Improved round tripping for attrs

Is your feature request related to a problem?

Consider the following dataset:

import xarray as xr
dataset = xr.Dataset()
dataset.attrs = {
    'empty_attribute': [],
    'attribute_of_length_1': ['one_item_only'],
    'attribute_of_length_2': ['one_item', 'two_items'],
}
dataset.to_netcdf('foo.nc')

loaded = xr.open_dataset('foo.nc')

from pprint import pprint
pprint(loaded.attrs)

pprint(loaded.attrs)
{'attribute_of_length_1': 'one_item_only',
 'attribute_of_length_2': ['one_item', 'two_items'],
 'empty_attribute': array([], dtype=float64)}

1. The attrs that contains an empty list has become an array of type float
2. The attrs that contains a list of one element, has been downcast to a scalar
3. The attrs that contains two elements has been kept as a list of strings.

Describe the solution you'd like

A away to ensure that lists stay lists.

Does this option already exists?

Describe alternatives you've considered

Writing nice error prone if statements

Additional context

I tried to look through https://github.com/pydata/xarray/blob/main/xarray/tests/test_dataset.py and didn't find anything that was testing this special behavior.

Start with the reproducible Dataset.to_netcdf and xr.open_dataset example, then inspect xarray/tests/test_dataset.py, which the issue identifies as a likely test location. Reproduce the empty, one-item, and two-item attribute cases and add coverage for preserving list values through round tripping.