Sie können beispielsweise kein Pydantic-Modell in eine `JSONResponse` einfügen, ohne es zuvor in ein `dict` zu konvertieren, bei dem alle Datentypen (wie `datetime`, `UUID`, usw.) in JSON-kompatible Typen konvertiert wurden.

In diesen Fällen können Sie den `jsonable_encoder` verwenden, um Ihre Daten zu konvertieren, bevor Sie sie an eine Response übergeben:

{* ../../docs_src/response_directly/tutorial001.py hl[6:7,21:22] *}

        SmbTreeConnectionTrace wrapper = new SmbTreeConnectionTrace(delegate);
        wrapper.acquire();
        wrapper.release();

        // Assert: delegate interactions occur when usage transitions happen
        verify(delegate, times(1)).acquire();
        verify(delegate, times(1)).release();
    }

    @Test
    @DisplayName("finalize() invokes checkRelease exactly once")

///

## `Annotated` im Typ des `q`-Parameters verwenden

Erinnern Sie sich, wie ich in [Einführung in Python-Typen](../python-types.md#typhinweise-mit-metadaten-annotationen){.internal-link target=_blank} sagte, dass Sie mittels `Annotated` Metadaten zu Ihren Parametern hinzufügen können?

Jetzt ist es an der Zeit, das mit FastAPI auszuprobieren. 🚀

        if (options.sessionId != null) {
            options.sessionId = options.sessionId.replaceAll("-", "_");
        }

        // Check that sessionId was sanitized (hyphens replaced with underscores)
        assertEquals("test_session_123", options.sessionId);
    }

    public void test_process_withPropertiesPath() throws Exception {
        // Test that properties path is properly handled

        // Act
        int responseCode = ntlmConnection.getResponseCode();

        // Assert
        assertEquals(HTTP_UNAUTHORIZED, responseCode);
        // Since we don't use NTLM, no reconnection should happen
    }

    /**
     * Test that getOutputStream() returns a CacheStream that wraps the underlying stream.
     * @throws IOException
     */
    @Test

    for (int i = 0; i < 2; i++) {
      try {
        memoizedSupplier.get();
        fail("failed to throw NullPointerException");
      } catch (NullPointerException e) {
        // this is what should happen
      }
    }
  }

  @J2ktIncompatible
  @GwtIncompatible // SerializableTester
  public void testMemoizeNonSerializable() throws Exception {
    CountingSupplier countingSupplier = new CountingSupplier();

Since HTTP requests frequently happen in parallel, connection pooling must be thread-safe.

These are the primary classes involved with establishing, sharing, and terminating connections:

    try {
      in.copyTo(out);
      fail();
    } catch (IOException expected) {
      return expected.getSuppressed().length;
    }
    throw new AssertionError(); // can't happen
  }

  private static CharSource newNormalCharSource() {
    return CharSource.wrap("ABC");
  }

  private static CharSink newNormalCharSink() {
    return new CharSink() {
      @Override

<img src="/img/tutorial/body/image02.png">

## Editor support { #editor-support }

In your editor, inside your function you will get type hints and completion everywhere (this wouldn't happen if you received a `dict` instead of a Pydantic model):

<img src="/img/tutorial/body/image03.png">

You also get error checks for incorrect type operations:

<img src="/img/tutorial/body/image04.png">

        when(cfg.getBufferCacheSize()).thenReturn(2);
        when(cfg.getMaximumBufferSize()).thenReturn(5);

        BufferCacheImpl impl = new BufferCacheImpl(cfg);

        // Verify interactions happen exactly once during construction
        verify(cfg, times(1)).getBufferCacheSize();
        verify(cfg, times(1)).getMaximumBufferSize();
        verifyNoMoreInteractions(cfg);