awesome-python README

The project's README from github.com/vinta/awesome-python. As one markdown file: README.md.

Awesome Python

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

Visit the website to search and filter projects more easily.

Sponsors

The #10 most-starred repo on GitHub. Put your product in front of Python developers. Become a sponsor.

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.

Deep Learning

Frameworks for Neural Networks and Deep Learning. Also see awesome-deep-learning.

Machine Learning

Libraries for Machine Learning. Also see awesome-machine-learning.

Natural Language Processing

Libraries for working with human languages.

Computer Vision

Libraries for Computer Vision.

Recommender Systems

Libraries for building recommender systems.

Web Development

Web Frameworks

Traditional full stack web frameworks. Also see Web APIs.

Web APIs

Libraries for building RESTful, GraphQL, and RPC APIs.

Web Servers

ASGI and WSGI compatible web servers.

WebSocket

Libraries for working with WebSocket.

Template Engines

Libraries and tools for templating and lexing.

Web Asset Management

Tools for managing, storing, compressing and minifying website assets.

Authentication

Libraries for implementing authentication schemes.

Admin Panels

Libraries for administrative interfaces.

CMS

Content Management Systems.

ERP

Enterprise resource planning frameworks.

Static Site Generators

Static site generator is a software that takes some text + templates as input and produces HTML files on the output.

HTTP & Scraping

HTTP Clients

Libraries for working with HTTP.

awesome-python (vinta/awesome-python)

Searching Database…

What is this?Awesome Python is a curated, opinionated guide to the best Python frameworks, libraries, and tools, organized by category — the classic answer to 'I want to do X in Python, which tool should I use?'
Is it software I install, or something I read?Something you read: a categorized list rather than a package — sections covering AI and ML, web development, data, DevOps, security, and more, each split into finer categories.
The README is huge — is there a better way to browse it?Yes, a companion website: it lets you search and filter the projects more easily than the raw list.
How much does it tell me about each entry?One line per project: a name and a short description, like 'flask - A microframework for Python' — enough to shortlist candidates, not full reviews.
Would a Python newcomer get value from it, or is it aimed at seasoned developers?It speaks to Python developers in general — the sponsor pitch promises products 'in front of Python developers' — and newcomers can use the categories as a map of the ecosystem.
What if I want to go deeper on one framework, like Django?Several entries link out to dedicated awesome lists — awesome-django, awesome-flask, awesome-pyramid, awesome-fasthtml — and the ML sections point to awesome-deep-learning and awesome-machine-learning.
Can I trust its picks?It is the #10 most-starred repo on GitHub, with over 326,000 stars, curated since 2014.
Is the list still being updated?Yes — GitHub metadata shows it is not archived, and the repo runs CI workflows, including one that deploys the companion website.
Creator
vinta
Size
6.7 MB
Stars
328.1K
Updated
CommitOct 17
Age
12y
Commits · 90 Days