Suggesting specific IO backends to install when open_dataset() fails

[shoyer]

Currently, Xarray's internal backends don't get registered unless the necessary dependencies are installed:

xarray/xarray/backends/netCDF4_.py

Lines 567 to 568 in 1305d9b

	if has_netcdf4:
	BACKEND_ENTRYPOINTS["netcdf4"] = NetCDF4BackendEntrypoint

In order to facilitating suggesting a specific backend to install (e.g., to improve error messages from opening tutorial datasets #5291), I would suggest that Xarray always registers its own backend entrypoints. Then we make the following changes to the plugin protocol:

• guess_can_open() should work regardless of whether the underlying backend is installed
• installed() returns a boolean reporting whether backend is installed. The default method in the base class would return True, for backwards compatibility.
• open_dataset() of course should error if the backend is not installed.

This will let us leverage the existing guess_can_open() functionality to suggest specific optional dependencies to install. E.g., if you supply a netCDF3 file: Xarray cannot find a matching installed backend for this file in the installed backends ["h5netcdf"]. Consider installing one of the following backends which reports a match: ["scipy", "netcdf4"]

Does this reasonable and worthwhile?

CC @aurghs @alexamici

[aurghs]

Me too, I was thinking about something like that to fix the error message.
Let me try to implement it. But I have really no time this week and the next one, sorry. I can do it after 23th if for you is ok.

[shoyer]

Sounds good, I'll make a short-term fix for the tutorial data

[shoyer]

Another advantage of "always registering" backends is that I think it will make for a better user-experience when installing a new dependency for IO via pip, because they won't have to restart their Python session: #5291 (comment)