datarobot-mlops-stats-aggregator library to compute statistics aggregations
MLOps Stats Aggregation Library (Python)
The Python library for MLOps stats aggregation has two entry points:
aggregate_stats function in
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 function defined in
is used to merge together the outputs of calls to
aggregate_stats. It returns a value with the same shape as that
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.
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