String params = "test";
        byte[] buffer = createBuffer(10, dataBytes, params);

        // Verify buffer structure
        assertTrue(buffer.length >= 14, "Buffer should contain header, params and data");
    }

    @Test
    public void testByteOperations() {
        // Test byte operations that were used in the original test
        byte b = (byte) 0xFF;
        int value = b & 0xFF;

> [!NOTE]
> To deploy MinIO on with persistent storage, you must map local persistent directories from the host OS to the container using the `podman -v` option.
> For example, `-v /mnt/data:/data` maps the host OS drive at `/mnt/data` to `/data` on the container.

## macOS

Use the following commands to run a standalone MinIO server on macOS.

	data, err := json.Marshal(item)
	if err != nil {
		return err
	}
	if GlobalKMS != nil {
		data, err = config.EncryptBytes(GlobalKMS, data, kms.Context{
			minioMetaBucket: path.Join(minioMetaBucket, objPath),
		})
		if err != nil {
			return err
		}
	}
	return saveConfig(ctx, iamOS.objAPI, objPath, data)
}

func decryptData(data []byte, objPath string) ([]byte, error) {

 * It allows adding, retrieving, and removing rules, as well as checking for their existence.
 */
public interface RuleManager {

    /**
     * Retrieves the rule associated with the given response data.
     *
     * @param responseData the response data for which the rule is to be retrieved
     * @return the rule associated with the given response data
     */

    @Inject
    private ArtifactRepositoryFactory artifactRepositoryFactory;

    @Test
    void testUnnecessaryRepositoryLookup() throws Exception {
        Artifact artifact = createTestPomArtifact("target/test-data/get-missing-pom");

        List<ArtifactRepository> repos = new ArrayList<>();
        repos.add(artifactRepositoryFactory.createArtifactRepository(

Declare the **query parameters** that you need in a **Pydantic model**, and then declare the parameter as `Query`:

{* ../../docs_src/query_param_models/tutorial001_an_py310.py hl[9:13,17] *}

**FastAPI** will **extract** the data for **each field** from the **query parameters** in the request and give you the Pydantic model you defined.

## Check the Docs { #check-the-docs }

You can see the query parameters in the docs UI at `/docs`:

post() {
    local endpoint="$1"
    local data="$2"

    local response=$(curl -X POST \
        -H "Authorization: token $GITHUB_TOKEN" \
        -H "Accept: application/vnd.github.v3+json" \
        -H "Content-Type: application/json" \
        "https://api.github.com/repos/gradle/gradle$endpoint" \
        -d "$data" \
        -w "\n%{http_code}" \
        2>/dev/null)

 */
package org.codelibs.fess.crawler.service;

import java.util.List;

import org.codelibs.fess.crawler.entity.AccessResult;
import org.codelibs.fess.crawler.util.AccessResultCallback;

/**
 * Interface for data service operations related to access results.
 *
 * @param <RESULT> the type of access result
 */
public interface DataService<RESULT extends AccessResult<?>> {

    /**
     * Stores the given access result.

        assertEquals(0, result);
    }

    @Test
    void testReadDataWireFormatWithValidLength() throws SMBProtocolDecodingException {
        // Prepare test data
        byte[] sourceData = { 10, 20, 30, 40, 50 };
        byte[] buffer = new byte[100];
        System.arraycopy(sourceData, 0, buffer, 10, sourceData.length);

        // Execute

            return null;
        })).status(Status.OK).result());
    }

    /**
     * Creates a new related query setting.
     *
     * @param body the related query configuration data to create
     * @return JSON response containing the created related query ID and status
     */
    // POST /api/admin/relatedquery/setting
    @Execute