Dekorator-`dependencies`

Auf die gleiche Weise können Sie eine `list`e von `Depends` im Parameter `dependencies` des Dekorators definieren (wie in [Abhängigkeiten in Pfadoperation-Dekoratoren](../../tutorial/dependencies/dependencies-in-path-operation-decorators.md){.internal-link target=_blank} erläutert), Sie könnten auch dort `Security` mit `scopes` verwenden....

Kullanım şekli oldukça basit. Örneğin bir `GET` isteği yapmak için aşağıdaki yeterli:

```Python
response = requests.get("http://example.com/some/url")
```

Bunun FastAPI'deki API <abbr title="Yol İşlemi: Path Operation">*yol işlemi*</abbr> şöyle görünür:

```Python hl_lines="1"
@app.get("/some/url")
def read_url():
    return {"message": "Hello World!"}
```

				return info, toStorageErr(errors.New(info.Error))
			}
			return info, nil
		},
	)

	return client.diskInfoCache.GetWithCtx(ctx)
}

// MakeVolBulk - create multiple volumes in a bulk operation.
func (client *storageRESTClient) MakeVolBulk(ctx context.Context, volumes ...string) (err error) {
	return errInvalidArgument
}

// MakeVol - create a volume on a remote disk.

    *   Added a new `rerandomize_each_iteration` argument for the `tf.data.Dataset.random()` operation, which controls whether the sequence of generated random numbers should be re-randomized every epoch or not (the default behavior). If `seed` is set and `rerandomize_each_iteration=True`, the `random()` operation will produce a different (deterministic) sequence of numbers every epoch.

  // 'inputFuture'. That field is non-final and non-volatile. There are 2 places where the
  // 'inputFuture' field is read and where we will have to consider visibility of the write
  // operation in the constructor.
  //
  // 1. In the listener that performs the callback. In this case it is fine since inputFuture is
  //    assigned prior to calling addListener, and addListener happens-before any invocation of the

  // This can be used to provide different probe parameters at the beginning of a Pod's lifecycle,
  // when it might take a long time to load data or warm a cache, than during steady-state operation.
  // This cannot be updated.
  // More info: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle#container-probes
  // +optional
  optional Probe startupProbe = 22;

               second_negative_one.get(), status.get()));
  ASSERT_EQ(TF_GetCode(status.get()), TF_OK) << TF_Message(status.get());

  // Un-pack the parallel tensor to verify that the operation was
  // successful. The resulting structure should be:
  //   second_device{first_device{1. * 3., 2. * 3.}, 3. * 3.}.
  std::array<TensorHandlePtr, 2> second_components;

*   [Java license example](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/java/src/main/java/org/tensorflow/Graph.java#L1)
*   [Go license example](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/go/operation.go#L1)
*   [Bash license example](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/ci_build/ci_build.sh#L2)

     * changing any bin. The operations must not take any action that could even momentarily
     * cause a concurrent read operation to see inconsistent data. This is made easier by the
     * nature of the read operations in Map. For example, no operation can reveal that the table
     * has grown but the threshold has not yet been updated, so there are no atomicity requirements
     * for this with respect to reads.

		groupSet.Add(k)
		return true
	})

	return groupSet.ToSlice(), nil
}

// ListGroups - lists groups. Since this is not going to be a frequent
// operation, we fetch this info from storage, and refresh the cache as well.
func (store *IAMStoreSys) ListGroups(ctx context.Context) (res []string, err error) {
	cache := store.lock()
	defer store.unlock()