Building a REST API with FastAPI

There’s something magical about building an API that just works. You write clean, intuitive code, and suddenly you have interactive documentation, automatic validation, and blazing-fast performance. That’s the FastAPI experience—a framework that feels like it was designed by developers who actually build production systems.

Whether you’re prototyping a side project or architecting enterprise services, FastAPI removes the friction between your ideas and working code. Let’s build something together.

Why FastAPI

FastAPI isn’t just another Python web framework—it’s a paradigm shift in how we think about API development.

Lightning Fast Performance: Built on Starlette and Pydantic, FastAPI delivers performance comparable to Node.js and Go. We’re talking tens of thousands of requests per second.

Type Safety That Actually Helps: Python type hints aren’t just decorative—FastAPI uses them to validate requests, serialize responses, and generate documentation automatically. Write types once, get benefits everywhere.

Documentation for Free: The moment you define an endpoint, FastAPI generates interactive API docs using OpenAPI (Swagger UI) and ReDoc. No configuration, no manual updates, no drift between code and documentation.

Async Native: First-class support for async/await means you can handle concurrent requests efficiently, making it perfect for I/O-bound workloads like database queries and external API calls.

Developer Experience: FastAPI was built with developer productivity in mind. The error messages are clear, the patterns are intuitive, and the ecosystem is rich.

Prerequisites

Before we dive in, ensure you have Python 3.8 or higher installed:

python --version

You’ll also want to set up a virtual environment to keep dependencies isolated:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

Your First API

Let’s create a simple API in minutes. First, install FastAPI and Uvicorn (an ASGI server):

pip install fastapi uvicorn[standard]

Create a file called main.py:

from fastapi import FastAPI

app = FastAPI()

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

@app.get("/health")
async def health_check():
    return {"status": "healthy"}

That’s it. Run your API:

uvicorn main:app --reload

Visit http://localhost:8000 to see your API in action. But here’s where it gets interesting—navigate to http://localhost:8000/docs. You’ll see a fully interactive API documentation page, complete with the ability to test endpoints directly in your browser. This is automatically generated from your code.

Try http://localhost:8000/redoc for an alternative documentation style. Both are production-ready and update automatically as you modify your code.

Adding Endpoints

Let’s build a simple task management API with full CRUD operations:

from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from typing import Optional

app = FastAPI()

# In-memory storage (use a database in production)
tasks = {}
task_id_counter = 1

class Task(BaseModel):
    title: str
    description: Optional[str] = None
    completed: bool = False

class TaskUpdate(BaseModel):
    title: Optional[str] = None
    description: Optional[str] = None
    completed: Optional[bool] = None

@app.get("/tasks")
async def get_tasks():
    """Retrieve all tasks"""
    return list(tasks.values())

@app.get("/tasks/{task_id}")
async def get_task(task_id: int):
    """Retrieve a specific task by ID"""
    if task_id not in tasks:
        raise HTTPException(status_code=404, detail="Task not found")
    return tasks[task_id]

@app.post("/tasks", status_code=201)
async def create_task(task: Task):
    """Create a new task"""
    global task_id_counter
    task_data = task.dict()
    task_data["id"] = task_id_counter
    tasks[task_id_counter] = task_data
    task_id_counter += 1
    return task_data

@app.put("/tasks/{task_id}")
async def update_task(task_id: int, task_update: TaskUpdate):
    """Update an existing task"""
    if task_id not in tasks:
        raise HTTPException(status_code=404, detail="Task not found")

    stored_task = tasks[task_id]
    update_data = task_update.dict(exclude_unset=True)

    for field, value in update_data.items():
        stored_task[field] = value

    return stored_task

@app.delete("/tasks/{task_id}", status_code=204)
async def delete_task(task_id: int):
    """Delete a task"""
    if task_id not in tasks:
        raise HTTPException(status_code=404, detail="Task not found")
    del tasks[task_id]
    return None

Notice how FastAPI handles:

• Path parameters (task_id) with automatic type conversion
• Request body validation through Pydantic models
• HTTP status codes and error handling
• Optional fields and default values

Test these endpoints in the auto-generated docs at /docs. You’ll see request/response schemas, required fields, and can execute requests right from the browser.

Data Validation

Pydantic models are where FastAPI’s type safety shines. Let’s enhance our Task model with validation:

from pydantic import BaseModel, Field, validator
from typing import Optional
from datetime import datetime

class Task(BaseModel):
    title: str = Field(..., min_length=1, max_length=100)
    description: Optional[str] = Field(None, max_length=500)
    completed: bool = False
    priority: int = Field(1, ge=1, le=5)
    created_at: datetime = Field(default_factory=datetime.now)

    @validator('title')
    def title_must_not_be_empty(cls, v):
        if not v.strip():
            raise ValueError('Title cannot be empty or whitespace')
        return v.strip()

    class Config:
        schema_extra = {
            "example": {
                "title": "Deploy new feature",
                "description": "Deploy the FastAPI service to production",
                "priority": 3,
                "completed": False
            }
        }

With these constraints:

• Title must be 1-100 characters and not just whitespace
• Description is optional but capped at 500 characters
• Priority must be between 1 and 5
• Created timestamp is set automatically
• The example appears in your API documentation

FastAPI validates incoming requests against these rules automatically. Invalid data returns a detailed error response with exactly which field failed validation and why.

What’s Next

You’ve built a working API with validation, documentation, and proper HTTP semantics. But this is just the beginning:

Database Integration: Connect to PostgreSQL, MySQL, or MongoDB using SQLAlchemy, Tortoise ORM, or motor. FastAPI works beautifully with async database drivers.

Authentication & Authorization: Implement JWT tokens, OAuth2 flows, or API key authentication. FastAPI has built-in security utilities that integrate with OpenAPI.

Background Tasks: Process emails, generate reports, or handle long-running operations without blocking API responses.

Testing: Write tests using pytest and FastAPI’s TestClient. The same type safety that helps you write code helps you write bulletproof tests.

Deployment: Package your API in Docker, deploy to Kubernetes, or use platforms like Railway, Fly.io, or AWS Lambda with Mangum.

Advanced Features: Explore WebSockets, GraphQL integration, middleware, CORS, rate limiting, and dependency injection patterns.

The FastAPI documentation is exceptional, and the community is vibrant. You’ve learned the fundamentals—now go build something amazing. The beauty of FastAPI is that as your requirements grow, the framework grows with you, never getting in your way.

Your API is waiting to be built. What will you create?