FastAPI: How to Start with One Simple Project

FastAPI has rapidly gained popularity in the Python community, and for good reason. Designed to be fast, easy to use, and robust, it enables developers to build APIs quickly while maintaining code readability and performance.

If you’re new to FastAPI, this guide walks you through setting up your first simple project from scratch. By the end, you’ll have a working REST API and the foundational knowledge to grow it into something more powerful.

Why FastAPI?

Before we dive into code, it’s worth understanding what sets FastAPI apart:

Speed: As the name suggests, it's fast—both in development time and performance, thanks to asynchronous support.
Automatic docs: With Swagger UI and ReDoc automatically generated from your code.
Type hints: Built on Python type annotations, improving editor support and catching errors early.
Built on Starlette and Pydantic: Ensures high performance and robust data validation.

Prerequisites

You’ll need:

Python 3.7+
Basic knowledge of Python
Familiarity with HTTP concepts (GET, POST, etc.)

Let’s get started.

Step 1: Project Setup

First, create a new directory for your project

mkdir fastapi-simple-api

cd fastapi-simple-api

Create a virtual environment and activate it:

python -m venv venv

source venv/bin/activate # On Windows: venv\Scripts\activate

Install FastAPI and a production server (Uvicorn):

pip install fastapi uvicorn

Step 2: Create the App

Create a file called main.py:

# main.py

from fastapi import FastAPI

app = FastAPI()

@app.get("/")

def read_root():

return {"message": "Hello, FastAPI!"}

@app.get("/items/{item_id}")

def read_item(item_id: int, q: str = None):

return {"item_id": item_id, "q": q}

This minimal app has:

A root endpoint (/) that returns a greeting.
A dynamic endpoint (/items/{item_id}) that accepts a path parameter and an optional query parameter.

Step 3: Run the Server

Start your API using Uvicorn:

uvicorn main:app --reload

The --reload flag restarts the server upon code changes, ideal for development.

Now visit:

http://127.0.0.1:8000/ — see your API in action.
http://127.0.0.1:8000/docs — access the Swagger UI.
http://127.0.0.1:8000/redoc — see the ReDoc UI.

Step 4: Add a POST Endpoint

Extend your app to accept POST data:

from pydantic import BaseModel

class Item(BaseModel):

name: str

price: float

is_offer: bool = None

@app.post("/items/")

def create_item(item: Item):

return {"received_item": item}

This endpoint allows clients to send JSON payloads like:

{

"name": "Book",

"price": 29.99,

"is_offer": true

}

FastAPI automatically validates and parses this data into a Python object.

Step 5: Next Steps

Now that your project is running, here are some suggestions to expand it:

Add PUT and DELETE methods
Connect to a database (e.g., SQLite with SQLAlchemy)
Organize code using routers and dependencies
Add authentication (OAuth2, JWT)

Final Thoughts

FastAPI strikes a perfect balance between power and simplicity. In just a few lines, you get a fully functioning API with validation, documentation, and high performance out of the box.

Starting with a simple project like this not only teaches you the fundamentals but sets the stage for building scalable web applications and microservices.

Happy coding!

AtulLab

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