%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