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8.1 Introduction to FastAPI

Table of Contents

Why FastAPI Matters for Backend Beginners

FastAPI is a modern Python framework that helps you build web backends and APIs quickly and safely. It is designed to be simple to start with, but powerful enough for large production systems.

If you already know a bit of Python, FastAPI lets you move from “basic Python scripts” to “real web APIs” with very little extra code.

Key Ideas Behind FastAPI

FastAPI is built around a few important ideas:

Core idea: In FastAPI, your function definitions (with Python types) describe your API behavior and data format, and FastAPI uses that to:

  • Validate requests,
  • Generate documentation,
  • Serialize responses.

This is very different from many older frameworks where you must write the same thing in several places: routes, validation code, and documentation.

A Tiny Example

Here is a minimal FastAPI application:

python 
from fastapi import FastAPI
app = FastAPI()
@app.get("/")
def read_root():
    return {"message": "Hello, FastAPI!"}

Run this with something like:

bash 
uvicorn main:app --reload

Then open:

You already have:

You will learn about routing, request bodies, validation, and so on in later chapters. Here we focus on what makes FastAPI special as a framework.

FastAPI Compared to Other Python Frameworks

You might have heard of Flask or Django. All three can build backends, but they have different strengths.

FrameworkStyleBest for
FlaskVery minimalTiny apps, learning HTTP, custom architectures
DjangoFull-featured “batteries”Large apps with built-in admin, ORM, templates
FastAPIModern API-focusedAPIs, microservices, async, strong typing

FastAPI is especially good when:

You can still use it for traditional HTML rendering, but it truly shines for APIs.

The Role of Type Hints in FastAPI

FastAPI is built on top of Python type hints. You write types for function parameters and return values, and FastAPI uses them.

Simple Query Parameter Example

python 
from fastapi import FastAPI
app = FastAPI()
@app.get("/items/")
def read_items(limit: int = 10):
    return {"limit": limit}

Here:

You did not write any explicit parsing or validation logic.

Request Body with Pydantic Model

FastAPI uses Pydantic models (you will study them later) to describe JSON bodies.

python 
from fastapi import FastAPI
from pydantic import BaseModel
app = FastAPI()
class User(BaseModel):
    name: str
    age: int
@app.post("/users/")
def create_user(user: User):
    return {"name": user.name, "is_adult": user.age >= 18}

FastAPI automatically:

You will explore this deeply in later chapters, but the idea is:

Rule: In FastAPI, your types are your contract. They define:

  • What the client must send.
  • What your code receives.
  • What your API returns.

Automatic API Documentation

FastAPI generates interactive documentation from your code and types.

There are two main UIs:

With the previous create_user example:

  1. Go to http://localhost:8000/docs
  2. You will see:
    • A POST /users/ endpoint
    • A schema for User with name and age
    • A “Try it out” button

You get:

This is especially useful when working with frontend developers or mobile developers. They can discover and test your API without extra tools.

Async-First Design

FastAPI has first class support for async / await, which is important for high performance I/O bound tasks like:

You can define async endpoints:

python 
from fastapi import FastAPI
import httpx
app = FastAPI()
@app.get("/external")
async def call_external():
    async with httpx.AsyncClient() as client:
        response = await client.get("https://httpbin.org/get")
    return response.json()

Key points:

You will learn more about asynchronous programming later in the course. For now, know that FastAPI is built to work very well with it.

Core Building Blocks in FastAPI

In later FastAPI chapters, you will see these topics in detail. For now, understand them at a high level.

1. Application Object

Every FastAPI project starts with an application instance:

python 
from fastapi import FastAPI
app = FastAPI()

You will attach:

to this app object.

2. Path Operations (Routes)

A path operation is a function that handles a specific HTTP method and path.

Basic patterns:

python 
@app.get("/users")      # GET /users
@app.post("/users")     # POST /users
@app.get("/users/{id}") # GET /users/123

Each decorator describes:

Then the function describes what to do.

3. Parameters

FastAPI reads data from different parts of the HTTP request based on function parameters:

Parameter kindWhere it comes fromExample
Path parameterURL path/users/{user_id}
Query parameterURL query string/items?limit=10
Request bodyJSON body@app.post("/items") with model
HeaderHTTP headersAuthorization header
CookieHTTP cookiesSession cookie

You declare them as function parameters, and FastAPI decides where to read them from based on type and helpers. Later chapters will cover path parameters, query parameters, and request bodies in detail.

4. Dependency Injection

FastAPI includes a built-in dependency injection system to share logic like:

Example idea (simplified):

python 
from fastapi import Depends
def get_settings():
    return {"debug": True}
@app.get("/info")
def info(settings = Depends(get_settings)):
    return settings

You will have a full chapter on dependencies, so for now just understand that:

Idea: FastAPI dependencies help you reuse logic across endpoints without repeating code, and keep your handlers clean.

Typical FastAPI Development Flow

Here is what developing with FastAPI usually looks like:

  1. Define your data models
    Using Pydantic and Python types for requests and responses.
  2. Create endpoints (routes)
    Decide on URLs and HTTP methods, write functions with type hints.
  3. Run with Uvicorn
    Use uvicorn to start the server in development.
  4. Test your API
    Use /docs to test manually, and pytest for automated tests later.
  5. Add extra features
    • Authentication and authorization
    • Database integration
    • Background tasks
    • Caching

FastAPI is largely about building clean APIs around well typed Python code.

Strengths and Limitations of FastAPI

Strengths

Limitations to Be Aware Of

How This Course Will Use FastAPI

In the FastAPI section of this course you will:

By the end, you will be able to:

Summary

From here, the next chapter will show you how to create a FastAPI project and run your first real application.

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