# Body - Campos { #body-fields }

De la misma manera que puedes declarar validaciones adicionales y metadatos en los parámetros de las *path operation function* con `Query`, `Path` y `Body`, puedes declarar validaciones y metadatos dentro de los modelos de Pydantic usando `Field` de Pydantic.

## Importar `Field` { #import-field }

Primero, tienes que importarlo:

{* ../../docs_src/body_fields/tutorial001_an_py310.py hl[4] *}

/// warning | Advertencia

    dict[str, dict[str, Any]],
]:
    schema_generator = GenerateJsonSchema(ref_template=REF_TEMPLATE)
    validation_fields = [field for field in fields if field.mode == "validation"]
    serialization_fields = [field for field in fields if field.mode == "serialization"]
    flat_validation_models = get_flat_models_from_fields(
        validation_fields, known_models=set()
    )

Mehr erfahren Sie am Ende dieser Seite.

///

## Zusätzliche Argumente für `Field` { #field-additional-arguments }

Wenn Sie `Field()` mit Pydantic-Modellen verwenden, können Sie ebenfalls zusätzliche `examples` deklarieren:

{* ../../docs_src/schema_extra_example/tutorial002_py310.py hl[2,8:11] *}

# Additional highlighted fields for queries.
query.additional.highlighted.fields=
# Additional search fields for queries.
query.additional.search.fields=
# Additional facet fields for queries.
query.additional.facet.fields=
# Additional sort fields for queries.
query.additional.sort.fields=
# Additional analyzed fields for queries.
query.additional.analyzed.fields=
# Additional not-analyzed fields for queries.

    return True


def _should_embed_body_fields(fields: list[ModelField]) -> bool:
    if not fields:
        return False
    # More than one dependency could have the same field, it would show up as multiple
    # fields but it's the same one, so count them by name
    body_param_names_set = {field.name for field in fields}
    # A top level field has to be a single field, not multiple
    if len(body_param_names_set) > 1:

            {
                "type": "missing",
                "loc": ["body", "name"],
                "msg": "Field required",
                "input": {},
            },
            {
                "type": "missing",
                "loc": ["body", "price"],
                "msg": "Field required",
                "input": {},
            },
        ]
    }

    return set(re.findall("{(.*?)}", path))


_invalid_args_message = (
    "Invalid args for response field! Hint: "
    "check that {type_} is a valid Pydantic field type. "
    "If you are using a return type annotation that is not a valid Pydantic "
    "field (e.g. Union[Response, dict, None]) you can disable generating the "
    "response model from the type annotation with the path operation decorator "

    /** Mapping type for array fields. */
    public static final String MAPPING_TYPE_ARRAY = "array";

    /** Mapping type for string fields. */
    public static final String MAPPING_TYPE_STRING = "string";

    /** Mapping type for long fields. */
    public static final String MAPPING_TYPE_LONG = "long";

    /** Mapping type for double fields. */

    # Core Vocabulary
    schema_: Optional[str] = Field(default=None, alias="$schema")
    vocabulary: Optional[str] = Field(default=None, alias="$vocabulary")
    id: Optional[str] = Field(default=None, alias="$id")
    anchor: Optional[str] = Field(default=None, alias="$anchor")
    dynamicAnchor: Optional[str] = Field(default=None, alias="$dynamicAnchor")
    ref: Optional[str] = Field(default=None, alias="$ref")

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

### Model for Output Response Data { #model-for-output-response-data }

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`):

<div class="screenshot">