FastAPI Foundations

FastAPI is a modern Python web framework for building high-performance REST APIs. It combines Python’s type annotations, Pydantic models, and automatic API documentation to simplify backend development. Before learning FastAPI, it’s important to understand how modern web applications communicate and why REST APIs have become the standard for backend development.

Topics Covered

In this module, you’ll learn:

Client and Server
Backend Development
APIs and REST APIs
Quick Start
HTTP Fundamentals
FastAPI Fundamentals
Routing and Request Handling
Request Validation
Response Models
Exception Handling
Building REST APIs
Best Practices

Try Yourself: 💻 VS Code | 🚀 Colab | 📥 Download
Verify Solutions: 💻 VS Code | 🚀 Colab | 📥 Download

By the end of this module, you’ll understand how web applications communicate and build your own REST APIs using FastAPI.

Client and Server

Most modern applications follow the Client-Server Architecture. The client requests a service. The server processes the request and returns a response.

        Request
Client ----------> Server
       <----------
        Response

Examples of Clients

Web Browser
React Application
Angular Application
Vue Application
Flutter Application
Android Application
iOS Application
Postman

Examples of Servers

FastAPI
Django
Flask
Express.js
Spring Boot

Exercise 1

Identify whether each of the following is a Client or a Server.

Component	Client or Server?
Chrome Browser	?
FastAPI	?
Flutter App	?
Django	?

Solution

Component	Type
Chrome Browser	Client
FastAPI	Server
Flutter App	Client
Django	Server

Exercise 2

Give any three examples of client applications.

Solution

Possible answers:

Chrome
Edge
React
Flutter
Android
iOS
Postman

Backend Development

The backend is responsible for processing requests and managing application data. Its responsibilities include:

Business Logic
Authentication
Authorization
Data Validation
Database Operations
Sending Responses

A typical web application looks like this.

Frontend
    │
HTTP Request
    ▼
Backend
    │
Business Logic
    │
Database
    │
HTTP Response
    ▼
Frontend

Examples of backend-powered applications:

Amazon
Flipkart
Gmail
Instagram
Netflix
WhatsApp

Exercise 1

List any four responsibilities of a backend application.

Solution

Possible answers:

Authentication
Authorization
Business Logic
Database Operations
Data Validation
Sending Responses

Exercise 2

Which component is responsible for storing and retrieving data?

Solution

Backend (through a Database)

Backend Returning HTML vs REST API

Backend applications are commonly developed in two different ways.

Backend Returning HTML

The backend generates the complete user interface.

Browser
    │
 GET /
    ▼
Backend
    │
HTML Page
    ▼
Browser

Examples:

Django Templates
Flask + Jinja
PHP
ASP.NET MVC

Backend Returning REST APIs

The backend returns only data, typically in JSON format. The frontend is responsible for rendering the user interface.

React

Angular

Vue

Flutter

Android

iOS
      │
 HTTP Request
      ▼
 FastAPI
      │
JSON Response
      ▼
Frontend

Comparison

Backend Returning HTML	Backend Returning REST APIs
Returns HTML pages	Returns JSON data
Backend generates UI	Frontend generates UI
Tight coupling	Loose coupling
Mostly websites	Websites, Mobile Apps, Desktop Apps
One frontend	Multiple frontends can reuse the same backend

Why REST APIs?

A single backend can serve multiple clients.

             React
               │
Android App ───┤
               │
Flutter App ───┤
               │
Desktop App ───┤
               │
          FastAPI
               │
           Database

This makes applications:

Reusable
Scalable
Platform Independent

Exercise 1

Which backend approach is generally used for React applications?

Solution

Backend Returning REST APIs

Exercise 2

Which backend approach is commonly used by traditional websites like WordPress?

Solution

Backend Returning HTML

What is an API?

An Application Programming Interface (API) is a set of rules that allows two software applications to communicate. Examples:

React ↔ FastAPI
Flutter ↔ FastAPI
Python ↔ Weather API
Python ↔ Payment Gateway
Python ↔ OpenAI API

Applications exchange information through requests and responses.

Client
   │
API Request
   ▼
Server
   │
API Response
   ▼
Client

Exercise 1

Give two real-world examples where APIs are used.

Solution

Examples:

Google Maps API
OpenAI API
Weather API
Payment Gateway API

Exercise 2

Who initiates an API request?

Solution

The Client.

What is a REST API?

A REST API (Representational State Transfer API) is an API that follows REST principles and communicates using the HTTP protocol. Instead of exposing functions, REST APIs expose resources. Examples:

/students

/books

/courses

/orders

Clients perform different operations using HTTP methods.

GET     /students

POST    /students

PUT     /students/101

PATCH   /students/101

DELETE  /students/101

Characteristics of REST APIs

Stateless
Resource-Oriented
Client-Server Based
Cacheable
Uniform Interface

Exercise 1

Is the following a resource?

/students

Solution

Yes.It represents the Students resource.

Exercise 2

Write suitable endpoints for the following resources.

Employees
Products

Solution

/employees

/products

Why FastAPI for REST APIs?

FastAPI is highly regarded in the industry for building backend REST APIs. Three main features make it stand out:

1. Async-First Architecture

FastAPI natively supports asynchronous programming (async/await).

High Concurrency: When building REST APIs that depend on external I/O bound tasks, such as calling Large Language Models (LLMs) or database operations, async allows the server to handle other incoming requests without waiting for the LLM response to finish.
GenAI Compatibility: This is particularly useful for AI systems where LLM calls are latency-heavy. The async-first model makes it highly efficient to stream LLM responses back to the client in real-time.

2. Built-in Pydantic Validation

FastAPI integrates Pydantic for data parsing and validation.

Input Validation: Enforces strict types on incoming payloads (JSON requests) before they enter your backend logic.
Cost & Time Efficiency: By validating request parameters upfront, FastAPI instantly filters out malformed data (returning a 422 Unprocessable Entity status code). This prevents your application from forwarding invalid payloads to external LLM providers, saving both token costs and execution time.

3. Automatic Interactive Documentation

FastAPI automatically generates interactive API documentation based on the OpenAPI specification:

Instant Testing: Enables developers to immediately visualize and test API endpoints directly from the browser (via Swagger UI at /docs or ReDoc at /redoc) without needing external client tools.
Always in Sync: Because the documentation is generated dynamically from your Python type hints and Pydantic schemas, the documentation is guaranteed to remain in sync with your actual backend code.

Quick Start

Let’s build our first FastAPI application.

Step 1: Create a Project

uv init student-api

cd student-api

Step 2: Install FastAPI

uv add fastapi uvicorn

Step 3: Project Structure

student-api/

├── .venv/
├── pyproject.toml
├── uv.lock
├── README.md
└── main.py

Step 4: Create `main.py`

from fastapi import FastAPI

app = FastAPI()


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

Step 5: Run the Application

uv run uvicorn main:app --reload

Output ?

Show Output

INFO:     Uvicorn running on http://127.0.0.1:8000
INFO:     Application startup complete.

Step 6: Open the Application

http://127.0.0.1:8000

Output ?

Show Output

{
    "message": "Welcome to FastAPI!"
}

Step 7: Interactive API Documentation

FastAPI automatically generates interactive API documentation. Swagger UI

http://127.0.0.1:8000/docs

ReDoc

http://127.0.0.1:8000/redoc

Exercise 1

Create a FastAPI application that returns:

{
    "message": "Hello FastAPI!"
}

Solution

from fastapi import FastAPI

app = FastAPI()


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

Exercise 2

Run the application and verify that the following pages are accessible.

http://127.0.0.1:8000

http://127.0.0.1:8000/docs

http://127.0.0.1:8000/redoc

Solution

uv run uvicorn main:app --reload

Then open the URLs in your browser.

HTTP Fundamentals

REST APIs communicate using the HTTP (HyperText Transfer Protocol). HTTP defines how clients and servers exchange information through requests and responses.

URL (Uniform Resource Locator)

A URL identifies the location of a resource on a server. Example:

http://127.0.0.1:8000/students/101?active=true

A URL consists of several parts.

Part	Example	Description
Protocol	`http`	Communication protocol
Host	`127.0.0.1`	Server address
Port	`8000`	Port number
Path	`/students/101`	Resource path
Query Parameter	`active=true`	Additional information

Endpoint

An Endpoint is a combination of an HTTP method and a URL path that performs a specific operation. Examples:

GET /students

GET /students/101

POST /students

In FastAPI,

@app.get("/students")
def get_students():
    return []

creates the endpoint

GET /students

URL vs Endpoint

URL	Endpoint
Complete address of a resource	HTTP Method + Path
`http://localhost:8000/students`	`GET /students`

HTTP Request

An HTTP Request is the complete message sent by a client. Example

POST /students HTTP/1.1
Host: localhost:8000
Content-Type: application/json
Accept: application/json
Authorization: Bearer <access-token>
User-Agent: PostmanRuntime/7.39.0

{
    "name": "Alice",
    "age": 20,
    "course": "Python"
}

Parts of an HTTP Request

Part	Purpose
POST	HTTP Method
`/students`	Endpoint
Host	Server Address
Content-Type	Format of the request body
Accept	Expected response format
Authorization	Authentication information
User-Agent	Client application
Body	Data sent to the server

HTTP Response

After processing the request, the server returns an HTTP Response. Example

HTTP/1.1 201 Created
Content-Type: application/json

{
    "id": 101,
    "name": "Alice",
    "age": 20,
    "course": "Python"
}

Parts of an HTTP Response

Part	Purpose
201	Status Code
Headers	Metadata
Body	Response Data

HTTP Methods

REST APIs commonly use the following methods.

Method	Purpose
GET	Retrieve data
POST	Create data
PUT	Update a resource
PATCH	Partially update a resource
DELETE	Delete a resource

Example:

GET      /students

GET      /students/101

POST     /students

PUT      /students/101

PATCH    /students/101

DELETE   /students/101

HTTP Status Codes

Every response contains a status code describing the result.

Status Code	Meaning
200	OK
201	Created
204	No Content
400	Bad Request
401	Unauthorized
403	Forbidden
404	Not Found
422	Validation Error
500	Internal Server Error

Testing REST APIs

REST APIs can be tested using several tools.

Tool	Purpose
Browser	Test simple GET requests
Swagger UI	Interactive API documentation
ReDoc	Read-only API documentation
Postman	API Testing
Bruno	Open-source API Client
Insomnia	Lightweight API Client
curl	Command-line testing
VS Code REST Client	Test APIs from VS Code

FastAPI Fundamentals

FastAPI is a modern, high-performance API framework. It is fundamentally different from traditional full-stack web frameworks like Django:

FastAPI (API-First): Focuses solely on building high-performance REST/GraphQL APIs that exchange clean, structured data (typically JSON).
Django (Full-Stack): A server-rendered framework that manages administrative dashboards, views, and directly renders HTML pages to send to the browser.

Why API-First is Essential for Modern & GenAI Apps

This backend-frontend decoupling is the industry standard today:

Modern Frontends: Single Page Applications (Next.js, React, Vue) and mobile apps only require a backend to serve raw JSON data, not server-rendered HTML.
Generative AI (GenAI): AI agents, LLM tool-calling (OpenAI, Claude), and real-time streaming interfaces rely heavily on highly concurrent web services. FastAPI’s async speed makes it the primary choice for modern AI and GenAI backend applications.

A FastAPI application begins by creating an instance of the FastAPI class.

from fastapi import FastAPI

app = FastAPI()

The app object represents the entire web application. Every API endpoint is registered with this object.

Creating Your First Route

from fastapi import FastAPI

app = FastAPI()


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

Open

http://127.0.0.1:8000

Output ?

Show Output

{
    "message": "Welcome to FastAPI!"
}

Routing

A Route maps an incoming HTTP request to a Python function.

@app.get("/hello")
def hello():
    return {
        "message": "Hello World"
    }

Every route consists of:

HTTP Method
URL Path
Python Function

HTTP Method Decorators

FastAPI provides decorators for common HTTP methods.

@app.get("/students")

@app.post("/students")

@app.put("/students/{id}")

@app.patch("/students/{id}")

@app.delete("/students/{id}")

Path Parameters

Path parameters allow values to be passed as part of the URL.

@app.get("/students/{student_id}")
def get_student(student_id: int):
    return {
        "student_id": student_id
    }

Open

http://127.0.0.1:8000/students/101

Output ?

Show Output

{
    "student_id": 101
}

Exercise 1

Create an endpoint that returns the given employee id. Sample URL

/employees/15

Expected Output

{
    "employee_id": 15
}

Solution

@app.get("/employees/{employee_id}")
def get_employee(employee_id: int):
    return {
        "employee_id": employee_id
    }

Query Parameters

Query parameters are optional values appended to a URL.

@app.get("/students")
def get_students(active: bool):
    return {
        "active": active
    }

Open

/students?active=true

Output ?

Show Output

{
    "active": true
}

Exercise 2

Create a route that accepts a query parameter named course. Sample URL

/students?course=Python

Expected Output

{
    "course": "Python"
}

Solution

@app.get("/students")
def get_students(course: str):
    return {
        "course": course
    }

Request Body

Data sent using POST, PUT and PATCH requests is called the Request Body. FastAPI uses Pydantic models to validate request data.

from pydantic import BaseModel

class Student(BaseModel):

    name: str
    age: int


@app.post("/students")
def create_student(student: Student):
    return student

Request Body

{
    "name": "Alice",
    "age": 20
}

Output ?

Show Output

{
    "name": "Alice",
    "age": 20
}

Request Validation

FastAPI automatically validates incoming request data. If invalid data is provided,

{
    "name": "Alice",
    "age": "twenty"
}

FastAPI returns Output ?

Show Output

422 Unprocessable Entity

No additional validation code is required because FastAPI uses Pydantic internally.

Exercise 1

Create a Book model with:

title
author
price

Create a POST endpoint that returns the received data.

Solution

from pydantic import BaseModel

class Book(BaseModel):

    title: str
    author: str
    price: float


@app.post("/books")
def create_book(book: Book):
    return book

Exercise 2

Send an invalid value for price and observe the validation error.

Solution

{
    "title": "Python",
    "author": "John",
    "price": "abc"
}

FastAPI automatically returns a 422 Validation Error.

Response Models

So far, our APIs have returned Python objects directly. FastAPI also allows us to define the structure of the response using response models. A response model ensures that the returned data:

Has the expected structure
Contains the correct data types
Automatically generates API documentation

Example

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class Student(BaseModel):

    id: int
    name: str
    age: int


@app.get(
    "/student",
    response_model=Student
)
def get_student():

    return {
        "id": 101,
        "name": "Alice",
        "age": 20
    }

Output ?

Show Output

{
    "id": 101,
    "name": "Alice",
    "age": 20
}

Returning Multiple Objects

@app.get(
    "/students",
    response_model=list[Student]
)
def get_students():

    return [
        {
            "id": 101,
            "name": "Alice",
            "age": 20
        },
        {
            "id": 102,
            "name": "Bob",
            "age": 21
        }
    ]

Output ?

Show Output

[
    {
        "id": 101,
        "name": "Alice",
        "age": 20
    },
    {
        "id": 102,
        "name": "Bob",
        "age": 21
    }
]

Exercise 1

Create an Employee model and return a single employee.

Solution

from pydantic import BaseModel

class Employee(BaseModel):

    id: int
    name: str


@app.get(
    "/employee",
    response_model=Employee
)
def get_employee():

    return {
        "id": 1,
        "name": "Rahul"
    }

Exercise 2

Return a list of books using response_model.

Solution

from pydantic import BaseModel

class Book(BaseModel):

    title: str
    price: float


@app.get(
    "/books",
    response_model=list[Book]
)
def get_books():

    return [
        {
            "title": "Python",
            "price": 499
        }
    ]

Basic Exception Handling

Sometimes a request cannot be processed successfully. Instead of returning invalid data, we should return an appropriate HTTP error. FastAPI provides the HTTPException class for this purpose.

Example

from fastapi import HTTPException

students = [
    {
        "id": 1,
        "name": "Alice"
    }
]


@app.get("/students/{student_id}")
def get_student(student_id: int):

    for student in students:

        if student["id"] == student_id:
            return student

    raise HTTPException(
        status_code=404,
        detail="Student not found"
    )

Request

/students/10

Output ?

Show Output

{
    "detail": "Student not found"
}

Common Exceptions

Status Code	Meaning
400	Bad Request
401	Unauthorized
403	Forbidden
404	Not Found
422	Validation Error
500	Internal Server Error

Exercise 1

Retrieve an employee by ID. Requirements:

Search for the employee in the given list.
Return the employee if found.
Raise a 404 Not Found exception if the employee does not exist.

employees = [
    {"id": 1, "name": "Rahul"},
    {"id": 2, "name": "Priya"},
    {"id": 3, "name": "Arjun"}
]

Solution

from fastapi import HTTPException

employees = [
    {"id": 1, "name": "Rahul"},
    {"id": 2, "name": "Priya"},
    {"id": 3, "name": "Arjun"}
]

@app.get("/employees/{employee_id}")
def get_employee(employee_id: int):

    for employee in employees:
        if employee["id"] == employee_id:
            return employee

    raise HTTPException(
        status_code=404,
        detail="Employee not found"
    )

Exercise 2

Raise a 400 exception if age is less than 18.

Solution

from fastapi import HTTPException


@app.post("/students")
def create_student(age: int):

    if age < 18:

        raise HTTPException(
            status_code=400,
            detail="Age must be at least 18"
        )

    return {
        "message": "Student Created"
    }

Request Validation

FastAPI automatically validates incoming request data using type annotations and Pydantic.

Function	Used For
`Path()`	Path Parameters
`Query()`	Query Parameters
`Body()`	Request Body
`Field()`	Model Attributes

Path Parameters

Required

student_id: Annotated[int, Path()]

With Validation

student_id: Annotated[int, Path(gt=0)]

Exercise

Create an endpoint to retrieve a product by its ID. Requirements:

Endpoint: /products/{product_id}
product_id must be greater than 0.

Solution

@app.get("/products/{product_id}")
def get_product(product_id: Annotated[int, Path(gt=0)]):
    return {"product_id": product_id}

Query Parameters

Required

course: Annotated[str, Query()]

Optional with Default

page: Annotated[int, Query()] = 1

With Validation

page: Annotated[int, Query(ge=1)] = 1

Exercise

Create an endpoint to list books. Requirements:

Accept an optional query parameter page.
Default value should be 1.

Example

/books?page=2

Solution

@app.get("/books")
def get_books(page: Annotated[int, Query()] = 1):
    return {"page": page}

Request Body

@app.post("/students")
def create_student(student: Annotated[Student, Body()]):
    return student

Exercise

Create a Book model with the following attributes.

title
price

Create a POST endpoint that returns the received object.

Solution

class Book(BaseModel):
    title: Annotated[str, Field()]
    price: Annotated[float, Field()]

@app.post("/books")
def create_book(book: Annotated[Book, Body()]):
    return book

Model Attributes

Required

name: Annotated[str, Field()]

Required with Validation

name: Annotated[str, Field(min_length=3)]

age: Annotated[int, Field(ge=18, le=60)]

Optional with Default

city: Annotated[str, Field()] = "Hyderabad"

Optional Nullable

email: Annotated[EmailStr | None, Field()] = None

Exercise

Modify the Book model. Requirements:

title should have a minimum length of 3.
price should be greater than 0.

Solution

class Book(BaseModel):
    title: Annotated[str, Field(min_length=3)]
    price: Annotated[float, Field(gt=0)]

Default Values

A value is considered required if no default value is assigned. Assigning a value using = makes it optional.

Requirement	Example
Required Path Parameter	`id: Annotated[int, Path()]`
Required Query Parameter	`course: Annotated[str, Query()]`
Optional Query Parameter	`page: Annotated[int, Query()] = 1`
Required Body Attribute	`name: Annotated[str, Field()]`
Optional Body Attribute	`city: Annotated[str, Field()] = "Hyderabad"`
Optional Nullable Attribute	`email: Annotated[EmailStr \| None, Field()] = None`

Exercise

Create an Employee model. Requirements:

name → required
department → default "IT"
salary → default 25000

Solution

class Employee(BaseModel):
    name: Annotated[str, Field()]
    department: Annotated[str, Field()] = "IT"
    salary: Annotated[float, Field()] = 25000

Exercise

Add optional contact details to the Employee model. Requirements:

email
phone

Both should be optional.

Solution

class Employee(BaseModel):
    name: Annotated[str, Field()]
    email: Annotated[EmailStr | None, Field()] = None
    phone: Annotated[str | None, Field()] = None

Common Validation Rules

Function	Common Rules
`Path()`	`gt`, `ge`, `lt`, `le`, `title`, `description`, `examples`
`Query()`	`gt`, `ge`, `lt`, `le`, `min_length`, `max_length`, `pattern`, `title`, `description`, `examples`
`Field()`	`gt`, `ge`, `lt`, `le`, `min_length`, `max_length`, `pattern`, `title`, `description`, `examples`

Validation Errors

FastAPI automatically validates:

Path Parameters
Query Parameters
Request Body
Model Attributes
Data Types

If validation fails, FastAPI automatically returns:

422 Unprocessable Entity

Key Points

Use Path() for path parameters.
Use Query() for query parameters.
Use Body() for request bodies.
Use Field() for model attributes.
Use Annotated to combine type hints with validation metadata.
A value is required if no default value is assigned.
A value becomes optional when a default value (including None) is assigned.
FastAPI automatically performs type conversion and request validation.

Mini Project - Student Management REST API

Let’s combine everything we’ve learned so far. We’ll build a simple Student Management API using an in-memory list.

Features

Get all students
Get a student by ID
Add a student
Update a student
Delete a student

The data will be stored in a Python list.

students = [
    {
        "id": 1,
        "name": "Alice",
        "age": 20
    },
    {
        "id": 2,
        "name": "Bob",
        "age": 21
    }
]

In the next module, we’ll replace this list with a database using SQLAlchemy ORM.

Best Practices

Use meaningful endpoint names.
Follow REST naming conventions.
Use Pydantic models for request and response data.
Return appropriate HTTP status codes.
Raise HTTPException for invalid requests.
Keep route functions simple and focused.
Test APIs using Swagger UI or Postman.

Practice

To reinforce what you’ve learned in this section, practice with the interactive follow-along notebook:

Follow-Along Practice

Practice creating FastAPI instances, defining path/query parameters, handling request payloads with Pydantic BaseModel schemas, customizing responses, and raising HTTPExceptions.💻 VS Code | 🚀 Colab | 📥 Download

Summary

In this module, you learned how to build REST APIs using FastAPI.

Key Concepts Covered

Client and Server
Backend Development
APIs and REST APIs
HTTP Fundamentals
FastAPI Fundamentals
Routing
Path Parameters
Query Parameters
Request Body
Request Validation
Response Models
Basic Exception Handling
Building REST APIs
Best Practices

You now have a solid understanding of FastAPI fundamentals. In the next module, you’ll learn how to organize larger applications using APIRouter, integrate a database with SQLAlchemy ORM, apply Dependency Injection, and build a modular FastAPI application.

​FastAPI Foundations

​Topics Covered

​Client and Server

​Examples of Clients

​Examples of Servers

​Exercise 1

​Exercise 2

​Backend Development

​Exercise 1

​Exercise 2

​Backend Returning HTML vs REST API

​Backend Returning HTML

​Backend Returning REST APIs

​Comparison

​Why REST APIs?

​Exercise 1

​Exercise 2

​What is an API?

​Exercise 1

​Exercise 2

​What is a REST API?

​Characteristics of REST APIs

​Exercise 1

​Exercise 2

​Why FastAPI for REST APIs?

​1. Async-First Architecture

​2. Built-in Pydantic Validation

​3. Automatic Interactive Documentation

​Quick Start

​Step 1: Create a Project

​Step 2: Install FastAPI

​Step 3: Project Structure

​Step 4: Create main.py

​Step 5: Run the Application

​Step 6: Open the Application

​Step 7: Interactive API Documentation

​Exercise 1

​Exercise 2

​HTTP Fundamentals

​URL (Uniform Resource Locator)

​Endpoint

​URL vs Endpoint

​HTTP Request

​Parts of an HTTP Request

​HTTP Response

​Parts of an HTTP Response

​HTTP Methods

​HTTP Status Codes

​Testing REST APIs

​FastAPI Fundamentals

​Why API-First is Essential for Modern & GenAI Apps

​Creating Your First Route

​Routing

​HTTP Method Decorators

​Path Parameters

​Exercise 1

​Query Parameters

​Exercise 2

​Request Body

​Request Validation

​Exercise 1

​Exercise 2

​Response Models

​Example

​Returning Multiple Objects

​Exercise 1

​Exercise 2

​Basic Exception Handling

​Example

​Common Exceptions

​Exercise 1

​Exercise 2

​Request Validation

​Path Parameters

​Exercise

​Query Parameters

​Exercise

​Request Body

​Exercise

​Model Attributes

FastAPI Foundations

Topics Covered

Client and Server

Examples of Clients

Examples of Servers

Exercise 1

Exercise 2

Backend Development

Exercise 1

Exercise 2

Backend Returning HTML vs REST API

Backend Returning HTML

Backend Returning REST APIs

Comparison

Why REST APIs?

Exercise 1

Exercise 2

What is an API?

Exercise 1

Exercise 2

What is a REST API?

Characteristics of REST APIs

Exercise 1

Exercise 2

Why FastAPI for REST APIs?

1. Async-First Architecture

2. Built-in Pydantic Validation

3. Automatic Interactive Documentation

Quick Start

Step 1: Create a Project

Step 2: Install FastAPI

Step 3: Project Structure

Step 4: Create `main.py`

Step 5: Run the Application

Step 6: Open the Application

Step 7: Interactive API Documentation

Exercise 1

Exercise 2

HTTP Fundamentals

URL (Uniform Resource Locator)

Endpoint

URL vs Endpoint

HTTP Request

Parts of an HTTP Request

HTTP Response

Parts of an HTTP Response

HTTP Methods

HTTP Status Codes

Testing REST APIs

FastAPI Fundamentals

Why API-First is Essential for Modern & GenAI Apps

Creating Your First Route

Routing

HTTP Method Decorators

Path Parameters

Exercise 1

Query Parameters

Exercise 2

Request Body

Request Validation

Exercise 1

Exercise 2

Response Models

Example

Returning Multiple Objects

Exercise 1

Exercise 2

Basic Exception Handling

Example

Common Exceptions

Exercise 1

Exercise 2

Request Validation

Path Parameters

Exercise

Query Parameters

Exercise

Request Body

Exercise

Model Attributes