automatic import of python-fast-histogram

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diff --git a/.gitignore b/.gitignore
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+/fast-histogram-0.11.tar.gz
diff --git a/python-fast-histogram.spec b/python-fast-histogram.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-fast-histogram
+Version:	0.11
+Release:	1
+Summary:	Fast simple 1D and 2D histograms
+License:	BSD
+URL:		https://github.com/astrofrog/fast-histogram
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/c2/35/36883176c938d8610271093e3b950048a928c200cd4a51b77b70cabd91c9/fast-histogram-0.11.tar.gz
+
+Requires:	python3-numpy
+Requires:	python3-pytest
+Requires:	python3-pytest-cov
+Requires:	python3-hypothesis[numpy]
+
+%description
+Sometimes you just want to compute simple 1D or 2D histograms with regular bins. Fast. No
+nonsense. `Numpy's <http://www.numpy.org>`__ histogram functions are
+versatile, and can handle for example non-regular binning, but this
+versatility comes at the expense of performance.
+The **fast-histogram** mini-package aims to provide simple and fast
+histogram functions for regular bins that don't compromise on performance. It doesn't do
+anything complicated - it just implements a simple histogram algorithm
+in C and keeps it simple. The aim is to have functions that are fast but
+also robust and reliable. The result is a 1D histogram function here that
+is **7-15x faster** than ``numpy.histogram``, and a 2D histogram function
+that is **20-25x faster** than ``numpy.histogram2d``.
+To install::
+    pip install fast-histogram
+or if you use conda you can instead do::
+    conda install -c conda-forge fast-histogram
+The ``fast_histogram`` module then provides two functions:
+``histogram1d`` and ``histogram2d``:
+    from fast_histogram import histogram1d, histogram2d
+
+%package -n python3-fast-histogram
+Summary:	Fast simple 1D and 2D histograms
+Provides:	python-fast-histogram
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+BuildRequires:	python3-cffi
+BuildRequires:	gcc
+BuildRequires:	gdb
+%description -n python3-fast-histogram
+Sometimes you just want to compute simple 1D or 2D histograms with regular bins. Fast. No
+nonsense. `Numpy's <http://www.numpy.org>`__ histogram functions are
+versatile, and can handle for example non-regular binning, but this
+versatility comes at the expense of performance.
+The **fast-histogram** mini-package aims to provide simple and fast
+histogram functions for regular bins that don't compromise on performance. It doesn't do
+anything complicated - it just implements a simple histogram algorithm
+in C and keeps it simple. The aim is to have functions that are fast but
+also robust and reliable. The result is a 1D histogram function here that
+is **7-15x faster** than ``numpy.histogram``, and a 2D histogram function
+that is **20-25x faster** than ``numpy.histogram2d``.
+To install::
+    pip install fast-histogram
+or if you use conda you can instead do::
+    conda install -c conda-forge fast-histogram
+The ``fast_histogram`` module then provides two functions:
+``histogram1d`` and ``histogram2d``:
+    from fast_histogram import histogram1d, histogram2d
+
+%package help
+Summary:	Development documents and examples for fast-histogram
+Provides:	python3-fast-histogram-doc
+%description help
+Sometimes you just want to compute simple 1D or 2D histograms with regular bins. Fast. No
+nonsense. `Numpy's <http://www.numpy.org>`__ histogram functions are
+versatile, and can handle for example non-regular binning, but this
+versatility comes at the expense of performance.
+The **fast-histogram** mini-package aims to provide simple and fast
+histogram functions for regular bins that don't compromise on performance. It doesn't do
+anything complicated - it just implements a simple histogram algorithm
+in C and keeps it simple. The aim is to have functions that are fast but
+also robust and reliable. The result is a 1D histogram function here that
+is **7-15x faster** than ``numpy.histogram``, and a 2D histogram function
+that is **20-25x faster** than ``numpy.histogram2d``.
+To install::
+    pip install fast-histogram
+or if you use conda you can instead do::
+    conda install -c conda-forge fast-histogram
+The ``fast_histogram`` module then provides two functions:
+``histogram1d`` and ``histogram2d``:
+    from fast_histogram import histogram1d, histogram2d
+
+%prep
+%autosetup -n fast-histogram-0.11
+
+%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-fast-histogram -f filelist.lst
+%dir %{python3_sitearch}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Wed Apr 12 2023 Python_Bot <Python_Bot@openeuler.org> - 0.11-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..e300e41
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+92f8790c43ff5cecc99ce2885d90e155  fast-histogram-0.11.tar.gz