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  • antarcticrainforest · 2 ✖

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  • open_mfdataset fails with cftime index when using parallel and dask delayed client · 2 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1026754743 https://github.com/pydata/xarray/issues/6226#issuecomment-1026754743 https://api.github.com/repos/pydata/xarray/issues/6226 IC_kwDOAMm_X849Mwi3 antarcticrainforest 10580038 2022-02-01T11:43:21Z 2022-02-01T11:44:32Z CONTRIBUTOR

Are we expecting the CFTimeIndex object to always have "O" as dtype? If so the solution would be straight forward. Which means I can create a PR.

 
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   open_mfdataset fails with cftime index when using parallel and dask delayed client 1120276279
1026656699 https://github.com/pydata/xarray/issues/6226#issuecomment-1026656699 https://api.github.com/repos/pydata/xarray/issues/6226 IC_kwDOAMm_X849MYm7 antarcticrainforest 10580038 2022-02-01T09:52:39Z 2022-02-01T09:52:39Z CONTRIBUTOR

I just ran into the very same issue. Are you sure that this is a problem with pandas? I've had a look into the pandas changes between 1.3.X and 1.4.X. Apparently the _new_Index method, which gets involved when serialising the index object, has been changed:

elif "dtype" not in d and "data" in d: # Prevent Index.__new__ from conducting inference; # "data" key not in RangeIndex d["dtype"] = d["data"].dtype return cls.__new__(cls, **d)

the problem is, that __new__ doesn't except a dtype argument. I've tried adding a dtype argument and it works. So I guess since this class inherits from pd.Index it needs to be updated?

 
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   open_mfdataset fails with cftime index when using parallel and dask delayed client 1120276279

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