issue_comments

That's right. I just did a quick 0.1 release of xncml, most likely rough around the edges. Give it a spin. PRs most welcome.

@rabernat If you're happy with it, this issue can probably be closed.

@andersy005 Sounds good !

Ok, another option would be to add that to xncml

@andersy005 What do you think ?

I've got a first draft that parses an NcML document and spits out an xarray.Dataset. It does not cover all the NcML syntax, but the essential elements are there.

It uses xsdata to parse the XML, using a datamodel automatically generated from the NcML 2-2 schema. I've scrapped test files from the netcdf-java repo to create a test suite.

Wondering what's the best place to host the code, tests and test data so others may give it a spin ?

I'd like to revive this issue. We're increasingly using NcML aggregations within our THREDDS server to create "logical" datasets. This allows us to fix some non-CF-conforming metadata fields without changing files on disk (which would break syncing with ESGF nodes). More importantly, by aggregating multiple time periods, variables and realizations, we're able to create catalog entries for simulations instead of files, which we expect will greatly facilitate parsing catalog search results. We'd like to offer the same aggregation functionality outside of the THREDDS server. Ideally, this would be supported right from the netcdf-c library (see https://github.com/Unidata/netcdf-c/issues/1478), but an xarray NcML backend is the second best option. I also imagine that NcML files could be use as a clean mechanism to create Zarr/NCZarr objects ie: *.nc -> open_ncml -> xr.Dataset -> to_zarr -> Zarr store

@andersy005 In terms of API, I think the need is not so much to create or modify NcML files, but rather to return an xarray.Dataset from an NcML description. My understanding is that open_ncml would be a wrapper around open_mfdataset. My hope is that NcML-based xarray.Dataset objects would behave similarly whether they are created from files on disk through xarray.open_ncml('sim.ncml') or xarray.open_dataset('https://.../thredds/sim.ncml').

The THREDDS repo contains a number of unit tests that could be emulated to steer the Python implementation. My understanding is that getting this done could involve a fair amount of work, so I'd like to see who's interested in collaborating on this and maybe schedule a meeting to plan work for this year or the next.