issue_comments: 372856076
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html_url | issue_url | id | node_id | user | created_at | updated_at | author_association | body | reactions | performed_via_github_app | issue |
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https://github.com/pydata/xarray/issues/1823#issuecomment-372856076 | https://api.github.com/repos/pydata/xarray/issues/1823 | 372856076 | MDEyOklzc3VlQ29tbWVudDM3Mjg1NjA3Ng== | 14314623 | 2018-03-13T23:40:54Z | 2018-03-13T23:40:54Z | CONTRIBUTOR | Would these two options be necessarily mutually exclusive? I think parallelizing the read in sounds amazing. But isnt there some merit in skipping some of the checks all together, if the user is sure about the structure of the data contained in the many files? I am often working with the aforementioned type of data (many files either contain a new timestep or a different variable, but most of the dimensions/coordinates are the same). In some cases I am finding that reading the data "lazily" consumes a significant amount of the time in my workflow. I am unsure how hard this would be to achieve, and perhaps it is not worth it after all. Just putting out a few ideas, while I wait for my |
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