Learn FastAPI: A Comprehensive Python Framework Tutorial

FastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.6+ based on standard Python type hints. It is built on top of Starlette for the web parts and Pydantic for data validation and serialization.

In this tutorial, we will cover the basics of FastAPI and how to build an API using this framework. We will explore the various features of FastAPI, including request handling, response handling, parameter validation, dependency injection, and more.

Prerequisites:

1. Basic knowledge of Python
2. Basic understanding of APIs

Let’s get started with our FastAPI tutorial:

1. Installation:
   First, you need to install FastAPI and Uvicorn, which is a lightning-fast ASGI server:

   pip install fastapi uvicorn

2. Create a basic app:
   Create a new Python file e.g., main.py, and import FastAPI:

   
   from fastapi import FastAPI

app = FastAPI()

3. Running the app:
You can run the app using Uvicorn:
```bash
uvicorn main:app --reload

This command starts the app on http://localhost:8000.

1. Building endpoints:
   Now, let’s build some endpoints in our app:

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

@app.get("/items/{item_id}")
def read_item(item_id: int, q: str = None):
return {"item_id": item_id, "q": q}

In the above code, we have defined two endpoints - one at the root path `/` and another at `/items/{item_id}` where `item_id` is a path parameter and `q` is a query parameter.

5. Request and response handling:
FastAPI automatically handles request and response serialization based on the data type hints specified in the function signature. For example, in the `read_item` function, FastAPI will automatically convert the return dictionary to JSON.

6. Parameter validation:
FastAPI supports automatic request validation using Pydantic models. You can define request and response models like:
```python
from pydantic import BaseModel

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

And then use these models in your endpoints:

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

FastAPI will automatically validate the incoming request JSON against the Item model.

1. Dependency injection:
   FastAPI supports dependency injection, allowing you to inject dependencies into your endpoint functions. For example, you can inject a database connection or a service object:

   
   from fastapi import Depends

async def get_db():
db = DBConnection()
try:
yield db
finally:
db.close()

@app.get("/items/")
async def read_items(db: DBConnection = Depends(get_db)):
items = db.get_items()
return items

8. API documentation:
FastAPI automatically generates interactive API documentation using Swagger UI. You can access the documentation at `http://localhost:8000/docs`.

9. Middleware:
FastAPI supports middleware for intercepting and modifying requests and responses. You can define middleware functions that can modify the request or response before it reaches the endpoint handler.

10. Background tasks:
FastAPI supports background tasks that can run asynchronously in the background. You can define background tasks to be executed after a request is processed.

This concludes our FastAPI tutorial. FastAPI is a powerful and modern web framework for building APIs with Python. It offers a lot of features out of the box and is very easy to use. I hope this tutorial has helped you get started with FastAPI. Happy coding!