How does this work? Let's check that out. 🤓

### Type Annotations and Tooling { #type-annotations-and-tooling }

First let's see how editors, mypy and other tools would see this.

`BaseUser` has the base fields. Then `UserIn` inherits from `BaseUser` and adds the `password` field, so, it will include all the fields from both models.

We annotate the function return type as `BaseUser`, but we are actually returning a `UserIn` instance.

    * This is for upgrades to direct dependencies from the project, or extra optional dependencies, normally in `pyproject.toml`. So, things that would affect final users, they would end up receiving the upgrade in their code base once they update. But this is not for upgrades to internal dependencies used for development, testing, docs, etc. Those internal dependencies, normally in `requirements.txt` files or GitHub Action versions should be marked as `internal`, not `upgrade`....

Como isso funciona? Vamos verificar. 🤓

### Anotações de tipo e ferramentas

Primeiro, vamos ver como editores, mypy e outras ferramentas veriam isso.

`BaseUser` tem os campos base. Então `UserIn` herda de `BaseUser` e adiciona o campo `password`, então, ele incluirá todos os campos de ambos os modelos.

Anotamos o tipo de retorno da função como `BaseUser`, mas na verdade estamos retornando uma instância `UserIn`.

* <a href="https://github.com/tiangolo/full-stack-flask-couchdb" class="external-link" target="_blank">https://github.com/tiangolo/full-stack-flask-couchdb</a>

E esses mesmos geradores _full-stack_ foram a base dos [Geradores de Projetos **FastAPI**](project-generation.md){.internal-link target=_blank}.

/// info

Flask-apispec foi criado pelos mesmos desenvolvedores do Marshmallow.

///

```

...porque no está claro si el valor por defecto debería ser `"rick"` o `"morty"`.

Así que utilizarías (preferentemente):

```Python
q: Annotated[str, Query()] = "rick"
```

...o en code bases más antiguos encontrarás:

```Python
q: str = Query(default="rick")
```

### Ventajas de `Annotated`

* If you are feeling too generous, you can try to **create an example** like that yourself, just based on the description of the problem. Just keep in mind that this might take a lot of time and it might be better to ask them to clarify the problem first.

### Suggest solutions { #suggest-solutions }

                entry.context.putAll(maskContext(context));
            }

            // Add MDC context efficiently
            addMdcContext(entry.context);

            // Process asynchronously or synchronously based on configuration
            if (asyncLogging && !shutdown) {
                if (!logQueue.offer(entry)) {
                    // Queue is full, log synchronously as fallback
                    processLogEntry(entry);

            });

            connected = true;
        } else {
            logger.warn("Could not connect to {}", address);
        }
    }

    /**
     * Creates a new OpenSearch client based on the configured address.
     *
     * @return The created OpenSearch client.
     */
    protected Client createClient() {
        final String[] hosts =

        // When
        int bytesWritten = request.writeBytesWireFormat(buffer, offset);

        // Then
        // The writeBytesWireFormat writes the structure and calculates padding
        // Base structure: 24 bytes, then pad8 alignment, then token: 5 bytes
        // Total bytes written includes padding for 8-byte alignment
        int expectedBytesWritten = 35;
        assertEquals(expectedBytesWritten, bytesWritten);

   */
  @Override
  int size();

  /**
   * Returns the number of occurrences of an element in this multiset (the <i>count</i> of the
   * element). Note that for an {@link Object#equals}-based multiset, this gives the same result as
   * {@link Collections#frequency} (which would presumably perform more poorly).
   *
   * <p><b>Note:</b> the utility method {@link Iterables#frequency} generalizes this operation; it