FastApi Training , study and exam guide
1 Introduction to FastAPI
1.1 What is FastAPI?
1.2 Advantages of FastAPI
1.3 FastAPI vs Other Frameworks
1.4 Installation and Setup
2 Core Concepts
2.1 Asynchronous Programming in Python
2.2 Understanding Pydantic Models
2.3 Dependency Injection
2.4 Routing and Path Operations
2.5 Request and Response Models
3 Building APIs with FastAPI
3.1 Creating a Basic API
3.2 Handling GET Requests
3.3 Handling POST Requests
3.4 Handling PUT and DELETE Requests
3.5 Query Parameters and Path Parameters
3.6 Request Body and JSON Data
3.7 File Uploads
4 Advanced Features
4.1 Authentication and Authorization
4.2 Middleware
4.3 Background Tasks
4.4 WebSockets
4.5 CORS (Cross-Origin Resource Sharing)
4.6 Custom Exception Handling
5 Database Integration
5.1 Connecting to a Database
5.2 ORM Integration (SQLAlchemy)
5.3 CRUD Operations with FastAPI
5.4 Database Migrations
5.5 Handling Relationships
6 Testing and Debugging
6.1 Writing Unit Tests
6.2 Using TestClient for Integration Tests
6.3 Debugging Techniques
6.4 Logging and Monitoring
7 Deployment
7.1 Deploying FastAPI with Uvicorn
7.2 Dockerizing FastAPI Applications
7.3 Deploying to Cloud Platforms (AWS, GCP, Azure)
7.4 Continuous Integration and Continuous Deployment (CICD)
8 Best Practices
8.1 Code Organization and Structure
8.2 Security Best Practices
8.3 Performance Optimization
8.4 Documentation and OpenAPI
8.5 Versioning APIs
9 Case Studies and Projects
9.1 Building a RESTful API
9.2 Implementing a CRUD Application
9.3 Real-World Project Example
9.4 Collaborative Project with Team
10 Exam Preparation
10.1 Overview of Exam Structure
10.2 Sample Questions and Answers
10.3 Practice Exercises
10.4 Mock Exam Simulation
Building a RESTful API with FastAPI

Building a RESTful API with FastAPI

Key Concepts

Building a RESTful API with FastAPI involves several key concepts:

Explaining Each Concept

1. HTTP Methods

HTTP methods define the type of operation to be performed on a resource. Common methods include:

Example:

from fastapi import FastAPI

app = FastAPI()

@app.get("/items/{item_id}")
def read_item(item_id: int):
    return {"item_id": item_id}

@app.post("/items/")
def create_item(item: dict):
    return {"item": item}

@app.put("/items/{item_id}")
def update_item(item_id: int, item: dict):
    return {"item_id": item_id, "updated_item": item}

@app.delete("/items/{item_id}")
def delete_item(item_id: int):
    return {"item_id": item_id, "status": "deleted"}
    

2. Endpoints

Endpoints are URLs that map to specific resources. They define the location of the resource and the operation to be performed.

Example:

@app.get("/items/{item_id}")
def read_item(item_id: int):
    return {"item_id": item_id}
    

3. Resource Representation

Resources are typically represented in JSON format. FastAPI automatically converts Python dictionaries to JSON.

Example:

@app.get("/items/{item_id}")
def read_item(item_id: int):
    return {"item_id": item_id, "name": "Sample Item"}
    

4. Status Codes

HTTP status codes indicate the result of an operation. Common codes include:

Example:

from fastapi import FastAPI, HTTPException

app = FastAPI()

@app.get("/items/{item_id}")
def read_item(item_id: int):
    if item_id < 0:
        raise HTTPException(status_code=400, detail="Item ID must be positive")
    return {"item_id": item_id}
    

5. Query Parameters and Path Parameters

Query parameters are appended to the URL and are used to filter or sort data. Path parameters are part of the URL path and are used to identify a specific resource.

Example:

@app.get("/items/")
def read_items(q: str = None):
    return {"q": q}

@app.get("/items/{item_id}")
def read_item(item_id: int):
    return {"item_id": item_id}
    

6. Request Body

The request body is used to send complex data structures to the API, typically in JSON format.

Example:

from pydantic import BaseModel

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

@app.post("/items/")
def create_item(item: Item):
    return {"item": item}
    

7. Response Formatting

Response formatting ensures that the data is structured in a way that is easily consumable by clients.

Example:

@app.get("/items/{item_id}")
def read_item(item_id: int):
    return {"item_id": item_id, "name": "Sample Item", "price": 9.99}
    

8. Error Handling

Error handling involves managing exceptions and providing meaningful error messages to clients.

Example:

from fastapi import FastAPI, HTTPException

app = FastAPI()

@app.get("/items/{item_id}")
def read_item(item_id: int):
    if item_id < 0:
        raise HTTPException(status_code=400, detail="Item ID must be positive")
    return {"item_id": item_id}
    

9. Documentation

API documentation helps users understand how to interact with the API. FastAPI automatically generates documentation using OpenAPI.

Example:

from fastapi import FastAPI

app = FastAPI()

@app.get("/items/{item_id}")
def read_item(item_id: int):
    """
    Retrieve an item by its ID.

    - **item_id**: The ID of the item to retrieve.
    """
    return {"item_id": item_id}
    

Analogies

Think of building a RESTful API as creating a library catalog system. HTTP methods are like the actions you can perform (borrow, return, update, delete books). Endpoints are like the sections of the library (fiction, non-fiction). Resource representation is like the book's metadata (title, author, ISBN). Status codes are like the librarian's responses (book found, book not found). Query parameters and path parameters are like the search filters (by author, by genre). The request body is like the book request form. Response formatting is like organizing the returned book list. Error handling is like the librarian's guidance when you make a mistake. Documentation is like the library's user manual.

By mastering these concepts, you can effectively build a RESTful API with FastAPI, ensuring it is robust, maintainable, and easy to use.