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/2015#issuecomment-375926070,https://api.github.com/repos/pydata/xarray/issues/2015,375926070,MDEyOklzc3VlQ29tbWVudDM3NTkyNjA3MA==,6815844,2018-03-24T21:26:54Z,2018-03-24T21:26:54Z,MEMBER,"I am curious why this test is failing in appveyor.
The casting rule of numpy should not depend on the operating system.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,308284379
https://github.com/pydata/xarray/pull/2015#issuecomment-375916591,https://api.github.com/repos/pydata/xarray/issues/2015,375916591,MDEyOklzc3VlQ29tbWVudDM3NTkxNjU5MQ==,6815844,2018-03-24T18:58:57Z,2018-03-24T18:58:57Z,MEMBER,"Thanks @fmaussion .

> Is there a way to make sure this line casts to a secure dtype better than my proposed solution to cast everything to a float64 first?

How about `np.array([np.int32(2)]) * np.array([np.int64(2)])`?

I am not sure whether numpy explains this casting behavior, but I guess this is intentional.
This is consistent with
```python
In [11]: (np.array([1.0], dtype=np.float32) * 1.0).dtype
Out[11]: dtype('float32')
```
where we expect the array dtype takes precedence.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,308284379