#!/usr/bin/env python

# Setup script for PyPI; use CMakeFile.txt to build extension modules

from setuptools import setup
from distutils.command.install_headers import install_headers
from distutils.command.build_py import build_py
from pybind11 import __version__
import os

package_data = [
 'include/pybind11/detail/class.h',
 'include/pybind11/detail/common.h',
 'include/pybind11/detail/descr.h',
 'include/pybind11/detail/init.h',
 'include/pybind11/detail/internals.h',
 'include/pybind11/detail/typeid.h',
 'include/pybind11/attr.h',
 'include/pybind11/buffer_info.h',
 'include/pybind11/cast.h',
 'include/pybind11/chrono.h',
 'include/pybind11/common.h',
 'include/pybind11/complex.h',
 'include/pybind11/eigen.h',
 'include/pybind11/embed.h',
 'include/pybind11/eval.h',
 'include/pybind11/functional.h',
 'include/pybind11/iostream.h',
 'include/pybind11/numpy.h',
 'include/pybind11/operators.h',
 'include/pybind11/options.h',
 'include/pybind11/pybind11.h',
 'include/pybind11/pytypes.h',
 'include/pybind11/stl.h',
 'include/pybind11/stl_bind.h',
]

# Prevent installation of pybind11 headers by setting
# PYBIND11_USE_CMAKE.
if os.environ.get('PYBIND11_USE_CMAKE'):
 headers = []
else:
 headers = package_data


class InstallHeaders(install_headers):
 """Use custom header installer because the default one flattens subdirectories"""
 def run(self):
 if not self.distribution.headers:
 return

 for header in self.distribution.headers:
 subdir = os.path.dirname(os.path.relpath(header, 'include/pybind11'))
 install_dir = os.path.join(self.install_dir, subdir)
 self.mkpath(install_dir)

 (out, _) = self.copy_file(header, install_dir)
 self.outfiles.append(out)


# Install the headers inside the package as well
class BuildPy(build_py):
 def build_package_data(self):
 build_py.build_package_data(self)
 for header in package_data:
 target = os.path.join(self.build_lib, 'pybind11', header)
 self.mkpath(os.path.dirname(target))
 self.copy_file(header, target, preserve_mode=False)


setup(
 name='pybind11',
 version=__version__,
 description='Seamless operability between C++11 and Python',
 author='Wenzel Jakob',
 author_email='wenzel.jakob@epfl.ch',
 url='https://github.com/pybind/pybind11',
 download_url='https://github.com/pybind/pybind11/tarball/v' + __version__,
 packages=['pybind11'],
 license='BSD',
 headers=headers,
 zip_safe=False,
 cmdclass=dict(install_headers=InstallHeaders, build_py=BuildPy),
 classifiers=[
 'Development Status :: 5 - Production/Stable',
 'Intended Audience :: Developers',
 'Topic :: Software Development :: Libraries :: Python Modules',
 'Topic :: Utilities',
 'Programming Language :: C++',
 'Programming Language :: Python :: 2.7',
 'Programming Language :: Python :: 3',
 'Programming Language :: Python :: 3.2',
 'Programming Language :: Python :: 3.3',
 'Programming Language :: Python :: 3.4',
 'Programming Language :: Python :: 3.5',
 'Programming Language :: Python :: 3.6',
 'License :: OSI Approved :: BSD License'
 ],
 keywords='C++11, Python bindings',
 long_description="""pybind11 is a lightweight header-only library that
exposes C++ types in Python and vice versa, mainly to create Python bindings of
existing C++ code. Its goals and syntax are similar to the excellent
Boost.Python by David Abrahams: to minimize boilerplate code in traditional
extension modules by inferring type information using compile-time
introspection.

The main issue with Boost.Python-and the reason for creating such a similar
project-is Boost. Boost is an enormously large and complex suite of utility
libraries that works with almost every C++ compiler in existence. This
compatibility has its cost: arcane template tricks and workarounds are
necessary to support the oldest and buggiest of compiler specimens. Now that
C++11-compatible compilers are widely available, this heavy machinery has
become an excessively large and unnecessary dependency.

Think of this library as a tiny self-contained version of Boost.Python with
everything stripped away that isn't relevant for binding generation. Without
comments, the core header files only require ~4K lines of code and depend on
Python (2.7 or 3.x, or PyPy2.7 >= 5.7) and the C++ standard library. This
compact implementation was possible thanks to some of the new C++11 language
features (specifically: tuples, lambda functions and variadic templates). Since
its creation, this library has grown beyond Boost.Python in many ways, leading
to dramatically simpler binding code in many common situations.""")