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README

Awesome Python

An opinionated guide to the best Python frameworks, libraries, tools, and resources.

Visit the website to search and filter projects more easily.

Sponsors

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Categories

AI & ML

Web Development

HTTP & Scraping

Database & Storage

Data & Science

Developer Tools

DevOps

CLI & GUI

Text & Documents

Media

Python Language

Python Toolchain

Security

Other

Projects

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.
  • langgraph - Low-level orchestration framework for building stateful, long-running LLM agents.
  • openai-agents - OpenAI's framework for building and managing AI agents.
  • OpenChronicle - Open-source, local-first memory for any tool-capable LLM agent.
  • promptise - A framework for building end-to-end production-ready agentic systems, scalable & secure MCP's and autonomous agents.
  • pydantic-ai - A Python agent framework for building generative AI applications with structured schemas.
  • TradingAgents - A multi-agents LLM financial trading framework.
  • Data Layer
  • instructor - A library for extracting structured data from LLMs, powered by Pydantic.
  • llama-index - A data framework for your LLM application.
  • mem0 - An intelligent memory layer for AI agents enabling personalized interactions.
  • outlines - Structured text generation for LLMs with JSON schema, regex, and grammar-constrained decoding.
  • Pre-trained Models and Inference
  • diffusers - A library that provides pre-trained diffusion models for generating and editing images, audio, and video.
  • LiteLLM - Call 100+ LLMs using OpenAI format.
  • mlx-lm - Run and fine-tune large language models on Apple Silicon with MLX.
  • sglang - A high-performance serving framework for large language models and multimodal models.
  • transformers - A framework that lets you easily use pre-trained transformer models for NLP, vision, and audio tasks.
  • unsloth - A library for faster LLM fine-tuning and training with reduced memory usage.
  • vllm - A high-throughput and memory-efficient inference and serving engine for LLMs.
  • Speech
  • openai-whisper - A general-purpose automatic speech recognition model trained on 680k hours of multilingual and multitask supervised data.
  • funasr - Industrial-grade speech recognition toolkit with 170x realtime speed, 50+ languages, speaker diarization, and emotion detection.
  • vibevoice - A family of open-source voice AI models from Microsoft for text-to-speech and long-form speech recognition.
  • voxcpm - A tokenizer-free text-to-speech foundation model for multilingual speech generation and voice cloning.

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 foundation model from Google Research for time-series forecasting.
  • xgboost - A scalable, portable, and distributed gradient boosting library.

Natural Language Processing

Libraries for working with human languages.

  • General
  • gensim - Topic Modeling for Humans.
  • nltk - A leading platform for building Python programs to work with human language data.
  • spacy - A library for industrial-strength natural language processing in Python and Cython.
  • stanza - The Stanford NLP Group's official Python library, supporting 60+ languages.
  • Chinese
  • funnlp - A collection of tools and datasets for Chinese NLP.
  • jieba - The most popular Chinese text segmentation library.

Computer Vision

Libraries for Computer Vision.

  • easyocr - Ready-to-use OCR with 40+ languages supported.
  • kornia - Open Source Differentiable Computer Vision Library for PyTorch.
  • opencv - Open Source Computer Vision Library.
  • pytesseract - A wrapper for Google Tesseract OCR.
  • ultralytics - Ultralytics YOLO for object detection, segmentation, pose estimation, and classification with state-of-the-art accuracy and speed.

Recommender Systems

Libraries for building recommender systems.

  • annoy - Approximate Nearest Neighbors in C++/Python optimized for memory usage.
  • implicit - A fast Python implementation of collaborative filtering for implicit datasets.
  • scikit-surprise - A scikit for building and analyzing recommender systems.

Web Development

Web Frameworks

Traditional full stack web frameworks. Also see Web APIs.

  • Synchronous
  • bottle - A fast and simple micro-framework distributed as a single file with no dependencies.
  • django - The most popular web framework in Python.
  • flask - A microframework for Python.
    • [awesome-flask](h

Core symbols most depended-on inside this repo

parse_readme
called by 25
website/readme_parser.py
build
called by 19
website/build.py
render_inline_text
called by 14
website/readme_parser.py
build_graphql_query
called by 14
website/fetch_github_stars.py
extract_github_repo
called by 10
website/build.py
render_inline_html
called by 9
website/readme_parser.py
annotate_entries_with_stars
called by 8
website/build.py
detect_source_type
called by 7
website/build.py

Shape

Method 130
Function 75
Class 29

Languages

Python95%
TypeScript5%

Modules by API surface

website/tests/test_build.py73 symbols
website/tests/test_readme_parser.py50 symbols
website/build.py36 symbols
website/tests/test_fetch_github_stars.py31 symbols
website/readme_parser.py27 symbols
website/static/main.js11 symbols
website/fetch_github_stars.py6 symbols

For agents

$ claude mcp add awesome-python \
  -- python -m otcore.mcp_server <graph>

⬇ download graph artifact