public static final int FILE_NOTIFY_CHANGE_FILE_NAME = 0x1;
    /**
     * Notify when a directory name changes
     */
    public static final int FILE_NOTIFY_CHANGE_DIR_NAME = 0x2;
    /**
     * Notify when file attributes change
     */
    public static final int FILE_NOTIFY_CHANGE_ATTRIBUTES = 0x4;
    /**
     * Notify when file size changes
     */
    public static final int FILE_NOTIFY_CHANGE_SIZE = 0x8;
    /**

The same way, this database wouldn't receive a Pydantic model (an object with attributes), only a `dict`.

You can use `jsonable_encoder` for that.

It receives an object, like a Pydantic model, and returns a JSON compatible version:

{* ../../docs_src/encoder/tutorial001_py310.py hl[4,21] *}

ncludes(elementName)) {\n      element.remove()\n      continue\n    }\n\n    const attributeList = [].concat(...element.attributes)\n    const allowedAttributes = [].concat(allowList['*'] || [], allowList[elementName] || [])\n\n    for (const attribute of attributeList) {\n      if (!allowedAttribute(attribute, allowedAttributes)) {\n        element.removeAttribute(attribute.nodeName)\n      }\n    }\n  }\n\n  return createdDocument.body.innerHTML\n}\n","/**\n * --------------------------------...

* For `PUT` requests to `/items/{item_id}`, read the body as JSON:
    * Check that it has a required attribute `name` that should be a `str`.
    * Check that it has a required attribute `price` that has to be a `float`.
    * Check that it has an optional attribute `is_offer`, that should be a `bool`, if present.
    * All this would also work for deeply nested JSON objects.

		uint16_t impersonation_level;
		uint8_t context_mode;
		uint8_t effective_only;
	} LsarQosInfo;

	typedef struct {
		uint32_t length;
		uint8_t *root_directory;
		unicode_string *object_name;
		uint32_t attributes;
		uint32_t security_descriptor;
		LsarQosInfo *security_quality_of_service;
	} LsarObjectAttributes;

	typedef struct {
		unicode_string name;
		sid_t *sid;
	} LsarDomainInfo;

	typedef struct {

		uint16_t impersonation_level;
		uint8_t context_mode;
		uint8_t effective_only;
	} LsarQosInfo;

	typedef struct {
		uint32_t length;
		uint8_t *root_directory;
		unicode_string *object_name;
		uint32_t attributes;
		uint32_t security_descriptor;
		LsarQosInfo *security_quality_of_service;
	} LsarObjectAttributes;

	typedef struct {
		unicode_string name;
		sid_t *sid;
	} LsarDomainInfo;

	typedef struct {

        </field>
        <field>
          <name>os</name>
          <version>1.0.0</version>
          <description><![CDATA[
            Specifies that this profile will be activated when matching OS attributes are detected.
          ]]></description>
          <association>
            <type>ActivationOS</type>
          </association>
        </field>
        <field>
          <name>property</name>

   *
   * OneAsymmetricKey ::= SEQUENCE {
   *   version                   Version,
   *   privateKeyAlgorithm       PrivateKeyAlgorithmIdentifier,
   *   privateKey                PrivateKey,
   *   attributes            [0] Attributes OPTIONAL,
   *   ...,
   *   [[2: publicKey        [1] PublicKey OPTIONAL ]],
   *   ...
   * }
   *
   * PrivateKeyInfo ::= OneAsymmetricKey
   * ```
   */

* `tags: List[str] = []` has a default of an empty list: `[]`.

but you might want to omit them from the result if they were not actually stored.

For example, if you have models with many optional attributes in a NoSQL database, but you don't want to send very long JSON responses full of default values.

### Use the `response_model_exclude_unset` parameter { #use-the-response-model-exclude-unset-parameter }

import com.vanniktech.maven.publish.KotlinJvm

plugins {
  kotlin("jvm")
  id("org.jetbrains.dokka")
  id("com.vanniktech.maven.publish.base")
  id("binary-compatibility-validator")
}

tasks.jar {
  manifest {
    attributes("Automatic-Module-Name" to "mockwebserver3.junit4")
  }
}

dependencies {
  api(projects.okhttp)
  api(projects.mockwebserver3)
  api(libs.junit)

  testImplementation(libs.assertk)