issue_comments

@mrpgraae no, I don't think this has been implemented yet.

Please take a look at #1508 for an example of the model to use: - Define an open classmethod method for loading from a URL. - __init__ should accept a pydap dataset object (whatever is returned from pydap.client.open_url)

You are also welcome to add any keyword parameters (e.g., session) that open_url accepts to the open method.

So the user API becomes: python pydap_ds = pydap.client.open_url(url, session=session) store = xarray.backends.PydapDataStore(pydap_ds) ds = xarray.open_dataset(store) or python store = xarray.backends.PydapDataStore.open(url, session=session) ds = xarray.open_dataset(store)

Nevermind, I figured it out (I was using an old version of pydap by mistake). See #1439 for the pydap fix.

I spent a few minutes on this but am still getting AttributeError. It would be great if someone could put some time into debugging this. Should be as simple as installing pydap (in both python 2 and 3 virtual/conda environments) and getting py.test -k PydapTest to pass.

I'm still having problems trying to get xarray.open_dataset to work with pydap. Using the latest commit on pydap/master (in which pydap/pydap#48 is merged) I'm now getting a new error: AttributeError: '<class 'pydap.model.BaseType'>' object has no attribute 'encode'. When I have some time, I'll look into it further and try to see what else is needed to restore compatibility.

Indeed, it would be great if someone using pydap could take a look into this. You can find our logic for interoperating with pydap here: https://github.com/pydata/xarray/blob/master/xarray/backends/pydap_.py

Pydap has a new v3.2 release, but it still needs some fixes to work with xarray -- or xarray needs to be updated to work with the new version of pydap. I think https://github.com/pydap/pydap/pull/48 once merged would probably be enough to restore xarray compatibility.

Parsing username/password from the URL would be very easy to add.

We need to figure out a solution for the proliferating arguments on open_dataset before we add many more, so I would prefer that for now.

Another option is to add session as an argument on xarray.backends.PydapDataStore, and encourage passing PydapDataStore objects into xarray.open_dataset for extra customizability, e.g., store = xarray.backends.PydapDataStore(url, session) ds = xarray.open_dataset(store)

If the dataset has a "time" dimension, try accessing the first few values. Can you view them in pydap? Xarray's open_dataset does a little more work than pydap's open_url, insofar as it actually downloads some array data.

If you write engine='pydap' in open_dataset, the URL should be passed directly on to pydap, but you'll still need to follow all of their other instructions. If you're getting an error message from xarray, let us know but otherwise I'm at a loss -- you should check with the folks at NASA.