input.put("foo", 1);
    input.put("bar", 2);
    input.put("foo", 3);
    input.put("foo", 1);
    ImmutableListMultimap<String, Integer> multimap = ImmutableListMultimap.copyOf(input);
    new EqualsTester().addEqualityGroup(input, multimap).testEquals();
  }

  public void testCopyOfEmpty() {
    ArrayListMultimap<String, Integer> input = ArrayListMultimap.create();

                                    /*remote_func_outputs=*/true);
}
TEST(CAPI, RemoteExecuteSilentCopiesLocalAsyncFuncOrdering) {
  // A remote input may be not ready when we start running a function. Test that
  // the function execution should wait until the remote input is ready.
  TestRemoteExecuteSilentCopiesFunc(/*async=*/true, /*remote=*/false,
                                    /*heavy_load_on_streaming_rpc=*/true);
}

     * requires some work.
     */

    return Collector.of(
        ImmutableTableCollectorState<R, C, V>::new,
        (state, input) ->
            state.put(
                rowFunction.apply(input),
                columnFunction.apply(input),
                valueFunction.apply(input),
                mergeFunction),
        (s1, s2) -> s1.combine(s2, mergeFunction),
        state -> state.toTable());
  }

  static <

  static <I extends @Nullable Object, O extends @Nullable Object> ListenableFuture<O> createAsync(
      ListenableFuture<I> input,
      AsyncFunction<? super I, ? extends O> function,
      Executor executor) {
    AsyncTransformFuture<I, O> output = new AsyncTransformFuture<>(input, function);
    input.addListener(output, rejectionPropagatingExecutor(executor, output));
    return output;
  }

    }

    /**
     * Memoizes a given function that takes a String input and produces a String output.
     * This method creates a new function that caches the results of the original function,
     * improving performance for repeated calls with the same input.
     *
     * @param callback The original function to be memoized. It takes a String as input and returns a String.

            throw new IORuntimeException(e);
        }
    }

    /**
     * Gets a byte array from an {@link InputStream}.
     * <p>
     * The input stream is not closed.
     * </p>
     *
     * @param is the input stream (must not be {@literal null})
     * @return the byte array
     */
    public static final byte[] getBytes(final InputStream is) {
        assertArgumentNotNull("is", is);

    assert response.json() == {
        "detail": [
            {
                "type": "int_parsing",
                "loc": ["body", "age"],
                "msg": "Input should be a valid integer, unable to parse string as an integer",
                "input": "seventy",
            }
        ]
    }


def test_no_data():
    response = client.post("/form/")
    assert response.status_code == 422, response.text

type PReader struct {
	args        *ReaderArgs
	readCloser  io.ReadCloser             // raw input
	buf         *bufio.Reader             // input to the splitter
	current     []jstream.KVS             // current block of results to be returned
	recordsRead int                       // number of records read in current slice
	input       chan *queueItem           // input for workers
	queue       chan *queueItem           // output from workers in order

        this.isWindowsVM = false;
    }

    @Input
    public String getBox() {
        return box.get();
    }

    public void setBox(String box) {
        // TODO: should verify this against the Vagrantfile, but would need to do so in afterEvaluate once vagrantfile is unmodifiable
        this.box.set(box);
    }

    @Input
    public Map<String, Object> getHostEnv() {
        return hostEnv.get();

自從 Pydantic v2 發佈後，生成的 OpenAPI 比以往更精確也更正確。😎

實際上，在某些情況下，同一個 Pydantic 模型在 OpenAPI 中會同時有兩個 JSON Schema：分別用於輸入與輸出，這取決於它是否有預設值。

來看看它如何運作，以及若需要時該如何調整。

## 作為輸入與輸出的 Pydantic 模型 { #pydantic-models-for-input-and-output }

假設你有一個帶有預設值的 Pydantic 模型，如下所示：

{* ../../docs_src/separate_openapi_schemas/tutorial001_py310.py ln[1:7] hl[7] *}

### 輸入用模型 { #model-for-input }

如果你把這個模型用作輸入，如下所示：