Sie können den Typ eines Pfad-Parameters in der Argumentliste der Funktion deklarieren, mit Standard-Python-Typannotationen:

{* ../../docs_src/path_params/tutorial002_py310.py hl[7] *}

In diesem Fall wird `item_id` als `int` deklariert, also als Ganzzahl.

/// check | Testen

Dadurch erhalten Sie Editor-Unterstützung innerhalb Ihrer Funktion, mit Fehlerprüfungen, Codevervollständigung, usw.

///

In diesem Fall werden sie auf alle *Pfadoperationen* in der Anwendung angewendet:

{* ../../docs_src/dependencies/tutorial012_an_py310.py hl[17] *}


Und alle Ideen aus dem Abschnitt über das [Hinzufügen von `dependencies` zu den *Pfadoperation-Dekoratoren*](dependencies-in-path-operation-decorators.md) gelten weiterhin, aber in diesem Fall für alle *Pfadoperationen* in der App.

    @Test
    @DisplayName("reauthenticate performs call without exception")
    void reauthenticate_happy() throws CIFSException {
        session.reauthenticate();
        verify(session).reauthenticate();
    }

    // Error propagation: reauthenticate throws CIFSException
    @Test
    @DisplayName("reauthenticate throws CIFSException when underlying call fails")
    void reauthenticate_throws() throws CIFSException {

{* ../../docs_src/body_multiple_params/tutorial001_an_py310.py hl[18:20] *}

/// note | Hinweis

Beachten Sie, dass in diesem Fall das `item`, welches vom Body genommen wird, optional ist. Da es `None` als Defaultwert hat.

///

## Mehrere Body-Parameter { #multiple-body-parameters }

        Field infoField = msrpcShareGetInfo.getClass().getSuperclass().getDeclaredField("info");
        infoField.setAccessible(true);
        infoField.set(msrpcShareGetInfo, info502);

        // Call getSecurity multiple times - should return consistent results
        ACE[] result1 = msrpcShareGetInfo.getSecurity();
        ACE[] result2 = msrpcShareGetInfo.getSecurity();

        // Both should be null (no DACL)

  auto tf_dlm_type = GetDlDataType(data_type, status);
  if (!status->status.ok()) {
    return nullptr;
  }

  TensorReference tensor_ref(*tensor);  // This will call buf_->Ref()
  auto* tf_dlm_tensor_ctx = new TfDlManagedTensorCtx(tensor_ref);
  tf_dlm_tensor_ctx->reference = tensor_ref;

  DLManagedTensor* dlm_tensor = &tf_dlm_tensor_ctx->tensor;

if NOT "%FESS_HEAP_SIZE%" == "" set FESS_MIN_MEM=%FESS_HEAP_SIZE%
if NOT "%FESS_HEAP_SIZE%" == "" set FESS_MAX_MEM=%FESS_HEAP_SIZE%

call:convertxm %FESS_MIN_MEM% JVM_XMS
call:convertxm %FESS_MAX_MEM% JVM_XMX

CALL "%FESS_HOME%\bin\fess.in.bat"

rem thread stack size
set JVM_SS=256

    return backingMap.get(element);
  }

  // Optional Operations - Modification Operations

  /**
   * {@inheritDoc}
   *
   * @throws IllegalArgumentException if the call would result in more than {@link
   *     Integer#MAX_VALUE} occurrences of {@code element} in this multiset.
   */
  @CanIgnoreReturnValue
  @Override
  public final int add(@ParametricNullness E element, int occurrences) {

        SmbFile parent = newParent();
        List<FileEntry> entries = Arrays.asList(entry("bad", SmbConstants.TYPE_SHARE), entry("good", SmbConstants.TYPE_SHARE));

        // First call throws, second accepts
        when(filter.accept(any())).thenThrow(new CIFSException("boom")).thenReturn(true);

        ShareEnumIterator it = new ShareEnumIterator(parent, entries.iterator(), filter);

        I end up not being able to add new features, fix bugs, review pull requests, etc. as fast as I wish because I have to spend too much time handling questions.

        All that, on top of all the incredible help provided by a bunch of community members, the [FastAPI Experts](https://fastapi.tiangolo.com/fastapi-people/#experts), that give a lot of their time to come here and help others.