out.write(data);
    assertThat(source.read()).isEqualTo(data);

    out.close();
    assertThrows(IOException.class, () -> out.write(42));

    // Verify that write had no effect
    assertThat(source.read()).isEqualTo(data);
    out.reset();
  }

  public void testReset() throws Exception {
    byte[] data = newPreFilledByteArray(100);

{* ../../docs_src/body_nested_models/tutorial003_py310.py hl[12] *}

With this, even if you receive a request with duplicate data, it will be converted to a set of unique items.

And whenever you output that data, even if the source had duplicates, it will be output as a set of unique items.

And it will be annotated / documented accordingly too.

## Nested Models { #nested-models }

Each attribute of a Pydantic model has a type.

In the previous example, because the classes were different, we had to use the `response_model` parameter. But that also means that we don't get the support from the editor and tools checking the function return type.

   * @since 19.0
   */
  Map<Range<K>, V> asDescendingMapOfRanges();

  /**
   * Returns a view of the part of this range map that intersects with {@code range}.
   *
   * <p>For example, if {@code rangeMap} had the entries {@code [1, 5] => "foo", (6, 8) => "bar",
   * (10, ∞) => "baz"} then {@code rangeMap.subRangeMap(Range.open(3, 12))} would return a range map
   * with the entries {@code (3, 5] => "foo", (6, 8) => "bar", (10, 12) => "baz"}.

			writeErrorResponse(ctx, w, toAPIError(ctx, err), r.URL)
			return
		}
		for _, rl := range lcCfg.Rules {
			updRule, ok := updatedRules[rl.ID]
			// original rule had expiry that is no longer in the new config,
			// or rule is present but missing expiration flags
			if (!rl.Expiration.IsNull() || !rl.NoncurrentVersionExpiration.IsNull()) &&

   * statistics had been added directly.
   */
  public void addAll(Stats values) {
    if (values.count() == 0) {
      return;
    }
    merge(values.count(), values.mean(), values.sumOfSquaresOfDeltas(), values.min(), values.max());
  }

  /**
   * Adds the given statistics to the dataset, as if the individual values used to compute the
   * statistics had been added directly.
   *

 for use in elements like the <developerConnection/>. It would be idea if we
 could encapsulate everything we need about the project in the POM including
 plugin parameters and anything else.

 We once had a document that Vincent and I agreed upon and I was about to
 implement it and then I disappeared for 8 months so it never came to pass.

 So I guess it's important to figure out what people are using properties

* and in there, find the module `dependencies` (the file at `app/dependencies.py`)...
* and from it, import the function `get_token_header`.

That works correctly! 🎉

---

The same way, if we had used three dots `...`, like in:

```Python
from ...dependencies import get_token_header
```

that would mean:

  /** Though this executor service may hold many threads, they are not executed concurrently. */
  private val tasksExecutor = Executors.newCachedThreadPool(threadFactory("TaskFaker"))

  /**
   * True if this task faker has ever had multiple tasks scheduled to run concurrently. Guarded by
   * `this`.
   */
  var isParallel = false

  /** Number of calls to [TaskRunner.Backend.execute]. Guarded by `this`. */
  var executeCallCount = 0

    }
    cache.invalidateAll();
    tasksFinished.await();

    // Check all of the removal notifications we received: they should have had correctly-associated
    // keys and values. (An earlier bug saw removal notifications for in-progress computations,
    // which had real keys with null values.)
    Map<String, String> removalNotifications = new HashMap<>();
    for (RemovalNotification<String, String> notification : listener) {