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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2024-11-18T21:59:12.736414+00:00 | 1,693,406,835,000 | 2fc3f6205a0a52ecbe6945188d2ea8a70c12dda4 | 3 | {
"blob_id": "2fc3f6205a0a52ecbe6945188d2ea8a70c12dda4",
"branch_name": "refs/heads/main",
"committer_date": 1693406835000,
"content_id": "c5719878b495e31927037d1317eb283f091da1ef",
"detected_licenses": [
"BSD-3-Clause"
],
"directory_id": "b24457559eff579d6e2f5723d188c894cae4029a",
"extension": "py"... | 2.59375 | stackv2 | """
Helper functions
----------------
"""
from __future__ import annotations
import typing as t
from typing import cast, overload
import sqlalchemy as sa
from sqlalchemy import inspect
from sqlalchemy.ext.compiler import compiles
from sqlalchemy.orm import DeclarativeBase
from .model import relationship
__all__ = ... | 354 | 33.36 | 88 | 19 | 2,636 | python | [] | 0 | true | |
2024-11-18T21:59:12.912634+00:00 | 1,606,495,999,000 | 7925364d4e54c371a09c0ca2b70c58911e88248b | 4 | {
"blob_id": "7925364d4e54c371a09c0ca2b70c58911e88248b",
"branch_name": "refs/heads/main",
"committer_date": 1606495999000,
"content_id": "540f074f0194105eb1c77305fd7cce9d193cf17f",
"detected_licenses": [
"MIT"
],
"directory_id": "cec8abc545d03b5150976e9803a9aaea58fa55e1",
"extension": "py",
"file... | 3.5625 | stackv2 | # First of all we initialize an object using an image. From here the image is converted to an HSV Image
#
# findSkin() is a function that by calling 2 other functions, it returns the final mask containing the skin.
# First we call the color segmentation that will segment the HSV picture in a mask.
# Then the region seg... | 77 | 44.04 | 159 | 12 | 816 | python | [] | 0 | true | |
2024-11-18T21:59:13.123072+00:00 | 1,571,154,219,000 | 79e860f3e371cbd5cecf8151c7cbb5e366d0e483 | 3 | {
"blob_id": "79e860f3e371cbd5cecf8151c7cbb5e366d0e483",
"branch_name": "refs/heads/master",
"committer_date": 1571154219000,
"content_id": "f5c6de90d0a61d125bb0e23488f4d3b11e6aba3c",
"detected_licenses": [
"MIT"
],
"directory_id": "421e00dcc509ca5cf0a3d221de6e9c5dc21e2f8d",
"extension": "py",
"fi... | 2.890625 | stackv2 | #! /usr/bin/python3
import json
import argparse
import sys
import string
import collections
ALPHABET_SIZE = len(string.ascii_lowercase)
SHIFT_STRING = string.ascii_lowercase + string.ascii_lowercase + string.ascii_uppercase + string.ascii_uppercase
letter_index_without_register = {}
letter_index_with_register = {}
d... | 177 | 33.88 | 112 | 16 | 1,380 | python | [] | 0 | true | |
2024-11-18T21:59:13.509271+00:00 | 1,579,555,575,000 | 15fa7eafab2529c2557c3531aac2e3e408cb816c | 3 | {
"blob_id": "15fa7eafab2529c2557c3531aac2e3e408cb816c",
"branch_name": "refs/heads/master",
"committer_date": 1579852878000,
"content_id": "4291412ec39b3977a46971494dbf9f8a3b9b5905",
"detected_licenses": [
"MIT"
],
"directory_id": "4fcd2998ed38f37c549807c60298650bc7fbcc7d",
"extension": "py",
"fi... | 2.921875 | stackv2 | import torch as tr
def sdf_plane(point: tr.Tensor):
""" Distance to plane whose normal is x-axis """
return point[..., 0]
def sdf_sphere(point: tr.Tensor, radius: tr.Tensor):
""" Distance to sphere """
return tr.norm(point, dim=-1) - radius
def sdf_box(point: tr.Tensor, box: tr.Tensor):
""" Di... | 46 | 27.11 | 73 | 13 | 350 | python | [] | 0 | true | |
2024-11-18T21:59:13.566977+00:00 | 1,472,745,124,000 | 33d5d345550800ff3de0abe0908632474d1ae7c7 | 3 | {
"blob_id": "33d5d345550800ff3de0abe0908632474d1ae7c7",
"branch_name": "refs/heads/master",
"committer_date": 1472745124000,
"content_id": "a4f91ea51b839b296fed673f80f15f42a213cb36",
"detected_licenses": [
"MIT"
],
"directory_id": "0f8d044d3011375cb0f2de271cd9538d4fb544c6",
"extension": "py",
"fi... | 2.890625 | stackv2 | #!/usr/bin/env python
# coding:utf-8
'''
The script is aims for formatting the srt files.
'''
__author__ = 'sherry'
__date__ = '27 Aug 2016'
# from os import listdir
# from os.path import isfile, join
# import pysrt
# import re
import glob
# 预定义文件夹地址
_filespath = "/Users/sherry/Downloads/Lesson1Subtitles/*"
def _ge... | 51 | 24.82 | 58 | 18 | 373 | python | [] | 0 | true | |
2024-11-18T21:59:13.879119+00:00 | 1,449,011,253,000 | 584c8260b3addf8e742003a8957a6c2c03dea12c | 3 | {
"blob_id": "584c8260b3addf8e742003a8957a6c2c03dea12c",
"branch_name": "refs/heads/master",
"committer_date": 1449011253000,
"content_id": "f1f1242752ef7e38c5913751c605d842b5d69827",
"detected_licenses": [
"MIT"
],
"directory_id": "c4932e8f15d1818fda385a3d750b8a491a49d1bd",
"extension": "py",
"fi... | 3.46875 | stackv2 | import networkx as nx
class ConceptHistory:
#history keeps a cpoy of the graph as reference for what's been presented so far
def __init__(self, callback):
self._historyGraph = nx.DiGraph()
self._historyRecord = []
self._callback = callback
def _addToHistory(self, user, action, node... | 83 | 40.23 | 85 | 19 | 807 | python | [] | 0 | true | |
2024-11-18T21:59:14.177950+00:00 | 1,586,800,582,000 | 4c44f7ab0c6583bdb160be8c4a01f7224f387792 | 3 | {
"blob_id": "4c44f7ab0c6583bdb160be8c4a01f7224f387792",
"branch_name": "refs/heads/master",
"committer_date": 1586800582000,
"content_id": "078d808fbab8c710a7ae028b8fa6091d27e10480",
"detected_licenses": [
"MIT"
],
"directory_id": "a7d14c76d68901da8f197eee934a420333592796",
"extension": "py",
"fi... | 3.171875 | stackv2 | import logging
import functools
def create_log_decorator():
"""
Creates a logging object and returns it
"""
logger = logging.getLogger("relia-logger")
logger.setLevel(logging.DEBUG)
# create the logging file handler
fh = logging.FileHandler("diagnostic.log")
fmt = '%(asctime)s - %(name... | 43 | 26.7 | 83 | 15 | 253 | python | [] | 0 | true | |
2024-11-18T21:59:14.382639+00:00 | 1,689,331,205,000 | 43280b8aed175c5487c18bc180d6c22f38133b66 | 3 | {
"blob_id": "43280b8aed175c5487c18bc180d6c22f38133b66",
"branch_name": "refs/heads/master",
"committer_date": 1689331205000,
"content_id": "8a9c08bc4fe5df6b445ca70720deb404bfb1d825",
"detected_licenses": [
"MIT"
],
"directory_id": "a655b14c035657d6916ab4d557e8adaebd77055d",
"extension": "py",
"fi... | 2.640625 | stackv2 | from kivy.app import App
from kivy.uix.boxlayout import BoxLayout
from kivy.lang import Builder
from plyer import flash
Builder.load_string('''
<FlashInterface>:
Button:
text: "Turn On"
on_release: root.turn_on()
Button:
text: "Turn off"
on_release: root.turn_off()
Button:... | 46 | 15.15 | 40 | 9 | 173 | python | [] | 0 | true | |
2024-11-18T21:59:14.583211+00:00 | 1,602,160,645,000 | 246a05544d65a5c8b00a4ac786e66f355febb4a4 | 2 | {
"blob_id": "246a05544d65a5c8b00a4ac786e66f355febb4a4",
"branch_name": "refs/heads/master",
"committer_date": 1602160645000,
"content_id": "4c584c0bd19e4ab7a67be041e0efd7d92b9ca1b3",
"detected_licenses": [
"MIT"
],
"directory_id": "5261a40658ddb6e38917b57a8f85686337647335",
"extension": "py",
"fi... | 2.3125 | stackv2 | # -*- coding: utf-8 -*-
"""
HISTORY:
Created on Fri May 22 23:39:22 2020
Project: Vortex GUI
Author: DIVE-LINK (www.dive-link.net), dive-link@mail.ru
Shustov Aleksey (SemperAnte), semte@semte.ru
TODO:
[x] switch widget
[x] ip address validator
[x] emulation file dialog
[x] waiting for co... | 240 | 34.8 | 111 | 17 | 1,924 | python | [] | 0 | true | |
2024-11-18T21:59:14.663948+00:00 | 1,678,801,789,000 | c9a5e22a21b7eb3703ec680a335583f49a68f6e8 | 2 | {
"blob_id": "c9a5e22a21b7eb3703ec680a335583f49a68f6e8",
"branch_name": "refs/heads/master",
"committer_date": 1678801789000,
"content_id": "79acfbaa1de79b1ac5cc88655ee2ce0fac667b7c",
"detected_licenses": [
"MIT"
],
"directory_id": "184b40438287d124117dcd48cf9abdab71e116c7",
"extension": "py",
"fi... | 2.5 | stackv2 | import argparse
import nox
nox.options.sessions = ["tests-3.11"]
@nox.session(python=["3.7", "3.8", "3.9", "3.10", "3.11"])
def tests(session):
session.install(".[test]")
command = ["pytest", "tests"] + list(session.posargs)
session.run(*command)
@nox.session
def lint(session):
session.install(".[d... | 65 | 29.17 | 103 | 12 | 511 | python | [] | 0 | true | |
2024-11-18T21:59:14.720816+00:00 | 1,560,979,431,000 | 3694ee321ff0dade1bff7f03605e6a82ca83a9fd | 3 | {
"blob_id": "3694ee321ff0dade1bff7f03605e6a82ca83a9fd",
"branch_name": "refs/heads/master",
"committer_date": 1560979431000,
"content_id": "ff1db638d0338c60d1372f1e5fd7bb41a3882715",
"detected_licenses": [
"MIT"
],
"directory_id": "9661ca39879ccb98fd32a2666a28e2e1a610ca2d",
"extension": "py",
"fi... | 3.046875 | stackv2 | #!/usr/bin/python
""" These two functions can be used with the json module for python as
an object hook to prevent unicode encoding of strings. Simply pass
the Decode_Dict function like so
<< a = json.load( file , object_hook = Decode_Dict ) >>
This will preserve all values but convert strings to ascii... | 51 | 42.75 | 73 | 13 | 503 | python | [] | 0 | true | |
2024-11-18T21:59:14.777149+00:00 | 1,443,464,880,000 | 98764aaec014c29035556373d3cfe1b809d288b2 | 2 | {
"blob_id": "98764aaec014c29035556373d3cfe1b809d288b2",
"branch_name": "refs/heads/master",
"committer_date": 1443464880000,
"content_id": "780913ca3852c3df1bc3a9f9e690200ead40e84c",
"detected_licenses": [
"MIT"
],
"directory_id": "116f2da1306fb65fbbeae572c9a9300536d9e919",
"extension": "py",
"fi... | 2.328125 | stackv2 | # -*- coding: utf-8 -*-
"""
Created on Fri Jul 24 15:50:53 2015
@author: Niklas Bendixen
"""
# Define here the models for your scraped items
#
# See documentation in:
# http://doc.scrapy.org/topics/items.html
from scrapy.item import Item, Field # http://doc.scrapy.org/en/1.0/topics/items.html
from scrapy.loader.... | 29 | 33.76 | 143 | 14 | 262 | python | [] | 0 | true | |
2024-11-18T21:59:14.825659+00:00 | 1,570,808,672,000 | 46eb87b4b67a6cb993a6dad3d1eb92fe795d30f2 | 3 | {
"blob_id": "46eb87b4b67a6cb993a6dad3d1eb92fe795d30f2",
"branch_name": "refs/heads/master",
"committer_date": 1570808672000,
"content_id": "8275f0bcd861c6babf36999b04fb70a0a858a321",
"detected_licenses": [
"MIT"
],
"directory_id": "295e30c065b6a27fb2ab3a676577f81ff7d6a71e",
"extension": "py",
"fi... | 2.734375 | stackv2 | """Track class."""
import logging
import trio
from ._streamer import Streamer
from ._transport import Transport
LOG = logging.getLogger(__name__)
class Track(trio.abc.AsyncResource, Streamer):
"""Something that can produce a stream."""
def __init__(self, func):
"""Store a function for later use.""... | 51 | 29.39 | 76 | 14 | 358 | python | [] | 0 | true | |
2024-11-18T21:59:15.132899+00:00 | 1,689,433,753,000 | 396eaeace6c7022357e6e014ffe3947b8fc36954 | 3 | {
"blob_id": "396eaeace6c7022357e6e014ffe3947b8fc36954",
"branch_name": "refs/heads/master",
"committer_date": 1689433753000,
"content_id": "8f5887bb542b1dcaa493fe67d463b2650eac8b93",
"detected_licenses": [
"MIT"
],
"directory_id": "b742c51d6a2bca6c370bfe28384e0b394b76b76c",
"extension": "py",
"fi... | 2.609375 | stackv2 | """Ability and ability type class definitions."""
from typing import Optional
from ..base import Cached
from ..census import Query
from ..models import AbilityData, AbilityTypeData, ResourceTypeData
from .._proxy import InstanceProxy
__all__ = [
'Ability',
'AbilityData',
'AbilityType',
'ResourceType'... | 330 | 27.51 | 72 | 13 | 2,269 | python | [] | 0 | true | |
2024-11-18T21:59:15.376281+00:00 | 1,541,842,511,000 | 999790a29b22edd46b2eca050f5030c813c657e6 | 3 | {
"blob_id": "999790a29b22edd46b2eca050f5030c813c657e6",
"branch_name": "refs/heads/master",
"committer_date": 1541842511000,
"content_id": "aadd69b7dad66ae86911131462d5d8dfbf895994",
"detected_licenses": [
"MIT"
],
"directory_id": "17e0f88e6ad20dcb8a1ee57fa4fd02626cfbac84",
"extension": "py",
"fi... | 2.953125 | stackv2 | class OpenpyxlTemplateException(Exception):
pass
class CellException(OpenpyxlTemplateException):
pass
class RowException(OpenpyxlTemplateException):
pass
class CellExceptions(RowException):
def __init__(self, cell_exceptions):
self.cell_exceptions = cell_exceptions
super().__init__... | 29 | 22.86 | 94 | 16 | 154 | python | [] | 0 | true | |
2024-11-18T21:59:15.628290+00:00 | 1,688,116,043,000 | ca1e58139f60bdec2d71ad42227d64af61a5a581 | 3 | {
"blob_id": "ca1e58139f60bdec2d71ad42227d64af61a5a581",
"branch_name": "refs/heads/master",
"committer_date": 1688116043000,
"content_id": "9aa288bcfbb3b089ab50415105dd6095863feaca",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "580a43c9bc8cc5cd5db745155e0721b5ba1664f6",
"extension": "py"... | 2.53125 | stackv2 | #
# Copyright 2021 Jaroslav Chmurny
#
# This file is part of AWS Sandbox.
#
# AWS Sandbox is free software developed for educational purposes. It
# is licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License... | 94 | 35.41 | 107 | 12 | 782 | python | [] | 0 | true | |
2024-11-18T21:59:15.941345+00:00 | 1,554,818,026,000 | 61a3fb11228054672ca166027fea142a18634028 | 2 | {
"blob_id": "61a3fb11228054672ca166027fea142a18634028",
"branch_name": "refs/heads/master",
"committer_date": 1554818026000,
"content_id": "51f8dd247aeec81f5a7cff45a2b8dd047f2308b8",
"detected_licenses": [
"MIT"
],
"directory_id": "cd656f5760c31f825f1f718544f7180c16118d90",
"extension": "py",
"fi... | 2.453125 | stackv2 | #!/usr/bin/env python3
"""
Release the code to the given directory as a binary package and a debian package.
The architecture is assumed to be AMD64 (i.e. Linux x64). If you want to release the code for a different architecture,
then please do that manually.
"""
import argparse
import os
import pathlib
import shutil
... | 128 | 32.3 | 119 | 15 | 1,061 | python | [] | 0 | true | |
2024-11-18T21:59:16.044447+00:00 | 1,445,712,077,000 | 57688344e770d3ca6fed0a2b427bfb991cca8e54 | 2 | {
"blob_id": "57688344e770d3ca6fed0a2b427bfb991cca8e54",
"branch_name": "refs/heads/master",
"committer_date": 1445712077000,
"content_id": "d72fa9e370f6f8ce82e5e365ef13d9f38f0dc538",
"detected_licenses": [
"BSD-2-Clause"
],
"directory_id": "b40162533f0e2f467ed975ba2aa1a221bac0b0b1",
"extension": "p... | 2.40625 | stackv2 | from flask import Flask,request,Response,json
from flask.ext.cors import CORS
from spacy.en import English
from scipy.stats import norm
import math
import scipy
pipeline = English()
app = Flask(__name__)
CORS(app)
@app.route("/", methods=['POST'])
def hello():
tokens = pipeline(request.form['line'])
headAndTok... | 32 | 28.16 | 100 | 13 | 243 | python | [{"finding_id": "codeql_py/flask-debug_82dc9f97cdc94423_d7cfa621", "tool_name": "codeql", "rule_id": "py/flask-debug", "finding_type": "problem", "severity": "medium", "confidence": "high", "message": "A Flask app appears to be run in debug mode. This may allow an attacker to run arbitrary code through the debugger.", ... | 1 | true | |
2024-11-18T21:59:16.619746+00:00 | 1,612,959,562,000 | bfbe2b8b17daac8847d77f48f92632ea8b90b9c4 | 3 | {
"blob_id": "bfbe2b8b17daac8847d77f48f92632ea8b90b9c4",
"branch_name": "refs/heads/master",
"committer_date": 1612959562000,
"content_id": "3f8f59cef6c30798d4c23c80f994fbe0d0e43426",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "ec7724453207548809e828aa213fd6b3adb9014c",
"extension": "py"... | 2.53125 | stackv2 | import json
from qgis.PyQt.QtCore import QVariant
# Coloque o caminho do arquivo JSON Para leitura
json_path = 'D:\\Desenvolvimento\\modelagens\\edgv_300\\master_file_300_shp.json'
# Coloque a pasta onde deseja que os arquivos shp sejam salvos.
folder_to_save = 'D:\\Desenvolvimento\\modelagens\\edgv_300\\shp300\\'
c... | 83 | 36.14 | 103 | 23 | 934 | python | [] | 0 | true | |
2024-11-18T21:59:16.813053+00:00 | 1,551,520,888,000 | 0634af8e30e6cb29f4a7721b38d7be5f23348bc5 | 4 | {
"blob_id": "0634af8e30e6cb29f4a7721b38d7be5f23348bc5",
"branch_name": "refs/heads/master",
"committer_date": 1551520888000,
"content_id": "dfcc03460a8d1dad010a49a2c0f6093e940a2558",
"detected_licenses": [
"MIT"
],
"directory_id": "4c8ecf39e363316d121c1031efcad89d750a0ddc",
"extension": "py",
"fi... | 3.90625 | stackv2 | def recursive_division(numberator, denominator):
# divide by denominator
x = numberator//denominator
# while divisible by denominator
while not x % denominator:
x //= denominator
return x
def is_recurring_decimal(n):
if n < 1:
raise ValueError('{n} must be greate... | 84 | 22.56 | 92 | 16 | 477 | python | [] | 0 | true | |
2024-11-18T21:59:17.194182+00:00 | 1,674,141,770,000 | d0b0e62e2df502d0c3b60ed1082aa0cca18f0ef6 | 3 | {
"blob_id": "d0b0e62e2df502d0c3b60ed1082aa0cca18f0ef6",
"branch_name": "refs/heads/main",
"committer_date": 1674141770000,
"content_id": "3203817d1580aa63aebd07644760593cbce2e6d1",
"detected_licenses": [
"MIT"
],
"directory_id": "159c51fb1bffd7af22fb1d70d2949bf92b13cd17",
"extension": "py",
"file... | 2.671875 | stackv2 | from .base import HQBase
class SettingsApi(HQBase):
""" Set of functions to access and modify Global Notice. """
_apiprefix = "/api/v1/settings"
def get_globalnotice(self):
"""GET /api/v1/settings/globalnotice"""
r = self._make_call('get', self._route_globalnotice)
return str(r[... | 27 | 26.89 | 83 | 13 | 176 | python | [] | 0 | true | |
2024-11-18T21:59:17.244024+00:00 | 1,612,962,953,000 | 0f8cf0a589b70b85a37065eb360b9bf027a3e108 | 3 | {
"blob_id": "0f8cf0a589b70b85a37065eb360b9bf027a3e108",
"branch_name": "refs/heads/master",
"committer_date": 1612962953000,
"content_id": "901429d6650fa4f5fa5bac8957436c34aa836a42",
"detected_licenses": [
"MIT"
],
"directory_id": "8bc7a924cf8c9691530b2eff71c1226eed87922c",
"extension": "py",
"fi... | 2.9375 | stackv2 | import spotipy.util as util
import pandas as pd
import spotipy
from datetime import datetime
class SpotifyUtil:
'''
Utility class for accessing Spotify API
'''
query_dict = {
'current_user_recently_played': 'parse_songplays',
'current_user_top_artists': 'parse_top_artists',
'cur... | 210 | 37.38 | 113 | 17 | 1,703 | python | [] | 0 | true | |
2024-11-18T21:59:17.365796+00:00 | 1,478,100,408,000 | 2f14e5e6e90655ad1c22acfba7ed4ee708e65497 | 3 | {
"blob_id": "2f14e5e6e90655ad1c22acfba7ed4ee708e65497",
"branch_name": "refs/heads/master",
"committer_date": 1478100408000,
"content_id": "ff374e0dacac288570073c99fb3183bb18edd552",
"detected_licenses": [
"MIT"
],
"directory_id": "a1b4e5ccfafd44ea84bf65ed0f6477a4951a75e7",
"extension": "py",
"fi... | 3.375 | stackv2 |
import os
import matplotlib.pyplot as plt
class FastaParser(object):
def __init__(self, path):
self.path = path
if not os.path.isfile(self.path):
raise IOError("There is no file at the path specified")
if self.path == None:
raise TypeError("You did not specify a file path")
file_in_path = open(sel... | 118 | 26.87 | 126 | 18 | 855 | python | [] | 0 | true | |
2024-11-18T21:59:17.618361+00:00 | 1,394,169,687,000 | 434de0abfbdec4352c9da32b9800880a0aba3572 | 2 | {
"blob_id": "434de0abfbdec4352c9da32b9800880a0aba3572",
"branch_name": "refs/heads/master",
"committer_date": 1394169687000,
"content_id": "3239ef1effd2aa881e3a921007bee9a5e39c4a2d",
"detected_licenses": [
"MIT"
],
"directory_id": "36a5fbfac3e499eedc2681259183cca50d23489d",
"extension": "py",
"fi... | 2.328125 | stackv2 | import pprint, traceback, re
from random import randrange
class perk:
def modifyAccuracyOffense(self, character = None, enemy = None, attack = None, amount = None, printFlag = True):
pass
def modifyAccuracyDefense(self, character = None, enemy = None, attack = None, amount = None, printFlag = True):
pass
def mo... | 253 | 29.87 | 117 | 16 | 2,135 | python | [] | 0 | true | |
2024-11-18T21:59:18.155058+00:00 | 1,590,258,065,000 | 732e83683f18f9da4d2b574311914b190b96ac8d | 2 | {
"blob_id": "732e83683f18f9da4d2b574311914b190b96ac8d",
"branch_name": "refs/heads/master",
"committer_date": 1590258065000,
"content_id": "14f5f76a690c9c3c439dc243b9435ae4024dd93b",
"detected_licenses": [
"MIT"
],
"directory_id": "5d96d7c1c928c812076302c3fdc62919573265fd",
"extension": "py",
"fi... | 2.375 | stackv2 | from six import PY3
from transliterate.utils import translit
if PY3:
from transliterate.contrib.apps.translipsum.utils import Generator
else:
from lipsum import Generator
__title__ = 'transliterate.contrib.apps.translipsum.__init__'
__author__ = 'Artur Barseghyan'
__copyright__ = '2013-2017 Artur Barseghyan'... | 41 | 31.83 | 71 | 12 | 309 | python | [] | 0 | true | |
2024-11-18T21:59:18.401147+00:00 | 1,689,183,080,000 | 3acf4ac052febbcab0c686df596f0cb770028643 | 3 | {
"blob_id": "3acf4ac052febbcab0c686df596f0cb770028643",
"branch_name": "refs/heads/master",
"committer_date": 1689183080000,
"content_id": "e6ed4f5da36dc4cd4d937e480209c56944988ac9",
"detected_licenses": [
"MIT"
],
"directory_id": "363b8f40cfa26a8269b57998f8397f430767fc2d",
"extension": "py",
"fi... | 2.53125 | stackv2 | # -*- coding: utf-8 -*-
import types
from decimal import Decimal
from throw_out_your_templates_1_core_wrappers import safe_bytes
from throw_out_your_templates_1_core_wrappers import safe_unicode
from throw_out_your_templates_3_core_visitor_map import DEFAULT
from throw_out_your_templates_3_core_visitor_map import Vis... | 39 | 38.82 | 82 | 15 | 400 | python | [] | 0 | true | |
2024-11-18T21:59:18.967857+00:00 | 1,582,290,627,000 | 729e0ed9ac08b7af5b82149b5e68559ab8c44d9a | 2 | {
"blob_id": "729e0ed9ac08b7af5b82149b5e68559ab8c44d9a",
"branch_name": "refs/heads/master",
"committer_date": 1582290627000,
"content_id": "66eb1e913ac33c14db79cf445b1d77381422f829",
"detected_licenses": [
"MIT"
],
"directory_id": "39747b041ce5bd6a86d55bc5b9ad789a572184fd",
"extension": "py",
"fi... | 2.46875 | stackv2 | #!/usr/bin/env python
from ete3 import NCBITaxa
import pandas as pd
from argparse import ArgumentParser
def get_seqids(df, seqid2taxid, ncbitaxa):
filtered = pd.DataFrame()
for i in df.index:
taxid = df.loc[i,"taxID"]
# Intersect descendants with those we have genomes for
descendants ... | 48 | 36.06 | 109 | 14 | 482 | python | [] | 0 | true | |
2024-11-18T21:59:19.038037+00:00 | 1,520,213,482,000 | 0ed3024d68d33f956247b68ec50cf06fecdbb250 | 2 | {
"blob_id": "0ed3024d68d33f956247b68ec50cf06fecdbb250",
"branch_name": "refs/heads/master",
"committer_date": 1520213482000,
"content_id": "2b1373866a763db45d8b5fe074eaf72f9d0db652",
"detected_licenses": [
"MIT"
],
"directory_id": "f1a3f9b6f651c0a60b06623faa9a7ecf84c05af1",
"extension": "py",
"fi... | 2.375 | stackv2 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# @Time : 2017/11/4 上午9:26
# @Author : fanqiang
# @Site :
# @File : spider.py
# @Software: PyCharm
import hashlib
import pathlib
import re
import subprocess
import time
from datetime import datetime
import requests
from PIL import Image, ImageEnhance
from pret... | 235 | 34.57 | 120 | 17 | 2,163 | python | [{"finding_id": "codeql_py/weak-sensitive-data-hashing_53854aab786bb72f_cccb8150", "tool_name": "codeql", "rule_id": "py/weak-sensitive-data-hashing", "finding_type": "path-problem", "severity": "medium", "confidence": "high", "message": "[Sensitive data (password)](1) is used in a hashing algorithm (MD5) that is insec... | 1 | true | |
2024-11-18T21:59:19.102708+00:00 | 1,610,417,687,000 | dfdb5fcbde4cd5fa4f3ac255c4a39d926b415db5 | 3 | {
"blob_id": "dfdb5fcbde4cd5fa4f3ac255c4a39d926b415db5",
"branch_name": "refs/heads/master",
"committer_date": 1610417687000,
"content_id": "eb4bf4e8352e1634901e9a8a47f0208d93a1d4e4",
"detected_licenses": [
"MIT"
],
"directory_id": "a8124c3361ec462e076fbe246c3571672a28a54b",
"extension": "py",
"fi... | 2.53125 | stackv2 | import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import numpy as np
import plotly.graph_objs as go
from datetime import datetime as dt
app = dash.Dash()
app.layout = html.Div([
html.H1(children='Choose a country',
style={
'textAlign... | 48 | 21.23 | 71 | 14 | 270 | python | [] | 0 | true | |
2024-11-18T21:59:19.338404+00:00 | 1,550,235,874,000 | f994b2f076c212cbb0560e3649fd57944d964ca0 | 3 | {
"blob_id": "f994b2f076c212cbb0560e3649fd57944d964ca0",
"branch_name": "refs/heads/master",
"committer_date": 1550235874000,
"content_id": "e5f5160e5d6730d146aa8c8272ec62bf282cc90b",
"detected_licenses": [
"MIT"
],
"directory_id": "e72411ef74b230a15e15515a09950972c170ecf7",
"extension": "py",
"fi... | 3.078125 | stackv2 | from model import *
# Helper
def lenVector(x, y):
return sqrt(x * x + y * y)
def normalizeVector(x, y):
l = sqrt(x * x + y * y)
if l == 0:
l = 0.001
return (x / l, y / l)
def partition(pred, data):
yes, no = [], []
for d in data:
(yes if pred(d) else no).append(d)
retu... | 392 | 34.46 | 114 | 22 | 3,354 | python | [] | 0 | true | |
2024-11-18T21:59:19.443334+00:00 | 1,487,959,616,000 | 06efe57484373002a03f69c490e808456b6f911b | 3 | {
"blob_id": "06efe57484373002a03f69c490e808456b6f911b",
"branch_name": "refs/heads/master",
"committer_date": 1487959616000,
"content_id": "674d74c746fcde9a6e805a66238a11bbe2fca264",
"detected_licenses": [
"MIT"
],
"directory_id": "39b5b8ce18f7bf9566bde4539b9ea9c329dc7f9a",
"extension": "py",
"fi... | 2.640625 | stackv2 | import numpy as np
import cv2
import argparse
import sys
parser = argparse.ArgumentParser(description='Capture Vidoe')
parser.add_argument('videoName', metavar='N', type=str,help='video name')
args = parser.parse_args()
videoName = args.videoName
if (videoName ==''):
print('please provide video name')
sys.exit(... | 38 | 22.42 | 73 | 11 | 233 | python | [] | 0 | true | |
2024-11-18T21:59:19.497935+00:00 | 1,481,814,998,000 | 60ef8571036b2902d67560d24f447eea64a54a83 | 2 | {
"blob_id": "60ef8571036b2902d67560d24f447eea64a54a83",
"branch_name": "refs/heads/master",
"committer_date": 1481814998000,
"content_id": "21391459915491d79ce723cc129d6dae921748ac",
"detected_licenses": [
"MIT"
],
"directory_id": "3afdbc5d33ce8248cc0635985078e91c15c48207",
"extension": "py",
"fi... | 2.359375 | stackv2 | ## @file config_obj.py
# @brief Defines a simple container for user and authentication details, as populated from a configuration file
#
import ConfigParser
config = ConfigParser.RawConfigParser()
config.read('.rektconfig.txt')
user = {'username':config.get('user', 'username'),
'client_id':config.get('user', 'client_... | 18 | 28 | 111 | 9 | 125 | python | [] | 0 | true | |
2024-11-18T21:59:19.713214+00:00 | 1,615,444,394,000 | f74b8d2d0691b72c01e37e80e5a47e6a7cb8a821 | 3 | {
"blob_id": "f74b8d2d0691b72c01e37e80e5a47e6a7cb8a821",
"branch_name": "refs/heads/main",
"committer_date": 1615444394000,
"content_id": "19e9890df87cd93fc535deb61c5141f52ba58f1a",
"detected_licenses": [
"MIT"
],
"directory_id": "bfef929f2c5681431f4eb2c297167c5c07f55b91",
"extension": "py",
"file... | 2.84375 | stackv2 | # Copyright 2021 Peizhi Yan. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | 56 | 23.25 | 80 | 11 | 349 | python | [] | 0 | true | |
2024-11-18T21:59:19.766036+00:00 | 1,575,479,967,000 | 8e037f03584d540f36b9355ff78da8562f17f9df | 3 | {
"blob_id": "8e037f03584d540f36b9355ff78da8562f17f9df",
"branch_name": "refs/heads/master",
"committer_date": 1575479967000,
"content_id": "b1414170a6850e4ad6588f5e1e3ca59524ced254",
"detected_licenses": [
"MIT"
],
"directory_id": "c20c653e1942a8c3681a4bd93bd8202f228328a0",
"extension": "py",
"fi... | 2.90625 | stackv2 | """
Code for figuring out various vector representions of documents
"""
import numpy as np
from collections import defaultdict
import tools
def tf_sents(doc):
""" Create a sentence level tf representation of the document """
words = set(word for word in tools.word_iter(doc))
word_pk = {word: pk for pk, w... | 122 | 28.52 | 87 | 23 | 848 | python | [] | 0 | true | |
2024-11-18T21:59:19.907432+00:00 | 1,432,048,990,000 | a369280b9f205a654d19b1bc4694e21947ff764d | 2 | {
"blob_id": "a369280b9f205a654d19b1bc4694e21947ff764d",
"branch_name": "refs/heads/master",
"committer_date": 1432048990000,
"content_id": "dd4b3659187326e341f289e67727f5f34df12e5f",
"detected_licenses": [
"MIT"
],
"directory_id": "8077e89e880f8ec006db88f37a050f3ff6553a8b",
"extension": "py",
"fi... | 2.5 | stackv2 | __author__ = 'John'
import numpy as np
from sklearn.decomposition import ProjectedGradientNMF
import recsys
import evaluate
import similarity
from nmf_analysis import mall_latent_helper as nmf_helper
from sklearn import decomposition
from numpy.linalg import inv
from sklearn.metrics.pairwise import pairwise_distances
... | 147 | 41.44 | 153 | 19 | 1,660 | python | [] | 0 | true | |
2024-11-18T21:59:20.171732+00:00 | 1,396,247,985,000 | f0196d3edbc34fa207794c68d2c35fe7eedd1c2d | 2 | {
"blob_id": "f0196d3edbc34fa207794c68d2c35fe7eedd1c2d",
"branch_name": "refs/heads/master",
"committer_date": 1396247985000,
"content_id": "adf3252e4ae4448fa6eb25fffeb7f9586469e313",
"detected_licenses": [
"MIT"
],
"directory_id": "8442bc86179825f2b73d10cbce661d88baf137df",
"extension": "py",
"fi... | 2.375 | stackv2 | #
# This file is part of Evergreen. See the NOTICE for more information.
#
import evergreen
from evergreen.futures._base import Executor, Future
from evergreen.locks import Lock
from evergreen.queue import Queue
class _WorkItem(object):
def __init__(self, future, fn, args, kwargs):
self.future = future
... | 73 | 27.07 | 80 | 14 | 435 | python | [] | 0 | true | |
2024-11-18T21:59:20.228695+00:00 | 1,578,575,818,000 | 1e6c6b413de36d169e1a4c6d55bcc52df6393ceb | 3 | {
"blob_id": "1e6c6b413de36d169e1a4c6d55bcc52df6393ceb",
"branch_name": "refs/heads/master",
"committer_date": 1578575818000,
"content_id": "7abe5f26c404024e2a7a7dac2297927ffdc34fea",
"detected_licenses": [
"MIT"
],
"directory_id": "56a14ad617c353feabbb092b5b7541f4e1fa1513",
"extension": "py",
"fi... | 2.515625 | stackv2 | from django.db import models
from django.contrib.auth.models import User
from django.utils.datetime_safe import date
import datetime
class Profile(models.Model):
'''
this is a model class that defines how a user profile will be created
'''
user = models.OneToOneField(User, on_delete = models.CASCADE, ... | 85 | 26.31 | 80 | 12 | 476 | python | [] | 0 | true | |
2024-11-18T21:59:20.488923+00:00 | 1,635,191,831,000 | 645ebebe050fa770771a238a345966ec9e6fc985 | 3 | {
"blob_id": "645ebebe050fa770771a238a345966ec9e6fc985",
"branch_name": "refs/heads/master",
"committer_date": 1635191831000,
"content_id": "3795e6b319cac5d6e7259107f8f73dcadaf8ac9f",
"detected_licenses": [
"BSD-3-Clause"
],
"directory_id": "c2f74061a6964fb52dc2ea10aabcfa756edbf469",
"extension": "p... | 2.5625 | stackv2 | import typing
from .general import __quotes
from .url_methods import __return_json_v3
def forex(apikey: str) -> typing.Optional[typing.List[typing.Dict]]:
"""
Query FMP /fx/ API
:param apikey: Your API key.
:return: A list of dictionaries.
"""
path = f"fx"
query_vars = {"apikey": apikey}... | 39 | 25.21 | 78 | 9 | 276 | python | [] | 0 | true | |
2024-11-18T21:59:20.818174+00:00 | 1,607,831,644,000 | 59ebee313b99483c72ce91b6640e516b764a26ed | 3 | {
"blob_id": "59ebee313b99483c72ce91b6640e516b764a26ed",
"branch_name": "refs/heads/master",
"committer_date": 1607831644000,
"content_id": "fb82c8366065f2f84b4f48688cc8d6078fd24d89",
"detected_licenses": [
"MIT"
],
"directory_id": "e1ca5e083adf94ee707a775cc4d343b9ae42792d",
"extension": "py",
"fi... | 2.8125 | stackv2 | #!/usr/bin/env python
from __future__ import print_function, unicode_literals
import subprocess
from PyInquirer import style_from_dict, Token, prompt, Separator
from pprint import pprint
import sys
from pyfiglet import Figlet
import argparse
import os
class Deepli(object):
"""
Code that runs deepli
"""
... | 89 | 22.15 | 68 | 17 | 494 | python | [] | 0 | true | |
2024-11-18T21:59:20.875167+00:00 | 1,647,262,466,000 | 17475bf45850090454f0078e4ba289491519e276 | 3 | {
"blob_id": "17475bf45850090454f0078e4ba289491519e276",
"branch_name": "refs/heads/master",
"committer_date": 1647262466000,
"content_id": "fefb65c8887138c0b8b29cdcada13a03c7ee0b9a",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "5fe6613dfe1eb6c94b277255bb0a7bded1a53525",
"extension": "py"... | 3.296875 | stackv2 | from typing import List
def findRepeatedDnaSequences(s: str) -> List[str]:
if len(s)<11:
return []
letters_val = {'A': '1', 'C':'2', 'G': '3', 'T':'4'}
s_num = [letters_val[i] for i in s]
values = {}
result = set()
v = s_num[:10]
values[int(''.join(v)... | 26 | 26.54 | 60 | 13 | 195 | python | [] | 0 | true | |
2024-11-18T21:59:20.937831+00:00 | 1,690,377,671,000 | fd52c226270a5fdfdd3a354249ee181bf98064ba | 3 | {
"blob_id": "fd52c226270a5fdfdd3a354249ee181bf98064ba",
"branch_name": "refs/heads/master",
"committer_date": 1690377671000,
"content_id": "c47929a7ad7f1f827322ba9e9168a8c43cede1f5",
"detected_licenses": [
"MIT"
],
"directory_id": "a0eb6744e6f7f509b96d21f0bc8b3f8387f6861c",
"extension": "py",
"fi... | 2.84375 | stackv2 | import util_make_files
util_make_files.pathlib_basic()
import pathlib
import os
import pprint
p_file = pathlib.Path('temp/file.txt')
print(p_file)
# temp/file.txt
print(type(p_file))
# <class 'pathlib.PosixPath'>
p_dir = pathlib.Path('temp/dir')
print(p_dir)
# temp/dir
print(type(p_dir))
# <class 'pathlib.Posix... | 122 | 15.4 | 72 | 12 | 550 | python | [] | 0 | true | |
2024-11-18T21:59:21.219549+00:00 | 1,559,879,241,000 | cf28dd2a6e1a2d5f96783f7f3242031e4e64a8b0 | 2 | {
"blob_id": "cf28dd2a6e1a2d5f96783f7f3242031e4e64a8b0",
"branch_name": "refs/heads/master",
"committer_date": 1559879241000,
"content_id": "842c3b59d507f46cfb66982a0d915b177eb91a20",
"detected_licenses": [
"MIT"
],
"directory_id": "415b5c3ccf75b55c39dadba0773419a21ebeb9d1",
"extension": "py",
"fi... | 2.46875 | stackv2 |
from .template import CollectionBuilder
from moff.node import CollectionNode, Node, node
class ListBuilderItem (CollectionBuilder):
# override
def is_mergeable(self, builder):
return False
# override
def merge(self, builder):
raise Error(".merge() is unsupported.")
# override
... | 21 | 22.1 | 48 | 13 | 104 | python | [] | 0 | true | |
2024-11-18T21:59:21.272074+00:00 | 1,686,041,559,000 | 0a6cac6c7f954658111c2c38410e1e28bd668125 | 3 | {
"blob_id": "0a6cac6c7f954658111c2c38410e1e28bd668125",
"branch_name": "refs/heads/main",
"committer_date": 1686041559000,
"content_id": "09827e667df3d13c0d4a2bb852bcd42a753c809b",
"detected_licenses": [
"BSD-3-Clause"
],
"directory_id": "3bfb784c1178906d3d42ab7e357a3066894a5a61",
"extension": "py"... | 2.859375 | stackv2 | import sys
from loguru import logger
from loguru._colorizer import Colorizer
def formatter(record: dict):
"""
Formats the logging message by:
- Adding color and bold
- Indenting the message
"""
base_format = (
"<b>" # bold
"<light-blue>[eds-scikit]</light-blue>"
"- ... | 51 | 24.14 | 67 | 12 | 307 | python | [] | 0 | true | |
2024-11-18T21:59:21.329874+00:00 | 1,466,259,415,000 | 535e39d7fe7371c3c52c7cf083f5713fc925f093 | 2 | {
"blob_id": "535e39d7fe7371c3c52c7cf083f5713fc925f093",
"branch_name": "refs/heads/master",
"committer_date": 1466259415000,
"content_id": "5111b400d490cda967a1cc070c3b3f72a6cd1341",
"detected_licenses": [
"MIT"
],
"directory_id": "3a23c6263d28ad5828eedd54cf9e8bb55a4b3196",
"extension": "py",
"fi... | 2.375 | stackv2 | import OSC, time
#import rtmidi_python as rtmidi
#midi_out = rtmidi.MidiOut()
#midi_out.open_port(0)
def handler(addr, tags, data, client_address):
txt = "OSCMessage '%s' from %s: " % (addr, client_address)
txt += str(data)
print(txt)
#num = data[0]
#print num
#midi_out.send_message([0x90, 192... | 22 | 30.14 | 113 | 10 | 233 | python | [] | 0 | true | |
2024-11-18T21:59:22.195734+00:00 | 1,608,915,396,000 | 6dc586b4c585504148ffffea1c01eed14d3a51af | 3 | {
"blob_id": "6dc586b4c585504148ffffea1c01eed14d3a51af",
"branch_name": "refs/heads/main",
"committer_date": 1608915396000,
"content_id": "881fbe95871ca390446734593c6aff8c81a3ae11",
"detected_licenses": [
"MIT"
],
"directory_id": "c8b22d7645c41f7e584ead42fb7d3070a1f5a6d4",
"extension": "py",
"file... | 2.75 | stackv2 | #!/usr/bin/env python3
from src.util import *
tiles = read_file_to_list("input.txt")
#optimazation, create variants once
for tile in tiles:
tile.createVariants()
solution = find_solution(tiles,[],set(),0,0)
print(solution[0][0].id * solution[0][-1].id * solution[-1][0].id * solution[-1][-1].id)
# end::starOne... | 34 | 18.65 | 88 | 11 | 196 | python | [] | 0 | true | |
2024-11-18T21:59:22.249242+00:00 | 1,517,025,137,000 | 288f23c256702dc86dfdbba940268cc6e7d326ac | 3 | {
"blob_id": "288f23c256702dc86dfdbba940268cc6e7d326ac",
"branch_name": "refs/heads/master",
"committer_date": 1517025137000,
"content_id": "cb13b3bd1c008a9a46454ffcf1d07c2b4f854b7e",
"detected_licenses": [
"MIT"
],
"directory_id": "cb2db085109c57c96674b03448a5698604eecc38",
"extension": "py",
"fi... | 3.390625 | stackv2 | import json
class HighScoreManager:
"""A HighScoreManager manages the recording of highscores achieved to
a highscore file.
"""
_data = None
def __init__(self, file="highscores.json", gamemode='regular',
auto_save=True, top_scores=10):
"""Constructs a HighScoreManager usin... | 123 | 33.86 | 80 | 16 | 935 | python | [] | 0 | true | |
2024-11-18T21:59:22.592337+00:00 | 1,675,017,549,000 | b686aea94ed6ce6c26b26d3ec194733d11c2347d | 2 | {
"blob_id": "b686aea94ed6ce6c26b26d3ec194733d11c2347d",
"branch_name": "refs/heads/main",
"committer_date": 1675017549000,
"content_id": "620e45c16e4abb32c1fa4a9b918fd0a6bc0149fe",
"detected_licenses": [
"MIT"
],
"directory_id": "de77d2ebb336a32149bd8a9a3d4d50018f264c3b",
"extension": "py",
"file... | 2.3125 | stackv2 | from simple_cqrs.domain_event import DomainEvent
from melange import QueuePublisher
from melange.backends import LocalSQSBackend
from melange.serializers import PickleSerializer, SerializerRegistry
class MyTestMessage:
def __init__(self, message: str) -> None:
self.message = message
if __name__ == "__m... | 25 | 30.96 | 68 | 11 | 172 | python | [] | 0 | true | |
2024-11-18T21:59:22.863163+00:00 | 1,406,720,604,000 | a1324d8c4735140d0b95435a924b1830b1a39eb1 | 3 | {
"blob_id": "a1324d8c4735140d0b95435a924b1830b1a39eb1",
"branch_name": "refs/heads/master",
"committer_date": 1406720604000,
"content_id": "bd462901b22988199d5003381f7a8e1aed0ff314",
"detected_licenses": [
"MIT"
],
"directory_id": "e3c5877e1837ef5f51c70c451fc09dfa83f0065e",
"extension": "py",
"fi... | 2.71875 | stackv2 | import cv2.cv as cv
import cv2
import numpy as np
from Tkinter import Tk
from tkFileDialog import askopenfilename
Tk().withdraw()
filename = askopenfilename()
img = cv2.imread(filename,0)
img = cv2.medianBlur(img,5)
cimg = cv2.cvtColor(img,cv2.COLOR_GRAY2BGR)
cannyimg=cv2.Canny(img,100,200)
circles = cv2.HoughCircle... | 28 | 27.75 | 112 | 12 | 280 | python | [] | 0 | true | |
2024-11-18T21:59:22.918961+00:00 | 1,517,257,089,000 | 655beefd45d79b0d064ded4061f40d3c47784031 | 2 | {
"blob_id": "655beefd45d79b0d064ded4061f40d3c47784031",
"branch_name": "refs/heads/master",
"committer_date": 1517257089000,
"content_id": "989b0a290429d0029fb7c97999e794c77b53ca15",
"detected_licenses": [
"MIT"
],
"directory_id": "1717c2caf13c0381df7aa9a50cd3e212b6e27ae3",
"extension": "py",
"fi... | 2.4375 | stackv2 | from __future__ import division
import argparse
import json
from multiprocessing import Pool
import sys
from gym_puyopuyo.state import State
from gym_puyopuyo.field import TallField
from puyotable.compress import state_encode, state_decode
from puyotable.canonization import canonize_state
from tabulate_deals import ... | 166 | 28.07 | 116 | 19 | 1,097 | python | [] | 0 | true | |
2024-11-18T21:59:23.021290+00:00 | 1,546,741,906,000 | 9f58e998fc508dddd658e90e5eef084c615e6792 | 3 | {
"blob_id": "9f58e998fc508dddd658e90e5eef084c615e6792",
"branch_name": "refs/heads/master",
"committer_date": 1546741906000,
"content_id": "d13730c1037ff6002b629d64c271d177aacb851b",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "9c27879bcba366f939c4b3bcbcbd2e504f48e5ab",
"extension": "py"... | 3.234375 | stackv2 | import click
import json
import csv
import sys
@click.command()
@click.argument('input', type=click.File('rb'))
def cli(input):
"""Dynamodb to CSV
Convert the aws dynamodb output (Scalar types, JSON) to CSV.
\b
Process from stdin:
dyndb2csv -
\b
Process from a file:
dyndb2csv... | 46 | 18.74 | 64 | 13 | 233 | python | [] | 0 | true | |
2024-11-18T21:59:23.124633+00:00 | 1,681,056,055,000 | 35ac79c1b7578eb96f8243dcf7a3c42629e01181 | 3 | {
"blob_id": "35ac79c1b7578eb96f8243dcf7a3c42629e01181",
"branch_name": "refs/heads/master",
"committer_date": 1681056055000,
"content_id": "c2ee020d201ca9919045ef32a7c6daf4e3b931ff",
"detected_licenses": [
"BSD-3-Clause"
],
"directory_id": "a97dd156cdf145493e9988a147d39eb7a67d781d",
"extension": "p... | 2.59375 | stackv2 | #!/usr/bin/env python
import asyncio
import json
import os
import secrets
import signal
import websockets
from connect4 import PLAYER1, PLAYER2, Connect4
JOIN = {}
WATCH = {}
async def error(websocket, message):
"""
Send an error message.
"""
event = {
"type": "error",
"message"... | 198 | 25.61 | 77 | 15 | 1,165 | python | [] | 0 | true | |
2024-11-18T21:59:23.396749+00:00 | 1,535,433,434,000 | b4964f77b5344cc8eef146e34871a002756794ed | 3 | {
"blob_id": "b4964f77b5344cc8eef146e34871a002756794ed",
"branch_name": "refs/heads/master",
"committer_date": 1535433434000,
"content_id": "80d083426acf27a98e6f5a88f3675310102ab3b1",
"detected_licenses": [
"MIT"
],
"directory_id": "a8206b29df21a7fc094f54c09e3e0ce11ddacacd",
"extension": "py",
"fi... | 3.046875 | stackv2 | # coding=utf-8
import os
import io
import ftplib
import pyftp
class FTP(ftplib.FTP):
def __init__(self, host='', user='', passwd='', acct='',
timeout=ftplib._GLOBAL_DEFAULT_TIMEOUT, port=None, source_address=None):
self.source_address = source_address
self.timeout = timeout
... | 130 | 29.93 | 89 | 14 | 939 | python | [] | 0 | true | |
2024-11-18T21:59:28.495528+00:00 | 1,692,680,717,000 | db7ec693ee58562501108d4f117982ff209da123 | 3 | {
"blob_id": "db7ec693ee58562501108d4f117982ff209da123",
"branch_name": "refs/heads/master",
"committer_date": 1692680717000,
"content_id": "7b6524318279f25866c23803c5b8a0a1816f3c1d",
"detected_licenses": [
"MIT"
],
"directory_id": "a475c244c10673d2cd037d31647eb97b093b153a",
"extension": "py",
"fi... | 2.640625 | stackv2 | '''
irqUART demo for pyboard
Author: shaoziyang
Date: 2020.6
http://www.micropython.org.cn
'''
from machine import Pin, UART
from irqUART import irqUART
cnt = 0
def U1_RX_IRQ(t):
global cnt
n = 0
while u1.any():
d = u1.any()
cnt+=d
n+=1
print('[', n, ']',... | 31 | 15.58 | 55 | 11 | 188 | python | [] | 0 | true | |
2024-11-18T21:59:28.556713+00:00 | 1,622,625,078,000 | f6276afe8b8d304eda1390406ab9fbcbdc1e3bcf | 4 | {
"blob_id": "f6276afe8b8d304eda1390406ab9fbcbdc1e3bcf",
"branch_name": "refs/heads/master",
"committer_date": 1622625078000,
"content_id": "d0f005acb8874a3be113d4b989c6b0da893ea418",
"detected_licenses": [
"MIT"
],
"directory_id": "f117d31ece12b25afe7182e0546f63f49a1a88d2",
"extension": "py",
"fi... | 3.96875 | stackv2 | class Dad:
basketball = 1
class Son(Dad):
dance = 2
basketball = 2
def isdance(self):
return f"Yes i dance {self.dance} no. of times"
class Grand_son(Son):
dance = 5
def isdance(self):
return f"I dance awesomely {self.dance} no. of times"
instance1 = Dad()
instance1 = Son()
in... | 21 | 24.48 | 107 | 10 | 148 | python | [] | 0 | true | |
2024-11-18T21:59:28.659034+00:00 | 1,609,734,505,000 | 5b6636eda8870a22ea899cb8ba03e4ffe32033f0 | 4 | {
"blob_id": "5b6636eda8870a22ea899cb8ba03e4ffe32033f0",
"branch_name": "refs/heads/master",
"committer_date": 1609734505000,
"content_id": "cb9359c9500d5a90cc510da4fa022469be0d689e",
"detected_licenses": [
"MIT"
],
"directory_id": "4d0eaa9d9a4d95f280a3b7cd0f05e1656b393894",
"extension": "py",
"fi... | 4.3125 | stackv2 | #Difficulty = Easy
#Submission Speed = 64.69%
'''
Solution-1:
Example: nums = [3,2,1,4] target = 6
Step1) Create a dictionary and populate it with elements of nums as the key and their corresponding index as values.
d = {
3:0,
2:1
1:2
4:3
}
Ste... | 56 | 36.11 | 125 | 13 | 509 | python | [] | 0 | true | |
2024-11-18T21:59:28.827653+00:00 | 1,566,523,034,000 | 616c3e0c3e53aaec7e85ae0965b25ddd77a8ea40 | 3 | {
"blob_id": "616c3e0c3e53aaec7e85ae0965b25ddd77a8ea40",
"branch_name": "refs/heads/master",
"committer_date": 1566523034000,
"content_id": "32eb7ed8192073562f4ea044938ef730b74d621d",
"detected_licenses": [
"MIT"
],
"directory_id": "0f2ca882c67a8dba0be5c0890c18c658aa10025a",
"extension": "py",
"fi... | 2.546875 | stackv2 | from tool.origin_createDataset import createDataset
def getImageListAndLabelList(txt):
"""
txt: a txt file that contain ImagesFullPath and Label
"""
with open(txt, 'r') as f:
lines = f.readlines()
images = [line.rstrip() for line in lines]
labels = [line.split("_")[-1].replace(".jpg... | 20 | 30.4 | 71 | 13 | 154 | python | [] | 0 | true | |
2024-11-18T22:11:23.982569+00:00 | 1,693,578,098,000 | 93fafd798aa7f9b25588bfed62ce7b1a4ddb3f95 | 3 | {
"blob_id": "93fafd798aa7f9b25588bfed62ce7b1a4ddb3f95",
"branch_name": "refs/heads/main",
"committer_date": 1693578098000,
"content_id": "e8435eae0bb4365565dd49680542b2a91b0919aa",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "98c182bda68e5c9d55c2b6317fe8a889069ed821",
"extension": "py",
... | 2.796875 | stackv2 | #!/usr/bin/python3
import json
import datetime
from shutil import copyfile
import os
import sys
filePath = "shared/src/commonMain/resources/schedule.json"
outputPath = filePath
# outputPathiOS = "iosApp/iosApp/schedule.json"
startDate = datetime.date.today()
customOutput = False
shouldPrint = False
# Gathering Arg... | 106 | 33.29 | 107 | 21 | 837 | python | [] | 0 | true | |
2024-11-18T22:11:24.295704+00:00 | 1,668,287,342,000 | 53f6c1a18c3707240a5b6b9ea79ae6820eee1acf | 3 | {
"blob_id": "53f6c1a18c3707240a5b6b9ea79ae6820eee1acf",
"branch_name": "refs/heads/master",
"committer_date": 1668287342000,
"content_id": "e196cd40ab2d303eab4c546ca400006d5ac92863",
"detected_licenses": [
"BSD-3-Clause"
],
"directory_id": "e84feb798166ad65670c11d3ddff7cfae0be4258",
"extension": "p... | 3.328125 | stackv2 | """
jsonspec.pointer.stages
~~~~~~~~~~~~~~~~~~~~~~~
"""
from collections.abc import Mapping, Sequence, Set
class Staged:
obj = None
parent_obj = None
parent_member = None
def __init__(self, obj, parent=None, member=None):
self.obj = obj
self.parent_obj = parent
self.... | 69 | 26.97 | 70 | 15 | 465 | python | [] | 0 | true | |
2024-11-18T22:11:24.454827+00:00 | 1,345,241,706,000 | 48eb2fa8c26bba285b321c43ff543da24c816936 | 3 | {
"blob_id": "48eb2fa8c26bba285b321c43ff543da24c816936",
"branch_name": "refs/heads/master",
"committer_date": 1345241706000,
"content_id": "408c4b2aae6f90bb7455a67363a3457e1caea75a",
"detected_licenses": [
"MIT"
],
"directory_id": "ea1cdf2a2b6393915b28b43eced814ada4b753b0",
"extension": "py",
"fi... | 2.53125 | stackv2 | from sikwidgets.widgets.page import Page
from sikwidgets.widgets.radio_button import RadioButton
from sikwidgets.widgets.widget import WidgetError
# TODO: https://answers.launchpad.net/sikuli/+question/183688
class MenuButton(RadioButton): # a button that spawns a menu
def click(self, offset=None):
previously_sele... | 62 | 29.5 | 78 | 11 | 439 | python | [] | 0 | true | |
2024-11-18T22:11:25.048759+00:00 | 1,601,991,484,000 | 655946785244c624a62769275d4853994314f143 | 3 | {
"blob_id": "655946785244c624a62769275d4853994314f143",
"branch_name": "refs/heads/master",
"committer_date": 1601991484000,
"content_id": "8cb5000965bf55a163c8c75ec3eba8dc739a8c81",
"detected_licenses": [
"MIT"
],
"directory_id": "50afc0db7ccfc6c80e1d3877fc61fb67a2ba6eb7",
"extension": "py",
"fi... | 3.390625 | stackv2 | def solution(day, date1, date2):
days = ["sunday", "monday", "tuesday", "wednesday", "thursday", "friday", "saturday"]
date1 = date1.split("/")
date2 = date2.split("/")
ans = int(date2[0]) - int(date1[0])
if date1[1] != date2[1]:
n = int(date2[1]) - int(date1[1])
ans += 30 * n
x ... | 20 | 29.1 | 89 | 12 | 198 | python | [] | 0 | true | |
2024-11-18T22:11:25.107986+00:00 | 1,487,536,958,000 | c7c89ea1922c55dc48b2139db5da8c965c81aa3f | 3 | {
"blob_id": "c7c89ea1922c55dc48b2139db5da8c965c81aa3f",
"branch_name": "refs/heads/master",
"committer_date": 1487536958000,
"content_id": "8f581ea77c57f4b3a56db879f3615427caf1f8a8",
"detected_licenses": [
"MIT"
],
"directory_id": "2bd4f6c81125ca42f338d4e4f27cf59d0e4d34a1",
"extension": "py",
"fi... | 3.09375 | stackv2 | #!/usr/bin/env python
"""CAM Newton's End Zone Dance
Floods a switch's CAM table with random MAC addresses, making it
start behaving as a hub.
TODO:
- argparse to set options
- check input for validity
"""
import re
import socket
import struct
import random
import time
def random_mac():
"""Returns a random MA... | 120 | 28.02 | 79 | 14 | 994 | python | [] | 0 | true | |
2024-11-18T22:11:25.369654+00:00 | 1,523,822,834,000 | a341a2bcea32697f5174ad35eb117121682ee22d | 3 | {
"blob_id": "a341a2bcea32697f5174ad35eb117121682ee22d",
"branch_name": "refs/heads/master",
"committer_date": 1523822834000,
"content_id": "ab96744ab8e9264c09cb71d27e8688a7c7be0f26",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "d7629c7ce339828eb0722a6f662dd57a4fad4ecc",
"extension": "py"... | 2.828125 | stackv2 | # -*- coding: utf-8 -*-
# Copyright 2017-2018 Niall McCarroll
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... | 79 | 37.85 | 108 | 13 | 723 | python | [] | 0 | true | |
2024-11-18T22:11:25.574506+00:00 | 1,606,319,281,000 | 9c735ecce7e993b21756cb2b42d56ffe70e862ae | 5 | {
"blob_id": "9c735ecce7e993b21756cb2b42d56ffe70e862ae",
"branch_name": "refs/heads/master",
"committer_date": 1606319281000,
"content_id": "15b4e5db39ecdaf3a079f65d5517191cccee3681",
"detected_licenses": [
"MIT"
],
"directory_id": "db874762d017c0c62b2a5db3c9a5fcc514d57405",
"extension": "py",
"fi... | 4.65625 | stackv2 | #Exercício Python 079: Crie um programa onde o usuário possa digitar vários valores numéricos
#cadastre-os em uma lista. Caso o número já exista lá dentro, ele não será adicionado.
#No final, serão exibidos todos os valores únicos digitados, em ordem crescente.
lista = []
while True:
num = int(input("Digite um nú... | 17 | 37.82 | 94 | 18 | 185 | python | [] | 0 | true | |
2024-11-18T22:11:25.833384+00:00 | 1,594,399,996,000 | 9d59835ce3ee4c0c61dfdf89a511f4a0c9d2e798 | 3 | {
"blob_id": "9d59835ce3ee4c0c61dfdf89a511f4a0c9d2e798",
"branch_name": "refs/heads/master",
"committer_date": 1594399996000,
"content_id": "533725e8d853473743f547b9cc3d79e5bf8e162b",
"detected_licenses": [
"MIT"
],
"directory_id": "b5c61f071ccb966f30ea2d0b5655aacf15d3779a",
"extension": "py",
"fi... | 2.8125 | stackv2 | import json
import Company
import Competence
import Credit
import Consult
import Global
import PySimpleGUI as view
def listCompany():
file = Global.DATABASE()
with open(file, 'r') as json_file:
dados = json.load(json_file)
count = len(dados)
listCompany = []
for index in range(count):
... | 94 | 28.17 | 70 | 15 | 535 | python | [] | 0 | true | |
2024-11-18T22:11:25.944948+00:00 | 1,586,275,587,000 | 0166a0dda7916355b391ae869499bcf39a2dc39c | 2 | {
"blob_id": "0166a0dda7916355b391ae869499bcf39a2dc39c",
"branch_name": "refs/heads/master",
"committer_date": 1586275587000,
"content_id": "2571c928682ed39e0d8b1c0dcd5915d58ea3c1d2",
"detected_licenses": [
"MIT",
"BSD-3-Clause",
"Apache-2.0"
],
"directory_id": "abe1a003574ece6d148a336e55add0b... | 2.359375 | stackv2 | from flask_login import current_user
from turkey import app
from turkey.models import Goal, Task, CompletedTask, TaskBreak
import datetime
import calendar
from turkey.utils import get_tasks_history, render_turkey
def get_completed_tasks_display(task_id):
week = get_tasks_history(task_id)
# Calculate widths t... | 115 | 30.48 | 98 | 16 | 781 | python | [] | 0 | true | |
2024-11-18T22:11:26.180368+00:00 | 1,511,948,152,000 | 847081f8a6d55e1c46fbac2c5d6f53a88595a8a1 | 3 | {
"blob_id": "847081f8a6d55e1c46fbac2c5d6f53a88595a8a1",
"branch_name": "refs/heads/master",
"committer_date": 1530201581000,
"content_id": "f69e7593ab63bc89d95ea8040956ef26a9c5677a",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "0afeeea3dbf502de1bcb76dc8c6ca6021d255d05",
"extension": "py"... | 3.015625 | stackv2 | import collections
import enum
import math
import sys
smallest_number = sys.float_info.epsilon
class Angle:
def __init__(self, radians):
self.__radians = radians
@classmethod
def from_radians(class_, radians):
return class_(radians)
@classmethod
def from_degrees(class_, degrees):
return class_... | 177 | 27.03 | 106 | 21 | 1,353 | python | [] | 0 | true | |
2024-11-18T22:11:26.312964+00:00 | 1,520,578,482,000 | cd54b05fdfdc7dc67b655332637ac23d386c6044 | 2 | {
"blob_id": "cd54b05fdfdc7dc67b655332637ac23d386c6044",
"branch_name": "refs/heads/master",
"committer_date": 1520578482000,
"content_id": "27e57a9cbcecfb0a45c60f9759d7396352f6034f",
"detected_licenses": [
"MIT"
],
"directory_id": "a158a3fa8465bec6222aeb2f38d0baaec0a97a28",
"extension": "py",
"fi... | 2.375 | stackv2 | import codecs
import json
import tldextract
DATA_FILE = "/home/rkapoor/Documents/ISI/data/DIG-Nov-Eval/gt-v02-all.jl"
DOMAIN_OF_INTEREST = 'backpage.com'
def safe_copy(json_from, json_to, field):
if field in json_from and json_from[field] is not None:
json_to[field] = json_from[field]
def get_domain(jso... | 35 | 26.37 | 76 | 13 | 247 | python | [] | 0 | true | |
2024-11-18T22:11:26.355052+00:00 | 1,693,720,774,000 | 977e1c3ae9cee9dd4095655fd7df2dae46c7d789 | 3 | {
"blob_id": "977e1c3ae9cee9dd4095655fd7df2dae46c7d789",
"branch_name": "refs/heads/master",
"committer_date": 1693720774000,
"content_id": "e4dd3435d6cd74d07f0e93697bf91415820d35b3",
"detected_licenses": [
"MIT"
],
"directory_id": "77bf313c3bb3d014f7f2b8b64cf92dad7abd0910",
"extension": "py",
"fi... | 3.21875 | stackv2 | # messages can be any size (that fits in memory)
# server.py
import socketserver
class MyTCPHandler(socketserver.BaseRequestHandler):
def handle(self):
self.data = self.request.recv(1024).strip()
print('from', str(self.client_address[0]))
print(self.data)
self.request.sendall(self.data.upper())
with socketse... | 33 | 29.55 | 73 | 13 | 255 | python | [] | 0 | true | |
2024-11-18T22:11:26.412859+00:00 | 1,689,687,458,000 | 5c6717bc3cba5b77a31e39fa5db20e7e66a8bb5a | 3 | {
"blob_id": "5c6717bc3cba5b77a31e39fa5db20e7e66a8bb5a",
"branch_name": "refs/heads/main",
"committer_date": 1689687458000,
"content_id": "8459d3cfe2a486ebdcf6f64c27cdb458a2d82263",
"detected_licenses": [
"MIT"
],
"directory_id": "47fdde90ff7017bbff0646c77ba66c51e8a5b74d",
"extension": "py",
"file... | 2.6875 | stackv2 | from enum import Enum
class MatchupType(str, Enum):
REGULAR = "regular"
PLAYOFF = "playoff"
PLAYOFF_BYE = "playoff_bye"
LOSER = "loser"
CHAMPIONSHIP = "championship"
def display(self):
if self == MatchupType.REGULAR:
return "Regular season matchup"
if self == Match... | 21 | 27.19 | 44 | 10 | 152 | python | [] | 0 | true | |
2024-11-18T22:11:26.566223+00:00 | 1,689,160,599,000 | 7882dddc607c263073820134512ffda73011447a | 2 | {
"blob_id": "7882dddc607c263073820134512ffda73011447a",
"branch_name": "refs/heads/master",
"committer_date": 1689160599000,
"content_id": "e18c6a145546317ba80ea0f93d5f2cf4a5521f43",
"detected_licenses": [
"MIT"
],
"directory_id": "627fbcb61f9420edb1e92d2f245c3a254e1f2506",
"extension": "py",
"fi... | 2.359375 | stackv2 | import winreg
import re
import pythoncom
import win32com.client
import ctypes
import wmi
from common.stringops import remove_non_ascii
def get_windows_data():
key = r"SOFTWARE\Microsoft\Windows NT\CurrentVersion"
with winreg.OpenKey(winreg.HKEY_LOCAL_MACHINE, key) as key:
releaseId = int(winreg.Query... | 129 | 32.71 | 110 | 16 | 1,017 | python | [] | 0 | true | |
2024-11-18T22:11:26.685015+00:00 | 1,598,880,787,000 | 80e07eaf21a3fa040eacded62df6b62f8e64283d | 3 | {
"blob_id": "80e07eaf21a3fa040eacded62df6b62f8e64283d",
"branch_name": "refs/heads/master",
"committer_date": 1598880787000,
"content_id": "bc1c75c52658225744a8a45447533aadfde90f05",
"detected_licenses": [
"MIT"
],
"directory_id": "556f6b68ba6401e6d7003edfdaca454925dab71a",
"extension": "py",
"fi... | 2.859375 | stackv2 | # OHLCV 데이터에서 기술적 분석 지표들의 FeatureSet을 추출한다
# -------------------------------------------------------------
import pandas as pd
import numpy as np
from MyUtil.ComFeatureSet import getUpDnClass
# 과거 n-day 동안의 주가 패턴으로 Feature Set을 구성한다
def getPatternFeatureSet(data, u, d, nPast=20, nHop=3, nFuture=20, binary=False):
... | 81 | 35.37 | 102 | 16 | 1,163 | python | [] | 0 | true | |
2024-11-18T22:11:26.730998+00:00 | 1,614,348,304,000 | 23634a6f74092cb9c4c0c69295f108c9a97b0f53 | 3 | {
"blob_id": "23634a6f74092cb9c4c0c69295f108c9a97b0f53",
"branch_name": "refs/heads/master",
"committer_date": 1614348304000,
"content_id": "ec1974ff423337c87d5753b45d6fb78f3cc54827",
"detected_licenses": [
"BSD-3-Clause"
],
"directory_id": "f4c20145f702b692316c6464e79a477d238771fd",
"extension": "p... | 2.703125 | stackv2 | import numpy as np
import pandas as pd
import scipy
from typing import List
from tqdm.auto import tqdm, trange
from .imputers import impute
from .tools.utils_bootstrap import empirical_bootstrap
from .tools import utils_preddiff as ut_preddiff
from functools import partial
global pbar
###############################... | 302 | 50.97 | 120 | 19 | 3,425 | python | [] | 0 | true | |
2024-11-18T22:11:26.947257+00:00 | 1,598,978,360,000 | a95275209de0ed5c1a1e76a6a2f81bbeeaa80975 | 2 | {
"blob_id": "a95275209de0ed5c1a1e76a6a2f81bbeeaa80975",
"branch_name": "refs/heads/master",
"committer_date": 1598978360000,
"content_id": "9f541b49e9e201725a3aa0e7a145179425a7f12b",
"detected_licenses": [
"MIT"
],
"directory_id": "4db5f7f602d353eff9e8e6de94cdd7f2b41f7bf3",
"extension": "py",
"fi... | 2.421875 | stackv2 | from .base import AbstractDataset
import pandas as pd
from datetime import date
class ML1MDataset(AbstractDataset):
@classmethod
def code(cls):
return 'ml-1m'
@classmethod
def url(cls):
return 'http://files.grouplens.org/datasets/movielens/ml-1m.zip'
@classmethod
def zip_fi... | 40 | 25.9 | 72 | 12 | 254 | python | [] | 0 | true | |
2024-11-18T22:11:27.260796+00:00 | 1,611,863,002,000 | 73d9caa5f0b6d32e678dca3213749da0f50f097f | 2 | {
"blob_id": "73d9caa5f0b6d32e678dca3213749da0f50f097f",
"branch_name": "refs/heads/master",
"committer_date": 1611863002000,
"content_id": "506338a62674f3980b02af9b04538897e35e0d07",
"detected_licenses": [
"MIT"
],
"directory_id": "5ebb857895b1c3adc1de0e04ecbb9e081ddef2b1",
"extension": "py",
"fi... | 2.3125 | stackv2 | from typing import List, Iterator
from .__core__ import PyotCore, PyotStatic
# PYOT STATIC OBJECTS
class LeaderboardPlayerData(PyotStatic):
puuid: str
game_name: str
tag_line: str
leaderboard_rank: int
ranked_rating: int
number_of_wins: int
@property
def account(self) -> "Account":
... | 48 | 25.56 | 80 | 14 | 320 | python | [] | 0 | true | |
2024-11-18T22:11:27.317037+00:00 | 1,596,381,974,000 | ba0c01e28e077518dd50d678f9e440a8a3470c94 | 3 | {
"blob_id": "ba0c01e28e077518dd50d678f9e440a8a3470c94",
"branch_name": "refs/heads/master",
"committer_date": 1596381974000,
"content_id": "f76ab3c70b534dddc66b49a1725c011d83f3b504",
"detected_licenses": [
"MIT"
],
"directory_id": "a01f33a7a6a355b2071963304577d8f3a4caaa0c",
"extension": "py",
"fi... | 3.265625 | stackv2 | # --------------
#Header files
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
#path of the data file- path
data = pd.read_csv(path)
#Code starts here
data['Gender'].replace('-','Agender',inplace=True)
gender_count = data['Gender'].value_counts()
gender_count.plot(kind='ba... | 76 | 23.88 | 87 | 12 | 522 | python | [] | 0 | true | |
2024-11-18T22:11:27.615238+00:00 | 1,619,928,035,000 | fe28d7f9c84880b3bfe746fa5fd5a98db5243d21 | 3 | {
"blob_id": "fe28d7f9c84880b3bfe746fa5fd5a98db5243d21",
"branch_name": "refs/heads/main",
"committer_date": 1619928035000,
"content_id": "702885514a87451d8c166241307da1308c903863",
"detected_licenses": [
"MIT"
],
"directory_id": "d49d3eca655d9b52b7249c256e091a5672b6fdd5",
"extension": "py",
"file... | 3.09375 | stackv2 | import numpy as np
import imageio
from PIL import Image
import sys
class stereoViterbi():
def endPointError(self, depthArray, gt):
rows, cols = depthArray.shape
error = np.sum(np.abs(depthArray - gt)) / (rows * cols)
return error
def errorRate(self, depthArray, gt):
rows, cols ... | 99 | 40.84 | 142 | 22 | 1,030 | python | [] | 0 | true | |
2024-11-18T22:11:27.686033+00:00 | 1,686,577,427,000 | 1a2e8306918956d534de1bc935a87f0e3f9e4312 | 3 | {
"blob_id": "1a2e8306918956d534de1bc935a87f0e3f9e4312",
"branch_name": "refs/heads/master",
"committer_date": 1686577427000,
"content_id": "537a2eea2cc41f181fd13c34e8ff365986016ac7",
"detected_licenses": [
"MIT"
],
"directory_id": "0948f5944bcb95af55ac258d6104044ddbedab6b",
"extension": "py",
"fi... | 2.71875 | stackv2 | # epd_async.py Demo of nano_gui asynchronous code.
# Needs a large screen e.g.
# https://www.waveshare.com/wiki/2.7inch_e-Paper_HAT
# or 4.2" Waveshare Pico ePaper display.
# Released under the MIT License (MIT). See LICENSE.
# Copyright (c) 2020-2022 Peter Hinch
# color_setup must set landcsape False, asyn True and ... | 127 | 30.09 | 98 | 16 | 1,211 | python | [] | 0 | true | |
2024-11-18T22:11:28.078508+00:00 | 1,618,605,866,000 | 5b63af9c7704d94141ea276cb7bdc95467c9b46e | 3 | {
"blob_id": "5b63af9c7704d94141ea276cb7bdc95467c9b46e",
"branch_name": "refs/heads/main",
"committer_date": 1618605866000,
"content_id": "eb57bbb9a91f24852eb35a40cf7a2b0a1257aa52",
"detected_licenses": [
"MIT"
],
"directory_id": "169607b7367203b983e50f5e609cff5b3d03b401",
"extension": "py",
"file... | 2.640625 | stackv2 | #!/usr/bin/env python3
# coding=utf-8
from struct import calcsize
'''
disambiguation of struct keys as used in F1 2020 telemetry
uint8 unsigned char B
int8 signed char b
uint16 unsigned short H
int16 short h
float f
uint64 unsigned long long Q
'''
header = "<HBBBBQfIBB"
#structu... | 128 | 26.42 | 88 | 11 | 1,060 | python | [] | 0 | true | |
2024-11-18T22:11:28.130194+00:00 | 1,521,598,529,000 | b39fc53d3343eabb683d9eb5264de490dca7b8c1 | 3 | {
"blob_id": "b39fc53d3343eabb683d9eb5264de490dca7b8c1",
"branch_name": "refs/heads/master",
"committer_date": 1521598529000,
"content_id": "34693fa027eb48d0392b78a6905dab7ae0907efc",
"detected_licenses": [
"MIT"
],
"directory_id": "50c51e40abbed5f8fe07399df61ffb3c8e648c06",
"extension": "py",
"fi... | 2.875 | stackv2 | import subprocess
import re
class NmapWrapper:
ip_addr_regex = re.compile('\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3}')
router_regex = re.compile('Nmap scan report for gateway')
NMAP_COMMAND = 'sudo nmap -p 22,80,445,65123,56123 -O 192.168.0.*'
def __init__(self):
self.router_ip = None
self.t... | 38 | 32.61 | 94 | 18 | 340 | python | [] | 0 | true | |
2024-11-18T22:11:28.237542+00:00 | 1,583,036,273,000 | a6e12a6780b7120b1abbdb34de4c8289d69d7ca3 | 3 | {
"blob_id": "a6e12a6780b7120b1abbdb34de4c8289d69d7ca3",
"branch_name": "refs/heads/master",
"committer_date": 1583036273000,
"content_id": "3401e7507db16060c32472b5316b7b490dd97964",
"detected_licenses": [
"MIT"
],
"directory_id": "39f06a517576bced6c1f7c228e907287a6ab221c",
"extension": "py",
"fi... | 2.65625 | stackv2 | from .DatabaseConnector import DatabaseConnector
from .FileDataManager import FileDataManager
import logging
class DatabaseDataManager:
def __init__(self, db_host, db_username, db_password, db_name):
self.connector = DatabaseConnector(db_host, db_username, db_password, db_name)
self.insert_statem... | 140 | 40.22 | 105 | 20 | 1,128 | python | [] | 0 | true | |
2024-11-18T22:11:28.287950+00:00 | 1,596,087,036,000 | d5bb142e961c85625b1a9cd0f456f9c7913a19bc | 2 | {
"blob_id": "d5bb142e961c85625b1a9cd0f456f9c7913a19bc",
"branch_name": "refs/heads/master",
"committer_date": 1596087036000,
"content_id": "18d39385215b1bddc2149cae2029c35b32405a52",
"detected_licenses": [
"MIT"
],
"directory_id": "eeeacb9258ac76ad1c967d5d79edcf8fd1cc9afa",
"extension": "py",
"fi... | 2.5 | stackv2 | class Anime():
def __init__():
return
def get_anime_details(self, id):
id = str(id)
params = {
'fields': ','.join(self.anime_fields),
}
uri = f'anime/{id}'
return self._api_handler.call(uri, params=params)
# need pagination here
def search_a... | 59 | 29.75 | 77 | 13 | 434 | python | [] | 0 | true | |
2024-11-18T22:11:28.382873+00:00 | 1,636,121,300,000 | 236e0baf300f14c8ceebaf729c5335f5ebf48e5a | 3 | {
"blob_id": "236e0baf300f14c8ceebaf729c5335f5ebf48e5a",
"branch_name": "refs/heads/master",
"committer_date": 1636121300000,
"content_id": "b777cc1562c92f0e7fe3dd30a699917effb19089",
"detected_licenses": [
"MIT"
],
"directory_id": "a13e3f41abc70b25160b4935fa4df07090a76799",
"extension": "py",
"fi... | 2.71875 | stackv2 | #!/usr/bin/env python
# coding: utf-8
#
# Load libraries
#
import pandas as pd # manipulate dataframes
import matplotlib
import matplotlib.pyplot as plt # plotting
import numpy as np
import time, h5py, imelt, torch, os
from sklearn.metrics import mean_squared_error
from tqdm import tqdm
# First we check if CUDA i... | 85 | 31.98 | 131 | 15 | 678 | python | [] | 0 | true | |
2024-11-18T22:11:28.498758+00:00 | 1,621,604,903,000 | 2a2dea01f781ac01e24dc99294951c0a7f0585f2 | 3 | {
"blob_id": "2a2dea01f781ac01e24dc99294951c0a7f0585f2",
"branch_name": "refs/heads/main",
"committer_date": 1621604903000,
"content_id": "6221e6ae96393c655dac10a83422320769998ea1",
"detected_licenses": [
"MIT"
],
"directory_id": "7fad93d1f6ad4b51d22a78ea31bbb0408f7ccff4",
"extension": "py",
"file... | 3.015625 | stackv2 | class InvalidToken(Exception):
"""An Exception Raised When an Invalid Token was Supplied."""
def __init__(self):
super(InvalidToken, self).__init__("An Invalid Bearer Token was Supplied to Weverse.")
class PageNotFound(Exception):
r"""
An Exception Raised When a link was not found.
Parame... | 24 | 29.25 | 94 | 11 | 164 | python | [] | 0 | true | |
2024-11-18T22:11:29.225346+00:00 | 1,592,281,968,000 | 7403bc25dffd01a7468612f712588c7c5be7e206 | 3 | {
"blob_id": "7403bc25dffd01a7468612f712588c7c5be7e206",
"branch_name": "refs/heads/master",
"committer_date": 1592281968000,
"content_id": "1d1c49ef5a3638ac20ebfe792af7e650477c3e6f",
"detected_licenses": [
"MIT"
],
"directory_id": "6189a9d1361c57aded429d811874808b28509381",
"extension": "py",
"fi... | 2.90625 | stackv2 | # This file will run the sequence of code that will pull all workspaces, channels, groups and threads from your user scope.
# Please go through the README for instructions on how to configure and run.
import files
import connect
# Read the oauth key.
auth_key_file = open("oauth_key.txt","r")
auth_key = auth_key_file.... | 101 | 35.65 | 123 | 17 | 857 | python | [] | 0 | true | |
2024-11-18T22:11:29.272318+00:00 | 1,681,117,027,000 | c02242a48a5cd17b80c30c27ccd8fcade6658562 | 3 | {
"blob_id": "c02242a48a5cd17b80c30c27ccd8fcade6658562",
"branch_name": "refs/heads/master",
"committer_date": 1681117027000,
"content_id": "be4f72ae05b08f5410171fb3ff1d1a4c72f0e23d",
"detected_licenses": [
"MIT"
],
"directory_id": "096ab431340d348cccefd2ece72da225603b4dbc",
"extension": "py",
"fi... | 2.953125 | stackv2 | """
Created on 10 Jan 2017
@author: Sergey Denisov
"""
from functools import wraps
from typing import Any
from time import sleep
import inspect
def development_mode(dev: bool, with_return: Any):
def decorator_function(func):
@wraps(func)
def inner(*args, **kwargs):
if not dev:
... | 122 | 25.32 | 131 | 20 | 733 | python | [] | 0 | true | |
2024-11-18T22:11:29.422447+00:00 | 1,607,797,565,000 | 812de2b5be1d1527955790e39a04586e8dbb54bf | 3 | {
"blob_id": "812de2b5be1d1527955790e39a04586e8dbb54bf",
"branch_name": "refs/heads/main",
"committer_date": 1607797565000,
"content_id": "4012b3ddb9079c778b3c07fd569818e789e40393",
"detected_licenses": [
"MIT"
],
"directory_id": "9acbbab24f239612a9a64914922e99da01c34d57",
"extension": "py",
"file... | 2.859375 | stackv2 | import joblib
class Churn:
def __init__(self):
self.scaler = joblib.load('../parameters/minmaxscaler_cycle3.joblib')
def data_cleaning(self, df1):
new_columns = {'Age': 'age', 'Balance': 'balance', 'NumOfProducts': 'num_of_products'}
df1.rename(columns=new_columns, inplace... | 25 | 32.84 | 94 | 11 | 202 | python | [] | 0 | true | |
2024-11-18T22:11:30.564506+00:00 | 1,540,658,464,000 | 62440f66e91bd82163a172fdb7d5b933b0d62c64 | 3 | {
"blob_id": "62440f66e91bd82163a172fdb7d5b933b0d62c64",
"branch_name": "refs/heads/master",
"committer_date": 1540658464000,
"content_id": "968841703e928cf65d29a8172ae2f461720b658d",
"detected_licenses": [
"MIT"
],
"directory_id": "91c4b223cb5d8ae9c99cdba09ec347685f979058",
"extension": "py",
"fi... | 3.28125 | stackv2 | from nltk.corpus import brown
class Corpus:
"""
Corpus wrapper that normalizes a pos-tagged corpus by setting all words to lowercase
"""
def __init__(self, tagged_sentences):
"""
:param tagged_sentences: list of lists of tuples, where each list is a sentence and each tuple is a token ... | 56 | 29.71 | 120 | 16 | 406 | python | [] | 0 | true | |
2024-11-18T22:11:30.898097+00:00 | 1,692,884,989,000 | 8f28e1446b2112acbce259c0a05e3d2efc96f15e | 3 | {
"blob_id": "8f28e1446b2112acbce259c0a05e3d2efc96f15e",
"branch_name": "refs/heads/master",
"committer_date": 1692884989000,
"content_id": "6b1d57430acdcc0bdb05ce722dc388c76bb71e27",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "080db1ae362de6823e7c78ab6071c82e347ce967",
"extension": "py"... | 2.625 | stackv2 | from pydantic import BaseModel
from typing import Dict
def _to_camel_case(snake_str: str) -> str:
components = snake_str.split('_')
# We capitalize the first letter of each component except the first one
# with the 'title' method and join them together.
return components[0] + ''.join(x.title() for x i... | 26 | 27.15 | 91 | 11 | 178 | python | [] | 0 | true | |
2024-11-18T22:11:30.981171+00:00 | 1,557,848,801,000 | 83e7ee3d751ad671201219136ae2637c6a261375 | 3 | {
"blob_id": "83e7ee3d751ad671201219136ae2637c6a261375",
"branch_name": "refs/heads/master",
"committer_date": 1557848801000,
"content_id": "66a27f70ab75946475a5d5da2cfc4fb6e23366aa",
"detected_licenses": [
"MIT"
],
"directory_id": "aac26984e0e869a6a6a604b7b249c8b6c4b13803",
"extension": "py",
"fi... | 3.15625 | stackv2 | import numpy as np
import os
from .SearchForFile import SearchForFile
from .SearchForFilePattern import SearchForFilePattern
def FindPDSFiles(InPath,FMTname,FilePattern):
'''
Searches a directory (InPath) for a .fmt file and for all of the
data files.
Inputs:
InPath: An absolute path to the folder which conta... | 41 | 31 | 66 | 12 | 352 | python | [] | 0 | true | |
2024-11-18T22:11:31.045512+00:00 | 1,532,043,324,000 | f82dcefb7aa5017b5153e6c109df9244ee99f4b3 | 2 | {
"blob_id": "f82dcefb7aa5017b5153e6c109df9244ee99f4b3",
"branch_name": "refs/heads/master",
"committer_date": 1532043324000,
"content_id": "f667a9b6e4b5f297ffe0af8359f70f16cf263caa",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "09e5c8b938dcdcec91cdb21092ed5ff9feecfc56",
"extension": "py"... | 2.328125 | stackv2 | import logging
import time
import sys
from btfxwss import BtfxWss
log = logging.getLogger(__name__)
fh = logging.FileHandler('test.log')
fh.setLevel(logging.DEBUG)
sh = logging.StreamHandler(sys.stdout)
sh.setLevel(logging.DEBUG)
log.addHandler(sh)
log.addHandler(fh)
logging.basicConfig(level=logging.DEBUG, handler... | 46 | 21.11 | 59 | 11 | 302 | python | [] | 0 | true | |
2024-11-18T22:11:31.093574+00:00 | 1,660,867,759,000 | c601e1f16557716a19f326990fa8e75cf665dad5 | 2 | {
"blob_id": "c601e1f16557716a19f326990fa8e75cf665dad5",
"branch_name": "refs/heads/master",
"committer_date": 1660867759000,
"content_id": "2b28f066e831da3c4d00fcb1465787fdd7285426",
"detected_licenses": [
"MIT"
],
"directory_id": "be879e2ecd58202003a3ea65d0bf5914cfce8188",
"extension": "py",
"fi... | 2.328125 | stackv2 | """
Dump FITS format data to JSON format for display on website.
"""
import json
import click
from astropy.table import Table
def _dump_json(data, filename):
click.secho('Writing {}'.format(filename), fg='green')
with open(str(filename), 'w') as fh:
json.dump(data, fh)
fh.write('\n')
table = T... | 57 | 24.82 | 127 | 12 | 482 | python | [] | 0 | true | |
2024-11-18T22:11:31.211354+00:00 | 1,563,204,980,000 | e49b5885d05b628f08b96ecdb86e480b8df1d26d | 2 | {
"blob_id": "e49b5885d05b628f08b96ecdb86e480b8df1d26d",
"branch_name": "refs/heads/master",
"committer_date": 1563204980000,
"content_id": "78c108cf27e3149aded7597e4694444b3f7a4bbe",
"detected_licenses": [
"MIT"
],
"directory_id": "d13d809413ce79d79d08c41e35d07324fe0616ea",
"extension": "py",
"fi... | 2.40625 | stackv2 | import logging
import json
import asyncio
import time
from tile_fetch import load_tiles
from upload import upload_file
logger = logging.getLogger()
logger.setLevel(logging.INFO)
logger.info('Loading function')
def lambda_handler(event, context):
logger.info('-=-=-=-=-=-= event -=-=-=-=-=-=')
logger.info(even... | 42 | 26.48 | 66 | 14 | 271 | python | [] | 0 | true | |
2024-11-18T22:11:31.268884+00:00 | 1,605,677,505,000 | 4dd0b5fcb3011ee9ea3b1009b45223e4a7fef3eb | 3 | {
"blob_id": "4dd0b5fcb3011ee9ea3b1009b45223e4a7fef3eb",
"branch_name": "refs/heads/main",
"committer_date": 1605677505000,
"content_id": "7f401ada3c37b176e5a30171034066e391272ede",
"detected_licenses": [
"MIT"
],
"directory_id": "aac8a771e69aae9850db2a4eb0d713984ddccbb0",
"extension": "py",
"file... | 2.640625 | stackv2 | #! /usr/bin/python3
from authordetect import Author, Tokenizer, SmartTimer
# NOTE: Set PYTHONHASHSEED to constant value to have deterministic hashing
# across Python interpreter processes.
import os
os.environ['PYTHONHASHSEED'] = str(0)
######################
# User Configuration #
######################
infile = '... | 53 | 21.62 | 74 | 9 | 306 | python | [] | 0 | true | |
2024-11-18T22:11:31.317841+00:00 | 1,480,000,762,000 | a675a988922d96ad5951f8cbcd249939e1cd37d4 | 3 | {
"blob_id": "a675a988922d96ad5951f8cbcd249939e1cd37d4",
"branch_name": "refs/heads/master",
"committer_date": 1480000762000,
"content_id": "2ff078a1287db862f7dd24ab79d5a7c16f2c14e4",
"detected_licenses": [
"MIT"
],
"directory_id": "d0cd3c2355d4afdc7d58cc7ba789387ef42a4e52",
"extension": "py",
"fi... | 2.546875 | stackv2 | # -*- coding: utf-8 -*-
# @Author: cody kochmann
# @Date: 2016-11-23 07:52:40
# @Last Modified 2016-11-24
# @Last Modified time: 2016-11-24 10:10:01
from functools import wraps
import logging
class default_output(object):
""" returns the backup plan if the decorated method fails
by: Cody Kochmann """
... | 25 | 32.72 | 76 | 14 | 215 | python | [] | 0 | true | |
2024-11-18T22:11:31.390214+00:00 | 1,518,031,233,000 | fbcf5e86a87f40df07b5dfdcb097a93303848447 | 3 | {
"blob_id": "fbcf5e86a87f40df07b5dfdcb097a93303848447",
"branch_name": "refs/heads/master",
"committer_date": 1518031233000,
"content_id": "61de62141fe7148a35eba0ff44cb4ae398fe576b",
"detected_licenses": [
"MIT"
],
"directory_id": "5ea68b963af59a5031afdeebb2b63f97f2f84d12",
"extension": "py",
"fi... | 3.09375 | stackv2 | # -*- coding: utf-8 -*-
import sqlite3
conn = sqlite3.connect("example.db")
conn.row_factory = sqlite3.Row
def get_all_with_options(options):
cursor = conn.cursor()
query = "SELECT * FROM hotel"
option_query = " WHERE "
valid_options = 0
for option in options:
if option[0] == 'name':
... | 67 | 30.58 | 113 | 17 | 505 | python | [] | 0 | true | |
2024-11-18T22:11:31.675538+00:00 | 1,489,155,173,000 | 89ed159bc482b936d056db4c2f664e6f3feba4e4 | 3 | {
"blob_id": "89ed159bc482b936d056db4c2f664e6f3feba4e4",
"branch_name": "refs/heads/master",
"committer_date": 1489155173000,
"content_id": "3aacd6441e3cc6240b4f9958598c1535b4a28247",
"detected_licenses": [
"MIT"
],
"directory_id": "c14863962358ef14b390aef405906195879f3f3d",
"extension": "py",
"fi... | 2.625 | stackv2 | from linguistic_treatment import CACMLinguisticTreatment
from settings import CACM, CACM_PATH, CS276, CS276_PATH, DOC_IDS_PATH, INDEX_PATH, \
PREFIX, INITIAL_MARKER, TERM_IDS_PATH, TITLE_MARKER
from collections import Counter
from copy import copy
from itertools import zip_longest
import os
class Index(object):... | 332 | 41.81 | 128 | 23 | 3,179 | python | [] | 0 | true | |
2024-11-18T22:11:31.839322+00:00 | 1,547,525,289,000 | 512f74206b1fd56ffd5772df4faa441f16d50e29 | 3 | {
"blob_id": "512f74206b1fd56ffd5772df4faa441f16d50e29",
"branch_name": "refs/heads/master",
"committer_date": 1547525289000,
"content_id": "d08caa8b8417148a7b7899e441d67577da1f2c1b",
"detected_licenses": [
"BSD-3-Clause"
],
"directory_id": "eb1bb61df95e400e1dc0755fc76d7a77ee922e62",
"extension": "p... | 2.90625 | stackv2 | #Copyright (c) 2013-2018 Hanson Robotics, Ltd.
from functools import update_wrapper
def get_enclosed(func, typ):
"""Return values in func's closure of type typ as a dictionary, which maps
their position in the cell list to the actual values."""
cells = {i: cell.cell_contents for i, cell in enumerate(func._... | 58 | 31.17 | 78 | 11 | 463 | python | [] | 0 | true | |
2024-11-18T22:11:31.886476+00:00 | 1,636,530,683,000 | a3318ae74f7a769fc726659b6336de49a1598965 | 2 | {
"blob_id": "a3318ae74f7a769fc726659b6336de49a1598965",
"branch_name": "refs/heads/master",
"committer_date": 1636530683000,
"content_id": "6ea9d9c67bfb22de4f07e5031155c563ccc8f309",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "9bfb73079afd1d5555c9662ec53f42905f65f22b",
"extension": "py"... | 2.5 | stackv2 | import tensorflow as tf
import nibabel as nib
import os
from utils.myfuncs import *
from utils.hausdorff_util import *
# Compute Accuracy
from data_loader.data_loader import DataGenerator
from models.lvae_mlp import lvae_mlp
from utils.config import process_config
from utils.utils import get_args
def testing(config):... | 98 | 36.47 | 112 | 18 | 850 | python | [] | 0 | true | |
2024-11-18T22:11:32.072959+00:00 | 1,638,966,352,000 | f6ca502907810cdb5ae97dfccdafe1ee6dc476d5 | 3 | {
"blob_id": "f6ca502907810cdb5ae97dfccdafe1ee6dc476d5",
"branch_name": "refs/heads/master",
"committer_date": 1638966352000,
"content_id": "c62be32faffb5084a38619b6347e830183f098da",
"detected_licenses": [
"MIT"
],
"directory_id": "cf96012ef7502cec83901a873bf694f5d6063186",
"extension": "py",
"fi... | 3.109375 | stackv2 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
__author__ = 'MICROYU'
import json
color2num = dict(
gray=30,
red=31,
green=32,
yellow=33,
blue=34,
magenta=35,
cyan=36,
white=37,
crimson=38
)
def colorize(string, color, bold=False, highlight=False):
"""
Colorize a string.
... | 73 | 26.04 | 86 | 19 | 513 | python | [] | 0 | true | |
2024-11-18T22:11:32.189728+00:00 | 1,613,179,609,000 | a14971229dd10bbf9c7dfd17279968e09c032f17 | 3 | {
"blob_id": "a14971229dd10bbf9c7dfd17279968e09c032f17",
"branch_name": "refs/heads/main",
"committer_date": 1613179609000,
"content_id": "a86df99a7efec89b79c6855450d0655e11283c6b",
"detected_licenses": [
"CC0-1.0"
],
"directory_id": "4ab658da446555037dd748f5c503859ab6e243f2",
"extension": "py",
"... | 3.0625 | stackv2 |
class Display_Body():
##!
##! Generates HTML BODY.
##!
def Display_Body(self):
html=[]
html=html+[ self.XML_Tag_Start("BODY") ]
args={
"width": "100%",
"border": "1",
}
html=html+[ self.XML_Tag_Start("TABLE",... | 70 | 23.43 | 78 | 17 | 421 | python | [] | 0 | true |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.