automatic import of python-pm4pyopeneuler20.03

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('<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/

+# 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
@@ -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('<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/

+# 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/

+# 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-2.7.2
+%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 <Python_Bot@openeuler.org> - 2.7.2-1
+* Sun Apr 23 2023 Python_Bot <Python_Bot@openeuler.org> - 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