automatic import of python-pyldavis

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diff --git a/.gitignore b/.gitignore
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+/pyLDAvis-3.4.0.tar.gz
diff --git a/python-pyldavis.spec b/python-pyldavis.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-pyLDAvis
+Version:	3.4.0
+Release:	1
+Summary:	Interactive topic model visualization. Port of the R package.
+License:	BSD-3-Clause
+URL:		https://github.com/bmabey/pyLDAvis
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/c8/87/c25ac784d4da5f63a7d8b4b9a51c931e9392a4984bec631ebb8cf5de8da6/pyLDAvis-3.4.0.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-numpy
+Requires:	python3-scipy
+Requires:	python3-pandas
+Requires:	python3-joblib
+Requires:	python3-jinja2
+Requires:	python3-numexpr
+Requires:	python3-funcy
+Requires:	python3-scikit-learn
+Requires:	python3-gensim
+Requires:	python3-setuptools
+
+%description
+Python library for interactive topic model visualization.
+This is a port of the fabulous `R package <https://github.com/cpsievert/LDAvis>`_ by `Carson Sievert <https://cpsievert.me/>`__ and `Kenny Shirley <http://www.kennyshirley.com/>`__.
+**pyLDAvis** is designed to help users interpret the topics in a topic model that has been fit to a corpus of text data. The package extracts information from a fitted LDA topic model to inform an interactive web-based visualization.
+The visualization is intended to be used within an IPython notebook but can also be saved to a stand-alone HTML file for easy sharing.
+Note: LDA stands for `latent Dirichlet allocation <https://en.wikipedia.org/wiki/Latent_Dirichlet_allocation>`_.
+|version status| |build status| |docs|
+Installation
+~~~~~~~~~~~~~~~~~~~~~~
+-  Stable version using pip:
+    pip install pyldavis
+-  Development version on GitHub
+Clone the repository and run ``python setup.py``
+Usage
+~~~~~~~~~~~~~~~~~~~~~~
+The best way to learn how to use **pyLDAvis** is to see it in action.
+Check out this `notebook for an overview <http://nbviewer.ipython.org/github/bmabey/pyLDAvis/blob/master/notebooks/pyLDAvis_overview.ipynb>`__.
+Refer to the `documentation <https://pyLDAvis.readthedocs.org>`__ for details.
+For a concise explanation of the visualization see this
+`vignette <http://cran.r-project.org/web/packages/LDAvis/vignettes/details.pdf>`__ from the LDAvis R package.
+Video demos
+~~~~~~~~~~~
+Ben Mabey walked through the visualization in this short talk using a Hacker News corpus:
+-  `Visualizing Topic Models <https://www.youtube.com/watch?v=tGxW2BzC_DU&index=4&list=PLykRMO7ZuHwP5cWnbEmP_mUIVgzd5DZgH>`__
+-  `Notebook and visualization used in the demo <http://nbviewer.ipython.org/github/bmabey/hacker_news_topic_modelling/blob/master/HN%20Topic%20Model%20Talk.ipynb>`__
+-  `Slide deck <https://speakerdeck.com/bmabey/visualizing-topic-models>`__
+`Carson Sievert <https://cpsievert.me/>`__ created a video demoing the R package. The visualization is the same and so it applies equally to pyLDAvis:
+-  `Visualizing & Exploring the Twenty Newsgroup Data <http://stat-graphics.org/movies/ldavis.html>`__
+More documentation
+~~~~~~~~~~~~~~~~~~
+To read about the methodology behind pyLDAvis, see `the original
+paper <http://nlp.stanford.edu/events/illvi2014/papers/sievert-illvi2014.pdf>`__,
+which was presented at the `2014 ACL Workshop on Interactive Language
+Learning, Visualization, and
+Interfaces <http://nlp.stanford.edu/events/illvi2014/>`__ in Baltimore
+on June 27, 2014.
+
+%package -n python3-pyLDAvis
+Summary:	Interactive topic model visualization. Port of the R package.
+Provides:	python-pyLDAvis
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-pyLDAvis
+Python library for interactive topic model visualization.
+This is a port of the fabulous `R package <https://github.com/cpsievert/LDAvis>`_ by `Carson Sievert <https://cpsievert.me/>`__ and `Kenny Shirley <http://www.kennyshirley.com/>`__.
+**pyLDAvis** is designed to help users interpret the topics in a topic model that has been fit to a corpus of text data. The package extracts information from a fitted LDA topic model to inform an interactive web-based visualization.
+The visualization is intended to be used within an IPython notebook but can also be saved to a stand-alone HTML file for easy sharing.
+Note: LDA stands for `latent Dirichlet allocation <https://en.wikipedia.org/wiki/Latent_Dirichlet_allocation>`_.
+|version status| |build status| |docs|
+Installation
+~~~~~~~~~~~~~~~~~~~~~~
+-  Stable version using pip:
+    pip install pyldavis
+-  Development version on GitHub
+Clone the repository and run ``python setup.py``
+Usage
+~~~~~~~~~~~~~~~~~~~~~~
+The best way to learn how to use **pyLDAvis** is to see it in action.
+Check out this `notebook for an overview <http://nbviewer.ipython.org/github/bmabey/pyLDAvis/blob/master/notebooks/pyLDAvis_overview.ipynb>`__.
+Refer to the `documentation <https://pyLDAvis.readthedocs.org>`__ for details.
+For a concise explanation of the visualization see this
+`vignette <http://cran.r-project.org/web/packages/LDAvis/vignettes/details.pdf>`__ from the LDAvis R package.
+Video demos
+~~~~~~~~~~~
+Ben Mabey walked through the visualization in this short talk using a Hacker News corpus:
+-  `Visualizing Topic Models <https://www.youtube.com/watch?v=tGxW2BzC_DU&index=4&list=PLykRMO7ZuHwP5cWnbEmP_mUIVgzd5DZgH>`__
+-  `Notebook and visualization used in the demo <http://nbviewer.ipython.org/github/bmabey/hacker_news_topic_modelling/blob/master/HN%20Topic%20Model%20Talk.ipynb>`__
+-  `Slide deck <https://speakerdeck.com/bmabey/visualizing-topic-models>`__
+`Carson Sievert <https://cpsievert.me/>`__ created a video demoing the R package. The visualization is the same and so it applies equally to pyLDAvis:
+-  `Visualizing & Exploring the Twenty Newsgroup Data <http://stat-graphics.org/movies/ldavis.html>`__
+More documentation
+~~~~~~~~~~~~~~~~~~
+To read about the methodology behind pyLDAvis, see `the original
+paper <http://nlp.stanford.edu/events/illvi2014/papers/sievert-illvi2014.pdf>`__,
+which was presented at the `2014 ACL Workshop on Interactive Language
+Learning, Visualization, and
+Interfaces <http://nlp.stanford.edu/events/illvi2014/>`__ in Baltimore
+on June 27, 2014.
+
+%package help
+Summary:	Development documents and examples for pyLDAvis
+Provides:	python3-pyLDAvis-doc
+%description help
+Python library for interactive topic model visualization.
+This is a port of the fabulous `R package <https://github.com/cpsievert/LDAvis>`_ by `Carson Sievert <https://cpsievert.me/>`__ and `Kenny Shirley <http://www.kennyshirley.com/>`__.
+**pyLDAvis** is designed to help users interpret the topics in a topic model that has been fit to a corpus of text data. The package extracts information from a fitted LDA topic model to inform an interactive web-based visualization.
+The visualization is intended to be used within an IPython notebook but can also be saved to a stand-alone HTML file for easy sharing.
+Note: LDA stands for `latent Dirichlet allocation <https://en.wikipedia.org/wiki/Latent_Dirichlet_allocation>`_.
+|version status| |build status| |docs|
+Installation
+~~~~~~~~~~~~~~~~~~~~~~
+-  Stable version using pip:
+    pip install pyldavis
+-  Development version on GitHub
+Clone the repository and run ``python setup.py``
+Usage
+~~~~~~~~~~~~~~~~~~~~~~
+The best way to learn how to use **pyLDAvis** is to see it in action.
+Check out this `notebook for an overview <http://nbviewer.ipython.org/github/bmabey/pyLDAvis/blob/master/notebooks/pyLDAvis_overview.ipynb>`__.
+Refer to the `documentation <https://pyLDAvis.readthedocs.org>`__ for details.
+For a concise explanation of the visualization see this
+`vignette <http://cran.r-project.org/web/packages/LDAvis/vignettes/details.pdf>`__ from the LDAvis R package.
+Video demos
+~~~~~~~~~~~
+Ben Mabey walked through the visualization in this short talk using a Hacker News corpus:
+-  `Visualizing Topic Models <https://www.youtube.com/watch?v=tGxW2BzC_DU&index=4&list=PLykRMO7ZuHwP5cWnbEmP_mUIVgzd5DZgH>`__
+-  `Notebook and visualization used in the demo <http://nbviewer.ipython.org/github/bmabey/hacker_news_topic_modelling/blob/master/HN%20Topic%20Model%20Talk.ipynb>`__
+-  `Slide deck <https://speakerdeck.com/bmabey/visualizing-topic-models>`__
+`Carson Sievert <https://cpsievert.me/>`__ created a video demoing the R package. The visualization is the same and so it applies equally to pyLDAvis:
+-  `Visualizing & Exploring the Twenty Newsgroup Data <http://stat-graphics.org/movies/ldavis.html>`__
+More documentation
+~~~~~~~~~~~~~~~~~~
+To read about the methodology behind pyLDAvis, see `the original
+paper <http://nlp.stanford.edu/events/illvi2014/papers/sievert-illvi2014.pdf>`__,
+which was presented at the `2014 ACL Workshop on Interactive Language
+Learning, Visualization, and
+Interfaces <http://nlp.stanford.edu/events/illvi2014/>`__ in Baltimore
+on June 27, 2014.
+
+%prep
+%autosetup -n pyLDAvis-3.4.0
+
+%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-pyLDAvis -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Mon Apr 10 2023 Python_Bot <Python_Bot@openeuler.org> - 3.4.0-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..06e6111
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+a212179656aaf1858d625b3d55a1395f  pyLDAvis-3.4.0.tar.gz