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- Continue to use nanosecond-precision Timestamps in precision-sensitive areas · 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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1507109914 | https://github.com/pydata/xarray/pull/7731#issuecomment-1507109914 | https://api.github.com/repos/pydata/xarray/issues/7731 | IC_kwDOAMm_X85Z1Kwa | spencerkclark 6628425 | 2023-04-13T14:50:15Z | 2023-04-13T14:50:15Z | MEMBER | Thanks for noting that @dcherian -- I think I got to all of them now. |
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Continue to use nanosecond-precision Timestamps in precision-sensitive areas 1657396474 | |
1506059299 | https://github.com/pydata/xarray/pull/7731#issuecomment-1506059299 | https://api.github.com/repos/pydata/xarray/issues/7731 | IC_kwDOAMm_X85ZxKQj | spencerkclark 6628425 | 2023-04-12T22:42:26Z | 2023-04-12T22:42:26Z | MEMBER | Thanks all for the help! Fingers crossed things should be all green now. Happy to address any more review comments. |
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Continue to use nanosecond-precision Timestamps in precision-sensitive areas 1657396474 | |
1499107154 | https://github.com/pydata/xarray/pull/7731#issuecomment-1499107154 | https://api.github.com/repos/pydata/xarray/issues/7731 | IC_kwDOAMm_X85ZWo9S | spencerkclark 6628425 | 2023-04-06T13:57:56Z | 2023-04-06T13:57:56Z | MEMBER | I'm fine waiting until #7724 is merged to let our main CI cover this. Indeed the upstream tests are flaky. Locally I just installed pandas 2 via pip to do testing during development. |
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Continue to use nanosecond-precision Timestamps in precision-sensitive areas 1657396474 |
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user 1