issues: 773750763

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773750763 MDU6SXNzdWU3NzM3NTA3NjM= 4727 xr.testing.assert_equal does not test for dtype 10194086 open 0     5 2020-12-23T13:14:41Z 2021-07-04T04:08:51Z   MEMBER      

In #4622 @toddrjen points out that xr.testing.assert_equal does not test for the dtype, only for the value. Therefore the following does not raise an error:

```python import numpy as np import xarray as xr import pandas as pd

xr.testing.assert_equal( xr.DataArray(np.array(1, dtype=int)), xr.DataArray(np.array(1, dtype=float)) ) xr.testing.assert_equal( xr.DataArray(np.array(1, dtype=int)), xr.DataArray(np.array(1, dtype=object)) ) xr.testing.assert_equal( xr.DataArray(np.array("a", dtype=str)), xr.DataArray(np.array("a", dtype=object)) ) ```

This comes back to numpy, i.e. the following is True:

python np.array(1, dtype=int) == np.array(1, dtype=float)

Depending on the situation one or the other is desirable or not. Thus, I would suggest to add a check_dtype argument to xr.testing.assert_equal and also to DataArray.equals (and Dataset and Variable and identical). I have not seen such an option in numpy, but pandas has it (e.g. pd.testing.assert_series_equal(left, right, check_dtype=True, ...). I would not change __eq__.

  • Thoughts?
  • What should the default be? We could try True first and see how many failures this creates?
  • What to do with coords and indexes? pd.testing.assert_series_equal has a check_index_type keyword. Probably we need check_coords_type as well? This makes the whole thing much more complicated... Also #4543
 
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