Compare FastAPI and web2py
Fast API is a high-performance web framework for building web applications with Python 3.6+ based on standard Python type hints. It is designed to be high performance and easy to learn.
web2py was originally designed as a teaching tool, but it gained adoption outside of the academic world. It is a full-stack framework containing all the components needed to build fully functional web applications using the Model View Controller (MVC) pattern. Inspired by the Ruby on Rails and Django. It is not very popular right now but was ranked amongst top Python web frameworks in 2011.
Let's see how FastAPI and web2py compare on various factors and features and which to choose when.
Type
Minimalistic framework based on starlette and pydantic for building fast web applications using async IO.
Type
Python full-stack for building web applications.
New addition to the Python web frameworks family but its popularity is on the rise.
Used by
Uber (internal use,) Explosion AI, Microsoft (internal use)
Used by
Not in use at any large company.
100 job openings which list Fast API as a requirement.
8 job openings which list web2py as a requirement.
Web2py takes a unique approach where models and controllers are executed in a single global environment, which is initialized at each HTTP request. While there are pros to this approach, such as developers never having to worry about cleaning up or avoid conflict between requests, the major disadvantage is that the code is models is executed with every request which carries a performance penalty.
Flexibility
Fast API is flexible to code and doesn't restrict users to a particular project or code layout.
Flexibility
Not as flexible as microframeworks, but doesn't always get in the way.
Ease of Learning
Easy to learn especially for people who are new to web development. However, it doesn't have a large number of online resources, courses and tutorials.
Ease of Learning
Limited online tutorials and resources, and many are several years old. The best resource for learning is web2py author's own
"web2py Complete Reference Manual", which seems to be written in 2013.
RDBMS Support
Through Plugins or Extensions
FastAPI doesn't come with built in ORM, however is compatible with
SQLAlchemy, Pydantic ORM mode.
RDBMS Support
Ships with a Database Abstraction Layer (DAL) which supports MySQL, PostgreSQL, SQLite, and many other relational databases.
NoSQL Support
Fast API supports many NoSQL databases like MongoDb, ElasticSearch, Cassandra, CouchDB and ArangoDB. Read more
here.
NoSQL Support
No built-in support. Very limited support for NoSQL databases. Currently, it only supports Google Datastore on the Google App Engine.
Admin Dashboard
Yes, uses Swagger as an API documentation web user interface.
Admin Dashboard
Yes ships with a built-in admin panel.
REST Support
Yes, allows developers to build REST APIs quickly.
Security
FastAPI provides several tools for many security schemes in the fastapi.security module. Not enough data.
Security
Built-in protection against input injections, XSS, and common vulnerabilities. Read more
here. It has known security vulnerabilities. Please see list
here.
Templating Library
FastAPI supports Jinja2 for templating and also supports aiofiles for serving static files
Web Forms
Ships with it's own
Forms, with basic features.
Web Forms
Built-in support. Read more
here.
Authentication
Fast API supports OAuth2, JWT and simple HTTP authentiation.
How is performance rating determined?
Performance rating is determined using reputable online benchmarks listed below.
Where is job data coming from?
Job data is collected from Indeed, Google Jobs and Stack Overflow jobs.
How is popularity calculated?
Popularity is calculated using a formula which looks at weighted score on the following publicly available data points:
- Popularity per Google Trends
- Number of GitHub Users
- Number of GitHub Stars
How is this calculated?
Ease of learning is calculated using the following data:
- Number of features and depth of tool.
- Number of online resources: articles, blogs, tutorials and YouTube videos.
- Number of courses
- Freshness of online material
For example, a microframework may not have a lot of online resources but still get a high-rating because it's minamalistic and easy to learn just by following official documentation.
If you found this useful, please help us grow by sharing this article with your followers using the sharing icons. Every share or call out will help. Thank you.
Credits
This page was made possible thanks to contributions from
Soumyaranjan Acharya who provided data and write up for Fast API.
Similar Comparisons
