html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/pull/6823#issuecomment-1204156997,https://api.github.com/repos/pydata/xarray/issues/6823,1204156997,IC_kwDOAMm_X85HxfpF,14371165,2022-08-03T16:05:10Z,2022-08-03T16:05:10Z,MEMBER,"> I guess we could introduce some sort of `xarray` specific formatting mini-language to solve that? For example:
> 
>     * `f""{arr:r}"": print the object's `repr` (the default)
> 
>     * `f""{arr:b}"": print the array backend's `repr`(only for`DataArray`/`Variable`)

Interesting idea. I was thinking just adding `format_spec` to `formatting.array_repr` so the repr can handle `__format__` as well should be enough. It seemed much more involved though.

Anyway that's for another PR. I think this PR is ready now, I think it should handle the main request in #5976 without being so intrusive in other cases.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1316549018
https://github.com/pydata/xarray/pull/6823#issuecomment-1200289273,https://api.github.com/repos/pydata/xarray/issues/6823,1200289273,IC_kwDOAMm_X85HivX5,14371165,2022-07-30T20:31:01Z,2022-07-30T20:31:01Z,MEMBER,"This is how it behaves right now. I believe this should be the same behavior as previously now with the extra possibility to format scalar arrays:


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

s = pd.Series(
    range(4),
    index=pd.MultiIndex.from_product([list(""ab""), list(""cd"")]),
)

da = xr.DataArray.from_series(s, sparse=True)

# Handle sparse:
print(f""Error: {da} is sparse"")
Error: <xarray.DataArray (level_0: 2, level_1: 2)>
<COO: shape=(2, 2), dtype=float64, nnz=4, fill_value=nan>
Coordinates:
  * level_0  (level_0) object 'a' 'b'
  * level_1  (level_1) object 'c' 'd' is sparse

# Handle format_spec:
da = xr.DataArray([1, 2, 3])

print(f'{da[0]}')
<xarray.DataArray ()>
array(1)

print(f'{da[0]:d}')
1

print(f'{da[0]:f}')
1.000000

da = xr.DataArray([1, 2, 3])
print(f'{da:.f}')
Traceback (most recent call last):
(...)
NotImplementedError: Using format_spec is only supported when shape is (). Got shape = (3,).
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1316549018
https://github.com/pydata/xarray/pull/6823#issuecomment-1193853083,https://api.github.com/repos/pydata/xarray/issues/6823,1193853083,IC_kwDOAMm_X85HKMCb,14371165,2022-07-25T10:15:16Z,2022-07-25T10:15:16Z,MEMBER,"Hmm, I'm not a fan that f-strings by default uses the backend array only:

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

s = pd.Series(
    range(4),
    index=pd.MultiIndex.from_product([list(""ab""), list(""cd"")]),
)

da = xr.DataArray.from_series(s, sparse=True)

# Uses __format__:
print(f""Error: {da} is sparse"")
Error: <COO: shape=(2, 2), dtype=float64, nnz=4, fill_value=nan> is sparse
```

Should it by default just use the repr instead? But it won't feel very consistent once string formatting are used though.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1316549018