../mkzip ../../zoneinfo.zip
cd ../..

files="update.bash zoneinfo.zip"
modified=true
if git diff --quiet $files; then
	modified=false
fi

if [ "$1" = "-work" ]; then
	echo Left workspace behind in work/.
	shift
else
	rm -rf work
fi

if ! $modified; then
	echo No updates needed.
	exit 0
fi

echo Updated for $CODE/$DATA: $files

commitmsg="lib/time: update to $CODE/$DATA

```

////

### 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`).

	if utils.AssertEqual(result.UpdatedAt, user.UpdatedAt) {
		t.Fatalf("Update struct should update UpdatedAt, was %+v, got %+v", result.UpdatedAt, user.UpdatedAt)
	}

	AssertObjEqual(t, result, User{Name: "update_with_select"}, "Name", "Age")
}

func TestSelectWithUpdateWithMap(t *testing.T) {

          fetch-depth: 0
      - name: Update jdks.yaml
        uses: gradle/update-jdks-action@main
      - name: Create Pull Request
        uses: peter-evans/create-pull-request@v7
        with:
          signoff: true
          sign-commits: true
          commit-message: "Update jdks.yaml"
          add-paths: .teamcity/jdks.yaml
          title: "Update jdks.yaml"

	if lastUpdatedAt.Format(time.RFC3339) == user4.Account.UpdatedAt.Format(time.RFC3339) {
		t.Fatalf("updated at should be updated, but not, old: %v, new %v", lastUpdatedAt.Format(time.RFC3339), user3.Account.UpdatedAt.Format(time.RFC3339))
	} else {
		user.Account.UpdatedAt = user4.Account.UpdatedAt
		CheckUser(t, user4, user)
	}

	t.Run("Polymorphic", func(t *testing.T) {
		pet := Pet{Name: "create"}

# 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

				return nil
			}
		}
		opts := updateServiceAccountOpts{
			secretKey:     change.Update.SecretKey,
			status:        change.Update.Status,
			name:          change.Update.Name,
			description:   change.Update.Description,
			sessionPolicy: sp,
			expiration:    change.Update.Expiration,
		}

				if i, ok := value.(BeforeUpdateInterface); ok {
					called = true
					db.AddError(i.BeforeUpdate(tx))
				}
			}

			return called
		})
	}
}

// Update update hook
func Update(config *Config) func(db *gorm.DB) {
	supportReturning := utils.Contains(config.UpdateClauses, "RETURNING")

	return func(db *gorm.DB) {
		if db.Error != nil {
			return
		}

////

//// tab | Python 3.8+

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

////

### Pydantics `update`-Parameter verwenden

Jetzt können Sie eine Kopie des existierenden Modells mittels `.model_copy()` erstellen, wobei Sie dem `update`-Parameter ein `dict` mit den zu ändernden Daten übergeben.

/// info

	// 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.