118f82f7be88e40636f874e27cc2b92cf4 | 2 | {
"blob_id": "afc470118f82f7be88e40636f874e27cc2b92cf4",
"branch_name": "refs/heads/master",
"committer_date": 1612691220000,
"content_id": "c64407fd485df984b069273e51bcc8f891eb559a",
"detected_licenses": [
"MIT"
],
"directory_id": "dca5fe58b5283376d149f352ce31f1b98778a8df",
"extension": "py",
"fi... | 2.34375 | stackv2 | # Author: Simon Blanke
# Email: simon.blanke@yahoo.com
# License: MIT License
import random
from tqdm.auto import tqdm
import scipy
import numpy as np
import pandas as pd
import multiprocessing
from .util import merge_dicts
class Config:
def __init__(self, *args, **kwargs):
kwargs_base = {
... | 178 | 29.2 | 112 | 15 | 1,208 | python | [] | 0 | true | |
2024-11-18T21:00:01.031655+00:00 | 1,636,524,825,000 | 5b7f529e6fa2739a114dbaed48989f0a1801463f | 4 | {
"blob_id": "5b7f529e6fa2739a114dbaed48989f0a1801463f",
"branch_name": "refs/heads/main",
"committer_date": 1636524825000,
"content_id": "48dda0e4ab65570c2aa1baf93f32abf5b2953b6a",
"detected_licenses": [
"MIT"
],
"directory_id": "39b7b6f5e38fb05b4e63afbc839e2abd79f3a6f9",
"extension": "py",
"file... | 3.75 | stackv2 | # ============================================= #
# Módulo de suporte para realização das tarefas #
# ============================================= #
import numpy as np
# ============================================= #
# Algoritmo QR #
# ============================================= ... | 333 | 29.35 | 114 | 16 | 2,892 | python | [] | 0 | true | |
2024-11-18T21:00:01.392727+00:00 | 1,692,297,954,000 | 8991e2d3576153c4a49d8fc9782dcf88a42d3a4c | 3 | {
"blob_id": "8991e2d3576153c4a49d8fc9782dcf88a42d3a4c",
"branch_name": "refs/heads/main",
"committer_date": 1692297954000,
"content_id": "641af84969cddc28e4c8b0936d456348e54c3503",
"detected_licenses": [
"MIT"
],
"directory_id": "7231c313f64c1e281d4d55e66f34d26bb5c4965d",
"extension": "py",
"file... | 3.09375 | stackv2 | """
Module containing kernel related classes
TODO: Replace kernel evaluation with compute_kern found in hyppo.common.tools by reducing
dependencies on autograd.numpy
"""
from __future__ import division
from builtins import str
from past.utils import old_div
from abc import ABC, abstractmethod
import autograd
import ... | 260 | 28.52 | 89 | 15 | 2,122 | python | [] | 0 | true | |
2024-11-18T21:00:01.503605+00:00 | 1,608,135,516,000 | 9d99e7d173963fbfc79250cc487b139eba41db7a | 3 | {
"blob_id": "9d99e7d173963fbfc79250cc487b139eba41db7a",
"branch_name": "refs/heads/master",
"committer_date": 1608135516000,
"content_id": "08b62332ff5274445330668fd4b5a0f3f47cf599",
"detected_licenses": [
"MIT"
],
"directory_id": "ba397ec0c1fed0347f46791eea0c3798cc6a2a0c",
"extension": "py",
"fi... | 2.65625 | stackv2 | # -*- coding: utf-8 -*-
# MIT License
# Copyright (c) 2020 Arthur
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, ... | 122 | 45.7 | 136 | 11 | 1,284 | python | [] | 0 | true | |
2024-11-18T21:00:02.395938+00:00 | 1,685,458,882,000 | d0d8d5d24bca591f4b9100744e249ec02dc64fc0 | 3 | {
"blob_id": "d0d8d5d24bca591f4b9100744e249ec02dc64fc0",
"branch_name": "refs/heads/master",
"committer_date": 1685458882000,
"content_id": "4310faa04094d52abff3c509951be4243ff53bbc",
"detected_licenses": [
"MIT"
],
"directory_id": "792c262e2d584f064575ab98050c3dcc0e10db85",
"extension": "py",
"fi... | 2.78125 | stackv2 | """Utility functions for avoiding conflicts in the FC."""
import os
from typing import Any, AsyncGenerator, List, Optional, Tuple
from wipac_telemetry import tracing_tools as wtt
from .mongo import Mongo
from .schema import types
def _is_conflict(uuid: Optional[str], file_found: Optional[types.Metadata]) -> bool:
... | 118 | 33.43 | 88 | 18 | 930 | python | [] | 0 | true | |
2024-11-18T21:00:02.449304+00:00 | 1,614,033,211,000 | f2ca5f9cf4bcce57e2ec18ec8c5c292dfa956c98 | 3 | {
"blob_id": "f2ca5f9cf4bcce57e2ec18ec8c5c292dfa956c98",
"branch_name": "refs/heads/master",
"committer_date": 1614033211000,
"content_id": "2166fc514608f1a179c9356d51078d02ef544fcf",
"detected_licenses": [
"MIT"
],
"directory_id": "3d028c8ba838fd5a918430017784f3b1d563502b",
"extension": "py",
"fi... | 2.59375 | stackv2 | import requests
import json
from bs4 import BeautifulSoup as BS
import re
import time
import os
from dotenv import load_dotenv
def scrape_from_artist(artist_id, file_name='lyrics.txt'):
initial_time = time.time()
base_url = "https://api.genius.com"
path = 'artists/{}/songs'.format(artist_id)
request_u... | 89 | 25.13 | 69 | 14 | 588 | python | [] | 0 | true | |
2024-11-18T21:00:02.598337+00:00 | 1,618,759,697,000 | 2a0bbe7b446125b0ee2a99aa1f5701c4b80a1d19 | 2 | {
"blob_id": "2a0bbe7b446125b0ee2a99aa1f5701c4b80a1d19",
"branch_name": "refs/heads/main",
"committer_date": 1618759697000,
"content_id": "980b91dde32823fc522234c9585ea8a5c6ae5368",
"detected_licenses": [
"MIT"
],
"directory_id": "6bfbd232b5d3038e8d8d1b53bce31482fdaf530e",
"extension": "py",
"file... | 2.359375 | stackv2 | import datetime
from typing import List
import ics
from config import cqu_class_time, cqu_maxweek, cqu_time
from cqu import sub
def getCquClassListByUname(uname: str, upass: str)->List[str]:
s = sub.CQU_Subject()
subSchedule = s.getSubByLogin(uname=uname,upass=upass)
class_list = []
for x in subSched... | 35 | 30.06 | 69 | 11 | 336 | python | [] | 0 | true | |
2024-11-18T21:00:03.037219+00:00 | 1,693,515,274,000 | 1783083f99362f3e6409e620d0de1bc55dca7935 | 3 | {
"blob_id": "1783083f99362f3e6409e620d0de1bc55dca7935",
"branch_name": "refs/heads/master",
"committer_date": 1693515274000,
"content_id": "de9e4631e8eebea342347bb40d30a8d16a96389f",
"detected_licenses": [
"BSD-3-Clause"
],
"directory_id": "a2e145c21db228c0a9764fe0d9cef784ec8ddb79",
"extension": "p... | 2.65625 | stackv2 | import os
from bugswarm.common import log
from bugswarm.common.log_downloader import download_log
from reproducer.reproduce_exception import ReproduceError
def analyze_and_compare(job_dispatcher, job, run):
"""
Analyze jobs, including those that are not reproduced (those that are missing a reproduced log mo... | 81 | 50.96 | 118 | 19 | 925 | python | [] | 0 | true | |
2024-11-18T21:00:03.100390+00:00 | 1,554,302,645,000 | cab2fb678f85fb689545028695dce15b9068d0c7 | 3 | {
"blob_id": "cab2fb678f85fb689545028695dce15b9068d0c7",
"branch_name": "refs/heads/master",
"committer_date": 1554302645000,
"content_id": "c945067a737bbbdcd9fabae2487eef19273adc46",
"detected_licenses": [
"MIT"
],
"directory_id": "9b1a11c85572e409478206028a8a8ff3c2a5bfc0",
"extension": "py",
"fi... | 3.3125 | stackv2 | '''
这是一个备份文件的脚本示例。
'''
import os
import time
def backupzip(source, target):
'''
ZIP备份文件函数。
自动将source目录列表的文件备份打包成zip文件，存放在target目录下的ymdHMS.zip。
source：备份文件路径列表。
target：备份文件存放路径。
'''
target = target + os.sep + time.strftime('%Y%m%d')
if not os.path.exists(target):
os.mkdir(ta... | 39 | 21.1 | 67 | 11 | 257 | python | [] | 0 | true | |
2024-11-18T21:00:03.164099+00:00 | 1,499,276,988,000 | 5f7e9d9a5feb8ac95b7c8b236e6aebe6e1356487 | 3 | {
"blob_id": "5f7e9d9a5feb8ac95b7c8b236e6aebe6e1356487",
"branch_name": "refs/heads/master",
"committer_date": 1499276988000,
"content_id": "a63c265fea1d953fe54bc349532a186ac4dbbe88",
"detected_licenses": [
"MIT"
],
"directory_id": "064672488e3e0b037f4a58a56dbfe72e861799cc",
"extension": "py",
"fi... | 2.515625 | stackv2 | import os
import smtplib
from email.header import Header
from email.mime.text import MIMEText
class Mail:
debug_level = True if os.getenv('FLASK_DEBUG', 0) == 1 else False
def __init__(self, smtp=smtplib.SMTP()):
self.from_address = None
self.to_address = None
self.subject = None
... | 39 | 27.26 | 79 | 14 | 250 | python | [] | 0 | true | |
2024-11-18T21:00:03.398608+00:00 | 1,513,882,110,000 | 54bca3b0de16ee5b82ea1808422edf52dea9d62e | 2 | {
"blob_id": "54bca3b0de16ee5b82ea1808422edf52dea9d62e",
"branch_name": "refs/heads/master",
"committer_date": 1513882110000,
"content_id": "b61e3e2283565941d88089c71b6cd934b27c2802",
"detected_licenses": [
"MIT"
],
"directory_id": "f33c1f5e37814c45a8dd0bcb85de3581a21defde",
"extension": "py",
"fi... | 2.328125 | stackv2 | import boto3
client_dynamo = boto3.client('dynamodb')
def lambda_handler(event, context):
token = event['authorizationToken']
auth_info = client_dynamo.get_item(TableName='tokens', Key={'token': { 'S': token } }).get('Item')
if (auth_info):
print auth_info
return generatePolicy('user', ev... | 31 | 34.68 | 148 | 16 | 293 | python | [] | 0 | true | |
2024-11-18T21:00:03.720335+00:00 | 1,462,141,121,000 | f2e60050169bdf68b871543f04ba8c9f2c58e98d | 3 | {
"blob_id": "f2e60050169bdf68b871543f04ba8c9f2c58e98d",
"branch_name": "refs/heads/master",
"committer_date": 1462141121000,
"content_id": "081045f7bd1cb85f52e5f9124dc4a81986e73e85",
"detected_licenses": [
"MIT"
],
"directory_id": "cf1a394ff57fe3339d8a8e7b99c1809d7f1e278b",
"extension": "py",
"fi... | 2.6875 | stackv2 | #!/usr/bin/env python
'''
Author: Andrew Scott
Date: 4/26/2016
'''
import hashlib
import os, sys, time
import multiprocessing
from random import shuffle
import itertools
import argparse
# Constants
##------------------------------------------------------------------------------------------
CORE_COUNT = multiproce... | 417 | 30.43 | 155 | 22 | 3,152 | python | [{"finding_id": "codeql_py/clear-text-storage-sensitive-data_fe506bb247ec38b9_6e157da0", "tool_name": "codeql", "rule_id": "py/clear-text-storage-sensitive-data", "finding_type": "path-problem", "severity": "medium", "confidence": "high", "message": "This expression stores [sensitive data (password)](1) as clear text.\... | 1 | true | |
2024-11-18T21:00:04.041482+00:00 | 1,683,896,947,000 | 72614043b2bdb0f91eb54fda96aa7565f35799d5 | 2 | {
"blob_id": "72614043b2bdb0f91eb54fda96aa7565f35799d5",
"branch_name": "refs/heads/master",
"committer_date": 1683896947000,
"content_id": "4c5ed6a947d8a4183837ce612c7725a103426cb7",
"detected_licenses": [
"BSD-2-Clause"
],
"directory_id": "bbb121f18a6e4015834b28780bd434655679360e",
"extension": "p... | 2.46875 | stackv2 | import os
import sys
from setuptools import setup, find_packages
PACKAGE_NAME = 'hamiltorch'
MINIMUM_PYTHON_VERSION = 3, 5
def check_python_version():
"""Exit when the Python version is too low."""
if sys.version_info < MINIMUM_PYTHON_VERSION:
sys.exit("Python {}.{}+ is required.".format(*MINIMUM_PYTH... | 38 | 37.53 | 140 | 15 | 362 | python | [] | 0 | true | |
2024-11-18T21:00:04.164962+00:00 | 1,571,985,555,000 | d97b025d7b660ee0c1768c8b2339694060d35309 | 3 | {
"blob_id": "d97b025d7b660ee0c1768c8b2339694060d35309",
"branch_name": "refs/heads/master",
"committer_date": 1571985555000,
"content_id": "7d72e52f3e63ae7fa5ced8589a39cf07eecfe11a",
"detected_licenses": [
"MIT"
],
"directory_id": "1837257009ceddc0e11836e3391413a1387d4f53",
"extension": "py",
"fi... | 3.0625 | stackv2 | import warnings
import cv2
import numpy as np
import shapely.geometry as geom
from matplotlib import patches as patches
from skimage import measure
class Point:
def __init__(self, *args, dtype=int):
if dtype not in [int, float]:
raise ValueError('dtype must be either int or float but {} is gi... | 423 | 28.51 | 119 | 17 | 3,101 | python | [] | 0 | true | |
2024-11-18T21:00:04.227181+00:00 | 1,590,370,982,000 | c5f402cba597ad39f35b39a5b1047bcf015c400a | 4 | {
"blob_id": "c5f402cba597ad39f35b39a5b1047bcf015c400a",
"branch_name": "refs/heads/master",
"committer_date": 1590370982000,
"content_id": "38102e59431d0ad407cd6485ce54efd5d13db6ce",
"detected_licenses": [
"MIT"
],
"directory_id": "7a9a741e115acc444538429ebd10e2b2c136d0b2",
"extension": "py",
"fi... | 3.9375 | stackv2 | """
课堂练习
请你在之前代码的基础上，写出提取食材的代码，并打印出来。
不懂做？点击下面的“需要帮助”。
"""
# 引用requests库
import requests
# 引用BeautifulSoup库
from bs4 import BeautifulSoup
# 获取数据
res_foods = requests.get('http://www.xiachufang.com/explore/')
# 解析数据
bs_foods = BeautifulSoup(res_foods.text, 'html.parser')
# 查找最小父级标签
list_foods = bs_foods.find_all('div'... | 56 | 20.46 | 62 | 9 | 492 | python | [] | 0 | true | |
2024-11-18T21:00:04.496791+00:00 | 1,692,696,275,000 | 37d9034ecb34ee7a17c8c824b712b8cc02d6f2f9 | 3 | {
"blob_id": "37d9034ecb34ee7a17c8c824b712b8cc02d6f2f9",
"branch_name": "refs/heads/main",
"committer_date": 1692696275000,
"content_id": "f708d071fa142d37a44bb0357c5c00e2834f8455",
"detected_licenses": [
"BSD-2-Clause"
],
"directory_id": "1cc43d5ed0a843289c8f6dafb6a16fab26a8eede",
"extension": "py"... | 2.5625 | stackv2 | """ Sphinx builders for output formats
"""
import sphinx
from sphinx.builders.text import TextBuilder
from . import doctree2md, doctree2py, doctree2nb
SPHINX_GE_6 = sphinx.version_info[0] >= 6
class MarkdownBuilder(TextBuilder):
name = 'markdown'
format = 'markdown'
out_suffix = '.md'
writer_class... | 57 | 28.49 | 79 | 12 | 405 | python | [] | 0 | true | |
2024-11-18T21:00:04.627890+00:00 | 1,611,617,237,000 | baf66cad19f5ff8cfa420ae8596f18d098723b84 | 4 | {
"blob_id": "baf66cad19f5ff8cfa420ae8596f18d098723b84",
"branch_name": "refs/heads/master",
"committer_date": 1611617237000,
"content_id": "8827e38f31ea366f3c0abfe00bab36e0ed2f4926",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "5b3d8b5c612c802fd846de63f86b57652d33f672",
"extension": "py"... | 3.96875 | stackv2 | # Python solution for 'Find the odd int' codewars question.
# Level: 6 kyu
# Tags: Fundamentals.
# Author: Jack Brokenshire
# Date: 07/03/2020
import unittest
def find_it(seq):
"""
Given an array, find the integer that appears an odd number of times. There will always be only one integer that
appears an ... | 35 | 31.17 | 116 | 13 | 432 | python | [] | 0 | true | |
2024-11-18T21:00:04.681523+00:00 | 1,526,352,497,000 | 0264bc85d86c5e9b332bf659813340718898a8fb | 3 | {
"blob_id": "0264bc85d86c5e9b332bf659813340718898a8fb",
"branch_name": "refs/heads/master",
"committer_date": 1526352497000,
"content_id": "0df19936f504a5cbf818915e0ee604651d1c2c30",
"detected_licenses": [
"MIT"
],
"directory_id": "33491b01251cd48a4c319ec1de61eb543ccc0e97",
"extension": "py",
"fi... | 2.984375 | stackv2 | """
Contains functions for combining translations into a summary string
"""
def metar(trans: {str: object}) -> str:
"""
Condense the translation strings into a single report summary string
"""
summary = []
if 'Wind' in trans and trans['Wind']:
summary.append('Winds ' + trans['Wind'])
i... | 49 | 42.63 | 93 | 18 | 537 | python | [] | 0 | true | |
2024-11-18T21:00:04.780142+00:00 | 1,603,019,535,000 | ac7438b9820d9180ab9dd56a83fc734983829321 | 3 | {
"blob_id": "ac7438b9820d9180ab9dd56a83fc734983829321",
"branch_name": "refs/heads/master",
"committer_date": 1603019535000,
"content_id": "f4a89b51855ff47c292c8c46b6436772e3da9e43",
"detected_licenses": [
"MIT"
],
"directory_id": "4f247138fe484ddc311d45109b38ad3706e40342",
"extension": "py",
"fi... | 2.578125 | stackv2 | from PIL import Image
import os
import numpy as np
import pandas as pd
import plotly.express as px
__author__ = "Sarsiz Chauhan"
img_name="keanu"
img_path = os.path.join(os.getcwd(), 'images/{}.jpg'.format(img_name))
# img_path = os.path.join(os.getcwd(), 'images/saz copy.jpg')
im = Image.open(img_path)
width, heig... | 55 | 24.38 | 93 | 13 | 415 | python | [] | 0 | true | |
2024-11-18T21:00:04.830415+00:00 | 1,614,716,218,000 | d7133b527f3a75608291d6846a3d63db992c06e6 | 3 | {
"blob_id": "d7133b527f3a75608291d6846a3d63db992c06e6",
"branch_name": "refs/heads/master",
"committer_date": 1614716218000,
"content_id": "f46b306c721f337cf8023d78f5eb14a7c8ada125",
"detected_licenses": [
"BSD-3-Clause",
"Apache-2.0"
],
"directory_id": "38926818c32a9ed3cbd4ff8dcbbf57f1318bb20d",... | 2.890625 | stackv2 | import sys
import os
import math
import numpy
# usage: parse_effects dir target_std
def weighted_std(values, weights_in):
"""
Return weighted standard deviation.
values, weights -- Numpy ndarrays with the same shape.
"""
average = numpy.average(values, weights=weights_in)
# Fast and numerically... | 42 | 24.4 | 58 | 18 | 277 | python | [] | 0 | true | |
2024-11-18T21:00:04.940314+00:00 | 1,588,919,246,000 | dc4fe8b4dc05a70a14f1623922d4199990942ed1 | 3 | {
"blob_id": "dc4fe8b4dc05a70a14f1623922d4199990942ed1",
"branch_name": "refs/heads/master",
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"detected_licenses": [
"Apache-2.0"
],
"directory_id": "9078bcd228b0d84d647c45811044974961aa170c",
"extension": "py"... | 3.1875 | stackv2 | from itertools import starmap
from Position import Position
from Moves import Moves
from RuleEngine import RuleEngine
from MoveGenerator import MoveGenerator
from Board import Board
class Player (object):
def __init__(self, type):
self.type = type
self.lastMoveHasCaptured = False
self.mg =... | 91 | 38.59 | 108 | 23 | 719 | python | [] | 0 | true | |
2024-11-18T21:00:04.986311+00:00 | 1,604,440,134,000 | fe3d8e46108c28db367e9df22988eeaa3342be0a | 3 | {
"blob_id": "fe3d8e46108c28db367e9df22988eeaa3342be0a",
"branch_name": "refs/heads/main",
"committer_date": 1604440134000,
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"detected_licenses": [
"MIT"
],
"directory_id": "fcf49543e3426294a83e075e6f6f588fd1a77200",
"extension": "py",
"file... | 3.09375 | stackv2 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Nov 2 10:48:17 2020
@author: elliemarfleet
"""
# import all necessary libraries in addition to class framework
import random
import operator
import tkinter
import matplotlib
matplotlib.use('TkAgg')
import matplotlib.pyplot
import matplotlib.animation ... | 182 | 21.52 | 115 | 12 | 1,037 | python | [] | 0 | true | |
2024-11-18T21:00:05.243114+00:00 | 1,619,472,892,000 | 49cdc94d6c79acd28562f01e5a6804d55884ce7a | 3 | {
"blob_id": "49cdc94d6c79acd28562f01e5a6804d55884ce7a",
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"detected_licenses": [
"MIT"
],
"directory_id": "9ea5af0d02cbb9a96f1482bf3bd86fbfe118d2c1",
"extension": "py",
"file... | 2.75 | stackv2 | import numpy as np
# Import the model from the auxillary folder
import sys
sys.path.append("aux")
from Example_3_4_aux import myModel
np.random.seed(1)
# Constants:
N = 10
Ntest = 100
H = 15
varType = "float64"
# Analytical solution
real = lambda x,y: np.exp(-x)*(x+y**3)
# Create the training data
X,Y = np.meshgr... | 48 | 24.23 | 73 | 11 | 382 | python | [] | 0 | true | |
2024-11-18T21:00:05.294010+00:00 | 1,538,675,613,000 | 214ce6f2f252d2128f23c406bbbdae3008b8c9ae | 2 | {
"blob_id": "214ce6f2f252d2128f23c406bbbdae3008b8c9ae",
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"committer_date": 1538675613000,
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"detected_licenses": [
"MIT"
],
"directory_id": "7beb31c44048bee2745c6e4fa062e02a282b3439",
"extension": "py",
"fi... | 2.359375 | stackv2 | """Index page handler package."""
import os
from arduinozore.handlers.crudHandler import CrudHandler
from arduinozore.handlers.tools import get_arduino
from arduinozore.handlers.tools import get_config_name
from arduinozore.models.card import Card
from arduinozore.models.device import Device
from arduinozore.models.se... | 109 | 32.58 | 77 | 15 | 747 | python | [] | 0 | true | |
2024-11-18T21:00:05.402093+00:00 | 1,583,257,129,000 | 0645fe37ed067e2ee6e899c4c091b0b8306292d0 | 2 | {
"blob_id": "0645fe37ed067e2ee6e899c4c091b0b8306292d0",
"branch_name": "refs/heads/master",
"committer_date": 1583257129000,
"content_id": "2ad54241da54d559d9f6c6384e4783f84d8a2489",
"detected_licenses": [
"MIT"
],
"directory_id": "eef13f4b5c1f1384571411c6241f9d6ee26809de",
"extension": "py",
"fi... | 2.3125 | stackv2 | from util import get_path
from util import plot_confusion_matrix
from util import get_categories
from util import generate_current_config_to_string
from util import TrainingData
from simple_cnn import step_decay
from sklearn.metrics import classification_report
import sklearn.metrics as metrics
from keras.callbacks im... | 160 | 43.83 | 174 | 17 | 1,597 | python | [] | 0 | true | |
2024-11-18T21:00:05.458705+00:00 | 1,597,732,863,000 | a2a57e715642200d17e3a22ff42acd6f049df25d | 2 | {
"blob_id": "a2a57e715642200d17e3a22ff42acd6f049df25d",
"branch_name": "refs/heads/master",
"committer_date": 1597732863000,
"content_id": "8da260007c7fa75ecb584e20f30a88c6dd7b4ad3",
"detected_licenses": [
"MIT"
],
"directory_id": "78ac7c4bcf5f8513d0b07cf411e37888f5a62d84",
"extension": "py",
"fi... | 2.328125 | stackv2 | # Written by Chun Kit Wong and CIRC under MIT license:
# https://github.com/wong-ck/DeepSegment/blob/master/LICENSE
import os
import sys
import tarfile
# search for utilities module under root dir
DIR_ROOT = os.path.join(os.path.dirname(__file__), "..", "..", "..")
DIR_ROOT = os.path.abspath(DIR_ROOT)
sys.path.inser... | 57 | 32.19 | 99 | 13 | 544 | python | [] | 0 | true | |
2024-11-18T21:10:21.373555+00:00 | 1,554,736,073,000 | 6df155882f33e4d93f699cebeb0e3bed081056fc | 4 | {
"blob_id": "6df155882f33e4d93f699cebeb0e3bed081056fc",
"branch_name": "refs/heads/master",
"committer_date": 1554736073000,
"content_id": "7ac68883cfd402dbdd0ed07127f077711dbdd5f9",
"detected_licenses": [
"BSD-3-Clause"
],
"directory_id": "70f5f279e051360310f95be895320d8fa6cd8d93",
"extension": "p... | 3.796875 | stackv2 | """
===========
Join styles
===========
Illustrate the three different join styles.
"""
import numpy as np
import matplotlib.pyplot as plt
def plot_angle(ax, x, y, angle, style):
phi = np.radians(angle)
xx = [x + .5, x, x + .5*np.cos(phi)]
yy = [y, y, y + .5*np.sin(phi)]
ax.plot(xx, yy, lw=8, color=... | 47 | 22.89 | 77 | 12 | 343 | python | [] | 0 | true | |
2024-11-18T21:10:21.485006+00:00 | 1,610,816,902,000 | 13365644d1cafe15f0413c686974be1a546986e7 | 3 | {
"blob_id": "13365644d1cafe15f0413c686974be1a546986e7",
"branch_name": "refs/heads/main",
"committer_date": 1610816902000,
"content_id": "21a883e6f151ffb8f283b109f16a156f8ddbe2d7",
"detected_licenses": [
"MIT"
],
"directory_id": "23662216f2883e08fba066bc6179c441459f2203",
"extension": "py",
"file... | 2.8125 | stackv2 | #!/usr/bin/env python3
from jagerml.helper import *
class Loss:
def rememberTrainableLayers(self, trainLayers):
self.trainLayers = trainLayers
def regularization(self):
regularizationLoss = 0
for layer in self.trainLayers:
if layer.weightL1 > 0:
regulari... | 165 | 25.73 | 92 | 18 | 1,137 | python | [] | 0 | true | |
2024-11-18T21:10:21.548418+00:00 | 1,502,741,967,000 | 7805848769231c96e796ac5722525451213f393c | 3 | {
"blob_id": "7805848769231c96e796ac5722525451213f393c",
"branch_name": "refs/heads/master",
"committer_date": 1502741967000,
"content_id": "a55276b470f799bb9815b72a687a5e2124adef24",
"detected_licenses": [
"MIT"
],
"directory_id": "f51307144b887adc352024aac108100c57d64950",
"extension": "py",
"fi... | 2.609375 | stackv2 | #!/usr/bin/env python
import argparse
import cPickle
import logging
from fuel.server import start_server
logger = logging.getLogger()
def main():
parser = argparse.ArgumentParser("Starts fuel server")
parser.add_argument("stream", help="The path to the pickled stream")
parser.add_argument("port", type=... | 27 | 24.52 | 72 | 11 | 164 | python | [] | 0 | true | |
2024-11-18T21:10:21.892663+00:00 | 1,608,283,635,000 | 21f4697374df43646f645a081cfadcc81fdc6909 | 2 | {
"blob_id": "21f4697374df43646f645a081cfadcc81fdc6909",
"branch_name": "refs/heads/master",
"committer_date": 1608283635000,
"content_id": "414e92abef77acd0db1f09a65b357ea92f46169d",
"detected_licenses": [
"MIT"
],
"directory_id": "19e7940e41d15a2dbd5e99525bed531b5d05208b",
"extension": "py",
"fi... | 2.40625 | stackv2 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Created on Tue Jul 30 23:41:38 2019
@author: liudiwei
"""
import random
import string
from douban.items import Subject
from scrapy.linkextractors import LinkExtractor
from scrapy.spiders import CrawlSpider, Request, Rule
class BookSubjectSpider(CrawlSpider):
n... | 56 | 31.11 | 97 | 16 | 445 | python | [] | 0 | true | |
2024-11-18T21:10:21.968891+00:00 | 1,556,499,582,000 | 03aace82ec48cb70284bdcd8ae7cdc2255642ab5 | 2 | {
"blob_id": "03aace82ec48cb70284bdcd8ae7cdc2255642ab5",
"branch_name": "refs/heads/master",
"committer_date": 1556499582000,
"content_id": "5945815b9c39ada244a7922548f9eff58fc68092",
"detected_licenses": [
"MIT"
],
"directory_id": "e5a12a65d7026b5dbad8c7fdeb2a1c41cf30c843",
"extension": "py",
"fi... | 2.421875 | stackv2 | #!/usr/bin/python3
import os
import time
import threading
import read_data
from sys import argv
from timer import preprocessing_timer, preprocessing_records
from multiprocessing import Process, Pool, TimeoutError
from threading import Thread
"""
REQUIREMENTS:
Command line tools:
vcf2bed (convert2bed sort-bed) bed... | 356 | 27.49 | 146 | 20 | 2,928 | python | [] | 0 | true | |
2024-11-18T21:10:22.041079+00:00 | 1,648,657,817,000 | f46e09a2a6a089d023245b23ade7e8462f42fded | 3 | {
"blob_id": "f46e09a2a6a089d023245b23ade7e8462f42fded",
"branch_name": "refs/heads/master",
"committer_date": 1648657817000,
"content_id": "8a27954b8d4490061b5e152ccca91885312f9d07",
"detected_licenses": [
"MIT"
],
"directory_id": "86e292a80731c6824fa410df41761db6a07939ca",
"extension": "py",
"fi... | 2.625 | stackv2 | #!/usr/bin/env python
import re
from operator import itemgetter
from EPPs.common import GenerateHamiltonInputEPP, InvalidStepError
class GenerateHamiltonInputQPCR(GenerateHamiltonInputEPP):
""""Generate a CSV containing the necessary information to for the Make QPCR 1 to 24 samples Hamilton method"""
_use_l... | 166 | 46.91 | 134 | 22 | 1,756 | python | [] | 0 | true | |
2024-11-18T21:10:23.403616+00:00 | 1,621,338,186,000 | 25d81cc6a9d393748eebfcd24a4b1b5d29571fa9 | 2 | {
"blob_id": "25d81cc6a9d393748eebfcd24a4b1b5d29571fa9",
"branch_name": "refs/heads/master",
"committer_date": 1621338186000,
"content_id": "bfbe12e053cf44365f5d04a7699329307b4a54d7",
"detected_licenses": [
"BSD-3-Clause"
],
"directory_id": "1e3dbdd5201937bd29dcc1897b5999df8a3adde7",
"extension": "p... | 2.453125 | stackv2 | import numpy as np
from skmultiflow.transform.base_transform import StreamTransform
# from skmultiflow.trees.nodes.active_learning_node_perceptron import compute_sd
from skmultiflow.utils.utils import get_dimensions
def compute_sd(sum_of_squares: float, sum_of_values: float, samples_seen: float):
variance = 0.0
... | 115 | 38.33 | 124 | 19 | 1,057 | python | [] | 0 | true | |
2024-11-18T21:10:23.449478+00:00 | 1,585,593,171,000 | e53c51b67cc8a6a9a50cb50b40ea428134ec54f8 | 3 | {
"blob_id": "e53c51b67cc8a6a9a50cb50b40ea428134ec54f8",
"branch_name": "refs/heads/master",
"committer_date": 1585593171000,
"content_id": "36fcc5d6d6c0dd3b622fc6da5ded6e2c1ea3d6d4",
"detected_licenses": [
"MIT"
],
"directory_id": "e6be223fc7354ba576ae2ad839e2c9426940a62e",
"extension": "py",
"fi... | 2.859375 | stackv2 | """
Implement commands that interact with AWS Data Pipeline
"""
import fnmatch
import logging
from operator import attrgetter
from typing import List
import boto3
import funcy
import etl.text
from etl.text import join_with_quotes
logger = logging.getLogger(__name__)
logger.addHandler(logging.NullHandler())
class ... | 112 | 33.88 | 119 | 17 | 800 | python | [] | 0 | true | |
2024-11-18T21:10:23.515694+00:00 | 1,585,585,694,000 | 94db90621b7ecb3965c3c30129a7a0a1e5f76cf0 | 2 | {
"blob_id": "94db90621b7ecb3965c3c30129a7a0a1e5f76cf0",
"branch_name": "refs/heads/master",
"committer_date": 1585585694000,
"content_id": "3fb84309727cab33fdfeace20d4ed55c5cc7f0d4",
"detected_licenses": [
"BSD-2-Clause",
"BSD-2-Clause-Views"
],
"directory_id": "a4f6ca0e54c42d47438d9117a7677fdfed... | 2.5 | stackv2 | import checking_functions as check
sensorSpecs = {"name": check.sensor_is_already_present, "description": check.field_is_void}
thingSpecs = {"name": check.thing_is_already_present}
observedPropertySpecs = {"name": check.observed_property_is_already_present}
dataStreamSpecs = {"name": check.data_stream_is_already_prese... | 29 | 37.1 | 91 | 8 | 266 | python | [] | 0 | true | |
2024-11-18T21:10:23.572338+00:00 | 1,693,250,306,000 | 1cf84bd882107708628e8272e4f133dcb51d3590 | 3 | {
"blob_id": "1cf84bd882107708628e8272e4f133dcb51d3590",
"branch_name": "refs/heads/master",
"committer_date": 1693250306000,
"content_id": "837aa87ec12f8e33dd5cf0d6dc3252844cd1785c",
"detected_licenses": [
"BSD-3-Clause"
],
"directory_id": "759b671e6b37617a2782f991d233d262e6a794ad",
"extension": "p... | 2.625 | stackv2 | """Helper functions for quick command line interfaces with skorch and
fire.
"""
from functools import partial
from importlib import import_module
from itertools import chain
import re
import shlex
import sys
from sklearn.base import BaseEstimator
from sklearn.pipeline import FeatureUnion
from sklearn.pipeline import... | 356 | 27.06 | 106 | 14 | 2,495 | python | [] | 0 | true | |
2024-11-18T21:10:23.829963+00:00 | 1,612,793,916,000 | 077e1841e57dcbd409eb055addb8d8456d4425f7 | 3 | {
"blob_id": "077e1841e57dcbd409eb055addb8d8456d4425f7",
"branch_name": "refs/heads/main",
"committer_date": 1612793916000,
"content_id": "be67267eee071bd299ef785f1c64824018326b14",
"detected_licenses": [
"MIT"
],
"directory_id": "6ebac72a9a90bf2c1db6eab2e8006028e19bced7",
"extension": "py",
"file... | 2.8125 | stackv2 | # autotransplate.py
# pip install googletrans==3.1.0a0
from googletrans import Translator, LANGUAGES
# print(LANGUAGES) #เอาไว้ดูวาภาษทาที่ต้องการแปลย่อว่ายังไง
from openpyxl import Workbook
from datetime import datetime
translator = Translator()
# result = translator.translate('แมว')
# print(result.text)
article =... | 39 | 23.56 | 69 | 10 | 280 | python | [] | 0 | true | |
2024-11-18T21:10:23.960932+00:00 | 1,454,396,664,000 | da27c098ced183fbd34ed54df9c60a57767ab5a1 | 3 | {
"blob_id": "da27c098ced183fbd34ed54df9c60a57767ab5a1",
"branch_name": "refs/heads/master",
"committer_date": 1454396664000,
"content_id": "e75cd9b37b71e4766ec10d7a1f10d999fff34f62",
"detected_licenses": [
"MIT"
],
"directory_id": "16f100da7ff8b105575e263929f922c4a771445b",
"extension": "py",
"fi... | 2.8125 | stackv2 | import mwclient as mw
import unicodecsv as csv
import json
import mwparserfromhell as parser
import re
from impl_languages_deduplication import get_standardized_lang
import redis
site = mw.Site('rosettacode.org', path='/mw/')
search_pattern = re.compile(r"([\s\S]*?)<lang (\w+)>([\s\S]+?)<\/lang>")
trim_pattern = re.co... | 139 | 38.38 | 80 | 20 | 1,156 | python | [] | 0 | true | |
2024-11-18T21:10:24.162744+00:00 | 1,530,663,302,000 | d92d5d0b054f75d10ef22cd72a3bebb35f2d3ed6 | 3 | {
"blob_id": "d92d5d0b054f75d10ef22cd72a3bebb35f2d3ed6",
"branch_name": "refs/heads/master",
"committer_date": 1530663302000,
"content_id": "514fd70d8f1745ac1bd2e865d6a04ae824cf3115",
"detected_licenses": [
"MIT"
],
"directory_id": "4464ce90fc28a5f3eeb8fce31c987ed7b51b49c2",
"extension": "py",
"fi... | 2.875 | stackv2 | import csv
import urllib.parse
import discord
import requests
from discord.ext import commands
class Runescape:
def __init__(self, bot: commands.Bot) -> None:
self.bot = bot
@commands.command(aliases=["rs3"], pass_context=True)
async def rs(self, ctx: commands.Context, *username):
"""
... | 160 | 32.99 | 74 | 21 | 1,713 | python | [] | 0 | true | |
2024-11-18T21:10:24.218133+00:00 | 1,611,076,890,000 | 301220755cd0aea029b9127f65904f341a5a32bc | 3 | {
"blob_id": "301220755cd0aea029b9127f65904f341a5a32bc",
"branch_name": "refs/heads/master",
"committer_date": 1611076890000,
"content_id": "fd5d677357e380d278e4425ed80b468ba0567c78",
"detected_licenses": [
"MIT"
],
"directory_id": "19d7629643cc10d75fad146ca90112de26311646",
"extension": "py",
"fi... | 2.734375 | stackv2 | """
EvenVizion library.
https://github.com/RnD-Oxagile/EvenVizion
Supporting paper at:
https://github.com/AIHunters/EvenVizion/blob/master/EvenVizion-video_based_camera_localization_component.pdf
This is licensed under an MIT license. See the README.md file
for more information.
This is an example of getting homogra... | 149 | 45.3 | 108 | 16 | 1,359 | python | [] | 0 | true | |
2024-11-18T21:10:24.328654+00:00 | 1,580,257,091,000 | 6db7b306503bc5bd2b6f72abc2f8bf4f530a8c7b | 4 | {
"blob_id": "6db7b306503bc5bd2b6f72abc2f8bf4f530a8c7b",
"branch_name": "refs/heads/master",
"committer_date": 1580257091000,
"content_id": "71f699b1b0df20ad6a7b9a3d28976f9e8034bcda",
"detected_licenses": [
"MIT"
],
"directory_id": "ca32a4673ed45d28e05c822f31cb9ba1d520cf27",
"extension": "py",
"fi... | 3.6875 | stackv2 | '''
Financial Modeling Prep is a new concept that informs you about stock markets information (news, currencies and stock prices).
This organization runs a free api that we will read data in from
'''
from urllib.request import urlopen
import json
from pandas import DataFrame
def get_jsonparsed_data(ticker):
"""
... | 47 | 22.64 | 126 | 10 | 260 | python | [] | 0 | true | |
2024-11-18T21:10:24.481713+00:00 | 1,435,473,076,000 | 8fc799821fe23b639a0dcfcaf01815834f2b96f4 | 2 | {
"blob_id": "8fc799821fe23b639a0dcfcaf01815834f2b96f4",
"branch_name": "refs/heads/master",
"committer_date": 1435473076000,
"content_id": "f66f9b03bd69293505852d318b53cd4a0efbcab4",
"detected_licenses": [
"MIT"
],
"directory_id": "a6a8aca7908f1951615b24b2518ac56cc0e2880c",
"extension": "py",
"fi... | 2.328125 | stackv2 | from flask import request, abort
from flask.ext.restful import Resource, reqparse
from model.news import News
from util.serialize import news_serialize, news_list_serialize
from util import cache
from util.adminAuth import auth_required
import boto
from PIL import Image
from StringIO import StringIO
import os
newsPar... | 193 | 26.03 | 79 | 19 | 1,189 | python | [] | 0 | true | |
2024-11-18T21:10:25.830528+00:00 | 1,583,378,293,000 | 8796f905d40a37ec9aa35e7d106c6c27c640b258 | 4 | {
"blob_id": "8796f905d40a37ec9aa35e7d106c6c27c640b258",
"branch_name": "refs/heads/master",
"committer_date": 1583378293000,
"content_id": "7502e8cca037996e9df6599da4a1468ecfeb62d6",
"detected_licenses": [
"MIT"
],
"directory_id": "51bb1a87d9496d9ce94aec7fe2d69d26da6db687",
"extension": "py",
"fi... | 4.3125 | stackv2 | '''
file_explorer.py
Matthew Grunauer
3/4/2020
A program that reads and writes to text files
'''
# Function allows for writing and appending to files
def file_writer(filename, mode):
userinp = ""
print("Welcome to the file writer. Type 'close_file' when finished")
try:
with open(filename + ".txt", ... | 73 | 37.23 | 85 | 18 | 633 | python | [] | 0 | true | |
2024-11-18T21:10:25.879343+00:00 | 1,693,217,472,000 | ab4a50cb4632d668a63f3415ef486bc74e091e48 | 3 | {
"blob_id": "ab4a50cb4632d668a63f3415ef486bc74e091e48",
"branch_name": "refs/heads/master",
"committer_date": 1693217472000,
"content_id": "029b7d157f2bbe43b3d930ab329c0de773c6d095",
"detected_licenses": [
"MIT"
],
"directory_id": "10ddfb2d43a8ec5d47ce35dc0b8acf4fd58dea94",
"extension": "py",
"fi... | 3.359375 | stackv2 | # Time: O(logn)
# Space: O(1)
class Solution(object):
def baseNeg2(self, N):
"""
:type N: int
:rtype: str
"""
result = []
while N:
result.append(str(-N & 1)) # N % -2
N = -(N >> 1) # N //= -2
result.reverse()
return "".join(... | 35 | 20.91 | 49 | 15 | 213 | python | [] | 0 | true | |
2024-11-18T21:10:26.123653+00:00 | 1,567,521,172,000 | 444eb677bad4a2d8a3c3cac9ca37ba40d15904d7 | 3 | {
"blob_id": "444eb677bad4a2d8a3c3cac9ca37ba40d15904d7",
"branch_name": "refs/heads/master",
"committer_date": 1567521172000,
"content_id": "45861879f9cb575d0efe76cabc5da22065786970",
"detected_licenses": [
"MIT"
],
"directory_id": "0e34b549d569949263cc827e693e27969b68e893",
"extension": "py",
"fi... | 2.703125 | stackv2 | #!/usr/bin/env python3
#title :stathelper.py
#description :helper functions for hypothesis testing
#author :Junjie Zhu
#date :20180408
#version :0.1
#usage :
#notes :
#python_version :3.6.0
#==================================================================... | 262 | 39.87 | 92 | 19 | 2,543 | python | [] | 0 | true | |
2024-11-18T21:10:26.531646+00:00 | 1,564,380,712,000 | dc32b8e759848260d896c814e4d2e7cd19079322 | 3 | {
"blob_id": "dc32b8e759848260d896c814e4d2e7cd19079322",
"branch_name": "refs/heads/master",
"committer_date": 1564380712000,
"content_id": "8632701ba50afa092145f9e99db5f69e038499b9",
"detected_licenses": [
"MIT"
],
"directory_id": "42ec7724362f766ba4b99c8413a746040ccd39a6",
"extension": "py",
"fi... | 2.609375 | stackv2 | import argparse
import random
from datetime import timedelta
from operator import getitem
from os import listdir, makedirs, remove
from os.path import join, exists, getsize
import h5py
import librosa
import numpy as np
import pandas as pd
import soundfile as sf
from python_speech_features import mfcc
from scipy.io imp... | 291 | 46.16 | 119 | 18 | 3,295 | python | [] | 0 | true | |
2024-11-18T21:10:27.093226+00:00 | 1,647,373,466,000 | 3304511311797d9d31e32e8767ddfcf7c573ff4c | 3 | {
"blob_id": "3304511311797d9d31e32e8767ddfcf7c573ff4c",
"branch_name": "refs/heads/master",
"committer_date": 1647373466000,
"content_id": "ea07b6467e4dcea746d8db117a9e474339031c23",
"detected_licenses": [
"BSD-3-Clause"
],
"directory_id": "f8491be7d1085039925d4672b52cc4cb4ec467db",
"extension": "p... | 2.703125 | stackv2 | from rest_framework import serializers
from .models import Creditcard
# Min and Max number of digits for a credit card
CC_DIGITS_MIN = 15
CC_DIGITS_MAX = 19
class CreditcardSerializer(serializers.ModelSerializer):
"""Serializer to map the Model instance into JSON format."""
email = serializers.ReadOnlyField... | 37 | 34.95 | 74 | 12 | 272 | python | [] | 0 | true | |
2024-11-18T21:10:27.217313+00:00 | 1,616,373,464,000 | 12deeec34394a7f977a459a69f4e0c72c01958fb | 3 | {
"blob_id": "12deeec34394a7f977a459a69f4e0c72c01958fb",
"branch_name": "refs/heads/master",
"committer_date": 1616373464000,
"content_id": "89dcb7f3791aafa99e1fc3a6af67cf0beea406f9",
"detected_licenses": [
"MIT"
],
"directory_id": "dbb320f62c06433b2ca92ee3dd51a6bde8527143",
"extension": "py",
"fi... | 3.3125 | stackv2 | from functools import lru_cache
from itertools import groupby
def candyCrush1D(S):
stack = []
for x in S:
if not stack:
stack.append((x, 1))
elif stack[-1][0] == x:
stack.append((x, stack[-1][1]+1))
elif stack[-1][1] >= 3:
temp = st... | 110 | 25.46 | 72 | 19 | 782 | python | [] | 0 | true | |
2024-11-18T21:10:27.512413+00:00 | 1,366,139,364,000 | fceb411a71a9e59b0ea89b5ea0178e78fc0b1e44 | 2 | {
"blob_id": "fceb411a71a9e59b0ea89b5ea0178e78fc0b1e44",
"branch_name": "refs/heads/master",
"committer_date": 1366139364000,
"content_id": "973e36c99b1398e16659e85a864d8d19fa0b7c9e",
"detected_licenses": [
"BSD-2-Clause-Views"
],
"directory_id": "d3e2439c132d1c9d57f8a4fe853c39744580a2d1",
"extensio... | 2.453125 | stackv2 | # encoding: utf-8
from datetime import datetime
from django.utils.encoding import force_unicode
from django.db import models
from django.db.models.aggregates import Max
import inspect
def get_table_for_field(model, field_name):
for field in model._meta.fields:
if field_name == field.attname:
... | 87 | 43.44 | 130 | 19 | 834 | python | [] | 0 | true | |
2024-11-18T21:10:27.685956+00:00 | 1,597,062,632,000 | ebedbdd7e57867b8df6441b5f8be4e14fbb011bf | 3 | {
"blob_id": "ebedbdd7e57867b8df6441b5f8be4e14fbb011bf",
"branch_name": "refs/heads/master",
"committer_date": 1597062632000,
"content_id": "69eca3621e6da9241143db57031d263dea94ead0",
"detected_licenses": [
"MIT"
],
"directory_id": "1e0718a10abf5772f9ea7ea93386c25a69999015",
"extension": "py",
"fi... | 2.65625 | stackv2 | import tensorflow as tf
import tensorflow.keras.backend as K
import tensorflow_probability as tfp
import numpy as np
def scaled_rmse_metric(scale=1.0, axis=0):
@tf.function
def scaled_rmse(y_true, y_pred):
return K.sqrt(K.mean(K.square((y_true - y_pred)*scale), axis=axis))
return scaled_rmse
def s... | 235 | 51.37 | 121 | 23 | 3,469 | python | [] | 0 | true | |
2024-11-18T21:10:27.820210+00:00 | 1,445,934,001,000 | 7496fcf669e8b8bcc7e0a104727748c18f5da0d8 | 2 | {
"blob_id": "7496fcf669e8b8bcc7e0a104727748c18f5da0d8",
"branch_name": "refs/heads/master",
"committer_date": 1445934001000,
"content_id": "dd0f1e6dfa73a310f4d27e7da1f709ad970c9d3e",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "2d821acbcef35b8c23379847ae42521aacc3d4d3",
"extension": "py"... | 2.34375 | stackv2 |
import tornado.web
from tornado.escape import json_encode
class BaseHandler(tornado.web.RequestHandler):
def get_current_user(self):
user = self.get_secure_cookie("authed_user")
return user or None
def _api_out(self, ok, data=None, msg=None):
return self.write(json_encode(dict(ok=ok... | 21 | 24 | 71 | 14 | 124 | python | [] | 0 | true | |
2024-11-18T21:10:28.057453+00:00 | 1,616,945,586,000 | 6516dc79d6fef9bba9472ea53b203da02d72068d | 3 | {
"blob_id": "6516dc79d6fef9bba9472ea53b203da02d72068d",
"branch_name": "refs/heads/main",
"committer_date": 1616945586000,
"content_id": "7203e759646b2de5bfeaef810bfa92d0b139c012",
"detected_licenses": [
"MIT"
],
"directory_id": "5af7205e7b82d17b4a4b405aa0a5c814136cc008",
"extension": "py",
"file... | 3.046875 | stackv2 | from typing import Any, NoReturn
from http_status_constants import HttpStatusCode
class ApiError(Exception):
""" Exception class for managed errors """
def __init__(self, error: Any, msg=None, http_status_code=HttpStatusCode.HTTP_STATUS_BAD_REQUEST) -> NoReturn:
if msg is None: # default useful err... | 18 | 31.39 | 114 | 12 | 129 | python | [] | 0 | true |
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