issue_comments: 50713976

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https://github.com/pydata/xarray/issues/190#issuecomment-50713976 https://api.github.com/repos/pydata/xarray/issues/190 50713976 MDEyOklzc3VlQ29tbWVudDUwNzEzOTc2 1217238 2014-07-31T05:26:39Z 2014-07-31T05:26:39Z MEMBER

There is at least one major advantage to using abbreviations: less typing and shorter lines of code!

e.g., compare:

python x = xray.Coord('x', np.arange(10)) y = xray.Coord('y', ['a', 'b', 'c']) arr = xray.DataArray(data, dims=['x', 'y'], coords=[x, y]) 'x' in arr.dims

and

python x = xray.Coordinate('x', np.arange(10)) y = xray.Coordinate('y', ['a', 'b', 'c']) arr = xray.DataArray(data, dimensions=['x', 'y'], coordinates=[x, y]) 'x' in arr.dimensions

h5py does use dims instead of dimensions: http://docs.h5py.org/en/2.3/high/dims.html and Iris also uses the abbreviations "dim" and "coord".

These are pretty common/obvious abbreviations and they are fundamental enough that I would not worry about imposing them on our users.

Right now, I am leaning toward switching to always using dim/dims and coord/coords/Coord before the 0.2 release. But I don't want to be too hasty about this -- any opinions out there? The counter argument would be that I should stop wasting my time bike-shedding (especially after I've already released this stuff out in the wild).

 
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