James Bourbeau

Thanks for surfacing @bnaul. I'm able to reproduce using the latest `pyarrow=8.0.0` and `pandas=1.4.2` releases (with the current `dask` `main` branch). > I can't quite make out whether the mistaken...

Have a possible workaround I'll push up in a bit...

So it turns out while ```python df = pd.DataFrame({"a": [1, 2]}, index=pd.Index(["A", "B"], dtype="string")) pa.Schema.from_pandas(df) ``` doesn't work, creating a `pyarrow.Table` and then extracting the schema with ```python df =...

> https://github.com/orgs/dask/teams/maintenance would be great if a few folks took a look at this and let us know what they thought 🙂 Apologies for the lack of response. I'll give...

Thanks for raising this @MrPowers. I agree using `.csv` seems more intuitive than `.part`. I'm not totally sure why `.part` was chosen originally (maybe @martindurant might know?). Also cc @rjzamora...

Just updating this issue. There was an attempt at resolving this issue over in https://github.com/dask/dask/pull/9073. That PR was closed due to lack of developer bandwidth, but was a good start...

We're seeing some gpuCI test failures (e.g. [this build](https://gpuci.gpuopenanalytics.com/job/dask/job/distributed/job/prb/job/distributed-prb/17/CUDA_VER=11.2,LINUX_VER=ubuntu18.04,PYTHON_VER=3.8,RAPIDS_VER=21.08/console) for https://github.com/dask/distributed/pull/5151)

The gpu CI build is already helping : )

Thanks for raising an issue @phobson. `dd.from_delayed` has a `verify_meta=` keyword that is True by default. Does setting `verify_meta=False` help here? As a side note, @rjzamora recently added a new...

Looks like adding the `cleanup` fixture to the `loop` fixture https://github.com/dask/distributed/blob/5feb17151cdf660a3443abf8596444a9f51dc575/distributed/utils_test.py#L138-L139 is what triggered this. Though not immediately sure why that's a problem