/**
     * Initialize global build parameters. This method accepts and a initialization function which in turn accepts a
     * {@link MutableBuildParams}. Initialization can be done in "stages", therefore changes override existing values, and values from
     * previous calls to {@link #init(Consumer)} carry forward. In cases where you want to clear existing values
     * {@link MutableBuildParams#reset()} may be used.

 * artifact publishing by reducing the artifacts and packaging reports that consist of multiple files.
 *
 * Reducing the number of reports also makes it easier to find the important ones when analysing a failed build in
 * TeamCity.
 */
val testFilesCleanup = project.extensions.create<TestFileCleanUpExtension>("testFilesCleanup").apply {
    reportOnly.convention(false)
}

      |
      |... contents of file1.txt ...
      |--BbC04y
      |Content-Disposition: file; filename="file2.gif"
      |Content-Transfer-Encoding: binary
      |Content-Type: image/gif
      |
      |... contents of file2.gif ...
      |--BbC04y--
      |
      |--AaB03x--
      |
      """.trimMargin().replace("\n", "\r\n")
    val body =
      MultipartBody

Par exemple, vous pouvez ajouter un type de média supplémentaire `image/png`, en déclarant que votre *chemin d'accès* peut renvoyer un objet JSON (avec le type de média `application/json`) ou une image PNG :

{* ../../docs_src/additional_responses/tutorial002_py310.py hl[17:22,26] *}

/// note | Remarque

---

Exemplos comuns de operações limitadas por CPU são coisas que exigem processamento matemático complexo.

Por exemplo:

* **Processamento de áudio** ou **imagem**
* **Visão Computacional**: uma imagem é composta por milhões de pixels, cada pixel tem 3 valores / cores, processar isso normalmente exige alguma computação em todos esses pixels ao mesmo tempo

) : FunctionalTestBucketProvider {
    private val objectMapper = ObjectMapper().registerKotlinModule()
    private val buckets: Map<TestCoverage, List<BuildTypeBucket>> by lazy {
        val uuidToTestCoverage = model.stages.flatMap { it.functionalTests }.associateBy { it.uuid }
        val testCoverageAndBuckets: List<Map<String, Any>> = objectMapper.readValue(testBucketsJson.readText())
        testCoverageAndBuckets.associate { testCoverageAndBucket ->

		// Unlock the 1st lock; ref=1 after this line
		nsLk.unlock("volume", "path", false)

		// Taking another lockMapMutex here allows queuing up additional lockers. This should
		// not be required but makes reproduction much easier.
		nsLk.lockMapMutex.Lock()

		// lk3 blocks.
		lk3ch := make(chan bool)
		go func() {
			lk3ch <- nsLk.lock(ctx, "volume", "path", "source", "opsID", false, 0)
		}()

		// lk4, blocks.

			scannerLogOnceIf(ctx, err, dataUsageObjNamePath)
		}
		attempts++
	}
}

var prefixUsageCache = cachevalue.New[map[string]uint64]()

// loadPrefixUsageFromBackend returns prefix usages found in passed buckets
//
//	e.g.:  /testbucket/prefix => 355601334
func loadPrefixUsageFromBackend(ctx context.Context, objAPI ObjectLayer, bucket string) (map[string]uint64, error) {
	z, ok := objAPI.(*erasureServerPools)

            SerializableTester.reserialize(newDelegatingListWithEquals(LIST1)))
        .addEqualityGroup(
            newDelegatingListWithEquals(LIST2),
            newProxyWithSubHandler1(LIST2), // Makes sure type of handler doesn't affect equality
            newProxyWithSubHandler2(LIST2))
        .addEqualityGroup(newDelegatingIterableWithEquals(LIST2)) // different interface
        .testEquals();
  }

   * Visited Nodes = {N1, N2, N3, N4}
   * </pre>
   */
  private static final class Undirected<N> extends EndpointPairIterator<N> {
    // It's a little weird that we add `null` to this set, but it makes for slightly simpler code.
    private @Nullable Set<@Nullable N> visitedNodes;

    private Undirected(BaseGraph<N> graph) {
      super(graph);