Flask and FastAPI are popular Python micro-frameworks used to build small scale websites or applications based on data science and machine learning.
Although FastAPI is a younger framework, more and more developers are currently switching to it in their new projects. Is it just a hype or is FastAPI superior to Flask? We’ve prepared a comparison of the key pros and cons of both Flask and FastAPI to help you decide what will be the best choice for your next data science application.
What is FastAPI?
FastAPI is a web development framework for Python 3.6 and newer versions. It was released in 2018 as an open source framework built on Starlette and uses standard Python type hints. The framework is used primarily for building fast web applications and Rest APIs.
FastAPI is built on the Asynchronous Server Gateway Interface (ASGI) web server Uvicorn, but you can also mount Web Server Gateway Interface (WSGI) applications using relevant middleware.
It’s currently used by Uber, Microsoft, Explosion AI and others.
Pros of FastAPI
FAstAPI has a high performance, concurrency can be easily supported, and it offers a simple and easy-to-use dependency injection system. Inbuilt data validation is another benefit to take into consideration.
If we were to name one quality by which FastAPI beats Flask, it’s the performance. FastAPI is actually known as one of the fastest Python web frameworks. In fact, only Starlette and Uvicorn, on which FastAPI is built, are faster. This superior performance is enabled precisely by ASGI, thanks to which FastAPI supports concurrency and asynchronous code. This is achieved by declaring the endpoints with async def syntax.
Native concurrency support
It used to be very hard to implement concurrent programming in Python - Async I/O was added with Python 3.4. With FastAPI, concurrency can be easily implemented without worrying about Event loop or async/await management.
Developers can simply declare the first path function as coroutines via the async def function wherever they deem appropriate and then declare specific points aws awaitable through await.
Dependency injection support
FastAPI offers a simple and easy-to-use dependency injection system. Dependency injection, a compositional way of declaring the necessary components required for the code to run properly.
It’s a method for achieving inversion of control, which increases modularity of the code and makes the system more scalable. In FastAPI, developers can simply declare relevant dependencies in the path operation functions assigned to the API endpoints.
Inbuilt documentation support
FastAPI offers an extremely handy automatic documentation system. It provides a browser-based user interface that interactively documents an API, powered by Swagger UI GUI.
Alternatively, developers can simply type in /redoc to obtain the alternative documentation consisting of all the endpoints listed. The documentation will always allow developers to easily explain the program to others, make it easier for front-end engineers to use your backend and add convenience when it comes to testing the API endpoints.
Inbuilt data validation
This is an enormous benefit - inbuilt data validation allows developers to create a compact code through skipping the validation. It can detect invalid datatypes during the run and returns the reason for bad input in JSON format.
FastAPI makes use of the Pydantic library for this purpose, which greatly simplifies the validation process and ensures faster typing than it would have been by hand. It can also reduce bugs and FastAPI authors claim it reduces developer errors by up to 40%.
Cons of FastAPI
You should take into consideration lack of inbuilt security system and small community of developers.
Lack of inbuilt security system
FastAPI doesn’t offer a built-in security system. Instead, it provides a fastapi.security module for security mechanisms. At the same time, it does support OAuth2.0.
Small community of developers
FastAPI is relatively new (8 years younger than Flask), which means its community is still rather small and their educational materials available for this framework are still limited. Upon searching, you will find that only a few books, guides or tutorials are available. At the same time, it is growing in popularity, so this may change in the coming years.
What is Flask?
Flask is a micro web framework written for Python. It’s lightweight, open source and offers a small and easily extensible core. It’s used primarily to develop minimalistic web applications and Rest APIs.
Flask was released in 2010 as a framework based on Werkzeug and Jinja2. It’s built on Web Server Gateway Interface (WSGI). You can use an ASGI server with Flask, but you’d need to utilize WSGI to ASGI middleware.
The framework supports REST development through extensions, eg. Flask-RESTful, Flask-Classful, Flask-RESTPlus, etc. It’s perfect for building e-commerce systems, social media bots or static sites. It’s not suitable for high-load enterprise software.
Flask is currently used by Netflix, Lyft or Zillow. It’s considered the most popular Python development framework for beginners.
Pros of Flask
With Flask you can build easily scalable applications. Another advantage is that Flask has a great flexibility.
Great for building scalable solutions
Flask was built to enable the growth of tech projects at speed. Flask applications are easily and extensively scalable. The framework supports the creation of complex applications by allowing developers to easily add new functionalities and use cases as needed. Flask is thus a great option for businesses that are starting small and intend to grow their new solution in the coming years.
Ample resources available
Flask has been in use for over a decade, so it has a vast number of supporting resources. There are a lot of extensions available and the Flask community is also well established - you can check GitHub for some useful data. That makes it relatively easy to learn for self-starters.
Developers will certainly enjoy the fact that most parts of Flask can be changed, which is rather rare in case of most other development frameworks. This is one of the greatest advantages of Flask. Because of this flexibility and minimalist nature, you can easily change the course of your projects while keeping the overall structure stable. Fast API is also flexible when it comes to the code and layout, however, Flask is even more flexible.
Flask may be a minimalist framework, but it’s well equipped to handle common security concerns like CSRF, XSS or JSON security. Developers can benefit from 3rd party extensions like Flask-Security as well, but they should be aware that adding these can result in performance drop. However, developers must always evaluate these extensions carefully and remember to update them manually on a regular basis and whenever vulnerabilities are discovered.
Cons of Flask
Take intro consideration the lack of support for asynchronicity and that Flask uses third-party modules, which might have a negative effect on security.
Lack of support for asynchronicity
Flask is developed for WSGI services like Gunicorn, and so it doesn’t offer native async support. This means that long-running queries may actually block the application. A REST API built with Flask will be able to handle a smaller number of users. All in all, every request will be handled in turns, which takes more time.
Flask makes use of third-party modules and that increases the risk of security breaches. Applying modules means that the development process isn’t solely between the developer and the framework. If a malicious module is implemented, the consequences can be grave, so programmers must pay extra attention to security mechanisms.
Lack of data validation
Validation of the data format is absent in Flask, which means that developers can pass any type of data, including strings or integers. There are extensions that can compensate for this shortcoming, eg. Flask-Marshmallow or Flask-inputs. Alternatively, developers can add a validation script for data inputs, but this will require additional effort.
Flask or FastAPI: which to choose for building a website or an app based on data science and machine learning
Both Flask and FastAPI can quickly set up web servers and data science apps in Python. They require the same amount of effort when it comes to deployment. How to decide which framework is better for your next project?
FastAPI is the best choice when speed and performance are of primary importance. If you’re building your own CDN and expect significant traffic, opt for this newer framework. With FastAPI, you can just download and use the framework which is built on cutting edge technology already and benefit from the project template will help you save time.
When you’re building APIs, FastAPI will be a better choice than Flask, especially when microservices are taken into consideration. The only argument for choosing Flask in this case would be if your organization already has a lot of tooling built around that framework.
In contrast, choose Flask when you need to build a simple microservice with a couple of API endpoints. It’s also a great option for building machine learning models and web application prototypes backed by data science.
Also, If you want to make an app that starts small, but has the potential to grow quickly and in directions you haven’t completely worked out yet, then Flask is an ideal choice. It's simple to use, runs smoothly thanks to just a handful of dependencies, even as you continue to scale.