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python-blockcanvas
python-blockcanvas.spec
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File python-blockcanvas.spec of Package python-blockcanvas
# # spec file for package python-blockcanvas # # Copyright (c) 2013 SUSE LINUX Products GmbH, Nuernberg, Germany. # # All modifications and additions to the file contributed by third parties # remain the property of their copyright owners, unless otherwise agreed # upon. The license for this file, and modifications and additions to the # file, is the same license as for the pristine package itself (unless the # license for the pristine package is not an Open Source License, in which # case the license is the MIT License). An "Open Source License" is a # license that conforms to the Open Source Definition (Version 1.9) # published by the Open Source Initiative. # Please submit bugfixes or comments via http://bugs.opensuse.org/ # %define modname blockcanvas Name: python-%{modname} Version: 4.0.3 Release: 0 Summary: Visual environment for creating simulation experiments License: BSD-3-Clause and LGPL-2.1 and GPL-2.0 Group: Development/Libraries/Python # the program is licensed as BSD-3-Clause, images are licensed under various other licenses Url: https://pypi.python.org/pypi/blockcanvas/ Source: http://www.enthought.com/repo/ets/%{modname}-%{version}.tar.gz BuildRoot: %{_tmppath}/%{name}-%{version}-build BuildRequires: fdupes BuildRequires: python-Sphinx BuildRequires: python-devel BuildRequires: python-setuptools %if 0%{?suse_version} <= 1110 %{!?python_sitearch: %global python_sitearch %(python -c "from distutils.sysconfig import get_python_lib; print get_python_lib(True);")} %py_requires %endif %description The blockcanvas project provides a visual environment for creating simulation experiments, where function and data are separated. Thus, you can define your simulation algorithm by visually connecting function blocks into a data flow network, and then run it with various data sets (known as "contexts"); likewise, you can use the same context in a different functional simulation. The project provides support for plotting, function searching and inspection, and optimization. It includes a stand-alone application that demonstrates the block-canvas environment, but the same functionality can be incorporated into other applications. The blockcanvas project relies on included libraries that allow multiple data sets using Numeric arrays to be incorporated in a Traits-based model in a way that is simple, fast, efficient, and consistent. Part of the Enthought Tool Suite (ETS). %package doc Summary: Documentation for %{name} Group: Development/Libraries/Python Recommends: %{name} %if 0%{?suse_version} > 1110 BuildArch: noarch %endif %description doc Documentation and help files for %{name} %prep %setup -q -n %{modname}-%{version} %build python setup.py build %install python setup.py install --prefix=%{_prefix} --root=%{buildroot} pushd docs make html popd rm docs/build/html/.buildinfo chmod a+x %{buildroot}%{python_sitearch}/%{modname}/canvas/enable_glyph_lib.py chmod a+x %{buildroot}%{python_sitearch}/%{modname}/cobyla2c/example.py chmod a+x %{buildroot}%{python_sitearch}/%{modname}/numerical_modeling/workflow/block_experiment_networkx/compiler_/ast/extract_children_trees.py %if 0%{?suse_version} > 1110 rm %{buildroot}%{python_sitearch}/%{modname}/cobyla2c/*.c %endif %fdupes %{buildroot} %fdupes -s docs/build/ %files %defattr(-,root,root,-) %doc LICENSE.txt image_LICENSE*.txt %{python_sitearch}/%{modname}/ %{python_sitearch}/%{modname}-%{version}-py*.egg-info/ %files doc %defattr(-,root,root,-) %doc README.rst docs/build/* docs/*.txt %changelog
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