From ef82a04fd24b1c82b2fca121ca8ad0cd53d2a692 Mon Sep 17 00:00:00 2001 From: CoprDistGit Date: Sun, 23 Apr 2023 11:04:53 +0000 Subject: automatic import of python-pm4py --- .gitignore | 1 + python-pm4py.spec | 248 +++++++++++++++++++++++++++--------------------------- sources | 2 +- 3 files changed, 126 insertions(+), 125 deletions(-) diff --git a/.gitignore b/.gitignore index 063179f..bd94763 100644 --- a/.gitignore +++ b/.gitignore @@ -1 +1,2 @@ /pm4py-2.7.2.tar.gz +/pm4py-2.7.3.tar.gz diff --git a/python-pm4py.spec b/python-pm4py.spec index 4a65a01..5000f72 100644 --- a/python-pm4py.spec +++ b/python-pm4py.spec @@ -1,11 +1,11 @@ %global _empty_manifest_terminate_build 0 Name: python-pm4py -Version: 2.7.2 +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/74/e0/60c9162bd5d1425b8c3219bb3542fa368673dde228249f8a452de45b3695/pm4py-2.7.2.tar.gz +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/85/73/ca654c443acda5d5bb059a77b94048d6fee95b485ac2a8f49d77a67c48a9/pm4py-2.7.3.tar.gz BuildArch: noarch Requires: python3-deprecation @@ -25,46 +25,46 @@ 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/ +# 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 @@ -74,96 +74,96 @@ 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/ +# 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/ +# 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 +%autosetup -n pm4py-2.7.3 %build %py3_build @@ -203,5 +203,5 @@ mv %{buildroot}/doclist.lst . %{_docdir}/* %changelog -* Tue Apr 11 2023 Python_Bot - 2.7.2-1 +* Sun Apr 23 2023 Python_Bot - 2.7.3-1 - Package Spec generated diff --git a/sources b/sources index 6226e67..03e9c2d 100644 --- a/sources +++ b/sources @@ -1 +1 @@ -f4ca8eb6b8d0031df5e0480904119646 pm4py-2.7.2.tar.gz +6cc409a1ce2caed91a250fe4d5f3c747 pm4py-2.7.3.tar.gz -- cgit v1.2.3