An opinionated guide to the best Python frameworks, libraries, tools, and resources.
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AI & ML
AI and Agents
Libraries for building AI applications, LLM integrations, and autonomous agents.
- Agent Skills
- django-ai-plugins - Django backend agent skills for Django, DRF, Celery, and Django-specific code review.
- graphify - Turn any folder of code, SQL schemas, docs, papers, images, or videos into a queryable knowledge graph.
- nuwa-skill - Nuwa distills the thinking of anyone — let Musk, Naval, Munger, and Feynman work for you.
- sentry-skills - Python-focused engineering skills for code review, debugging, and backend workflows.
- trailofbits-skills - Python-friendly security skills for auditing, testing, and safer backend development.
- Orchestration
- ag2 - An open-source AgentOS for multi-agent orchestration and building agentic AI systems.
- autogen - A programming framework for building agentic AI applications.
- bernstein - A deterministic Python orchestrator for CLI coding agents (Claude Code, Codex, Gemini CLI, and 40+ more) with parallel git worktrees and an HMAC-signed audit chain.
- bindu - A framework that wraps any agent handler with DID-based cryptographic identity, A2A JSON-RPC over HTTP, OAuth2 auth, x402 (USDC) payments, and a built-in operator inbox.
- bub - A lightweight, hook-first Python framework for channel-native agents that live alongside people.
- crewai - A framework for orchestrating role-playing autonomous AI agents for collaborative task solving.
- dspy - A framework for programming, not prompting, language models.
- hermes-agent - An adaptive AI agent framework that grows with you.
- langchain - Building applications with LLMs through composability.
Deep Learning
Frameworks for Neural Networks and Deep Learning. Also see awesome-deep-learning.
- jax - A library for high-performance numerical computing with automatic differentiation and JIT compilation.
- keras - A high-level deep learning library with support for JAX, TensorFlow, and PyTorch backends.
- pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration.
- pytorch-lightning - Deep learning framework to train, deploy, and ship AI products Lightning fast.
- stable-baselines3 - PyTorch implementations of Stable Baselines (deep) reinforcement learning algorithms.
- tensorflow - The most popular Deep Learning framework created by Google.
Machine Learning
Libraries for Machine Learning. Also see awesome-machine-learning.
- catboost - A fast, scalable, high performance gradient boosting on decision trees library.
- feature_engine - sklearn compatible API with the widest toolset for feature engineering and selection.
- h2o - Open Source Fast Scalable Machine Learning Platform.
- lightgbm - A fast, distributed, high performance gradient boosting framework.
- mindsdb - MindsDB is an open source AI layer for existing databases that allows you to effortlessly develop, train and deploy state-of-the-art machine learning models using standard queries.
- pgmpy - A Python library for probabilistic graphical models and Bayesian networks.
- scikit-learn - The most popular Python library for Machine Learning with extensive documentation and community support.
- scikit-lego - A collection of lego bricks for scikit-learn pipelines.
- spark.ml - Apache Spark's scalable Machine Learning library for distributed computing.
- TabGAN - Synthetic tabular data generation using GANs, Diffusion Models, and LLMs.
- timesfm - A pretrained