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|
%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.
[](https://pypi.org/project/cute-ranking/)
[](https://badge.fury.io/py/cute-ranking)
[](https://pepy.tech/project/cute-ranking)
[](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.
[](https://pypi.org/project/cute-ranking/)
[](https://badge.fury.io/py/cute-ranking)
[](https://pepy.tech/project/cute-ranking)
[](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.
[](https://pypi.org/project/cute-ranking/)
[](https://badge.fury.io/py/cute-ranking)
[](https://pepy.tech/project/cute-ranking)
[](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 <Python_Bot@openeuler.org> - 0.0.3-1
- Package Spec generated
|
