### Type Annotations and Tooling

First let's see how editors, mypy and other tools would see this.

`BaseUser` has the base fields. Then `UserIn` inherits from `BaseUser` and adds the `password` field, so, it will include all the fields from both models.

We annotate the function return type as `BaseUser`, but we are actually returning a `UserIn` instance.

    }

    /**
     * <code>public</code>かどうか返します。
     *
     * @param field
     *            フィールド。{@literal null}であってはいけません
     * @return パブリックかどうか
     */
    public static boolean isPublic(final Field field) {
        assertArgumentNotNull("field", field);

        return isPublic(field.getModifiers());
    }

    /**
     * <code>public</code>,<code>static</code>,<code>final</code>かどうか返します。

                    "type": "missing",
                    "loc": ["body", "file"],
                    "msg": "Field required",
                    "input": None,
                },
                {
                    "type": "missing",
                    "loc": ["body", "fileb"],
                    "msg": "Field required",
                    "input": None,
                },
                {

            if (fieldSet.contains(CLUSTER_NAME)) {
                builder.field(CLUSTER_NAME, response.getClusterName());
            }
            if (fieldSet.contains(STATUS)) {
                builder.field(STATUS, response.getStatus().name().toLowerCase(Locale.ROOT));
            }
            if (fieldSet.contains(TIMED_OUT)) {
                builder.field(TIMED_OUT, response.isTimedOut());
            }

////

For example, in one of the ways the OAuth2 specification can be used (called "password flow") it is required to send a `username` and `password` as form fields.

The <abbr title="specification">spec</abbr> requires the fields to be exactly named `username` and `password`, and to be sent as form fields, not JSON.

Por exemplo, você pode usar isso para adicionar metadados para uma interface de usuário de front-end, etc.

///

## `Field` de argumentos adicionais

Ao usar `Field ()` com modelos Pydantic, você também pode declarar informações extras para o **JSON Schema** passando quaisquer outros argumentos arbitrários para a função.

func (z *ActiveWorkerStat) DecodeMsg(dc *msgp.Reader) (err error) {
	var field []byte
	_ = field
	var zb0001 uint32
	zb0001, err = dc.ReadMapHeader()
	if err != nil {
		err = msgp.WrapError(err)
		return
	}
	for zb0001 > 0 {
		zb0001--
		field, err = dc.ReadMapKeyPtr()
		if err != nil {
			err = msgp.WrapError(err)
			return
		}
		switch msgp.UnsafeString(field) {
		case "Curr":
			z.Curr, err = dc.ReadInt()

                    "loc": ["query", "q"],
                    "msg": "Field required",
                    "input": None,
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {
            "detail": [
                {
                    "loc": ["query", "q"],
                    "msg": "field required",
                    "type": "value_error.missing",

        builder.startObject();
        if (sessionId != null) {
            builder.field(SESSION_ID, sessionId);
        }
        if (ruleId != null) {
            builder.field(RULE_ID, ruleId);
        }
        if (url != null) {
            builder.field(URL, url);
        }
        if (parentUrl != null) {
            builder.field(PARENT_URL, parentUrl);
        }
        if (status != null) {

                    "msg": "Field required",
                    "input": {"username": "Foo"},
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {
            "detail": [
                {
                    "loc": ["body", "password"],
                    "msg": "field required",
                    "type": "value_error.missing",