sha,message,author_date,committer_date,raw_author,raw_author_label,raw_committer,raw_committer_label,repo,repo_label,author,author_label,committer,committer_label
553314dcd699a84aa7cc806377150ca0d57a6024,Use dist: xenial and python: 3.7 on Travis (#447),2019-05-03T18:16:52Z,2019-05-03T18:16:52Z,13ae486343ea6454a93114c6f558ffea2f2c6874,Simon Willison,cd792325681cbad9f663f2879d8b69f1edbb678f,GitHub,107914493,datasette,9599,simonw,19864447,web-flow
ea66c45df96479ef66a89caa71fff1a97a862646,"Extract facet code out into a new plugin hook, closes #427 (#445)

Datasette previously only supported one type of faceting: exact column value counting.

With this change, faceting logic is extracted out into one or more separate classes which can implement other patterns of faceting - this is discussed in #427, but potential upcoming facet types include facet-by-date, facet-by-JSON-array, facet-by-many-2-many and more.

A new plugin hook, register_facet_classes, can be used by plugins to add in additional facet classes.

Each class must implement two methods: suggest(), which scans columns in the table to decide if they might be worth suggesting for faceting, and facet_results(), which executes the facet operation and returns results ready to be displayed in the UI.",2019-05-03T00:11:26Z,2019-05-03T00:11:26Z,13ae486343ea6454a93114c6f558ffea2f2c6874,Simon Willison,cd792325681cbad9f663f2879d8b69f1edbb678f,GitHub,107914493,datasette,9599,simonw,19864447,web-flow