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When the dask library is installed as a dependency (through the result_caching module, see here), calls to scipy.stats.pearsonr become significantly slower. This slowdown notably impacts performance during ceiling calculations, which rely on result_caching. Removing or bypassing dask in this workflow returns pearsonr to its expected speed. We need to investigate why dask is causing this overhead and how to mitigate it without sacrificing functionality in result_caching.
The text was updated successfully, but these errors were encountered:
When the
dask
library is installed as a dependency (through theresult_caching
module, see here), calls toscipy.stats.pearsonr
become significantly slower. This slowdown notably impacts performance during ceiling calculations, which rely onresult_caching
. Removing or bypassingdask
in this workflow returnspearsonr
to its expected speed. We need to investigate whydask
is causing this overhead and how to mitigate it without sacrificing functionality inresult_caching
.The text was updated successfully, but these errors were encountered: