bot-gradle <******@****.***> 1762783320 +0000

repos:
  - repo: https://github.com/pre-commit/pre-commit-hooks
    rev: v6.0.0
    hooks:
      - id: check-added-large-files
        args: ['--maxkb=750']
      - id: check-toml
      - id: check-yaml
        args:
        - --unsafe
      - id: end-of-file-fixer
      - id: trailing-whitespace

  - repo: local
    hooks:
      - id: local-ruff-check
        name: ruff check

    raw_body = await request.body()
    try:
        data = yaml.safe_load(raw_body)
    except yaml.YAMLError:
        raise HTTPException(status_code=422, detail="Invalid YAML")
    try:
        item = Item.parse_obj(data)
    except ValidationError as e:
        raise HTTPException(status_code=422, detail=e.errors())

    raw_body = await request.body()
    try:
        data = yaml.safe_load(raw_body)
    except yaml.YAMLError:
        raise HTTPException(status_code=422, detail="Invalid YAML")
    try:
        item = Item.model_validate(data)
    except ValidationError as e:
        raise HTTPException(status_code=422, detail=e.errors(include_url=False))

          sed -n '/^version:/,$p' .teamcity/jdks.yaml >> .teamcity/jdks.yaml.tmp
          mv .teamcity/jdks.yaml.tmp .teamcity/jdks.yaml
      - name: Create Pull Request
        id: create-pull-request
        uses: peter-evans/create-pull-request@v8
        with:
          signoff: true
          sign-commits: true
          commit-message: "Update jdks.yaml"
          add-paths: .teamcity/jdks.yaml
          title: "Update jdks.yaml"

Luego usamos el request directamente, y extraemos el cuerpo como `bytes`. Esto significa que FastAPI ni siquiera intentará parsear la carga útil del request como JSON.

Y luego en nuestro código, parseamos ese contenido YAML directamente, y nuevamente estamos usando el mismo modelo Pydantic para validar el contenido YAML:

//// tab | Pydantic v2

Então utilizamos a requisição diretamente, e extraímos o corpo como `bytes`. Isso significa que o FastAPI não vai sequer tentar analisar o corpo da requisição como JSON.

E então no nosso código, nós analisamos o conteúdo YAML diretamente, e estamos utilizando o mesmo modelo Pydantic para validar o conteúdo YAML:

//// tab | Pydantic v2

## 2. Run Distributed MinIO on Docker Compose

        x - x-men
        x - x-avengers
        """
    response = client.post("/items/", content=yaml_data)
    assert response.status_code == 422, response.text
    assert response.json() == {"detail": "Invalid YAML"}


def test_post_invalid(client: TestClient):
    yaml_data = """
        name: Deadpoolio
        tags:
        - x-force
        - x-men
        - x-avengers
        - sneaky: object
        """

        - '!pyproject.toml'

internal:
  - all:
    - changed-files:
      - any-glob-to-any-file:
        - .github/**
        - scripts/**
        - .gitignore
        - .pre-commit-config.yaml
        - pdm_build.py
        - requirements*.txt
        - docs/en/data/sponsors.yml
        - docs/en/overrides/main.html
      - all-globs-to-all-files:
        - '!docs/*/docs/**'
        - '!fastapi/**'