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  • ashwinvis · 2 ✖

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  • Performance: numpy indexes small amounts of data 1000 faster than xarray · 2 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
539352070 https://github.com/pydata/xarray/issues/2799#issuecomment-539352070 https://api.github.com/repos/pydata/xarray/issues/2799 MDEyOklzc3VlQ29tbWVudDUzOTM1MjA3MA== ashwinvis 9155111 2019-10-08T06:08:27Z 2019-10-08T06:08:48Z CONTRIBUTOR

I suspect system jitter in the profiling as the time for Dataset.isel went up. It would be useful to run sudo python -m pyperf system tune before running profiler/benchmarks.

 
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   Performance: numpy indexes small amounts of data 1000 faster than xarray 416962458
538366978 https://github.com/pydata/xarray/issues/2799#issuecomment-538366978 https://api.github.com/repos/pydata/xarray/issues/2799 MDEyOklzc3VlQ29tbWVudDUzODM2Njk3OA== ashwinvis 9155111 2019-10-04T11:57:10Z 2019-10-04T11:57:10Z CONTRIBUTOR

At first sight it looks somewhat like a hybrid between Cython (for the ahead-of-time transpiling to C++) and numba (for having python-compatible syntax).

Not really. Pythran always releases the GIL and does a bunch of optimizations between transpilation and compilations.

A good approach would be try out different compilers and see what performance is obtained, without losing readability (https://github.com/pydata/xarray/issues/2799#issuecomment-469444519). See scikit-image/scikit-image/issues/4199 where the package transonic was being experimentally tested to replace Cython-only code with python code + type hints. As a bonus, you get to switch between Cython, Pythran and Numba,

 
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   Performance: numpy indexes small amounts of data 1000 faster than xarray 416962458

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