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1 row where "closed_at" is on date 2022-10-28, comments = 5 and user = 2448579 sorted by updated_at descending

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id node_id number title user state locked assignee milestone comments created_at updated_at ▲ closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
1284094480 I_kwDOAMm_X85MiboQ 6722 Avoid loading any data for reprs dcherian 2448579 closed 0     5 2022-06-24T19:04:30Z 2022-10-28T16:23:20Z 2022-10-28T16:23:20Z MEMBER      

What happened?

For "small" datasets, we load in to memory when displaying the repr. For cloud backed datasets with large number of "small" variables, this can use a lot of time sequentially loading O(100) variables just for a repr.

https://github.com/pydata/xarray/blob/6c8db5ed005e000b35ad8b6ea9080105e608e976/xarray/core/formatting.py#L548-L549

What did you expect to happen?

Fast reprs!

Minimal Complete Verifiable Example

This dataset has 48 "small" variables ```Python import xarray as xr

dc1 = xr.open_dataset('s3://its-live-data/datacubes/v02/N40E080/ITS_LIVE_vel_EPSG32645_G0120_X250000_Y4750000.zarr', engine= 'zarr', storage_options = {'anon':True}) dc1.repr_html() ```

On 2022.03.0 this repr takes 36.4s If I comment the array.size condition I get 6μs.

MVCE confirmation

  • [x] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
  • [x] Complete example — the example is self-contained, including all data and the text of any traceback.
  • [x] Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
  • [x] New issue — a search of GitHub Issues suggests this is not a duplicate.

Relevant log output

No response

Anything else we need to know?

No response

Environment

INSTALLED VERSIONS ------------------ commit: None python: 3.10.4 | packaged by conda-forge | (main, Mar 24 2022, 17:43:32) [Clang 12.0.1 ] python-bits: 64 OS: Darwin OS-release: 21.5.0 machine: x86_64 processor: i386 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: ('en_US', 'UTF-8') libhdf5: None libnetcdf: None xarray: 2022.3.0 pandas: 1.4.2 numpy: 1.22.4 scipy: 1.8.1 netCDF4: None pydap: None h5netcdf: None h5py: None Nio: None zarr: 2.11.3 cftime: None nc_time_axis: None PseudoNetCDF: None rasterio: 1.2.10 cfgrib: None iris: None bottleneck: None dask: 2022.05.2 distributed: None matplotlib: 3.5.2 cartopy: 0.20.2 seaborn: 0.11.2 numbagg: None fsspec: 2022.5.0 cupy: None pint: None sparse: None setuptools: 62.3.2 pip: 22.1.2 conda: None pytest: None IPython: 8.4.0 sphinx: 4.5.0
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  completed xarray 13221727 issue

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