////

That extra info will be added as-is to the output **JSON Schema** for that model, and it will be used in the API docs.

//// tab | Pydantic v2

In Pydantic version 2, you would use the attribute `model_config`, that takes a `dict` as described in <a href="https://docs.pydantic.dev/latest/api/config/" class="external-link" target="_blank">Pydantic's docs: Configuration</a>.

/^(?!javascript:)(?:[a-z0-9+.-]+:|[^&:/?#]*(?:[/?#]|$))/i\n\nconst allowedAttribute = (attribute, allowedAttributeList) => {\n  const attributeName = attribute.nodeName.toLowerCase()\n\n  if (allowedAttributeList.includes(attributeName)) {\n    if (uriAttributes.has(attributeName)) {\n      return Boolean(SAFE_URL_PATTERN.test(attribute.nodeValue))\n    }\n\n    return true\n  }\n\n  // Check if a regular expression validates the attribute.\n  return allowedAttributeList.filter(attributeRegex => attributeRegex...

    // ===================================================================================
    //                                                                           Attribute
    //                                                                           =========
    // keeping parsed request parameters, normal texts or uploaded files

    // ===================================================================================
    //                                                                           Attribute
    //                                                                           =========
    @Resource
    private BadWordService badWordService;
    @Resource
    private BadWordPager badWordPager;

    /**

     */
    public RoleQueryHelper() {
        super();
    }

    private static final Logger logger = LogManager.getLogger(RoleQueryHelper.class);

    /**
     * The key for user roles in the request attribute.
     */
    protected static final String USER_ROLES = "userRoles";

    /**
     * The cached cipher for encryption and decryption.
     */
    protected CachedCipher cipher;

    /**

    </default>
  </defaults>
  <classes>
    <class rootElement="true" xml.tagName="metadata" java.clone="deep">
      <name>Metadata</name>
      <version>1.0.0+</version>
      <fields>
        <field xml.attribute="true" xml.tagName="modelVersion">
          <name>modelVersion</name>
          <version>1.1.0+</version>
          <type>String</type>
          <description>The version of the underlying metadata model.</description>

#### Daten-„Schema“

Der Begriff „Schema“ kann sich auch auf die Form von Daten beziehen, wie z. B. einen JSON-Inhalt.

In diesem Fall sind die JSON-Attribute und deren Datentypen, usw. gemeint.

#### OpenAPI und JSON Schema

# https://github.com/tensorflow/tensorflow/blob/cd67f4f3723f9165aabedd0171aaadc6290636e5/tensorflow/tensorflow.bzl#L396-L425
# And is usable in the "deps" attribute instead of the "srcs" attribute
# as a workaround for https://github.com/tensorflow/tensorflow/issues/34117
cc_import(
    name = "libtensorflow_framework_import_lib",
    shared_library = select({

    // ===================================================================================
    //                                                                           Attribute
    //                                                                           =========
    protected List<QueryBuilder> queryBuilderList;
    protected List<FieldSortBuilder> fieldSortBuilderList;

    // ===================================================================================
    //                                                                           Attribute
    //                                                                           =========
    protected List<QueryBuilder> queryBuilderList;
    protected List<FieldSortBuilder> fieldSortBuilderList;