FastAPI Basics

What is FastAPI?

FastAPI is a modern, high-performance web framework for building APIs with Python 3.7+ based on standard Python type hints. It is designed to be easy to use, fast (as the name suggests), and highly efficient. FastAPI is built on top of Starlette for the web parts and Pydantic for data validation and settings management.

What are the main features of FastAPI?

The main features of FastAPI include:

• High Performance: FastAPI is one of the fastest Python web frameworks available, comparable to Node.js and Go.
• Automatic Data Validation: It uses Python type hints and Pydantic for data validation and serialization.
• Easy to Learn and Use: FastAPI has a simple, intuitive API that makes it easy to create APIs quickly.
• Asynchronous Support: FastAPI is designed with async support, enabling efficient handling of concurrent requests.
• Interactive API Documentation: It provides automatic, interactive API documentation using Swagger UI and ReDoc.

How do you install FastAPI?

You can install FastAPI using the pip package manager. Additionally, you'll need an ASGI server like uvicorn to run your FastAPI application.

Example of installing FastAPI and Uvicorn:

pip install fastapi uvicorn

How do you create a basic FastAPI application?

Creating a basic FastAPI application involves defining routes, which handle specific HTTP requests (GET, POST, etc.), and running the app using an ASGI server like Uvicorn.

Example of a basic FastAPI app:

from fastapi import FastAPI

app = FastAPI()

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

if __name__ == "__main__":
    import uvicorn
    uvicorn.run(app, host="0.0.0.0", port=8000)

In this example, the FastAPI application defines a single route / that responds with a JSON object. You can run the application using Uvicorn, which will start the FastAPI app on http://localhost:8000.

What are path parameters in FastAPI?

Path parameters in FastAPI allow you to capture dynamic values from the URL path. You can define these parameters by including them in the URL path within curly braces {}, and they will be passed as function arguments to the route handler.

Example of using path parameters:

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

In this example, item_id is a path parameter, and it is passed to the read_item function when accessing a URL like /items/5.

How do you handle query parameters in FastAPI?

Query parameters in FastAPI are used to pass additional data in the URL as key-value pairs after the ? symbol. They are optional and can be accessed in the route handler by defining them as function parameters.

Example of using query parameters:

@app.get("/items/")
def read_item(skip: int = 0, limit: int = 10):
    return {"skip": skip, "limit": limit}

In this example, skip and limit are query parameters. You can access the URL like /items/?skip=0&limit=10 to pass values for these parameters.

How do you handle request bodies in FastAPI?

FastAPI uses Pydantic models to define and validate request bodies. You can define a Pydantic model to specify the expected structure and types of data in the request body.

Example of handling request bodies:

from pydantic import BaseModel

class Item(BaseModel):
    name: str
    price: float

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

In this example, the Item model defines the expected structure for the request body, with fields name and price. The route /items/ accepts POST requests with a JSON body that matches the Item model.

How do you document APIs in FastAPI?

FastAPI automatically generates interactive API documentation based on the defined routes and data models. You can access the documentation by visiting /docs (Swagger UI) or /redoc (ReDoc) after running the FastAPI app.

Example of accessing API documentation:

http://localhost:8000/docs

Swagger UI provides an interactive API explorer that allows you to test your API directly from the browser, while ReDoc offers a static, comprehensive documentation view.

What are the advantages of using FastAPI for asynchronous programming?

FastAPI is designed with asynchronous programming in mind, making it ideal for handling I/O-bound operations like database queries, file handling, and network requests. You can define asynchronous routes using the async def syntax, which allows the application to handle multiple requests concurrently without blocking.

Example of an asynchronous route:

@app.get("/async/")
async def async_endpoint():
    await some_async_function()
    return {"message": "This is an async endpoint"}

In this example, async def is used to define an asynchronous route, and await is used to call asynchronous functions. This improves performance for tasks like database queries, file I/O, or API calls that involve waiting for external resources.

How do you run FastAPI applications?

FastAPI applications are typically run using an ASGI server like Uvicorn, which is designed for handling asynchronous applications. Uvicorn can be used to start your FastAPI application and handle HTTP requests.

Example of running a FastAPI app using Uvicorn:

uvicorn main:app --reload

In this example, the FastAPI app defined in the main.py file is started with live-reloading enabled using the --reload flag. The app will automatically restart when changes are detected in the code.