Support for attributes with different dtypes when serialising to netcdf4

[lewisacidic]

At the moment, bool and dates aren't supported as attributes when serializing to netcdf4:

>>> da = xr.DataArray(range(5), attrs={'test': True})
>>> da 
<xarray.DataArray (dim_0: 5)>
array([0, 1, 2, 3, 4])
Dimensions without coordinates: dim_0
Attributes:
    test:     True

>>> da.to_netcdf('test_bool.nc')
...
TypeError: illegal data type for attribute, must be one of dict_keys(['S1', 'i1', 'u1', 'i2', 'u2', 'i4', 'u4', 'i8', 'u8', 'f4', 'f8']), got b1

>>> da = xr.DataArray(range(5), attrs={'test': pd.to_datetime('now')})
>>> da
<xarray.DataArray (dim_0: 5)>
array([0, 1, 2, 3, 4])
Dimensions without coordinates: dim_0
Attributes:
    test:     2017-08-03 13:02:29

>>> da.to_netcdf('test_dt.nc')
...
TypeError: Invalid value for attr: 2017-08-03 13:02:29 must be a number string, ndarray or a list/tuple of numbers/strings for serialization to netCDF files

I assume bool attributes aren't supported by netcdf4-python and dates are difficult (could always just write these as a string), but this would be really nice to have if possible.

As an aside, using h5netcdf works for bools, but coerces them to int64.

[shoyer]

These aren't supported by the netCDF4 file format, so there's not a straightforward way to add them.

We could add some custom serialization logic (like we do for variable dtypes like bool), but without the ability to put an attribute on an attribute I don't see how we could round-trip this safely.

I suppose as a last resort we could write such attributes as bytestrings in some custom serialization format, but then it has the downside of not being readable by any other tool.

[shoyer]

I guess this could work as part of your PR #1421 to support using pickle for array values.

[stale]

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[half-adder]

Still relevant