*/
@ExtendWith(MockitoExtension.class)
class NetbiosAddressTest {

    @Test
    void testConstantValues() {
        // Test that constants are properly defined
        assertEquals("*\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000",
                NbtAddress.ANY_HOSTS_NAME);

## Overview

MinIO supports two storage classes, Reduced Redundancy class and Standard class. These classes can be defined using environment variables
set before starting MinIO server. After the data and parity drives for each storage class are defined using environment variables,
you can set the storage class of an object via request metadata field `x-amz-storage-class`. MinIO server then honors the storage class by

   * comes from a data structure supporting efficient indexed random access, typically an array or
   * list.
   *
   * <p>The order of the resulting stream is defined if and only if the order of the original stream
   * was defined.
   */
  public static <T extends @Nullable Object, R extends @Nullable Object> Stream<R> mapWithIndex(
      Stream<T> stream, FunctionWithIndex<? super T, ? extends R> function) {

    class InterfaceMethodContractTest {

        @Test
        @DisplayName("Should define exactly four public methods")
        void shouldDefineExactlyFourPublicMethods() {
            java.lang.reflect.Method[] methods = SmbSession.class.getDeclaredMethods();
            assertEquals(4, methods.length, "SmbSession should define exactly 4 methods");
        }

        @Test

    * Because pydantic data structures are just instances of classes you define; auto-completion, linting, mypy and your intuition should all work properly with your validated data.
* Validate **complex structures**:
    * Use of hierarchical Pydantic models, Python `typing`’s `List` and `Dict`, etc.
    * And validators allow complex data schemas to be clearly and easily defined, checked and documented as JSON Schema.

 */
@TestInstance(TestInstance.Lifecycle.PER_CLASS)
class FileInformationTest {

    /**
     * Test that interface constants are correctly defined
     */
    @Test
    @DisplayName("Test FileInformation constants are correctly defined")
    void testInterfaceConstants() {
        // Verify all constants have expected values
        assertEquals((byte) 20, FileInformation.FILE_ENDOFFILE_INFO);

{* ../../docs_src/request_form_models/tutorial001_an_py39.py hl[9:11,15] *}

**FastAPI** will **extract** the data for **each field** from the **form data** in the request and give you the Pydantic model you defined.

## Check the Docs { #check-the-docs }

You can verify it in the docs UI at `/docs`:

<div class="screenshot">
<img src="/img/tutorial/request-form-models/image01.png">
</div>

If you want to secure your API, there are several better things you can do, for example:

* Make sure you have well defined Pydantic models for your request bodies and responses.
* Configure any required permissions and roles using dependencies.
* Never store plaintext passwords, only password hashes.

     */
    @ParameterizedTest
    @MethodSource("provideErrorClassAndCodeForGetErrorString")
    @DisplayName("getErrorString should return correct messages for all defined error classes and codes")
    void testGetErrorString(int errorClass, int errorCode, String expectedMessage) {
        assertEquals(expectedMessage, NbtException.getErrorString(errorClass, errorCode),

import static org.junit.jupiter.api.Assertions.assertNotNull;

import org.junit.jupiter.api.Test;

/**
 * Tests for the {@link ResolverType} enum.
 * This class ensures that the enum constants are defined as expected.
 */
class ResolverTypeTest {

    /**
     * Tests that all expected enum constants exist.
     */
    @Test
    void testEnumConstants() {