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+%global _empty_manifest_terminate_build 0
+Name:		python-nxviz
+Version:	0.7.4
+Release:	1
+Summary:	Graph Visualization Package
+License:	MIT license
+URL:		https://github.com/ericmjl/nxviz
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/94/d7/7635769f432b35d7cb05a16847ee6f0e64416476a552c91e56afe579666f/nxviz-0.7.4.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-matplotlib
+Requires:	python3-more-itertools
+Requires:	python3-networkx
+Requires:	python3-numpy
+Requires:	python3-palettable
+Requires:	python3-pandas
+Requires:	python3-seaborn
+
+%description
+# nxviz: Composable and rational network visualizations in matplotlib
+
+`nxviz` is a package for building _rational_ network visualizations
+using matplotlib as a backend.
+Inspired heavily by the principles espoused in the grammar of graphics,
+nxviz provides ways to _compose_ a graph visualization together
+by adhering to the following recipe:
+
+1. Prioritize node placement, mapping data to position and visual properties,
+2. Draw in edges, mapping data to visual properties,
+3. Add in annotations and highlights on the graph.
+
+`nxviz` is simultaneously a data visualization research project,
+art project,
+and declarative data visualization tool.
+We hope you enjoy using it to build beautiful graph visualizations.
+
+## Installation
+
+### Official Releases
+
+`nxviz` is available on PyPI:
+
+```bash
+pip install nxviz
+```
+
+It's also available on conda-forge:
+
+```bash
+conda install -c conda-forge nxviz
+```
+
+### Pre-releases
+
+Pre-releases are done by installing directly from git:
+
+```bash
+pip install git+https://github.com/ericmjl/nxviz.git
+```
+
+## Quickstart
+
+To make a Circos plot:
+
+```python
+# We assume you have a graph G that is a NetworkX graph object.
+# In this example, all nodes possess the "group" and "value" node attributes
+# where "group" is categorical and "value" is continuous,
+# and all edges have the "edge_value" node attribute as well.
+
+import nxviz as nv
+ax = nv.circos(
+    G,
+    group_by="group",
+    sort_by="value",
+    node_color_by="group",
+    edge_alpha_by="edge_value"
+)
+
+nv.annotate.circos_group(G, group_by="group")
+```
+
+![](images/circos.png)
+
+For more examples, including other plots that can be made,
+please see the examples gallery on the docs.
+
+
+
+
+%package -n python3-nxviz
+Summary:	Graph Visualization Package
+Provides:	python-nxviz
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-nxviz
+# nxviz: Composable and rational network visualizations in matplotlib
+
+`nxviz` is a package for building _rational_ network visualizations
+using matplotlib as a backend.
+Inspired heavily by the principles espoused in the grammar of graphics,
+nxviz provides ways to _compose_ a graph visualization together
+by adhering to the following recipe:
+
+1. Prioritize node placement, mapping data to position and visual properties,
+2. Draw in edges, mapping data to visual properties,
+3. Add in annotations and highlights on the graph.
+
+`nxviz` is simultaneously a data visualization research project,
+art project,
+and declarative data visualization tool.
+We hope you enjoy using it to build beautiful graph visualizations.
+
+## Installation
+
+### Official Releases
+
+`nxviz` is available on PyPI:
+
+```bash
+pip install nxviz
+```
+
+It's also available on conda-forge:
+
+```bash
+conda install -c conda-forge nxviz
+```
+
+### Pre-releases
+
+Pre-releases are done by installing directly from git:
+
+```bash
+pip install git+https://github.com/ericmjl/nxviz.git
+```
+
+## Quickstart
+
+To make a Circos plot:
+
+```python
+# We assume you have a graph G that is a NetworkX graph object.
+# In this example, all nodes possess the "group" and "value" node attributes
+# where "group" is categorical and "value" is continuous,
+# and all edges have the "edge_value" node attribute as well.
+
+import nxviz as nv
+ax = nv.circos(
+    G,
+    group_by="group",
+    sort_by="value",
+    node_color_by="group",
+    edge_alpha_by="edge_value"
+)
+
+nv.annotate.circos_group(G, group_by="group")
+```
+
+![](images/circos.png)
+
+For more examples, including other plots that can be made,
+please see the examples gallery on the docs.
+
+
+
+
+%package help
+Summary:	Development documents and examples for nxviz
+Provides:	python3-nxviz-doc
+%description help
+# nxviz: Composable and rational network visualizations in matplotlib
+
+`nxviz` is a package for building _rational_ network visualizations
+using matplotlib as a backend.
+Inspired heavily by the principles espoused in the grammar of graphics,
+nxviz provides ways to _compose_ a graph visualization together
+by adhering to the following recipe:
+
+1. Prioritize node placement, mapping data to position and visual properties,
+2. Draw in edges, mapping data to visual properties,
+3. Add in annotations and highlights on the graph.
+
+`nxviz` is simultaneously a data visualization research project,
+art project,
+and declarative data visualization tool.
+We hope you enjoy using it to build beautiful graph visualizations.
+
+## Installation
+
+### Official Releases
+
+`nxviz` is available on PyPI:
+
+```bash
+pip install nxviz
+```
+
+It's also available on conda-forge:
+
+```bash
+conda install -c conda-forge nxviz
+```
+
+### Pre-releases
+
+Pre-releases are done by installing directly from git:
+
+```bash
+pip install git+https://github.com/ericmjl/nxviz.git
+```
+
+## Quickstart
+
+To make a Circos plot:
+
+```python
+# We assume you have a graph G that is a NetworkX graph object.
+# In this example, all nodes possess the "group" and "value" node attributes
+# where "group" is categorical and "value" is continuous,
+# and all edges have the "edge_value" node attribute as well.
+
+import nxviz as nv
+ax = nv.circos(
+    G,
+    group_by="group",
+    sort_by="value",
+    node_color_by="group",
+    edge_alpha_by="edge_value"
+)
+
+nv.annotate.circos_group(G, group_by="group")
+```
+
+![](images/circos.png)
+
+For more examples, including other plots that can be made,
+please see the examples gallery on the docs.
+
+
+
+
+%prep
+%autosetup -n nxviz-0.7.4
+
+%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-nxviz -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Thu May 18 2023 Python_Bot <Python_Bot@openeuler.org> - 0.7.4-1
+- Package Spec generated