Justus Magin

which ones fail if you add the 3D variable?

with this: ```python ds2 = ds.time.dt.strftime("%Y%m%d%H%M%S").str.encode("utf-8").to_dataset().assign(d1=ds.d1) ``` but we don't really need to check if the first dataset already fails. Now I'd probably check if it's just the size that...

okay, then does changing the dtype do anything? I.e. does this only happen with `datetime64` / bytes, or do int / float / str also fail?

great, good to know. Can you try this with `h5py`: ```python import h5py N_TIMES = 48 with h5py.File("test.nc", mode="w") as f: time = f.create_dataset("time", (N_TIMES,), dtype="i") time[:] = 0 d1...

Since we have eliminated `xarray` with this, you should be able to submit an issue to the [`h5py`](https://github.com/h5py/h5py) issue tracker while mentioning that this is probably a bug in `libhdf5`...

the issue is that we only have a minimum dependencies CI (i.e. `pandas` and `numpy` but not `matplotlib`) and one that tests all dependencies with minimum versions. This means that...

I wonder if it would help to have a custom type that unlike `tuple` is invalid for coordinates / data variables, but allows to reduce the redundancy? E.g. ```python indexes...

`assert_equal` and `assert_identical` are currently calling `.equals` / `.identical` and the only thing they really add on top of that is the diff formatting, which is what you want to...

can you try if your test (without the other changes) fails with `rasterio=1.2.3` and passes with `rasterio>=1.2.4` (I think that's the first version that includes the commit you referenced)?

I suspect that's because you're installing via `pip`, where both the `h5netcdf` and the `netcdf4` wheel bundle the HDF5 library (but different versions, apparently). If that's correct, you should get...