Getting Started with FastAPI: Building a CRUD API Tutorial

Overview

FastAPI is a high-performance web framework for building APIs with Python. Its key features include:

Type hint-based: Leverages Python type hints for automatic request/response validation
Auto-generated documentation: Swagger UI (OpenAPI) is automatically generated, allowing you to test APIs from the browser
High performance: Built on Starlette + Pydantic, delivering performance comparable to Node.js and Go

In this article, we’ll walk through building a TODO app CRUD API using FastAPI.

Prerequisites

Python 3.11 or higher
uv installed (see Setting Up a Python Development Environment on Mac with UV)

Environment Setup

First, create a project and install the required packages.

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uv init fastapi-todo
cd fastapi-todo
uv add fastapi uvicorn

fastapi is the web framework itself, and uvicorn is the ASGI server.

Hello World

Let’s start by verifying FastAPI works with a minimal setup. Create a main.py file.

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from fastapi import FastAPI

app = FastAPI()


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

Start the server:

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uv run uvicorn main:app --reload

The --reload option automatically reloads the server when code changes are detected.

Open http://localhost:8000 in your browser and you’ll see:

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

Swagger UI

One of FastAPI’s greatest features is its auto-generated API documentation. Visit http://localhost:8000/docs to see the Swagger UI.

You can test APIs directly from here, eliminating the need for curl or Postman during development.

Implementing the CRUD API

Let’s implement the CRUD API for a TODO app.

Defining Models

First, define the TODO data structure using Pydantic models. Replace main.py with the following:

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from fastapi import FastAPI, HTTPException
from pydantic import BaseModel


app = FastAPI()


class TodoCreate(BaseModel):
    title: str
    completed: bool = False


class TodoResponse(BaseModel):
    id: int
    title: str
    completed: bool


todos: dict[int, dict] = {}
next_id: int = 1

TodoCreate: Request body schema for creating and updating TODOs
TodoResponse: Response type definition
todos: In-memory data store (dict)
next_id: Auto-incrementing ID counter

Create (POST)

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@app.post("/todos", response_model=TodoResponse)
def create_todo(todo: TodoCreate):
    global next_id
    todo_data = {"id": next_id, "title": todo.title, "completed": todo.completed}
    todos[next_id] = todo_data
    next_id += 1
    return todo_data

By specifying response_model=TodoResponse, the response type is reflected in the Swagger UI.

List (GET)

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@app.get("/todos", response_model=list[TodoResponse])
def list_todos():
    return list(todos.values())

Get by ID (GET)

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@app.get("/todos/{todo_id}", response_model=TodoResponse)
def get_todo(todo_id: int):
    if todo_id not in todos:
        raise HTTPException(status_code=404, detail="Todo not found")
    return todos[todo_id]

Returns a 404 error via HTTPException when the ID doesn’t exist.

Update (PUT)

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@app.put("/todos/{todo_id}", response_model=TodoResponse)
def update_todo(todo_id: int, todo: TodoCreate):
    if todo_id not in todos:
        raise HTTPException(status_code=404, detail="Todo not found")
    todo_data = {"id": todo_id, "title": todo.title, "completed": todo.completed}
    todos[todo_id] = todo_data
    return todo_data

Delete (DELETE)

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@app.delete("/todos/{todo_id}")
def delete_todo(todo_id: int):
    if todo_id not in todos:
        raise HTTPException(status_code=404, detail="Todo not found")
    del todos[todo_id]
    return {"detail": "Todo deleted"}

Complete Code

Here’s the full main.py with all endpoints combined:

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from fastapi import FastAPI, HTTPException
from pydantic import BaseModel


app = FastAPI()


class TodoCreate(BaseModel):
    title: str
    completed: bool = False


class TodoResponse(BaseModel):
    id: int
    title: str
    completed: bool


todos: dict[int, dict] = {}
next_id: int = 1


@app.post("/todos", response_model=TodoResponse)
def create_todo(todo: TodoCreate):
    global next_id
    todo_data = {"id": next_id, "title": todo.title, "completed": todo.completed}
    todos[next_id] = todo_data
    next_id += 1
    return todo_data


@app.get("/todos", response_model=list[TodoResponse])
def list_todos():
    return list(todos.values())


@app.get("/todos/{todo_id}", response_model=TodoResponse)
def get_todo(todo_id: int):
    if todo_id not in todos:
        raise HTTPException(status_code=404, detail="Todo not found")
    return todos[todo_id]


@app.put("/todos/{todo_id}", response_model=TodoResponse)
def update_todo(todo_id: int, todo: TodoCreate):
    if todo_id not in todos:
        raise HTTPException(status_code=404, detail="Todo not found")
    todo_data = {"id": todo_id, "title": todo.title, "completed": todo.completed}
    todos[todo_id] = todo_data
    return todo_data


@app.delete("/todos/{todo_id}")
def delete_todo(todo_id: int):
    if todo_id not in todos:
        raise HTTPException(status_code=404, detail="Todo not found")
    del todos[todo_id]
    return {"detail": "Todo deleted"}

Testing

Start the server and test through the Swagger UI.

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uv run uvicorn main:app --reload

Visit http://localhost:8000/docs and test in the following order:

1. Create a TODO

Open POST /todos, click “Try it out”, and enter:

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{
  "title": "Go shopping",
  "completed": false
}

Click “Execute” to get a response like:

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{
  "id": 1,
  "title": "Go shopping",
  "completed": false
}

2. List TODOs

Execute GET /todos to see the list of created TODOs.

3. Update

Use PUT /todos/1 to change completed to true:

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{
  "title": "Go shopping",
  "completed": true
}

4. Delete

Execute DELETE /todos/1 to delete the TODO. Verify with GET /todos that an empty array is returned.

Summary

In this article, we built a TODO CRUD API using FastAPI. Here are the key advantages:

Automatic request/response validation with Pydantic models
Interactive API documentation via Swagger UI
Simple API specification definition using just Python type hints

We used an in-memory data store in this tutorial, but in real applications, you would use an ORM like SQLAlchemy to connect to a database.

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