This documentation is for the unstable version of GoodData, currrently in development.
For stable version, go to the latest stable version of this article.
For stable version, go to the latest stable version of this article.
catalog_workspace_content.
load_and_put_declarative_ldm
load_and_put_declarative_ldm(workspace_id: str, layout_root_path: Path, validator: Optional[DataSourceValidator], standalone_copy: bool)
This method combines load_declarative_ldm and put_declarative_ldm methods to load and set layouts stored using store_declarative_ldm.
Parameters
| name | type | description |
|---|---|---|
| workspace_id | str | Workspace identification string e.g. "demo" |
| layout_root_path | Path | Path to the root of the layout directory. Defaults to Path.cwd(). |
| validator | Optional[DataSourceValidator] | Object that manages validation, whether each data_source_id in LDM corresponds to existing data source. Defaults to None. |
| standalone_copy | bool | If true, then workspace data filter references will be removed from LDM. Note that first, the copy is made so we do not interfere with the original input. |
Returns
NoneExample
The load and put can be done two ways.
Either by one call:
# Load and put logical data model.
sdk.catalog_workspace_content.load_and_put_declarative_ldm(
workspace_id="123",
layout_root_path=Path.cwd()
)Or by two separate calls:
# Load stored declarative Logical Data Model
logical_model = sdk.catalog_workspace_content.load_declarative_ldm(
workspace_id="123",
layout_root_path=Path.cwd()
)
# Put logical data model
sdk.catalog_workspace_content.put_declarative_ldm(
workspace_id="123",
ldm=logical_model
)The result is identical.