this.defaultGeoInfo = defaultGeoInfo;
    }

    /**
     * Generates a unique identifier string by creating a UUID and removing hyphens.
     *
     * @return a unique identifier string
     */
    public String generateId() {
        return UUID.randomUUID().toString().replace("-", StringUtil.EMPTY);
    }

    /**

./mc mb "${ALIAS_NAME}"/"${BUCKET}"
rm -rf "${SRC_DIR}" "${INLINED_DIR}" "${DEST_DIR}" && mkdir -p "${SRC_DIR}" "${INLINED_DIR}" "${DEST_DIR}"
for idx in {1..10}; do
	# generate random nr of blocks
	COUNT=$((RANDOM % 100 + 100))
	# generate random content
	dd if=/dev/urandom bs=50K count="${COUNT}" of="${SRC_DIR}"/file"$idx"
done

# create small object that will be inlined into xl.meta

          # For discussion, see the first setup-java block.
          # The generate-docs workflow doesn't run tests, so we don't have to care which version Maven would select for that step.
          # But we need Java 11 for JDiff.
          java-version: |
            11
            25
          distribution: 'temurin'
          cache: 'maven'
      - name: 'Generate latest docs'
        env:

     */
    public abstract void invalidate();

    /**
     * Generate local key for this memory region
     *
     * @return local key
     */
    protected abstract int generateLocalKey();

    /**
     * Generate remote key for this memory region
     *
     * @return remote key
     */
    protected abstract int generateRemoteKey();

		Value:  ":" + GlobalMinioDefaultPort,
		Usage:  "bind to a specific ADDRESS:PORT, ADDRESS can be an IP or hostname",
		EnvVar: "MINIO_ADDRESS",
	},
}

var fmtGenCmd = cli.Command{
	Name:   "fmt-gen",
	Usage:  "Generate format.json files for an erasure server pool",
	Flags:  append(fmtGenFlags, GlobalFlags...),
	Action: fmtGenMain,
	Hidden: true,
	CustomHelpTemplate: `NAME:
  {{.HelpName}} - {{.Usage}}

USAGE:

### **4.1 Spark Pi**

Test the Spark installation by running the following compute intensive example, which calculates pi by “throwing darts” at a circle. The program generates points in the unit square ((0,0) to (1,1)) and counts how many points fall within the unit circle within the square. The result approximates pi.

Follow these steps to run the Spark Pi example:

- Login as user **‘spark’**.

	Shared     = flag.Bool("shared", false, "generate code that can be linked into a shared library")
	Dynlink    = flag.Bool("dynlink", false, "support references to Go symbols defined in other shared libraries")
	Linkshared = flag.Bool("linkshared", false, "generate code that will be linked against Go shared libraries")

Like `item.model_dump(exclude_unset=True)`.

That would generate a `dict` with only the data that was set when creating the `item` model, excluding default values.

Then you can use this to generate a `dict` with only the data that was set (sent in the request), omitting default values:

{* ../../docs_src/body_updates/tutorial002_py310.py hl[32] *}

          </params>
        </configuration>
        <executions>
          <execution>
            <id>velocity</id>
            <goals>
              <goal>velocity</goal>
            </goals>
            <phase>generate-sources</phase>
            <configuration>
              <templates>
                <template>merger.vm</template>
                <template>transformer.vm</template>
                <template>reader-stax.vm</template>

		}

		value, err := webID.Retrieve()
		if err != nil && !testCase.expectedErr {
			c.Fatalf("Test %d: Expected to generate STS creds, got err: %#v", i+1, err)
		}
		if err == nil && testCase.expectedErr {
			c.Fatalf("Test %d: An error is unexpected to generate STS creds, got err: %#v", i+1, err)
		}

		if err != nil && testCase.expectedErr {
			continue
		}