/**
 * Abstract base class for CrawlerClient implementations.
 * Provides common functionality for handling initialization parameters,
 * content length checks, and default method implementations.
 * It defines the basic structure and configuration options for crawler clients.
 */
public abstract class AbstractCrawlerClient implements CrawlerClient {

    private static final Logger logger = LogManager.getLogger(AbstractCrawlerClient.class);

 * which is optimal, and <i>not</i> the size of the internal hashtable, which could be much larger
 * than {@code size()}. Furthermore, this structure only depends on a fixed number of arrays; {@code
 * add(x)} operations <i>do not</i> create objects for the garbage collector to deal with, and for

// op executed under the tape. A separate map (`tensorflow::eager::OpTape`)
// maintains the map from `op_id` to a `OpTapeEntry` which stores the `op_type`,
// inputs and outputs and the gradient function These data structures combined
// allow us to trace the data dependencies between operations and hence compute
// gradients.
//
// `ZerosLike` is not expected to be called and returns a nullptr. The creation

* list (as in Python list): list
* context manager: context manager (do not translate to "gestor de contexto" or "administrador de contexto")
* a little bit: un poquito
* graph (data structure, as in "dependency graph"): grafo (do not translate to "gráfico")
* form data: form data (do not translate to "datos de formulario" or "datos de form")
* import (as in code import): import (do not translate to "importación")

```console
$ <font color="#4E9A06">fastapi</font> dev

  <span style="background-color:#009485"><font color="#D3D7CF"> FastAPI </font></span>  Starting development server 🚀

             Searching for package file structure from directories
             with <font color="#3465A4">__init__.py</font> files
             Importing from <font color="#75507B">/home/user/code/</font><font color="#AD7FA8">awesomeapp</font>

```console
$ <font color="#4E9A06">fastapi</font> dev

  <span style="background-color:#009485"><font color="#D3D7CF"> FastAPI </font></span>  Starting development server 🚀

             Searching for package file structure from directories with
             <font color="#3465A4">__init__.py</font> files
             Importing from <font color="#75507B">/home/user/code/</font><font color="#AD7FA8">awesomeapp</font>

dataclass는 자동으로 Pydantic dataclass로 변환됩니다.

이렇게 하면 해당 스키마가 API docs 사용자 인터페이스에 표시됩니다:

<img src="/img/tutorial/dataclasses/image01.png">

## 중첩 데이터 구조에서 Dataclasses 사용하기 { #dataclasses-in-nested-data-structures }

`dataclasses`를 다른 타입 애너테이션과 조합해 중첩 데이터 구조를 만들 수도 있습니다.

일부 경우에는 Pydantic 버전의 `dataclasses`를 사용해야 할 수도 있습니다. 예를 들어 자동 생성된 API 문서에서 오류가 발생하는 경우입니다.

그런 경우 표준 `dataclasses`를 드롭인 대체재인 `pydantic.dataclasses`로 간단히 바꾸면 됩니다:

#include "tensorflow/core/platform/types.h"
#include "tensorflow/core/public/session.h"

namespace tensorflow {
class Device;
class DeviceMgr;
class ServerInterface;
}  // namespace tensorflow

// Internal structures used by the C API. These are likely to change and should
// not be depended on.

struct TF_SessionOptions {
  tensorflow::SessionOptions options;
};

struct TF_DeprecatedSession {
  tensorflow::Session* session;

        // Test that the exception is serializable
        ThemeException exception = new ThemeException("Serialization test");

        // Verify that the exception can be created and has the expected structure
        assertNotNull(exception);
        assertTrue(exception instanceof java.io.Serializable);
    }

    @Test
    public void test_nestedExceptions() {
        // Test nested exception handling

     * @throws UnknownHostException if the IP address is not found
     */
    @Test
    void testConstructor() throws IOException, PACDecodingException, UnknownHostException {
        // Build a sample Kerberos EncData structure
        ASN1EncodableVector vector = new ASN1EncodableVector();
        vector.add(new DERTaggedObject(2, new DERGeneralString("TEST.REALM")));

        ASN1EncodableVector principalVector = new ASN1EncodableVector();