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/3257#issuecomment-526550941,https://api.github.com/repos/pydata/xarray/issues/3257,526550941,MDEyOklzc3VlQ29tbWVudDUyNjU1MDk0MQ==,10050469,2019-08-30T10:27:22Z,2019-08-30T12:38:00Z,MEMBER,"> Can't we have a nightly build of docker images with all the xarray depencencies?

This would help on Travis yes, but not on RTD which doesn't support docker. But otherwise yes, I've also found that CI is faster and more reliable with docker. In terms of resources ""in general"", I wonder if it wouldn't be nice to share a common testing image base with other packages of the pydata ecosytem. ","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,484711431
https://github.com/pydata/xarray/issues/3257#issuecomment-526545364,https://api.github.com/repos/pydata/xarray/issues/3257,526545364,MDEyOklzc3VlQ29tbWVudDUyNjU0NTM2NA==,10050469,2019-08-30T10:07:59Z,2019-08-30T10:07:59Z,MEMBER,"RTD is struggling with resources, and I can understand that. What is really annoying (and the problem is often the same on travis) is that the conda install is taking a huge part of the build process resources. See e.g. https://github.com/readthedocs/readthedocs.org/issues/6025 , where I ended up using pip for very satisfying results (!).","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,484711431