%global _empty_manifest_terminate_build 0 Name: python-onehot Version: 0.1.4 Release: 1 Summary: One-Hot encoder with sklearn-ish API interface that process mixed string and numeric labels directly. License: MIT URL: http://github.com/kmedian/onehot Source0: https://mirrors.nju.edu.cn/pypi/web/packages/d5/22/ebc5e445551aeb9a3afcf6c5d8fe21d7544f63269329e162546236f41635/onehot-0.1.4.tar.gz BuildArch: noarch %description [![Build Status](https://travis-ci.org/kmedian/onehot.svg?branch=master)](https://travis-ci.org/kmedian/onehot) [![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/kmedian/onehot/master?urlpath=lab) # onehot.OneHotDummy One-Hot encoder with sklearn-ish API interface that process mixed string and numeric labels directly. [onehot.OneHotDummy](onehot/onehotdummy_class.py) does basically the same as [LabelEncoder](http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelEncoder.html) and [OneHotEncoder](http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.OneHotEncoder.html) combined. It is also inspired by [pandas.get_dummies](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.get_dummies.html) and in particular its ease of use. ## Table of Contents * [Installation](#installation) * [Usage](#usage) * [Commands](#commands) * [Support](#support) * [Contributing](#contributing) ## Installation The `onehot` [git repo](http://github.com/kmedian/onehot) is available as [PyPi package](https://pypi.org/project/onehot) ``` pip install onehot ``` ## Usage Check the [examples](examples) folder for notebooks. ## Commands * Check syntax: `flake8 --ignore=F401` * Remove `.pyc` files: `find . -type f -name "*.pyc" | xargs rm` * Remove `__pycache__` folders: `find . -type d -name "__pycache__" | xargs rm -rf` * Upload to PyPi: `python setup.py sdist upload -r pypi` * Upload to PyPi with twine: `python setup.py sdist && twine upload -r pypi dist/*` ## Debugging * Notebooks to profile python code are in the [profile](profile) folder ## Support Please [open an issue](https://github.com/kmedian/onehot/issues/new) for support. ## Contributing Please contribute using [Github Flow](https://guides.github.com/introduction/flow/). Create a branch, add commits, and [open a pull request](https://github.com/kmedian/onehot/compare/). %package -n python3-onehot Summary: One-Hot encoder with sklearn-ish API interface that process mixed string and numeric labels directly. Provides: python-onehot BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-onehot [![Build Status](https://travis-ci.org/kmedian/onehot.svg?branch=master)](https://travis-ci.org/kmedian/onehot) [![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/kmedian/onehot/master?urlpath=lab) # onehot.OneHotDummy One-Hot encoder with sklearn-ish API interface that process mixed string and numeric labels directly. [onehot.OneHotDummy](onehot/onehotdummy_class.py) does basically the same as [LabelEncoder](http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelEncoder.html) and [OneHotEncoder](http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.OneHotEncoder.html) combined. It is also inspired by [pandas.get_dummies](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.get_dummies.html) and in particular its ease of use. ## Table of Contents * [Installation](#installation) * [Usage](#usage) * [Commands](#commands) * [Support](#support) * [Contributing](#contributing) ## Installation The `onehot` [git repo](http://github.com/kmedian/onehot) is available as [PyPi package](https://pypi.org/project/onehot) ``` pip install onehot ``` ## Usage Check the [examples](examples) folder for notebooks. ## Commands * Check syntax: `flake8 --ignore=F401` * Remove `.pyc` files: `find . -type f -name "*.pyc" | xargs rm` * Remove `__pycache__` folders: `find . -type d -name "__pycache__" | xargs rm -rf` * Upload to PyPi: `python setup.py sdist upload -r pypi` * Upload to PyPi with twine: `python setup.py sdist && twine upload -r pypi dist/*` ## Debugging * Notebooks to profile python code are in the [profile](profile) folder ## Support Please [open an issue](https://github.com/kmedian/onehot/issues/new) for support. ## Contributing Please contribute using [Github Flow](https://guides.github.com/introduction/flow/). Create a branch, add commits, and [open a pull request](https://github.com/kmedian/onehot/compare/). %package help Summary: Development documents and examples for onehot Provides: python3-onehot-doc %description help [![Build Status](https://travis-ci.org/kmedian/onehot.svg?branch=master)](https://travis-ci.org/kmedian/onehot) [![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/kmedian/onehot/master?urlpath=lab) # onehot.OneHotDummy One-Hot encoder with sklearn-ish API interface that process mixed string and numeric labels directly. [onehot.OneHotDummy](onehot/onehotdummy_class.py) does basically the same as [LabelEncoder](http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelEncoder.html) and [OneHotEncoder](http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.OneHotEncoder.html) combined. It is also inspired by [pandas.get_dummies](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.get_dummies.html) and in particular its ease of use. ## Table of Contents * [Installation](#installation) * [Usage](#usage) * [Commands](#commands) * [Support](#support) * [Contributing](#contributing) ## Installation The `onehot` [git repo](http://github.com/kmedian/onehot) is available as [PyPi package](https://pypi.org/project/onehot) ``` pip install onehot ``` ## Usage Check the [examples](examples) folder for notebooks. ## Commands * Check syntax: `flake8 --ignore=F401` * Remove `.pyc` files: `find . -type f -name "*.pyc" | xargs rm` * Remove `__pycache__` folders: `find . -type d -name "__pycache__" | xargs rm -rf` * Upload to PyPi: `python setup.py sdist upload -r pypi` * Upload to PyPi with twine: `python setup.py sdist && twine upload -r pypi dist/*` ## Debugging * Notebooks to profile python code are in the [profile](profile) folder ## Support Please [open an issue](https://github.com/kmedian/onehot/issues/new) for support. ## Contributing Please contribute using [Github Flow](https://guides.github.com/introduction/flow/). Create a branch, add commits, and [open a pull request](https://github.com/kmedian/onehot/compare/). %prep %autosetup -n onehot-0.1.4 %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-onehot -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Fri May 05 2023 Python_Bot - 0.1.4-1 - Package Spec generated