DataFrameFactory.
for_exec_result_id
for_exec_result_id(
result_id: str, label_overrides: Optional[LabelOverrides], result_cache_metadata: Optional[ResultCacheMetadata], result_size_dimensions_limits: ResultSizeDimensions, result_size_bytes_limit: Optional[int], use_local_ids_in_headers: bool, use_primary_labels_in_attributes: bool, page_size: int
) ->
Tuple[pandas.DataFrame, DataFrameMetadata]
Retrieves a DataFrame and DataFrame metadata for a given execution result identifier.
Example of label_overrides structure: .. code-block:: python { "labels": { "local_attribute_id": { "title": "My new attribute label" ,... }, "metrics": { "local_metric_id": { "title": "My new metric label" },... } }
Parameters
| name | type | description |
|---|---|---|
| result_id | str | Execution result identifier. |
| label_overrides | Optional[LabelOverrides] | Label overrides for metrics and attributes. |
| result_cache_metadata | Optional[ResultCacheMetadata] | Cache metadata for the execution result. |
| result_size_dimensions_limits | ResultSizeDimensions | A tuple containing maximum size of result dimensions. |
| result_size_bytes_limit | Optional[int] | Maximum size of result in bytes. |
| use_local_ids_in_headers | bool | Use local identifier in headers. |
| use_primary_labels_in_attributes | bool | Use primary labels in attributes. |
| page_size | int | Number of records per page. |
Returns
| type | description |
|---|---|
| Tuple[pandas.DataFrame, DataFrameMetadata] | Tuple holding DataFrame and DataFrame metadata. |