path: root/python-cdlib.spec

%global _empty_manifest_terminate_build 0
Name:		python-cdlib
Version:	0.2.6
Release:	1
Summary:	Community Discovery Library
License:	BSD-Clause-2
URL:		https://github.com/GiulioRossetti/cdlib
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/eb/6d/97167dce848b65023a272e2ffd04b2e462612efdb3538d16e2b8b2221a15/cdlib-0.2.6.tar.gz
BuildArch:	noarch

Requires:	python3-numpy
Requires:	python3-future
Requires:	python3-matplotlib
Requires:	python3-scikit-learn
Requires:	python3-tqdm
Requires:	python3-networkx
Requires:	python3-demon
Requires:	python3-louvain
Requires:	python3-nf1
Requires:	python3-scipy
Requires:	python3-pulp
Requires:	python3-seaborn
Requires:	python3-pandas
Requires:	python3-eva-lcd
Requires:	python3-bimlpa
Requires:	python3-markov-clustering
Requires:	python3-chinese-whispers
Requires:	python3-igraph
Requires:	python3-angel-cd
Requires:	python3-pooch
Requires:	python3-dynetx
Requires:	python3-thresholdclustering
Requires:	python3-pyclustering
Requires:	python3-cython
Requires:	python3-Levenshtein
Requires:	python3-infomap
Requires:	python3-wurlitzer
Requires:	python3-GraphRicciCurvature
Requires:	python3-networkit
Requires:	python3-pycombo
Requires:	python3-leidenalg
Requires:	python3-karateclub

%description
``CDlib`` is a meta-library for community discovery in complex networks: it implements algorithms, clustering fitness functions as well as visualization facilities.
``CDlib`` is designed around the ``networkx`` python library: however, when needed, it takes care to automatically convert (from and to) ``igraph`` object so to provide an abstraction on specific algorithm implementations to the final user.
``CDlib`` provides a standardized input/output facilities for several Community Discovery algorithms: whenever possible, to guarantee literature coherent results, implementations of CD algorithms are inherited from their original projects (acknowledged on the [documentation](https://cdlib.readthedocs.io)).
If you use ``CDlib`` as support to your research consider citing:
> G. Rossetti, L. Milli, R. Cazabet.
> **CDlib: a Python Library to Extract, Compare and Evaluate Communities from Complex Networks.**
> Applied Network Science Journal. 2019. 
> [DOI:10.1007/s41109-019-0165-9]()
## Tutorial and Online Environments
Check out the official [tutorial](https://colab.research.google.com/github/GiulioRossetti/cdlib/blob/master/docs/CDlib.ipynb) to get started!
If you would like to test ``CDlib`` functionalities without installing anything on your machine consider using the preconfigured Jupyter Hub instances offered by [SoBigData++](https://sobigdata.d4science.org/group/sobigdata-gateway/explore?siteId=20371853).
## Installation
``CDlib`` *requires* python>=3.8.
To install the latest version of our library just download (or clone) the current project, open a terminal and run the following commands:
```bash
pip install -r requirements.txt
pip install -r requirements_optional.txt # (Optional) this might not work in Windows systems due to C-based dependencies.
pip install .
```
Alternatively use pip
```bash
pip install cdlib
```
or conda
```bash
conda config --add channels giuliorossetti
conda config --add channels conda-forge
conda install cdlib
```
### Optional Dependencies (pip package)
``CDlib`` relies on a few packages calling C code that can be cumbersome to install on Windows machines: to address such issue, the default installation does not try to install set up such requirements.
Such a choice has been made to allow (even) non *unix user to install the library and get access to its core functionalities. 
To integrate the standard installation with you can either:
- (Windows) manually install the optional packages (versions details are specified in ``requirements_optional.txt``) following the original projects guidelines, or
- (Linux/OSX) run the command:
```bash
pip install cdlib[C]
```
Such caveat will install everything that can be easily automated under Linux/OSX. 
#### (Advanced) 
##### Graph-tool
The only optional dependency that will remain unsatisfied following the previous procedures will be ``graph-tool`` (used to add SBM models). 
If you need it up and running, refer to the official [documentation](https://git.skewed.de/count0/graph-tool/wikis/installation-instructions) and install the conda-forge version of the package.
##### ASLPAw
Since its 2.1.0 release ``ASLPAw`` relies on ``gmpy2`` whose installation through pip is not easy to automatize due to some C dependencies.
To address such issue test the following recipe:
```bash
conda install gmpy2 
pip install shuffle_graph>=2.1.0 similarity-index-of-label-graph>=2.0.1 ASLPAw>=2.1.0
```
In case this does not solve the issue, please refer to the official ``gmpy2`` [installation](https://gmpy2.readthedocs.io/en/latest/intro.html#installation) instructions.
### Optional Dependencies (Conda package)
``CDlib`` relies on a few packages not available through conda: to install it please use pip:
```bash
pip install pycombo
pip install GraphRicciCurvature
conda install gmpy2 
pip install shuffle_graph>=2.1.0 similarity-index-of-label-graph>=2.0.1 ASLPAw>=2.1.0
```
In case ASLPAw installation fails, please refer to the official ``gmpy2`` [installation](https://gmpy2.readthedocs.io/en/latest/intro.html#installation) instructions.
## Collaborate with us!
``CDlib`` is an active project, any contribution is welcome!
If you like to include your model in CDlib feel free to fork the project, open an issue and contact us.
### How to contribute to this project?
Contributing is good, doing it correctly is better! Check out our [rules](https://github.com/GiulioRossetti/cdlib/blob/master/.github/CONTRIBUTING.md), issue a proper [pull request](https://github.com/GiulioRossetti/cdlib/blob/master/.github/PULL_REQUEST_TEMPLATE.md) /[bug report](https://github.com/GiulioRossetti/cdlib/blob/master/.github/ISSUE_TEMPLATE/bug_report.md) / [feature request](https://github.com/GiulioRossetti/cdlib/blob/master/.github/ISSUE_TEMPLATE/feature_request.md).
We are a welcoming community... just follow the [Code of Conduct](https://github.com/GiulioRossetti/cdlib/blob/master/.github/CODE_OF_CONDUCT.md).

%package -n python3-cdlib
Summary:	Community Discovery Library
Provides:	python-cdlib
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-cdlib
``CDlib`` is a meta-library for community discovery in complex networks: it implements algorithms, clustering fitness functions as well as visualization facilities.
``CDlib`` is designed around the ``networkx`` python library: however, when needed, it takes care to automatically convert (from and to) ``igraph`` object so to provide an abstraction on specific algorithm implementations to the final user.
``CDlib`` provides a standardized input/output facilities for several Community Discovery algorithms: whenever possible, to guarantee literature coherent results, implementations of CD algorithms are inherited from their original projects (acknowledged on the [documentation](https://cdlib.readthedocs.io)).
If you use ``CDlib`` as support to your research consider citing:
> G. Rossetti, L. Milli, R. Cazabet.
> **CDlib: a Python Library to Extract, Compare and Evaluate Communities from Complex Networks.**
> Applied Network Science Journal. 2019. 
> [DOI:10.1007/s41109-019-0165-9]()
## Tutorial and Online Environments
Check out the official [tutorial](https://colab.research.google.com/github/GiulioRossetti/cdlib/blob/master/docs/CDlib.ipynb) to get started!
If you would like to test ``CDlib`` functionalities without installing anything on your machine consider using the preconfigured Jupyter Hub instances offered by [SoBigData++](https://sobigdata.d4science.org/group/sobigdata-gateway/explore?siteId=20371853).
## Installation
``CDlib`` *requires* python>=3.8.
To install the latest version of our library just download (or clone) the current project, open a terminal and run the following commands:
```bash
pip install -r requirements.txt
pip install -r requirements_optional.txt # (Optional) this might not work in Windows systems due to C-based dependencies.
pip install .
```
Alternatively use pip
```bash
pip install cdlib
```
or conda
```bash
conda config --add channels giuliorossetti
conda config --add channels conda-forge
conda install cdlib
```
### Optional Dependencies (pip package)
``CDlib`` relies on a few packages calling C code that can be cumbersome to install on Windows machines: to address such issue, the default installation does not try to install set up such requirements.
Such a choice has been made to allow (even) non *unix user to install the library and get access to its core functionalities. 
To integrate the standard installation with you can either:
- (Windows) manually install the optional packages (versions details are specified in ``requirements_optional.txt``) following the original projects guidelines, or
- (Linux/OSX) run the command:
```bash
pip install cdlib[C]
```
Such caveat will install everything that can be easily automated under Linux/OSX. 
#### (Advanced) 
##### Graph-tool
The only optional dependency that will remain unsatisfied following the previous procedures will be ``graph-tool`` (used to add SBM models). 
If you need it up and running, refer to the official [documentation](https://git.skewed.de/count0/graph-tool/wikis/installation-instructions) and install the conda-forge version of the package.
##### ASLPAw
Since its 2.1.0 release ``ASLPAw`` relies on ``gmpy2`` whose installation through pip is not easy to automatize due to some C dependencies.
To address such issue test the following recipe:
```bash
conda install gmpy2 
pip install shuffle_graph>=2.1.0 similarity-index-of-label-graph>=2.0.1 ASLPAw>=2.1.0
```
In case this does not solve the issue, please refer to the official ``gmpy2`` [installation](https://gmpy2.readthedocs.io/en/latest/intro.html#installation) instructions.
### Optional Dependencies (Conda package)
``CDlib`` relies on a few packages not available through conda: to install it please use pip:
```bash
pip install pycombo
pip install GraphRicciCurvature
conda install gmpy2 
pip install shuffle_graph>=2.1.0 similarity-index-of-label-graph>=2.0.1 ASLPAw>=2.1.0
```
In case ASLPAw installation fails, please refer to the official ``gmpy2`` [installation](https://gmpy2.readthedocs.io/en/latest/intro.html#installation) instructions.
## Collaborate with us!
``CDlib`` is an active project, any contribution is welcome!
If you like to include your model in CDlib feel free to fork the project, open an issue and contact us.
### How to contribute to this project?
Contributing is good, doing it correctly is better! Check out our [rules](https://github.com/GiulioRossetti/cdlib/blob/master/.github/CONTRIBUTING.md), issue a proper [pull request](https://github.com/GiulioRossetti/cdlib/blob/master/.github/PULL_REQUEST_TEMPLATE.md) /[bug report](https://github.com/GiulioRossetti/cdlib/blob/master/.github/ISSUE_TEMPLATE/bug_report.md) / [feature request](https://github.com/GiulioRossetti/cdlib/blob/master/.github/ISSUE_TEMPLATE/feature_request.md).
We are a welcoming community... just follow the [Code of Conduct](https://github.com/GiulioRossetti/cdlib/blob/master/.github/CODE_OF_CONDUCT.md).

%package help
Summary:	Development documents and examples for cdlib
Provides:	python3-cdlib-doc
%description help
``CDlib`` is a meta-library for community discovery in complex networks: it implements algorithms, clustering fitness functions as well as visualization facilities.
``CDlib`` is designed around the ``networkx`` python library: however, when needed, it takes care to automatically convert (from and to) ``igraph`` object so to provide an abstraction on specific algorithm implementations to the final user.
``CDlib`` provides a standardized input/output facilities for several Community Discovery algorithms: whenever possible, to guarantee literature coherent results, implementations of CD algorithms are inherited from their original projects (acknowledged on the [documentation](https://cdlib.readthedocs.io)).
If you use ``CDlib`` as support to your research consider citing:
> G. Rossetti, L. Milli, R. Cazabet.
> **CDlib: a Python Library to Extract, Compare and Evaluate Communities from Complex Networks.**
> Applied Network Science Journal. 2019. 
> [DOI:10.1007/s41109-019-0165-9]()
## Tutorial and Online Environments
Check out the official [tutorial](https://colab.research.google.com/github/GiulioRossetti/cdlib/blob/master/docs/CDlib.ipynb) to get started!
If you would like to test ``CDlib`` functionalities without installing anything on your machine consider using the preconfigured Jupyter Hub instances offered by [SoBigData++](https://sobigdata.d4science.org/group/sobigdata-gateway/explore?siteId=20371853).
## Installation
``CDlib`` *requires* python>=3.8.
To install the latest version of our library just download (or clone) the current project, open a terminal and run the following commands:
```bash
pip install -r requirements.txt
pip install -r requirements_optional.txt # (Optional) this might not work in Windows systems due to C-based dependencies.
pip install .
```
Alternatively use pip
```bash
pip install cdlib
```
or conda
```bash
conda config --add channels giuliorossetti
conda config --add channels conda-forge
conda install cdlib
```
### Optional Dependencies (pip package)
``CDlib`` relies on a few packages calling C code that can be cumbersome to install on Windows machines: to address such issue, the default installation does not try to install set up such requirements.
Such a choice has been made to allow (even) non *unix user to install the library and get access to its core functionalities. 
To integrate the standard installation with you can either:
- (Windows) manually install the optional packages (versions details are specified in ``requirements_optional.txt``) following the original projects guidelines, or
- (Linux/OSX) run the command:
```bash
pip install cdlib[C]
```
Such caveat will install everything that can be easily automated under Linux/OSX. 
#### (Advanced) 
##### Graph-tool
The only optional dependency that will remain unsatisfied following the previous procedures will be ``graph-tool`` (used to add SBM models). 
If you need it up and running, refer to the official [documentation](https://git.skewed.de/count0/graph-tool/wikis/installation-instructions) and install the conda-forge version of the package.
##### ASLPAw
Since its 2.1.0 release ``ASLPAw`` relies on ``gmpy2`` whose installation through pip is not easy to automatize due to some C dependencies.
To address such issue test the following recipe:
```bash
conda install gmpy2 
pip install shuffle_graph>=2.1.0 similarity-index-of-label-graph>=2.0.1 ASLPAw>=2.1.0
```
In case this does not solve the issue, please refer to the official ``gmpy2`` [installation](https://gmpy2.readthedocs.io/en/latest/intro.html#installation) instructions.
### Optional Dependencies (Conda package)
``CDlib`` relies on a few packages not available through conda: to install it please use pip:
```bash
pip install pycombo
pip install GraphRicciCurvature
conda install gmpy2 
pip install shuffle_graph>=2.1.0 similarity-index-of-label-graph>=2.0.1 ASLPAw>=2.1.0
```
In case ASLPAw installation fails, please refer to the official ``gmpy2`` [installation](https://gmpy2.readthedocs.io/en/latest/intro.html#installation) instructions.
## Collaborate with us!
``CDlib`` is an active project, any contribution is welcome!
If you like to include your model in CDlib feel free to fork the project, open an issue and contact us.
### How to contribute to this project?
Contributing is good, doing it correctly is better! Check out our [rules](https://github.com/GiulioRossetti/cdlib/blob/master/.github/CONTRIBUTING.md), issue a proper [pull request](https://github.com/GiulioRossetti/cdlib/blob/master/.github/PULL_REQUEST_TEMPLATE.md) /[bug report](https://github.com/GiulioRossetti/cdlib/blob/master/.github/ISSUE_TEMPLATE/bug_report.md) / [feature request](https://github.com/GiulioRossetti/cdlib/blob/master/.github/ISSUE_TEMPLATE/feature_request.md).
We are a welcoming community... just follow the [Code of Conduct](https://github.com/GiulioRossetti/cdlib/blob/master/.github/CODE_OF_CONDUCT.md).

%prep
%autosetup -n cdlib-0.2.6

%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-cdlib -f filelist.lst
%dir %{python3_sitelib}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Thu Jun 08 2023 Python_Bot <Python_Bot@openeuler.org> - 0.2.6-1
- Package Spec generated