implementation("com.google.guava:guava:33.5.0-jre")

  // 2. Use Guava types in your public API:
  api("com.google.guava:guava:33.5.0-jre")

  // 3. Android - Use Guava in your implementation only:
  implementation("com.google.guava:guava:33.5.0-android")

  // 4. Android - Use Guava types in your public API:
  api("com.google.guava:guava:33.5.0-android")
}
```

Hug was one of the first frameworks to implement the declaration of API parameter types using Python type hints. This was a great idea that inspired other tools to do the same.

It used custom types in its declarations instead of standard Python types, but it was still a huge step forward.

It also was one of the first frameworks to generate a custom schema declaring the whole API in JSON.

        require_serial: true
        language: unsupported
        types: [python]

      - id: local-ruff-format
        name: ruff format
        entry: uv run ruff format --force-exclude --exit-non-zero-on-format
        require_serial: true
        language: unsupported
        types: [python]

      - id: add-permalinks-pages
        language: unsupported
        name: add-permalinks-pages

import jakarta.validation.ConstraintValidator;
import jakarta.validation.ConstraintValidatorContext;

/**
 * Validator implementation for URI type constraints.
 * This validator checks URI strings against specified protocol types.
 */
public class UriTypeValidator implements ConstraintValidator<UriType, String> {

    /**
     * Default constructor for UriTypeValidator.
     */
    public UriTypeValidator() {
        // Default constructor

     * <p>
     * Important: this "static" list of types should be in-sync with core provided types.
     */
    protected ArtifactTypeRegistry getArtifactTypeRegistry() {
        DefaultArtifactTypeRegistry stereotypes = new DefaultArtifactTypeRegistry();
        new DefaultTypeProvider().types().forEach(stereotypes::add);
        return stereotypes;
    }

Por ejemplo, no puedes poner un modelo de Pydantic en un `JSONResponse` sin primero convertirlo a un `dict` con todos los tipos de datos (como `datetime`, `UUID`, etc.) convertidos a tipos compatibles con JSON.

Para esos casos, puedes usar el `jsonable_encoder` para convertir tus datos antes de pasarlos a un response:

Hug a été l'un des premiers frameworks à implémenter la déclaration des types de paramètres d'API en utilisant les type hints Python. C'était une excellente idée qui a inspiré d'autres outils à faire de même.

Il utilisait des types personnalisés dans ses déclarations au lieu des types Python standard, mais c'était tout de même un énorme pas en avant.

        If you found a clear typo, please open a PR with a fix instead of opening an issue.

  - type: dropdown
    id: issue-type
    attributes:
      label: Issue type
      options:
        - Wrong or misleading information
        - Missing information
        - Styling or Accessibility
        - Typo (please open a PR instead)
    validations:
      required: true

            counter++
        }

        //updating/modifying the metadata and making sure every type reference across the metadata is fully qualified
        //so, the superClassName, interfaces and types needed by declared properties and declared methods will have fully qualified name
        TypeNameResolver resolver = new TypeNameResolver(repository)
        repository.each { name, metaData ->

            }
        }
    }

    @Test
    @DisplayName("Should have resource types with power-of-2 values")
    void testResourceTypeBitPatterns() {
        // Resource types should be powers of 2 for bit flag usage
        int[] types = { SmbConstants.TYPE_FILESYSTEM, SmbConstants.TYPE_WORKGROUP, SmbConstants.TYPE_SERVER, SmbConstants.TYPE_SHARE,