From 2492a9fe98ef1985e10e8ef3429a1b24c6da138f Mon Sep 17 00:00:00 2001 From: CoprDistGit Date: Tue, 11 Apr 2023 09:07:02 +0000 Subject: automatic import of python-pm4py --- .gitignore | 1 + python-pm4py.spec | 207 ++++++++++++++++++++++++++++++++++++++++++++++++++++++ sources | 1 + 3 files changed, 209 insertions(+) create mode 100644 python-pm4py.spec create mode 100644 sources diff --git a/.gitignore b/.gitignore index e69de29..063179f 100644 --- a/.gitignore +++ b/.gitignore @@ -0,0 +1 @@ +/pm4py-2.7.2.tar.gz diff --git a/python-pm4py.spec b/python-pm4py.spec new file mode 100644 index 0000000..4a65a01 --- /dev/null +++ b/python-pm4py.spec @@ -0,0 +1,207 @@ +%global _empty_manifest_terminate_build 0 +Name: python-pm4py +Version: 2.7.2 +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/74/e0/60c9162bd5d1425b8c3219bb3542fa368673dde228249f8a452de45b3695/pm4py-2.7.2.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('') + 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('') + 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('') + 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-2.7.2 + +%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 +* Tue Apr 11 2023 Python_Bot - 2.7.2-1 +- Package Spec generated diff --git a/sources b/sources new file mode 100644 index 0000000..6226e67 --- /dev/null +++ b/sources @@ -0,0 +1 @@ +f4ca8eb6b8d0031df5e0480904119646 pm4py-2.7.2.tar.gz -- cgit v1.2.3