Just for the record, I just ran into this for the specific case of nested dictionary attrs in Dataarray.attrs.

It's definitely an issue in 2022.3.0 and 2022.6.0. Here's a minimal test example in case anyone else runs into this too...

```python

MINIMAL EXAMPLE

import xarray as xr import numpy as np

data = xr.DataArray(np.random.randn(2, 3), dims=("x", "y"), coords={"x": [10, 20]}) data.attrs['flat']='0' data.attrs['nested']={'level1':'1'}

data2 = data.copy(deep=True) data2.attrs['flat']='2' # OK

data2.attrs['nested']={'level1':'2'} # OK

data2.attrs['nested']['level1'] = '2' # Fails - overwrites data

data2.attrs['nested'].update({'level1':'2'}) # Fails - overwrites data

print(data.attrs) print(data2.attrs) ```

Outputs

In XR 2022.3.0 and 2022.6.0 this gives (incorrect): ``` {'flat': '0', 'nested': {'level1': '2'}} {'flat': '2', 'nested': {'level1': '2'}}

```

As a work-around, safe attrs copy with deepcopy works:

```python data2 = data.copy(deep=True) data2.attrs = copy.deepcopy(data.attrs)

```

With correct results after modification: ``` {'flat': '0', 'nested': {'level1': '1'}} {'flat': '2', 'nested': {'level1': '2'}}

```

EDIT 26th Sept: retested in 2022.6.0 and found it was, in fact, failing there too. Updated comment to reflect this.

Ok, I thought that copying attrs was fixed. Seems like it did not...

Sorry for the mix-up there - think I initially tested in 2022.6 with the extra data2.attrs = copy.deepcopy(data.attrs) implemented. Caught it with the new test routine 😄

OK, new test now pushed as #7086. (Hopefully added in the right place and style!)

A couple of additional notes:

• Revision to my comment above: this actually fails in 2022.3 and 2022.6 for nested attribs.
• I took a look at the source code in dataarray.py, but couldn't see an obvious way to fix this and/or didn't understand the attrs copying process generally.
• I tested the equivalent case for DataSet attrs too (see below), and this seems fine as per your previous comments above, so I think https://github.com/pydata/xarray/pull/2839 (which includes a ds level test) still applies to ds.attrs, however the issue does affect the individual arrays within the dataset still (as expected).

```python import xarray as xr

ds = xr.Dataset({"a": (["x"], [1, 2, 3])}, attrs={"t": 1, "nested":{"t2": 1}}) ds.a.attrs = {"t": 'a1', "nested":{"t2": 'a1'}}

ds2 = ds.copy(deep=True) ds.attrs["t"] = 5 ds.attrs["nested"]["t2"] = 10

ds2.a.attrs["t"] = 'a2' ds2.a.attrs["nested"]["t2"] = 'a2'

print(ds.attrs) print(ds.a.attrs) print(ds2.attrs) print(ds2.a.attrs)

```

Results in:

``` {'t': 5, 'nested': {'t2': 10}} {'t': 'a1', 'nested': {'t2': 'a2'}} {'t': 1, 'nested': {'t2': 1}} {'t': 'a2', 'nested': {'t2': 'a2'}}

```

Absolutely @headtr1ck, glad that it was useful - I'm a bit green re: tests and PRs to large projects, but will make a stab at it. I'm just consulting the Contributing guide now.