```Python
user_in = UserIn(username="john", password="secret", email="******@****.***")
```

e depois chamarmos:

```Python
user_dict = user_in.dict()
```

agora temos um `dict` com os dados na variável `user_dict` (é um `dict` em vez de um objeto de modelo Pydantic).

E se chamarmos:

```Python
print(user_dict)
```

teríamos um `dict` Python com:

```Python
{
    'username': 'john',

   * @throws NullPointerException if {@code string} is null
   */
  protected final String escapeSlow(String s, int index) {
    int slen = s.length();

    // Get a destination buffer and setup some loop variables.
    char[] dest = Platform.charBufferFromThreadLocal();
    int destSize = dest.length;
    int destIndex = 0;
    int lastEscape = 0;

    // Loop through the rest of the string, replacing when needed into the

///

Die Variable `oauth2_scheme` ist eine Instanz von `OAuth2PasswordBearer`, aber auch ein „Callable“.

Es könnte wie folgt aufgerufen werden:

```Python
oauth2_scheme(some, parameters)
```

  /**
   * @throws IllegalArgumentException if {@code existingValue} is not null.
   */
  /*
   * We could have declared this method 'static' but the additional compile-time checks achieved by
   * referencing the type variables seem worthwhile.
   */
  final void checkNoDuplicate(R rowKey, C columnKey, @Nullable V existingValue, V newValue) {
    checkArgument(
        existingValue == null,

```Python
user_in = UserIn(username="john", password="secret", email="******@****.***")
```

und wir rufen seine `.dict()`-Methode auf:

```Python
user_dict = user_in.dict()
```

dann haben wir jetzt in der Variable `user_dict` ein `dict` mit den gleichen Daten (es ist ein `dict` statt eines Pydantic-Modellobjekts).

Wenn wir es ausgeben:

```Python
print(user_dict)
```

bekommen wir ein Python-`dict`:

```Python

Vous écrivez du python standard avec des annotations de types:

```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

    exit 1
fi

if [ -z "$FESS_CLASSPATH" ]; then
    echo "You must set the FESS_CLASSPATH var" >&2
    exit 1
fi

# Special-case path variables.
case `uname` in
    CYGWIN*)
        FESS_CLASSPATH=`cygpath -p -w "$FESS_CLASSPATH"`
        FESS_HOME=`cygpath -p -w "$FESS_HOME"`
        if [ "x$FESS_CONF_PATH" != "x" ] ; then

- Mixing `local-path` and `distributed-path` is not allowed, doing so would cause MinIO to refuse starting the server.
- Ellipses and bracket notation (e.g. `{1...10}`) are allowed.

> NOTE: MinIO environmental variables still take precedence over the `config.yaml` file, however `config.yaml` is preferred over MinIO internal config KV settings via `mc admin config set alias/ <sub-system>`.

### TODO

Je schrijft gewoon standaard Python met types:

```Python
from datetime import date

from pydantic import BaseModel

# Declareer een variabele als een str
# en krijg editorondersteuning in de functie
def main(user_id: str):
    return user_id


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

if [ ! -x "$JAVACMD" ]; then
  echo "Error: JAVA_HOME is not defined correctly." >&2
  echo "  We cannot execute $JAVACMD" >&2
  exit 1
fi

if [ -z "$JAVA_HOME" ]; then
  echo "Warning: JAVA_HOME environment variable is not set." >&2
fi

# traverses directory structure from process work directory to filesystem root
# first directory with .mvn subdirectory is considered project base directory
find_maven_basedir() {