* Walidacja **złożonych struktur**:
    * Wykorzystanie hierarchicznych modeli Pydantic, Pythonowego modułu `typing` zawierającego `List`, `Dict`, itp.
    * Walidatory umożliwiają jasne i łatwe definiowanie, sprawdzanie złożonych struktur danych oraz dokumentowanie ich jako JSON Schema.
    * Możesz mieć głęboko **zagnieżdżone obiekty JSON** i wszystkie je poddać walidacji i adnotować.

               },
               "expr": "sum (rate(galley_validation_failed[$__rate_interval]))",
               "legendFormat": "Failure"
            }
         ],
         "title": "Validation",
         "type": "timeseries"
      },
      {
         "datasource": {
            "type": "datasource",
            "uid": "-- Mixed --"
         },

<img src="/img/python-types/image06.png">

## Les modèles Pydantic

<a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a> est une bibliothèque Python pour effectuer de la validation de données.

Vous déclarez la forme de la donnée avec des classes et des attributs.

Chaque attribut possède un type.

  
  If `username.expression` used 'claims.email', then 'claims.email_verified' must have been used in `username.expression` or `extra[*].valueExpression` or `claimValidationRules[*].expression`. An example claim validation rule expression that matches the validation automatically applied when `username.claim` is set to 'email' is 'claims.?email_verified.orValue(true)'.
   ([#123737](https://github.com/kubernetes/kubernetes/pull/123737), [@enj](https://github.com/enj))

            System.setProperties(oldProps);
        }
    }

    protected int doInvoke(C context) throws Exception {
        pushProperties(context);
        validate(context);
        prepare(context);
        configureLogging(context);
        activateLogging(context);
        helpOrVersionAndMayExit(context);
        preCommands(context);
        container(context);

		if apiErr != noError {
			return fmt.Errorf("bucket replication config validation error: %#v", apiErr)
		}
		err = newReplicationConfig.Validate(bucket, sameTarget)
		if err != nil {
			return err
		}
		// Config looks good, so we save it.
		replCfgData, err := xml.Marshal(newReplicationConfig)
		if err != nil {

// along with this program.  If not, see <http://www.gnu.org/licenses/>.

package s3select

// /////////////////////////////////////////////////////////////////////
//
//	Validation errors.
//
// /////////////////////////////////////////////////////////////////////
func errExpressionTooLong(err error) *s3Error {
	return &s3Error{
		code:       "ExpressionTooLong",

    READY_FOR_RELEASE("Ready for Release", "Once a day: Rerun tests in more environments", "ReadyforRelease"),
    WEEKLY_VALIDATION("Weekly Validation", "Once a week: Run tests in even more environments but less often", "WeeklyValidation"),
    HISTORICAL_PERFORMANCE("Historical Performance", "Once a week: Run performance tests for multiple Gradle versions", "HistoricalPerformance"),

Kubelet to establish connections to Pods, retrieve container logs, and more. While Kubernetes already validates the proxying address for Nodes, a bug in kube-apiserver made it possible to bypass this validation. Bypassing this validation could allow authenticated requests destined for Nodes to be redirected to the API Server through its private network.

The merged fix enforces validation against the proxying address for a Node. In some cases, the fix can break clients that depend on the...

///

### JSON Schemas Feld `examples`

Aber dann fügte JSON Schema ein <a href="https://json-schema.org/draft/2019-09/json-schema-validation.html#rfc.section.9.5" class="external-link" target="_blank">`examples`</a>-Feld zu einer neuen Version der Spezifikation hinzu.