datarobot-mlops-stats-aggregator 10.1.2

datarobot-mlops-stats-aggregator library to compute statistics aggregations

MLOps Stats Aggregation Library (Python)

Usage

The Python library for MLOps stats aggregation has two entry points:

aggregate_stats

The aggregate_stats function in aggregation.py is the primary entry point into the library. This function accepts dataframes of raw features and/or predictions and aggregates statistics suitable to be submitted to DataRobot MLOps for deployment monitoring. In order to use this function, the types of each tracked feature must be specified, and certain feature types (e.g. currency) require additional format information. See the docstring and type declarations of aggregate_stats for details about specific requirements.

merge_stats

The merge_stats function defined in merging.py is used to merge together the outputs of calls to aggregate_stats. It returns a value with the same shape as that returned by aggregate_stats. Merging stats makes sense (for example) in the MLOps Tracking Agent, which will buffer stats aggregated by the MLOps Reporting Library. The agent can merge those buffered stats before sending them in a single payload to DataRobot MLOps.