Yes, it is absolutely possible to create a REST API with Python. Python is a very popular language for writing REST APIs because of its simplicity, flexibility, and large ecosystem of web frameworks and libraries.
Some key advantages of using Python for REST APIs:
- Simple and readable syntax that allows for rapid development.
- Many great web frameworks like Flask, Django, Pyramid, etc. that make it easy to build and expose REST APIs.
- A wide choice of libraries like Requests, HTTPie, etc. for sending and receiving HTTP requests.
- Built-in JSON support for parsing and generating JSON data.
- Good performance for most REST API use cases.
- Easy to find Python web hosting like Heroku, AWS, GCP, Azure, etc.
- Large open source ecosystem with many reusable components.
Overall, Python provides an excellent balance of productivity and performance for REST API development. Many high-traffic APIs used in production are written in Python including APIs for Dropbox, Reddit, Pinterest, and many more.
What is a REST API?
REST (Representational State Transfer) is an architectural style for building web APIs that relies on standard HTTP methods like GET, POST, PUT, DELETE and standard status codes to enable communication between different systems.
Some key principles of REST APIs:
- Client-Server separation – The API exposes resources and actions that can be accessed by clients.
- Stateless – No client information is stored on the server between requests.
- Cacheable – API responses should be cacheable when applicable to improve performance.
- Uniform interface – Resources are exposed at endpoints and actions are performed using HTTP methods.
- Layered system – The API can be proxied, load balanced and firewalls added for security.
REST APIs expose CRUD operations for resources using:
- GET – Retrieve a resource
- POST – Create a new resource
- PUT/PATCH – Update an existing resource
- DELETE – Delete a resource
Responses are usually JSON providing easy serialization and deserialization.
Overall, REST provides a simple yet powerful architecture for exposing services and data on the web.
Benefits of REST APIs
Some benefits of using REST APIs:
- Standardized and scalable architecture.
- Language agnostic – APIs can be consumed by any language.
- Good performance and caching support.
- Simple and lightweight – no complex formats like SOAP or WSDL.
- Good documentation using OpenAPI specification.
- Easy integration with web and mobile apps.
This makes REST a great choice for public APIs consumed by many different clients.
How to create a REST API in Python
There are a few main steps required to create a REST API in Python:
1. Choose a Python web framework
Popular options include:
- Flask – A microframework great for smaller APIs and services. Easy to use and get started.
- Django – A full-featured framework good for complex, database-driven apps and APIs.
- Pyramid – Built to be very customizable and handles large, complex apps well.
- Falcon – Focuses on speed and performance making it great for large APIs and sites.
- FastAPI – Asynchronous and fast, great documentation and auto-generated OpenAPI specs.
For a simple REST API, Flask provides an easy starting point.
2. Define the API resources and routes
Decide what data resources your API will expose and what routes it will handle. Some examples:
| Resource | Routes |
| Users | /users [GET, POST] |
| User | /users/{id} [GET, PUT, DELETE] |
| Posts | /posts [GET, POST] |
Common resource routes support GET, POST, PUT/PATCH and DELETE operations.
3. Write handler functions for the routes
For each route, write a Python function that handles the request and returns the response:
“`python
@app.route(“/users”, methods=[“GET”])
def get_users():
users = get_all_users_from_database()
return jsonify(users)
“`
The function accesses the required data from a database, file, external API, etc and creates and returns the response.
4. Specify the input and output formats
For a REST API, JSON is a standard format for input data and API responses. This can be handled in Flask using the `jsonify()` method.
Input data from requests can be accessed using:
“`python
user_data = request.get_json()
“`
5. Add error handling
Handle expected errors and return standard response codes like:
– `400 Bad Request` – Invalid request data.
– `401 Unauthorized` – Invalid authentication.
– `403 Forbidden` – No permissions.
– `404 Not Found` – Invalid resource URI.
– `500 Internal Server Error` – Server error.
This provides consistent, standardized error handling.
Example REST API in Python with Flask
Here is simple REST API built with Flask that manages a list of authors and books:
“`python
from flask import Flask, request, jsonify
app = Flask(__name__)
authors = [
{“id”: 1, “name”: “Author 1”},
{“id”: 2, “name”: “Author 2”}
]
books = [
{“id”: 1, “title”: “Book 1”, “author_id”: 1},
{“id”: 2, “title”: “Book 2”, “author_id”: 1}
]
@app.route(“/authors”, methods=[“GET”])
def get_authors():
return jsonify(authors)
@app.route(“/authors/
def get_author(author_id):
author = next((a for a in authors if a[“id”] == author_id), None)
if author:
return jsonify(author)
else:
return jsonify({“message”: “Author not found”}), 404
@app.route(“/authors”, methods=[“POST”])
def create_author():
data = request.get_json()
author = {
“id”: len(authors) + 1,
“name”: data[“name”]
}
authors.append(author)
return jsonify(author), 201
@app.route(“/books”, methods=[“GET”])
def get_books():
return jsonify(books)
@app.route(“/books”, methods=[“POST”])
def create_book():
data = request.get_json()
book = {
“id”: len(books) + 1,
“title”: data[“title”],
“author_id”: data[“author_id”]
}
books.append(book)
return jsonify(book), 201
if __name__ == “__main__”:
app.run()
“`
This provides the core CRUD routes for managing authors and books resources.
To test the API, we can use cURL or an API client like Postman to send requests and view the JSON responses.
Some example requests:
“`
# Get all authors
GET /authors
# Get a specific author
GET /authors/1
# Create a new author
POST /authors
{
“name”: “Author 3”
}
# Get all books
GET /books
# Create a new book
POST /books
{
“title”: “Book 3”,
“author_id”: 1
}
“`
This provides a basic example of how to expose and test a simple REST API with Flask and Python.
Building production-ready REST APIs in Python
For a production-ready, robust REST API, there are several other important considerations:
Data validation
Validate data on input and output to catch errors and provide useful error messages. Libraries like Marshmallow can help with data validation and serialization.
Authentication and authorization
Secure access to the API, usually with an access token that represents the user’s identity and permissions. JWT or OAuth2 can be used for token-based authentication.
Rate limiting
Limit the number of requests a client can make to prevent abuse and protect API availability. This is especially important for public APIs.
API documentation
Auto-generate interactive API documentation using OpenAPI (formerly Swagger) to provide documentation and sandbox testing of API endpoints.
Versioning
Support multiple API versions to allow gracefully introducing changes without breaking existing integrations.
Testing and monitoring
Comprehensive unit and integration tests to ensure quality. Monitoring metrics, request logging and alerting helps catch issues in production.
Hosting and deployment
Host the API on a reliable web host or cloud provider. Containers and orchestration help automate deployment.
Overall these practices require more work but lead to an API that is robust, secure and maintainable.
Conclusion
Python provides an excellent platform for building REST APIs of all types. The simple syntax and powerful web frameworks available make development quick and easy to get started.
With additional tools and design practices, production-level APIs can be built that are reliable, scalable and secure. Many companies use Python to power their public developer APIs as well as internal APIs used by frontends, mobile apps and other services.
So if you need to build or extend an API, Python and frameworks like Flask give you the perfect mix of productivity and power to create robust REST APIs.