* calling it should not be necessary with a high throughput cache. Only caches built with {@link
 * #removalListener removalListener}, {@link #expireAfterWrite expireAfterWrite}, {@link
 * #expireAfterAccess expireAfterAccess}, {@link #weakKeys weakKeys}, {@link #weakValues
 * weakValues}, or {@link #softValues softValues} perform periodic maintenance.
 *
 * <p>The caches produced by {@code CacheBuilder} are serializable, and the deserialized caches

import jcifs.ntlmssp.Type3Message;
import jcifs.smb.NtlmPasswordAuthentication;

/**
 * This class is used internally by {@code NtlmHttpFilter},
 * {@code NtlmServlet}, and {@code NetworkExplorer} to negotiate password
 * hashes via NTLM SSP with MSIE. It might also be used directly by servlet
 * containers to incorporate similar functionality.
 * <p>
 * How NTLMSSP is used in conjunction with HTTP and MSIE clients is

specific versions. This is necessary to ensure reproducibility of the build.
The pinned versions of the full transitive closure of TensorFlow's dependencies
together with their corresponding hashes are specified in
`requirements_lock_<python version>.txt` files (e.g.
`requirements_lock_3_12.txt` for `Python 3.12`).

To update the lock files, make sure

* Il peut y avoir **plusieurs processus** du **même programme** exécutés simultanément.

Si vous ouvrez le « gestionnaire des tâches » ou le « moniteur système » (ou des outils similaires) de votre système d'exploitation, vous verrez nombre de ces processus en cours d'exécution.

   * {@code key}, simply waits for that thread to finish and returns its loaded value. Note that
   * multiple threads can concurrently load values for distinct keys.
   *
   * <p>Caches loaded by a {@link CacheLoader} will call {@link CacheLoader#load} to load new values
   * into the cache. Newly loaded values are added to the cache using {@code

   * {@code key}, simply waits for that thread to finish and returns its loaded value. Note that
   * multiple threads can concurrently load values for distinct keys.
   *
   * <p>Caches loaded by a {@link CacheLoader} will call {@link CacheLoader#load} to load new values
   * into the cache. Newly loaded values are added to the cache using {@code

  public static void testSubtypeOfStaticAnonymousClass() {
    Class<?> superclass = new Mall<Outdoor>().new Shop<Electronics>() {}.getClass();
    assertTrue(TypeToken.of(superclass).isSubtypeOf(superclass));
    assertFalse(
        TypeToken.of(new Mall<Outdoor>().new Shop<Electronics>() {}.getClass())
            .isSubtypeOf(superclass));
  }

 *
 * @author Zoe Piepmeier
 * @since 16.0
 */
@Beta
public final class HashingOutputStream extends FilterOutputStream {
  private final Hasher hasher;

  /**
   * Creates an output stream that hashes using the given {@link HashFunction}, and forwards all
   * data written to it to the underlying {@link OutputStream}.
   *

    lines: list[str] = []
    for line in content.split("\n"):
        match = header_with_permalink_pattern.match(line)
        if match:
            hashes, title, *_ = match.groups()
            line = f"{hashes} {title}"
        lines.append(line)
    return "\n".join(lines)


def generate_readme_content() -> str:
    en_index = en_docs_path / "docs" / "index.md"

import org.lastaflute.web.util.LaRequestUtil;

/**
 * Helper class for detecting and categorizing user agent types from HTTP requests.
 * This class analyzes the User-Agent header to determine which browser type is being used
 * and caches the result in the request attribute for performance optimization.
 *
 */
public class UserAgentHelper {

    /**
     * Default constructor for UserAgentHelper.
     */
    public UserAgentHelper() {