Fastapi Python Complete Tutorial: Request Body and Pydantic Model

Welcome to the ninth tutorial in our Fastapi Python Complete Tutorial series. In this tutorial, we will be covering the Request Body and Pydantic Model in Fastapi.

What is a Request Body?

In Fastapi, a Request Body is the data that is sent from the client to the server in an HTTP request. This data can be in the form of JSON, form data, files, etc. Fastapi provides a straightforward way to work with request bodies using Pydantic models.

What is Pydantic?

Pydantic is a data validation and settings management library in Python. It provides a way to define the structure of the data using Python classes and ensures that the data adheres to those structures. Fastapi integrates seamlessly with Pydantic, allowing you to define the request body structure using Pydantic models.

Using Pydantic Model in Fastapi

When working with request bodies in Fastapi, you can define the structure of the request body using Pydantic models. Here’s an example of how you can do this:

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()

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

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

In this example, we have defined a Pydantic model called Item, which has two fields – name and price. We then use this model as the type for the request body of the create_item endpoint. Fastapi will automatically validate the incoming request body against the Item model and deserialize it into an Item object.

Conclusion

Working with request bodies in Fastapi is made easy and reliable by using Pydantic models. By defining the structure of the request body using Pydantic models, you can ensure that the data is validated and properly serialized/deserialized. This makes handling request bodies in Fastapi a breeze.

That’s all for this tutorial! Stay tuned for more in our Fastapi Python Complete Tutorial series.