Broomstick provides a set of functions to compute metrics based on GrimoireLab data.
It tries to de-couple the implementation of the metrics and the data access layer. GrimoireLab data model is currently based on ElasticSearch indexes, so it is the current data access layer. On top of this, Pandas data frames are used to store and return the data.
A basic view of Broomstick components could be:
broomstick/data: data access layer. Returns basic data types and Pandas data frames.broomstick/metrics: where the metrics are implemented.test: self-explanatory, the tests.notebooks: Jupyter notebooks to implement different use cases based on the metrics provided by Broomstick. They can be seen as specific reports. They are not part of Broomstick by themselves, nevertheless they can be considered a front-end for the Broomstick metrics.