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Separate OpenAPI Schemas for Input and Output (or not)

When using Pydantic v2, the generated OpenAPI is a bit more exact and correct than before. 😎

In fact, in some cases, it will even have two JSON Schemas in OpenAPI for the same Pydantic model, for input and output, depending on if they have default values.

Let's see how that works and how to change it if you need to do that.

Pydantic Models for Input and Output

Let's say you have a Pydantic model with default values, like this one:

from fastapi import FastAPI
from pydantic import BaseModel


class Item(BaseModel):
    name: str
    description: str | None = None

# Code below omitted 👇

👀 Full file preview

from fastapi import FastAPI
from pydantic import BaseModel


class Item(BaseModel):
    name: str
    description: str | None = None


app = FastAPI()


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


@app.get("/items/")
def read_items() -> list[Item]:
    return [
        Item(
            name="Portal Gun",
            description="Device to travel through the multi-rick-verse",
        ),
        Item(name="Plumbus"),
    ]
from typing import Optional

from fastapi import FastAPI
from pydantic import BaseModel


class Item(BaseModel):
    name: str
    description: Optional[str] = None

# Code below omitted 👇

👀 Full file preview

from typing import Optional

from fastapi import FastAPI
from pydantic import BaseModel


class Item(BaseModel):
    name: str
    description: Optional[str] = None


app = FastAPI()


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


@app.get("/items/")
def read_items() -> list[Item]:
    return [
        Item(
            name="Portal Gun",
            description="Device to travel through the multi-rick-verse",
        ),
        Item(name="Plumbus"),
    ]
from typing import List, Union

from fastapi import FastAPI
from pydantic import BaseModel


class Item(BaseModel):
    name: str
    description: Union[str, None] = None

# Code below omitted 👇

👀 Full file preview

from typing import List, Union

from fastapi import FastAPI
from pydantic import BaseModel


class Item(BaseModel):
    name: str
    description: Union[str, None] = None


app = FastAPI()


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


@app.get("/items/")
def read_items() -> List[Item]:
    return [
        Item(
            name="Portal Gun",
            description="Device to travel through the multi-rick-verse",
        ),
        Item(name="Plumbus"),
    ]

If you use this model as an input like here:

from fastapi import FastAPI
from pydantic import BaseModel


class Item(BaseModel):
    name: str
    description: str | None = None


app = FastAPI()


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

# Code below omitted 👇

👀 Full file preview

from fastapi import FastAPI
from pydantic import BaseModel


class Item(BaseModel):
    name: str
    description: str | None = None


app = FastAPI()


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


@app.get("/items/")
def read_items() -> list[Item]:
    return [
        Item(
            name="Portal Gun",
            description="Device to travel through the multi-rick-verse",
        ),
        Item(name="Plumbus"),
    ]
from typing import Optional

from fastapi import FastAPI
from pydantic import BaseModel


class Item(BaseModel):
    name: str
    description: Optional[str] = None


app = FastAPI()


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

# Code below omitted 👇

👀 Full file preview

from typing import Optional

from fastapi import FastAPI
from pydantic import BaseModel


class Item(BaseModel):
    name: str
    description: Optional[str] = None


app = FastAPI()


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


@app.get("/items/")
def read_items() -> list[Item]:
    return [
        Item(
            name="Portal Gun",
            description="Device to travel through the multi-rick-verse",
        ),
        Item(name="Plumbus"),
    ]
from typing import List, Union

from fastapi import FastAPI
from pydantic import BaseModel


class Item(BaseModel):
    name: str
    description: Union[str, None] = None


app = FastAPI()


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

# Code below omitted 👇

👀 Full file preview

from typing import List, Union

from fastapi import FastAPI
from pydantic import BaseModel


class Item(BaseModel):
    name: str
    description: Union[str, None] = None


app = FastAPI()


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


@app.get("/items/")
def read_items() -> List[Item]:
    return [
        Item(
            name="Portal Gun",
            description="Device to travel through the multi-rick-verse",
        ),
        Item(name="Plumbus"),
    ]

...then the description field will not be required. Because it has a default value of None.

You can confirm that in the docs:

But if you use the same model as an output, like here:

from fastapi import FastAPI
from pydantic import BaseModel


class Item(BaseModel):
    name: str
    description: str | None = None


app = FastAPI()


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


@app.get("/items/")
def read_items() -> list[Item]:
    return [
        Item(
            name="Portal Gun",
            description="Device to travel through the multi-rick-verse",
        ),
        Item(name="Plumbus"),
    ]
from typing import Optional

from fastapi import FastAPI
from pydantic import BaseModel


class Item(BaseModel):
    name: str
    description: Optional[str] = None


app = FastAPI()


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


@app.get("/items/")
def read_items() -> list[Item]:
    return [
        Item(
            name="Portal Gun",
            description="Device to travel through the multi-rick-verse",
        ),
        Item(name="Plumbus"),
    ]
from typing import List, Union

from fastapi import FastAPI
from pydantic import BaseModel


class Item(BaseModel):
    name: str
    description: Union[str, None] = None


app = FastAPI()


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


@app.get("/items/")
def read_items() -> List[Item]:
    return [
        Item(
            name="Portal Gun",
            description="Device to travel through the multi-rick-verse",
        ),
        Item(name="Plumbus"),
    ]

...then because description has a default value, if you don't return anything for that field, it will still have that default value.

If you interact with the docs and check the response, even though the code didn't add anything in one of the description fields, the JSON response contains the default value (null):

This means that it will always have a value, it's just that sometimes the value could be None (or null in the JSON output).

That means that, clients using your API don't have to check if the value exists or not, they can asume the field will always be there, but just that in some cases it will have the default value of None.

The way to describe this in OpenAPI, is to mark that field as required, because it will always be there.

Because of that, the JSON Schema for a model can be different depending on if it's used for input or output, for input the description will not be required, for output it will be required (and possibly None, or in JSON terms, null).

You can check the output model in the docs too:

With this feature from Pydantic v2, your API documentation is more precise, and if you have autogenerated clients and SDKs, they will be more precise too, with a better developer experience and consistency. 🎉

Do not Separate Schemas

Now, there are some cases where you might want to have the same schema for input and output.

Probably the main use case for this is if you already have some autogenerated client code/SDKs and you don't want to update all the autogenerated client code/SDKs yet, you probably will want to do it at some point, but maybe not right now.

In that case, you can disable this feature in FastAPI, with the parameter separate_input_output_schemas=False.

from fastapi import FastAPI
from pydantic import BaseModel


class Item(BaseModel):
    name: str
    description: str | None = None


app = FastAPI(separate_input_output_schemas=False)


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


@app.get("/items/")
def read_items() -> list[Item]:
    return [
        Item(
            name="Portal Gun",
            description="Device to travel through the multi-rick-verse",
        ),
        Item(name="Plumbus"),
    ]
from typing import Optional

from fastapi import FastAPI
from pydantic import BaseModel


class Item(BaseModel):
    name: str
    description: Optional[str] = None


app = FastAPI(separate_input_output_schemas=False)


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


@app.get("/items/")
def read_items() -> list[Item]:
    return [
        Item(
            name="Portal Gun",
            description="Device to travel through the multi-rick-verse",
        ),
        Item(name="Plumbus"),
    ]
from typing import List, Union

from fastapi import FastAPI
from pydantic import BaseModel


class Item(BaseModel):
    name: str
    description: Union[str, None] = None


app = FastAPI(separate_input_output_schemas=False)


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


@app.get("/items/")
def read_items() -> List[Item]:
    return [
        Item(
            name="Portal Gun",
            description="Device to travel through the multi-rick-verse",
        ),
        Item(name="Plumbus"),
    ]

And now there will be one single schema for input and output for each model: