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Fix slowdown in DataFrame repr in jupyter notebook #16656

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merged 25 commits into from
Aug 28, 2024

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galipremsagar
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Description

Fixes: #15747

This PR fixes slow-down in DataFrame repr inside a jupyter notebook.

Checklist

  • I am familiar with the Contributing Guidelines.
  • New or existing tests cover these changes.
  • The documentation is up to date with these changes.

@galipremsagar galipremsagar added bug Something isn't working non-breaking Non-breaking change labels Aug 26, 2024
@galipremsagar galipremsagar self-assigned this Aug 26, 2024
@galipremsagar galipremsagar requested a review from a team as a code owner August 26, 2024 16:14
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@github-actions github-actions bot added Python Affects Python cuDF API. cudf.pandas Issues specific to cudf.pandas labels Aug 26, 2024
@galipremsagar galipremsagar requested a review from a team as a code owner August 26, 2024 16:18
@galipremsagar galipremsagar requested a review from a team as a code owner August 27, 2024 17:54
Co-authored-by: Matthew Roeschke <10647082+mroeschke@users.noreply.github.com>
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These changes LGTM. I checked that the dataframe in the original issue "hangs" for me without the _ipython_canary_method_should_not_exist_ method raising an AttributeError and doesn't hang when it does. Do you why that is?

Also, do we need to something similar for pd.Series?

@galipremsagar
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These changes LGTM. I checked that the dataframe in the original issue "hangs" for me without the _ipython_canary_method_should_not_exist_ method raising an AttributeError and doesn't hang when it does. Do you why that is?

It is because of this: #16656 (comment)

Also, do we need to something similar for pd.Series?

Nope, Series doesn't have a repr_html, and doesn't seem to have the hangs either.

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/merge

@rapids-bot rapids-bot bot merged commit 569939f into rapidsai:branch-24.10 Aug 28, 2024
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bug Something isn't working cudf.pandas Issues specific to cudf.pandas non-breaking Non-breaking change Python Affects Python cuDF API.
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[BUG] cudf.pandas dataframe.__repr__ slow in jupyterlab for large datasets
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