caution
This function is experimental and might be changed or removed in a future minor release. Use with caution in production code.
fetch_runs_table_global()
Python package: neptune-query
Fetches a table of run metadata, with runs as rows and attributes as columns. The query targets projects globally, across all workspaces that the user can access with the provided API token.
To limit the results, define filters for runs to search or attributes to include.
Parameters
Returns
pandas.DataFrame – A DataFrame similar to the runs table in the web app.
The DataFrame has:
- a single-level index
"run"with run IDs - a single-level column index with attribute names
For series attributes, the last logged value is returned.
Raises
AttributeTypeInferenceError– If the attribute type wasn't specified in a filter passed to therunsargument.ConflictingAttributeTypes– If there are conflicting attribute types under the same path and thetype_suffix_in_column_namesargument is set toFalse.
Example
Fetch two specific runs across all projects, with attributes matching loss or configs as columns:
import neptune_query.experimental as nq_experimental
nq_experimental.fetch_runs_table_global(
runs=["run-123", "run-456"], # exact run IDs
attributes=r"loss | configs",
)
Fetch runs that belong to a specific experiment, with attributes matching loss or configs as columns:
import neptune_query.experimental as nq_experimental
from neptune_query.filters import Filter, Attribute
nq_experimental.fetch_runs_table_global(
runs=Filter.eq(Attribute("sys/experiment/name", "string"), "exp-week-9"),
attributes=r"loss | configs",
)