// Note: Real SmbTransportImpl will report as disconnected without actual socket
        SmbTransportImpl second = testPool.getSmbTransport(ctx, address, 445, false);

        // Then: Will create new connection since real transport has no socket
        assertNotSame(first, second, "Should create new connection when first is disconnected");
    }

    @Test

                .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);

	input := `{"id": 0,"title": "Test Record","desc": "Some text","synonyms": ["foo", "bar", "whatever"]}
	{"id": 1,"title": "Second Record","desc": "another text","synonyms": ["some", "synonym", "value"]}
	{"id": 2,"title": "Second Record","desc": "another text","numbers": [2, 3.0, 4]}
	{"id": 3,"title": "Second Record","desc": "another text","nested": [[2, 3.0, 4], [7, 8.5, 9]]}`

	testTable := []struct {
		name       string

   * that would have been produced in that idle time). So, if rate == 1 permit per second, and
   * arrivals come exactly one second after the previous, then storedPermits is _never_ increased --
   * we would only increase it for arrivals _later_ than the expected one second.
   */

  /**
   * This implements the following function where coldInterval = coldFactor * stableInterval.
   *

        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。

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

Aqui, o `new_dict` terá todos os pares de chave-valor do `old_dict` mais o novo par de chave-valor:

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

        List<LogNotificationEvent> first = helper.drainAll();
        assertEquals(1, first.size());
        List<LogNotificationEvent> second = helper.drainAll();
        assertTrue(second.isEmpty());
    }

    @Test
    public void test_offer_bufferCapacity() {
        LogNotificationHelper helper = new LogNotificationHelper();

```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 {