Matej Cepl
50c5ac0836
- Skip testing with ipywiodgets on python39: no longer supported since ipython 8.19 OBS-URL: https://build.opensuse.org/request/show/1156710 OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-swifter?expand=0&rev=24
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7.1 KiB
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173 lines
7.1 KiB
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Sun Mar 10 12:16:27 UTC 2024 - Ben Greiner <code@bnavigator.de>
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- Skip testing with ipywiodgets on python39: no longer supported
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since ipython 8.19
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Tue Aug 1 08:59:00 UTC 2023 - Markéta Machová <mmachova@suse.com>
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- Update to 1.4.0
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* Significantly reduced core dependencies of swifter library.
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* Removed deprecated loffset parameter
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* Updated README to be more readable for darkmode users
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Fri Jun 2 03:20:27 UTC 2023 - Steve Kowalik <steven.kowalik@suse.com>
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- Stop skipping Python 3.11.
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Sat Mar 25 12:14:06 UTC 2023 - Ben Greiner <code@bnavigator.de>
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- Update to 1.3.4
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* Enable indexing after a groupby, e.g.
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df.swifter.groupby(by)[key].apply(func)
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* Improve groupby apply progress bar
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* Previously, the groupby apply progress bar only appeared after
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the data was distributed across the cores.
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* Now, the groupby apply progress bar appears before the data is
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distributed for a more realistic reflection of how long it took
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* Additional groupby apply code refactoring and optimizations,
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including removing the mutability of the data within ray
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- Version 1.3.3
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* Enable users to pass in df.index as the by parameter for the
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df.swifter.groupby(by).apply(func) command
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- Version 1.3.2
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* Enable users to df.swifter.groupby.apply, which requires a new
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package (ray) that now available as an extra_requires.
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* To use groupby apply, install swifter as pip install -U
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swifter[groupby]
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* All credit goes to user @diditforlulz273 for writing the
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performant groupby apply code, that is now part of swifter!
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- Version 1.2.0
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* Enable users to force_parallel which immediately forces swifter
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to jump to using dask apply. This enables a simple interface
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for parallel processing, but disables swifter's algorithm to
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determine the fastest apply solution possible.
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- Version 1.1.4
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* Enable users to leverage set_defaults functionality so they
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don't have to keep invoking individual settings on a per
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swifter invocation basis
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- Version 1.1.3
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* Enhance the robustness of swifter by randomizing the sample
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index to avoid sparse data impacting the validity of apply
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validation
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* Resolve issue where functions that return a non array-like
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cause swifter to fail on vectorization
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Sun Mar 27 19:09:15 UTC 2022 - Ben Greiner <code@bnavigator.de>
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- Update to 1.1.2
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* Resolve installation issue by removing import from setup.py
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- Reenable python310 build, now that dask is available
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Mon Feb 7 12:23:58 UTC 2022 - Ben Greiner <code@bnavigator.de>
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- Update to 1.1.1
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* Resolve installation issues by removing modin dependency, and
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modin apply route for axis=1 string applies
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* apply_dask_on_strings returns to original functionality, which
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allows control over whether to use dask or pandas by default
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for string applies
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* Sample applies now suppress logging in addition to stdout and
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stderr
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* Allow new kwargs offset and origin for pandas df.resample
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- Require and BuildRequire everything that is declared in the
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setuptools metadata in order to avoid possible pkg_resources
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failures
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- Skip python310 due to python310-dask not available yet
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Sun Feb 21 13:50:23 UTC 2021 - Ben Greiner <code@bnavigator.de>
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- Skip python36 build: With NumPy 1.20, python36-numpy is no
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longer available in Tumbleweed (NEP 29)
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Tue Feb 9 09:48:29 UTC 2021 - Ben Greiner <code@bnavigator.de>
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- Update to 1.0.7
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* Sample applies now suppress logging in addition to stdout and
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stderr
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* Allow new kwargs offset and origin for pandas df.resample
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- Changes in 1.0.5
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* Added warnings/errors for swifter methods which do not exist
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when using modin dataframes
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* Updated Dask Dataframe dependencies to require a more recent
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version
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* Updated examples/speed benchmark notebooks
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- Changes in 1.0.3
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* Fixed bug with string, axis=1 applies for pandas dataframes
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that prevented swifter from leveraging modin for
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parallelization when returning a series instead of a dataframe
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- Changes in 1.0.2
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* Remove pickle5 hard dependency
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- Changes in 1.0.1
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* Reduce resources consumed by swifter by only importing modin/
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ray when necessary.
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* Added swifter.register_modin() function, which gives access to
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modin.DataFrame.swifter.apply(...), but is only required if
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modin is imported after swifter. If you import modin before
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swifter, this is not necessary.
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- Changes in 1.0.0
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* Two major enhancements are included in this release, both
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involving the use of modin in swifter. Special thanks to Devin
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Petersohn for the collaboration.
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* Enable compatibility with modin dataframes. Compatibility not
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only allows modin dataframes to work with
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df.swifter.apply(...), but still attempts to vectorize the
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operation which can lead to a performance boost.
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Example:
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import modin.pandas as pd
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df = pd.DataFrame(...)
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df.swifter.apply(...)
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* Significantly speed up swifter axis=1 string applies by using
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Modin, resolving a long-standing issue for swifter.
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* Use Modin for axis=1 string applies, unless
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allow_dask_on_strings(True) is set. If that flag is set, still
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use Dask.
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NOTE: this means that allow_dask_on_strings() is no longer
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required to work with text data using swifter.
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- Changes in 0.305
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* Remove Numba hard dependency, but still handle TypingErrors
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when numba is installed
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* Only call tqdm's progress_apply on transformations (e.g.
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Resampler, Rolling) when tqdm has an implementation for that
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object.
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- Do not require modin and skip the tests involving it.
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gh#jmcarpenter2/swifter#147
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-------------------------------------------------------------------
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Thu May 7 07:13:07 UTC 2020 - Tomáš Chvátal <tchvatal@suse.com>
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- Update to 0.304:
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* Various fixes for updated dependencies
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-------------------------------------------------------------------
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Mon Feb 10 15:09:53 UTC 2020 - Todd R <toddrme2178@gmail.com>
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- Update to 0.301
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* Following pandas release v1.0.0, removing deprecated keyword args "broadcast" and "reduce"
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-------------------------------------------------------------------
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Thu Jan 30 19:22:19 UTC 2020 - Todd R <toddrme2178@gmail.com>
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- Update to 0.300
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* Added new applymap method for pandas dataframes.
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df.swifter.applymap(...)
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- Update to 0.297
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* Fixed issue causing errors when using swifter on empty
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dataframes. Now swifter will perform a pandas apply on empty
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dataframes.
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- Drop upstream-included use_current_exe.patch
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-------------------------------------------------------------------
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Tue Nov 26 15:37:36 UTC 2019 - Todd R <toddrme2178@gmail.com>
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- Initial version
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- Add use_current_exe.patch
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See https://github.com/jmcarpenter2/swifter/pull/92
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