Aggregate Asset Value Cardinality

async AsyncCogniteClient.assets.aggregate_cardinality_values(
property: AssetProperty | str | list[str],
advanced_filter: Filter | dict[str, Any] | None = None,
aggregate_filter: AggregationFilter | dict[str, Any] | None = None,
filter: AssetFilter | dict[str, Any] | None = None,
) → int

Find approximate property count for assets.

Parameters:

  • property (AssetPropertyLike) – The property to count the cardinality of.

  • advanced_filter (Filter | dict[str, Any] | None) – The advanced filter to narrow down assets.

  • aggregate_filter (AggregationFilter | dict[str, Any] | None) – The filter to apply to the resulting buckets.

  • filter (AssetFilter | dict[str, Any] | None) – The filter to narrow down assets (strict matching).

Returns:

The number of properties matching the specified filters and search.

Return type:

int

Examples

Count the number of labels used by assets in your CDF project:

>>> from cognite.client import CogniteClient
>>> from cognite.client.data_classes.assets import AssetProperty
>>> client = CogniteClient()
>>> # async_client = AsyncCogniteClient()  # another option
>>> label_count = client.assets.aggregate_cardinality_values(AssetProperty.labels)

Count the number of timezones (metadata key) for assets with the word “critical” in the description in your CDF project:

>>> from cognite.client.data_classes.filters import Search
>>> from cognite.client.data_classes.assets import AssetProperty
>>> is_critical = Search(AssetProperty.description, "critical")
>>> critical_assets = client.assets.aggregate_cardinality_values(
...     AssetProperty.metadata_key("timezone"), advanced_filter=is_critical
... )