*
 * <p>This class uses various utilities such as ReadingConverter, Normalizer, and SuggestAnalyzer
 * to process and analyze the input data.</p>
 *
 * <p>It also handles the exclusion of search words based on certain criteria and manages the
 * maximum length of analyzed content.</p>
 *
 * <p>Methods in this class may throw SuggesterException in case of failures during the parsing process.</p>
 *

experience, nationality, personal appearance, race, religion, or sexual identity
and orientation.

## Our Standards

Examples of behavior that contributes to creating a positive environment include:

*   Using welcoming and inclusive language.
*   Being respectful of differing viewpoints and experiences.
*   Gracefully accepting constructive criticism.
*   Focusing on what is best for the community.
*   Showing empathy towards other community members.

   * guaranteed to be exactly +/-1 even when the data are perfectly (anti-)correlated, due to
   * numerical errors. However, it is guaranteed to be in the inclusive range [-1, +1].
   *
   * <h3>Non-finite values</h3>
   *
   * <p>If the dataset contains any non-finite values ({@link Double#POSITIVE_INFINITY}, {@link

                    totalAttemptsBlocked.incrementAndGet();
                    totalIpsBlocked.incrementAndGet();
                    log.warn("IP {} is blocked due to excessive attempts", sourceIp);
                    return false;
                } else {
                    // Block expired, reset
                    ip.reset();
                }
            }

                (AuthenticationType) null);
        this.context = tc;
    }

    /**
     * Create an {@code NtlmPasswordAuthentication} object with raw password
     * hashes. This is used exclusively by the {@code jcifs.http.NtlmSsp}
     * class which is in turn used by NTLM HTTP authentication functionality.
     *
     * @param domain the authentication domain
     * @param username the username to authenticate with

///

/// warning | Attention

Pour faire cela, vous devez vous assurer que chacun de vos *chemin* ait un nom unique.

Même s'ils se trouvent dans des modules différents (fichiers Python).

///

## Exclusion d'OpenAPI

Pour exclure un *chemin* du schéma OpenAPI généré (et donc des systèmes de documentation automatiques), utilisez le paramètre `include_in_schema` et assignez-lui la valeur `False` :

            </ul>
          </description>
          <type>String</type>
        </field>
        <field>
          <name>provides</name>
          <version>1.0.0/1.0.99</version> <!-- fake upperbound, it's inclusive -->
          <type>DOM</type>
          <description>
            Toolchain identification information, which will be matched against project requirements.

- **Extensible Architecture**: Plugin system for custom extractors, transformers, and clients
- **Rate Limiting**: Politeness policies and interval controllers
- **URL Filtering**: Regex-based inclusion/exclusion patterns
- **Data Persistence**: Multiple backend options including OpenSearch integration

## Technology Stack

- **Java**: 21+ (requires Java 21 or higher)
- **Build System**: Maven 3.x

  /**
   * Load 8 bytes into long in a little endian manner, from the substring between position and
   * position + 8. The array must have at least 8 bytes from offset (inclusive).
   *
   * @param input the input bytes
   * @param offset the offset into the array at which to start
   * @return a long of a concatenated 8 bytes
   */
  static long load64(byte[] input, int offset) {

   * guaranteed to be exactly +/-1 even when the data are perfectly (anti-)correlated, due to
   * numerical errors. However, it is guaranteed to be in the inclusive range [-1, +1].
   *
   * <h3>Non-finite values</h3>
   *
   * <p>If the dataset contains any non-finite values ({@link Double#POSITIVE_INFINITY}, {@link