issue_comments: 612598462

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https://github.com/pydata/xarray/issues/3959#issuecomment-612598462 https://api.github.com/repos/pydata/xarray/issues/3959 612598462 MDEyOklzc3VlQ29tbWVudDYxMjU5ODQ2Mg== 14808389 2020-04-12T11:11:26Z 2020-04-12T22:18:31Z MEMBER

Is there any reason not to put the name of the type into attrs and just switch on that rather than the keys in data_vars?

Not really, I just thought the variables in the dataset were a way to uniquely identify its variant (i.e. do the validation of the dataset's structure). If you have different means to do so, of course you can use that instead.

Re TypedDict: the PEP introducing TypedDict especially mentions that it is only intended for Dict[str, Any] (so no subclasses of Dict for TypedDict). However, looking at the code of TypedDict, we should be able to do something similar for Dataset.

Edit: we'd still need to convince mypy that the custom TypedDict is a type...

so I'm curious if that has been discussed much

I don't think so? There were a few discussions about subclassing, but I couldn't find anything about static type analysis. It's definitely worth having this discussion, either here (repurposing this issue) or in a new issue.

 
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