implements Serializable {
    final Converter<A, B> first;
    final Converter<B, C> second;

    ConverterComposition(Converter<A, B> first, Converter<B, C> second) {
      this.first = first;
      this.second = second;
    }

    /*
     * These gymnastics are a little confusing. Basically this class has neither legacy nor

                .insert(EncodeTensorNameSlice(
                    string(v2_reader_->key()) /* full var's name */,
                    TensorSlice(slice_proto)))
                .second);
    }
  }

  // Second pass: adds the entries, ignoring the filtered keys.
  std::unique_ptr<TensorSliceReader::VarToShapeMap> var_to_shape_map(
      new TensorSliceReader::VarToShapeMap);

package cmd

import (
	"context"
	"time"
)

var sharedLockTimeout = newDynamicTimeoutWithOpts(dynamicTimeoutOpts{
	timeout:       30 * time.Second,
	minimum:       10 * time.Second,
	retryInterval: time.Minute,
})

type sharedLock struct {
	lockContext chan LockContext
}

func (ld sharedLock) backgroundRoutine(ctx context.Context, objAPI ObjectLayer, lockName string) {

	}
	return target.send(eventData)
}

// send - sends an event to the Nats.
func (target *NATSTarget) send(eventData event.Event) error {
	objectName, err := url.QueryUnescape(eventData.S3.Object.Key)
	if err != nil {
		return err
	}
	key := eventData.S3.Bucket.Name + "/" + objectName

	data, err := json.Marshal(event.Log{EventName: eventData.EventName, Key: key, Records: []event.Event{eventData}})
	if err != nil {

   * as a false predicate is found.
   *
   * <p><b>Discouraged:</b> Prefer using {@code first.and(second)}.
   */
  public static <T extends @Nullable Object> Predicate<T> and(
      Predicate<? super T> first, Predicate<? super T> second) {
    return new AndPredicate<>(Predicates.<T>asList(checkNotNull(first), checkNotNull(second)));
  }

  /**

```Python
old_dict = {
    "old key": "old value",
    "second old key": "second old value",
}
new_dict = {**old_dict, "new key": "new value"}
```

Ici, `new_dict` contiendra toutes les paires clé-valeur de `old_dict` plus la nouvelle paire clé-valeur :

```Python
{
    "old key": "old value",
    "second old key": "second old value",
    "new key": "new value",
}
```

            Map<String, String> orderedMap = new LinkedHashMap<>();
            orderedMap.put("third", "3");
            orderedMap.put("first", "1");
            orderedMap.put("second", "2");

            // Create model and set properties
            Model model = new Model();
            Properties props = model.getProperties();

对于这些情况，你可以使用Python的技术，将 `dict` 与 `**dict_to_unpack` 解包：
```Python
old_dict = {
    "old key": "old value",
    "second old key": "second old value",
}
new_dict = {**old_dict, "new key": "new value"}
```

这里， new_dict 将包含来自 old_dict 的所有键值对加上新的键值对：
```python
{
    "old key": "old value",
    "second old key": "second old value",
    "new key": "new value",
}
```
您可以使用该技术在路径操作中重用一些预定义的响应，并将它们与其他自定义响应相结合。
**例如：**

        // Second call - should use cache
        long start2 = System.nanoTime();
        helper.setProperty(bean2, "name", String.class, config);
        long time2 = System.nanoTime() - start2;

        assertEquals("testValue", bean1.getName());
        assertEquals("testValue", bean2.getName());

        // Second call should be faster (though this is not guaranteed in all environments)

            });
    }

    private static <T> Map<AccessorKey, T> diff(Map<AccessorKey, T> first, Map<AccessorKey, T> second) {
        return first.entrySet().stream()
            .filter(e -> !second.containsKey(e.getKey()))
            .collect(Collectors.toMap(Map.Entry::getKey, Map.Entry::getValue));
    }