issue_comments: 303606683

How about something like the following:

In encode_cf_variable, create a new variable with pickle encoded data (if appropriate). This looks something like: ```python def encode_cf_variable(var, allow_pickle=False): ... if var.dtype == object: if allow_pickle: var = maybe_encode_pickle(var) else: raise TypeError return var

def maybe_encode_pickle(var): if var.dtype == object: attrs = var.attrs.copy() safe_setitem('_FileFormat', 'python-pickle') protocol = var.encoding.pop('pickle_protocol', 2) data = utils.encode_pickle(var.values, protocol=protocol) var = Variable(var.dims, data, attrs, var.encoding) return var `` This reuses theencoding` parameter for setting the pickle protocol version, which is already what we use for similar variable specific encoding details.

In the netCDF backends, add a check for variable with dtype == object with a _FileFormat attribute. If this is the case, call a create_vlen_int8_dtype method to create an appropriate dtype using backend specific methods (The behavior on the base class should raise an error), and proceed with writing the data in the usual way.

For decoding, reverse the process. Convert custom vlen dtypes to dtype=object in the appropriate backend specific array wrapper type, but don't decode data. If allow_pickle=True and var.attrs['_FileFormat'] == 'python-pickle', then decode_cf_variable should do the unpickling, moving _FileFormat from attrs to encoding.

For bonus points, generalize handling of vlen types with encoding. Something like encoding={'dtype': {'vlen': np.int8}} could indicate that a special vlen with np.int8 data should be created to encode this variable's data. (This is inspired by h5py's API for special types.)