diff --git python-anfft/python-anfft.spec python-anfft/python-anfft.spec.tmp
index f9b65f65e3..6ae6548bac 100644
--- python-anfft/python-anfft.spec
+++ python-anfft/python-anfft.spec.tmp
@@ -3,33 +3,41 @@
 Summary:	ANFFT is an FFT package for Python, based on FFTW
 Name:		python-%{module}
 Version:	0.2
-Release:	10%{?dist}
+Release:	11%{?dist}
 Source0:	http://anfft.googlecode.com/files/%{module}-%{version}.tar.gz
 License:	GPLv3+
 Group:		Development/Languages
 URL:		http://anfft.googlecode.com/
 
 BuildRequires:	numpy fftw-libs python2
-Requires:	numpy fftw-libs python2
 BuildArch:	noarch
 
 
-%description
-ANFFT is intended to be used in situations where large numbers
-of expensive FFTs must be performed, and for which the speed 
-of the built-in NumPy or SciPy functions has been found insufficient.
-
-By default, ANFFT provides immediate results by using FFTW's 
-"estimate" mode, which does not require tuning and is still very fast. 
-However, each high-level function provides a keyword named "measure" 
-which will invoke the full FFTW planning machinery. 
-FFTW will investigate which implementations are fastest on your 
-hardware for the given problem size, and ANFFT will transparently 
-cache this information to speed up later transforms on arrays of 
-the same size and type. Accumulated FFTW "wisdom" about which 
-methods work best is stored across Python sessions in a configuration
+%global _description\
+ANFFT is intended to be used in situations where large numbers\
+of expensive FFTs must be performed, and for which the speed\
+of the built-in NumPy or SciPy functions has been found insufficient.\
+\
+By default, ANFFT provides immediate results by using FFTW's\
+"estimate" mode, which does not require tuning and is still very fast.\
+However, each high-level function provides a keyword named "measure"\
+which will invoke the full FFTW planning machinery.\
+FFTW will investigate which implementations are fastest on your\
+hardware for the given problem size, and ANFFT will transparently\
+cache this information to speed up later transforms on arrays of\
+the same size and type. Accumulated FFTW "wisdom" about which\
+methods work best is stored across Python sessions in a configuration\
 file in ~/.anfft
 
+%description %_description
+
+%package -n python2-%{module}
+Summary: %summary
+Requires:	numpy fftw-libs python2
+%{?python_provide:%python_provide python2-%{module}}
+
+%description -n python2-%{module} %_description
+
 %prep
 %setup -q -n %{module}-%{version}
 
@@ -46,12 +54,16 @@ python test.py
 
 python setup.py install -O1 --skip-build  --root=%{buildroot}
 
-%files
+%files -n python2-%{module}
 %doc COPYING.txt README.txt
 %{python_sitelib}/anfft/
 %{python_sitelib}/anfft-%{version}-py*.egg-info
 
 %changelog
+* Sat Aug 12 2017 Zbigniew Jędrzejewski-Szmek <zbyszek@in.waw.pl> - 0.2-11
+- Python 2 binary package renamed to python2-anfft
+  See https://fedoraproject.org/wiki/FinalizingFedoraSwitchtoPython3
+
 * Thu Jul 27 2017 Fedora Release Engineering <releng@fedoraproject.org> - 0.2-10
 - Rebuilt for https://fedoraproject.org/wiki/Fedora_27_Mass_Rebuild