!!! info
    In Pydantic v1 the method was called `.copy()`, it was deprecated (but still supported) in Pydantic v2, and renamed to `.model_copy()`.

    The examples here use `.copy()` for compatibility with Pydantic v1, but you should use `.model_copy()` instead if you can use Pydantic v2.

Like `stored_item_model.model_copy(update=update_data)`:

Wie in `stored_item_model.model_copy(update=update_data)`:

=== "Python 3.10+"

    ```Python hl_lines="33"
    {!> ../../../docs_src/body_updates/tutorial002_py310.py!}
    ```

=== "Python 3.9+"

    ```Python hl_lines="35"
    {!> ../../../docs_src/body_updates/tutorial002_py39.py!}
    ```

=== "Python 3.8+"

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

	// 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.

# This Workflow updates tensorflow/tools/toolchains/remote_config/configs.bzl
# to reference the most recent versions of the SIG Build Docker images.
name: Update RBE Configs
on:
  workflow_dispatch:

permissions:
  contents: read

jobs:
  rbe:
    name: Update RBE Configs
    runs-on: ubuntu-latest

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

=== "🐍 3️⃣.6️⃣ & 🔛"

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

=== "🐍 3️⃣.9️⃣ & 🔛"

    ```Python hl_lines="35"
    {!> ../../../docs_src/body_updates/tutorial002_py39.py!}
    ```

=== "🐍 3️⃣.1️⃣0️⃣ & 🔛"

    ```Python hl_lines="33"

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

### Pydanticの`update`パラメータ

ここで、`.copy()`を用いて既存のモデルのコピーを作成し、`update`パラメータに更新するデータを含む`dict`を渡すことができます。

`stored_item_model.copy(update=update_data)`のように:

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

### 部分的更新のまとめ

まとめると、部分的な更新を適用するには、次のようにします:

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：

)

// initlicenseUpdateJob start the periodic license update job in the background.
func initLicenseUpdateJob(ctx context.Context, objAPI ObjectLayer) {
	go func() {
		r := rand.New(rand.NewSource(time.Now().UnixNano()))
		// Leader node (that successfully acquires the lock inside licenceUpdaterLoop)
		// will keep performing the license update. If the leader goes down for some

zirain <******@****.***> 1713796107 +0800

					}
				}
				// Collect updates.
				updates := make(chan dataUsageEntry, 1)
				var wg sync.WaitGroup
				wg.Add(1)
				go func(name string) {
					defer wg.Done()
					for update := range updates {
						select {
						case <-ctx.Done():
						case bucketResults <- dataUsageEntryInfo{
							Name:   name,
							Parent: dataUsageRoot,
							Entry:  update,
						}:
						}
					}