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

Here, `new_dict` will contain all the key-value pairs from `old_dict` plus the new key-value pair:

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

    List<E> subArray = asList(array).subList(0, getNumElements());
    E[] expectedSubArray = createSamplesArray();
    for (int i = 0; i < getNumElements(); i++) {
      assertTrue(
          "toArray(overSizedE[]) should contain element " + expectedSubArray[i],
          subArray.contains(expectedSubArray[i]));
    }
    assertNull(
        "The array element immediately following the end of the collection should be nulled",

 * given key agrees with the order in which the values were added.
 *
 * <p>This multimap allows duplicate key-value pairs. After adding a new key-value pair equal to an
 * existing key-value pair, the {@code ArrayListMultimap} will contain entries for both the new
 * value and the old value.
 *
 * <p>Keys and values may be null. All optional multimap methods are supported, and all returned
 * views are modifiable.
 *

   * {@code EnumHashBiMap} or an {@link EnumBiMap}, the new bimap has the same key type as the input
   * bimap. Otherwise, the specified map must contain at least one mapping, in order to determine
   * the key type.
   *
   * @param map the map whose mappings are to be placed in this map

        List<String> nameList = List.of(names);
        assertTrue(nameList.contains("file1.txt"), "Should contain file1.txt");
        assertTrue(nameList.contains("file2.txt"), "Should contain file2.txt");
        assertTrue(nameList.contains("subdir") || nameList.contains("subdir/"), "Should contain subdir");
    }

    @Test
    void testDirectoryDeletion() throws Exception {

      pool.shutdownNow();
    }

    // Since we have access to the backing map, verify that there are no zeroes in the map
    for (AtomicInteger value : map.values()) {
      assertTrue("map should not contain a zero", value.get() != 0);
    }
  }

  private static class MutateTask implements Callable<int[]> {
    private final ConcurrentHashMultiset<String> multiset;
    private final ImmutableList<String> keys;

        SmbException exception = new SmbException("Test exception");

        // Then
        assertNotNull(exception.getStackTrace());
        assertTrue(exception.getStackTrace().length > 0);

        // Should contain this test method in stack trace
        boolean foundTestMethod = false;
        for (StackTraceElement element : exception.getStackTrace()) {
            if (element.getMethodName().contains("testStackTracePreservation")) {

/// tip

Keep in mind that JSON only supports `str` as keys.

But Pydantic has automatic data conversion.

This means that, even though your API clients can only send strings as keys, as long as those strings contain pure integers, Pydantic will convert them and validate them.

And the `dict` you receive as `weights` will actually have `int` keys and `float` values.

///

## Recap { #recap }

	if extractedExpect != expectedExpect {
		t.Errorf("expect header incorrect value: expected `%s`, got `%s`", expectedExpect, extractedExpect)
	}

	// case where the headers don't contain the one of the signed header in the signed headers list.
	signedHeaders = append(signedHeaders, "X-Amz-Credential")
	// expected to fail with `ErrUnsignedHeaders`.
	_, errCode = extractSignedHeaders(signedHeaders, r)

      return false
    }

    // Normalize hostname and pattern by turning them into absolute domain names if they are not
    // yet absolute. This is needed because server certificates do not normally contain absolute
    // names or patterns, but they should be treated as absolute. At the same time, any hostname
    // presented to this method should also be treated as absolute for the purposes of matching