pybind11/setup.py

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#!/usr/bin/env python
# Setup script for PyPI; use CMakeFile.txt to build extension modules
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from setuptools import setup
from distutils.command.install_headers import install_headers
from pybind11 import __version__
import os
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# Prevent installation of pybind11 headers by setting
# PYBIND11_USE_CMAKE.
if os.environ.get('PYBIND11_USE_CMAKE'):
headers = []
else:
headers = [
'include/pybind11/detail/class.h',
'include/pybind11/detail/common.h',
'include/pybind11/detail/descr.h',
Allow binding factory functions as constructors This allows you to use: cls.def(py::init(&factory_function)); where `factory_function` returns a pointer, holder, or value of the class type (or a derived type). Various compile-time checks (static_asserts) are performed to ensure the function is valid, and various run-time type checks where necessary. Some other details of this feature: - The `py::init` name doesn't conflict with the templated no-argument `py::init<...>()`, but keeps the naming consistent: the existing templated, no-argument one wraps constructors, the no-template, function-argument one wraps factory functions. - If returning a CppClass (whether by value or pointer) when an CppAlias is required (i.e. python-side inheritance and a declared alias), a dynamic_cast to the alias is attempted (for the pointer version); if it fails, or if returned by value, an Alias(Class &&) constructor is invoked. If this constructor doesn't exist, a runtime error occurs. - for holder returns when an alias is required, we try a dynamic_cast of the wrapped pointer to the alias to see if it is already an alias instance; if it isn't, we raise an error. - `py::init(class_factory, alias_factory)` is also available that takes two factories: the first is called when an alias is not needed, the second when it is. - Reimplement factory instance clearing. The previous implementation failed under python-side multiple inheritance: *each* inherited type's factory init would clear the instance instead of only setting its own type value. The new implementation here clears just the relevant value pointer. - dealloc is updated to explicitly set the leftover value pointer to nullptr and the `holder_constructed` flag to false so that it can be used to clear preallocated value without needing to rebuild the instance internals data. - Added various tests to test out new allocation/deallocation code. - With preallocation now done lazily, init factory holders can completely avoid the extra overhead of needing an extra allocation/deallocation. - Updated documentation to make factory constructors the default advanced constructor style. - If an `__init__` is called a second time, we have two choices: we can throw away the first instance, replacing it with the second; or we can ignore the second call. The latter is slightly easier, so do that.
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'include/pybind11/detail/init.h',
'include/pybind11/detail/internals.h',
'include/pybind11/detail/typeid.h',
'include/pybind11/attr.h',
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'include/pybind11/buffer_info.h',
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'include/pybind11/cast.h',
'include/pybind11/chrono.h',
'include/pybind11/common.h',
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'include/pybind11/complex.h',
'include/pybind11/eigen.h',
'include/pybind11/embed.h',
'include/pybind11/eval.h',
'include/pybind11/functional.h',
'include/pybind11/iostream.h',
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'include/pybind11/numpy.h',
'include/pybind11/operators.h',
'include/pybind11/options.h',
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'include/pybind11/pybind11.h',
'include/pybind11/pytypes.h',
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'include/pybind11/stl.h',
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'include/pybind11/stl_bind.h',
]
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)
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/wjakob/pybind11',
download_url='https://github.com/wjakob/pybind11/tarball/v' + __version__,
packages=['pybind11'],
license='BSD',
headers=headers,
cmdclass=dict(install_headers=InstallHeaders),
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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',
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'Programming Language :: Python :: 3.6',
'License :: OSI Approved :: BSD License'
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],
keywords='C++11, Python bindings',
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long_description="""pybind11 is a lightweight header-only library that
exposes C++ types in Python and vice versa, mainly to create Python bindings of
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existing C++ code. Its goals and syntax are similar to the excellent
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Boost.Python by David Abrahams: to minimize boilerplate code in traditional
extension modules by inferring type information using compile-time
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introspection.
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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
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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
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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.""")