https://github.com/joist-orm/joist-orm/blob/16cc73f148b6f962...
I forgot the speedup this got us on a 400-500 table schema, but it was noticeable -- curious if you could do the same / what the perf impact would be.
https://github.com/joist-orm/joist-orm/blob/16cc73f148b6f962...
I forgot the speedup this got us on a 400-500 table schema, but it was noticeable -- curious if you could do the same / what the perf impact would be.
But lets say we just always cleared all the tables: 5ms per test * 6000 tests == 30s, across 15 test processes it is 2s of overhead to the test run. Meh. You are better off auditing your test setup functions that get reused (create_test_user etc) for how many queries they do, you might find that your overall test setup spends 20% of it's runtime creating users. When I did this I found that 50% of our test runtime was processing stack traces in logging statements (to show where in the code it was being logged from), modifying it to only put tracebacks on INFO and above cut our total testing time by almost 50%.
We use sequences, which is neither of those, and has been very reliable for us.
I included the disclaimer that you need a schema that follows strict sequence name => table name conventions, but that's what we have.
> 20% of runtime creating users
Right -- we also have ~2-3 "stable" rows of users that every test needs, so we can skip re-creating for each test.