automatic import of python-datasketch

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diff --git a/.gitignore b/.gitignore
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+/datasketch-1.5.9.tar.gz
diff --git a/python-datasketch.spec b/python-datasketch.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-datasketch
+Version:	1.5.9
+Release:	1
+Summary:	Probabilistic data structures for processing and searching very large datasets
+License:	MIT
+URL:		https://ekzhu.github.io/datasketch
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/34/42/22ca877495066c15f05ed0fef1769545ff81efc97de0bfca49e703e06a49/datasketch-1.5.9.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-numpy
+Requires:	python3-scipy
+Requires:	python3-pyhash
+Requires:	python3-matplotlib
+Requires:	python3-scikit-learn
+Requires:	python3-scipy
+Requires:	python3-pandas
+Requires:	python3-SetSimilaritySearch
+Requires:	python3-pyfarmhash
+Requires:	python3-nltk
+Requires:	python3-cassandra-driver
+Requires:	python3-aiounittest
+Requires:	python3-motor
+Requires:	python3-redis
+Requires:	python3-cassandra-driver
+Requires:	python3-redis
+Requires:	python3-mock
+Requires:	python3-mockredispy
+Requires:	python3-coverage
+Requires:	python3-pymongo
+Requires:	python3-nose
+Requires:	python3-nose-exclude
+Requires:	python3-pytest
+
+%description
+datasketch gives you probabilistic data structures that can process and
+search very large amount of data super fast, with little loss of
+accuracy.
+This package contains the following data sketches:
++-------------------------+-----------------------------------------------+
+| Data Sketch             | Usage                                         |
++=========================+===============================================+
+| `MinHash`_              | estimate Jaccard similarity and cardinality   |
++-------------------------+-----------------------------------------------+
+| `Weighted MinHash`_     | estimate weighted Jaccard similarity          |
++-------------------------+-----------------------------------------------+
+| `HyperLogLog`_          | estimate cardinality                          |
++-------------------------+-----------------------------------------------+
+| `HyperLogLog++`_        | estimate cardinality                          |
++-------------------------+-----------------------------------------------+
+The following indexes for data sketches are provided to support
+sub-linear query time:
++---------------------------+-----------------------------+------------------------+
+| Index                     | For Data Sketch             | Supported Query Type   |
++===========================+=============================+========================+
+| `MinHash LSH`_            | MinHash, Weighted MinHash   | Jaccard Threshold      |
++---------------------------+-----------------------------+------------------------+
+| `MinHash LSH Forest`_     | MinHash, Weighted MinHash   | Jaccard Top-K          |
++---------------------------+-----------------------------+------------------------+
+| `MinHash LSH Ensemble`_   | MinHash                     | Containment Threshold  |
++---------------------------+-----------------------------+------------------------+
+datasketch must be used with Python 2.7 or above, NumPy 1.11 or above, and Scipy. 
+Note that `MinHash LSH`_ and `MinHash LSH Ensemble`_ also support Redis and Cassandra 
+storage layer (see `MinHash LSH at Scale`_).
+
+%package -n python3-datasketch
+Summary:	Probabilistic data structures for processing and searching very large datasets
+Provides:	python-datasketch
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-datasketch
+datasketch gives you probabilistic data structures that can process and
+search very large amount of data super fast, with little loss of
+accuracy.
+This package contains the following data sketches:
++-------------------------+-----------------------------------------------+
+| Data Sketch             | Usage                                         |
++=========================+===============================================+
+| `MinHash`_              | estimate Jaccard similarity and cardinality   |
++-------------------------+-----------------------------------------------+
+| `Weighted MinHash`_     | estimate weighted Jaccard similarity          |
++-------------------------+-----------------------------------------------+
+| `HyperLogLog`_          | estimate cardinality                          |
++-------------------------+-----------------------------------------------+
+| `HyperLogLog++`_        | estimate cardinality                          |
++-------------------------+-----------------------------------------------+
+The following indexes for data sketches are provided to support
+sub-linear query time:
++---------------------------+-----------------------------+------------------------+
+| Index                     | For Data Sketch             | Supported Query Type   |
++===========================+=============================+========================+
+| `MinHash LSH`_            | MinHash, Weighted MinHash   | Jaccard Threshold      |
++---------------------------+-----------------------------+------------------------+
+| `MinHash LSH Forest`_     | MinHash, Weighted MinHash   | Jaccard Top-K          |
++---------------------------+-----------------------------+------------------------+
+| `MinHash LSH Ensemble`_   | MinHash                     | Containment Threshold  |
++---------------------------+-----------------------------+------------------------+
+datasketch must be used with Python 2.7 or above, NumPy 1.11 or above, and Scipy. 
+Note that `MinHash LSH`_ and `MinHash LSH Ensemble`_ also support Redis and Cassandra 
+storage layer (see `MinHash LSH at Scale`_).
+
+%package help
+Summary:	Development documents and examples for datasketch
+Provides:	python3-datasketch-doc
+%description help
+datasketch gives you probabilistic data structures that can process and
+search very large amount of data super fast, with little loss of
+accuracy.
+This package contains the following data sketches:
++-------------------------+-----------------------------------------------+
+| Data Sketch             | Usage                                         |
++=========================+===============================================+
+| `MinHash`_              | estimate Jaccard similarity and cardinality   |
++-------------------------+-----------------------------------------------+
+| `Weighted MinHash`_     | estimate weighted Jaccard similarity          |
++-------------------------+-----------------------------------------------+
+| `HyperLogLog`_          | estimate cardinality                          |
++-------------------------+-----------------------------------------------+
+| `HyperLogLog++`_        | estimate cardinality                          |
++-------------------------+-----------------------------------------------+
+The following indexes for data sketches are provided to support
+sub-linear query time:
++---------------------------+-----------------------------+------------------------+
+| Index                     | For Data Sketch             | Supported Query Type   |
++===========================+=============================+========================+
+| `MinHash LSH`_            | MinHash, Weighted MinHash   | Jaccard Threshold      |
++---------------------------+-----------------------------+------------------------+
+| `MinHash LSH Forest`_     | MinHash, Weighted MinHash   | Jaccard Top-K          |
++---------------------------+-----------------------------+------------------------+
+| `MinHash LSH Ensemble`_   | MinHash                     | Containment Threshold  |
++---------------------------+-----------------------------+------------------------+
+datasketch must be used with Python 2.7 or above, NumPy 1.11 or above, and Scipy. 
+Note that `MinHash LSH`_ and `MinHash LSH Ensemble`_ also support Redis and Cassandra 
+storage layer (see `MinHash LSH at Scale`_).
+
+%prep
+%autosetup -n datasketch-1.5.9
+
+%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-datasketch -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Mon Apr 10 2023 Python_Bot <Python_Bot@openeuler.org> - 1.5.9-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..f5d4048
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+0bae5da2d263450d6d25d3e474977029  datasketch-1.5.9.tar.gz