%global _empty_manifest_terminate_build 0 Name: python-cute-ranking Version: 0.0.3 Release: 1 Summary: A cute little python module for calculating different ranking metrics. Based entirely on the gist from https://gist.github.com/bwhite/3726239. License: Apache Software License 2.0 URL: https://github.com/ncoop57/cute_ranking/tree/main/ Source0: https://mirrors.aliyun.com/pypi/web/packages/af/7e/ef728679c6f11668b99c8f4d5e3bbda5f1abd05c983850ca04cf666ff9c3/cute_ranking-0.0.3.tar.gz BuildArch: noarch Requires: python3-numpy %description # Cute Ranking > A cute little python module for calculating different ranking metrics. Based entirely on the gist from https://gist.github.com/bwhite/3726239. [![PyPI - Python Version](https://img.shields.io/pypi/pyversions/cute-ranking)](https://pypi.org/project/cute-ranking/) [![PyPI Status](https://badge.fury.io/py/cute-ranking.svg)](https://badge.fury.io/py/cute-ranking) [![PyPI Status](https://pepy.tech/badge/cute-ranking)](https://pepy.tech/project/cute-ranking) [![license](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://github.com/ncoop57/cute-ranking/blob/main/LICENSE) ## Install Requires a minimum python installation of 3.6 `pip install cute_ranking` ## How to use ```python from cute_ranking.core import mean_reciprocal_rank relevancies = [[0, 0, 1], [0, 1, 0], [1, 0, 0]] mean_reciprocal_rank(relevancies) ``` 0.611111111111111 The library current supports the following information retrieval ranking metrics: 1. Mean Reciprocal Rank - `mean_reciprocal_rank` 2. Relevancy Precision - `r_precision` 3. Precision at K - `precision_at_k` 4. Recall at K - `recall_at_k` 5. F1 score at K - `f1_score_at_k` 6. Average Precision - `average_precision` 7. Mean Average Precision - `mean_average_precision` 8. Discounted Cumulative Gain at K - `dcg_at_k` 9. Normalized Discounted Cumulative Gain at K - `ndcg_at_k` 10. Mean Rank - `mean_rank` 11. Hit@k - `hit_rate_at_k` # Contributing PRs and issues welcome! Please make sure to read through the `CONTRIBUTING.md` doc for how to contribute :). %package -n python3-cute-ranking Summary: A cute little python module for calculating different ranking metrics. Based entirely on the gist from https://gist.github.com/bwhite/3726239. Provides: python-cute-ranking BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-cute-ranking # Cute Ranking > A cute little python module for calculating different ranking metrics. Based entirely on the gist from https://gist.github.com/bwhite/3726239. [![PyPI - Python Version](https://img.shields.io/pypi/pyversions/cute-ranking)](https://pypi.org/project/cute-ranking/) [![PyPI Status](https://badge.fury.io/py/cute-ranking.svg)](https://badge.fury.io/py/cute-ranking) [![PyPI Status](https://pepy.tech/badge/cute-ranking)](https://pepy.tech/project/cute-ranking) [![license](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://github.com/ncoop57/cute-ranking/blob/main/LICENSE) ## Install Requires a minimum python installation of 3.6 `pip install cute_ranking` ## How to use ```python from cute_ranking.core import mean_reciprocal_rank relevancies = [[0, 0, 1], [0, 1, 0], [1, 0, 0]] mean_reciprocal_rank(relevancies) ``` 0.611111111111111 The library current supports the following information retrieval ranking metrics: 1. Mean Reciprocal Rank - `mean_reciprocal_rank` 2. Relevancy Precision - `r_precision` 3. Precision at K - `precision_at_k` 4. Recall at K - `recall_at_k` 5. F1 score at K - `f1_score_at_k` 6. Average Precision - `average_precision` 7. Mean Average Precision - `mean_average_precision` 8. Discounted Cumulative Gain at K - `dcg_at_k` 9. Normalized Discounted Cumulative Gain at K - `ndcg_at_k` 10. Mean Rank - `mean_rank` 11. Hit@k - `hit_rate_at_k` # Contributing PRs and issues welcome! Please make sure to read through the `CONTRIBUTING.md` doc for how to contribute :). %package help Summary: Development documents and examples for cute-ranking Provides: python3-cute-ranking-doc %description help # Cute Ranking > A cute little python module for calculating different ranking metrics. Based entirely on the gist from https://gist.github.com/bwhite/3726239. [![PyPI - Python Version](https://img.shields.io/pypi/pyversions/cute-ranking)](https://pypi.org/project/cute-ranking/) [![PyPI Status](https://badge.fury.io/py/cute-ranking.svg)](https://badge.fury.io/py/cute-ranking) [![PyPI Status](https://pepy.tech/badge/cute-ranking)](https://pepy.tech/project/cute-ranking) [![license](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://github.com/ncoop57/cute-ranking/blob/main/LICENSE) ## Install Requires a minimum python installation of 3.6 `pip install cute_ranking` ## How to use ```python from cute_ranking.core import mean_reciprocal_rank relevancies = [[0, 0, 1], [0, 1, 0], [1, 0, 0]] mean_reciprocal_rank(relevancies) ``` 0.611111111111111 The library current supports the following information retrieval ranking metrics: 1. Mean Reciprocal Rank - `mean_reciprocal_rank` 2. Relevancy Precision - `r_precision` 3. Precision at K - `precision_at_k` 4. Recall at K - `recall_at_k` 5. F1 score at K - `f1_score_at_k` 6. Average Precision - `average_precision` 7. Mean Average Precision - `mean_average_precision` 8. Discounted Cumulative Gain at K - `dcg_at_k` 9. Normalized Discounted Cumulative Gain at K - `ndcg_at_k` 10. Mean Rank - `mean_rank` 11. Hit@k - `hit_rate_at_k` # Contributing PRs and issues welcome! Please make sure to read through the `CONTRIBUTING.md` doc for how to contribute :). %prep %autosetup -n cute_ranking-0.0.3 %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-cute-ranking -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Tue Jun 20 2023 Python_Bot - 0.0.3-1 - Package Spec generated