## OpenAPI condicional desde configuraciones y variables de entorno { #conditional-openapi-from-settings-and-env-vars }

Puedes usar fácilmente las mismas configuraciones de Pydantic para configurar tu OpenAPI generado y las interfaces de usuario de la documentación.

Por ejemplo:

{* ../../docs_src/conditional_openapi/tutorial001_py310.py hl[6,11] *}

이 도구는 Python docstring 내부에 YAML(또 다른 문법)을 작성해야 하는 문제를 해결했습니다.

Flask + Flask-apispec + Marshmallow + Webargs 조합은 **FastAPI**를 만들기 전까지 제가 가장 좋아하던 백엔드 stack이었습니다.

이를 사용하면서 여러 Flask full-stack generator가 만들어졌습니다. 이것들이 지금까지 저(그리고 여러 외부 팀)가 사용해 온 주요 stack입니다:

* [https://github.com/tiangolo/full-stack](https://github.com/tiangolo/full-stack)

import java.lang.annotation.RetentionPolicy;
import java.util.Collection;
import java.util.Set;
import org.jspecify.annotations.Nullable;

/**
 * When describing the features of the collection produced by a given generator (i.e. in a call to
 * {@link
 * com.google.common.collect.testing.FeatureSpecificTestSuiteBuilder#withFeatures(Feature...)}),
 * this annotation specifies each of the different sizes for which a test suite should be built. (In

import java.lang.annotation.RetentionPolicy;
import java.util.Collection;
import java.util.Set;
import org.jspecify.annotations.Nullable;

/**
 * When describing the features of the collection produced by a given generator (i.e. in a call to
 * {@link
 * com.google.common.collect.testing.FeatureSpecificTestSuiteBuilder#withFeatures(Feature...)}),
 * this annotation specifies each of the different sizes for which a test suite should be built. (In

import com.google.common.collect.testing.UnhashableObject;
import com.google.common.primitives.Chars;
import java.util.Collections;
import java.util.List;
import org.jspecify.annotations.NullMarked;

/**
 * Common generators of different types of lists.
 *
 * @author Hayward Chan
 */
@GwtCompatible
@NullMarked
public final class ListGenerators {

  private ListGenerators() {}

{"index":{"_index":"fess_config.scheduled_job","_id":"thumbnail_generate"}}

  @Override
  public String[] createArray(int length) {
    return new String[length];
  }

  /**
   * {@inheritDoc}
   *
   * <p>By default, returns the supplied elements in their given order; however, generators for
   * containers with a known order other than insertion order must override this method.
   *
   * <p>Note: This default implementation is overkill (but valid) for an unordered container. An

  @Override
  public Integer[] createArray(int length) {
    return new Integer[length];
  }

  /**
   * {@inheritDoc}
   *
   * <p>By default, returns the supplied elements in their given order; however, generators for
   * containers with a known order other than insertion order must override this method.
   *
   * <p>Note: This default implementation is overkill (but valid) for an unordered container. An

  @Override
  public String[] createArray(int length) {
    return new String[length];
  }

  /**
   * {@inheritDoc}
   *
   * <p>By default, returns the supplied elements in their given order; however, generators for
   * containers with a known order other than insertion order must override this method.
   *
   * <p>Note: This default implementation is overkill (but valid) for an unordered container. An

Aquí tienes varias formas de hacerlo.

## Datos extra de JSON Schema en modelos de Pydantic { #extra-json-schema-data-in-pydantic-models }

Puedes declarar `examples` para un modelo de Pydantic que se añadirá al JSON Schema generado.

{* ../../docs_src/schema_extra_example/tutorial001_py310.py hl[13:24] *}

Esa información extra se añadirá tal cual al **JSON Schema** resultante para ese modelo, y se usará en la documentación de la API.