Agora vamos usar os utilitários fornecidos pelo **FastAPI** para lidar com isso.

### `OAuth2PasswordRequestForm` { #oauth2passwordrequestform }

Primeiro, importe `OAuth2PasswordRequestForm` e use-o como uma dependência com `Depends` na *operação de rota* para `/token`:

{* ../../docs_src/security/tutorial003_an_py310.py hl[4,78] *}

     * <code>SmbResource</code> was modified. The value returned is suitable for
     * constructing a {@link java.util.Date} object (i.e. seconds since Epoch
     * 1970). Times should be the same as those reported using the properties
     * dialog of the Windows Explorer program.
     *
     * @return The number of milliseconds since the 00:00:00 GMT, January 1,
     *         1970 as a <code>long</code> value

	for i := 0; i < len(s); {
		r, wid := utf8.DecodeRune(s[i:])
		r = mapping(r)
		if r >= 0 {
			b = utf8.AppendRune(b, r)
		}
		i += wid
	}
	return b
}

// Despite being an exported symbol,
// Repeat is linknamed by widely used packages.
// Notable members of the hall of shame include:
//   - gitee.com/quant1x/num
//
// Do not remove or change the type signature.
// See go.dev/issue/67401.

    * Old behavior:
      * environment variables explicitly whitelisted via --docker-env-metadata-whitelist were exported as `container_env_*=*`. Default is zero so by default non were exported
      * all docker labels were exported as `container_label_*=*`
    * New behavior:
      * Only `container_name`, `pod_name`, `namespace`, `id`, `image`, and `name` labels are exposed

func newRateMeasurement(initTime time.Time) *rateMeasurement {
	return &rateMeasurement{
		startTime: initTime,
	}
}

// incrementBytes add bytes reported for a bucket/target.
func (m *rateMeasurement) incrementBytes(bytes uint64) {
	atomic.AddUint64(&m.bytesSinceLastWindow, bytes)
}

// updateExponentialMovingAverage processes the measurements captured so far.

Vamos criar a primeira versão mais simples do app com um único modelo **SQLModel**.

Depois, vamos melhorá-lo aumentando a segurança e versatilidade com **múltiplos modelos** abaixo. 🤓

### Criar Modelos { #create-models }

Importe o `SQLModel` e crie um modelo de banco de dados:

{* ../../docs_src/sql_databases/tutorial001_an_py310.py ln[1:11] hl[7:11] *}

		if w.reuseBlocks || o.reusable {
			metaDataPoolPut(o.metadata)
		}
	}

	return nil
}

// stream entries to the output.
// The returned channel should be closed when done.
// Any error is reported when closing the metacacheWriter.
func (w *metacacheWriter) stream() (chan<- metaCacheEntry, error) {
	if w.creator != nil {
		err := w.creator()
		w.creator = nil
		if err != nil {

///

### Criar o objeto `Settings` { #create-the-settings-object }

Importe `BaseSettings` do Pydantic e crie uma subclasse, muito parecido com um modelo do Pydantic.

Da mesma forma que com modelos do Pydantic, você declara atributos de classe com anotações de tipo e, possivelmente, valores padrão.

     * This means that developer will either have to type groupId or wait for build execution of all modules which
     *   were fine, but they are still before one which reported errors.
     * <p>Then the returned value is {@code groupId:artifactId} when there is a name clash and
     * {@code :artifactId} if there is no conflict.
     * This method is made package-private for testing purposes.

                .filter(rap -> !allAvailableProfiles.contains(rap))
                .collect(toSet());

        if (!notFoundRequiredProfiles.isEmpty()) {
            // Use SLF4J formatter for consistency with warnings reported by logger
            final String message = MessageFormatter.format(
                            "The requested profiles {} could not be activated or deactivated because they do not"