{* ../../docs_src/body_updates/tutorial002_py310.py hl[32] *}

### Використання параметра `update` у Pydantic { #using-pydantics-update-parameter }

Тепер Ви можете створити копію наявної моделі за допомогою `.model_copy()`, і передати параметр `update` з `dict`, який містить дані для оновлення.

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

{* ../../docs_src/body_updates/tutorial002_py310.py hl[33] *}

{* ../../docs_src/body_updates/tutorial002_py310.py hl[32] *}

### Usando o parâmetro `update` do Pydantic { #using-pydantics-update-parameter }

Agora, você pode criar uma cópia do modelo existente usando `.model_copy()`, e passar o parâmetro `update` com um `dict` contendo os dados para atualizar.

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

{* ../../docs_src/body_updates/tutorial002_py310.py hl[33] *}

{* ../../docs_src/body_updates/tutorial002_py310.py hl[32] *}

### 使用 Pydantic 的 `update` 参数 { #using-pydantics-update-parameter }

接下来，用 `.model_copy()` 为已有模型创建副本，并传入 `update` 参数，值为包含更新数据的 `dict`。

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

{* ../../docs_src/body_updates/tutorial002_py310.py hl[33] *}

### 部分更新小结 { #partial-updates-recap }

简而言之，应用部分更新应当：

* （可选）使用 `PATCH` 而不是 `PUT`。
* 提取已存储的数据。

### Pydantic의 `update` 파라미터 사용하기 { #using-pydantics-update-parameter }

이제 `.model_copy()`를 사용해 기존 모델의 복사본을 만들고, 업데이트할 데이터가 들어있는 `dict`를 `update` 파라미터로 전달할 수 있습니다.

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

{* ../../docs_src/body_updates/tutorial002_py310.py hl[33] *}

### 부분 업데이트 요약 { #partial-updates-recap }

정리하면, 부분 업데이트를 적용하려면 다음을 수행합니다:

        with:
          signoff: true
          sign-commits: true
          commit-message: "Update jdks.yaml"
          add-paths: .teamcity/jdks.yaml
          title: "Update jdks.yaml"
          body: "This PR updates JDK to the latest versions available in `.teamcity/jdks.yaml`."
          delete-branch: true
          branch: "devprod/update-jdks"
          branch-suffix: timestamp
          labels: |
            in:building-gradle

# 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

        with:
          commit-message: Update test buckets
          branch: devprod/update-test-buckets
          branch-suffix: timestamp
          delete-branch: true
          title: 'Update test buckets'
          signoff: true
          sign-commits: true
          labels: |
            in:building-gradle
            @dev-productivity
          body: |

          branch-suffix: timestamp
          delete-branch: true
          title: 'Update performance test durations'
          signoff: true
          sign-commits: true
          labels: |
            in:building-gradle
            @dev-productivity
          body: |

package clause

type Update struct {
	Modifier string
	Table    Table
}

// Name update clause name
func (update Update) Name() string {
	return "UPDATE"
}

// Build build update clause
func (update Update) Build(builder Builder) {
	if update.Modifier != "" {
		builder.WriteString(update.Modifier)
		builder.WriteByte(' ')
	}

	if update.Table.Name == "" {
		builder.WriteQuoted(currentTable)
	} else {

	// 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.