automatic import of python-heatmapz

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diff --git a/.gitignore b/.gitignore
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+/heatmapz-0.0.4.tar.gz
diff --git a/python-heatmapz.spec b/python-heatmapz.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-heatmapz
+Version:	0.0.4
+Release:	1
+Summary:	Create heatmaps with shapes and size as a parameter
+License:	BSD License
+URL:		https://github.com/drazenz/heatmap
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/4a/07/736df758be785db1f6f809945b96a1103af8d25b24419c4bd64f68ae3c60/heatmapz-0.0.4.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-matplotlib
+Requires:	python3-pandas
+Requires:	python3-seaborn
+
+%description
+### **`heatmap(x, y, **kwargs)`**
+**Parameters**:
+**`x`** : A list, np.array or pandas.Series containing the values for the horizontal dimension
+**`y`** : A list, np.array or pandas.Series containing the values for the vertical dimension
+**Optional parameters**:
+**`color`** : A list, np.array or pandas.Series containing values based on which to apply the heatmap color. Should have the same length as `x` and `y`.
+**`palette`** : A list of colors to use as the heatmap palette. The values from `color` are mapped onto the palette so that `min(color) -> palette[0]` and `max(color) -> palette[len(palette)-1]`, and the values in between are linearly interpolated. A good way to choose or create a palette is to simply use Seaborn palettes (https://seaborn.pydata.org/tutorial/color_palettes.html).
+**`color_range`** : A tuple `(color_min, color_max)` that enables capping the values of `color` being mapped to `palette`. All `color` values less than `color_min` are capped to `color_min`, and all `color` values larger than `color_max` are capped to `color_max`. Then those values are mapped to `palette` as described under `color`.
+**`size`** : A list, np.array or pandas.Series containing values based on which to apply the size to the shapes in the plot. Should have the same length as `x` and `y`.
+**`size_range`** : A tuple `(size_min, size_max)` that enables capping the values of `size` being applied to the shapes in the plot. Essentially controls min and max size of the shapes. 
+**`size_scale`** : Used to scale the size of the shapes in the plot to make them fit the size of the fields in the matrix. Default value is 500. You will likely need to fiddle with this parameter in order to find the right value for your figure size and the size range applied.
+**`x_order`** : Should contain all distinct values of `x` ordered in the way you want them shown on the x-axis from left to right.
+**`y_order`** : Should contain all distinct values of `y` ordered in the way you want them shown on the y-axis from bottom to top.
+**`marker`** : Specify the shape to use in the plot. It can be any of the **matplotlib** marker shapes (https://matplotlib.org/api/markers_api.html). The default is 's' for square.
+**`xlabel`** : Label for the x-axis. Default is none.
+
+%package -n python3-heatmapz
+Summary:	Create heatmaps with shapes and size as a parameter
+Provides:	python-heatmapz
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-heatmapz
+### **`heatmap(x, y, **kwargs)`**
+**Parameters**:
+**`x`** : A list, np.array or pandas.Series containing the values for the horizontal dimension
+**`y`** : A list, np.array or pandas.Series containing the values for the vertical dimension
+**Optional parameters**:
+**`color`** : A list, np.array or pandas.Series containing values based on which to apply the heatmap color. Should have the same length as `x` and `y`.
+**`palette`** : A list of colors to use as the heatmap palette. The values from `color` are mapped onto the palette so that `min(color) -> palette[0]` and `max(color) -> palette[len(palette)-1]`, and the values in between are linearly interpolated. A good way to choose or create a palette is to simply use Seaborn palettes (https://seaborn.pydata.org/tutorial/color_palettes.html).
+**`color_range`** : A tuple `(color_min, color_max)` that enables capping the values of `color` being mapped to `palette`. All `color` values less than `color_min` are capped to `color_min`, and all `color` values larger than `color_max` are capped to `color_max`. Then those values are mapped to `palette` as described under `color`.
+**`size`** : A list, np.array or pandas.Series containing values based on which to apply the size to the shapes in the plot. Should have the same length as `x` and `y`.
+**`size_range`** : A tuple `(size_min, size_max)` that enables capping the values of `size` being applied to the shapes in the plot. Essentially controls min and max size of the shapes. 
+**`size_scale`** : Used to scale the size of the shapes in the plot to make them fit the size of the fields in the matrix. Default value is 500. You will likely need to fiddle with this parameter in order to find the right value for your figure size and the size range applied.
+**`x_order`** : Should contain all distinct values of `x` ordered in the way you want them shown on the x-axis from left to right.
+**`y_order`** : Should contain all distinct values of `y` ordered in the way you want them shown on the y-axis from bottom to top.
+**`marker`** : Specify the shape to use in the plot. It can be any of the **matplotlib** marker shapes (https://matplotlib.org/api/markers_api.html). The default is 's' for square.
+**`xlabel`** : Label for the x-axis. Default is none.
+
+%package help
+Summary:	Development documents and examples for heatmapz
+Provides:	python3-heatmapz-doc
+%description help
+### **`heatmap(x, y, **kwargs)`**
+**Parameters**:
+**`x`** : A list, np.array or pandas.Series containing the values for the horizontal dimension
+**`y`** : A list, np.array or pandas.Series containing the values for the vertical dimension
+**Optional parameters**:
+**`color`** : A list, np.array or pandas.Series containing values based on which to apply the heatmap color. Should have the same length as `x` and `y`.
+**`palette`** : A list of colors to use as the heatmap palette. The values from `color` are mapped onto the palette so that `min(color) -> palette[0]` and `max(color) -> palette[len(palette)-1]`, and the values in between are linearly interpolated. A good way to choose or create a palette is to simply use Seaborn palettes (https://seaborn.pydata.org/tutorial/color_palettes.html).
+**`color_range`** : A tuple `(color_min, color_max)` that enables capping the values of `color` being mapped to `palette`. All `color` values less than `color_min` are capped to `color_min`, and all `color` values larger than `color_max` are capped to `color_max`. Then those values are mapped to `palette` as described under `color`.
+**`size`** : A list, np.array or pandas.Series containing values based on which to apply the size to the shapes in the plot. Should have the same length as `x` and `y`.
+**`size_range`** : A tuple `(size_min, size_max)` that enables capping the values of `size` being applied to the shapes in the plot. Essentially controls min and max size of the shapes. 
+**`size_scale`** : Used to scale the size of the shapes in the plot to make them fit the size of the fields in the matrix. Default value is 500. You will likely need to fiddle with this parameter in order to find the right value for your figure size and the size range applied.
+**`x_order`** : Should contain all distinct values of `x` ordered in the way you want them shown on the x-axis from left to right.
+**`y_order`** : Should contain all distinct values of `y` ordered in the way you want them shown on the y-axis from bottom to top.
+**`marker`** : Specify the shape to use in the plot. It can be any of the **matplotlib** marker shapes (https://matplotlib.org/api/markers_api.html). The default is 's' for square.
+**`xlabel`** : Label for the x-axis. Default is none.
+
+%prep
+%autosetup -n heatmapz-0.0.4
+
+%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-heatmapz -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Wed May 31 2023 Python_Bot <Python_Bot@openeuler.org> - 0.0.4-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
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+19d4c77af00913040d40f19a10da6dfd  heatmapz-0.0.4.tar.gz