An open-source post-exploitation framework for students, researchers and developers.
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Updated
Aug 20, 2026 - Python
An open-source post-exploitation framework for students, researchers and developers.
Because `model.fit()` isn't an explanation
It's Python with a Lissp.
単一HTMLで動く WBS/ガント+イナズマ線ビューア。データはJSON1枚・Claude Codeで保守 / Single-file WBS & Gantt viewer with inazuma (progress) line. Zero dependencies, AI-maintainable.
A powerful event-driven framework for simulations, games, and complex systems with comprehensive event sourcing, querying, and analysis capabilities.
Python 3.7+ function annotations -> CLI
StandAlone Async single-file cross-platform Prettifier Beautifier for the Web.
Advanced, Light Weight & Extremely Fast MD5 Cracker/Decoder/Decryptor written in Python 3
Simple secure asynchronous message queue
Standalone scrobbler program, not a continuously running process, written in Python 3 that works together with cmus. Allows offline mode, scrobbling multiple servers simultaneously, sending a now playing request and handles pause status well.
🦎 Minimal Python command-line parser inspired by Facebook's Hydra. Handles and parses arbitrary arguments into dot-accessible nested dictionaries.
A simple diceware generator with no dependencies.
Zero-dependency Python CLI for the n8n REST API. 80+ commands for workflows, executions, credentials, nodes, webhooks. Auto-updating catalog of 543+ nodes. Multi-instance profiles. pip install, no npm/Node.js required. Works with n8n Cloud and self-hosted. Built for AI agents and automation scripts.
🐍📊 Git Py Stats is a Python-powered version of Git Quick Stats that provides a streamlined and cross-platform way to access various statistics in your git repository.
Simple dotfile pre-processor with a per-file configuration and no dependencies.
Zero-dependency, single-file Python implementations of popular libraries — benchmarked for performance parity | 零依赖单文件 Python 常用库实现,性能对标主流库
Simple subcommand CLIs with argparse
MiniML is a lightweight Machine and Deep Learning framework dedicated to training neural networks in embedded systems, redefining conventional and heavyweight models into different methods that can be exported and executed on low-cost microcontrollers (Arduino, ESP32, STM32).
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