Try sharing common parts of workflow compute to make tests run faster #182
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This is demonstrating an approach that could save some test runtime. In this example a parametrized test is running a nearly identical workflow 8 times, each time loading data from scratch, etc. The change here moves some of the common parts into a module-scope fixture. On my machine this reduces the test runtime from 50 seconds to 22 seconds. I do not know if this is a great solution. If we want to go with this, a helper utility could be made: Given a sciline.Pipeline and a set of keys, compute all intermediate results that to not depend on those keys and set the results as "static" data in the workflow. This would avoid error-prone manual authoring of fixtures like the one I added here.
nvaytet
reviewed
Nov 1, 2024
| @@ -98,10 +121,11 @@ def test_pipeline_can_compute_IofQ(uncertainties, qxy: bool): | |||
| BackgroundSubtractedIofQxy, | |||
| ], | |||
| ) | |||
| def test_pipeline_can_compute_IofQ_in_event_mode(uncertainties, target): | |||
| pipeline = make_workflow() | |||
| def test_pipeline_can_compute_IofQ_in_event_mode( | |||
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I think the approach is fine. The test looks almost identical to before, it just has a fixture which has some pre-computed stuff in it. It's not making some tests depend on others or anything like that.
How does it change the overall time it takes to run all tests?
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How does it change the overall time it takes to run all tests?
You would have to do something similar for quite a few more tests. But the worse offender is currently the beam-center finder, but I don't feel it is worth playing with that.
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This is demonstrating an approach that could save some test runtime. In this example a parametrized test is running a nearly identical workflow 8 times, each time loading data from scratch, etc.
The change here moves some of the common parts into a module-scope fixture. On my machine this reduces the test runtime from 50 seconds to 22 seconds.
I do not know if this is a great solution. If we want to go with this, a helper utility could be made: Given a sciline.Pipeline and a set of keys, compute all intermediate results that to not depend on those keys and set the results as "static" data in the workflow. This would avoid error-prone manual authoring of fixtures like the one I added here.