id,node_id,number,title,user,state,locked,assignee,milestone,comments,created_at,updated_at,closed_at,author_association,active_lock_reason,draft,pull_request,body,reactions,performed_via_github_app,state_reason,repo,type
847014702,MDU6SXNzdWU4NDcwMTQ3MDI=,5098,open_dataset regression,2448579,closed,0,35919497,,2,2021-03-31T17:32:03Z,2021-04-15T12:11:34Z,2021-04-15T12:11:34Z,MEMBER,,,,"<!-- Please include a self-contained copy-pastable example that generates the issue if possible.

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**What happened**:

`open_dataset` doesn't replace `~` any more

**What you expected to happen**:

should replace `~` for backward compatibility

**Minimal Complete Verifiable Example**:

```python
import xarray as xr

da = xr.DataArray([1, 2, 3])
da.to_netcdf(""~/bug_report.nc"")

xr.open_dataarray(""~/bug_report.nc"")
```

**Anything else we need to know?**:
works on 0.17.0, fails on master
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717410970,MDU6SXNzdWU3MTc0MTA5NzA=,4496,Flexible backends - Harmonise zarr chunking with other backends chunking,35919497,closed,0,35919497,,7,2020-10-08T14:43:23Z,2020-12-10T10:51:09Z,2020-12-10T10:51:09Z,COLLABORATOR,,,,"<!-- Please do a quick search of existing issues to make sure that this has not been asked before. -->

**Is your feature request related to a problem? Please describe.**
In #4309 we proposed to separate xarray - backend tasks, more or less in this way:
- Backend returns a dataset
- xarray manage chunks and cache.

With the changes in open_dataset to support also zarr (#4187 ), we introduced a slightly different behavior for zarr chunking with respect the other backends.

*Behavior of all the backends except zar*
- if chunk == {} or 'auto': it uses dask and only one chunk per variable
- if the user defines chunks for not all the dimensions, along these dimensions it uses only one chunk:
```python
>>> ds = xr.open_dataset('test.nc', chunks={'x': 4})
>>> print(ds['foo'].chunks)
((4, 4, 4, 4, 4), (4,))
``` 
*Zarr chunking behavior* is very similar, but it has a different default when the user doesn't choose the size of the chunk along some dimensions, i.e.
- if chunk == {} or 'auto': it uses in both cases the on-disk chunks
- if the user defines the chunks for not all the dimensions, along these dimensions it uses no disk chunck:
```python
>>> ds = xr.open_dataset('test.zarr', engine='zarr', chunks={'x': 4})
>>> print(ds['foo'].encoding['chunks'])
(5, 2)
>>> print(ds['foo'].chunks)
((4, 4, 4, 4, 4), (2, 2))
```   

**Describe the solution you'd like**

We could extend easily zarr behavior to all the backends (which, for now, don't use the field variable.encodings['chunks']): 
if no chunks are defined in encoding, we use as default the dimension size, otherwise, we use the encoded chunks. So for now we are not going to change any external behavior, but if needed the other backends can use this interface.
I have some additional notes:

- The key value `auto` is redundant because it has the same behavior as `{}`, we could remove one of them.
- I would separate the concepts ""on disk chunk"" and ""preferred chunking"".  We can use a different key in encodings or ask the backend to expose a function to compute the preferred chunking.

One last question:
- In the new interface of open_dataset there is a new key, imported from open_zarr: `overwrite_encoded_chunks`. Is it really needed? Why do we support to overwrite of the encoded chunks at readi time? This operation can be easily done after or at write time.
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