Aggregate Sequences Value Cardinality

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

Find approximate property count for sequences.

Parameters:

  • property (SequenceProperty | str | list[str]) – The property to count the cardinality of.

  • advanced_filter (Filter | dict[str, Any] | None) – The filter to narrow down the sequences to count cardinality.

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

  • filter (SequenceFilter | dict[str, Any] | None) – The filter to narrow down the sequences to count requiring exact match.

Returns:

The number of properties matching the specified filters and search.

Return type:

int

Examples

Count the number of different values for the metadata key “efficiency” used for sequences in your CDF project:

>>> from cognite.client import CogniteClient
>>> from cognite.client.data_classes.sequences import SequenceProperty
>>> client = CogniteClient()
>>> # async_client = AsyncCogniteClient()  # another option
>>> count = client.sequences.aggregate_cardinality_values(
...     SequenceProperty.metadata_key("efficiency")
... )

Count the number of timezones (metadata key) for sequences with the word “critical” in the description in your CDF project, but exclude timezones from america:

>>> from cognite.client.data_classes import filters, aggregations as aggs
>>> from cognite.client.data_classes.sequences import SequenceProperty
>>> not_america = aggs.Not(aggs.Prefix("america"))
>>> is_critical = filters.Search(SequenceProperty.description, "critical")
>>> timezone_count = client.sequences.aggregate_cardinality_values(
...     SequenceProperty.metadata_key("timezone"),
...     advanced_filter=is_critical,
...     aggregate_filter=not_america,
... )