issue_comments: 669502001
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| html_url | issue_url | id | node_id | user | created_at | updated_at | author_association | body | reactions | performed_via_github_app | issue |
|---|---|---|---|---|---|---|---|---|---|---|---|
| https://github.com/pydata/xarray/issues/4313#issuecomment-669502001 | https://api.github.com/repos/pydata/xarray/issues/4313 | 669502001 | MDEyOklzc3VlQ29tbWVudDY2OTUwMjAwMQ== | 221526 | 2020-08-05T20:52:33Z | 2020-08-05T20:52:33Z | CONTRIBUTOR | So on MetPy we moved to treating our CI system as an application and pinning every direct dependency in a requirements.txt (which can be used by conda as well). We then let dependabot handle the updates. This let's us manage the updates on a package-by-package basis, where we have a single PR that lets us see what the ramifications are with regards to tests, CI, even linting. We've been running for a limited time, but so far it has done a good job of insulating general development (coming in on PRs) from changes in the environment, which now shouldn't change on CI from run to run (yeah, yeah 2nd-order dependencies, just pin problematic ones too). For instance, for the pandas 1.1.0 breakage, we just haven't merged the PR that moves the pin there, and that has kept our doc builds green on MetPy. |
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