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/issues/7354#issuecomment-1352342017,https://api.github.com/repos/pydata/xarray/issues/7354,1352342017,IC_kwDOAMm_X85QmxoB,2443309,2022-12-14T23:08:43Z,2022-12-14T23:09:06Z,MEMBER,"After thinking about this for a bit longer, I think we should be strongly considering dropping source encoding for datasets generated by `open_mfdataset`. Or, if nothing else, thinking about ways to alert the user that encoding was not consistent across all of the datasets loaded.
Other relevant issues:
- https://github.com/pydata/xarray/issues/1614
- https://github.com/pydata/xarray/issues/6323
- https://github.com/pydata/xarray/issues/7039","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1474785646
https://github.com/pydata/xarray/issues/7354#issuecomment-1352337857,https://api.github.com/repos/pydata/xarray/issues/7354,1352337857,IC_kwDOAMm_X85QmwnB,2443309,2022-12-14T23:04:58Z,2022-12-14T23:04:58Z,MEMBER,"I took a minute to look into this and think I understand what is going on. First, a little debugging:
```python
for name in [files[0], files[1], path]:
print(name)
ds = xr.open_zarr(name, decode_cf=False)
print(' > time.attrs', ds.time.attrs)
print(' > time.encoding', ds.time.encoding)
```
```
tmp_dir/2022-09-01T03:00:00.zarr.zip
> time.attrs {'calendar': 'proleptic_gregorian', 'units': 'days since 2022-09-01 03:00:00'}
> time.encoding {'chunks': (1,), 'preferred_chunks': {'time': 1}, 'compressor': Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0), 'filters': None, 'dtype': dtype('int64')}
tmp_dir/2022-09-01T04:00:00.zarr.zip
> time.attrs {'calendar': 'proleptic_gregorian', 'units': 'days since 2022-09-01 04:00:00'}
> time.encoding {'chunks': (1,), 'preferred_chunks': {'time': 1}, 'compressor': Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0), 'filters': None, 'dtype': dtype('int64')}
tmp.zarr.zip
> time.attrs {'calendar': 'proleptic_gregorian', 'units': 'days since 2022-09-01'}
> time.encoding {'chunks': (1,), 'preferred_chunks': {'time': 1}, 'compressor': Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0), 'filters': None, 'dtype': dtype('int64')}
```
A few things that I noticed:
- the dtype of the time variable is `int64`.
- the units attr is `days since ...`.
`open_mfdataset` tends to take the units of the first file and doesn't check if all the others agree. It also does not clear out the dtype encoding.
One quick solution here is that you could add
```python
del dataset['time'].encoding['units']
```
to the line right after your `open_mfdataset` call. You could also update the dtype of your time variable to be a float64.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1474785646
https://github.com/pydata/xarray/issues/7354#issuecomment-1345876149,https://api.github.com/repos/pydata/xarray/issues/7354,1345876149,IC_kwDOAMm_X85QOHC1,2443309,2022-12-12T04:57:05Z,2022-12-12T04:57:05Z,MEMBER,@peterdudfield - have you tried this workflow with the latest version of xarray (`2022.12.0`)?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1474785646