Return a Response Directly¶
When you create a FastAPI path operation you can normally return any data from it: a dict, a list, a Pydantic model, a database model, etc.
If you declare a Response Model FastAPI will use it to serialize the data to JSON, using Pydantic.
If you don't declare a response model, FastAPI will use the jsonable_encoder explained in JSON Compatible Encoder and put it in a JSONResponse.
You could also create a JSONResponse directly and return it.
Tip
You will normally have much better performance using a Response Model than returning a JSONResponse directly, as that way it serializes the data using Pydantic, in Rust.
Return a Response¶
You can return any Response or any sub-class of it.
Info
JSONResponse itself is a sub-class of Response.
And when you return a Response, FastAPI will pass it directly.
It won't do any data conversion with Pydantic models, it won't convert the contents to any type, etc.
This gives you a lot of flexibility. You can return any data type, override any data declaration or validation, etc.
Using the jsonable_encoder in a Response¶
Because FastAPI doesn't make any changes to a Response you return, you have to make sure its contents are ready for it.
For example, you cannot put a Pydantic model in a JSONResponse without first converting it to a dict with all the data types (like datetime, UUID, etc) converted to JSON-compatible types.
For those cases, you can use the jsonable_encoder to convert your data before passing it to a response:
from datetime import datetime
from fastapi import FastAPI
from fastapi.encoders import jsonable_encoder
from fastapi.responses import JSONResponse
from pydantic import BaseModel
class Item(BaseModel):
title: str
timestamp: datetime
description: str | None = None
app = FastAPI()
@app.put("/items/{id}")
def update_item(id: str, item: Item):
json_compatible_item_data = jsonable_encoder(item)
return JSONResponse(content=json_compatible_item_data)
Technical Details
You could also use from starlette.responses import JSONResponse.
FastAPI provides the same starlette.responses as fastapi.responses just as a convenience for you, the developer. But most of the available responses come directly from Starlette.
Returning a custom Response¶
The example above shows all the parts you need, but it's not very useful yet, as you could have just returned the item directly, and FastAPI would put it in a JSONResponse for you, converting it to a dict, etc. All that by default.
Now, let's see how you could use that to return a custom response.
Let's say that you want to return an XML response.
You could put your XML content in a string, put that in a Response, and return it:
from fastapi import FastAPI, Response
app = FastAPI()
@app.get("/legacy/")
def get_legacy_data():
data = """<?xml version="1.0"?>
<shampoo>
<Header>
Apply shampoo here.
</Header>
<Body>
You'll have to use soap here.
</Body>
</shampoo>
"""
return Response(content=data, media_type="application/xml")
How a Response Model Works¶
When you declare a Response Model in a path operation, FastAPI will use it to serialize the data to JSON, using Pydantic.
from fastapi import FastAPI
from pydantic import BaseModel
app = FastAPI()
class Item(BaseModel):
name: str
description: str | None = None
price: float
tax: float | None = None
tags: list[str] = []
@app.post("/items/")
async def create_item(item: Item) -> Item:
return item
@app.get("/items/")
async def read_items() -> list[Item]:
return [
Item(name="Portal Gun", price=42.0),
Item(name="Plumbus", price=32.0),
]
As that will happen on the Rust side, the performance will be much better than if it was done with regular Python and the JSONResponse class.
When using a response model FastAPI won't use the jsonable_encoder to convert the data (which would be slower) nor the JSONResponse class.
Instead it takes the JSON bytes generated with Pydantic using the response model and returns a Response with the right media type for JSON directly (application/json).
Notes¶
When you return a Response directly its data is not validated, converted (serialized), or documented automatically.
But you can still document it as described in Additional Responses in OpenAPI.
You can see in later sections how to use/declare these custom Responses while still having automatic data conversion, documentation, etc.