issues: 929818771
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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 |
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| 929818771 | MDU6SXNzdWU5Mjk4MTg3NzE= | 5529 | Very poor html repr performance on large multi-indexes | 5635139 | closed | 0 | 5 | 2021-06-25T04:31:27Z | 2022-03-29T07:05:32Z | 2022-03-29T07:05:32Z | MEMBER | What happened: We have catestrophic performance on the html repr of some long multi-indexed data arrays. Here's a case of it taking 12s. Minimal Complete Verifiable Example: ```python import xarray as xr ds = xr.tutorial.load_dataset("air_temperature") da = ds["air"].stack(z=[...]) da.shape (3869000,)%timeit -n 1 -r 1 da.repr_html() 12.4 s !!``` Anything else we need to know?: I thought we'd fixed some issues here: https://github.com/pydata/xarray/pull/4846/files Environment: Output of <tt>xr.show_versions()</tt>INSTALLED VERSIONS ------------------ commit: None python: 3.8.10 (default, May 9 2021, 13:21:55) [Clang 12.0.5 (clang-1205.0.22.9)] python-bits: 64 OS: Darwin OS-release: 20.4.0 machine: x86_64 processor: i386 byteorder: little LC_ALL: None LANG: None LOCALE: ('en_US', 'UTF-8') libhdf5: None libnetcdf: None xarray: 0.18.2 pandas: 1.2.4 numpy: 1.20.3 scipy: 1.6.3 netCDF4: None pydap: None h5netcdf: None h5py: None Nio: None zarr: 2.8.3 cftime: 1.4.1 nc_time_axis: None PseudoNetCDF: None rasterio: 1.2.3 cfgrib: None iris: None bottleneck: 1.3.2 dask: 2021.06.1 distributed: 2021.06.1 matplotlib: 3.4.2 cartopy: None seaborn: 0.11.1 numbagg: 0.2.1 pint: None setuptools: 56.0.0 pip: 21.1.2 conda: None pytest: 6.2.4 IPython: 7.24.0 sphinx: 4.0.1 |
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completed | 13221727 | issue |