additionalJapicmpClasspath.from(resolveKotlinCompilerEmbeddable());
        } catch (Exception e) {
            throw new RuntimeException("Got an error while patching JapicmpTask task", e);
        }
    }

    private Configuration resolveKotlinCompilerEmbeddable() {
        Project project = getProject();
        DependencyHandler dependencies = project.getDependencies();

import jakarta.servlet.http.HttpServletResponse;

/**
 * Interface for managing web API request processing.
 * Implementations of this interface handle specific types of web API requests
 * by matching incoming requests and processing them accordingly.
 */
public interface WebApiManager {

    /**
     * Checks if the request matches this API manager.
     * @param request The HTTP servlet request.

 *
 * @author Paul Lindner
 */
@NullUnmarked
public class SplitterBenchmark {
  // overall size of string
  @Param({"1", "10", "100", "1000"})
  int length;

  // Number of matching strings
  @Param({"xxxx", "xxXx", "xXxX", "XXXX"})
  String text;

  private String input;

  private static final Splitter CHAR_SPLITTER = Splitter.on('X');

 *     {@code MapMaker}, it was added to {@code CacheBuilder}, which throws {@code
 *     ExecutionException}, {@code UncheckedExecutionException}, and {@code ExecutionError}. Any
 *     code that is still catching {@code ComputationException} may need to be updated to catch some
 *     of those types instead. (Note that this type, though deprecated, is not planned to be removed
 *     from Guava.)
 */
@Deprecated
@GwtCompatible

## What Does Deployment Mean { #what-does-deployment-mean }

To **deploy** an application means to perform the necessary steps to make it **available to the users**.

For a **web API**, it normally involves putting it in a **remote machine**, with a **server program** that provides good performance, stability, etc, so that your **users** can **access** the application efficiently and without interruptions or problems.

Eso, más el simple hecho de que Python es el lenguaje principal para **Data Science**, Machine Learning y especialmente Deep Learning, hacen de FastAPI una muy buena opción para APIs web de Data Science / Machine Learning y aplicaciones (entre muchas otras).

    }

    /**
     * Gets the appropriate web API manager for the given request.
     *
     * @param request The HTTP servlet request
     * @return The matching web API manager, or null if no match found
     */
    public WebApiManager get(final HttpServletRequest request) {
        for (final WebApiManager webApiManager : webApiManagers) {

{
    "description": "TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications.",
    "license": "Apache-2.0",
    "title": "TensorFlow",
    "upload_type": "software",
    "creators": [
        {
            "name": "TensorFlow Developers"
        }

   */
  static int tableSize(int expectedSize) {
    // We use entries next == 0 to indicate UNSET, so actual capacity is 1 less than requested.
    return max(MIN_HASH_TABLE_SIZE, Hashing.closedTableSize(expectedSize + 1, 1.0));
  }

  /** Creates and returns a properly-sized array with the given number of buckets. */
  static Object createTable(int buckets) {
    if (buckets < 2

	}

	// Tests hashing order to be consistent.
	for i, testCase := range testCases {
		hashedOrder := hashOrder(testCase.objectName, 16)
		if !reflect.DeepEqual(testCase.hashedOrder, hashedOrder) {
			t.Errorf("Test case %d: Expected \"%v\" but failed \"%v\"", i+1, testCase.hashedOrder, hashedOrder)
		}
	}

	// Tests hashing order to fail for when order is '-1'.