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perf: improved performance of TabularDataset.__eq__ by a factor of up to 2 #697

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merged 5 commits into from
May 6, 2024
Merged

perf: improved performance of TabularDataset.__eq__ by a factor of up to 2 #697

merged 5 commits into from
May 6, 2024

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Marsmaennchen221
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Summary of Changes

perf: improved performance of TabularDataset.__eq__ by a factor of up to 2
perf: slightly improved performance of TabularDataset.__hash__
fix: corrected TabularDataset.__sizeof__

@Marsmaennchen221
perf: improved performance of TabularDataset.__eq__ by a factor of …
78596ad 
…up to 2

perf: slightly improved performance of `TabularDataset.__hash__`
fix: corrected `TabularDataset.__sizeof__`
@Marsmaennchen221 Marsmaennchen221 requested a review from a team as a code owner May 3, 2024 00:55
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github-actions bot commented May 3, 2024 •
edited

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@Marsmaennchen221
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@lars-reimann do you really want to save the exact same data twice in a TabularDataset? Wouldn't it be better to not save the whole table and compact _features, _target and _extras if the user uses the TabularDataset.to_table method?

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codecov bot commented May 3, 2024 •
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Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 100.00%. Comparing base (102de2d) to head (1c4de0e).

Additional details and impacted files 
@@            Coverage Diff            @@
##              main      #697   +/-   ##
=========================================
  Coverage   100.00%   100.00%           
=========================================
  Files           66        66           
  Lines         4873      4873           
=========================================
  Hits          4873      4873

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lars-reimann commented May 3, 2024 •
edited

Due to pandas's copy-on-write semantics the current approach should barely need more memory. We only store some extra pointers. And this implementation maintains the column order of the original table.

We should add some performance benchmarks , though, to check runtime and memory use of the current implementation (not needed for this PR).

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Regarding column order: Should that matter for equality? If so, we should compare the tables and the names of target, features, and extras.

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Regarding column order: Should that matter for equality? If so, we should compare the tables and the names of target, features, and extras.

In the Table equals method, we do not compare the order of columns, so I don't think we should do it in a TabularDataset.

@Marsmaennchen221 Marsmaennchen221 mentioned this pull request May 6, 2024
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@lars-reimann lars-reimann merged commit cd7f55b into main May 6, 2024
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@lars-reimann lars-reimann deleted the perf-improve-tabular-dataset branch May 6, 2024 14:17
lars-reimann pushed a commit that referenced this pull request May 6, 2024
@Marsmaennchen221 @megalinter-bot @lars-reimann
perf: improved performance of TabularDataset.__eq__ by a factor of …
d6c7b48 
…up to 2 (#697)

### Summary of Changes

perf: improved performance of `TabularDataset.__eq__` by a factor of up
to 2
perf: slightly improved performance of `TabularDataset.__hash__`
fix: corrected `TabularDataset.__sizeof__`

---------

Co-authored-by: megalinter-bot <129584137+megalinter-bot@users.noreply.github.com>
lars-reimann pushed a commit that referenced this pull request May 9, 2024
@semantic-release-bot
chore(release): 0.24.0 [skip ci]
22d6cb6 
## [0.24.0](v0.23.0...v0.24.0) (2024-05-09)

### Features

* `Column.plot_histogram()` using `Table.plot_histograms` for consistent results ([#726](#726)) ([576492c](576492c))
* `Regressor.summarize_metrics` and `Classifier.summarize_metrics` ([#729](#729)) ([1cc14b1](1cc14b1)), closes [#713](#713)
* `Table.keep_only_rows` ([#721](#721)) ([923a6c2](923a6c2))
* `Table.remove_rows` ([#720](#720)) ([a1cdaef](a1cdaef)), closes [#698](#698)
* Add `ImageDataset` and Layer for ConvolutionalNeuralNetworks ([#645](#645)) ([5b6d219](5b6d219)), closes [#579](#579) [#580](#580) [#581](#581)
* added load_percentage parameter to ImageList.from_files to load a subset of the given files ([#739](#739)) ([0564b52](0564b52)), closes [#736](#736)
* added rnn layer and TimeSeries conversion ([#615](#615)) ([6cad203](6cad203)), closes [#614](#614) [#648](#648) [#656](#656) [#601](#601)
* Basic implementation of cell with polars ([#734](#734)) ([004630b](004630b)), closes [#712](#712)
* deprecate `Table.add_column` and `Table.add_row` ([#723](#723)) ([5dd9d02](5dd9d02)), closes [#722](#722)
* deprecated `Table.from_excel_file` and `Table.to_excel_file` ([#728](#728)) ([c89e0bf](c89e0bf)), closes [#727](#727)
* Larger histogram plot if table only has one column ([#716](#716)) ([31ffd12](31ffd12))
* polars implementation of a column ([#738](#738)) ([732aa48](732aa48)), closes [#712](#712)
* polars implementation of a row ([#733](#733)) ([ff627f6](ff627f6)), closes [#712](#712)
* polars implementation of table ([#744](#744)) ([fc49895](fc49895)), closes [#638](#638) [#641](#641) [#649](#649) [#712](#712)
* regularization for decision trees and random forests ([#730](#730)) ([102de2d](102de2d)), closes [#700](#700)
* Remove device information in image class ([#735](#735)) ([d783caa](d783caa)), closes [#524](#524)
* return fitted transformer and transformed table from `fit_and_transform` ([#724](#724)) ([2960d35](2960d35)), closes [#613](#613)

### Bug Fixes

* make `Image.clone` internal ([#725](#725)) ([215a472](215a472)), closes [#626](#626)

### Performance Improvements

* improved performance of `TabularDataset.__eq__` by a factor of up to 2 ([#697](#697)) ([cd7f55b](cd7f55b))
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🎉 This PR is included in version 0.24.0 🎉

The release is available on:

Your semantic-release bot 📦🚀

@lars-reimann lars-reimann added the released Included in a release label May 9, 2024
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