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- groutr · 3 ✖
id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
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1489744942 | https://github.com/pydata/xarray/pull/7698#issuecomment-1489744942 | https://api.github.com/repos/pydata/xarray/issues/7698 | IC_kwDOAMm_X85Yy7Qu | groutr 10678620 | 2023-03-30T06:02:41Z | 2023-03-30T06:03:03Z | NONE | Agreed, and a reference to a pretty authoritative source: https://github.com/python/cpython/blob/3.11/Modules/_io/bufferedio.c#L915 It's confusing the method has a parameter called One workaround is to use |
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Use read1 instead of read to get magic number 1646350377 | |
1489312337 | https://github.com/pydata/xarray/issues/7697#issuecomment-1489312337 | https://api.github.com/repos/pydata/xarray/issues/7697 | IC_kwDOAMm_X85YxRpR | groutr 10678620 | 2023-03-29T20:59:24Z | 2023-03-29T20:59:24Z | NONE | @dcherian I'll look at that. I thought the @headtr1ck I was just informed that the underlying filesystem is actually a networked filesystem. The PR might still be useful, but the latest profile seems more reasonable in light of my new info. |
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open_mfdataset very slow 1646267547 | |
1489267595 | https://github.com/pydata/xarray/issues/7697#issuecomment-1489267595 | https://api.github.com/repos/pydata/xarray/issues/7697 | IC_kwDOAMm_X85YxGuL | groutr 10678620 | 2023-03-29T20:30:49Z | 2023-03-29T20:33:28Z | NONE |
I tried setting the engine to 'netcdf4' and while it did help a little bit, it still seems slow on my system. Here is my profile with I'm not sure what to make of this profile. I don't see anything in the file_manager that would be especially slow. Perhaps it is a filesystem bottleneck at this point (given that the cpu time is 132s of the total 288s duration). |
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open_mfdataset very slow 1646267547 |
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