return "", false, "", "", fmt.Errorf(format, args...)
	}
	goTool, err := goTool()
	if err != nil {
		return errorf("%w", err)
	}
	cmd := exec.Command(goTool, "list", "-e", "-f", "{{.ImportPath}}:{{.Standard}}{{with .Module}}:{{.Path}}:{{.Dir}}{{end}}", ".")
	out, err := cmd.Output()
	if err != nil {
		if ee, ok := err.(*exec.ExitError); ok && len(ee.Stderr) > 0 {
			return errorf("%v: %s", cmd, ee.Stderr)
		}

### Browser-Benutzeroberfläche

- Suchoberfläche: http://localhost:8080/

![Suchoberfläche](https://fess.codelibs.org/_images/fess_search_result1.png)

- Administrationsoberfläche: http://localhost:8080/admin/ (Standard-Benutzername/Passwort ist admin/admin)

![Administrationsoberfläche](https://fess.codelibs.org/_images/fess_admin_dashboard.png)

For example, it was clear that ideally it should be based on standard Python type hints.

Also, the best approach was to use already existing standards.

	"strings"

	"github.com/minio/minio/internal/logger"
	ftp "goftp.io/server/v2"
)

var globalRemoteFTPClientTransport = NewRemoteTargetHTTPTransport(true)()

// minioLogger use an instance of this to log in a standard format
type minioLogger struct{}

// Print implement Logger
func (log *minioLogger) Print(sessionID string, message interface{}) {
	if serverDebugLog {
		fmt.Printf("%s %s\n", sessionID, message)
	}
}

			bucketMGMap[mg.CollectorPath] = mg
		} else {
			mgMap[mg.CollectorPath] = mg
		}
	}

	// Prepare to register the collectors. Other than `MetricGroup` collectors,
	// we also have standard collectors like `GoCollector`.

	// Create all Non-`MetricGroup` collectors here.
	collectors := map[collectorPath]prometheus.Collector{
		debugGoCollectorPath: collectors.NewGoCollector(),
	}

```Python hl_lines="4"
{!> ../../docs_src/body/tutorial001.py!}
```

////

## Create your data model

Then you declare your data model as a class that inherits from `BaseModel`.

Use standard Python types for all the attributes:

//// tab | Python 3.10+

```Python hl_lines="5-9"
{!> ../../docs_src/body/tutorial001_py310.py!}
```

////

//// tab | Python 3.8+

```Python hl_lines="7-11"

```Python hl_lines="4"
{!../../docs_src/body/tutorial001.py!}
```

## Créez votre modèle de données

Déclarez ensuite votre modèle de données en tant que classe qui hérite de `BaseModel`.

Utilisez les types Python standard pour tous les attributs :

```Python hl_lines="7-11"
{!../../docs_src/body/tutorial001.py!}
```

In Python 3.9 wäre das:

```Python
my_list: list[str]
```

Und in Python-Versionen vor 3.9:

```Python
from typing import List

my_list: List[str]
```

Das ist alles Standard-Python-Syntax für Typdeklarationen.

Verwenden Sie dieselbe Standardsyntax für Modellattribute mit inneren Typen.

In unserem Beispiel können wir also bewirken, dass `tags` spezifisch eine „Liste von Strings“ ist:

        print(statsDetails['BytesProcessed'])
```

## 4. Run the Program

Upload a sample dataset to MinIO using the following commands.

```sh
curl "https://population.un.org/wpp/Download/Files/1_Indicators%20(Standard)/CSV_FILES/WPP2019_TotalPopulationBySex.csv" > TotalPopulation.csv
mc mb myminio/mycsvbucket
gzip TotalPopulation.csv
mc cp TotalPopulation.csv.gz myminio/mycsvbucket/sampledata/
```

<div class="termy">

```console
$ pip install "fastapi[standard]"

---> 100%
```

</div>

👆 🔜 💪 🔫 💽, 🏭 ✅ <a href="https://www.uvicorn.org" class="external-link" target="_blank">Uvicorn</a> ⚖️ <a href="https://github.com/pgjones/hypercorn" class="external-link" target="_blank">Hypercorn</a>.

<div class="termy">

```console
$ pip install "uvicorn[standard]"

---> 100%
```

</div>