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
FastAPI Training: Core Concepts

FastAPI Training: Core Concepts

1. Dependency Injection

Dependency Injection is a design pattern used in FastAPI to manage and inject dependencies into your endpoints. This pattern helps in decoupling the components of your application, making it easier to test and maintain.

Imagine you are building a library management system where each book needs to be checked for availability before being issued. Instead of writing the availability check logic directly within each endpoint, you can create a dependency that handles this check. This way, the logic is centralized and can be reused across multiple endpoints.

Here is an example of how to use dependency injection in FastAPI:

from fastapi import Depends, FastAPI

app = FastAPI()

class BookChecker:
    def is_available(self, book_id: int):
        # Logic to check book availability
        return True

def get_book_checker():
    return BookChecker()

@app.get("/issue_book/{book_id}")
def issue_book(book_id: int, book_checker: BookChecker = Depends(get_book_checker)):
    if book_checker.is_available(book_id):
        return {"message": "Book is available and issued"}
    return {"message": "Book is not available"}
    

In this example, the get_book_checker function returns an instance of BookChecker, which is then injected into the issue_book endpoint using the Depends function. This ensures that the availability check logic is reusable and centralized.

2. Path Parameters and Query Parameters

Path Parameters and Query Parameters are essential components in defining the structure and behavior of your API endpoints. Path parameters are used to capture values from the URL path, while query parameters are used to capture values from the query string.

Consider a scenario where you are building a weather API. The path parameter could be used to specify the city for which the weather information is requested, while the query parameter could be used to specify additional details like the date range.

Here is an example of how to use path and query parameters in FastAPI:

from fastapi import FastAPI

app = FastAPI()

@app.get("/weather/{city}")
def get_weather(city: str, start_date: str = None, end_date: str = None):
    weather_data = {
        "city": city,
        "start_date": start_date,
        "end_date": end_date,
        "temperature": "25°C",
        "conditions": "Sunny"
    }
    return weather_data
    

In this example, the city is a path parameter that captures the city name from the URL. The start_date and end_date are query parameters that capture additional information from the query string. This allows users to request weather data for a specific city and optionally specify a date range.