///

## OpenAPI and API docs { #openapi-and-api-docs }

If you return additional status codes and responses directly, they won't be included in the OpenAPI schema (the API docs), because FastAPI doesn't have a way to know beforehand what you are going to return.

        verify(supplier, times(1)).get();
        verifyNoMoreInteractions(supplier);
    }

    @Test
    @DisplayName("No collaborator interaction occurs if exception is thrown beforehand")
    void noInteraction_whenExceptionOccursBeforeCall() {
        // Arrange
        Runnable r = mock(Runnable.class);

        void testToStringAfterReadingData() {
            byte[] buffer = createValidDfsReferralBuffer();
            String beforeRead = response.toString();

            response.readDataWireFormat(buffer, 0, buffer.length);
            String afterRead = response.toString();

            assertNotEquals(beforeRead, afterRead);
            assertTrue(afterRead.contains("pathConsumed="));

## Bodies of arbitrary `dict`s { #bodies-of-arbitrary-dicts }

You can also declare a body as a `dict` with keys of some type and values of some other type.

This way, you don't have to know beforehand what the valid field/attribute names are (as would be the case with Pydantic models).

This would be useful if you want to receive keys that you don't already know.

---

This is useful if you don't know the valid field/attribute names (that would be needed for a Pydantic model) beforehand.

In this case, you can use `typing.Dict` (or just `dict` in Python 3.9 and above):

{* ../../docs_src/extra_models/tutorial005_py39.py hl[6] *}

## Recap { #recap }

        when(cfg.isTraceResourceUsage()).thenReturn(false);
        stubValidTree(3L, true, true);
        SmbFileHandleImpl h = new SmbFileHandleImpl(cfg, 9, tree, "//x", 0, 0, 0, 0, 0L);

        // Make invalid beforehand
        when(tree.isConnected()).thenReturn(false);
        h.close();

        verify(tree, never()).send(isA(Smb2CloseRequest.class), any());

*   Hot-fix was needed for an issue affecting the TensorFlow installation
    process.
    *   TensorFlow 2.15.0 Python package was requesting `tensorrt`-related
        packages that cannot be found unless the user installs them beforehand
        or provides additional installation flags.
    *   This dependency affected anyone installing TensorFlow 2.15 alongside
        NVIDIA CUDA dependencies via `pip install tensorflow[and-cuda]`.