issue_comments: 1112889800

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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/1727#issuecomment-1112889800 https://api.github.com/repos/simonw/datasette/issues/1727 1112889800 IC_kwDOBm6k_c5CVVnI 9599 2022-04-29T05:29:38Z 2022-04-29T05:29:38Z OWNER

OK, I just got the most incredible result with that!

I started up a container running bash like this, from my datasette checkout. I'm mapping port 8005 on my laptop to port 8001 inside the container because laptop port 8001 was already doing something else: docker run -it --rm --name my-running-script -p 8005:8001 -v "$PWD":/usr/src/myapp \ -w /usr/src/myapp nogil/python bash Then in bash I ran the following commands to install Datasette and its dependencies: pip install -e '.[test]' pip install datasette-pretty-traces # For debug tracing Then I started Datasette against my github.db database (from github-to-sqlite.dogsheep.net/github.db) like this:

datasette github.db -h 0.0.0.0 --setting trace_debug 1 I hit the following two URLs to compare the parallel v.s. not parallel implementations:

  • http://127.0.0.1:8005/github/issues?_facet=milestone&_facet=repo&_trace=1&_size=10
  • http://127.0.0.1:8005/github/issues?_facet=milestone&_facet=repo&_trace=1&_size=10&_noparallel=1

And... the parallel one beat the non-parallel one decisively, on multiple page refreshes!

Not parallel: 77ms

Parallel: 47ms

So yeah, I'm very confident this is a problem with the GIL. And I am absolutely stunned that @colesbury's fork ran Datasette (which has some reasonably tricky threading and async stuff going on) out of the box!

 
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