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I propose two new methods, FindEventIdsData and FindEventsData and a set
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of new symbols/enums called AggregateMethod as described below.
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* everything is a mixture of python and pseudo code
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) --> (auau) "tuple of two lists of equal length containing integers"
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) --> (aEau) "same as above, but in the first list the ids are replaced by the actual events"
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* track was played maximum on Banshee
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>>> ids = FindEventIds(
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... TimeRange.always(),
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... [Event.new_for_values(actor="banshee", subject_interpretation=Interpretation.MUSIC),],
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... ResultType.MostPopularSubjects
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Which means, the subject of event 1 is most popular, followed by
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But we currently don't know *how* popular they are.
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>>> ids, data = FindEventIDsData(
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... TimeRange.always(),
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... [Event.new_for_values(actor="banshee", subject_interpretation=Interpretation.MUSIC),],
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... ResultType.MostPopularSubjects,
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... AggregateMethod.Count
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So, ids is the same as above; data contains the `count` for each
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subject. So the subject represented by event 1 was played 500 times,
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followed by the subject represented by event 2 with 250 times.
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* average number of plays from each player