Hello,

As the test suite is growing, it’s getting slower. I’ve tried to make it faster 
by running tests in parallel.

The current state of my experiment is here: 
https://github.com/django/django/pull/4063 
<https://github.com/django/django/pull/4063>

I’m distributing the tests to workers with the multiprocessing module. While 
the idea is simple, the unittest APIs make its implementation painful.

** Results **

Without the patch:

Ran 9016 tests in 350.610s
./runtests.py  355,86s user 20,48s system 92% cpu 6:48,23 total

With the patch

Ran 9016 tests in 125.778s
./runtests.py --parallel  512,31s user 29,92s system 300% cpu 3:00,73 total

Since it takes almost one minute to create databases, parallelization makes the 
execution of tests go from 6 minutes to 2 minutes.

This isn’t bad, but the x3 speedup is a bit disappointing given that I have 4 
physical / 8 logical cores. Perhaps the IPC is expensive.

Does anyone have insights about scaling with multiprocessing?

** Limitations **

This technique works well with in-memory SQLite databases. Each process gets 
its own copy of the database in its memory space.

It fails with on-disk SQLite databases. SQLite can’t cope with this level of 
concurrency. It timeouts while attempting to lock the database.

It fails with PostgreSQL (and, I assume, other databases) because tests 
collide, for instance when they attempt to load the same fixture.

** Next steps **

At this point, the patch improves the common use case of running 
`./runtests.py` locally to check a database-independent change, and little else.

Do you think it would be useful to include it in Django anyway? Do you have 
concerns about the implementation? Charitably, I’ll say that “it works”…

Releasing it separately as a custom test runner may be more appropriate.

What do you think?

-- 
Aymeric.



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