"required": ["ok"],
                        "type": "object",
                        "properties": {"ok": {"title": "Ok", "type": "boolean"}},
                    },
                    "ValidationError": {
                        "title": "ValidationError",
                        "required": ["loc", "msg", "type"],
                        "type": "object",
                        "properties": {

```Python hl_lines="2  14"
{!../../../docs_src/custom_response/tutorial007.py!}
```

#### Using `StreamingResponse` with file-like objects

If you have a file-like object (e.g. the object returned by `open()`), you can create a generator function to iterate over that file-like object.

That way, you don't have to read it all first in memory, and you can pass that generator function to the `StreamingResponse`, and return it.

                        # TODO: remove when deprecating Pydantic v1
                        ["username"],
                    ),
                    "type": "object",
                    "properties": {
                        "username": {"title": "Username", "type": "string"},
                        "email": IsDict(
                            {

    * une validation même pour les objets <abbr title="JavaScript Object Notation">JSON</abbr> profondément imbriqués.
* <abbr title="aussi connu sous le nom de : serialization, parsing, marshalling">Une conversion</abbr> des données d'entrée : venant du réseau et allant vers les données et types de Python, permettant de lire :
    * le <abbr title="JavaScript Object Notation">JSON</abbr>.

            "schemas": {
                "Body_login_login_post": {
                    "title": "Body_login_login_post",
                    "required": ["grant_type", "username", "password"],
                    "type": "object",
                    "properties": {
                        "grant_type": {
                            "title": "Grant Type",
                            "pattern": "password",

            },
        },
        "components": {
            "schemas": {
                "Item": {
                    "title": "Item",
                    "required": ["name"],
                    "type": "object",
                    "properties": {
                        "name": {"title": "Name", "type": "string"},
                        "price": IsDict(
                            {

### Create a `PeeweeGetterDict` for the Pydantic *models* / schemas

When you access a relationship in a Peewee object, like in `some_user.items`, Peewee doesn't provide a `list` of `Item`.

It provides a special custom object of class `ModelSelect`.

It's possible to create a `list` of its items with `list(some_user.items)`.

    writeOnly: Optional[bool] = None
    examples: Optional[List[Any]] = None
    # Ref: OpenAPI 3.1.0: https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.1.0.md#schema-object
    # Schema Object
    discriminator: Optional[Discriminator] = None
    xml: Optional[XML] = None
    externalDocs: Optional[ExternalDocumentation] = None
    example: Annotated[
        Optional[Any],

            },
        },
        "components": {
            "schemas": {
                "HTTPValidationError": {
                    "title": "HTTPValidationError",
                    "type": "object",
                    "properties": {
                        "detail": {
                            "title": "Detail",
                            "type": "array",

Wliczając w to zewnętrzne biblioteki, również oparte o Pydantic, takie jak <abbr title="Mapowanie obiektowo-relacyjne. Po angielsku: Object-Relational Mapper">ORM</abbr>, <abbr title="Object-Document Mapper">ODM</abbr> dla baz danych.