*      writes to, reads from, and closes the pipe in a single operation.
 * <li> <code>TransactNamedPipe</code> A message-type pipe call that
 *      writes to and reads from an existing pipe descriptor in one operation.
 * <li> <code>CreateFile</code>, <code>ReadFile</code>,
 *      <code>WriteFile</code>, and <code>CloseFile</code> A byte-type pipe can

            return null;
        });

        return asJson(new ApiUpdateResponse().id(dataConfig.getId()).created(true).status(Status.OK).result());
    }

    /**
     * Updates an existing data config setting.
     *
     * @param body the request body containing updated data config information
     * @return JSON response with result status
     */
    // PUT /api/admin/dataconfig/setting

 * writes to, reads from, and closes the pipe in a single operation.
 * <li><code>TransactNamedPipe</code> A message-type pipe call that
 * writes to and reads from an existing pipe descriptor in one operation.
 * <li><code>CreateFile</code>, <code>ReadFile</code>,
 * <code>WriteFile</code>, and <code>CloseFile</code> A byte-type pipe can

import jcifs.DfsReferralData;
import jcifs.SmbSession;
import jcifs.SmbTransport;
import jcifs.smb.SmbException;
import jcifs.smb.SmbTransportInternal;

/**
 * RDMA-enabled SMB transport that wraps existing SMB transport
 * and adds RDMA capabilities for direct memory access operations.
 */
public class RdmaTransport implements SmbTransportInternal {

     */
    @Config
    public static final String MAVEN_VERSION_FILTER = "maven.session.versionFilter";

    /**
     * User property for chained LRM: the new "head" local repository to use, and "push" the existing into tail.
     * Similar to <code>maven.repo.local.tail</code>, this property may contain comma separated list of paths to be

    * Pydantic'in veri yapıları aslında sadece senin tanımladığın classlar; Bu yüzden doğrulanmış dataların ile otomatik tamamlama, linting ve mypy'ı kullanarak sorunsuz bir şekilde çalışabilirsin
* **En kompleks** yapıları bile doğrula:
    * Hiyerarşik Pydantic modellerinin kullanımı ile beraber, Python `typing`’s `List` and `Dict`, vs gibi şeyleri doğrula.

    * Ponieważ struktury danych Pydantic to po prostu instancje klas, które definiujesz; autouzupełnianie, linting, mypy i twoja intuicja powinny działać poprawnie z Twoimi zwalidowanymi danymi.
* Walidacja **złożonych struktur**:
    * Wykorzystanie hierarchicznych modeli Pydantic, Pythonowego modułu `typing` zawierającego `List`, `Dict`, itp.

    * Weil Pydantics Datenstrukturen einfach nur Instanzen ihrer definierten Klassen sind; Autovervollständigung, Linting, mypy und ihre Intuition sollten alle einwandfrei mit ihren validierten Daten funktionieren.
* Validierung von **komplexen Strukturen**:
    * Benutzung von hierarchischen Pydantic-Modellen, Python-`typing`s `List` und `Dict`, etc.

    * Because pydantic data structures are just instances of classes you define; auto-completion, linting, mypy and your intuition should all work properly with your validated data.
* Validate **complex structures**:
    * Use of hierarchical Pydantic models, Python `typing`’s `List` and `Dict`, etc.

        public DfsStorageInfo() {
            // Default constructor
        }

        /**
         * Storage state flags
         */
        public int state;
        /**
         * Server name hosting the storage
         */
        public String server_name;
        /**
         * Share name on the server
         */
        public String share_name;

        @Override