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