// Check if we are in DCOS environment, return
	// deployment guide for update procedures.
	if IsDCOS() {
		return mesosDeploymentDoc
	}

	// Check if we are in kubernetes environment, return
	// deployment guide for update procedures.
	if IsKubernetes() {
		return kubernetesDeploymentDoc
	}

	// Check if we are docker environment, return docker update command
	if IsDocker() {
		// Construct release tag name.

	return allErrs, nil
}

// BeforeUpdate ensures that common operations for all resources are performed on update. It only returns
// errors that can be converted to api.Status. It will invoke update validation with the provided existing
// and updated objects.
// It sets zero values only if the object does not have a zero value for the respective field.

	wg.Add(1)
	go func() {
		defer wg.Done()
		// continuously submits a patch that updates a label and verifies the label update was effective
		labelName := "timestamp"
		for i := 0; ; i++ {
			select {
			case <-stopCh:
				return
			default:
				expectedLabelValue := fmt.Sprint(i)

        try (StemmerOverrideUpdater updater = new StemmerOverrideUpdater(item)) {
            reload(updater);
        }
    }

    @Override
    public synchronized void update(final StemmerOverrideItem item) {
        try (StemmerOverrideUpdater updater = new StemmerOverrideUpdater(item)) {
            reload(updater);
        }
    }

    @Override

	minAvailable := intstr.FromInt32(8)
	update := policy.PodDisruptionBudget{
		ObjectMeta: obtainedPdb.ObjectMeta,
		Spec: policy.PodDisruptionBudgetSpec{
			MinAvailable: &minAvailable,
		},
		Status: policy.PodDisruptionBudgetStatus{
			ExpectedPods: 8,
		},
	}

apiVersion: release-notes/v2
kind: feature
area: networking
issue:
- 27183
- 27151
- 27185
releaseNotes:
- |

=== "🐍 3️⃣.1️⃣0️⃣ & 🔛"

    ```Python hl_lines="32"
    {!> ../../../docs_src/body_updates/tutorial002_py310.py!}
    ```

### ⚙️ Pydantic `update` 🔢

🔜, 👆 💪 ✍ 📁 ♻ 🏷 ⚙️ `.copy()`, & 🚶‍♀️ `update` 🔢 ⏮️ `dict` ⚗ 💽 ℹ.

💖 `stored_item_model.copy(update=update_data)`:

=== "🐍 3️⃣.6️⃣ & 🔛"

    ```Python hl_lines="35"
    {!> ../../../docs_src/body_updates/tutorial002.py!}
    ```

然后再用它生成一个只含已设置（在请求中所发送）数据，且省略了默认值的 `dict`：

```Python hl_lines="34"
{!../../../docs_src/body_updates/tutorial002.py!}
```

### 使用 Pydantic 的 `update` 参数

接下来，用 `.copy()` 为已有模型创建调用 `update` 参数的副本，该参数为包含更新数据的 `dict`。

例如，`stored_item_model.copy(update=update_data)`：

```Python hl_lines="35"
{!../../../docs_src/body_updates/tutorial002.py!}
```

### 更新部分数据小结

简而言之，更新部分数据应：

    ```Python hl_lines="34"
    {!> ../../../docs_src/body_updates/tutorial002.py!}
    ```

### Использование параметра `update` в Pydantic

Теперь можно создать копию существующей модели, используя `.copy()`, и передать параметр `update` с `dict`, содержащим данные для обновления.

Например, `stored_item_model.copy(update=update_data)`:

=== "Python 3.10+"

    ```Python hl_lines="33"

    ```

### Partial updates recap

In summary, to apply partial updates you would:

* (Optionally) use `PATCH` instead of `PUT`.
* Retrieve the stored data.
* Put that data in a Pydantic model.
* Generate a `dict` without default values from the input model (using `exclude_unset`).