type float32 float32

// float64 is the set of all IEEE 754 64-bit floating-point numbers.
type float64 float64

// complex64 is the set of all complex numbers with float32 real and
// imaginary parts.
type complex64 complex64

// complex128 is the set of all complex numbers with float64 real and
// imaginary parts.
type complex128 complex128

					ef.TagSettings[k] = v
				}
			}
		case reflect.Invalid, reflect.Uintptr, reflect.Array, reflect.Chan, reflect.Func, reflect.Interface,
			reflect.Map, reflect.Ptr, reflect.Slice, reflect.UnsafePointer, reflect.Complex64, reflect.Complex128:
			schema.err = fmt.Errorf("invalid embedded struct for %s's field %s, should be struct, but got %v", field.Schema.Name, field.Name, field.FieldType)
		}
	}

	return field
}

pkg go/types, const Bool BasicKind
pkg go/types, const Byte = 8
pkg go/types, const Byte BasicKind
pkg go/types, const Complex128 = 16
pkg go/types, const Complex128 BasicKind
pkg go/types, const Complex64 = 15
pkg go/types, const Complex64 BasicKind
pkg go/types, const FieldVal = 0
pkg go/types, const FieldVal SelectionKind
pkg go/types, const Float32 = 13
pkg go/types, const Float32 BasicKind
pkg go/types, const Float64 = 14

* Valida **estruturas complexas**:
    * Use modelos hierárquicos do Pydantic, `List` e `Dict` do `typing` do Python, etc.
    * Validadores permitem que esquemas de dados complexos sejam limpos e facilmente definidos, conferidos e documentados como JSON Schema.

* Valide les **structures complexes**:
    * Utilise les modèles hiérarchique de Pydantic, le `typage` Python pour les `Lists`, `Dict`, etc.
    * Et les validateurs permettent aux schémas de données complexes d'être clairement et facilement définis, validés et documentés sous forme d'un schéma JSON.

* Valideer **complexe structuren**:
    * Gebruik van hiërarchische Pydantic modellen, Python `typing`'s `List` en `Dict`, enz.
    * Met validators kunnen complexe dataschema's duidelijk en eenvoudig worden gedefinieerd, gecontroleerd en gedocumenteerd als JSON Schema.

Mas antes disso, controlar código assíncrono era bem mais complexo e difícil.

Nas versões anteriores do Python, você poderia utilizar threads ou <a href="http://www.gevent.org/" class="external-link" target="_blank">Gevent</a>. Mas o código é um pouco mais complexo de entender, debugar, e pensar sobre.

## Recap

With what you have seen up to now, you can set up a secure **FastAPI** application using standards like OAuth2 and JWT.

In almost any framework handling the security becomes a rather complex subject quite quickly.

 *   <li>network/transfer errors</li>
 *   <li>file system errors: permissions</li>
 * </ul>
 *
 * TODO carlos: all these possible has*Exceptions and get*Exceptions methods make the clients too
 *       complex requiring a long list of checks, need to create a parent/interface/encapsulation
 *       for the types of exceptions
 */
@Deprecated
public class ArtifactResolutionResult {

The most common is the implicit flow.

The most secure is the code flow, but it's more complex to implement as it requires more steps. As it is more complex, many providers end up suggesting the implicit flow.

/// note

It's common that each authentication provider names their flows in a different way, to make it part of their brand.