Further - the underlying ranking is buried in needless mystique (you know a boolean should query, sums the scores, right?). You shouldn't need to read a book (like Relevant Search ;) ) to unpack mystique that's really basic math.

Why not just let people build ranking systems with vectorized math in a numpy/pandas stack?

SearchArray lets anyone build a relevance prototype in Pandas. Typically building / experimenting with a smaller labeled dataset. If it works out, you can transfer it relatively easily to Elasticsearch or Solr for implementation and testing.

SearchArray is a pandas extension array that creates an underlying search index for BM25 term/phrase based searching.

It's not quite done (will it ever be?) but its getting far enough along to be useful. So feedback is very welcome.

https://github.com/softwaredoug/searcharray