default:
		log.Printf("username is %q, account created on %s\n", username, created)
	}
}

func ExampleDB_ExecContext() {
	id := 47
	result, err := db.ExecContext(ctx, "UPDATE balances SET balance = balance + 10 WHERE user_id = ?", id)
	if err != nil {
		log.Fatal(err)
	}
	rows, err := result.RowsAffected()
	if err != nil {
		log.Fatal(err)
	}
	if rows != 1 {
		log.Fatalf("expected to affect 1 row, affected %d", rows)
	}
}

👆 ✍ 🐩 🐍 ⏮️ 🆎:

```Python
from datetime import date

from pydantic import BaseModel

# Declare a variable as a str
# and get editor support inside the function
def main(user_id: str):
    return user_id


# A Pydantic model
class User(BaseModel):
    id: int
    name: str
    joined: date
```

👈 💪 ⤴️ ⚙️ 💖:

```Python

from typing import List, Dict
from datetime import date

from pydantic import BaseModel

# Deklarieren Sie eine Variable als ein `str`
# und bekommen Sie Editor-Unterstütung innerhalb der Funktion
def main(user_id: str):
    return user_id


# Ein Pydantic-Modell
class User(BaseModel):
    id: int
    name: str
    joined: date
```

Das kann nun wie folgt verwendet werden:

```Python

```Python
from typing import List, Dict
from datetime import date

from pydantic import BaseModel

# Değişkeni str olarak belirt
# ve o fonksiyon için harika bir editör desteği al
def main(user_id: str):
    return user_id


# Pydantic modeli
class User(BaseModel):
    id: int
    name: str
    joined: date
```

Sonrasında bu şekilde kullanabilirsin

```Python

```Python
from datetime import date

from pydantic import BaseModel

# Zadeklaruj parametr jako str
# i uzyskaj wsparcie edytora wewnątrz funkcji
def main(user_id: str):
    return user_id


# Model Pydantic
class User(BaseModel):
    id: int
    name: str
    joined: date
```

A one będą mogły zostać później użyte w następujący sposób:

```Python

You write standard Python with types:

```Python
from datetime import date

from pydantic import BaseModel

# Declare a variable as a str
# and get editor support inside the function
def main(user_id: str):
    return user_id


# A Pydantic model
class User(BaseModel):
    id: int
    name: str
    joined: date
```

That can then be used like:

```Python

* `/items/public/`
* `/items/private/`
* `/users/{user_id}/activate`
* `/items/pro/`

开发人员可以使用依赖项及其子依赖项为这些路径操作添加不同的权限：

```mermaid
graph TB

current_user(["current_user"])
active_user(["active_user"])
admin_user(["admin_user"])
paying_user(["paying_user"])

public["/items/public/"]
private["/items/private/"]
activate_user["/users/{user_id}/activate"]
pro_items["/items/pro/"]

Nehmen wir zum Beispiel an, Sie haben vier API-Endpunkte (*Pfadoperationen*):

* `/items/public/`
* `/items/private/`
* `/users/{user_id}/activate`
* `/items/pro/`

Dann könnten Sie für jeden davon unterschiedliche Berechtigungsanforderungen hinzufügen, nur mit Abhängigkeiten und Unterabhängigkeiten:

```mermaid
graph TB

Você escreve Python padrão com tipos:

```Python
from datetime import date

from pydantic import BaseModel

# Declare uma variável como str
# e obtenha suporte do editor dentro da função
def main(user_id: str):
    return user_id


# Um modelo do Pydantic
class User(BaseModel):
    id: int
    name: str
    joined: date
```

Que então pode ser usado como:

```Python

```Python
from datetime import date

from pydantic import BaseModel

# Déclare une variable comme étant une str
# et profitez de l'aide de votre IDE dans cette fonction
def main(user_id: str):
    return user_id


# Un modèle Pydantic
class User(BaseModel):
    id: int
    name: str
    joined: date
```
Qui peuvent ensuite être utilisés comme cela:

```Python