How to Create Endpoints in FastAPI: Step-by-Step Tutorial

How to Create Endpoints in FastAPI: A Step-by-Step Tutorial

FastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.7+ based on standard Python type hints. In this comprehensive tutorial, you’ll learn how to create endpoints using FastAPI from scratch. We will cover prerequisites, setup, coding examples, troubleshooting, and a summary checklist to reinforce your learning.

Prerequisites

Basic knowledge of Python programming
Python 3.7 or higher installed on your machine
A code editor such as VSCode or PyCharm
Familiarity with REST APIs and HTTP methods is helpful but not mandatory

Step 1: Installing FastAPI and Uvicorn

First, install FastAPI and Uvicorn, the ASGI server that will run your FastAPI app. Use the following command:

pip install fastapi uvicorn

Step 2: Creating Your First FastAPI App

Create a Python file, for example main.py, and start by importing FastAPI and setting up the app instance:

from fastapi import FastAPI

app = FastAPI()

Step 3: Defining a Root Endpoint

Next, create a root endpoint (“/”) using the decorator @app.get to handle GET requests. This will return a simple JSON response.

@app.get("/")
async def read_root():
    return {"message": "Welcome to FastAPI!"}

Step 4: Adding More Endpoints

You can define new endpoints with different paths and HTTP methods. For example, adding a path parameter to greet a user by name:

@app.get("/hello/{name}")
async def greet_name(name: str):
    return {"message": f"Hello, {name}!"}

Step 5: Running Your FastAPI Server

Run your application with the Uvicorn server using the command:

uvicorn main:app --reload

The --reload flag restarts the server on code changes, ideal during development. Open http://127.0.0.1:8000/ in your browser to see the root endpoint.

Step 6: Creating POST Endpoints

FastAPI makes building POST endpoints simple. Here’s an example of an endpoint that accepts JSON data:

from fastapi import Request

@app.post("/items/")
async def create_item(request: Request):
    data = await request.json()
    return {"received_item": data}

Step 7: Using Pydantic Models for Data Validation

Define request bodies and responses with Python classes using Pydantic (Official site). This ensures data validation and parsing:

from pydantic import BaseModel

class Item(BaseModel):
    name: str
    description: str | None = None
    price: float

@app.post("/items/create/")
async def create_item(item: Item):
    return {"item_name": item.name, "price": item.price}

Troubleshooting Tips

Issue: Server won’t start or uvicorn command not found.
Solution: Ensure uvicorn is installed correctly with `pip show uvicorn`. Use a virtual environment for cleaner installs.
Issue: JSON parsing errors.
Solution: Check your request content-type header is `application/json` and the body is valid JSON.
Issue: Endpoint returns 404.
Solution: Verify your route path matches the URL requested and method (GET, POST, etc.) matches.

Summary Checklist

Installed FastAPI and Uvicorn
Created FastAPI app instance
Defined GET and POST endpoints
Used Pydantic models for data validation
Ran development server with auto-reload
Tested endpoints with browser or tools like curl/Postman

For more Python web development tutorials, check out our comprehensive guide on How to Install FastAPI: A Complete Beginner’s Guide. This will help you set up your environment properly before building endpoints.

FastAPI empowers developers to create high-performance web APIs quickly and with less code. Experiment with different HTTP methods, path parameters, and request validations to master it.