⚡️Lightning-fast linter for .env files. Written in Rust 🦀
GOAL: Incident Response Playbooks Mapped to MITRE Attack Tactics and Techniques. [Contributors Friendly]
Ward is a modern test framework for Python with a focus on productivity and readability.
Update informer for CLI/GUI applications written in Rust 🦀
A github action to automate a contributors section in readme.
#网络爬虫#RSS feed builder created with Bun🥖 and Hono🔥- builds from webpages, email folders, and REST API calls.
#Awesome#ResourceHub is an open-source project that serves as a one-stop repository of valuable resources curated by the amazing contributors in the community🚀
A node package & userscript that removes tracking or garbage parameters from URLs making them shorter, cleaner and a lot nicer to read.
#安卓#A flutter app where users can exchange books within their nearby location range.
A registry of community-led codemods & code automation recipes for popular refactors, migrations, and dependency upgrades.
findadoc.jp web site
Translations for Findadoc Japan
Contribute on this repository with valid pull request to Hacktoberfest 2022 and earn amazing swags!🎁🎁🔥🔥
This Repository is made for all those who are Newbie in the Field of Open Source and wants to kick off their journey as an Open Source Contributor through Hacktober. Kindly refrain from making Multipl...
Travel back in time to debug your Python ⏰ 🐍
Simple hello world in different language syntax
RDAP Lookup is an open-source, web application that utilizes the Next.js 13 App Router to perform robust Registration Data Access Protocol (RDAP) queries. It provides a modern, user-friendly interface...
#算法刷题#Hacktoberfest is a month-long virtual festival event to celebrate open source contributions presented by Digital Ocean and DEV. It is the easiest way to get into open source!
greening is an opinionated, lightweight project automation tool for solo developers and creative coders. With just a few commands, you can scaffold a production-ready Python package — complete with d...
Let's put probability on trial by simulating trials and recording success % and comparing it with expectations from probability(favorable/total) || Tech Stack: js , html ,css