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Name: python310-swifter | Distribution: openSUSE:Factory:zSystems |
Version: 1.4.0 | Vendor: openSUSE |
Release: 1.1 | Build date: Thu Aug 3 14:54:26 2023 |
Group: Unspecified | Build host: s390zp22 |
Size: 169967 | Source RPM: python-swifter-1.4.0-1.1.src.rpm |
Packager: https://bugs.opensuse.org | |
Url: https://github.com/jmcarpenter2/swifter | |
Summary: Tool to speed up pandas calculations |
A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner
MIT
* Tue Aug 01 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 02 2023 Steve Kowalik <steven.kowalik@suse.com> - Stop skipping Python 3.11. * Sat Mar 25 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 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 07 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 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 09 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 07 2020 Tomáš Chvátal <tchvatal@suse.com> - Update to 0.304: * Various fixes for updated dependencies * Mon Feb 10 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 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
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