Stephan Hoyer

An interface that accepts file images in the form of `bytes` would be a big improvement over what we have now. The driver of performance is the number of memory...

@rsignell-usgs Nope, it can only do netCDF4/HDF5 files. But you could try pydap for that...

Indeed, calling this pure Python is perhaps overly generous -- it does depend on the HDF5 C library. The implementation of netCDF4 on top of HDF5 is pure Python, though....

@jswhit as for your initialization issues, that does seem strange/unfortunate. I haven't encountered that personally on OS X (I'm using h5py and netCDF4 via conda).

@jswhit Yes and no. It doesn't do numpy-style broadcasting indexing so it's not inconsistent with orthogonal indexing, but it also does not support indexing with one than one array, e.g.,...

@gamaanderson Interesting. I'm sure it depends on lots of specifics about your configuration and workflow. For example, I found that `scipy.io.netcdf` can be about twice as fast for reading netCDF3...

@gamaanderson I've been developing h5netcdf on h5py 2.4 and 2.5. You'll definitely need at least h5py 2.1, because that's the first release that included support for dimension scales (which are...

@gamaanderson This feedback is super helpful, thanks! 1. This was mostly intentional -- I'm not a big fan of overloading attribute access in this somewhat ambiguous way. But if people...

It might make sense to use a higher level abstraction like [xarray](http://xarray.pydata.org) for this. You could load your data in memory into an xarray.Dataset, and use xarray to modify the...

This isn't well documented at present at xarray, but you can pass in an open netCDF4.Dataset object to `xarray.backends.NetCDF4DataStore`: https://github.com/pydata/xarray/pull/1508