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/6259#issuecomment-1077728973,https://api.github.com/repos/pydata/xarray/issues/6259,1077728973,IC_kwDOAMm_X85APNbN,3487237,2022-03-24T15:03:50Z,2022-03-24T15:03:50Z,NONE,"What?! Whoa I did not know about the `preprocess` option and it looks really powerful! I have been getting the derived datasets to work but I think this would do the job in a more simple and easy-to-understand way. I will give it a try.

`intake-xarray` should now work with `open_mfdataset` — I added this as an option, though it's probably not in a release yet.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1128759050
https://github.com/pydata/xarray/issues/6259#issuecomment-1077043912,https://api.github.com/repos/pydata/xarray/issues/6259,1077043912,IC_kwDOAMm_X85AMmLI,2448579,2022-03-24T04:00:52Z,2022-03-24T04:00:52Z,MEMBER,You could do the same correction with the `preprocess` kwarg to `open_mfdataset` (which can handle a single file). But if `intake` only uses `open_dataset` we could consider adding `preprocess` to `open_dataset`,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1128759050
https://github.com/pydata/xarray/issues/6259#issuecomment-1035604231,https://api.github.com/repos/pydata/xarray/issues/6259,1035604231,IC_kwDOAMm_X849uhEH,3487237,2022-02-10T22:39:16Z,2022-02-10T22:39:16Z,NONE,"Thanks @d70-t for the idea! I haven't tried out the derived datasets capabilities in `intake`, but I'll give them a try. Sounds like they could be pretty powerful.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1128759050
https://github.com/pydata/xarray/issues/6259#issuecomment-1034098265,https://api.github.com/repos/pydata/xarray/issues/6259,1034098265,IC_kwDOAMm_X849oxZZ,6574622,2022-02-09T19:05:44Z,2022-02-09T19:05:44Z,CONTRIBUTOR,"This sounds like it could theoretically be handled using [intake derived datasets](https://intake.readthedocs.io/en/latest/transforms.html?highlight=transform#barebone-example). To be fair, derived datasets are probably still in their early stages. But the basic idea would be to apply arbitrary transformations to a dataset after it has been opened (e.g. with `decode_cf=False`) and represent the outcome of this transformation as an entry in the catalog. A suitable transformation function might be something like:
```python
def fix_calendar(ds):
    ds.time.calendar = ""proleptic_gregorian""
    return xr.decode_cf(ds)
```
... but maybe it is still more convenient or useful to handle it in xarray directly (e.g. I don't know if stac has a similar approach).","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1128759050