html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,issue,performed_via_github_app
https://github.com/simonw/datasette/issues/420#issuecomment-474407617,https://api.github.com/repos/simonw/datasette/issues/420,474407617,MDEyOklzc3VlQ29tbWVudDQ3NDQwNzYxNw==,9599,2019-03-19T14:55:51Z,2019-03-19T14:55:51Z,OWNER,"A microbenchmark against `fivethirtyeight.db` (415 tables):

    In [1]: import sqlite3                                                                                              
    In [2]: c = sqlite3.connect(""fivethirtyeight.db"")                                                                   
    In [3]: %timeit c.execute(""select name from sqlite_master where type = 'table'"").fetchall()                         
    283 µs ± 12.3 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)
    In [4]: tables = [r[0] for r in c.execute(""select name from sqlite_master where type = 'table'"").fetchall()]        
    In [5]: len(tables)                                                                                                 
    Out[5]: 415
    In [6]: %timeit [c.execute(""pragma foreign_keys([{}])"".format(t)).fetchall() for t in tables]                       
    1.81 ms ± 161 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)

So running `pragma foreign_keys()` against 415 tables only takes 1.81ms. This is going to be fine.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",421971339,