FastAPI vs Flask: Which Python Framework Should You Choose?

Python dominates the backend ecosystem with its simplicity and versatility, and two frameworks often come up in discussions: Flask and FastAPI. If you’re building an API or web application, you may wonder — FastAPI vs Flask: which one is better?

In this article, we’ll break down the key differences, performance benchmarks, use cases, and code examples so you can make an informed choice.

Flask: A Battle-Tested Classic

Flask, released in 2010, is a lightweight microframework designed with flexibility in mind. It gives developers the building blocks to create web apps and APIs with minimal boilerplate.

Key Features:

• Simple, minimalistic design
• Huge ecosystem of extensions
• Well-documented and stable
• Ideal for prototypes and smaller apps

Example: Simple Flask API

from flask import Flask, jsonify

app = Flask(__name__)

@app.route('/hello', methods=['GET'])
def hello():
    return jsonify({"message": "Hello from Flask!"})

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

FastAPI: The Modern Challenger

FastAPI, released in 2018, is a modern, high-performance framework for building APIs with Python 3.6+ type hints. Built on top of Starlette and Pydantic, it’s designed for speed and developer productivity.

Key Features:

• Asynchronous support (async/await)
• Automatic API docs with Swagger & ReDoc
• Built-in data validation using Pydantic
• Much faster than Flask in benchmarks

Example: Simple FastAPI API

from fastapi import FastAPI

app = FastAPI()

@app.get("/hello")
def hello():
    return {"message": "Hello from FastAPI!"}

Once you run this, FastAPI automatically provides interactive docs at /docs.

FastAPI vs Flask: Head-to-Head Comparison

from fastapi import FastAPI
import asyncio

app = FastAPI()

@app.get("/async-task")
async def async_task():
    await asyncio.sleep(1)
    return {"status": "Task completed"}