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integrate numpy datetime64 for greater range of years #77
Description
- how much does the code change? how much does numpy.datetime64 help, how heavy of a dependency is this?
- could this be optional, for people who need the expanded year range but not installed by default?
benchmarking / documentation:
- how long does it take to run the test suite with/without numpy?
- how big is the installation size with/without?
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rlskoeser commentedon Jul 11, 2024
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rlskoeser commentedon Jul 11, 2024
From NumPy installation docs:
[-]test integrating numpy datetime64 for greater range of years[/-][+]integrate numpy datetime64 for greater range of years[/+]Merge pull request #84 from dh-tech/experiment/numpy-datetime64
rlskoeser commentedon Nov 8, 2024
@ColeDCrawford as I close this out, I remembered you wanted some benchmarking / assessment on the numpy inclusion. The test suite is pretty fast either way, and we've also been expanding the functionality in other ways, so it's not a strict comparison.
Running a checkout of the 0.2 tag, I get
Running in current develop, I get
I compared the virtualenv size when installing version 0.2 and current develop. Without numpy, the virtualenv is 14MB; with numpy it's 46MB. Looking at the folders in the sitep ackages for the latter, the numpy folder is 31MB on its own.
Let me know if you think any of this needs to be documented in the changelog or elsewhere.
ColeDCrawford commentedon Nov 8, 2024
Nice, thanks for remembering that. Seems like a negligible performance difference with the main change being the payload size, but we knew about that going in. I think it would be nice to note in the changelog for the v1.0 release