t.printStackTrace(pw);
            pw.flush();
            return systemHelper.abbreviateLongText(sw.toString());
        } catch (final IOException e) {
            logger.warn("Failed to print the stack trace {}", t.getMessage(), e);
        }
        return StringUtil.EMPTY;
    }

    // Avoid expectEquals() here to delay reason manufacture until necessary.
    if (getList().size() != expectedList.size()) {
      fail("size mismatch: " + reportContext(expectedList));
    }
    for (int i = 0; i < expectedList.size(); i++) {
      E expected = expectedList.get(i);
      E actual = getList().get(i);
      if (expected != actual && (expected == null || !expected.equals(actual))) {

# Дополнительные типы данных

До сих пор вы использовали простые типы данных, такие как:

* `int`
* `float`
* `str`
* `bool`

Но вы также можете использовать и более сложные типы.

При этом у вас останутся те же возможности , что и до сих пор:

* Отличная поддержка редактора.
* Преобразование данных из входящих запросов.
* Преобразование данных для ответа.
* Валидация данных.
* Автоматическая аннотация и документация.

   * analysis that that means "plain {@code T}" rather than the inferred type {@code @Nullable T}.
   * (And even if annotations on local variables were permitted as an optional hint, no annotation
   * would be the right tool for the job here: {@code @Nullable} is the annotation that we're trying
   * to get rid of, and {@code @NonNull} would be wrong for our use case for the same reason as

            && Objects.equals(getColumnKey(), other.getColumnKey())
            && Objects.equals(getValue(), other.getValue());
      }
      return false;
    }

    @Override
    public int hashCode() {
      return Objects.hash(getRowKey(), getColumnKey(), getValue());
    }

    @Override
    public String toString() {
      return "(" + getRowKey() + "," + getColumnKey() + ")=" + getValue();

from pydantic import BaseModel

# Declare a variable as a str
# and get editor support inside the function
def main(user_id: str):
    return user_id


# A Pydantic model
class User(BaseModel):
    id: int
    name: str
    joined: date
```

که سپس میتوان به این شکل از آن استفاده کرد:

```Python
my_user: User = User(id=3, name="John Doe", joined="2018-07-19")

second_user_data = {
    "id": 4,

	FTP  []string
	SFTP []string

	MemLimit uint64

	UserTimeout         time.Duration
	IdleTimeout         time.Duration
	ReadHeaderTimeout   time.Duration
	MaxIdleConnsPerHost int

	SendBufSize, RecvBufSize int
	CrossDomainXML           string
	// The layout of disks as interpreted
	Layout disksLayout
}

var (
	// Global user opts context
	globalServerCtxt serverCtxt

            cb.query().addOrderBy_Term_Asc();
            cb.fetchFirst(ComponentUtil.getFessConfig().getPageRelatedqueryMaxFetchSizeAsInteger());
        });
    }

    @Override
    public int load() {
        final Map<String, Map<String, String[]>> relatedQueryMap = new HashMap<>();
        getAvailableRelatedQueryList().stream().forEach(entity -> {
            final String key = getHostKey(entity);

        assertNull(exception.getCause());
    }

    public void test_constructor_withLongMessage() {
        // Test constructor with long message
        StringBuilder sb = new StringBuilder();
        for (int i = 0; i < 1000; i++) {
            sb.append("Dictionary error ");
        }
        String longMessage = sb.toString();
        DictionaryException exception = new DictionaryException(longMessage);

      assertTrue(response.content.contains("Disallow"))
    } catch (ee: ExecutionException) {
      throw ee.cause?.cause ?: ee.cause!!
    }
  }

  data class Response(
    val code: Int,
    val negotiatedProtocol: String,
    val content: String,
  )

  private fun execute(
    engine: HttpEngine,
    executor: ExecutorService,
    url: String,
  ): CompletableFuture<Response> {