rm -f "$WORK_DIR/dist-minio-9000.log" "$WORK_DIR/dist-minio-9001.log" "$WORK_DIR/dist-minio-9002.log" "$WORK_DIR/dist-minio-9003.log"

	return "$rv"
}

function purge() {
	rm -rf "$1"
}

function __init__() {
	echo "Initializing environment"
	mkdir -p "$WORK_DIR"
	mkdir -p "$MINIO_CONFIG_DIR"
	mkdir -p "$MINT_DATA_DIR"

	MC_BUILD_DIR="mc-$RANDOM"

from pydantic import BaseModel, Field, ValidationError

from .utils import needs_pydanticv1, needs_pydanticv2


class Person:
    def __init__(self, name: str):
        self.name = name


class Pet:
    def __init__(self, owner: Person, name: str):
        self.owner = owner
        self.name = name


@dataclass
class Item:
    name: str
    count: int

    # Settings management
    "pydantic-settings >=2.0.0",
    # Extra Pydantic data types
    "pydantic-extra-types >=2.0.0",
]

[tool.pdm]
version = { source = "file", path = "fastapi/__init__.py" }
distribution = true

[tool.pdm.build]
source-includes = [
    "tests/",
    "docs_src/",
    "requirements*.txt",
    "scripts/",
    # For a test
    "docs/en/docs/img/favicon.png",

    _REGISTRY[calib_method] = cls
    return cls

  return decorator


class _CalibrationAlgorithmBase(abc.ABC):
  """Abstract base class for calibration algorithm."""

  def __init__(
      self,
      statistics: calib_stats_pb2.CalibrationStatistics,
      calib_opts: stablehlo_quant_config_pb2.CalibrationOptions,
  ):
    self._statistics = statistics
    self._calib_opts = calib_opts

    class GatherModel(autotrackable.AutoTrackable):
      """A simple model with a single gather."""

      def __init__(self, use_variable):
        """Initializes a GatherModel.

        Args:
          use_variable: If True, creates a variable for weight.
        """
        super(GatherModel, self).__init__()
        w_val = np.random.randn(128, 32).astype('f4')
        if use_variable:

或者

```Python
something(some_argument, some_keyword_argument="foo")
```

这就是 "可调用对象"。

## 类作为依赖项

您可能会注意到，要创建一个 Python 类的实例，您可以使用相同的语法。

举个例子:

```Python
class Cat:
    def __init__(self, name: str):
        self.name = name


fluffy = Cat(name="Mr Fluffy")
```

在这个例子中, `fluffy` 是一个 `Cat` 类的实例。

为了创建 `fluffy`，你调用了 `Cat` 。

所以，Python 类也是 **可调用对象**。

## Klassen als Abhängigkeiten

Möglicherweise stellen Sie fest, dass Sie zum Erstellen einer Instanz einer Python-Klasse die gleiche Syntax verwenden.

Zum Beispiel:

```Python
class Cat:
    def __init__(self, name: str):
        self.name = name


fluffy = Cat(name="Mr Fluffy")
```

In diesem Fall ist `fluffy` eine Instanz der Klasse `Cat`.

Und um `fluffy` zu erzeugen, rufen Sie `Cat` auf.

```

then it is a "callable".

## Classes as dependencies

You might notice that to create an instance of a Python class, you use that same syntax.

For example:

```Python
class Cat:
    def __init__(self, name: str):
        self.name = name


fluffy = Cat(name="Mr Fluffy")
```

In this case, `fluffy` is an instance of the class `Cat`.

And to create `fluffy`, you are "calling" `Cat`.

```

상기와 같은 방식으로 "호출(실행)" 할 수 있다면 "호출 가능"이 됩니다.

## 의존성으로서의 클래스

파이썬 클래스의 인스턴스를 생성하기 위해 사용하는 것과 동일한 문법을 사용한다는 걸 알 수 있습니다.

예를 들어:

```Python
class Cat:
    def __init__(self, name: str):
        self.name = name


fluffy = Cat(name="Mr Fluffy")
```

이 경우에 `fluffy`는 클래스 `Cat`의 인스턴스입니다. 그리고 우리는 `fluffy`를 만들기 위해서 `Cat`을 "호출"했습니다.

따라서, 파이썬 클래스는 **호출 가능**합니다.

в таком случае он является "вызываемым".

## Классы как зависимости

Вы можете заметить, что для создания экземпляра класса в Python используется тот же синтаксис.

Например:

```Python
class Cat:
    def __init__(self, name: str):
        self.name = name


fluffy = Cat(name="Mr Fluffy")
```

В данном случае `fluffy` является экземпляром класса `Cat`.

А чтобы создать `fluffy`, вы "вызываете" `Cat`.