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Run Continuous Integration tests on Github Actions #475
Run Continuous Integration tests on Github Actions #475
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We can speed up the dependency install using caching too, see https://github.com/goanpeca/setup-miniconda#caching. I've used it for one of my projects, the relevant commit is at weiji14/deepicedrain@391632b.
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Yes, I saw that. But I'm not sure how the caches are updated. For example, we may cache numpy v1.18.0 now. When new numpy versions are released, conda will download and install the latest version (e.g., numpy v1.19.0). What will happen to the caches? Do the caches contains the tarballs of numpy v1.18.0, v1.19.0 or both? Do we have to manually update the cache key?
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The cache would hash the
environment.yml/requirement.txt
files, and unless the hash changes, the cache will stay at v1.18.0 (unless we manually update the cache key). Maybe we should start thinking about a minimum supported dependency policy, as I suggested at #340 (comment).There was a problem hiding this comment.
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We need to change these lines when bumping to 6.1. In 6.1, the earth relief data are stored in
~/.gmt/server/earth/earth_relief/
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Need to change
gmt which -Ga
in GMT 6.1.