Lassen wir es uns den aktuellen Benutzer überreichen.

## Ein Benutzermodell erstellen

Erstellen wir zunächst ein Pydantic-Benutzermodell.

So wie wir Pydantic zum Deklarieren von Bodys verwenden, können wir es auch überall sonst verwenden:

//// tab | Python 3.10+

```Python hl_lines="5  12-16"
{!> ../../docs_src/security/tutorial002_an_py310.py!}
```

////

//// tab | Python 3.9+

```Python hl_lines="5  12-16"

			}
		}
	}

	const maxInt = int(^uint(0) >> 1)

	runTestCases("", []testCase{
		0: {"--", -2147483647, "negative"},
		1: {"", maxInt, ""},
		2: {"-", 10, ""},
		3: {"gopher", 0, ""},
		4: {"-", -1, "negative"},
		5: {"--", -102, "negative"},
		6: {string(make([]byte, 255)), int((^uint(0))/255 + 1), "overflow"},
	})

	const is64Bit = 1<<(^uintptr(0)>>63)/2 != 0

	"github.com/minio/minio/internal/event/target"
	"github.com/minio/minio/internal/logger"
	"github.com/minio/pkg/v3/env"
	xnet "github.com/minio/pkg/v3/net"
)

const (
	formatNamespace = "namespace"
)

const (
	logSubsys = "notify"
)

func logOnceIf(ctx context.Context, err error, id string, errKind ...interface{}) {
	logger.LogOnceIf(ctx, logSubsys, err, id, errKind...)
}

package cmd

import (
	"context"
	"fmt"
	"math"
	"net/http"
	"sync"
	"time"

	"github.com/minio/madmin-go/v3"
	"github.com/prometheus/client_golang/prometheus"
)

const (
	resourceMetricsCollectionInterval = time.Minute
	resourceMetricsCacheInterval      = time.Minute

	// drive stats
	totalInodes    MetricName = "total_inodes"
	readsPerSec    MetricName = "reads_per_sec"

	"k8s.io/apimachinery/pkg/runtime"

	"istio.io/api/annotation"
	"istio.io/api/label"
	"istio.io/istio/pkg/config/constants"
	"istio.io/istio/pkg/kube"
	"istio.io/istio/pkg/test/util/assert"
)

const (
	testPodName          = "testPod"
	testNSName           = "testNS"
	testSandboxDirectory = "/tmp"
	invalidVersion       = "0.1.0"
	preVersion           = "0.2.0"
)

var mockConfTmpl = `{

	"github.com/minio/minio/internal/logger"
	xldap "github.com/minio/pkg/v3/ldap"
	"github.com/minio/pkg/v3/policy"
	"github.com/puzpuzpuz/xsync/v3"
)

const (
	srStatePrefix = minioConfigPrefix + "/site-replication"
	srStateFile   = "state.json"
)

const (
	srStateFormatVersion1 = 1
)

var (
	errSRCannotJoin = SRError{
		Cause: errors.New("this site is already configured for site-replication"),

	"github.com/minio/minio/internal/fips"
	"github.com/minio/minio/internal/kms"
	"github.com/minio/minio/internal/logger"
	"github.com/minio/pkg/v3/policy"
	"github.com/minio/sio"
)

const (
	legacyBucketObjectLockEnabledConfigFile = "object-lock-enabled.json"
	legacyBucketObjectLockEnabledConfig     = `{"x-amz-bucket-object-lock-enabled":true}`

	bucketMetadataFile    = ".metadata.bin"

 * {@link QuantilesBenchmark}. These algorithms each calculate either a single quantile or multiple
 * quantiles. All algorithms modify the dataset they are given (the cost of a copy to avoid this
 * will be constant across algorithms).
 *
 * @author Pete Gillin
 * @since 20.0
 */
enum QuantilesAlgorithm {

  /**

Você também pode usá-lo para gerar código automaticamente para clientes que se comunicam com sua API. Por exemplo, aplicativos front-end, móveis ou IoT.

## Recapitulando, passo a passo

### Passo 1: importe `FastAPI`

```Python hl_lines="1"
{!../../docs_src/first_steps/tutorial001.py!}
```

Das ist, wie es sein sollte, denn wenn Sie einen Pydantic-`ValidationError` in Ihrer *Response* oder irgendwo sonst in ihrem Code haben (es sei denn, im *Request* des Clients), ist das tatsächlich ein Bug in ihrem Code.