Map<String, Object> doc = new HashMap<>();

        Map<String, Object> nestedMap = new HashMap<>();
        nestedMap.put("nestedKey", "nestedValue");
        doc.put("nested", nestedMap);

        List<Map<String, Object>> listOfMaps = new ArrayList<>();
        listOfMaps.add(nestedMap);
        doc.put("listOfMaps", listOfMaps);

        // Should return null when no clauses are added
        assertNull(result);
    }

    // Test convertBooleanQuery with nested BooleanQuery
    public void test_convertBooleanQuery_withNestedBooleanQuery() {
        // Create inner BooleanQuery
        BooleanQuery.Builder innerBoolQueryBuilder = new BooleanQuery.Builder();

   *     minValue()}
   */
  public abstract @Nullable C previous(C value);

  /**
   * Returns a signed value indicating how many nested invocations of {@link #next} (if positive) or
   * {@link #previous} (if negative) are needed to reach {@code end} starting from {@code start}.

A group's DN may be associated with an [access policy](#managing-usergroup-access-policy).

#### Nested groups usage in LDAP/AD
If you are using Active directory with nested groups you have to add LDAP_MATCHING_RULE_IN_CHAIN: :1.2.840.113556.1.4.1941: to your query.
For example:
```shell

  public void testLenientFormat_badArgumentToString() {
    assertThat(Strings.lenientFormat("boiler %s plate", new ThrowsOnToString()))
        .matches(
            // J2kt nested class name does not use "$"
            "boiler <com\\.google\\.common\\.base\\.StringsTest[.$]ThrowsOnToString@[0-9a-f]+ "
                + "threw java\\.lang\\.UnsupportedOperationException> plate");
  }

Você também poderá receber verificações de erros para operações de tipos incorretas:

<img src="/img/tutorial/body/image04.png">

Isso não é por acaso, todo o framework foi construído em volta deste design.

E foi imensamente testado na fase de design, antes de qualquer implementação, para garantir que funcionaria para todos os editores de texto.

Houveram mudanças no próprio Pydantic para que isso fosse possível.

 *
 * This class provides methods to normalize text by reading characters from a provided Reader
 * and processing them according to specific rules. The main functionality is encapsulated
 * within the nested {@link TextNormalizeContext} class.
 *
 * <p>The text normalization process includes:
 * <ul>
 *   <li>Treating ISO control characters and specified space characters as spaces.</li>

///

### Editor-ondersteuning

Het gehele framework is ontworpen om eenvoudig en intuïtief te zijn in gebruik. Alle beslissingen zijn getest op meerdere code-editors nog voordat het daadwerkelijke ontwikkelen begon, om zo de beste ontwikkelervaring te garanderen.

You could also access the value `"lenet"` with `ModelName.lenet.value`.

///

#### Return *enumeration members* { #return-enumeration-members }

You can return *enum members* from your *path operation*, even nested in a JSON body (e.g. a `dict`).

They will be converted to their corresponding values (strings in this case) before returning them to the client:

{* ../../docs_src/path_params/tutorial005.py hl[18,21,23] *}

// does various checks while doing so. `input_nodes` will contain the same
// information as input_tensors just in a different structure to make
// following processing easier. TODO(iga): Simplify this nested structure.
absl::Status ProcessInputs(
    const TF_Graph* fn_body, const char* fn_name, int ninputs,
    const TF_Output* inputs, std::vector<OutputTensor>* input_tensors,