Top 37 Python Web Frameworks: Features, Pros & Cons Explained

The author spent two weeks compiling a comprehensive list of Python web development libraries (referred to as web frameworks) for reference and learning.

What is a web framework? A web framework provides a set of common tools and methods that simplify website development, allowing developers to focus on business logic while the framework handles routine tasks such as routing, templating, database access, and security.

Why use a web framework? Using a framework reduces the amount of code you need to write for data caching, database interaction, security checks, and other common features, enabling faster development and easier problem solving through community support.

The frameworks are ordered by usage statistics and documentation activity; the author recommends using the top‑ranked ones because they have richer documentation, larger communities, and better support.

Django

Official website: https://github.com/django/django.git

Pros: High‑level Python web framework with rapid development, minimal code, strong extensibility, rich feature set, and extensive template options. It follows the MTV (Model‑Template‑View) pattern and is considered the leading Python web framework.

Cons: Includes many modules unnecessary for lightweight apps, less lightweight than Flask, heavy abstraction can make deep customisation difficult, performance lower than compiled languages, and a steep learning curve.

Flask

Official website: https://flask.palletsprojects.com/en/2.0.x/

Pros: A lightweight micro‑framework that is extremely simple and fast to set up; ideal for small prototypes and quick development.

Cons: For large applications you must design routing rules yourself, and beginners may inadvertently create low‑quality code.

Pyramid

Official website: https://trypyramid.com/

Pros: Highly extensible and flexible, easy to start, suitable for medium‑scale projects that evolve during development.

Cons: Low domestic visibility, advanced usage often requires reading source code; default Chameleon template limits flexibility.

web.py

Official website: https://webpy.org/

Pros: Simple yet powerful; used by Yandex and praised by Guido van Rossum.

Cons: Lacks full Python 3 compatibility, missing async support and maintenance uncertainty.

Tornado

Official website: https://www.tornadoweb.org/en/stable/

Pros: Asynchronous network library capable of handling thousands of open connections; ideal for high‑concurrency scenarios.

Cons: Requires Python 3.5+; older Python 2 support dropped; integration can be complex.

TurboGears

Official website: https://www.turbogears.org/

Pros: Attempts to combine the best of Django, Rails, and earlier TurboGears; supports multiple databases, JavaScript toolkits, and many data formats.

Cons: Basic management features, few third‑party extensions, and documentation can be overwhelming due to its highly modular nature.

CherryPy

Official website: https://cherrypy.org/

Pros: Allows object‑oriented development with minimal code; stable and suitable for small‑scale systems.

Cons: Provides only low‑level building blocks, lacking built‑in templating and higher‑level features.

Falcon

Official website: http://falconframework.org/

Pros: High‑performance microframework for large‑scale APIs and mobile back‑ends; reliable and scalable.

Cons: Very minimal; only routing, middleware, and hooks are provided, so additional features must be implemented by the developer.

Asgineer

Official website: https://asgineer.readthedocs.io/

Pros: Asynchronous framework with minimal abstraction, fast on Uvicorn, supports long‑polling, SSE, websockets, and efficient static asset serving.

Cons: Documentation is scarce in Chinese.

Bottle

Official website: https://bottlepy.org/docs/dev/

Pros: Single‑file WSGI microframework with no external dependencies; supports clean URLs, multiple template engines, and easy access to HTTP metadata.

Cons: Lacks many features such as form validation and CSRF protection; additional functionality must be added manually.

Emmett

Official website: https://emmett.sh/

Pros: Simple syntax, focuses on product development rather than framework intricacies; clear routing definitions.

Cons: Chinese documentation is limited.

FastAPI

Official website: https://fastapi.tiangolo.com/

Pros: Modern, high‑performance API framework built on standard Python type hints; comparable speed to NodeJS and Go, reduces developer errors, concise and robust.

Cons: Does not include a templating engine out of the box.

Responder

Official website: https://python-responder.org/

Pros: Built on Starlette, offers a more developer‑friendly API while retaining high‑performance async capabilities.

Cons: Still a young project; some packaging and code issues remain.

Molten

Official website: https://moltenframework.com/

Pros: Minimal, extensible, fast framework for building HTTP APIs; uses type hints and mypy for validation.

Cons: No third‑party validation libraries, requires manual dependency registration.

Clastic

Official website: https://github.com/mahmoud/clastic

Pros: Strong emphasis on testability, no global state, flexible routing, and easy WSGI integration.

Cons: Mismatched URL‑routing parameters can raise exceptions at build time.

Aiohttp

Official website: https://docs.aiohttp.org/en/stable/

Pros: Asynchronous HTTP client/server for asyncio; supports WebSockets, middleware, and signals.

Cons: Certain HEAD request handling quirks in older versions.

Masonite

Official website: https://docs.masoniteproject.com/

Pros: Modern, developer‑centric framework with batteries‑included, highly extensible, great for both beginners and experienced developers.

Cons: Community and ecosystem are still growing compared to Django.

Quart

Official website: https://pgjones.gitlab.io/quart/

Pros: Microframework supporting HTML templates, JSON APIs, WebSockets, and streaming; compatible with ASGI.

Cons: Requires Python 3.7 or newer.

Klein

Official website: https://github.com/twisted/klein

Pros: Tiny API similar to Bottle/Flask but built on well‑tested Werkzeug and Twisted components.

Cons: May feel outdated.

Nameko

Official website: https://github.com/nameko/nameko

Pros: Provides AMQP RPC, event publishing, HTTP, and WebSocket support; includes utilities for testing.

Cons: Errors may not be logged automatically; heavy tasks can cause retries.

CubicWeb

Official website: https://www.cubicweb.org/

Pros: Semantic web framework with reusable components, strong Python features, and support for multiple back‑ends.

Cons: RQL query language can be cumbersome; setup is complex; lacks a native template engine.

Zope2

Official website: https://zope.readthedocs.io/en/latest/

Pros: One of the earliest Python web frameworks; object‑publishing system suited for OOP development.

Cons: Overkill for simple REST APIs or basic sites; installation can be involved.

Web2py

Official website: http://web2py.com/

Pros: Free, open‑source, rapid development with browser‑based IDE, built‑in admin, and strong security.

Cons: Only compatible with Python 2.x (Python 3 support still in progress).

Pylons

Official website: https://docs.pylonsproject.org/projects/pylons-webframework/en/latest/

Pros: Open‑source WSGI‑based framework with modular components; influenced by Ruby on Rails.

Cons: Merged into Pyramid and now only maintained; new projects should start with Pyramid.

Cubes

Official website: https://pythonhosted.org/cubes/

Pros: Lightweight framework for reporting, OLAP, and multidimensional data analysis.

Cons: Limited aggregation capabilities; requires explicit model definition before server start.

Dpark

Official website: https://github.com/Liangchengdeye/Dpark

Pros: Python clone of Spark for distributed computing; flexible MapReduce‑like API; used internally at Douban.

Cons: Relies on processes; Python GIL limits true multithreaded concurrency.

Buildbot

Official website: https://buildbot.python.org/all/#/

Pros: Open‑source continuous integration tool written in Python; highly extensible and used by major projects.

Cons: Multi‑project support is limited.