8 Popular Python Frameworks for Building APIs

APIs have become the glue holding modern software together. As Python has grown into one of the world‘s most popular languages for building all kinds of applications, dozens of API frameworks have emerged to help Python developers build robust and scalable interfaces.

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But if you‘re new to Python APIs, the dizzying number of options can make it hard to choose the right tools for your needs. You may be wondering:

What even is an API framework and why would I need one?
What key features should I look for?
How do I choose between so many frameworks for Python?

In this definitive guide, you‘ll find a comprehensive overview of the top API frameworks available for Python today and the key factors to consider when choosing between them. You‘ll learn:

What core features to expect from an API framework
8 leading options for Python API development
How frameworks compare across metrics like speed, flexibility, and scalability
When to use specific frameworks based on your needs

Equipped with this knowledge, you‘ll be able to hit the ground running with an API-first approach in Python. So let‘s dive in!

The Rising Need for Python API Frameworks

First – what exactly is an API framework?

An API framework handles a lot of repetitive coding needed to build great APIs like request routing, input validation, authentication etc. This frees you up to focus on the custom business logic unique to your API.

Some Benefits of Using an API Framework

Save weeks of development time with out-of-box features
Best practices baked in means higher quality APIs
Quickly adapt APIs to changing business requirements
Tap into vast community knowledge for help

The need for API frameworks has grown exponentially as companies adopt:

Microservices – Small independent services vs large apps
Mobile/IoT devices – Myriad devices that need APIs
Developer ecosystems – External developers building on APIs

No wonder new Python frameworks keep popping up!

But while choice is great, too much choice can paralyze decision making.

Let‘s now explore 8 leading contenders that have risen to become trusted solutions for Python API developers.

8 Popular Python API Frameworks

1. Django REST Framework

As Django grew into the world‘s most popular Python web framework, Django REST Framework emerged as an easy way to build web APIs alongside Django sites.

Why Choose Django REST Framework?

Fully integrated with other Django components
Automatic web admin interface for APIs
ORM brings powerful database abstraction
Excellent for internal APIs used by Django web apps

Companies like Red Hat, Mozilla, Heroku use and contribute to Django REST as a robust choice for Python APIs.

Sample Code:

# urls.py
from django.urls import path
from myapp.views import UserViewSet

urlpatterns = [
    path(‘users/‘, UserViewSet.as_view({‘get‘: ‘list‘}))
]

2. Flask-RESTful

Flask-RESTful combines the simplicity of lightweight microframework Flask with best practices for building REST APIs.

Why Flask-RESTful?

Minimal setup and conventions over configuration
Great ecosystem of related Flask extensions
Easy serialization to multiple formats like JSON API, XML, CSV
Awesome for getting started with well-structured Python APIs

Pinterest uses Flask-RESTful to create flexible internal web services.

Sample Code:

from flask import Flask
from flask_restful import Resource, Api

app = Flask(__name__)
api = Api(app)

class User(Resource):
    def get(self):
        return {‘name‘: ‘John‘}

api.add_resource(User, ‘/users/‘)

if __name__ == ‘__main__‘:
    app.run(debug=True)

3. Falcon

Falcon describes itself as a "bare-metal" Python web API framework meaning it aims to provide a direct interface to the HTTP protocol without too many abstractions on top.

Why Falcon?

Ultra fast performance. Up to 10x of Django in benchmarks.
Ideal for very I/O intensive backend services
Great for scaling to need high loads
Easy migration for existing Python WSGI services

Falcon powers APIs at Rackspace, SurveyMonkey and Dropbox.

Sample Code:

import falcon

class UserResource:
    def on_get(self, req, resp):
        user = get_user_data()  
        resp.media = user

api = application = falcon.API()
api.add_route(‘/user‘, UserResource())

4. FastAPI

As the name suggests, FastAPI is a modern Python framework focused on high performance APIs with automatic interactive documentation.

Why Use FastAPI?

New generation framework built on modern Python standards
Ultra fast (just behind Falcon)
Automatic API doc generation from signatures & types
Friendly error messages, easy debugging
Built-in data validation

Startups like Skillshare use FastAPI to create scalable web APIs with developer happiness and rapid iteration in mind.

Sample Code:

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()

class User(BaseModel):
    name: str

@app.post("/users/")  
async def create_user(user: User):
    return user

5. Connexion

Connexion embraces the OpenAPI/Swagger specification to design your API contract first and then map endpoints to Python functions implementing API logic.

Why Connexion Stands Apart

Design-first development forces API-first thinking
Tools to quickly build services from OpenAPI contract
Keeps documentation in sync with implementation
OpenAPI ecosystem brings tons of ready tools

With API definitions at its core, Connexion facilitates multiple teams buildling services across large organiztions like Zurich Insurance Group.

Sample Code:

# api-spec.yml
paths:
  /users:  
    get:
      operationId: "app.get_users"

#app.py
import connexion

# Map operationId to a function  
def get_users():
    return [‘John‘, ‘Jane‘]

app = connexion.FlaskApp(__name__, specification_dir=‘.‘)
app.add_api(‘api-spec.yml‘)

6. Hug

Hug aims to expose Python function APIs across multiple interfaces including HTTP, CLI, local with minimual repetition.

How Hug Simplifies Python APIs

Single source for business logic – write once, run anywhere
Auto-generates documentation
Performance focused through code compilation
Encourages clean contract-first development
Great for quickly mocking up services administrating systems

Hug helps Fortune 500 company NCR harmonize APIs across interface boundaries.

Sample Code

import hug

@hug.get()
def hello_world():
    return {‘message‘: ‘Hello World!‘} 

@hug.cli
def hello(name):
    print(f‘Hello {name}!‘)

if __name__ == ‘__main__‘:
    hello()

7. Cornice

Cornice builds web services on top of popular Python web framework Pyramid with simplicity and extensibility as primary goals.

Cornice Highlights

Delivers correct HTTP responses
Flexible validation logic
Multi format serialization
Easy integration into existing Pyramid projects
OpenAPI support for auto docs

Wagwalking leverages Cornice and Pyramid to create fast product APIs that scale painlessly.

Sample Code

from cornice import Service
from functools import wraps

users = Service(name=‘users‘, path=‘/users‘)

@users.get()
def get_info(request):
    return {‘name‘: ‘John‘}

8. Eve

Eve is built on top of battle-tested Flask framework to create highly customizable REST APIs with no code generation that connect to SQL and NoSQL databases.

Why Consider Eve?

Quickly spin up CRUD REST services
Automatic Swagger documentation
User management, auth and access controls
Support for MongoDB, SQL, Neo4j etc.
Hooks to customize any part of of API
Horizontal scalability built-in

From scrappy startups to large companies like Autodesk, Eve helps ship production-ready APIs faster through its expansive feature set.

Sample Code

from eve import Eve 

app = Eve() 
app.run()

This simple app provides a full CRUD REST API on people collection!

Now that you havetour of the major Python API frameworks landscape, let‘s compare them across some key metrics.

Comparing Python API Frameworks

Here is an at-a-glance overview of how these 8 leading contenders stack up across some key criteria:

Framework	Performance	Scalability	Community
Django REST	Good	Excellent	Very large
Flask-RESTful	Good	Very good	Very large
Falcon	Excellent	Excellent	Medium
FastAPI	Excellent	Very good	Large
Connexion	Good	Good	Small
Hug	Very good	Fair	Small
Cornice	Very good	Excellent	Small
Eve	Good	Excellent	Medium

And some additional factors to consider:

Ease of Use: Django REST, Flask-RESTful and FastAPI are easiest to get started with. Falcon, Connexion have a steeper initial learning curve.

Flexibility: Flask-RESTful and Falcon provide unopinionated toolkit to build APIs customized to any need. Django REST Fwork (DRF) enforces more conventions.

Data Validation: DRF, Flask-RESTful, FastAPI, Connexion have great support for automatic data validation.

Documentation: FastAPI and Connexion lead the pack with auto-generated interactive documentation. Eve, DRF close behind.

Legacy App Integration: DRF excellent for incorporating APIs alongside Django apps, Cornice great for adding APIs to Pyramid apps.

Microservices: Falcon, Nameko and Cornice excel at building independent, scalable services in Python. FastAPI also very good.

So which one is the "best" Python API framework? The short answer is…it depends!

Let‘s explore some common scenarios and which frameworks fit them best.

Recommended Python Frameworks By Use Case

I need to quickly prototype a simple REST API

Flask-RESTful is fantastic for spinning up quick REST APIs with minimal fuss. It stays out of your way, keeping things simple but extensible.

Eve is another great option if you want auto database integration.

I‘m building the API for an internal web app

Django REST Framework offers awesome integration with other components of Django ecosystem like admin, databases and Django auth. Building the API will feel like part of the same overall website project.

My API needs to handle huge traffic and scale

Falcon is optimized for speed and can handle insane loads with low overhead. It shines for data intensive services that power public APIs requiring high scalability & throughput.

Cornice for Pyramid and FastAPI are also great scalable options.

I need to break a monolith Django/Flask project into microservices

For Django projects, Django REST makes it easy to gradually migrate pieces into reusable services leveraging existing data model and auth setup.

If starting from Flask, Connexion build services based on OpenAPI contracts to force clear interfaces upfront.

And Cornice does wonders to carve out services from Pyramid monoliths.

My team needs to build many internal APIs

FastAPI is fantastic for productivity given its stellar editor support, error messaging and auto docs. You can build more internal APIs faster by removing boilerplate.

Connexion also shines through its design-first approach using OpenAPI contracts for defining clear, consistent interfaces upfront.

I‘m exposing data from Postgres/MySQL via an API

Django REST Framework makes accessing relational data and associated business logic a joy. Use its viewsets for powerful ORM integrations.

Eve also specializes in auto CRUD APIs from SQL and NoSQL databases.

Learn by Coding! Hands-on API Framework Tutorials

Hopefully you now feel empowered to choose a Python API framework aligned to your needs.

The best way forward is to code up a small prototype API with your shortlisted frameworks to get first-hand experience.

Here are some handy tutorials:

Conclusion

With the right framework, you can build production-ready APIs faster than ever before in Python. We walked through 8 amazing options that can satisfy a diverse range of needs.

Key highlights:

Django REST, Flask-RESTful shine for internal web APIs
Falcon & FastAPI are meant for speed
Connexion & Eve allow designing APIs first
Cornice & Hug simplify breaking apps into services

There‘s no universally best framework. Let your specific requirements guide you to pick the right tool for your next Python API project.

The frameworks themselves keep getting better too. For example, Django REST maintains excellent integration with Django as it modernizes to support async and GraphQL. And FastAPI is adding features like database integrations while retaining performance.

So make sure to periodically reevaluate to adjust to your evolving needs.

I hope you enjoyed this tour of Python API frameworks landscape and feel ready to start building your next awesome API using one of these tools!

8 Popular Python Frameworks for Building APIs

The Rising Need for Python API Frameworks

8 Popular Python API Frameworks

1. Django REST Framework

2. Flask-RESTful

3. Falcon

4. FastAPI

5. Connexion

6. Hug

7. Cornice

8. Eve

Comparing Python API Frameworks

Recommended Python Frameworks By Use Case

I need to quickly prototype a simple REST API

I‘m building the API for an internal web app

My API needs to handle huge traffic and scale

I need to break a monolith Django/Flask project into microservices

My team needs to build many internal APIs

I‘m exposing data from Postgres/MySQL via an API

Learn by Coding! Hands-on API Framework Tutorials

Conclusion

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