@lru_cache
def get_mkdocs_material_langs() -> list[str]:
    material_path = Path(material.__file__).parent
    material_langs_path = material_path / "templates" / "partials" / "languages"
    langs = [file.stem for file in material_langs_path.glob("*.html")]
    return langs


class EnFile(File):
    pass


def on_config(config: MkDocsConfig, **kwargs: Any) -> MkDocsConfig:

///

Como `stored_item_model.model_copy(update=update_data)`:

{* ../../docs_src/body_updates/tutorial002_py310.py hl[33] *}

### Resumen de actualizaciones parciales { #partial-updates-recap }

En resumen, para aplicar actualizaciones parciales deberías:

* (Opcionalmente) usar `PATCH` en lugar de `PUT`.
* Recuperar los datos almacenados.
* Poner esos datos en un modelo de Pydantic.

Like `stored_item_model.model_copy(update=update_data)`:

{* ../../docs_src/body_updates/tutorial002_py310.py hl[33] *}

### Partial updates recap { #partial-updates-recap }

In summary, to apply partial updates you would:

* (Optionally) use `PATCH` instead of `PUT`.
* Retrieve the stored data.
* Put that data in a Pydantic model.

@pytest.mark.parametrize(
    "route,value",
    [
        ("/partial-function-dependency", "partial-function-dependency"),
        (
            "/partial-async-function-dependency",
            "partial-async-function-dependency",
        ),
        ("/partial-gen-dependency", "partial-gen-dependency"),
        ("/partial-async-gen-dependency", "partial-async-gen-dependency"),
        ("/partial-callable-dependency", "partial-callable-dependency"),

Und die Daten würden mit diesem „neuen“ `tax` von `10.5` gespeichert werden.

## Teil-Aktualisierungen mit `PATCH` { #partial-updates-with-patch }

Sie können auch die <a href="https://developer.mozilla.org/en-US/docs/Web/HTTP/Methods/PATCH" class="external-link" target="_blank">HTTP `PATCH`</a> Operation verwenden, um Daten *teilweise* zu ersetzen.

import inspect
import sys
from dataclasses import dataclass, field
from functools import cached_property, partial
from typing import Any, Callable, Optional, Union

from fastapi._compat import ModelField
from fastapi.security.base import SecurityBase
from fastapi.types import DependencyCacheKey
from typing_extensions import Literal

if sys.version_info >= (3, 13):  # pragma: no cover
    from inspect import iscoroutinefunction

If you have an old FastAPI app, you might be using Pydantic version 1.

FastAPI version 0.100.0 had support for either Pydantic v1 or v2. It would use whichever you had installed.

FastAPI version 0.119.0 introduced partial support for Pydantic v1 from inside of Pydantic v2 (as `pydantic.v1`), to facilitate the migration to v2.

FastAPI 0.126.0 dropped support for Pydantic v1, while still supporting `pydantic.v1` for a little while.

/// warning

from fastapi import Depends, FastAPI, HTTPException

app = FastAPI()


data = {
    "plumbus": {"description": "Freshly pickled plumbus", "owner": "Morty"},
    "portal-gun": {"description": "Gun to create portals", "owner": "Rick"},
}


class OwnerError(Exception):
    pass


def get_username():
    try:
        yield "Rick"
    except OwnerError as e:
        raise HTTPException(status_code=400, detail=f"Owner error: {e}")

                throw new ExtractException("Failed to extract content from ZIP archive. No entries could be processed.", e);
            }
            if (logger.isWarnEnabled()) {
                logger.warn("Partial extraction from ZIP archive. Processed: {}, Failed: {}", processedEntries, failedEntries, e);
            }
        }

        return new ExtractData(buf.toString().trim());
    }

    /**

                throw new ExtractException("Failed to extract content from TAR archive. No entries could be processed.", e);
            }
            if (logger.isWarnEnabled()) {
                logger.warn("Partial extraction from TAR archive. Processed: {}, Failed: {}", processedEntries, failedEntries, e);
            }
        }

        return buf.toString().trim();
    }

    /**