Back in 2020, I wrote an article about Abandoning Flask for FastAPI. When I was writing that post, I was primarily focused on the syntax differences between the two frameworks. I had also worked to transition a project of mine from using Flask to FastAPI. However, a few years later I thought it would be interesting to revisit the comparison, this time focusing on more of the differences between them.
In this comparison, we won't be looking at the differences to install or use, but more of the details in each framework, the documentation, capabilities, and so on. To begin, I'm going to talk a little about Flask and FastAPI, look at some pros and cons, and even a few use cases for each. Finally, we'll dive into the details of the frameworks and compare them.
A Little About Flask
Flask is a Python microframework used for the easier development of web-based applications. This web application framework uses WSGI (Web Server Gateway Interface) as the standard interface between web servers and web applications. For beginners, Flask is easy to pick up as it has a smaller learning curve, while still being very Pythonic (in syntax). As a microframework, it is lightweight and runs especially well on small projects. However, larger or more complex programs can also be created using Flask, simply by allowing multiple files, as it is an extensible framework.
When considering an ORM (Object-Relational Mapping), Flask's extensibility allows you to pick and choose, as it does not have one chosen by default. This also means that while the framework is simple at its core, and scalable as well, there is no layer of abstraction for database support. This is made up for in the extensibility, as any missing features can be added back in. There are, however, many other features, such as URL routing and a template engine.
While being based on the WSGI toolkit as a web app framework, it also is closely based on the Jinja2 template engine. This is another popular template engine that combines the template with a data source to create a dynamic web page.
Pros to Flask
Flask is very beginner-friendly and simple to learn. This makes creating apps quicker and more comfortable. Because of its extensibility, Flask is very flexible. It allows unit testing and many other features, such as integrated support.
Flask is minimalist, and yet still powerful. This makes it easy to work with while still having scalability for large projects. Flask also has a large amount of documentation as well as resources available for learning.
Although not chosen by default, Flask can use an ORM, or “true SQL”. You can use something like SqlAlchemy, or, for a better match, there are Flask-specific ORMs such as Flask-SqlAlchemy.
Cons of Flask
Flask is synchronous by default and has a single source. This means that every request is handled in turns where one must wait for the previous task to finish. Flask also uses Modules, which are between the framework and developer. These are prone to security breaches. Because Flask is by default, it is not explicitly designed to handle async programming, so it is not async-friendly.
Flask is a web framework and HTML-oriented, which means it's not necessarily designed for making APIs. Of course, it is very possible, just not the main intention of Flask.
Because there's no official way of writing in Flask, it's better to be more knowledgeable about the framework before taking on a larger project. This is only because it may be more difficult for beginners to learn how, as some defaults do not exist, and you would have to know what to add in for every capability you may need.
Flask Use Cases
Although it is not advisable to use Flask for high-load enterprise software, there are still many different reasons you may want to use this framework, perhaps for personal use or commercial projects. One example would be for static sites. Another might be bots, such as for Facebook or Twitter. Flask could be used to create an E-commerce system or even an online social network.
A Little About FastAPI
FastAPI is a web microframework for building APIs with Python. It is high-performance, modern, and robust. The framework uses ASGI (Asynchronous Server Gateway Interface) as the standard interface between web servers and web applications. FastAPI is easy to use and learn, and fast to code.
The high performance and speed of FastAPI are due to tasks being run asynchronously, so they do not have to wait for previous tasks to finish. FastAPI is based on open standards for APIs. It is short to use, meaning minimized code duplication, which could result in fewer bugs. It is also intuitive, which can result in a shorter debugging time.
Although not enforced, the template engine suggested is Jinja2. FastAPI also works with any database you may choose, and any style of the library to talk to that database.
Pros of FastAPI
FastAPI is based on Python 3.6+ standard type hints, OpenAPI, JSON Schema, and OAuth 2.0. It also validates the developer's data type even when nested in JSON requests. FastAPI also has a Python library that makes it easy to build a GraphQL API.
FastAPI provides high-performance, making it very fast. It also supports background tasks and can handle WebSockets. FastAPI also has interactive API documentation, as well as a dependency injection system. Editor completion allows developers with type checks and autocompletion for more efficient coding. Although FastAPI has an Async IO, you can choose to use non-async libraries instead.
Cons of FastAPI
The major downside to FastAPI is that it is still fairly new. This means that even with detailed documentation, there are not many other external materials to use for learning. This means that the community is also small in comparison to other frameworks.
Because FastAPI offers such a rich API interface, especially for REST API, the web framework, in many places on a list, is ranked lower than Flask when comparing Python microframeworks.
Use Cases for FastAPI
FastAPI is a great choice for any project that is concerned about the speed of requests. For example, Netflix uses FastAPI for its internal crisis management. FastAPI also scales well for deploying production-ready machine learning models, which also work best when wrapped around a REST API and deployed in a microservice.
Comparing Flask and FastAPI
The first major difference you may have noticed is that Flask uses WSGI as its standard interface, while FastAPI uses ASGI. As mentioned, WSGI handles requests synchronously. This means requests are handled sequentially, and one cannot start until the previous task finishes. ASGI, on the other hand, handles requests asynchronously. This means that tasks do not have to wait for others to finish, and requests don't process in a particular order.
Another difference has to do with the community. Flask has been around longer than FastAPI and has amassed a large community. This means not only great documentation but also outside help from people writing on how to use Flask. Because FastAPI is still newer, the community has not quite grown as large as of yet. This means that even though there is great documentation, there is not much outside help.
In terms of performance, FastAPI is much faster. This is because requests are handled asynchronously. This also makes FastAPI better for larger-scale projects, especially enterprise when compared to Flask, as it is better at handling more requests much faster.
For flexibility, FastAPI is very flexible code-wise and doesn't restrict the code layout. However, Flask is more flexible in comparison, as a lot of Flask is plug-and-go. You can choose your libraries, which makes it more flexible than FastAPI, even though FasAPI is flexible as well.
Flask is very straightforward, making it very beginner-friendly on the learning curve. There is also an abundance of resources online, not just in the documentation but also in forums. If starting with web development, FastAPI is easier to learn, as it is straightforward but also because of the autocompletion and aid it gives the user. However, FastAPI does not have the community behind it, meaning it does not have as much outside help.
In today's article, we reviewed the differences between Flask and FastAPI. First, we looked at a description of each framework, then reviewed the pros, the cons, and a few use cases for each. Among some of those differences included the learning curve, the community, the flexibility, how Flask is WSGI, and how FastAPI is ASGI. After a little over a year since my previous article about Abandoning Flask for FastAPI, I enjoyed learning more about the differences between the two besides the syntax, which had been the focus of the original article. Hopefully, you found this interesting as well. Until next time, cheers!
- What is Flask Python
- FastAPI vs. Flask
- [Choosing between Django, Flask, and FastAPI]](https://www.section.io/engineering-education/choosing-between-django-flask-and-fastapi/)
- How Python's WSGI vs. ASGI is Like Baking a Cake " Developer Content from Vonage ♥