%global _empty_manifest_terminate_build 0 Name: python-pandarallel Version: 1.6.4 Release: 1 Summary: An easy to use library to speed up computation (by parallelizing on multi CPUs) with pandas. License: BSD URL: https://nalepae.github.io/pandarallel Source0: https://mirrors.nju.edu.cn/pypi/web/packages/bd/87/351e04dc5eb4d6c5d8ceaecf353e99e5bcda5be406457c5775263d0e5769/pandarallel-1.6.4.tar.gz BuildArch: noarch %description # Pandaral·lel [![PyPI version fury.io](https://badge.fury.io/py/pandarallel.svg)](https://pypi.python.org/pypi/pandarallel/) [![PyPI license](https://img.shields.io/pypi/l/pandarallel.svg)](https://pypi.python.org/pypi/pandarallel/) [![PyPI download month](https://img.shields.io/pypi/dm/pandarallel.svg)](https://pypi.python.org/pypi/pandarallel/) | Without parallelization | ![Without Pandarallel](https://github.com/nalepae/pandarallel/blob/master/docs/progress_apply.gif?raw=true) | | :----------------------: | ----------------------------------------------------------------------------------------------------------------- | | **With parallelization** | ![With Pandarallel](https://github.com/nalepae/pandarallel/blob/master/docs/progress_parallel_apply.gif?raw=true) | **Pandaral.lel** provides a simple way to parallelize your pandas operations on all your CPUs by changing only one line of code. It also displays progress bars. ## Maintainers - [Manu NALEPA](https://github.com/nalepae/) - [till-m](https://github.com/till-m) ## Installation ```bash pip install pandarallel [--upgrade] [--user] ``` ## Quickstart ```python from pandarallel import pandarallel pandarallel.initialize(progress_bar=True) # df.apply(func) df.parallel_apply(func) ``` ## Usage Be sure to check out the [documentation](https://nalepae.github.io/pandarallel). ## Examples An example of each available `pandas` API is available: - For [Mac & Linux](https://github.com/nalepae/pandarallel/blob/master/docs/examples_mac_linux.ipynb) - For [Windows](https://github.com/nalepae/pandarallel/blob/master/docs/examples_windows.ipynb) %package -n python3-pandarallel Summary: An easy to use library to speed up computation (by parallelizing on multi CPUs) with pandas. Provides: python-pandarallel BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-pandarallel # Pandaral·lel [![PyPI version fury.io](https://badge.fury.io/py/pandarallel.svg)](https://pypi.python.org/pypi/pandarallel/) [![PyPI license](https://img.shields.io/pypi/l/pandarallel.svg)](https://pypi.python.org/pypi/pandarallel/) [![PyPI download month](https://img.shields.io/pypi/dm/pandarallel.svg)](https://pypi.python.org/pypi/pandarallel/) | Without parallelization | ![Without Pandarallel](https://github.com/nalepae/pandarallel/blob/master/docs/progress_apply.gif?raw=true) | | :----------------------: | ----------------------------------------------------------------------------------------------------------------- | | **With parallelization** | ![With Pandarallel](https://github.com/nalepae/pandarallel/blob/master/docs/progress_parallel_apply.gif?raw=true) | **Pandaral.lel** provides a simple way to parallelize your pandas operations on all your CPUs by changing only one line of code. It also displays progress bars. ## Maintainers - [Manu NALEPA](https://github.com/nalepae/) - [till-m](https://github.com/till-m) ## Installation ```bash pip install pandarallel [--upgrade] [--user] ``` ## Quickstart ```python from pandarallel import pandarallel pandarallel.initialize(progress_bar=True) # df.apply(func) df.parallel_apply(func) ``` ## Usage Be sure to check out the [documentation](https://nalepae.github.io/pandarallel). ## Examples An example of each available `pandas` API is available: - For [Mac & Linux](https://github.com/nalepae/pandarallel/blob/master/docs/examples_mac_linux.ipynb) - For [Windows](https://github.com/nalepae/pandarallel/blob/master/docs/examples_windows.ipynb) %package help Summary: Development documents and examples for pandarallel Provides: python3-pandarallel-doc %description help # Pandaral·lel [![PyPI version fury.io](https://badge.fury.io/py/pandarallel.svg)](https://pypi.python.org/pypi/pandarallel/) [![PyPI license](https://img.shields.io/pypi/l/pandarallel.svg)](https://pypi.python.org/pypi/pandarallel/) [![PyPI download month](https://img.shields.io/pypi/dm/pandarallel.svg)](https://pypi.python.org/pypi/pandarallel/) | Without parallelization | ![Without Pandarallel](https://github.com/nalepae/pandarallel/blob/master/docs/progress_apply.gif?raw=true) | | :----------------------: | ----------------------------------------------------------------------------------------------------------------- | | **With parallelization** | ![With Pandarallel](https://github.com/nalepae/pandarallel/blob/master/docs/progress_parallel_apply.gif?raw=true) | **Pandaral.lel** provides a simple way to parallelize your pandas operations on all your CPUs by changing only one line of code. It also displays progress bars. ## Maintainers - [Manu NALEPA](https://github.com/nalepae/) - [till-m](https://github.com/till-m) ## Installation ```bash pip install pandarallel [--upgrade] [--user] ``` ## Quickstart ```python from pandarallel import pandarallel pandarallel.initialize(progress_bar=True) # df.apply(func) df.parallel_apply(func) ``` ## Usage Be sure to check out the [documentation](https://nalepae.github.io/pandarallel). ## Examples An example of each available `pandas` API is available: - For [Mac & Linux](https://github.com/nalepae/pandarallel/blob/master/docs/examples_mac_linux.ipynb) - For [Windows](https://github.com/nalepae/pandarallel/blob/master/docs/examples_windows.ipynb) %prep %autosetup -n pandarallel-1.6.4 %build %py3_build %install %py3_install install -d -m755 %{buildroot}/%{_pkgdocdir} if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi pushd %{buildroot} if [ -d usr/lib ]; then find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/lib64 ]; then find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/bin ]; then find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/sbin ]; then find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst fi touch doclist.lst if [ -d usr/share/man ]; then find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst fi popd mv %{buildroot}/filelist.lst . mv %{buildroot}/doclist.lst . %files -n python3-pandarallel -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Mon Apr 10 2023 Python_Bot - 1.6.4-1 - Package Spec generated