StartTime *metav1.Time `json:"startTime,omitempty" protobuf:"bytes,7,opt,name=startTime"`
}

type CarpCondition struct {
	// Type is the type of the condition.
	// Currently only Ready.
	// More info: http://kubernetes.io/docs/user-guide/carp-states#carp-conditions
	Type CarpConditionType `json:"type" protobuf:"bytes,1,opt,name=type,casttype=CarpConditionType"`
	// Status is the status of the condition.
	// Can be True, False, Unknown.

	// +optional
	// +listType=map
	// +listMapKey=type
	Conditions []metav1.Condition `json:"conditions,omitempty" protobuf:"bytes,3,rep,name=conditions"`
}

// TypeChecking contains results of type checking the expressions in the
// ValidatingAdmissionPolicy
type TypeChecking struct {
	// The type checking warnings for each expression.
	// +optional
	// +listType=atomic

我们用的是冒号（`:`），不是等号（`=`）。

而且添加类型提示一般不会改变原来的运行结果。

现在假设我们又一次正在创建这个函数，这次添加了类型提示。

在同样的地方，通过 `Ctrl+Space` 触发自动补全，你会发现：

<img src="https://fastapi.tiangolo.com/img/python-types/image02.png">

这样，你可以滚动查看选项，直到你找到看起来眼熟的那个：

<img src="https://fastapi.tiangolo.com/img/python-types/image03.png">

## 更多动机

下面是一个已经有类型提示的函数：

```Python hl_lines="1"
{!../../../docs_src/python_types/tutorial003.py!}
```

}

// StatefulSetConditionType describes the condition types of StatefulSets.
type StatefulSetConditionType string

// TODO: Add valid condition types for Statefulsets.

// StatefulSetCondition describes the state of a statefulset at a certain point.
type StatefulSetCondition struct {
	// Type of statefulset condition.
	Type StatefulSetConditionType
	// Status of the condition, one of True, False, Unknown.

<img src="/img/python-types/image02.png">

⏮️ 👈, 👆 💪 📜, 👀 🎛, ⏭ 👆 🔎 1️⃣ 👈 "💍 🔔":

<img src="/img/python-types/image03.png">

## 🌅 🎯

✅ 👉 🔢, ⚫️ ⏪ ✔️ 🆎 🔑:

```Python hl_lines="1"
{!../../../docs_src/python_types/tutorial003.py!}
```

↩️ 👨‍🎨 💭 🆎 🔢, 👆 🚫 🕴 🤚 🛠️, 👆 🤚 ❌ ✅:

<img src="/img/python-types/image04.png">

일반적으로 타입힌트를 추가한다고 해서 특별하게 어떤 일이 일어나지도 않습니다.

그렇지만 이제, 다시 함수를 만드는 도중이라고 생각해봅시다. 다만 이번엔 타입 힌트가 있습니다.

같은 상황에서 `Ctrl+Space`로 자동완성을 작동시키면,

<img src="/img/python-types/image02.png">

아래와 같이 "그렇지!"하는 옵션이 나올때까지 스크롤을 내려서 볼 수 있습니다:

<img src="/img/python-types/image03.png">

## 더 큰 동기부여

아래 함수를 보면, 이미 타입 힌트가 적용되어 있는 걸 볼 수 있습니다:

```Python hl_lines="1"
{!../../../docs_src/python_types/tutorial003.py!}
```

		desc     string
		function func(v reflect.Type) bool
		okTypes  []any
	}{
		{
			desc:     "IsTypeStructPtr",
			function: IsTypeStructPtr,
			okTypes:  []any{&testStruct},
		},
		{
			desc:     "IsTypeSlicePtr",
			function: IsTypeSlicePtr,
			okTypes:  []any{&testSlice},
		},
		{
			desc:     "IsTypeMap",
			function: IsTypeMap,
			okTypes:  []any{testNilMap, testMap},
		},
		{

Diese Typen mit inneren Typen werden „**generische**“ Typen genannt. Es ist möglich, sie mit ihren inneren Typen zu deklarieren.

Um diese Typen und die inneren Typen zu deklarieren, können Sie Pythons Standardmodul `typing` verwenden. Es existiert speziell für die Unterstützung dieser Typhinweise.

#### Neuere Python-Versionen

    * In requests and responses, handled the same as a `float`.
* You can check all the valid pydantic data types here: <a href="https://docs.pydantic.dev/latest/usage/types/types/" class="external-link" target="_blank">Pydantic data types</a>.

## Example

Here's an example *path operation* with parameters using some of the above types.

=== "Python 3.10+"

    ```Python hl_lines="1  3  12-16"

	// Also, avoid specifying:
	// 1. Duplicates, the same NUMA node, and memory type, but with a different value.
	// 2. zero limits for any memory type.
	// 3. NUMAs nodes IDs that do not exist under the machine.
	// 4. memory types except for memory and hugepages-<size>
	ReservedMemory []MemoryReservation
	// EnableProfiling enables /debug/pprof handler.