TestScriptEngine engine1 = new TestScriptEngine("first");
        TestScriptEngine engine2 = new TestScriptEngine("second");

        scriptEngineFactory.add("test", engine1);
        scriptEngineFactory.add("test", engine2);

        // Should get the second engine
        ScriptEngine retrieved = scriptEngineFactory.getScriptEngine("test");
        assertEquals(engine2, retrieved);
    }

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

此處，`new_dict` 會包含 `old_dict` 的所有鍵值配對，再加上新的鍵值配對：

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

你可以用這個技巧在「路徑操作」中重用一些預先定義的回應，並與其他自訂回應結合。

    }

    /**
     * Sets the minimum number of seconds that a response will continue to be fresh for. If the
     * response will be stale when [minFresh] have elapsed, the cached response will not be used and
     * a network request will be made.
     *
     * @param minFresh a non-negative integer. This is stored and transmitted with
     *     [TimeUnit.SECONDS] precision; finer precision will be lost.
     */

package com.google.common.util.concurrent;

import static com.google.common.util.concurrent.MoreExecutors.directExecutor;
import static java.util.concurrent.Executors.newCachedThreadPool;
import static java.util.concurrent.TimeUnit.SECONDS;

import com.google.common.annotations.GwtIncompatible;
import com.google.common.annotations.J2ktIncompatible;
import com.google.common.testing.NullPointerTester;
import java.util.concurrent.CountDownLatch;

	if m.expMovingAvg == 0 {
		// Should address initial calculation and should be fine for resuming from 0
		m.expMovingAvg = float64(bytesSinceLastWindow) / duration.Seconds()
		return
	}

	increment := float64(bytesSinceLastWindow) / duration.Seconds()
	m.expMovingAvg = exponentialMovingAverage(betaBucket, m.expMovingAvg, increment)
}

// exponentialMovingAverage calculates the exponential moving average

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

Burada `new_dict`, `old_dict` içindeki tüm key-value çiftlerini ve buna ek olarak yeni key-value çiftini içerir:

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

    if (attr.first == "dtype") {
      if (attr.second.type() == tensorflow::DT_INT32) {
        found_dtype = true;
      } else {
        return false;
      }
    } else if (attr.first == "value") {
      if (attr.second.has_tensor() &&
          attr.second.tensor().int_val_size() == 1 &&
          attr.second.tensor().int_val(0) == v) {
        found_value = true;
      } else {

      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

        byte[] first = impl.getBuffer(); // should return slot 0 -> a
        byte[] second = impl.getBuffer(); // then slot 1 -> c
        byte[] third = impl.getBuffer(); // cache empty -> new with size 3

        assertSame(a, first, "First get should return first cached buffer");
        assertSame(c, second, "Second get should return second cached buffer");

	driveCountMD = NewGaugeMD(driveCount,
		"Count of all drives")

	// iostat related
	driveReadsPerSecMD = NewGaugeMD(driveReadsPerSec,
		"Reads per second on a drive",
		allDriveLabels...)
	driveReadsKBPerSecMD = NewGaugeMD(driveReadsKBPerSec,
		"Kilobytes read per second on a drive",
		allDriveLabels...)
	driveReadsAwaitMD = NewGaugeMD(driveReadsAwait,
		"Average time for read requests served on a drive",
		allDriveLabels...)