List data sets

async AsyncCogniteClient.data_sets.list(
metadata: dict[str, str] | None = None,
created_time: dict[str, Any] | TimestampRange | None = None,
last_updated_time: dict[str, Any] | TimestampRange | None = None,
external_id_prefix: str | None = None,
write_protected: bool | None = None,
limit: int | None = 25,
) → DataSetList

List data sets.

Parameters:

  • metadata (dict[str, str] | None) – Custom, application-specific metadata. String key -> String value.

  • created_time (dict[str, Any] | TimestampRange | None) – Range between two timestamps.

  • last_updated_time (dict[str, Any] | TimestampRange | None) – Range between two timestamps.

  • external_id_prefix (str | None) – Filter by this (case-sensitive) prefix for the external ID.

  • write_protected (bool | None) – Specify whether the filtered data sets are write-protected, or not. Set to True to only list write-protected data sets.

  • limit (int | None) – Maximum number of data sets to return. Defaults to 25. Set to -1, float(“inf”) or None to return all items.

Returns:

List of requested data sets

Return type:

DataSetList

Examples

List data sets and filter on write_protected:

>>> from cognite.client import CogniteClient, AsyncCogniteClient
>>> client = CogniteClient()
>>> # async_client = AsyncCogniteClient()  # another option
>>> data_sets_list = client.data_sets.list(limit=5, write_protected=False)

Iterate over data sets, one-by-one:

>>> for data_set in client.data_sets():
...     data_set  # do something with the data set

Iterate over chunks of data sets to reduce memory load:

>>> for data_set_list in client.data_sets(chunk_size=2500):
...     data_set_list  # do something with the list