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/pull/2031#issuecomment-378472194,https://api.github.com/repos/pydata/xarray/issues/2031,378472194,MDEyOklzc3VlQ29tbWVudDM3ODQ3MjE5NA==,5635139,2018-04-04T03:52:21Z,2018-04-04T03:52:21Z,MEMBER,Yes good idea. I'll add that to my (metaphorical) list.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,309976469
https://github.com/pydata/xarray/pull/2031#issuecomment-378423195,https://api.github.com/repos/pydata/xarray/issues/2031,378423195,MDEyOklzc3VlQ29tbWVudDM3ODQyMzE5NQ==,5635139,2018-04-03T22:45:47Z,2018-04-03T22:45:47Z,MEMBER,"I'll merge this later tonight given @shoyer 's previous approval, unless there's any feedback","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,309976469
https://github.com/pydata/xarray/pull/2031#issuecomment-378253855,https://api.github.com/repos/pydata/xarray/issues/2031,378253855,MDEyOklzc3VlQ29tbWVudDM3ODI1Mzg1NQ==,5635139,2018-04-03T13:40:57Z,2018-04-03T13:40:57Z,MEMBER,Green! @shoyer ,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,309976469
https://github.com/pydata/xarray/pull/2031#issuecomment-377642905,https://api.github.com/repos/pydata/xarray/issues/2031,377642905,MDEyOklzc3VlQ29tbWVudDM3NzY0MjkwNQ==,5635139,2018-03-30T23:08:12Z,2018-03-30T23:08:12Z,MEMBER,"Any thoughts on this approach of writing out the result on a slice of a sample dataset / dataarray? 

I've been thinking about expect tests, as described by @yminsky [here](https://blog.janestreet.com/testing-with-expectations/). 
That would be something like: 
- Have some example datasets (similar to what we do now, though with a well known seed)
- Run our functions and save to a file, as a known good output
- During tests, compare the result to the known good output
- Where different, raise and show the diff

That's a bit harder with numerical data than with small lists of words (the example in the link), but also helpful - we don't have to manually construct the result in python - just check the first time & commit the result. And would enable tests across moderately sized data, rather than only 'toy' examples.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,309976469
https://github.com/pydata/xarray/pull/2031#issuecomment-377573270,https://api.github.com/repos/pydata/xarray/issues/2031,377573270,MDEyOklzc3VlQ29tbWVudDM3NzU3MzI3MA==,5635139,2018-03-30T17:12:56Z,2018-03-30T17:12:56Z,MEMBER,"Fails on Numpy pre 1.13. Is that too recent to upgrade min version? 1.14.2 is current, so would be aggressive","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,309976469