{* ../../docs_src/body_nested_models/tutorial003_py310.py hl[12] *}

With this, even if you receive a request with duplicate data, it will be converted to a set of unique items.

And whenever you output that data, even if the source had duplicates, it will be output as a set of unique items.

And it will be annotated / documented accordingly too.

## Nested Models { #nested-models }

Each attribute of a Pydantic model has a type.

        return task;
    }

    /**
     * Generates a thumbnail image and saves it to the specified output file.
     *
     * <p>This method processes the image content associated with the thumbnail ID,
     * validates the image format, applies scaling and cropping transformations,
     * and writes the resulting thumbnail to the output file.</p>
     *
     * @param thumbnailId the unique identifier for the thumbnail

    private static LogStream inst;

    /**
     * The current logging level.
     */
    public static int level = 1;

    /**
     * Constructs a LogStream with the specified output stream.
     *
     * @param stream the output stream for logging
     */
    public LogStream(final PrintStream stream) {
        super(stream);
    }

    /**
     * Sets the logging level.
     *

 */
public class WitnessHeartbeatMessage extends WitnessRpcMessage {

    // Input parameters for WitnessHeartbeat
    private byte[] contextHandle;
    private long sequenceNumber;

    // Output parameters for WitnessHeartbeat
    private long responseSequenceNumber;
    private long heartbeatInterval;

    /**
     * Creates a new WitnessHeartbeat RPC message.
     */
    public WitnessHeartbeatMessage() {

			}
		}
		// Test passes as expected, but the output values are verified for correctness here.
		if actualErr == nil && testCase.shouldPass {
			// Asserting whether the md5 output is correct.
			if testCase.inputMd5 != actualInfo.ETag {

      value:
      render: shell
    validations:
      required: true
  - type: textarea
    id: logs
    attributes:
      label: Relevant log output
      description: Please copy and paste any relevant log output. This will be automatically formatted into code, so no need for backticks.

/src/main/webapp/WEB-INF/db/*.lock.db
/src/main/webapp/WEB-INF/logs/fess*
/.settings/
.project
.classpath
*.iml
.idea
.vscode
.DS_Store
/plugins/
/modules/
/tomcat.8080/
dbflute_fess/output/doc/lastadoc-fess.html
dbflute_fess/schema/project-lastadoc-fess.json
src/main/resources/fess_indices/fess_config.access_token/access_token.bulk
src/main/resources/ga_client_secrets.p12
src/main/webapp/WEB-INF/project.properties

Und wenn Sie alle verfügbaren Schemas (JSON-Schemas) in OpenAPI überprüfen, werden Sie feststellen, dass es zwei gibt, ein `Item-Input` und ein `Item-Output`.

Für `Item-Input` ist `description` **nicht erforderlich**, es hat kein rotes Sternchen.

Aber für `Item-Output` ist `description` **erforderlich**, es hat ein rotes Sternchen.

<div class="screenshot">
<img src="/img/tutorial/separate-openapi-schemas/image04.png">
</div>

     */
    @Test
    void testGetOutputStreamCachesData() throws IOException {
        // Arrange
        // Enable output mode
        when(mockConnection.getDoOutput()).thenReturn(true);
        ntlmConnection.setDoOutput(true);

        // Mock initial connection's output stream (needed for CacheStream)
        OutputStream initialOutputStream = mock(OutputStream.class);

	for _, test := range lexTests {
		input := NewInput(test.name)
		input.Push(NewTokenizer(test.name, strings.NewReader(test.input), nil))
		result := drain(input)
		if result != test.output {
			t.Errorf("%s: got %q expected %q", test.name, result, test.output)
		}
	}
}

// lines joins the arguments together as complete lines.
func lines(a ...string) string {
	return strings.Join(a, "\n") + "\n"
}