And Swagger UI has supported this particular `examples` field for a while. So, you can use it to **show** different **examples in the docs UI**.

The shape of this OpenAPI-specific field `examples` is a `dict` with **multiple examples** (instead of a `list`), each with extra information that will be added to **OpenAPI** too.

This schema definition includes your API paths, the possible parameters they take, etc.

#### Data "schema" { #data-schema }

The term "schema" might also refer to the shape of some data, like a JSON content.

In that case, it would mean the JSON attributes, and data types they have, etc.

#### OpenAPI and JSON Schema { #openapi-and-json-schema }

* Add a **JSON Schema** for the response, in the OpenAPI *path operation*.
    * This will be used by the **automatic docs**.
    * It will also be used by automatic client code generation tools.

{* ../../docs_src/dependencies/tutorial007_py39.py hl[3,5] *}

## Sub-dependencies with `yield` { #sub-dependencies-with-yield }

You can have sub-dependencies and "trees" of sub-dependencies of any size and shape, and any or all of them can use `yield`.

**FastAPI** will make sure that the "exit code" in each dependency with `yield` is run in the correct order.

{* ../../docs_src/security/tutorial005_an_py310.py hl[106,108:116] *}

## Verificar el `username` y la forma de los datos { #verify-the-username-and-data-shape }

Verificamos que obtenemos un `username`, y extraemos los scopes.

For example, if you declare a parameter of type `Hero`, it will be read from the **JSON body**.

The same way, you can declare it as the function's **return type**, and then the shape of the data will show up in the automatic API docs UI.

{* ../../docs_src/sql_databases/tutorial001_an_py310.py ln[40:45] hl[40:45] *}

## Pydantic models { #pydantic-models }

<a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a> is a Python library to perform data validation.

You declare the "shape" of the data as classes with attributes.

And each attribute has a type.

                or is_scalar_sequence_field(field)
                or (
                    lenient_issubclass(field.type_, BaseModel)
                    # For Pydantic v1
                    and getattr(field, "shape", 1) == 1
                )
            )

    return ParamDetails(type_annotation=type_annotation, depends=depends, field=field)


def add_param_to_fields(*, field: ModelField, dependant: Dependant) -> None: