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%global _empty_manifest_terminate_build 0
Name: python-pm4py
Version: 2.7.3
Release: 1
Summary: Process mining for Python
License: GPL 3.0
URL: http://www.pm4py.org
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/85/73/ca654c443acda5d5bb059a77b94048d6fee95b485ac2a8f49d77a67c48a9/pm4py-2.7.3.tar.gz
BuildArch: noarch
Requires: python3-deprecation
Requires: python3-graphviz
Requires: python3-intervaltree
Requires: python3-lxml
Requires: python3-matplotlib
Requires: python3-networkx
Requires: python3-numpy
Requires: python3-pandas
Requires: python3-pydotplus
Requires: python3-pytz
Requires: python3-scipy
Requires: python3-stringdist
Requires: python3-tqdm
Requires: python3-cvxopt
Requires: python3-cvxopt
%description
# pm4py
pm4py is a python library that supports (state-of-the-art) process mining algorithms in python.
It is open source (licensed under GPL) and intended to be used in both academia and industry projects.
pm4py is a product of the Fraunhofer Institute for Applied Information Technology.
## Documentation / API
The full documentation of pm4py can be found at http://pm4py.org/
## First Example
A very simple example, to whet your appetite:
import pm4py
if __name__ == "__main__":
log = pm4py.read_xes('<path-to-xes-log-file.xes>')
net, initial_marking, final_marking = pm4py.discover_petri_net_inductive(log)
pm4py.view_petri_net(net, initial_marking, final_marking, format="svg")
## Installation
pm4py can be installed on Python 3.8.x / 3.9.x / 3.10.x / 3.11.x by invoking:
*pip install -U pm4py*
## Requirements
pm4py depends on some other Python packages, with different levels of importance:
* *Essential requirements*: numpy, pandas, deprecation, networkx
* *Normal requirements* (installed by default with the pm4py package, important for mainstream usage): graphviz, intervaltree, lxml, matplotlib, pydotplus, pytz, scipy, stringdist, tqdm
* *Optional requirements* (not installed by default): scikit-learn, pyemd, pyvis, jsonschema, polars, openai, pywin32, python-dateutil, requests, workalendar
## Release Notes
To track the incremental updates, please refer to the *CHANGELOG* file.
## Third Party Dependencies
As scientific library in the Python ecosystem, we rely on external libraries to offer our features.
In the */third_party* folder, we list all the licenses of our direct dependencies.
Please check the */third_party/LICENSES_TRANSITIVE* file to get a full list of all transitive dependencies and the corresponding license.
## Citing pm4py
If you are using pm4py in your scientific work, please cite pm4py as follows:
Berti, A., van Zelst, S.J., van der Aalst, W.M.P. (2019): Process Mining for Python (PM4Py): Bridging the Gap Between Process-and Data Science. In: Proceedings of the ICPM Demo Track 2019, co-located with 1st International Conference on Process Mining (ICPM 2019), Aachen, Germany, June 24-26, 2019. pp. 13-16 (2019). http://ceur-ws.org/Vol-2374/
%package -n python3-pm4py
Summary: Process mining for Python
Provides: python-pm4py
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-pm4py
# pm4py
pm4py is a python library that supports (state-of-the-art) process mining algorithms in python.
It is open source (licensed under GPL) and intended to be used in both academia and industry projects.
pm4py is a product of the Fraunhofer Institute for Applied Information Technology.
## Documentation / API
The full documentation of pm4py can be found at http://pm4py.org/
## First Example
A very simple example, to whet your appetite:
import pm4py
if __name__ == "__main__":
log = pm4py.read_xes('<path-to-xes-log-file.xes>')
net, initial_marking, final_marking = pm4py.discover_petri_net_inductive(log)
pm4py.view_petri_net(net, initial_marking, final_marking, format="svg")
## Installation
pm4py can be installed on Python 3.8.x / 3.9.x / 3.10.x / 3.11.x by invoking:
*pip install -U pm4py*
## Requirements
pm4py depends on some other Python packages, with different levels of importance:
* *Essential requirements*: numpy, pandas, deprecation, networkx
* *Normal requirements* (installed by default with the pm4py package, important for mainstream usage): graphviz, intervaltree, lxml, matplotlib, pydotplus, pytz, scipy, stringdist, tqdm
* *Optional requirements* (not installed by default): scikit-learn, pyemd, pyvis, jsonschema, polars, openai, pywin32, python-dateutil, requests, workalendar
## Release Notes
To track the incremental updates, please refer to the *CHANGELOG* file.
## Third Party Dependencies
As scientific library in the Python ecosystem, we rely on external libraries to offer our features.
In the */third_party* folder, we list all the licenses of our direct dependencies.
Please check the */third_party/LICENSES_TRANSITIVE* file to get a full list of all transitive dependencies and the corresponding license.
## Citing pm4py
If you are using pm4py in your scientific work, please cite pm4py as follows:
Berti, A., van Zelst, S.J., van der Aalst, W.M.P. (2019): Process Mining for Python (PM4Py): Bridging the Gap Between Process-and Data Science. In: Proceedings of the ICPM Demo Track 2019, co-located with 1st International Conference on Process Mining (ICPM 2019), Aachen, Germany, June 24-26, 2019. pp. 13-16 (2019). http://ceur-ws.org/Vol-2374/
%package help
Summary: Development documents and examples for pm4py
Provides: python3-pm4py-doc
%description help
# pm4py
pm4py is a python library that supports (state-of-the-art) process mining algorithms in python.
It is open source (licensed under GPL) and intended to be used in both academia and industry projects.
pm4py is a product of the Fraunhofer Institute for Applied Information Technology.
## Documentation / API
The full documentation of pm4py can be found at http://pm4py.org/
## First Example
A very simple example, to whet your appetite:
import pm4py
if __name__ == "__main__":
log = pm4py.read_xes('<path-to-xes-log-file.xes>')
net, initial_marking, final_marking = pm4py.discover_petri_net_inductive(log)
pm4py.view_petri_net(net, initial_marking, final_marking, format="svg")
## Installation
pm4py can be installed on Python 3.8.x / 3.9.x / 3.10.x / 3.11.x by invoking:
*pip install -U pm4py*
## Requirements
pm4py depends on some other Python packages, with different levels of importance:
* *Essential requirements*: numpy, pandas, deprecation, networkx
* *Normal requirements* (installed by default with the pm4py package, important for mainstream usage): graphviz, intervaltree, lxml, matplotlib, pydotplus, pytz, scipy, stringdist, tqdm
* *Optional requirements* (not installed by default): scikit-learn, pyemd, pyvis, jsonschema, polars, openai, pywin32, python-dateutil, requests, workalendar
## Release Notes
To track the incremental updates, please refer to the *CHANGELOG* file.
## Third Party Dependencies
As scientific library in the Python ecosystem, we rely on external libraries to offer our features.
In the */third_party* folder, we list all the licenses of our direct dependencies.
Please check the */third_party/LICENSES_TRANSITIVE* file to get a full list of all transitive dependencies and the corresponding license.
## Citing pm4py
If you are using pm4py in your scientific work, please cite pm4py as follows:
Berti, A., van Zelst, S.J., van der Aalst, W.M.P. (2019): Process Mining for Python (PM4Py): Bridging the Gap Between Process-and Data Science. In: Proceedings of the ICPM Demo Track 2019, co-located with 1st International Conference on Process Mining (ICPM 2019), Aachen, Germany, June 24-26, 2019. pp. 13-16 (2019). http://ceur-ws.org/Vol-2374/
%prep
%autosetup -n pm4py-2.7.3
%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-pm4py -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Sun Apr 23 2023 Python_Bot <Python_Bot@openeuler.org> - 2.7.3-1
- Package Spec generated
|
