%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