)]}'
{"doc/source/graph.rst":[{"author":{"_account_id":1921,"name":"Andrea Frittoli","email":"andrea.frittoli@gmail.com","username":"andrea-frittoli"},"change_message_id":"f3f0b0ced6be3aaf26053e8b440e117badf786ab","unresolved":false,"context_lines":[{"line_number":149,"context_line":""},{"line_number":150,"context_line":"will generate a graph like:"},{"line_number":151,"context_line":""},{"line_number":152,"context_line":".. image:: graph-run_time_meta.png"},{"line_number":153,"context_line":""},{"line_number":154,"context_line":"It\u0027s also worth noting the --filter_list argument used in the command above."},{"line_number":155,"context_line":"In some cases, especially larger data sets, there are too many distinct values"}],"source_content_type":"text/x-rst","patch_set":7,"id":"ba2be162_43011539","line":152,"range":{"start_line":152,"start_character":0,"end_line":152,"end_character":34},"updated":"2017-03-06 20:49:27.000000000","message":"The PNG is too big, have a look at the rendered docs.","commit_id":"37514e68b33962cd24820ce58f3c2975e87e08f5"}],"subunit2sql/analysis/run_time_meta.py":[{"author":{"_account_id":1921,"name":"Andrea Frittoli","email":"andrea.frittoli@gmail.com","username":"andrea-frittoli"},"change_message_id":"f3f0b0ced6be3aaf26053e8b440e117badf786ab","unresolved":false,"context_lines":[{"line_number":54,"context_line":"            [(k, pd.Series(v)) for k, v in run_times.iteritems()]))"},{"line_number":55,"context_line":"    else:"},{"line_number":56,"context_line":"        df \u003d pd.DataFrame(dict("},{"line_number":57,"context_line":"            [(k, pd.Series(v)) for k, v in run_times.iteritems()"},{"line_number":58,"context_line":"             if k in filter_list]))"},{"line_number":59,"context_line":"    if not CONF.title:"},{"line_number":60,"context_line":"        title \u003d \"Run aggregate run time grouped by metadata\""}],"source_content_type":"text/x-python","patch_set":7,"id":"ba2be162_fea9be91","line":57,"range":{"start_line":57,"start_character":53,"end_line":57,"end_character":62},"updated":"2017-03-06 20:49:27.000000000","message":"For py3 compatibility it would be nicer to use:\n\ndict([k, pd.Series(run_times(k) for k in run_times if k in filter_list])\n\nbut I\u0027m not sure if it would be much worse performance-wise.","commit_id":"37514e68b33962cd24820ce58f3c2975e87e08f5"}]}