jobs:
  test:
    strategy:
      matrix:
        os: [ windows-latest, macos-latest ]
        python-version: [ "3.14" ]
        include:
          - os: ubuntu-latest
            python-version: "3.9"
            coverage: coverage
          - os: macos-latest
            python-version: "3.10"
            coverage: coverage
          - os: windows-latest
            python-version: "3.12"
            coverage: coverage

    out_path.parent.mkdir(parents=True, exist_ok=True)
    original_content = en_path.read_text(encoding="utf-8")
    old_translation: str | None = None
    if out_path.exists():
        print(f"Found existing translation: {out_path}")
        old_translation = out_path.read_text(encoding="utf-8")
    print(f"Translating {en_path} to {language} ({language_name})")
    agent = Agent("openai:gpt-5.2")

{* ../../docs_src/dataclasses_/tutorial001_py310.py hl[1,6:11,18:19] *}

Isso ainda é suportado graças ao **Pydantic**, pois ele tem <a href="https://docs.pydantic.dev/latest/concepts/dataclasses/#use-of-stdlib-dataclasses-with-basemodel" class="external-link" target="_blank">suporte interno para `dataclasses`</a>.

{* ../../docs_src/dataclasses_/tutorial001_py310.py hl[1,6:11,18:19] *}

Esto sigue siendo soportado gracias a **Pydantic**, ya que tiene <a href="https://docs.pydantic.dev/latest/concepts/dataclasses/#use-of-stdlib-dataclasses-with-basemodel" class="external-link" target="_blank">soporte interno para `dataclasses`</a>.

There are some additional dependencies you might want to install.

Additional optional Pydantic dependencies:

* <a href="https://docs.pydantic.dev/latest/usage/pydantic_settings/" target="_blank"><code>pydantic-settings</code></a> - for settings management.
* <a href="https://docs.pydantic.dev/latest/usage/types/extra_types/extra_types/" target="_blank"><code>pydantic-extra-types</code></a> - for extra types to be used with Pydantic.

        type: string
        required: false
        default: ""

env:
  UV_SYSTEM_PYTHON: 1

jobs:
  langs:
    runs-on: ubuntu-latest
    outputs:
      langs: ${{ steps.show-langs.outputs.langs }}
      commands: ${{ steps.show-langs.outputs.commands }}
    steps:
      - uses: actions/checkout@v6
      - name: Set up Python

    types:
      - opened
      - synchronize

env:
  # Forks and Dependabot don't have access to secrets
  HAS_SECRETS: ${{ secrets.PRE_COMMIT != '' }}

jobs:
  pre-commit:
    runs-on: ubuntu-latest
    steps:
      - name: Dump GitHub context
        env:
          GITHUB_CONTEXT: ${{ toJson(github) }}
        run: echo "$GITHUB_CONTEXT"
      - uses: actions/checkout@v5
        name: Checkout PR for own repo

Als Nächstes werden die Daten konvertiert und validiert. Wenn Sie also dieses `settings`-Objekt verwenden, verfügen Sie über Daten mit den von Ihnen deklarierten Typen (z. B. ist `items_per_user` ein `int`).

### `settings` verwenden { #use-the-settings }

# Verwendung von Datenklassen { #using-dataclasses }

FastAPI basiert auf **Pydantic**, und ich habe Ihnen gezeigt, wie Sie Pydantic-Modelle verwenden können, um <abbr title="Request – Anfrage: Daten, die der Client zum Server sendet">Requests</abbr> und <abbr title="Response – Antwort: Daten, die der Server zum anfragenden Client zurücksendet">Responses</abbr> zu deklarieren.

{* ../../docs_src/dataclasses_/tutorial001_py310.py hl[1,6:11,18:19] *}

This is still supported thanks to **Pydantic**, as it has <a href="https://docs.pydantic.dev/latest/concepts/dataclasses/#use-of-stdlib-dataclasses-with-basemodel" class="external-link" target="_blank">internal support for `dataclasses`</a>.