@SuppressWarnings("JUnit4ClassUsedInJUnit3")
public class MapEqualsTester<K, V> extends AbstractMapTester<K, V> {
  public void testEquals_otherMapWithSameEntries() {
    assertTrue(
        "A Map should equal any other Map containing the same entries.",
        getMap().equals(newHashMap(getSampleEntries())));
  }

  @CollectionSize.Require(absent = CollectionSize.ZERO)
  public void testEquals_otherMapWithDifferentEntries() {

If you have a big application, you might end up accumulating **several tags**, and you would want to make sure you always use the **same tag** for related *path operations*.

In these cases, it could make sense to store the tags in an `Enum`.

**FastAPI** supports that the same way as with plain strings:

{* ../../docs_src/path_operation_configuration/tutorial002b.py hl[1,8:10,13,18] *}

  ]
}
```

because the path parameter `item_id` had a value of `"foo"`, which is not an `int`.

The same error would appear if you provided a `float` instead of an `int`, as in: <a href="http://127.0.0.1:8000/items/4.2" class="external-link" target="_blank">http://127.0.0.1:8000/items/4.2</a>

/// check

So, with the same Python type declaration, **FastAPI** gives you data validation.

   * same order. (It is guaranteed to return true for instances constructed from the same values in
   * the same order if {@code strictfp} is in effect, or if the system architecture guarantees
   * {@code strictfp}-like semantics.)
   */
  @Override
  public boolean equals(@Nullable Object obj) {
    if (obj == null) {
      return false;
    }
    if (getClass() != obj.getClass()) {
      return false;
    }

    // enclosed with same start
    assertEquals(range, range.span(Range.closed(4, 6)));

    // enclosed, interior
    assertEquals(range, range.span(Range.closed(5, 7)));

    // enclosed with same end
    assertEquals(range, range.span(Range.closed(6, 8)));

    // equal
    assertEquals(range, range.span(range));

    // enclosing with same start

            path: CAs/public.crt
```

Note that the `secretName` should be same as the secret name created in previous step. Then add the below section under
`spec.containers[].volumeMounts[]`

```yaml
    volumeMounts:
        - name: secret-volume
          mountPath: /<user-running-minio>/.minio/certs
```

Here the name of `volumeMount` should match the name of `volume` created previously. Also `mountPath` must be set to the path of

   *   <li>{@code proxy.toString()} delegates to {@link AbstractInvocationHandler#toString}
   *   <li>{@code proxy.equals(argument)} returns true if:
   *       <ul>
   *         <li>{@code proxy} and {@code argument} are of the same type
   *         <li>and {@link AbstractInvocationHandler#equals} returns true for the {@link
   *             InvocationHandler} of {@code argument}
   *       </ul>

And of course, it supports the same:

* data validation
* data serialization
* data documentation, etc.

This works the same way as with Pydantic models. And it is actually achieved in the same way underneath, using Pydantic.

/// info

Keep in mind that dataclasses can't do everything Pydantic models can do.

Linux containers run using the same Linux kernel of the host (machine, virtual machine, cloud server, etc). This just means that they are very lightweight (compared to full virtual machines emulating an entire operating system).

     * @return local host address
     */
    NetbiosAddress getLocalHost();

    /**
     * Gets the local host NetBIOS name.
     *
     * @return the local host name
     */
    NetbiosName getLocalName();

    /**
     * Gets the unknown NetBIOS name instance.
     *
     * @return the unknown name
     */
    NetbiosName getUnknownName();

    /**