package org.codelibs.curl.io;

import java.io.File;
import java.io.IOException;
import java.nio.file.Files;
import java.util.logging.Logger;

import org.apache.commons.io.output.DeferredFileOutputStream;

/**
 * ContentOutputStream is a custom output stream that extends DeferredFileOutputStream.
 * It writes data to a temporary file once the data size exceeds a specified threshold.
 *

@REM Optional ENV vars
@REM   MVNW_REPOURL - repo url base for downloading maven distribution
@REM   MVNW_USERNAME/MVNW_PASSWORD - user and password for downloading maven
@REM   MVNW_VERBOSE - true: enable verbose log; others: silence the output
@REM ----------------------------------------------------------------------------

@IF "%__MVNW_ARG0_NAME__%"=="" (SET __MVNW_ARG0_NAME__=%~nx0)
@SET __MVNW_CMD__=
@SET __MVNW_ERROR__=

        help.execute(context);

        // Verify that logger.info was called multiple times
        // We can't easily verify the exact content without capturing the logger output,
        // but we can verify that the method executes without errors
        Mockito.verify(context.logger, Mockito.atLeastOnce()).info(Mockito.anyString());
    }

    @Test

		{Bucket: "test-getobjectinfo", Name: "Asia/empty-dir/", ContentType: "application/octet-stream", IsDir: true},
	}
	testCases := []struct {
		bucketName string
		objectName string

		// Expected output of GetObjectInfo.
		result ObjectInfo
		err    error
		// Flag indicating whether the test is expected to pass or not.
		shouldPass bool
	}{
		// Test cases with invalid bucket names ( Test number 1-4 ).

        assertEquals(dataRemaining, response.getDataRemaining());

        // Verify data was copied to output buffer
        byte[] copiedData = Arrays.copyOfRange(outputBuffer, 0, dataLength);
        assertArrayEquals(testData, copiedData);
    }

    @Test
    @DisplayName("Should throw exception when output buffer too small")
    void testReadBytesWireFormatBufferTooSmall() throws Exception {
        // Given

{* ../../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.

    page = context.new_page()
    page.goto("http://localhost:8000/docs")
    page.get_by_role("button", name="Item-Input").click()
    page.get_by_role("button", name="Item-Output").click()
    page.set_viewport_size({"width": 960, "height": 820})
    # Manually add the screenshot
    page.screenshot(
        path="docs/en/docs/img/tutorial/separate-openapi-schemas/image04.png"
    )

                                    <tr>
                                        <th><la:message key="labels.dict_mapping_target"/></th>
                                        <td>${f:br(f:h(output))}<la:hidden property="output"/></td>
                                    </tr>
                                    </tbody>
                                </table>
                            </div>

 */
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() {

      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.