automatic import of python-momentum

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+%global _empty_manifest_terminate_build 0
+Name:		python-momentum
+Version:	0.2.7
+Release:	1
+Summary:	Running estimates of moments
+License:	MIT
+URL:		https://github.com/microprediction/momentum
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/9d/7c/1f52beeb73b440ecd2cdccf1898e8dbc0e796af158a890e95ddfa585f49f/momentum-0.2.7.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-wheel
+
+%description
+# momentum ![tests](https://github.com/microprediction/momentum/workflows/tests/badge.svg) ![deploy](https://github.com/microprediction/momentum/workflows/deploy/badge.svg)
+A trivial mini-package for computing the running univariate mean, variance, kurtosis and skew
+
+- No dependencies ... not even numpy.
+- No classes ... unless you want them.
+- State is a dict, for trivial serialization. 
+- Tested against scipy, creme, statistics
+
+For multivariate covariance updating, maybe see [precise](https://github.com/microprediction/precise). 
+
+### Install 
+
+    pip install momentum
+
+### Usage: running mean, var
+
+    from momentum import var_init, var_update
+    from pprint import pprint
+    
+    m = var_init()
+    for x in [5,3,2.4,1.0,5.0]:
+        m = var_update(m,x)
+    pprint(m)
+    
+    
+
+### Usage: running mean, var, kurtosis and skew 
+
+    from momentum import kurtosis_init, kurtosis_update
+    
+    m = kurtosis_init()
+    for x in [5,3,2.4,1.0,5.0]:
+        m = kurtosis_update(m,x)
+    pprint(m)
+    
+    
+File an issue if you need more help using this. 
+    
+  
+### Usage: running recency-weighted mean, var
+
+    from momentum import rvar_init, rvar_update
+    from pprint import pprint
+    
+    m = rvar_init(rho=0.01,n=15)
+    for x in [5,3,2.4,1.0,5.0]:
+        m = rvar_update(m,x)
+    pprint(m)
+    
+This will switch from running variance to a weighted variance after 15 data points. 
+    
+
+
+
+
+%package -n python3-momentum
+Summary:	Running estimates of moments
+Provides:	python-momentum
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-momentum
+# momentum ![tests](https://github.com/microprediction/momentum/workflows/tests/badge.svg) ![deploy](https://github.com/microprediction/momentum/workflows/deploy/badge.svg)
+A trivial mini-package for computing the running univariate mean, variance, kurtosis and skew
+
+- No dependencies ... not even numpy.
+- No classes ... unless you want them.
+- State is a dict, for trivial serialization. 
+- Tested against scipy, creme, statistics
+
+For multivariate covariance updating, maybe see [precise](https://github.com/microprediction/precise). 
+
+### Install 
+
+    pip install momentum
+
+### Usage: running mean, var
+
+    from momentum import var_init, var_update
+    from pprint import pprint
+    
+    m = var_init()
+    for x in [5,3,2.4,1.0,5.0]:
+        m = var_update(m,x)
+    pprint(m)
+    
+    
+
+### Usage: running mean, var, kurtosis and skew 
+
+    from momentum import kurtosis_init, kurtosis_update
+    
+    m = kurtosis_init()
+    for x in [5,3,2.4,1.0,5.0]:
+        m = kurtosis_update(m,x)
+    pprint(m)
+    
+    
+File an issue if you need more help using this. 
+    
+  
+### Usage: running recency-weighted mean, var
+
+    from momentum import rvar_init, rvar_update
+    from pprint import pprint
+    
+    m = rvar_init(rho=0.01,n=15)
+    for x in [5,3,2.4,1.0,5.0]:
+        m = rvar_update(m,x)
+    pprint(m)
+    
+This will switch from running variance to a weighted variance after 15 data points. 
+    
+
+
+
+
+%package help
+Summary:	Development documents and examples for momentum
+Provides:	python3-momentum-doc
+%description help
+# momentum ![tests](https://github.com/microprediction/momentum/workflows/tests/badge.svg) ![deploy](https://github.com/microprediction/momentum/workflows/deploy/badge.svg)
+A trivial mini-package for computing the running univariate mean, variance, kurtosis and skew
+
+- No dependencies ... not even numpy.
+- No classes ... unless you want them.
+- State is a dict, for trivial serialization. 
+- Tested against scipy, creme, statistics
+
+For multivariate covariance updating, maybe see [precise](https://github.com/microprediction/precise). 
+
+### Install 
+
+    pip install momentum
+
+### Usage: running mean, var
+
+    from momentum import var_init, var_update
+    from pprint import pprint
+    
+    m = var_init()
+    for x in [5,3,2.4,1.0,5.0]:
+        m = var_update(m,x)
+    pprint(m)
+    
+    
+
+### Usage: running mean, var, kurtosis and skew 
+
+    from momentum import kurtosis_init, kurtosis_update
+    
+    m = kurtosis_init()
+    for x in [5,3,2.4,1.0,5.0]:
+        m = kurtosis_update(m,x)
+    pprint(m)
+    
+    
+File an issue if you need more help using this. 
+    
+  
+### Usage: running recency-weighted mean, var
+
+    from momentum import rvar_init, rvar_update
+    from pprint import pprint
+    
+    m = rvar_init(rho=0.01,n=15)
+    for x in [5,3,2.4,1.0,5.0]:
+        m = rvar_update(m,x)
+    pprint(m)
+    
+This will switch from running variance to a weighted variance after 15 data points. 
+    
+
+
+
+
+%prep
+%autosetup -n momentum-0.2.7
+
+%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-momentum -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Thu May 18 2023 Python_Bot <Python_Bot@openeuler.org> - 0.2.7-1
+- Package Spec generated