report_run_with_results

Create a new Run, report results to it, and close it.

dbnl.report_run_with_results(
    project: ,
    column_data: pd.DataFrame,
    scalar_data: Optional[Union[dict[str, Any], pd.DataFrame]] = None
    display_name: Optional[str] = None,
    row_id: Optional[list[str]] = None,
    run_config_id: Optional[str] = None,
    metadata: Optional[dict[str, str]] = None,
) -> Run:

Parameters

Arguments	Description
project	The dbnl Project that this Run will be associated with.
column_data	A pandas DataFrame with all the column results to report to dbnl. If run_config_id is provided, the columns of the DataFrame must match the columns described in the RunConfig.
scalar_data	A dict or pandas DataFrame with all the scalar results to report to dbnl. If run_config_id is provided, the key of the dict must match the scalars described in the RunConfig.
display_name	An optional display name for the Run. Display names do not have to be unique.
row_id	An optional list of the column names that can be used as unique identifiers.
run_config_id	ID of the RunConfig to use for the Run, defaults to None. If provided, the RunConfig is used as is and the results are validated against it. If not provided, a new Run Config is inferred from the column_data.
metadata	Any additional key-value pairs information the user wants to track.

Returns

Type	Description
Run	The closed Run with the uploaded data.

Examples

import dbnl
import pandas as pd
dbnl.login()


proj = dbnl.get_or_create_project(name="test_p1")
test_data = pd.DataFrame({"error": [0.11, 0.33, 0.52, 0.24]})

run = dbnl.report_run_with_results(
    project=proj,
    column_data=test_data,
    row_id=["idx"],
)