Comparing 3 Popular Python REST APIs: Which One To Pick?

Are you looking to create a Python REST API quickly and efficiently? You’ve come to the right place! This article will explore three popular and powerful REST frameworks:

1. FastAPI
2. Flask
3. Django REST.

By the end of this article, you’ll better understand the pros and cons of using these Python frameworks for building your REST APIs, depending on your situation and requirements.

FastAPI

FastAPI is a relative newcomer to the world of Python REST API frameworks. It has quickly gained popularity in the past years. Developed by Sebastián Ramírez and first released in 2018, it was built to create an easy-to-use, high-performance framework for building APIs with Python 3.6+ type hints. Ramírez, with his experience in API development, sought to address common pitfalls and issues he faced in his work. FastAPI is the culmination of those efforts, providing developers with a powerful, flexible, fast tool.

Intended primarily for building APIs, FastAPI utilizes modern Python features such as async and await for asynchronous support and type hints for data validation and serialization. It’s particularly well-suited for building microservices, real-time applications, and larger web applications that require high performance and scalability. The core philosophy of FastAPI revolves around being easy to use, fast to code, and designed to be easy to use with editors and tools.

Perhaps the most compelling feature of FastAPI is its speed. It’s one of the fastest Python frameworks available, on par with NodeJS and Go. It achieves this speed thanks to Starlette for the web parts and Pydantic for the data parts. But speed isn’t its only strength. FastAPI also offers automatic interactive API documentation, robust input validation, and dependency injection, making it a comprehensive and powerful tool for building HTTP APIs.

FastAPI pros and cons

Pros:

1. Speed: FastAPI is one of the fastest Python REST frameworks available, on par with NodeJS and Go, thanks to its use of Starlette for the web parts and Pydantic for the data parts.
2. Easy to Use: FastAPI is designed to be easy and intuitive, with sensible defaults and excellent error messages.
3. Type Checking: FastAPI uses Python’s type hints for request parameters and endpoints. This allows for excellent editor support, improved debugging, and easier collaboration through self-documented code. Moreover, it enables automatic data validation, serialization, and documentation.
4. Automatic Interactive API Documentation: With FastAPI, the API documentation is created automatically through OpenAPI, providing interactive exploration of the API from the browser.
5. Asynchronous Support: FastAPI has built-in support for asynchronous request handling, which can lead to performance gains.

Cons:

1. Less Mature: Compared to Flask and Django, FastAPI is newer and thus has a smaller community and fewer resources for help and examples. However, this won’t be an issue for the most common usage patterns.
2. Limited Middleware and Extensions: While FastAPI does offer middleware and extension support, it doesn’t have the same range of readily available middleware and extensions that some other, more mature frameworks have.
3. Potential Overhead: The additional features and functionality that FastAPI provides can add complexity and overhead, which might be unnecessary for smaller, simpler applications.

Creating a Python REST API with FastAPI

To install FastAPI, you can use pip install:

pip install fastapiCode language: Python (python)

You will also need an ASGI server. A popular choice is uvicorn:

pip install uvicornCode language: Python (python)

And here’s a simple Hello World API:

from fastapi import FastAPI

app = FastAPI()

@app.get("/")
def read_root():
    return {"Hello": "World"}

if __name__ == "__main__":
    import uvicorn
    uvicorn.run(app, host="127.0.0.1", port=8000)Code language: Python (python)

As you can see, it’s just a few lines of code to start!

Flask

Flask, an esteemed member of the Python web framework family, was born out of an April Fool’s Day joke by Armin Ronacher in 2010. What started as a simple wrapper around Werkzeug and Jinja, two of Ronacher’s earlier projects, evolved into a fully-fledged micro web framework. The idea was to create a web application framework that was easy to use, lightweight, and more flexible than Django, which was, at the time, the dominant Python web framework.

Flask is designed as a microframework, making it perfect for developing small to medium-sized web applications and services. Its “micro” nature does not equate to a lack of functionality but refers to Flask’s modular and easy-to-extend core. It is unopinionated, meaning it does not dictate or make assumptions about your project layout or technological choices, giving you the freedom to choose the tools and libraries that best suit your application’s needs.

One of Flask’s most compelling features is its simplicity. It provides only what’s necessary to handle web requests and responses, leaving the rest to third-party libraries and extensions. This makes it easy to understand and quick to start with, especially for developers new to web development. The framework includes built-in URL routing, easy handling of HTTP requests and responses, and support for Jinja2 templating out of the box.

Flask pros and cons

Pros:

1. Simplicity: Flask is known for its simplicity and minimalism, with a small learning curve, making it ideal for beginners in web development.
2. Flexibility: With Flask, you have a lot of flexibility in structuring your applications. It doesn’t make many decisions for you, so you can choose the tools and libraries you want to use.
3. Extensible: Flask has a rich ecosystem of extensions, allowing you to add functionality to your application as if it was implemented in Flask itself.
4. Good for Small to Medium Projects: Flask’s lightweight and modular design makes it a great choice for small to medium-sized projects.

Cons:

1. Not Suitable for Large Applications: Flask is not designed to build large applications out-of-the-box. A more feature-rich framework like Django may be a better fit for larger applications with more complex needs.
2. Lacks Some Out-of-the-Box Functionality: Flask leaves much up to the developer or third-party extensions, like form validation, user authentication, or ORM. This could be a con if you want a framework with more built-in functionality.
3. Asynchronous Support: While (since 2.0) Flask added async support, it’s not designed from the ground up to be asynchronous, so it doesn’t match the speed of FastAPI. Please note that raw request speed is rarely the issue when it comes to performance issues, though. Most of the time, it’s a slow DB query and such that is holding you back.

Creating a Python REST API with Flask

To install Flask, we can again use pip install:

pip install FlaskCode language: Python (python)

And now our Hello World API:

from flask import Flask, jsonify

app = Flask(__name__)

@app.route("/")
def hello_world():
    return jsonify({"Hello": "World"})

if __name__ == "__main__":
    app.run(debug=True)Code language: Python (python)

Like FastAPI, you can get up and running with Flask with only a few line of code.

Django REST Framework

The Django REST Framework (DRF), a powerful toolkit for building Web APIs, is built on the foundation of Django, a high-level Python Web framework that has been around since 2005. Adrian Holovaty and Simon Willison created the Django framework as part of their work on the Lawrence Journal-World newspaper. Later, Tom Christie, a long-time contributor to Django, developed Django REST Framework, first released in 2011. It was designed to take the robustness of Django and apply it to the world of APIs, providing a flexible and feature-rich environment for API development.

Django REST Framework is specifically designed for building APIs, making it a go-to choice for developers looking to create everything from simple web services to complex, data-driven applications. It leverages Django’s strengths, providing comprehensive tools for building Web APIs. It complements Django’s capabilities with better support for RESTful architecture, API views, serialization, and more.

Among its compelling features, Django REST Framework provides a browsable API, robust serialization, and comprehensive authentication and permission policies. The browsable API is an enormous usability win, making it easy for developers to navigate, visualize, and interact with the API from their web browser. The serialization engine is flexible and powerful, allowing complex data types to convert to and from native Python datatypes easily. Furthermore, the framework’s authentication policies support various schemes, including OAuth1 and OAuth2.

Django REST Framework is a great choice if:

• You also plan on using Django anyway, and/or:
• You want to make use of its powerful ORM and scaffolding tools.

If you don’t, you might want to consider FastAPI or Flask since they are more lightweight and will definitely get you started quicker.

Django pros and cons

Pros:

1. Batteries Included: Django is a high-level Python web framework that encourages rapid development and clean, pragmatic design. It’s a “batteries included” framework with robustness and simplicity.
2. Admin Interface: Django has a built-in admin interface that makes it easy to build CRUD interfaces.
3. ORM Support: Django has a powerful ORM that allows you to interact with your database. In other words, it’s a way to create, retrieve, update, and delete records in your database using pure Python (instead of SQL).
4. Authentication and Permissions: Django REST Framework has multiple built-in authentication policies and allows for easy customization of authorization rules.
5. Thorough Documentation: Django and Django REST Framework have comprehensive and well-organized documentation. It’s a very mature and well-documented project.

Cons:

1. Steep Learning Curve: Due to its “batteries included” nature, Django can be a lot to take in for new developers. The framework makes many decisions for you; understanding them can take time.
2. Monolithic: Django follows a monolithic architecture, which might not suit every application. Flask or FastAPI might be a better choice if you are looking for a microservices design.
3. Not Asynchronous: Django is not (fully) asynchronous. It won’t come close to the raw performance of FastAPI. But, again, raw HTTP request performance is rarely an issue for most users.
4. Too Much for Small Projects: Django’s robust features can be overkill for small, simple applications. The simple Hello World example below demonstrates that the steps to get started are much more involved than FastAPI and Flask.

Creating a Python REST API with Django REST Framework

To install the Django REST framework, you also need Django. You can install both at once:

pip install django djangorestframeworkCode language: Python (python)

First of all, you need to create a Django project and an ‘app’:

django-admin startproject myproject
cd myproject
python manage.py startapp myappCode language: Python (python)

Next, we need to add the rest_framework and our newly created app my_app to the list of installed apps in the file myproject/settings.py.

Now, we can create a Django view to serve our endpoint. Create a file called hello_world.py in the views folder:

from rest_framework.response import Response
from rest_framework.decorators import api_view

@api_view(['GET'])
def hello_world(request):
    return Response({"Hello": "World"})Code language: Python (python)

We’re not there yet, though. We also need to create a route to expose this endpoint. To do so, create a urls.py file in the myapp directory and add the following code:

from django.urls import path
from . import views

urlpatterns = [
    path('', views.hello_world, name='hello_world'),
]Code language: Python (python)

And now we add our myapp routes to the main urls.py file in myproject/urls.py:

from django.contrib import admin
from django.urls import path, include

urlpatterns = [
    path('admin/', admin.site.urls),
    path('api/', include('myapp.urls')),
]Code language: Python (python)

And finally, we can run the server:

python manage.py runserverCode language: Python (python)

You can now navigate to http://127.0.0.1:8000/api/ to view your new Django REST Framework API.

As you can see, using Django and Django Rest Framework is a lot more involved. However, you will get a lot in return, especially when you want to serve data with your API and model that data using Django’s Object Relational Model. In this case, the Django admin area will automatically offer you a GUI-based way to CRUD operations on your data (Create, Read, Update, Delete).

Conclusion

Choosing the right framework to build an HTTP API with Python can be complex. Each framework brings its own unique set of benefits and challenges to the table.

FastAPI stands out with its speed, automatic API documentation, and robust input validation. It’s a great option for developers who want to build high-performance APIs quickly.

On the other hand, Flask is loved for its simplicity and flexibility, making it an excellent choice for smaller projects or for developers just starting their journey in web development.

With its comprehensive feature set, Django REST Framework is a robust choice for larger, more complex projects. Its “batteries included” nature means it can handle various tasks out of the box, freeing developers to focus on their application’s unique features.

If you don’t know where to start and don’t need to model your data (in a database), I recommend picking FastAPI or Flask. Django is probably a great fit if you need a data model with multiple tables, users, etc.