Hi, I am using netCDF4 to store complex data using the recommended strategy of creating a compound data type with the real and imaginary parts. This all works well, but reading the data into a numpy array is a bit clumsy. Typically I do: nc = netCDF4.Dataset('my.nc') cplx_data = nc.groups['mygroup'].variables['cplx_stuff'][:].view('complex') which directly gives a nice complex numpy array. This is OK for small arrays, but is wasteful if I only need some chunks of the array because it reads all the data in, reducing the utility of the mmap feature of netCDF. I'm wondering if there is a better way to directly make a numpy array view that uses the netcdf variable's memory mapped buffer directly. Looking at the Variable class, there is no access to this buffer directly which could then be passed to np.ndarray(buffer=...). Any ideas of simple solutions to this problem? Thanks, Glenn