max_length=max_length,
            discriminator=discriminator,
            multiple_of=multiple_of,
            allow_nan=allow_inf_nan,
            max_digits=max_digits,
            decimal_places=decimal_places,
            **extra,
        )
        if examples is not None:
            kwargs["examples"] = examples
        if regex is not None:
            warnings.warn(

        Doc(
            """
            Maximum number of allow digits for strings.
            """
        ),
    ] = _Unset,
    decimal_places: Annotated[
        Union[int, None],
        Doc(
            """
            Maximum number of decimal places allowed for numbers.
            """
        ),
    ] = _Unset,
    examples: Annotated[
        Optional[List[Any]],
        Doc(

      r._elem.remove(testsuite._elem)
  if len(r) > 0:  # pylint: disable=g-explicit-length-test
    result += r

# Insert the number of failures for each test to help identify flakes
# need to clarify for shard
for p in result._elem.xpath(".//error | .//failure"):
  key = re.sub(r"0x\w+", "", p.getparent().get("name", "")) + p.text
  p.text = runfiles_matcher.sub("[testroot]/", p.text)

    # For example: https://$remotePilotAddress:15017/inject
    injectionURL: ""

  # Revision is set as 'version' label and part of the resource names when installing multiple control planes.
  revision: ""

  sidecarInjectorWebhook:
    # This enables injection of sidecar in all namespaces,

   * it is returned directly. Otherwise, a new array of size {@code minLength + padding} is
   * returned, containing the values of {@code array}, and zeroes in the remaining places.
   *
   * @param array the source array
   * @param minLength the minimum length the returned array must guarantee
   * @param padding an extra amount to "grow" the array by if growth is necessary

## Anwendungsfall

Beginnen wir mit einem Beispiel-**Anwendungsfall** und schauen uns dann an, wie wir ihn mit dieser Methode implementieren können.

* La variable `prices` es un `dict`:
    * Los keys de este `dict` son de tipo `str` (Digamos que son el nombre de cada ítem).
    * Los valores de este `dict` son de tipo `float` (Digamos que son el precio de cada ítem).

### Clases como tipos

También puedes declarar una clase como el tipo de una variable.

Digamos que tienes una clase `Person`con un nombre:

```Python hl_lines="1-3"
{!../../../docs_src/python_types/tutorial009.py!}

	//
	// NOTE that we are requeueing namespaces here explicitly to work around
	// test flakes with the fake kube client in `pkg/kube/client.go` -
	// because we are using `List()` in the handler, without this requeue,
	// the fake client will sometimes drop pod events leading to test flakes.
	//
	// WaitForCacheSync *helps*, but does not entirely fix this problem

  EXPECT_EQ(dltensor_out->ndim, dltensor_in->ndim);
  EXPECT_EQ(dltensor_out->dtype.code, dltensor_in->dtype.code);
  EXPECT_EQ(dltensor_out->dtype.bits, dltensor_in->dtype.bits);
  EXPECT_EQ(dltensor_out->dtype.lanes, dltensor_in->dtype.lanes);
  for (int i = 0; i < dltensor_in->ndim; ++i) {
    EXPECT_EQ(dltensor_out->shape[i], dltensor_in->shape[i]);
    if (dltensor_out->strides) {
      if (i == dltensor_in->ndim - 1) {

# General - How To - Recipes

Here are several pointers to other places in the docs, for general or frequent questions.

## Filter Data - Security

To ensure that you don't return more data than you should, read the docs for [Tutorial - Response Model - Return Type](../tutorial/response-model.md){.internal-link target=_blank}.

## Documentation Tags - OpenAPI