issue_comments: 388749495

This data as json

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/817#issuecomment-388749495 https://api.github.com/repos/pydata/xarray/issues/817 388749495 MDEyOklzc3VlQ29tbWVudDM4ODc0OTQ5NQ== 6488896 2018-05-14T09:11:08Z 2018-05-14T09:11:08Z NONE

I am trying to understand the logic by looking through the comments/discussion on this commit. After two years of development, there are quite some changes on the API itself e.g. the logic on the gzipped file handling seems already moved from api.py to scipy_.py. So I think it would be better to start a new commit from the latest version.

To bring the concept on the same table, there are 3 backends that can be used to handle gzipped netCDF file namely scipy, netcdf4 and pydap. scipy backend only support netCDF3 so far and that is the only implemented method to handle gzipped netCDF3 file. netcdf4 and pydap should able to deal with netCDF4 file given the file is first opened by gzip.open (as it was implement in scipy_.py).

So what we need to do is to make both netCDF4_.py and pydap_.py aware of the file is end with .gz and first open it using gzip.open. Following tests also need to be done to verify the implementation of the logic. I have looked at vcrpy and it seems a nice idea to speed up tests with HTTP stuff involved. I must confess I only use xarray with local file so it may takes quite a while to understand the issue. 

{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   146079798