要使 `await` 工作，它必须位于支持这种异步机制的函数内。因此，只需使用 `async def` 声明它：

```Python hl_lines="1"
async def get_burgers(number: int):
    # Do some asynchronous stuff to create the burgers
    return burgers
```

...而不是 `def`:

```Python hl_lines="2"
# This is not asynchronous
def get_sequential_burgers(number: int):
    # Do some sequential stuff to create the burgers
    return burgers
```

	var buffer bytes.Buffer
	// data to be written into buffer.
	data := "1234567890"
	// seed the random number generator once.
	rand.Seed(3)
	// generate a random number between 13 and 200.
	randInt := getRandomRange(13, 200, -1)
	// write into buffer till length of the buffer is greater than the generated random number.
	for i := 0; i <= randInt; i += 10 {
		buffer.WriteString(data)
	}

    * objets JSON (`dict`).
    * listes JSON (`list`) définissant des types d'éléments.
    * Champs String (`str`), définition de longueur minimum ou maximale.
    * Nombres (`int`, `float`) avec valeur minimale and maximale, etc.

* Validation pour des types plus exotiques, tel que:
    * URL.
    * Email.
    * UUID.
    * ...et autres.

is the initial Agreement Steward. The Eclipse Foundation may assign the
responsibility to serve as the Agreement Steward to a suitable separate
entity. Each new version of the Agreement will be given a distinguishing
version number. The Program (including Contributions) may always be
Distributed subject to the version of the Agreement under which it was
received. In addition, after a new version of the Agreement is published,

///

### Evitar colisiones de nombres { #avoid-name-collisions }

Estamos importando el submódulo `items` directamente, en lugar de importar solo su variable `router`.

Esto se debe a que también tenemos otra variable llamada `router` en el submódulo `users`.

			if pctUsed := int(disk.Used * 100 / disk.Total); pctUsed > maxUsedPct {
				maxUsedPct = pctUsed
			}
		}

		// Since we are comparing pools that may have a different number of sets
		// we multiply by the number of sets in the pool.
		// This will compensate for differences in set sizes
		// when choosing destination pool.
		// Different set sizes are already compensated by less disks.

Hierbei können Sie **Typannotationen** genauso verwenden, wie Sie es bei Werten von Funktions-**Parametern** machen; verwenden Sie Pydantic-Modelle, Listen, Dicts und skalare Werte wie Nummern, Booleans, usw.

{* ../../docs_src/response_model/tutorial001_01_py310.py hl[16,21] *}

FastAPI wird diesen Rückgabetyp verwenden, um:

* Die zurückzugebenden Daten zu **validieren**.

        InvalidArgument("Node ", node->name(), " was not found in the graph");
    return -1;
  }

  tensorflow::shape_inference::ShapeHandle shape = ic->output(output.index);

  // Unknown rank means the number of dimensions is -1.
  if (!ic->RankKnown(shape)) {
    return -1;
  }

  return ic->Rank(shape);
}

void TF_GraphGetTensorShape(TF_Graph* graph, TF_Output output, int64_t* dims,

pkg go/doc/comment, type List struct, Items []*ListItem #51082
pkg go/doc/comment, type ListItem struct #51082
pkg go/doc/comment, type ListItem struct, Content []Block #51082
pkg go/doc/comment, type ListItem struct, Number string #51082
pkg go/doc/comment, type Paragraph struct #51082
pkg go/doc/comment, type Paragraph struct, Text []Text #51082
pkg go/doc/comment, type Parser struct #51082

			expectedError: hash.BadDigest{ExpectedMD5: invalidMD5, CalculatedMD5: getMD5Hash(fiveMBBytes)},
		},

		// data with size different from the actual number of bytes available in the reader
		26: {bucketName: bucket, objName: object, inputData: data, inputDataSize: int64(len(data) - 1), expectedMd5: getMD5Hash(data[:len(data)-1]), expectedError: ioutil.ErrOverread},