sections_fts: 14

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rowid	title	content
14	register_facet_classes()	Return a list of additional Facet subclasses to be registered. The design of this plugin hook is unstable and may change. See issue 830 . Each Facet subclass implements a new type of facet operation. The class should look like this: class SpecialFacet(Facet): # This key must be unique across all facet classes: type = "special" async def suggest(self): # Use self.sql and self.params to suggest some facets suggested_facets = [] suggested_facets.append( { "name": column, # Or other unique name # Construct the URL that will enable this facet: "toggle_url": self.ds.absolute_url( self.request, path_with_added_args( self.request, {"_facet": column} ), ), } ) return suggested_facets async def facet_results(self): # This should execute the facet operation and return results, again # using self.sql and self.params as the starting point facet_results = [] facets_timed_out = [] facet_size = self.get_facet_size() # Do some calculations here... for column in columns_selected_for_facet: try: facet_results_values = [] # More calculations... facet_results_values.append( { "value": value, "label": label, "count": count, "toggle_url": self.ds.absolute_url( self.request, toggle_path ), "selected": selected, } ) facet_results.append( { "name": column, "results": facet_results_values, "truncated": len(facet_rows_results) > facet_size, } ) except QueryInterrupted: facets_timed_out.append(column) return facet_results, facets_timed_out See datasette/facets.py for examples of how these classes can work. The plugin hook can then be used to register the new facet class like this: @hookimpl def register_facet_classes(): return [SpecialFacet]