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Author SHA1 Message Date
nobody
6b477f5813 This commit was manufactured by cvs2svn to create branch 'split-config'.
[SVN r10742]
2001-08-04 14:31:38 +00:00
864 changed files with 26013 additions and 62512 deletions

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@@ -1,7 +0,0 @@
# -*- python -*-
from faber.tools.boost import boostbook
from faber.tools.python import python
bb = boostbook(prefix='/usr/share/boostbook')
p = python(command='$PYTHON')

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@@ -1,37 +0,0 @@
name: deploy documentation
on: [push]
jobs:
deploy:
runs-on: ubuntu-20.04
steps:
- uses: actions/checkout@v2
- name: setup
run: |
sudo apt-get update
sudo apt-get install \
libboost1.71-tools-dev \
python3 \
python3-numpy \
python3-sphinx \
xsltproc \
docbook-xsl
sudo python3 -m pip install --upgrade pip
sudo python3 -m pip install faber
- name: build
run: |
sed -e "s/\$PYTHON/python3/g" .ci/faber > ~/.faber
faber --builddir=build doc.html
if [ "${GITHUB_REF##*/}" == master ]; then
echo "destination_dir=doc/html" >> $GITHUB_ENV
else
echo "destination_dir=doc/develop/html" >> $GITHUB_ENV
fi
- name: deploy
uses: peaceiris/actions-gh-pages@v3
with:
github_token: ${{ secrets.GITHUB_TOKEN }}
publish_dir: build/doc/html
destination_dir: ${{ env.destination_dir }}
keep_files: true

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@@ -1,50 +0,0 @@
name: Test OSX
on: [push, pull_request]
jobs:
build:
runs-on: macOS-latest
strategy:
fail-fast: false
matrix:
python-version: [3.8.10]
cxx: [clang++]
std: [c++11, c++14] # TODO: c++17 is failing !
steps:
- uses: actions/checkout@v4
- name: setup python
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}
- name: setup prerequisites
run: |
brew install boost
python -m pip install --upgrade pip
python -m pip install setuptools faber
- name: build
run: |
python --version
${{ matrix.cxx }} --version
brew info boost
faber -v
sed -e "s/\$PYTHON/python/g" .ci/faber > ~/.faber
faber \
--with-boost-include=$(brew --prefix boost)/include \
--builddir=build \
cxx.name=${{ matrix.cxx }} \
cxxflags=-std=${{ matrix.std }} \
cppflags=-std=${{ matrix.std }} \
-j`sysctl -n hw.ncpu`
- name: test
run: |
faber \
--with-boost-include=$(brew --prefix boost)/include \
--builddir=build\
cxx.name=${{ matrix.cxx }} \
cxxflags=-std=${{ matrix.std }} \
cppflags=-std=${{ matrix.std }} \
-j`sysctl -n hw.ncpu` \
test.report

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@@ -1,53 +0,0 @@
name: Test Ubuntu
on: [push, pull_request]
jobs:
build:
runs-on: ubuntu-latest
strategy:
fail-fast: false
matrix:
python: [python, python3]
cxx: [g++, clang++]
std: [c++98, c++11, c++14, c++17]
include:
# Add the appropriate docker image for each compiler.
# The images from teeks99/boost-python-test already have boost::python
# pre-reqs installed, see:
# https://github.com/teeks99/boost-python-test-docker
- cxx: clang++
docker-img: teeks99/boost-python-test:clang-12_1.76.0
- cxx: g++
docker-img: teeks99/boost-python-test:gcc-10_1.76.0
container:
image: ${{ matrix.docker-img }}
steps:
- uses: actions/checkout@v4
- name: build
run: |
${{ matrix.python }} --version
${{ matrix.cxx }} --version
faber -v
sed -e "s/\$PYTHON/${{ matrix.python }}/g" .ci/faber > ~/.faber
faber \
--with-boost-include=${BOOST_PY_DEPS} \
--builddir=build \
cxx.name=${{ matrix.cxx }} \
cxxflags=-std=${{ matrix.std }} \
cppflags=-std=${{ matrix.std }} \
-j`nproc`
- name: test
run: |
faber \
--with-boost-include=${BOOST_PY_DEPS} \
--builddir=build \
cxx.name=${{ matrix.cxx }} \
cxxflags=-std=${{ matrix.std }} \
cppflags=-std=${{ matrix.std }} \
-j`nproc` \
test.report

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@@ -1,49 +0,0 @@
name: Test Windows
on: [push, pull_request]
jobs:
build:
runs-on: windows-latest
strategy:
fail-fast: false
matrix:
python-version: [3.7]
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}
- uses: microsoft/setup-msbuild@v1.1
- name: setup boost prerequisites
uses: lukka/run-vcpkg@v6
with:
vcpkgGitCommitId: '88b1071e39f13b632644d9d953738d345a4ac055'
vcpkgDirectory: '${{ runner.workspace }}/vcpkg'
vcpkgTriplet: x64-windows
vcpkgArguments: >
boost-config
boost-core
boost-function
boost-graph
boost-iterator
boost-lexical-cast
boost-mpl
boost-preprocessor
boost-smart-ptr
boost-static-assert
boost-align
- name: setup faber
run: |
python -m pip install --upgrade pip
python -m pip install setuptools faber numpy
faber --info=tools cxx
- name: build
shell: cmd
run: |
faber --builddir=build cxx.name=msvc --with-boost-include=${{ runner.workspace }}/vcpkg/installed/x64-windows/include -j4
- name: test
shell: cmd
run: |
faber --builddir=build cxx.name=msvc --with-boost-include=${{ runner.workspace }}/vcpkg/installed/x64-windows/include -j4 test.report

4
.gitignore vendored
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@@ -1,4 +0,0 @@
bin.SCons
*.pyc
*~
\#*\#

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@@ -1,176 +0,0 @@
# Copyright 2020, 2021 Peter Dimov
# Distributed under the Boost Software License, Version 1.0.
# https://www.boost.org/LICENSE_1_0.txt
cmake_minimum_required(VERSION 3.14...3.20)
project(boost_python VERSION "${BOOST_SUPERPROJECT_VERSION}" LANGUAGES CXX)
find_package(Python REQUIRED COMPONENTS Development OPTIONAL_COMPONENTS NumPy)
if(Python_NumPy_FOUND)
message(STATUS "Boost.Python: using Python ${Python_VERSION} with NumPy at ${Python_NumPy_INCLUDE_DIRS}")
else()
message(STATUS "Boost.Python: using Python ${Python_VERSION} without NumPy")
endif()
# boost_pythonXY
set(_pyver ${Python_VERSION_MAJOR}${Python_VERSION_MINOR})
set(_boost_python boost_python${_pyver})
add_library(${_boost_python}
src/dict.cpp
src/errors.cpp
src/exec.cpp
src/import.cpp
src/list.cpp
src/long.cpp
src/module.cpp
src/object_operators.cpp
src/object_protocol.cpp
src/slice.cpp
src/str.cpp
src/tuple.cpp
src/wrapper.cpp
src/converter/from_python.cpp
src/converter/registry.cpp
src/converter/type_id.cpp
src/converter/builtin_converters.cpp
src/converter/arg_to_python_base.cpp
src/object/enum.cpp
src/object/class.cpp
src/object/function.cpp
src/object/inheritance.cpp
src/object/life_support.cpp
src/object/pickle_support.cpp
src/object/iterator.cpp
src/object/stl_iterator.cpp
src/object_protocol.cpp
src/object_operators.cpp
src/object/function_doc_signature.cpp
)
add_library(Boost::python${_pyver} ALIAS ${_boost_python})
target_include_directories(${_boost_python} PUBLIC include)
target_link_libraries(${_boost_python}
PUBLIC
Boost::align
Boost::bind
Boost::config
Boost::conversion
Boost::core
Boost::detail
Boost::foreach
Boost::function
Boost::iterator
Boost::lexical_cast
Boost::mpl
Boost::numeric_conversion
Boost::preprocessor
Boost::smart_ptr
Boost::static_assert
Boost::tuple
Boost::type_traits
Boost::utility
Python::Module
PRIVATE
Boost::graph
Boost::integer
Boost::property_map
)
target_compile_definitions(${_boost_python}
PUBLIC BOOST_PYTHON_NO_LIB
PRIVATE BOOST_PYTHON_SOURCE
)
if(BUILD_SHARED_LIBS)
target_compile_definitions(${_boost_python} PUBLIC BOOST_PYTHON_DYN_LINK)
else()
target_compile_definitions(${_boost_python} PUBLIC BOOST_PYTHON_STATIC_LINK BOOST_PYTHON_STATIC_LIB)
endif()
# Boost::python alias
add_library(boost_python INTERFACE)
add_library(Boost::python ALIAS boost_python)
target_link_libraries(boost_python INTERFACE Boost::python${_pyver})
# Installation
if(BOOST_SUPERPROJECT_VERSION AND NOT CMAKE_VERSION VERSION_LESS 3.13)
boost_install(TARGETS ${_boost_python} boost_python VERSION ${BOOST_SUPERPROJECT_VERSION} HEADER_DIRECTORY include)
endif()
if(Python_NumPy_FOUND)
# boost_numpyXY
set(_boost_numpy boost_numpy${_pyver})
add_library(${_boost_numpy}
src/numpy/dtype.cpp
src/numpy/matrix.cpp
src/numpy/ndarray.cpp
src/numpy/numpy.cpp
src/numpy/scalars.cpp
src/numpy/ufunc.cpp
)
add_library(Boost::numpy${_pyver} ALIAS ${_boost_numpy})
target_include_directories(${_boost_numpy} PUBLIC include)
target_link_libraries(${_boost_numpy}
PUBLIC
Boost::config
Boost::core
Boost::detail
Boost::mpl
Boost::python
Boost::smart_ptr
Python::NumPy
)
target_compile_definitions(${_boost_numpy}
PUBLIC BOOST_NUMPY_NO_LIB
PRIVATE BOOST_NUMPY_SOURCE
)
if(BUILD_SHARED_LIBS)
target_compile_definitions(${_boost_numpy} PUBLIC BOOST_NUMPY_DYN_LINK)
else()
target_compile_definitions(${_boost_numpy} PUBLIC BOOST_NUMPY_STATIC_LINK BOOST_NUMPY_STATIC_LIB)
endif()
# Boost::numpy alias
add_library(boost_numpy INTERFACE)
add_library(Boost::numpy ALIAS boost_numpy)
target_link_libraries(boost_numpy INTERFACE Boost::numpy${_pyver})
# Installation
if(BOOST_SUPERPROJECT_VERSION AND NOT CMAKE_VERSION VERSION_LESS 3.13)
boost_install(TARGETS ${_boost_numpy} boost_numpy VERSION ${BOOST_SUPERPROJECT_VERSION})
endif()
endif()
unset(_pyver)
unset(_boost_python)
unset(_boost_numpy)
# Testing
if(BUILD_TESTING AND EXISTS "${CMAKE_CURRENT_SOURCE_DIR}/test/CMakeLists.txt")
add_subdirectory(test)
endif()

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@@ -1,23 +0,0 @@
Boost Software License - Version 1.0 - August 17th, 2003
Permission is hereby granted, free of charge, to any person or organization
obtaining a copy of the software and accompanying documentation covered by
this license (the "Software") to use, reproduce, display, distribute,
execute, and transmit the Software, and to prepare derivative works of the
Software, and to permit third-parties to whom the Software is furnished to
do so, all subject to the following:
The copyright notices in the Software and this entire statement, including
the above license grant, this restriction and the following disclaimer,
must be included in all copies of the Software, in whole or in part, and
all derivative works of the Software, unless such copies or derivative
works are solely in the form of machine-executable object code generated by
a source language processor.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE, TITLE AND NON-INFRINGEMENT. IN NO EVENT
SHALL THE COPYRIGHT HOLDERS OR ANYONE DISTRIBUTING THE SOFTWARE BE LIABLE
FOR ANY DAMAGES OR OTHER LIABILITY, WHETHER IN CONTRACT, TORT OR OTHERWISE,
ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
DEALINGS IN THE SOFTWARE.

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@@ -1,59 +0,0 @@
![logo](https://raw.githubusercontent.com/boostorg/python/develop/doc/images/bpl.png)
# Synopsis
[![Join the chat at https://gitter.im/boostorg/python](https://badges.gitter.im/boostorg/python.svg)](https://gitter.im/boostorg/python?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
Welcome to Boost.Python, a C++ library which enables seamless interoperability between C++ and the Python programming language. The library includes support for:
* References and Pointers
* Globally Registered Type Coercions
* Automatic Cross-Module Type Conversions
* Efficient Function Overloading
* C++ to Python Exception Translation
* Default Arguments
* Keyword Arguments
* Manipulating Python objects in C++
* Exporting C++ Iterators as Python Iterators
* Documentation Strings
See the [Boost.Python](http://boostorg.github.io/python) documentation for details.
**Hint :** Check out the [development version](http://boostorg.github.io/python/develop) of the documentation to see work in progress.
# Building ![Test Ubuntu](https://github.com/boostorg/python/workflows/Test%20Ubuntu/badge.svg) ![Test OSX](https://github.com/boostorg/python/workflows/Test%20OSX/badge.svg) ![Test Windows](https://github.com/boostorg/python/workflows/Test%20Windows/badge.svg)
While Boost.Python is part of the Boost C++ Libraries super-project, and thus can be compiled as part of Boost, it can also be compiled and installed stand-alone, i.e. against a pre-installed Boost package.
## Prerequisites
* [Python](http://www.python.org)
* [Boost](http://www.boost.org)
* [Faber](https://stefanseefeld.github.io/faber)
## Build
Run
```
faber
```
to build the library.
## Test
Run
```
faber test.report
```
to run the tests.
## Build docs
Run
```
faber doc.html
```
to build the documentation.

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# Copyright René Ferdinand Rivera Morell 2024
# Distributed under the Boost Software License, Version 1.0.
# (See accompanying file LICENSE_1_0.txt or copy at
# http://www.boost.org/LICENSE_1_0.txt)
require-b2 5.2 ;
constant boost_dependencies :
/boost/align//boost_align
/boost/bind//boost_bind
/boost/config//boost_config
/boost/conversion//boost_conversion
/boost/core//boost_core
/boost/detail//boost_detail
/boost/foreach//boost_foreach
/boost/function//boost_function
/boost/iterator//boost_iterator
/boost/lexical_cast//boost_lexical_cast
/boost/mpl//boost_mpl
/boost/numeric_conversion//boost_numeric_conversion
/boost/preprocessor//boost_preprocessor
/boost/static_assert//boost_static_assert
/boost/tuple//boost_tuple
/boost/type_traits//boost_type_traits
/boost/utility//boost_utility ;
project /boost/python
: common-requirements
<include>include
;
explicit
[ alias boost_python : build//boost_python ]
[ alias boost_numpy : build//boost_numpy ]
[ alias all : boost_python boost_numpy test ]
;
call-if : boost-library python
: install boost_python boost_numpy
;

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# Copyright David Abrahams 2001-2006. Distributed under the Boost
# Software License, Version 1.0. (See accompanying
# file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
# (C) Copyright David Abrahams 2001. Permission to copy, use, modify, sell and
# distribute this software is granted provided this copyright notice appears
# in all copies. This software is provided "as is" without express or implied
# warranty, and with no claim as to its suitability for any purpose.
#
# Boost.Python build and test Jamfile
#
# Declares the following targets:
# 1. libboost_python, a static link library to be linked with all
# Boost.Python modules
#
# 2. pairs of test targets of the form <name>.test and <name>.run
# <name>.test runs the test when it is out-of-date, and the "all" target
# depends on it so that it it is built by default. <name>.run runs
# a test unconditionally, and can be used to force a test to run.. Each
# test target builds one or more Boost.Python modules and runs a Python
# script to test them. The test names are:
#
# from ../test
#
# comprehensive - a comprehensive test of Boost.Python features
#
# from ../example:
# abstract -
# getting_started1 -
# getting_started2 -
# simple_vector -
# do_it_yourself_convts -
# pickle1 -
# pickle2 -
# pickle3 -
#
# dvect1 -
# dvect2 -
# ivect1 -
# ivect2 -
# noncopyable -
#
# subproject-specific environment/command-line variables:
#
# PYTHON_TEST_ARGS - specifies arguments to be passed to test scripts on
# the command line. "-v" can be useful if you want to
# see the output of successful tests.
#
# PYTHON_VECT_ITERATIONS - specifies the number of test iterations to use for
# the dvect and ivect tests above.
import os ;
import indirect ;
import modules ;
import feature ;
import property ;
import python ;
if ! [ python.configured ] && ! ( --without-python in [ modules.peek : ARGV ] )
{
# Attempt default configuration of python
import toolset : using ;
using python ;
}
# declare the location of this subproject relative to the root
subproject libs/python/build ;
if [ python.configured ] || ( --without-python in [ modules.peek : ARGV ] )
# Do some OS-specific setup
if $(NT)
{
alias config-warning ;
}
else
{
message config-warning
: "warning: No python installation configured and autoconfiguration"
: "note: failed. See http://www.boost.org/libs/python/doc/building.html"
: "note: for configuration instructions or pass --without-python to"
: "note: suppress this message and silently skip all Boost.Python targets"
PYTHON_ROOT ?= c:/tools/python ;
PYTHON_INCLUDES ?= <include>$(PYTHON_ROOT)/include <gcc><*><include>/usr/include/python2.1 ;
PYTHON_LIBS ?= c:/cygnus/lib/python2.1/config/libpython2.1.dll.a ;
PYTHON_LIB_PATH = $(PYTHON_ROOT)/libs ;
# common properties required for compiling any Python module.
PYTHON_PROPERTIES ?=
<gcc><*><define>SIZEOF_LONG=4
<gcc><*><define>USE_DL_IMPORT
<runtime-link>dynamic
;
SHELL_SET ?= "set " ;
SHELL_EXPORT ?= ; # shell variables are exported by default
}
else if $(UNIX)
{
PYTHON_INCLUDES ?= <include>/usr/include/python1.5 ;
PYTHON_LIBS ?= /usr/lib/python1.5/config/libpython1.5.a ;
SHELL_SET ?= "" ;
SHELL_EXPORT ?= "export " ;
}
constant boost_dependencies_private :
/boost/graph//boost_graph
/boost/integer//boost_integer
/boost/property_map//boost_property_map
/boost/smart_ptr//boost_smart_ptr
;
#######################
project
: source-location ../src
: common-requirements <library>$(boost_dependencies)
: requirements <library>$(boost_dependencies_private)
;
#
# Declare the boost python static link library
#
rule cond ( test ? : yes * : no * ) { if $(test) { return $(yes) ; } else { return $(no) ; } }
rule unless ( test ? : yes * : no * ) { if ! $(test) { return $(yes) ; } else { return $(no) ; } }
local rule eq ( a : b ) { if $(a) = $(b) { return 1 ; } }
# standard include requirements for anything using Boost.Python
BOOST_PYTHON_INCLUDES = <include>$(BOOST_ROOT) $(PYTHON_INCLUDES) ;
rule tag ( name : type ? : property-set )
# Base names of the source files for libboost_python
CPP_SOURCES =
classes conversions extension_class functions
init_function module_builder objects types cross_module ;
lib libboost_python : ../src/$(CPP_SOURCES).cpp
# requirements
: $(BOOST_PYTHON_INCLUDES)
<shared-linkable>true
$(PYTHON_PROPERTIES) ;
#######################
# boost-python name : sources : requirements : default-BUILD
#
# Declare a boost python module. Return a list of the DLL files generated.
rule boost-python
{
if python-tag in [ RULENAMES $(__name__) ]
# declare a DLL; add the boost python library to sources
dll $(<) : <lib>libboost_python $(>)
# Requirements
: $(3) # caller-specified requirements
# standard requirements
$(BOOST_PYTHON_INCLUDES)
<msvc><*><library-path>$(PYTHON_LIB_PATH)
<gcc><*><library-file>$(PYTHON_LIBS)
$(PYTHON_PROPERTIES)
: $(4) ; # pass on the default-BUILD, if any
}
#######################
# boost-python-test target : python-script sources : requirements : local-build : args
#
# declare two python module tests: $(<).test which builds when out-of-date, and
# $(<).run which builds unconditionally.
rule boost-python-test
{
# tell Jam that the python script is relative to this directory
SEARCH on $(>[1]) = $(SEARCH_SOURCE) ;
# required command-line args can be specified in argument 5
# The user can add additional arguments in PYTHON_TEST_ARGS.
local gPYTHON_TEST_ARGS = $(5) $(PYTHON_TEST_ARGS) ;
# declare the two subsidiary tests.
declare-local-target $(<:S=.test) : $(>) : $(PYTHON_PROPERTIES) : $(4) : PYTHON_TEST ;
declare-local-target $(<:S=.run) : $(>) : $(PYTHON_PROPERTIES) : $(4) : PYTHON_RUNTEST ;
}
# how do we invoke python?
PYTHON ?= python ;
# special rules for two new target types: PYTHON_TEST and PYTHON_RUNTEST.
# These are identical except that PYTHON_TEST runs the test when out-of-date, and
# PYTHON_RUNTEST runs the test unconditionally. These are used by boost-python-test.
SUFPYTHON_TEST = .test ;
gGENERATOR_FUNCTION(PYTHON_TEST) = python-test-target ;
rule python-test-target # test-target : sources :
{
python-test-aux $(<) : $(>) ;
Clean clean : $(<) ; # remove the test-target as part of any clean operation
type-DEPENDS test : $(<) ;
MakeLocate $(<) : $(LOCATE_TARGET) ;
}
actions python-test-target
{
$(SHELL_SET)PYTHONPATH=$(PYTHONPATH)
$(SHELL_EXPORT)PYTHONPATH
$(PYTHON) "$(>)" $(ARGS) > "$(<)"
}
SUFPYTHON_RUNTEST = .run ;
gGENERATOR_FUNCTION(PYTHON_RUNTEST) = python-runtest-target ;
rule python-runtest-target # test-target : sources :
{
python-test-aux $(<) : $(>) ;
NOTFILE $(<) ;
ALWAYS $(<) ;
}
actions python-runtest-target
{
$(SHELL_SET)PYTHONPATH=$(PYTHONPATH)
$(SHELL_EXPORT)PYTHONPATH
$(PYTHON) "$(>)" $(ARGS)
}
rule python-test-aux # target : sources
{
DEPENDS $(<) : $(>) ;
ARGS on $(<) += $(gPYTHON_TEST_ARGS) ;
# Some tests need an extra command-line arg if built with
# msvc. Checking the target grist is a cheap way to
# find out.
switch $(<)
{
return [ $(__name__).python-tag $(name) : $(type) : $(property-set) ] ;
case <*\\\\msvc\\\\*>* : ARGS on $(<) += --broken-auto-ptr ;
}
# compute the PYTHONPATH environment variable that will allow the test to
# find all of the modules on which it depends.
PYTHONPATH on $(<) = [ join
$(gLOCATE($(>[1]))) # location of python test file
$(gRUN_PATH($(<))) # location of module dependencies
[ join-path $(TOP) libs python test ] # location of doctest
$(PYTHONPATH) # base PYTHONPATH from environment
: $(SPLITPATH) ] ; # platform path separator
}
if [ python.configured ]
############# comprehensive module and test ###########
boost-python boost_python_test : ../test/comprehensive.cpp ;
boost-python-test comprehensive : [ join-path $(DOTDOT) test comprehensive.py ] <lib>boost_python_test ;
############# simple tests from ../example ############
rule boost-python-example-test
{
lib boost_python
: # sources
list.cpp
long.cpp
dict.cpp
tuple.cpp
str.cpp
slice.cpp
converter/from_python.cpp
converter/registry.cpp
converter/type_id.cpp
object/enum.cpp
object/class.cpp
object/function.cpp
object/inheritance.cpp
object/life_support.cpp
object/pickle_support.cpp
errors.cpp
module.cpp
converter/builtin_converters.cpp
converter/arg_to_python_base.cpp
object/iterator.cpp
object/stl_iterator.cpp
object_protocol.cpp
object_operators.cpp
wrapper.cpp
import.cpp
exec.cpp
object/function_doc_signature.cpp
: # requirements
<link>static:<define>BOOST_PYTHON_STATIC_LIB
<define>BOOST_PYTHON_SOURCE
# On Windows, all code using Python has to link to the Python
# import library.
#
# On *nix we never link libboost_python to libpython. When
# extending Python, all Python symbols are provided by the
# Python interpreter executable. When embedding Python, the
# client executable is expected to explicitly link to
# /python//python (the target representing libpython) itself.
#
# python_for_extensions is a target defined by Boost.Build to
# provide the Python include paths, and on Windows, the Python
# import library, as usage requirements.
[ cond [ python.configured ] : <library>/python//python_for_extensions ]
# we prevent building when there is no python available
# as it's not possible anyway, and to cause dependents to
# fail to build
[ unless [ python.configured ] : <build>no ]
<dependency>config-warning
<python-debugging>on:<define>BOOST_DEBUG_PYTHON
-<tag>@%boostcpp.tag
-<tag>@$(BOOST_JAMROOT_MODULE)%$(BOOST_JAMROOT_MODULE).tag
<tag>@tag
<conditional>@python.require-py
: # default build
<link>shared
: # usage requirements
<link>static:<define>BOOST_PYTHON_STATIC_LIB
<python-debugging>on:<define>BOOST_DEBUG_PYTHON
<define>BOOST_PYTHON_NO_LIB
;
boost-python $(<) : ../example/$(<).cpp ;
boost-python-test $(<) : [ join-path $(DOTDOT) example test_$(<).py ] <lib>$(<) ;
}
else
boost-python-example-test abstract ;
boost-python-example-test getting_started1 ;
boost-python-example-test getting_started2 ;
boost-python-example-test simple_vector ;
boost-python-example-test do_it_yourself_convts ;
boost-python-example-test pickle1 ;
boost-python-example-test pickle2 ;
boost-python-example-test pickle3 ;
boost-python ivect : ../example/ivect.cpp ;
boost-python dvect : ../example/dvect.cpp ;
boost-python noncopyable_export : ../example/noncopyable_export.cpp ;
boost-python noncopyable_import : ../example/noncopyable_import.cpp ;
############## cross-module tests from ../example ##########
# A simple rule to build a test which depends on multiple modules in the PYTHONPATH
rule boost-python-multi-example-test # test-name : python-file libs
{
alias boost_python : config-warning ;
boost-python-test $(<) : ../example/tst_$(<).py <lib>$(>) : : : $(PYTHON_VECT_ITERATIONS) ;
}
PYTHON_VECT_ITERATIONS ?= 10 ;
if [ python.configured ] && [ python.numpy ]
{
boost-python-multi-example-test dvect1 : ivect dvect ;
boost-python-multi-example-test dvect2 : ivect dvect ;
numpy-include = [ python.numpy-include ] ;
lib boost_numpy
: # sources
numpy/dtype.cpp
numpy/matrix.cpp
numpy/ndarray.cpp
numpy/numpy.cpp
numpy/scalars.cpp
numpy/ufunc.cpp
: # requirements
<link>static:<define>BOOST_NUMPY_STATIC_LIB
<define>BOOST_NUMPY_SOURCE
[ cond [ python.numpy ] : <library>/python//python_for_extensions ]
[ unless [ python.numpy ] : <build>no ]
<library>/python//numpy
<library>boost_python
<python-debugging>on:<define>BOOST_DEBUG_PYTHON
-<tag>@%boostcpp.tag
-<tag>@$(BOOST_JAMROOT_MODULE)%$(BOOST_JAMROOT_MODULE).tag
<tag>@tag
<conditional>@python.require-py
boost-python-multi-example-test ivect1 : ivect dvect ;
boost-python-multi-example-test ivect2 : ivect dvect ;
: # default build
<link>shared
: # usage requirements
<link>static:<define>BOOST_NUMPY_STATIC_LIB
<python-debugging>on:<define>BOOST_DEBUG_PYTHON
<define>BOOST_NUMPY_NO_LIB
;
boost-python-multi-example-test noncopyable : noncopyable_import noncopyable_export ;
}
else
{
alias boost_numpy : config-warning ;
}

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build/como.mak Normal file
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# Revision History:
# 17 Apr 01 include cross-module support, compile getting_started1 (R.W. Grosse-Kunstleve) UNTESTED!
# 06 Mar 01 Fixed typo in use of "PYTHON_LIB" (Dave Abrahams)
# 04 Mar 01 Changed library name to libboost_python.a (David Abrahams)
LIBSRC = \
classes.cpp \
conversions.cpp \
cross_module.cpp \
extension_class.cpp \
functions.cpp \
init_function.cpp \
module_builder.cpp \
objects.cpp \
types.cpp
LIBOBJ = $(LIBSRC:.cpp=.o)
OBJ = $(LIBOBJ)
ifeq "$(OS)" "Windows_NT"
PYTHON_LIB=c:/tools/python/libs/python15.lib
INC = -Ic:/cygnus/usr/include/g++-3 -Ic:/cygnus/usr/include -Ic:/boost -Ic:/tools/python/include
MODULE_EXTENSION=dll
else
INC = -I/usr/local/include/python1.5
MODULE_EXTENSION=so
endif
%.o: ../src/%.cpp
como --pic $(INC) -o $*.o -c $<
%.d: ../src/%.cpp
@echo creating $@
@set -e; como -M $(INC) -c $< \
| sed 's/\($*\)\.o[ :]*/\1.o $@ : /g' > $@; \
[ -s $@ ] || rm -f $@
getting_started1: getting_started1.o libboost_python.a
como-dyn-link -o ../example/getting_started1.$(MODULE_EXTENSION) $(PYTHON_LIB) getting_started1.o -L. -lboost_python
ln -s ../test/doctest.py ../example
python ../example/test_getting_started1.py
getting_started1.o: ../example/getting_started1.cpp
como --pic $(INC) -o $*.o -c $<
clean:
rm -rf *.o *.$(MODULE_EXTENSION) *.a *.d *.pyc *.bak a.out
libboost_python.a: $(LIBOBJ)
rm -f libboost_python.a
ar cq libboost_python.a $(LIBOBJ)
DEP = $(OBJ:.o=.d)
ifneq "$(MAKECMDGOALS)" "clean"
include $(DEP)
endif

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142
build/filemgr.py Normal file
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# Revision history:
# 12 Apr 01 use os.path, shutil
# Initial version: R.W. Grosse-Kunstleve
bpl_src = "/libs/python/src"
bpl_tst = "/libs/python/test"
bpl_exa = "/libs/python/example"
files = (
bpl_src + "/classes.cpp",
bpl_src + "/conversions.cpp",
bpl_src + "/extension_class.cpp",
bpl_src + "/functions.cpp",
bpl_src + "/init_function.cpp",
bpl_src + "/module_builder.cpp",
bpl_src + "/objects.cpp",
bpl_src + "/types.cpp",
bpl_src + "/cross_module.cpp",
bpl_tst + "/comprehensive.cpp",
bpl_tst + "/comprehensive.hpp",
bpl_tst + "/comprehensive.py",
bpl_tst + "/doctest.py",
bpl_exa + "/abstract.cpp",
bpl_exa + "/getting_started1.cpp",
bpl_exa + "/getting_started2.cpp",
bpl_exa + "/simple_vector.cpp",
bpl_exa + "/do_it_yourself_convts.cpp",
bpl_exa + "/pickle1.cpp",
bpl_exa + "/pickle2.cpp",
bpl_exa + "/pickle3.cpp",
bpl_exa + "/test_abstract.py",
bpl_exa + "/test_getting_started1.py",
bpl_exa + "/test_getting_started2.py",
bpl_exa + "/test_simple_vector.py",
bpl_exa + "/test_do_it_yourself_convts.py",
bpl_exa + "/test_pickle1.py",
bpl_exa + "/test_pickle2.py",
bpl_exa + "/test_pickle3.py",
bpl_exa + "/noncopyable.h",
bpl_exa + "/noncopyable_export.cpp",
bpl_exa + "/noncopyable_import.cpp",
bpl_exa + "/dvect.h",
bpl_exa + "/dvect.cpp",
bpl_exa + "/dvect_conversions.cpp",
bpl_exa + "/dvect_defs.cpp",
bpl_exa + "/ivect.h",
bpl_exa + "/ivect.cpp",
bpl_exa + "/ivect_conversions.cpp",
bpl_exa + "/ivect_defs.cpp",
bpl_exa + "/tst_noncopyable.py",
bpl_exa + "/tst_dvect1.py",
bpl_exa + "/tst_dvect2.py",
bpl_exa + "/tst_ivect1.py",
bpl_exa + "/tst_ivect2.py",
bpl_exa + "/test_cross_module.py",
bpl_exa + "/vector_wrapper.h",
bpl_exa + "/richcmp1.cpp",
bpl_exa + "/richcmp2.cpp",
bpl_exa + "/richcmp3.cpp",
bpl_exa + "/test_richcmp1.py",
bpl_exa + "/test_richcmp2.py",
bpl_exa + "/test_richcmp3.py",
)
defs = (
"boost_python_test",
"abstract",
"getting_started1",
"getting_started2",
"simple_vector",
"do_it_yourself_convts",
"pickle1",
"pickle2",
"pickle3",
"noncopyable_export",
"noncopyable_import",
"ivect",
"dvect",
"richcmp1",
"richcmp2",
"richcmp3",
)
if (__name__ == "__main__"):
import sys, os, shutil
path = sys.argv[1]
mode = sys.argv[2]
if (not mode in ("softlinks", "unlink", "cp", "rm", "copy", "del")):
raise RuntimeError, \
"usage: python filemgr.py path <softlinks|unlink|cp|rm|copy|del>"
if (mode in ("cp", "copy")):
for fn in files:
f = os.path.basename(fn)
print "Copying: " + f
shutil.copy(path + fn, ".")
elif (mode == "softlinks"):
for fn in files:
f = os.path.basename(fn)
if (os.path.exists(f)):
print "File exists: " + f
else:
print "Linking: " + f
os.symlink(path + fn, f)
elif (mode in ("rm", "del")):
for fn in files:
f = os.path.basename(fn)
if (os.path.exists(f)):
print "Removing: " + f
try: os.unlink(f)
except: pass
elif (mode == "unlink"):
for fn in files:
f = os.path.basename(fn)
if (os.path.exists(f)):
if (os.path.islink(f)):
print "Unlinking: " + f
try: os.unlink(f)
except: pass
else:
print "Not a softlink: " + f
if (mode in ("softlinks", "cp", "copy")):
for d in defs:
fn = d + ".def"
print "Creating: " + fn
f = open(fn, "w")
f.write("EXPORTS\n")
f.write("\tinit" + d + "\n")
f.close()
if (mode in ("unlink", "rm", "del")):
for d in defs:
fn = d + ".def"
if (os.path.exists(fn)):
print "Removing: " + fn
try: os.unlink(fn)
except: pass

87
build/gcc.mak Normal file
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# Revision History
# 17 Apr 01 include cross-module support, compile getting_started1 (R.W. Grosse-Kunstleve)
# 17 Apr 01 build shared library (patch provided by Dan Nuffer)
# 04 Mar 01 Changed library name to libboost_python.a, various cleanups,
# attempted Cygwin compatibility. Still needs testing on Linux
# (David Abrahams)
LIBSRC = \
classes.cpp \
conversions.cpp \
cross_module.cpp \
extension_class.cpp \
functions.cpp \
init_function.cpp \
module_builder.cpp \
objects.cpp \
types.cpp
LIBOBJ = $(LIBSRC:.cpp=.o)
OBJ = $(LIBOBJ)
LIBNAME = libboost_python
# libpython2.0.dll
ifeq "$(OS)" "Windows_NT"
ROOT=c:/cygnus
INC = -Ic:/cygnus/usr/include/g++-3 -Ic:/cygnus/usr/include -Ic:/boost -I$(PYTHON_INC)
MODULE_EXTENSION=dll
PYTHON_LIB=c:/cygnus/usr/local/lib/python2.0/config/libpython2.0.dll.a
SHARED_LIB = $(LIBNAME).dll
else
PYTHON_INC=$(ROOT)/usr/local/Python-2.0/include/python2.0
BOOST_INC=../../..
INC = -I$(BOOST_INC) -I$(PYTHON_INC)
MODULE_EXTENSION=so
VERSION=1
SHARED_LIB = $(LIBNAME).so.$(VERSION)
endif
%.o: ../src/%.cpp
g++ -fPIC -Wall -W $(INC) $(CXXFLAGS) -o $*.o -c $<
%.d: ../src/%.cpp
@echo creating $@
@set -e; g++ -M $(INC) -c $< \
| sed 's/\($*\)\.o[ :]*/\1.o $@ : /g' > $@; \
[ -s $@ ] || rm -f $@
PYTHON = python
all: test $(SHARED_LIB) getting_started1
test: comprehensive.o $(LIBNAME).a $(SHARED_LIB)
g++ $(CXXFLAGS) -shared -o ../test/boost_python_test.$(MODULE_EXTENSION) comprehensive.o -L. -lboost_python $(PYTHON_LIB)
$(PYTHON) ../test/comprehensive.py
comprehensive.o: ../test/comprehensive.cpp
g++ $(CXXFLAGS) --template-depth-32 -fPIC -Wall -W $(INC) -o $*.o -c $<
getting_started1: getting_started1.o $(LIBNAME).a
g++ $(CXXFLAGS) -shared -o ../example/getting_started1.$(MODULE_EXTENSION) getting_started1.o -L. -lboost_python $(PYTHON_LIB)
ln -s ../test/doctest.py ../example
$(PYTHON) ../example/test_getting_started1.py
getting_started1.o: ../example/getting_started1.cpp
g++ $(CXXFLAGS) --template-depth-32 -fPIC -Wall -W $(INC) -o $*.o -c $<
clean:
rm -rf *.o *.$(MODULE_EXTENSION) *.a *.d *.pyc *.bak a.out
$(LIBNAME).a: $(LIBOBJ)
rm -f $@
ar cqs $@ $(LIBOBJ)
$(SHARED_LIB): $(LIBOBJ)
g++ $(CXXFLAGS) -shared -o $@ -Wl,--soname=$(LIBNAME).$(MODULE_EXTENSION)
DEP = $(OBJ:.o=.d)
ifneq "$(MAKECMDGOALS)" "clean"
include $(DEP)
endif

View File

@@ -0,0 +1,136 @@
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BSC32=bscmake.exe
# ADD BASE BSC32 /nologo
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# ADD CPP /nologo /MDd /W3 /GR /GX /Zi /Od /I "..\..\..\.." /I "c:\tools\python\include" /D "WIN32" /D "_DEBUG" /D "_WINDOWS" /D "_MBCS" /D "_USRDLL" /D "TEST_EXPORTS" /D "BOOST_DEBUG_PYTHON" /YX /FD /GZ /c
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# ADD MTL /nologo /D "_DEBUG" /mktyplib203 /win32
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BSC32=bscmake.exe
# ADD BASE BSC32 /nologo
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# ADD LINK32 kernel32.lib user32.lib gdi32.lib winspool.lib comdlg32.lib advapi32.lib shell32.lib ole32.lib oleaut32.lib uuid.lib odbc32.lib odbccp32.lib /nologo /dll /incremental:no /pdb:"DebugPython/boost_python_test_d.pdb" /debug /machine:I386 /out:"DebugPython/getting_started1_d.dll" /pdbtype:sept /libpath:"c:\tools\python\src\PCbuild"
# SUBTRACT LINK32 /pdb:none
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# Begin Group "Source Files"
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View File

@@ -0,0 +1,135 @@
# Microsoft Developer Studio Project File - Name="getting_started2" - Package Owner=<4>
# Microsoft Developer Studio Generated Build File, Format Version 6.00
# ** DO NOT EDIT **
# TARGTYPE "Win32 (x86) Dynamic-Link Library" 0x0102
CFG=getting_started2 - Win32 DebugPython
!MESSAGE This is not a valid makefile. To build this project using NMAKE,
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!MESSAGE
!MESSAGE NMAKE /f "getting_started2.mak".
!MESSAGE
!MESSAGE You can specify a configuration when running NMAKE
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!MESSAGE
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MTL=midl.exe
RSC=rc.exe
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# PROP BASE Use_MFC 0
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177
build/irix_CC.mak Normal file
View File

@@ -0,0 +1,177 @@
# Usage:
#
# Create a new empty directory anywhere (preferably not in the boost tree).
# Copy this Makefile to that new directory and rename it to "Makefile"
# Adjust the pathnames below.
#
# make softlinks Create softlinks to source code and tests
# make Compile all sources
# make test Run doctest tests
# make clean Remove all object files
# make unlink Remove softlinks
#
# Revision history:
# 12 Apr 01 new macro ROOT to simplify configuration (R.W. Grosse-Kunstleve)
# Initial version: R.W. Grosse-Kunstleve
ROOT=$(HOME)
BOOST=$(ROOT)/boost
PYEXE=/usr/local/Python-1.5.2/bin/python
PYINC=-I/usr/local/Python-1.5.2/include/python1.5
#PYEXE=/usr/local/Python-2.1/bin/python
#PYINC=-I/usr/local/Python-2.1/include/python2.1
STLPORTINC=-I$(BOOST)/boost/compatibility/cpp_c_headers
STDOPTS=
WARNOPTS=-woff 1001,1234,1682
OPTOPTS=-g
CPP=CC -LANG:std -n32 -mips4
CPPOPTS=$(STLPORTINC) $(STLPORTOPTS) -I$(BOOST) $(PYINC) \
$(STDOPTS) $(WARNOPTS) $(OPTOPTS)
MAKEDEP=-M
LD=CC -LANG:std -n32 -mips4
LDOPTS=-shared
OBJ=classes.o conversions.o extension_class.o functions.o \
init_function.o module_builder.o \
objects.o types.o cross_module.o
DEPOBJ=$(OBJ) \
comprehensive.o \
abstract.o \
getting_started1.o getting_started2.o \
simple_vector.o \
do_it_yourself_convts.o \
pickle1.o pickle2.o pickle3.o \
noncopyable_export.o noncopyable_import.o \
ivect.o dvect.o \
richcmp1.o richcmp2.o richcmp3.o
.SUFFIXES: .o .cpp
all: libboost_python.a \
boost_python_test.so \
abstract.so \
getting_started1.so getting_started2.so \
simple_vector.so \
do_it_yourself_convts.so \
pickle1.so pickle2.so pickle3.so \
noncopyable_export.so noncopyable_import.so \
ivect.so dvect.so \
richcmp1.so richcmp2.so richcmp3.so
libboost_python.a: $(OBJ)
rm -f libboost_python.a
$(CPP) -ar -o libboost_python.a $(OBJ)
boost_python_test.so: $(OBJ) comprehensive.o
$(LD) $(LDOPTS) $(OBJ) comprehensive.o -o boost_python_test.so -lm
abstract.so: $(OBJ) abstract.o
$(LD) $(LDOPTS) $(OBJ) abstract.o -o abstract.so
getting_started1.so: $(OBJ) getting_started1.o
$(LD) $(LDOPTS) $(OBJ) getting_started1.o -o getting_started1.so
getting_started2.so: $(OBJ) getting_started2.o
$(LD) $(LDOPTS) $(OBJ) getting_started2.o -o getting_started2.so
simple_vector.so: $(OBJ) simple_vector.o
$(LD) $(LDOPTS) $(OBJ) simple_vector.o -o simple_vector.so
do_it_yourself_convts.so: $(OBJ) do_it_yourself_convts.o
$(LD) $(LDOPTS) $(OBJ) do_it_yourself_convts.o -o do_it_yourself_convts.so
pickle1.so: $(OBJ) pickle1.o
$(LD) $(LDOPTS) $(OBJ) pickle1.o -o pickle1.so
pickle2.so: $(OBJ) pickle2.o
$(LD) $(LDOPTS) $(OBJ) pickle2.o -o pickle2.so
pickle3.so: $(OBJ) pickle3.o
$(LD) $(LDOPTS) $(OBJ) pickle3.o -o pickle3.so
noncopyable_export.so: $(OBJ) noncopyable_export.o
$(LD) $(LDOPTS) $(OBJ) $(HIDDEN) \
noncopyable_export.o -o noncopyable_export.so
noncopyable_import.so: $(OBJ) noncopyable_import.o
$(LD) $(LDOPTS) $(OBJ) $(HIDDEN) \
noncopyable_import.o -o noncopyable_import.so
ivect.so: $(OBJ) ivect.o
$(LD) $(LDOPTS) $(OBJ) $(HIDDEN) ivect.o -o ivect.so
dvect.so: $(OBJ) dvect.o
$(LD) $(LDOPTS) $(OBJ) $(HIDDEN) dvect.o -o dvect.so
richcmp1.so: $(OBJ) richcmp1.o
$(LD) $(LDOPTS) $(OBJ) richcmp1.o -o richcmp1.so
richcmp2.so: $(OBJ) richcmp2.o
$(LD) $(LDOPTS) $(OBJ) richcmp2.o -o richcmp2.so
richcmp3.so: $(OBJ) richcmp3.o
$(LD) $(LDOPTS) $(OBJ) richcmp3.o -o richcmp3.so
.cpp.o:
$(CPP) $(CPPOPTS) -c $*.cpp
test:
$(PYEXE) comprehensive.py
$(PYEXE) test_abstract.py
$(PYEXE) test_getting_started1.py
$(PYEXE) test_getting_started2.py
$(PYEXE) test_simple_vector.py
$(PYEXE) test_do_it_yourself_convts.py
$(PYEXE) test_pickle1.py
$(PYEXE) test_pickle2.py
$(PYEXE) test_pickle3.py
$(PYEXE) test_cross_module.py
$(PYEXE) test_richcmp1.py
$(PYEXE) test_richcmp2.py
$(PYEXE) test_richcmp3.py
clean:
rm -f $(OBJ) libboost_python.a libboost_python.a.input
rm -f comprehensive.o boost_python_test.so
rm -f abstract.o abstract.so
rm -f getting_started1.o getting_started1.so
rm -f getting_started2.o getting_started2.so
rm -f simple_vector.o simple_vector.so
rm -f do_it_yourself_convts.o do_it_yourself_convts.so
rm -f pickle1.o pickle1.so
rm -f pickle2.o pickle2.so
rm -f pickle3.o pickle3.so
rm -f noncopyable_export.o noncopyable_export.so
rm -f noncopyable_import.o noncopyable_import.so
rm -f ivect.o ivect.so
rm -f dvect.o dvect.so
rm -f richcmp1.o richcmp1.so
rm -f richcmp2.o richcmp2.so
rm -f richcmp3.o richcmp3.so
rm -f so_locations *.pyc
rm -rf ii_files
softlinks:
$(PYEXE) $(BOOST)/libs/python/build/filemgr.py $(BOOST) softlinks
unlink:
$(PYEXE) $(BOOST)/libs/python/build/filemgr.py $(BOOST) unlink
cp:
$(PYEXE) $(BOOST)/libs/python/build/filemgr.py $(BOOST) cp
rm:
$(PYEXE) $(BOOST)/libs/python/build/filemgr.py $(BOOST) rm
depend:
@ cat Makefile.nodepend; \
for obj in $(DEPOBJ); \
do \
bn=`echo "$$obj" | cut -d. -f1`; \
$(CPP) $(CPPOPTS) $(MAKEDEP) "$$bn".cpp; \
done

177
build/linux_gcc.mak Normal file
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# Usage:
#
# Create a new empty directory anywhere (preferably not in the boost tree).
# Copy this Makefile to that new directory and rename it to "Makefile"
# Adjust the pathnames below.
#
# make softlinks Create softlinks to source code and tests
# make Compile all sources
# make test Run doctest tests
# make clean Remove all object files
# make unlink Remove softlinks
#
# Revision history:
# 12 Apr 01 new macro ROOT to simplify configuration (R.W. Grosse-Kunstleve)
# Initial version: R.W. Grosse-Kunstleve
ROOT=$(HOME)
BOOST=$(ROOT)/boost
PYEXE=PYTHONPATH=. /usr/bin/python
PYINC=-I/usr/include/python1.5
#PYEXE=/usr/local/Python-1.5.2/bin/python
#PYINC=-I/usr/local/Python-1.5.2/include/python1.5
#PYEXE=/usr/local/Python-2.1/bin/python
#PYINC=-I/usr/local/Python-2.1/include/python2.1
STDOPTS=-fPIC -ftemplate-depth-21
WARNOPTS=
OPTOPTS=-g
CPP=g++
CPPOPTS=$(STLPORTINC) $(STLPORTOPTS) -I$(BOOST) $(PYINC) \
$(STDOPTS) $(WARNOPTS) $(OPTOPTS)
MAKEDEP=-M
LD=$(CPP)
LDOPTS=-shared
OBJ=classes.o conversions.o extension_class.o functions.o \
init_function.o module_builder.o \
objects.o types.o cross_module.o
DEPOBJ=$(OBJ) \
comprehensive.o \
abstract.o \
getting_started1.o getting_started2.o \
simple_vector.o \
do_it_yourself_convts.o \
pickle1.o pickle2.o pickle3.o \
noncopyable_export.o noncopyable_import.o \
ivect.o dvect.o \
richcmp1.o richcmp2.o richcmp3.o
.SUFFIXES: .o .cpp
all: libboost_python.a \
boost_python_test.so \
abstract.so \
getting_started1.so getting_started2.so \
simple_vector.so \
do_it_yourself_convts.so \
pickle1.so pickle2.so pickle3.so \
noncopyable_export.so noncopyable_import.so \
ivect.so dvect.so \
richcmp1.so richcmp2.so richcmp3.so
libboost_python.a: $(OBJ)
rm -f libboost_python.a
ar r libboost_python.a $(OBJ)
boost_python_test.so: $(OBJ) comprehensive.o
$(LD) $(LDOPTS) $(OBJ) comprehensive.o -o boost_python_test.so -lm
abstract.so: $(OBJ) abstract.o
$(LD) $(LDOPTS) $(OBJ) abstract.o -o abstract.so
getting_started1.so: $(OBJ) getting_started1.o
$(LD) $(LDOPTS) $(OBJ) getting_started1.o -o getting_started1.so
getting_started2.so: $(OBJ) getting_started2.o
$(LD) $(LDOPTS) $(OBJ) getting_started2.o -o getting_started2.so
simple_vector.so: $(OBJ) simple_vector.o
$(LD) $(LDOPTS) $(OBJ) simple_vector.o -o simple_vector.so
do_it_yourself_convts.so: $(OBJ) do_it_yourself_convts.o
$(LD) $(LDOPTS) $(OBJ) do_it_yourself_convts.o -o do_it_yourself_convts.so
pickle1.so: $(OBJ) pickle1.o
$(LD) $(LDOPTS) $(OBJ) pickle1.o -o pickle1.so
pickle2.so: $(OBJ) pickle2.o
$(LD) $(LDOPTS) $(OBJ) pickle2.o -o pickle2.so
pickle3.so: $(OBJ) pickle3.o
$(LD) $(LDOPTS) $(OBJ) pickle3.o -o pickle3.so
noncopyable_export.so: $(OBJ) noncopyable_export.o
$(LD) $(LDOPTS) $(OBJ) $(HIDDEN) \
noncopyable_export.o -o noncopyable_export.so
noncopyable_import.so: $(OBJ) noncopyable_import.o
$(LD) $(LDOPTS) $(OBJ) $(HIDDEN) \
noncopyable_import.o -o noncopyable_import.so
ivect.so: $(OBJ) ivect.o
$(LD) $(LDOPTS) $(OBJ) $(HIDDEN) ivect.o -o ivect.so
dvect.so: $(OBJ) dvect.o
$(LD) $(LDOPTS) $(OBJ) $(HIDDEN) dvect.o -o dvect.so
richcmp1.so: $(OBJ) richcmp1.o
$(LD) $(LDOPTS) $(OBJ) richcmp1.o -o richcmp1.so
richcmp2.so: $(OBJ) richcmp2.o
$(LD) $(LDOPTS) $(OBJ) richcmp2.o -o richcmp2.so
richcmp3.so: $(OBJ) richcmp3.o
$(LD) $(LDOPTS) $(OBJ) richcmp3.o -o richcmp3.so
.cpp.o:
$(CPP) $(CPPOPTS) -c $*.cpp
test:
$(PYEXE) comprehensive.py
$(PYEXE) test_abstract.py
$(PYEXE) test_getting_started1.py
$(PYEXE) test_getting_started2.py
$(PYEXE) test_simple_vector.py
$(PYEXE) test_do_it_yourself_convts.py
$(PYEXE) test_pickle1.py
$(PYEXE) test_pickle2.py
$(PYEXE) test_pickle3.py
$(PYEXE) test_cross_module.py
$(PYEXE) test_richcmp1.py
$(PYEXE) test_richcmp2.py
$(PYEXE) test_richcmp3.py
clean:
rm -f $(OBJ) libboost_python.a libboost_python.a.input
rm -f comprehensive.o boost_python_test.so
rm -f abstract.o abstract.so
rm -f getting_started1.o getting_started1.so
rm -f getting_started2.o getting_started2.so
rm -f simple_vector.o simple_vector.so
rm -f do_it_yourself_convts.o do_it_yourself_convts.so
rm -f pickle1.o pickle1.so
rm -f pickle2.o pickle2.so
rm -f pickle3.o pickle3.so
rm -f noncopyable_export.o noncopyable_export.so
rm -f noncopyable_import.o noncopyable_import.so
rm -f ivect.o ivect.so
rm -f dvect.o dvect.so
rm -f richcmp1.o richcmp1.so
rm -f richcmp2.o richcmp2.so
rm -f richcmp3.o richcmp3.so
rm -f so_locations *.pyc
softlinks:
$(PYEXE) $(BOOST)/libs/python/build/filemgr.py $(BOOST) softlinks
unlink:
$(PYEXE) $(BOOST)/libs/python/build/filemgr.py $(BOOST) unlink
cp:
$(PYEXE) $(BOOST)/libs/python/build/filemgr.py $(BOOST) cp
rm:
$(PYEXE) $(BOOST)/libs/python/build/filemgr.py $(BOOST) rm
depend:
@ cat Makefile.nodepend; \
for obj in $(DEPOBJ); \
do \
bn=`echo "$$obj" | cut -d. -f1`; \
$(CPP) $(CPPOPTS) $(MAKEDEP) "$$bn".cpp; \
done

211
build/mingw32.mak Normal file
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# Usage:
#
# make copy Copy the sources and tests
# make Compile all sources
# make test Run doctest tests
# make clean Remove all object files
# make del Remove the sources and tests
#
# Revision history:
# 12 Apr 01 new macro ROOT to simplify configuration (R.W. Grosse-Kunstleve)
# Initial version: R.W. Grosse-Kunstleve
# To install mingw32, follow instructions at:
# http://starship.python.net/crew/kernr/mingw32/Notes.html
# In particular, install:
# ftp://ftp.xraylith.wisc.edu/pub/khan/gnu-win32/mingw32/gcc-2.95.2/gcc-2.95.2-msvcrt.exe
# ftp://ftp.xraylith.wisc.edu/pub/khan/gnu-win32/mingw32/gcc-2.95.2/fixes/quote-fix-msvcrt.exe
# http://starship.python.net/crew/kernr/mingw32/Python-1.5.2-mingw32.zip
# Unpack the first two archives in the default locations and update your PATH.
# Unpack the third archive in \usr.
# Note: comprehensive.cpp generates compiler errors and later crashes.
# L:\boost\boost\python\detail\extension_class.hpp:643: warning:
# alignment of `vtable for class
# boost::python::detail::held_instance<bpl_test::Derived1>'
# is greater than maximum object file alignment. Using 16.
# Could this be fixed with compiler options?
# -fhuge-objects looks interesting, but requires recompiling the C++ library.
# (what exactly does that mean?)
# -fvtable-thunks eliminates the compiler warning, but
# "import boost_python_test" still causes a crash.
ROOT=L:
BOOST_WIN="$(ROOT)\boost"
BOOST_UNIX=$(HOME)/boost
PYEXE="C:\Program files\Python\python.exe"
PYINC=-I"C:\usr\include\python1.5"
PYLIB="C:\usr\lib\libpython15.a"
STDOPTS=-ftemplate-depth-21
WARNOPTS=
OPTOPTS=-g
CPP=g++
CPPOPTS=$(STLPORTINC) $(STLPORTOPTS) -I$(BOOST_WIN) $(PYINC) \
$(STDOPTS) $(WARNOPTS) $(OPTOPTS)
LD=g++
LDOPTS=-shared
OBJ=classes.o conversions.o extension_class.o functions.o \
init_function.o module_builder.o \
objects.o types.o cross_module.o
.SUFFIXES: .o .cpp
all: libboost_python.a \
abstract.pyd \
getting_started1.pyd getting_started2.pyd \
simple_vector.pyd \
do_it_yourself_convts.pyd \
pickle1.pyd pickle2.pyd pickle3.pyd \
noncopyable_export.pyd noncopyable_import.pyd \
ivect.pyd dvect.pyd \
richcmp1.pyd richcmp2.pyd richcmp3.pyd
libboost_python.a: $(OBJ)
-del libboost_python.a
ar r libboost_python.a $(OBJ)
DLLWRAPOPTS=-s --driver-name g++ -s \
--entry _DllMainCRTStartup@12 --target=i386-mingw32
boost_python_test.pyd: $(OBJ) comprehensive.o
dllwrap $(DLLWRAPOPTS) \
--dllname boost_python_test.pyd \
--def boost_python_test.def \
$(OBJ) comprehensive.o $(PYLIB)
abstract.pyd: $(OBJ) abstract.o
dllwrap $(DLLWRAPOPTS) \
--dllname abstract.pyd \
--def abstract.def \
$(OBJ) abstract.o $(PYLIB)
getting_started1.pyd: $(OBJ) getting_started1.o
dllwrap $(DLLWRAPOPTS) \
--dllname getting_started1.pyd \
--def getting_started1.def \
$(OBJ) getting_started1.o $(PYLIB)
getting_started2.pyd: $(OBJ) getting_started2.o
dllwrap $(DLLWRAPOPTS) \
--dllname getting_started2.pyd \
--def getting_started2.def \
$(OBJ) getting_started2.o $(PYLIB)
simple_vector.pyd: $(OBJ) simple_vector.o
dllwrap $(DLLWRAPOPTS) \
--dllname simple_vector.pyd \
--def simple_vector.def \
$(OBJ) simple_vector.o $(PYLIB)
do_it_yourself_convts.pyd: $(OBJ) do_it_yourself_convts.o
dllwrap $(DLLWRAPOPTS) \
--dllname do_it_yourself_convts.pyd \
--def do_it_yourself_convts.def \
$(OBJ) do_it_yourself_convts.o $(PYLIB)
pickle1.pyd: $(OBJ) pickle1.o
dllwrap $(DLLWRAPOPTS) \
--dllname pickle1.pyd \
--def pickle1.def \
$(OBJ) pickle1.o $(PYLIB)
pickle2.pyd: $(OBJ) pickle2.o
dllwrap $(DLLWRAPOPTS) \
--dllname pickle2.pyd \
--def pickle2.def \
$(OBJ) pickle2.o $(PYLIB)
pickle3.pyd: $(OBJ) pickle3.o
dllwrap $(DLLWRAPOPTS) \
--dllname pickle3.pyd \
--def pickle3.def \
$(OBJ) pickle3.o $(PYLIB)
noncopyable_export.pyd: $(OBJ) noncopyable_export.o
dllwrap $(DLLWRAPOPTS) \
--dllname noncopyable_export.pyd \
--def noncopyable_export.def \
$(OBJ) noncopyable_export.o $(PYLIB)
noncopyable_import.pyd: $(OBJ) noncopyable_import.o
dllwrap $(DLLWRAPOPTS) \
--dllname noncopyable_import.pyd \
--def noncopyable_import.def \
$(OBJ) noncopyable_import.o $(PYLIB)
ivect.pyd: $(OBJ) ivect.o
dllwrap $(DLLWRAPOPTS) \
--dllname ivect.pyd \
--def ivect.def \
$(OBJ) ivect.o $(PYLIB)
dvect.pyd: $(OBJ) dvect.o
dllwrap $(DLLWRAPOPTS) \
--dllname dvect.pyd \
--def dvect.def \
$(OBJ) dvect.o $(PYLIB)
richcmp1.pyd: $(OBJ) richcmp1.o
dllwrap $(DLLWRAPOPTS) \
--dllname richcmp1.pyd \
--def richcmp1.def \
$(OBJ) richcmp1.o $(PYLIB)
richcmp2.pyd: $(OBJ) richcmp2.o
dllwrap $(DLLWRAPOPTS) \
--dllname richcmp2.pyd \
--def richcmp2.def \
$(OBJ) richcmp2.o $(PYLIB)
richcmp3.pyd: $(OBJ) richcmp3.o
dllwrap $(DLLWRAPOPTS) \
--dllname richcmp3.pyd \
--def richcmp3.def \
$(OBJ) richcmp3.o $(PYLIB)
.cpp.o:
$(CPP) $(CPPOPTS) -c $*.cpp
test:
# $(PYEXE) comprehensive.py
$(PYEXE) test_abstract.py
$(PYEXE) test_getting_started1.py
$(PYEXE) test_getting_started2.py
$(PYEXE) test_simple_vector.py
$(PYEXE) test_do_it_yourself_convts.py
$(PYEXE) test_pickle1.py
$(PYEXE) test_pickle2.py
$(PYEXE) test_pickle3.py
$(PYEXE) test_cross_module.py
$(PYEXE) test_richcmp1.py
$(PYEXE) test_richcmp2.py
$(PYEXE) test_richcmp3.py
clean:
-del *.o
-del *.a
-del *.pyd
-del *.pyc
softlinks:
python $(BOOST_UNIX)/libs/python/build/filemgr.py $(BOOST_UNIX) softlinks
unlink:
python $(BOOST_UNIX)/libs/python/build/filemgr.py $(BOOST_UNIX) unlink
cp:
python $(BOOST_UNIX)/libs/python/build/filemgr.py $(BOOST_UNIX) cp
rm:
python $(BOOST_UNIX)/libs/python/build/filemgr.py $(BOOST_UNIX) rm
copy:
$(PYEXE) $(BOOST_WIN)\libs\python\build\filemgr.py $(BOOST_WIN) copy
del:
$(PYEXE) $(BOOST_WIN)\libs\python\build\filemgr.py $(BOOST_WIN) del

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# Usage:
#
# Create a new empty directory anywhere (preferably not in the boost tree).
# Copy this Makefile to that new directory and rename it to "Makefile"
# Adjust the pathnames below.
#
# make softlinks Create softlinks to source code and tests
# make Compile all sources
# make test Run doctest tests
# make clean Remove all object files
# make unlink Remove softlinks
#
# Revision history:
# 12 Apr 01 new macro ROOT to simplify configuration (R.W. Grosse-Kunstleve)
# Initial version: R.W. Grosse-Kunstleve
ROOT=$(HOME)
BOOST=$(ROOT)/boost
PYEXE=/usr/local/Python-1.5.2/bin/python
PYINC=-I/usr/local/Python-1.5.2/include/python1.5
#PYEXE=/usr/local/Python-2.1/bin/python
#PYINC=-I/usr/local/Python-2.1/include/python2.1
#STLPORTINC=-I/usr/local/STLport-4.1b3/stlport
#STLPORTINC=-I/usr/local/STLport-4.1b4/stlport
#STLPORTOPTS= \
# -D__USE_STD_IOSTREAM \
# -D__STL_NO_SGI_IOSTREAMS \
# -D__STL_USE_NATIVE_STRING \
# -D__STL_NO_NEW_C_HEADERS \
# -D_RWSTD_COMPILE_INSTANTIATE=1
STLPORTINC=-I$(BOOST)/boost/compatibility/cpp_c_headers
STDOPTS=-std strict_ansi
# use -msg_display_number to obtain integer tags for -msg_disable
WARNOPTS=-msg_disable 186,450,1115
OPTOPTS=-g
CPP=cxx
CPPOPTS=$(STLPORTINC) $(STLPORTOPTS) -I$(BOOST) $(PYINC) \
$(STDOPTS) $(WARNOPTS) $(OPTOPTS)
MAKEDEP=-Em
LD=cxx
LDOPTS=-shared -expect_unresolved 'Py*' -expect_unresolved '_Py*'
#HIDDEN=-hidden
OBJ=classes.o conversions.o extension_class.o functions.o \
init_function.o module_builder.o \
objects.o types.o cross_module.o
DEPOBJ=$(OBJ) \
comprehensive.o \
abstract.o \
getting_started1.o getting_started2.o \
simple_vector.o \
do_it_yourself_convts.o \
pickle1.o pickle2.o pickle3.o \
noncopyable_export.o noncopyable_import.o \
ivect.o dvect.o \
richcmp1.o richcmp2.o richcmp3.o
.SUFFIXES: .o .cpp
all: libboost_python.a \
boost_python_test.so \
abstract.so \
getting_started1.so getting_started2.so \
simple_vector.so \
do_it_yourself_convts.so \
pickle1.so pickle2.so pickle3.so \
noncopyable_export.so noncopyable_import.so \
ivect.so dvect.so \
richcmp1.so richcmp2.so richcmp3.so
libboost_python.a: $(OBJ)
rm -f libboost_python.a
cd cxx_repository; \
ls -1 > ../libboost_python.a.input; \
ar r ../libboost_python.a -input ../libboost_python.a.input
rm -f libboost_python.a.input
ar r libboost_python.a $(OBJ)
boost_python_test.so: $(OBJ) comprehensive.o
$(LD) $(LDOPTS) $(OBJ) comprehensive.o -o boost_python_test.so -lm
abstract.so: $(OBJ) abstract.o
$(LD) $(LDOPTS) $(OBJ) abstract.o -o abstract.so
getting_started1.so: $(OBJ) getting_started1.o
$(LD) $(LDOPTS) $(OBJ) getting_started1.o -o getting_started1.so
getting_started2.so: $(OBJ) getting_started2.o
$(LD) $(LDOPTS) $(OBJ) getting_started2.o -o getting_started2.so
simple_vector.so: $(OBJ) simple_vector.o
$(LD) $(LDOPTS) $(OBJ) simple_vector.o -o simple_vector.so
do_it_yourself_convts.so: $(OBJ) do_it_yourself_convts.o
$(LD) $(LDOPTS) $(OBJ) do_it_yourself_convts.o -o do_it_yourself_convts.so
pickle1.so: $(OBJ) pickle1.o
$(LD) $(LDOPTS) $(OBJ) pickle1.o -o pickle1.so
pickle2.so: $(OBJ) pickle2.o
$(LD) $(LDOPTS) $(OBJ) pickle2.o -o pickle2.so
pickle3.so: $(OBJ) pickle3.o
$(LD) $(LDOPTS) $(OBJ) pickle3.o -o pickle3.so
noncopyable_export.so: $(OBJ) noncopyable_export.o
$(LD) $(LDOPTS) $(OBJ) $(HIDDEN) \
noncopyable_export.o -o noncopyable_export.so
noncopyable_import.so: $(OBJ) noncopyable_import.o
$(LD) $(LDOPTS) $(OBJ) $(HIDDEN) \
noncopyable_import.o -o noncopyable_import.so
ivect.so: $(OBJ) ivect.o
$(LD) $(LDOPTS) $(OBJ) $(HIDDEN) ivect.o -o ivect.so
dvect.so: $(OBJ) dvect.o
$(LD) $(LDOPTS) $(OBJ) $(HIDDEN) dvect.o -o dvect.so
richcmp1.so: $(OBJ) richcmp1.o
$(LD) $(LDOPTS) $(OBJ) richcmp1.o -o richcmp1.so
richcmp2.so: $(OBJ) richcmp2.o
$(LD) $(LDOPTS) $(OBJ) richcmp2.o -o richcmp2.so
richcmp3.so: $(OBJ) richcmp3.o
$(LD) $(LDOPTS) $(OBJ) richcmp3.o -o richcmp3.so
.cpp.o:
$(CPP) $(CPPOPTS) -c $*.cpp
test:
$(PYEXE) comprehensive.py
$(PYEXE) test_abstract.py
$(PYEXE) test_getting_started1.py
$(PYEXE) test_getting_started2.py
$(PYEXE) test_simple_vector.py
$(PYEXE) test_do_it_yourself_convts.py
$(PYEXE) test_pickle1.py
$(PYEXE) test_pickle2.py
$(PYEXE) test_pickle3.py
$(PYEXE) test_cross_module.py
$(PYEXE) test_richcmp1.py
$(PYEXE) test_richcmp2.py
$(PYEXE) test_richcmp3.py
clean:
rm -f $(OBJ) libboost_python.a libboost_python.a.input
rm -f comprehensive.o boost_python_test.so
rm -f abstract.o abstract.so
rm -f getting_started1.o getting_started1.so
rm -f getting_started2.o getting_started2.so
rm -f simple_vector.o simple_vector.so
rm -f do_it_yourself_convts.o do_it_yourself_convts.so
rm -f pickle1.o pickle1.so
rm -f pickle2.o pickle2.so
rm -f pickle3.o pickle3.so
rm -f noncopyable_export.o noncopyable_export.so
rm -f noncopyable_import.o noncopyable_import.so
rm -f ivect.o ivect.so
rm -f dvect.o dvect.so
rm -f richcmp1.o richcmp1.so
rm -f richcmp2.o richcmp2.so
rm -f richcmp3.o richcmp3.so
rm -f so_locations *.pyc
rm -rf cxx_repository
softlinks:
$(PYEXE) $(BOOST)/libs/python/build/filemgr.py $(BOOST) softlinks
unlink:
$(PYEXE) $(BOOST)/libs/python/build/filemgr.py $(BOOST) unlink
cp:
$(PYEXE) $(BOOST)/libs/python/build/filemgr.py $(BOOST) cp
rm:
$(PYEXE) $(BOOST)/libs/python/build/filemgr.py $(BOOST) rm
depend:
@ cat Makefile.nodepend; \
for obj in $(DEPOBJ); \
do \
bn=`echo "$$obj" | cut -d. -f1`; \
$(CPP) $(CPPOPTS) $(MAKEDEP) "$$bn".cpp; \
done

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# Usage:
#
# make copy Copy the sources and tests
# make Compile all sources
# make test Run doctest tests
# make clean Remove all object files
# make del Remove the sources and tests
#
# Revision history:
# 12 Apr 01 new macro ROOT to simplify configuration (R.W. Grosse-Kunstleve)
# Initial version: R.W. Grosse-Kunstleve
ROOT=L:
BOOST_WIN="$(ROOT)\boost"
BOOST_UNIX=$(HOME)/boost
PYEXE="C:\Program files\Python\python.exe"
PYINC=/I"C:\Program files\Python\include"
PYLIB="C:\Program files\Python\libs\python15.lib"
#PYEXE="C:\Python21\python.exe"
#PYINC=/I"C:\Python21\include"
#PYLIB="C:\Python21\libs\python21.lib"
STDOPTS=/nologo /MD /GR /GX /Zm200
WARNOPTS=
OPTOPTS=
CPP=cl.exe
CPPOPTS=$(STLPORTINC) $(STLPORTOPTS) /I$(BOOST_WIN) $(PYINC) \
$(STDOPTS) $(WARNOPTS) $(OPTOPTS)
LD=link.exe
LDOPTS=/nologo /dll /incremental:no
OBJ=classes.obj conversions.obj extension_class.obj functions.obj \
init_function.obj module_builder.obj \
objects.obj types.obj cross_module.obj
.SUFFIXES: .obj .cpp
all: boost_python.lib \
boost_python_test.pyd \
abstract.pyd \
getting_started1.pyd getting_started2.pyd \
simple_vector.pyd \
do_it_yourself_convts.pyd \
pickle1.pyd pickle2.pyd pickle3.pyd \
noncopyable_export.pyd noncopyable_import.pyd \
ivect.pyd dvect.pyd \
richcmp1.pyd richcmp2.pyd richcmp3.pyd
boost_python.lib: $(OBJ)
$(LD) -lib /nologo /out:boost_python.lib $(OBJ)
boost_python_test.pyd: $(OBJ) comprehensive.obj
$(LD) $(LDOPTS) $(OBJ) comprehensive.obj $(PYLIB) /export:initboost_python_test /out:"boost_python_test.pyd"
abstract.pyd: $(OBJ) abstract.obj
$(LD) $(LDOPTS) $(OBJ) abstract.obj $(PYLIB) /export:initabstract /out:"abstract.pyd"
getting_started1.pyd: $(OBJ) getting_started1.obj
$(LD) $(LDOPTS) $(OBJ) getting_started1.obj $(PYLIB) /export:initgetting_started1 /out:"getting_started1.pyd"
getting_started2.pyd: $(OBJ) getting_started2.obj
$(LD) $(LDOPTS) $(OBJ) getting_started2.obj $(PYLIB) /export:initgetting_started2 /out:"getting_started2.pyd"
simple_vector.pyd: $(OBJ) simple_vector.obj
$(LD) $(LDOPTS) $(OBJ) simple_vector.obj $(PYLIB) /export:initsimple_vector /out:"simple_vector.pyd"
do_it_yourself_convts.pyd: $(OBJ) do_it_yourself_convts.obj
$(LD) $(LDOPTS) $(OBJ) do_it_yourself_convts.obj $(PYLIB) /export:initdo_it_yourself_convts /out:"do_it_yourself_convts.pyd"
pickle1.pyd: $(OBJ) pickle1.obj
$(LD) $(LDOPTS) $(OBJ) pickle1.obj $(PYLIB) /export:initpickle1 /out:"pickle1.pyd"
pickle2.pyd: $(OBJ) pickle2.obj
$(LD) $(LDOPTS) $(OBJ) pickle2.obj $(PYLIB) /export:initpickle2 /out:"pickle2.pyd"
pickle3.pyd: $(OBJ) pickle3.obj
$(LD) $(LDOPTS) $(OBJ) pickle3.obj $(PYLIB) /export:initpickle3 /out:"pickle3.pyd"
noncopyable_export.pyd: $(OBJ) noncopyable_export.obj
$(LD) $(LDOPTS) $(OBJ) noncopyable_export.obj $(PYLIB) /export:initnoncopyable_export /out:"noncopyable_export.pyd"
noncopyable_import.pyd: $(OBJ) noncopyable_import.obj
$(LD) $(LDOPTS) $(OBJ) noncopyable_import.obj $(PYLIB) /export:initnoncopyable_import /out:"noncopyable_import.pyd"
ivect.pyd: $(OBJ) ivect.obj
$(LD) $(LDOPTS) $(OBJ) ivect.obj $(PYLIB) /export:initivect /out:"ivect.pyd"
dvect.pyd: $(OBJ) dvect.obj
$(LD) $(LDOPTS) $(OBJ) dvect.obj $(PYLIB) /export:initdvect /out:"dvect.pyd"
richcmp1.pyd: $(OBJ) richcmp1.obj
$(LD) $(LDOPTS) $(OBJ) richcmp1.obj $(PYLIB) /export:initrichcmp1 /out:"richcmp1.pyd"
richcmp2.pyd: $(OBJ) richcmp2.obj
$(LD) $(LDOPTS) $(OBJ) richcmp2.obj $(PYLIB) /export:initrichcmp2 /out:"richcmp2.pyd"
richcmp3.pyd: $(OBJ) richcmp3.obj
$(LD) $(LDOPTS) $(OBJ) richcmp3.obj $(PYLIB) /export:initrichcmp3 /out:"richcmp3.pyd"
.cpp.obj:
$(CPP) $(CPPOPTS) /c $*.cpp
test:
$(PYEXE) comprehensive.py --broken-auto-ptr
$(PYEXE) test_abstract.py
$(PYEXE) test_getting_started1.py
$(PYEXE) test_getting_started2.py
$(PYEXE) test_simple_vector.py
$(PYEXE) test_do_it_yourself_convts.py
$(PYEXE) test_pickle1.py
$(PYEXE) test_pickle2.py
$(PYEXE) test_pickle3.py
$(PYEXE) test_cross_module.py --broken-auto-ptr
$(PYEXE) test_richcmp1.py
$(PYEXE) test_richcmp2.py
$(PYEXE) test_richcmp3.py
clean:
-del *.obj
-del *.lib
-del *.exp
-del *.idb
-del *.pyd
-del *.pyc
softlinks:
python $(BOOST_UNIX)/libs/python/build/filemgr.py $(BOOST_UNIX) softlinks
unlink:
python $(BOOST_UNIX)/libs/python/build/filemgr.py $(BOOST_UNIX) unlink
cp:
python $(BOOST_UNIX)/libs/python/build/filemgr.py $(BOOST_UNIX) cp
rm:
python $(BOOST_UNIX)/libs/python/build/filemgr.py $(BOOST_UNIX) rm
copy:
$(PYEXE) $(BOOST_WIN)\libs\python\build\filemgr.py $(BOOST_WIN) copy
del:
$(PYEXE) $(BOOST_WIN)\libs\python\build\filemgr.py $(BOOST_WIN) del

View File

@@ -1,66 +0,0 @@
# Copyright (c) 2006 Joel de Guzman
# Copyright (c) 2015 Stefan Seefeld
#
# Distributed under the Boost Software License, Version 1.0. (See accompanying
# file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
import boostbook ;
import quickbook ;
import docutils ;
import os ;
path-constant here : . ;
path-constant images : html/images ;
project python/doc
: requirements
-<xsl:param>boost.defaults=Boost
<format>html:<xsl:param>boost.defaults=none
<format>html:<xsl:param>toc.max.depth=3
<format>html:<xsl:param>toc.section.depth=2
<format>html:<xsl:param>chunk.section.depth=1
;
make numpy : numpy/index.rst : @sphinx-build ;
if [ os.name ] = NT
{
actions sphinx-build { chdir "$(>:D)" && make clean && make html}
}
else
{
actions sphinx-build { make -C "$(>:D)" clean html}
}
boostbook python : python.qbk
: <format>html:<name>$(here)/html
<format>html:<xsl:param>generate.toc="library nop; chapter toc; section toc;"
<format>html:<xsl:param>html.stylesheet=boostbook.css
<format>html:<xsl:param>boost.image.src=images/boost.png
<format>html:<xsl:param>boost.graphics.root=images/
;
boostbook tutorial : tutorial.qbk
: <format>html:<name>$(here)/html/tutorial
<format>html:<xsl:param>html.stylesheet=../boostbook.css
<format>html:<xsl:param>boost.image.src=../images/boost.png
<format>html:<xsl:param>boost.graphics.root=../images/
;
boostbook reference : reference.qbk
: <format>html:<name>$(here)/html/reference
<format>html:<xsl:param>html.stylesheet=../boostbook.css
<format>html:<xsl:param>boost.image.src=../images/boost.png
<format>html:<xsl:param>boost.graphics.root=../images/
;
html article : article.rst
: <location>html
<docutils-html>"--link-stylesheet --traceback --trim-footnote-reference-space --footnote-references=superscript --stylesheet=rst.css"
;
###############################################################################
alias boostdoc ;
explicit boostdoc ;
alias boostrelease : python tutorial reference numpy article ;
explicit boostrelease ;

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@@ -1,947 +0,0 @@
+++++++++++++++++++++++++++++++++++++++++++
Building Hybrid Systems with Boost.Python
+++++++++++++++++++++++++++++++++++++++++++
:Author: David Abrahams
:Contact: dave@boost-consulting.com
:organization: `Boost Consulting`_
:date: 2003-05-14
:Author: Ralf W. Grosse-Kunstleve
:copyright: Copyright David Abrahams and Ralf W. Grosse-Kunstleve 2003. All rights reserved
.. contents:: Table of Contents
.. _`Boost Consulting`: http://www.boost-consulting.com
==========
Abstract
==========
Boost.Python is an open source C++ library which provides a concise
IDL-like interface for binding C++ classes and functions to
Python. Leveraging the full power of C++ compile-time introspection
and of recently developed metaprogramming techniques, this is achieved
entirely in pure C++, without introducing a new syntax.
Boost.Python's rich set of features and high-level interface make it
possible to engineer packages from the ground up as hybrid systems,
giving programmers easy and coherent access to both the efficient
compile-time polymorphism of C++ and the extremely convenient run-time
polymorphism of Python.
==============
Introduction
==============
Python and C++ are in many ways as different as two languages could
be: while C++ is usually compiled to machine-code, Python is
interpreted. Python's dynamic type system is often cited as the
foundation of its flexibility, while in C++ static typing is the
cornerstone of its efficiency. C++ has an intricate and difficult
compile-time meta-language, while in Python, practically everything
happens at runtime.
Yet for many programmers, these very differences mean that Python and
C++ complement one another perfectly. Performance bottlenecks in
Python programs can be rewritten in C++ for maximal speed, and
authors of powerful C++ libraries choose Python as a middleware
language for its flexible system integration capabilities.
Furthermore, the surface differences mask some strong similarities:
* 'C'-family control structures (if, while, for...)
* Support for object-orientation, functional programming, and generic
programming (these are both *multi-paradigm* programming languages.)
* Comprehensive operator overloading facilities, recognizing the
importance of syntactic variability for readability and
expressivity.
* High-level concepts such as collections and iterators.
* High-level encapsulation facilities (C++: namespaces, Python: modules)
to support the design of re-usable libraries.
* Exception-handling for effective management of error conditions.
* C++ idioms in common use, such as handle/body classes and
reference-counted smart pointers mirror Python reference semantics.
Given Python's rich 'C' interoperability API, it should in principle
be possible to expose C++ type and function interfaces to Python with
an analogous interface to their C++ counterparts. However, the
facilities provided by Python alone for integration with C++ are
relatively meager. Compared to C++ and Python, 'C' has only very
rudimentary abstraction facilities, and support for exception-handling
is completely missing. 'C' extension module writers are required to
manually manage Python reference counts, which is both annoyingly
tedious and extremely error-prone. Traditional extension modules also
tend to contain a great deal of boilerplate code repetition which
makes them difficult to maintain, especially when wrapping an evolving
API.
These limitations have lead to the development of a variety of wrapping
systems. SWIG_ is probably the most popular package for the
integration of C/C++ and Python. A more recent development is SIP_,
which was specifically designed for interfacing Python with the Qt_
graphical user interface library. Both SWIG and SIP introduce their
own specialized languages for customizing inter-language bindings.
This has certain advantages, but having to deal with three different
languages (Python, C/C++ and the interface language) also introduces
practical and mental difficulties. The CXX_ package demonstrates an
interesting alternative. It shows that at least some parts of
Python's 'C' API can be wrapped and presented through a much more
user-friendly C++ interface. However, unlike SWIG and SIP, CXX does
not include support for wrapping C++ classes as new Python types.
The features and goals of Boost.Python_ overlap significantly with
many of these other systems. That said, Boost.Python attempts to
maximize convenience and flexibility without introducing a separate
wrapping language. Instead, it presents the user with a high-level
C++ interface for wrapping C++ classes and functions, managing much of
the complexity behind-the-scenes with static metaprogramming.
Boost.Python also goes beyond the scope of earlier systems by
providing:
* Support for C++ virtual functions that can be overridden in Python.
* Comprehensive lifetime management facilities for low-level C++
pointers and references.
* Support for organizing extensions as Python packages,
with a central registry for inter-language type conversions.
* A safe and convenient mechanism for tying into Python's powerful
serialization engine (pickle).
* Coherence with the rules for handling C++ lvalues and rvalues that
can only come from a deep understanding of both the Python and C++
type systems.
The key insight that sparked the development of Boost.Python is that
much of the boilerplate code in traditional extension modules could be
eliminated using C++ compile-time introspection. Each argument of a
wrapped C++ function must be extracted from a Python object using a
procedure that depends on the argument type. Similarly the function's
return type determines how the return value will be converted from C++
to Python. Of course argument and return types are part of each
function's type, and this is exactly the source from which
Boost.Python deduces most of the information required.
This approach leads to *user guided wrapping*: as much information is
extracted directly from the source code to be wrapped as is possible
within the framework of pure C++, and some additional information is
supplied explicitly by the user. Mostly the guidance is mechanical
and little real intervention is required. Because the interface
specification is written in the same full-featured language as the
code being exposed, the user has unprecedented power available when
she does need to take control.
.. _Python: http://www.python.org/
.. _SWIG: http://www.swig.org/
.. _SIP: http://www.riverbankcomputing.co.uk/sip/index.php
.. _Qt: http://www.trolltech.com/
.. _CXX: http://cxx.sourceforge.net/
.. _Boost.Python: http://www.boost.org/libs/python/doc
===========================
Boost.Python Design Goals
===========================
The primary goal of Boost.Python is to allow users to expose C++
classes and functions to Python using nothing more than a C++
compiler. In broad strokes, the user experience should be one of
directly manipulating C++ objects from Python.
However, it's also important not to translate all interfaces *too*
literally: the idioms of each language must be respected. For
example, though C++ and Python both have an iterator concept, they are
expressed very differently. Boost.Python has to be able to bridge the
interface gap.
It must be possible to insulate Python users from crashes resulting
from trivial misuses of C++ interfaces, such as accessing
already-deleted objects. By the same token the library should
insulate C++ users from low-level Python 'C' API, replacing
error-prone 'C' interfaces like manual reference-count management and
raw ``PyObject`` pointers with more-robust alternatives.
Support for component-based development is crucial, so that C++ types
exposed in one extension module can be passed to functions exposed in
another without loss of crucial information like C++ inheritance
relationships.
Finally, all wrapping must be *non-intrusive*, without modifying or
even seeing the original C++ source code. Existing C++ libraries have
to be wrappable by third parties who only have access to header files
and binaries.
==========================
Hello Boost.Python World
==========================
And now for a preview of Boost.Python, and how it improves on the raw
facilities offered by Python. Here's a function we might want to
expose::
char const* greet(unsigned x)
{
static char const* const msgs[] = { "hello", "Boost.Python", "world!" };
if (x > 2)
throw std::range_error("greet: index out of range");
return msgs[x];
}
To wrap this function in standard C++ using the Python 'C' API, we'd
need something like this::
extern "C" // all Python interactions use 'C' linkage and calling convention
{
// Wrapper to handle argument/result conversion and checking
PyObject* greet_wrap(PyObject* args, PyObject * keywords)
{
int x;
if (PyArg_ParseTuple(args, "i", &x)) // extract/check arguments
{
char const* result = greet(x); // invoke wrapped function
return PyString_FromString(result); // convert result to Python
}
return 0; // error occurred
}
// Table of wrapped functions to be exposed by the module
static PyMethodDef methods[] = {
{ "greet", greet_wrap, METH_VARARGS, "return one of 3 parts of a greeting" }
, { NULL, NULL, 0, NULL } // sentinel
};
// module initialization function
DL_EXPORT init_hello()
{
(void) Py_InitModule("hello", methods); // add the methods to the module
}
}
Now here's the wrapping code we'd use to expose it with Boost.Python::
#include <boost/python.hpp>
using namespace boost::python;
BOOST_PYTHON_MODULE(hello)
{
def("greet", greet, "return one of 3 parts of a greeting");
}
and here it is in action::
>>> import hello
>>> for x in range(3):
... print hello.greet(x)
...
hello
Boost.Python
world!
Aside from the fact that the 'C' API version is much more verbose,
it's worth noting a few things that it doesn't handle correctly:
* The original function accepts an unsigned integer, and the Python
'C' API only gives us a way of extracting signed integers. The
Boost.Python version will raise a Python exception if we try to pass
a negative number to ``hello.greet``, but the other one will proceed
to do whatever the C++ implementation does when converting an
negative integer to unsigned (usually wrapping to some very large
number), and pass the incorrect translation on to the wrapped
function.
* That brings us to the second problem: if the C++ ``greet()``
function is called with a number greater than 2, it will throw an
exception. Typically, if a C++ exception propagates across the
boundary with code generated by a 'C' compiler, it will cause a
crash. As you can see in the first version, there's no C++
scaffolding there to prevent this from happening. Functions wrapped
by Boost.Python automatically include an exception-handling layer
which protects Python users by translating unhandled C++ exceptions
into a corresponding Python exception.
* A slightly more-subtle limitation is that the argument conversion
used in the Python 'C' API case can only get that integer ``x`` in
*one way*. PyArg_ParseTuple can't convert Python ``long`` objects
(arbitrary-precision integers) which happen to fit in an ``unsigned
int`` but not in a ``signed long``, nor will it ever handle a
wrapped C++ class with a user-defined implicit ``operator unsigned
int()`` conversion. Boost.Python's dynamic type conversion
registry allows users to add arbitrary conversion methods.
==================
Library Overview
==================
This section outlines some of the library's major features. Except as
neccessary to avoid confusion, details of library implementation are
omitted.
------------------
Exposing Classes
------------------
C++ classes and structs are exposed with a similarly-terse interface.
Given::
struct World
{
void set(std::string msg) { this->msg = msg; }
std::string greet() { return msg; }
std::string msg;
};
The following code will expose it in our extension module::
#include <boost/python.hpp>
BOOST_PYTHON_MODULE(hello)
{
class_<World>("World")
.def("greet", &World::greet)
.def("set", &World::set)
;
}
Although this code has a certain pythonic familiarity, people
sometimes find the syntax bit confusing because it doesn't look like
most of the C++ code they're used to. All the same, this is just
standard C++. Because of their flexible syntax and operator
overloading, C++ and Python are great for defining domain-specific
(sub)languages
(DSLs), and that's what we've done in Boost.Python. To break it down::
class_<World>("World")
constructs an unnamed object of type ``class_<World>`` and passes
``"World"`` to its constructor. This creates a new-style Python class
called ``World`` in the extension module, and associates it with the
C++ type ``World`` in the Boost.Python type conversion registry. We
might have also written::
class_<World> w("World");
but that would've been more verbose, since we'd have to name ``w``
again to invoke its ``def()`` member function::
w.def("greet", &World::greet)
There's nothing special about the location of the dot for member
access in the original example: C++ allows any amount of whitespace on
either side of a token, and placing the dot at the beginning of each
line allows us to chain as many successive calls to member functions
as we like with a uniform syntax. The other key fact that allows
chaining is that ``class_<>`` member functions all return a reference
to ``*this``.
So the example is equivalent to::
class_<World> w("World");
w.def("greet", &World::greet);
w.def("set", &World::set);
It's occasionally useful to be able to break down the components of a
Boost.Python class wrapper in this way, but the rest of this article
will stick to the terse syntax.
For completeness, here's the wrapped class in use: ::
>>> import hello
>>> planet = hello.World()
>>> planet.set('howdy')
>>> planet.greet()
'howdy'
Constructors
============
Since our ``World`` class is just a plain ``struct``, it has an
implicit no-argument (nullary) constructor. Boost.Python exposes the
nullary constructor by default, which is why we were able to write: ::
>>> planet = hello.World()
However, well-designed classes in any language may require constructor
arguments in order to establish their invariants. Unlike Python,
where ``__init__`` is just a specially-named method, In C++
constructors cannot be handled like ordinary member functions. In
particular, we can't take their address: ``&World::World`` is an
error. The library provides a different interface for specifying
constructors. Given::
struct World
{
World(std::string msg); // added constructor
...
we can modify our wrapping code as follows::
class_<World>("World", init<std::string>())
...
of course, a C++ class may have additional constructors, and we can
expose those as well by passing more instances of ``init<...>`` to
``def()``::
class_<World>("World", init<std::string>())
.def(init<double, double>())
...
Boost.Python allows wrapped functions, member functions, and
constructors to be overloaded to mirror C++ overloading.
Data Members and Properties
===========================
Any publicly-accessible data members in a C++ class can be easily
exposed as either ``readonly`` or ``readwrite`` attributes::
class_<World>("World", init<std::string>())
.def_readonly("msg", &World::msg)
...
and can be used directly in Python: ::
>>> planet = hello.World('howdy')
>>> planet.msg
'howdy'
This does *not* result in adding attributes to the ``World`` instance
``__dict__``, which can result in substantial memory savings when
wrapping large data structures. In fact, no instance ``__dict__``
will be created at all unless attributes are explicitly added from
Python. Boost.Python owes this capability to the new Python 2.2 type
system, in particular the descriptor interface and ``property`` type.
In C++, publicly-accessible data members are considered a sign of poor
design because they break encapsulation, and style guides usually
dictate the use of "getter" and "setter" functions instead. In
Python, however, ``__getattr__``, ``__setattr__``, and since 2.2,
``property`` mean that attribute access is just one more
well-encapsulated syntactic tool at the programmer's disposal.
Boost.Python bridges this idiomatic gap by making Python ``property``
creation directly available to users. If ``msg`` were private, we
could still expose it as attribute in Python as follows::
class_<World>("World", init<std::string>())
.add_property("msg", &World::greet, &World::set)
...
The example above mirrors the familiar usage of properties in Python
2.2+: ::
>>> class World(object):
... __init__(self, msg):
... self.__msg = msg
... def greet(self):
... return self.__msg
... def set(self, msg):
... self.__msg = msg
... msg = property(greet, set)
Operator Overloading
====================
The ability to write arithmetic operators for user-defined types has
been a major factor in the success of both languages for numerical
computation, and the success of packages like NumPy_ attests to the
power of exposing operators in extension modules. Boost.Python
provides a concise mechanism for wrapping operator overloads. The
example below shows a fragment from a wrapper for the Boost rational
number library::
class_<rational<int> >("rational_int")
.def(init<int, int>()) // constructor, e.g. rational_int(3,4)
.def("numerator", &rational<int>::numerator)
.def("denominator", &rational<int>::denominator)
.def(-self) // __neg__ (unary minus)
.def(self + self) // __add__ (homogeneous)
.def(self * self) // __mul__
.def(self + int()) // __add__ (heterogenous)
.def(int() + self) // __radd__
...
The magic is performed using a simplified application of "expression
templates" [VELD1995]_, a technique originally developed for
optimization of high-performance matrix algebra expressions. The
essence is that instead of performing the computation immediately,
operators are overloaded to construct a type *representing* the
computation. In matrix algebra, dramatic optimizations are often
available when the structure of an entire expression can be taken into
account, rather than evaluating each operation "greedily".
Boost.Python uses the same technique to build an appropriate Python
method object based on expressions involving ``self``.
.. _NumPy: http://www.pfdubois.com/numpy/
Inheritance
===========
C++ inheritance relationships can be represented to Boost.Python by adding
an optional ``bases<...>`` argument to the ``class_<...>`` template
parameter list as follows::
class_<Derived, bases<Base1,Base2> >("Derived")
...
This has two effects:
1. When the ``class_<...>`` is created, Python type objects
corresponding to ``Base1`` and ``Base2`` are looked up in
Boost.Python's registry, and are used as bases for the new Python
``Derived`` type object, so methods exposed for the Python ``Base1``
and ``Base2`` types are automatically members of the ``Derived``
type. Because the registry is global, this works correctly even if
``Derived`` is exposed in a different module from either of its
bases.
2. C++ conversions from ``Derived`` to its bases are added to the
Boost.Python registry. Thus wrapped C++ methods expecting (a
pointer or reference to) an object of either base type can be
called with an object wrapping a ``Derived`` instance. Wrapped
member functions of class ``T`` are treated as though they have an
implicit first argument of ``T&``, so these conversions are
neccessary to allow the base class methods to be called for derived
objects.
Of course it's possible to derive new Python classes from wrapped C++
class instances. Because Boost.Python uses the new-style class
system, that works very much as for the Python built-in types. There
is one significant detail in which it differs: the built-in types
generally establish their invariants in their ``__new__`` function, so
that derived classes do not need to call ``__init__`` on the base
class before invoking its methods : ::
>>> class L(list):
... def __init__(self):
... pass
...
>>> L().reverse()
>>>
Because C++ object construction is a one-step operation, C++ instance
data cannot be constructed until the arguments are available, in the
``__init__`` function: ::
>>> class D(SomeBoostPythonClass):
... def __init__(self):
... pass
...
>>> D().some_boost_python_method()
Traceback (most recent call last):
File "<stdin>", line 1, in ?
TypeError: bad argument type for built-in operation
This happened because Boost.Python couldn't find instance data of type
``SomeBoostPythonClass`` within the ``D`` instance; ``D``'s ``__init__``
function masked construction of the base class. It could be corrected
by either removing ``D``'s ``__init__`` function or having it call
``SomeBoostPythonClass.__init__(...)`` explicitly.
Virtual Functions
=================
Deriving new types in Python from extension classes is not very
interesting unless they can be used polymorphically from C++. In
other words, Python method implementations should appear to override
the implementation of C++ virtual functions when called *through base
class pointers/references from C++*. Since the only way to alter the
behavior of a virtual function is to override it in a derived class,
the user must build a special derived class to dispatch a polymorphic
class' virtual functions::
//
// interface to wrap:
//
class Base
{
public:
virtual int f(std::string x) { return 42; }
virtual ~Base();
};
int calls_f(Base const& b, std::string x) { return b.f(x); }
//
// Wrapping Code
//
// Dispatcher class
struct BaseWrap : Base
{
// Store a pointer to the Python object
BaseWrap(PyObject* self_) : self(self_) {}
PyObject* self;
// Default implementation, for when f is not overridden
int f_default(std::string x) { return this->Base::f(x); }
// Dispatch implementation
int f(std::string x) { return call_method<int>(self, "f", x); }
};
...
def("calls_f", calls_f);
class_<Base, BaseWrap>("Base")
.def("f", &Base::f, &BaseWrap::f_default)
;
Now here's some Python code which demonstrates: ::
>>> class Derived(Base):
... def f(self, s):
... return len(s)
...
>>> calls_f(Base(), 'foo')
42
>>> calls_f(Derived(), 'forty-two')
9
Things to notice about the dispatcher class:
* The key element which allows overriding in Python is the
``call_method`` invocation, which uses the same global type
conversion registry as the C++ function wrapping does to convert its
arguments from C++ to Python and its return type from Python to C++.
* Any constructor signatures you wish to wrap must be replicated with
an initial ``PyObject*`` argument
* The dispatcher must store this argument so that it can be used to
invoke ``call_method``
* The ``f_default`` member function is needed when the function being
exposed is not pure virtual; there's no other way ``Base::f`` can be
called on an object of type ``BaseWrap``, since it overrides ``f``.
Deeper Reflection on the Horizon?
=================================
Admittedly, this formula is tedious to repeat, especially on a project
with many polymorphic classes. That it is neccessary reflects some
limitations in C++'s compile-time introspection capabilities: there's
no way to enumerate the members of a class and find out which are
virtual functions. At least one very promising project has been
started to write a front-end which can generate these dispatchers (and
other wrapping code) automatically from C++ headers.
Pyste_ is being developed by Bruno da Silva de Oliveira. It builds on
GCC_XML_, which generates an XML version of GCC's internal program
representation. Since GCC is a highly-conformant C++ compiler, this
ensures correct handling of the most-sophisticated template code and
full access to the underlying type system. In keeping with the
Boost.Python philosophy, a Pyste interface description is neither
intrusive on the code being wrapped, nor expressed in some unfamiliar
language: instead it is a 100% pure Python script. If Pyste is
successful it will mark a move away from wrapping everything directly
in C++ for many of our users. It will also allow us the choice to
shift some of the metaprogram code from C++ to Python. We expect that
soon, not only our users but the Boost.Python developers themselves
will be "thinking hybrid" about their own code.
.. _`GCC_XML`: http://www.gccxml.org/HTML/Index.html
.. _`Pyste`: http://www.boost.org/libs/python/pyste
---------------
Serialization
---------------
*Serialization* is the process of converting objects in memory to a
form that can be stored on disk or sent over a network connection. The
serialized object (most often a plain string) can be retrieved and
converted back to the original object. A good serialization system will
automatically convert entire object hierarchies. Python's standard
``pickle`` module is just such a system. It leverages the language's strong
runtime introspection facilities for serializing practically arbitrary
user-defined objects. With a few simple and unintrusive provisions this
powerful machinery can be extended to also work for wrapped C++ objects.
Here is an example::
#include <string>
struct World
{
World(std::string a_msg) : msg(a_msg) {}
std::string greet() const { return msg; }
std::string msg;
};
#include <boost/python.hpp>
using namespace boost::python;
struct World_picklers : pickle_suite
{
static tuple
getinitargs(World const& w) { return make_tuple(w.greet()); }
};
BOOST_PYTHON_MODULE(hello)
{
class_<World>("World", init<std::string>())
.def("greet", &World::greet)
.def_pickle(World_picklers())
;
}
Now let's create a ``World`` object and put it to rest on disk::
>>> import hello
>>> import pickle
>>> a_world = hello.World("howdy")
>>> pickle.dump(a_world, open("my_world", "w"))
In a potentially *different script* on a potentially *different
computer* with a potentially *different operating system*::
>>> import pickle
>>> resurrected_world = pickle.load(open("my_world", "r"))
>>> resurrected_world.greet()
'howdy'
Of course the ``cPickle`` module can also be used for faster
processing.
Boost.Python's ``pickle_suite`` fully supports the ``pickle`` protocol
defined in the standard Python documentation. Like a __getinitargs__
function in Python, the pickle_suite's getinitargs() is responsible for
creating the argument tuple that will be use to reconstruct the pickled
object. The other elements of the Python pickling protocol,
__getstate__ and __setstate__ can be optionally provided via C++
getstate and setstate functions. C++'s static type system allows the
library to ensure at compile-time that nonsensical combinations of
functions (e.g. getstate without setstate) are not used.
Enabling serialization of more complex C++ objects requires a little
more work than is shown in the example above. Fortunately the
``object`` interface (see next section) greatly helps in keeping the
code manageable.
------------------
Object interface
------------------
Experienced 'C' language extension module authors will be familiar
with the ubiquitous ``PyObject*``, manual reference-counting, and the
need to remember which API calls return "new" (owned) references or
"borrowed" (raw) references. These constraints are not just
cumbersome but also a major source of errors, especially in the
presence of exceptions.
Boost.Python provides a class ``object`` which automates reference
counting and provides conversion to Python from C++ objects of
arbitrary type. This significantly reduces the learning effort for
prospective extension module writers.
Creating an ``object`` from any other type is extremely simple::
object s("hello, world"); // s manages a Python string
``object`` has templated interactions with all other types, with
automatic to-python conversions. It happens so naturally that it's
easily overlooked::
object ten_Os = 10 * s[4]; // -> "oooooooooo"
In the example above, ``4`` and ``10`` are converted to Python objects
before the indexing and multiplication operations are invoked.
The ``extract<T>`` class template can be used to convert Python objects
to C++ types::
double x = extract<double>(o);
If a conversion in either direction cannot be performed, an
appropriate exception is thrown at runtime.
The ``object`` type is accompanied by a set of derived types
that mirror the Python built-in types such as ``list``, ``dict``,
``tuple``, etc. as much as possible. This enables convenient
manipulation of these high-level types from C++::
dict d;
d["some"] = "thing";
d["lucky_number"] = 13;
list l = d.keys();
This almost looks and works like regular Python code, but it is pure
C++. Of course we can wrap C++ functions which accept or return
``object`` instances.
=================
Thinking hybrid
=================
Because of the practical and mental difficulties of combining
programming languages, it is common to settle a single language at the
outset of any development effort. For many applications, performance
considerations dictate the use of a compiled language for the core
algorithms. Unfortunately, due to the complexity of the static type
system, the price we pay for runtime performance is often a
significant increase in development time. Experience shows that
writing maintainable C++ code usually takes longer and requires *far*
more hard-earned working experience than developing comparable Python
code. Even when developers are comfortable working exclusively in
compiled languages, they often augment their systems by some type of
ad hoc scripting layer for the benefit of their users without ever
availing themselves of the same advantages.
Boost.Python enables us to *think hybrid*. Python can be used for
rapidly prototyping a new application; its ease of use and the large
pool of standard libraries give us a head start on the way to a
working system. If necessary, the working code can be used to
discover rate-limiting hotspots. To maximize performance these can
be reimplemented in C++, together with the Boost.Python bindings
needed to tie them back into the existing higher-level procedure.
Of course, this *top-down* approach is less attractive if it is clear
from the start that many algorithms will eventually have to be
implemented in C++. Fortunately Boost.Python also enables us to
pursue a *bottom-up* approach. We have used this approach very
successfully in the development of a toolbox for scientific
applications. The toolbox started out mainly as a library of C++
classes with Boost.Python bindings, and for a while the growth was
mainly concentrated on the C++ parts. However, as the toolbox is
becoming more complete, more and more newly added functionality can be
implemented in Python.
.. image:: images/python_cpp_mix.png
This figure shows the estimated ratio of newly added C++ and Python
code over time as new algorithms are implemented. We expect this
ratio to level out near 70% Python. Being able to solve new problems
mostly in Python rather than a more difficult statically typed
language is the return on our investment in Boost.Python. The ability
to access all of our code from Python allows a broader group of
developers to use it in the rapid development of new applications.
=====================
Development history
=====================
The first version of Boost.Python was developed in 2000 by Dave
Abrahams at Dragon Systems, where he was privileged to have Tim Peters
as a guide to "The Zen of Python". One of Dave's jobs was to develop
a Python-based natural language processing system. Since it was
eventually going to be targeting embedded hardware, it was always
assumed that the compute-intensive core would be rewritten in C++ to
optimize speed and memory footprint [#proto]_. The project also wanted to
test all of its C++ code using Python test scripts [#test]_. The only
tool we knew of for binding C++ and Python was SWIG_, and at the time
its handling of C++ was weak. It would be false to claim any deep
insight into the possible advantages of Boost.Python's approach at
this point. Dave's interest and expertise in fancy C++ template
tricks had just reached the point where he could do some real damage,
and Boost.Python emerged as it did because it filled a need and
because it seemed like a cool thing to try.
This early version was aimed at many of the same basic goals we've
described in this paper, differing most-noticeably by having a
slightly more cumbersome syntax and by lack of special support for
operator overloading, pickling, and component-based development.
These last three features were quickly added by Ullrich Koethe and
Ralf Grosse-Kunstleve [#feature]_, and other enthusiastic contributors arrived
on the scene to contribute enhancements like support for nested
modules and static member functions.
By early 2001 development had stabilized and few new features were
being added, however a disturbing new fact came to light: Ralf had
begun testing Boost.Python on pre-release versions of a compiler using
the EDG_ front-end, and the mechanism at the core of Boost.Python
responsible for handling conversions between Python and C++ types was
failing to compile. As it turned out, we had been exploiting a very
common bug in the implementation of all the C++ compilers we had
tested. We knew that as C++ compilers rapidly became more
standards-compliant, the library would begin failing on more
platforms. Unfortunately, because the mechanism was so central to the
functioning of the library, fixing the problem looked very difficult.
Fortunately, later that year Lawrence Berkeley and later Lawrence
Livermore National labs contracted with `Boost Consulting`_ for support
and development of Boost.Python, and there was a new opportunity to
address fundamental issues and ensure a future for the library. A
redesign effort began with the low level type conversion architecture,
building in standards-compliance and support for component-based
development (in contrast to version 1 where conversions had to be
explicitly imported and exported across module boundaries). A new
analysis of the relationship between the Python and C++ objects was
done, resulting in more intuitive handling for C++ lvalues and
rvalues.
The emergence of a powerful new type system in Python 2.2 made the
choice of whether to maintain compatibility with Python 1.5.2 easy:
the opportunity to throw away a great deal of elaborate code for
emulating classic Python classes alone was too good to pass up. In
addition, Python iterators and descriptors provided crucial and
elegant tools for representing similar C++ constructs. The
development of the generalized ``object`` interface allowed us to
further shield C++ programmers from the dangers and syntactic burdens
of the Python 'C' API. A great number of other features including C++
exception translation, improved support for overloaded functions, and
most significantly, CallPolicies for handling pointers and
references, were added during this period.
In October 2002, version 2 of Boost.Python was released. Development
since then has concentrated on improved support for C++ runtime
polymorphism and smart pointers. Peter Dimov's ingenious
``boost::shared_ptr`` design in particular has allowed us to give the
hybrid developer a consistent interface for moving objects back and
forth across the language barrier without loss of information. At
first, we were concerned that the sophistication and complexity of the
Boost.Python v2 implementation might discourage contributors, but the
emergence of Pyste_ and several other significant feature
contributions have laid those fears to rest. Daily questions on the
Python C++-sig and a backlog of desired improvements show that the
library is getting used. To us, the future looks bright.
.. _`EDG`: http://www.edg.com
=============
Conclusions
=============
Boost.Python achieves seamless interoperability between two rich and
complimentary language environments. Because it leverages template
metaprogramming to introspect about types and functions, the user
never has to learn a third syntax: the interface definitions are
written in concise and maintainable C++. Also, the wrapping system
doesn't have to parse C++ headers or represent the type system: the
compiler does that work for us.
Computationally intensive tasks play to the strengths of C++ and are
often impossible to implement efficiently in pure Python, while jobs
like serialization that are trivial in Python can be very difficult in
pure C++. Given the luxury of building a hybrid software system from
the ground up, we can approach design with new confidence and power.
===========
Citations
===========
.. [VELD1995] T. Veldhuizen, "Expression Templates," C++ Report,
Vol. 7 No. 5 June 1995, pp. 26-31.
http://osl.iu.edu/~tveldhui/papers/Expression-Templates/exprtmpl.html
===========
Footnotes
===========
.. [#proto] In retrospect, it seems that "thinking hybrid" from the
ground up might have been better for the NLP system: the
natural component boundaries defined by the pure python
prototype turned out to be inappropriate for getting the
desired performance and memory footprint out of the C++ core,
which eventually caused some redesign overhead on the Python
side when the core was moved to C++.
.. [#test] We also have some reservations about driving all C++
testing through a Python interface, unless that's the only way
it will be ultimately used. Any transition across language
boundaries with such different object models can inevitably
mask bugs.
.. [#feature] These features were expressed very differently in v1 of
Boost.Python

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@@ -1,716 +0,0 @@
/*=============================================================================
Copyright (c) 2004 Joel de Guzman
http://spirit.sourceforge.net/
Copyright 2013 Niall Douglas additions for colors and alignment.
Copyright 2013 Paul A. Bristow additions for more colors and alignments.
Distributed under the Boost Software License, Version 1.0. (See accompany-
ing file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
=============================================================================*/
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180
doc/building.html Normal file
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@@ -0,0 +1,180 @@
<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
<meta name="generator" content="HTML Tidy, see www.w3.org">
<title>Building an Extension Module</title>
<div>
<h1><img width="277" height="86" align="center" src=
"../../../c++boost.gif" alt="c++boost.gif (8819 bytes)">Building an
Extension Module</h1>
<p>The build process for Boost is currently undergoing some evolution,
and, it is to be hoped, improvement. The following facts may help:
<hr>
Makefiles for various platforms and a Visual Studio project
reside in the Boost subdirectory <tt>libs/python/build</tt>.
Build targets include:
<ul>
<li>The <tt>boost_python</tt> library for static linking with your
extension module. On the various Unices, this library will be
called <tt>libboost_python.a</tt>. When using Visual C++, the
library will be called <tt>boost_python.lib</tt>.
<p>
<li>A comprehensive test of Boost.Python features. This test builds
a Boost.Python extension module, then runs Python to import the
module, and runs a series of tests on it using <tt><a href=
"../test/doctest.py">doctest</a></tt>. Source code for the module
and tests is available in the Boost subdirectory
<tt>libs/python/test</tt>.
<p>
<li>Various examples from the Boost subdirectory
<tt>libs/python/example</tt>.
All these examples include a doctest modeled
on the comprehensive test above.
</ul>
<hr>
There is a group of makefiles with support for simultaneous
compilation on multiple platforms and a consistent set of
features that build the <tt>boost_python</tt> library for static
linking, the comprehensive test, and all examples in
<tt>libs/python/example</tt>:
<ul>
<li><a href="../build/vc60.mak">vc60.mak</a>:
Visual C++ 6.0 Service Pack 4
<li><a href="../build/mingw32.mak">mingw32.mak</a>:
mingw32 (Win32-targeted) gcc 2.95.2
<li><a href="../build/linux_gcc.mak">linux_gcc.mak</a>:
gcc 2.95.2 on Linux/Unix
<li><a href="../build/tru64_cxx.mak">tru64_cxx.mak</a>:
Compaq Alpha using the Compaq cxx compiler
<li><a href="../build/irix_CC.mak">irix_CC.mak</a>:
Silicon Graphics IRIX 6.5 CC compiler
</ul>
<a href="http://cctbx.sourceforge.net/page_installation_adv.html#installation_boost_python"
>Usage of these makefiles is described here.</a>
<hr>
There is another group of makefiles for GNU make.
These makefiles are less redundant than the makefiles
in the group above,
but the list of compilation targets is not as complete
and there is no support for simultaneous compilation
on multiple platforms.
<ul>
<li><a href="../build/como.mak">como.mak</a>:
Comeau C++ on Linux
<li><a href="../build/gcc.mak">gcc.mak</a>:
GCC on Linux/Unix.
</ul>
<hr>
A project workspace for Microsoft Visual Studio is provided at <tt><a
href="../build/build.dsw">libs/python/build/build.dsw</a></tt>. The
include paths for this project may need to be changed for your
installation. They currently assume that python has been installed at
<tt>c:\tools\python</tt>. Three configurations of all targets are
supported:
<ul>
<li>Release (optimization, <tt>-DNDEBUG</tt>)
<li>Debug (no optimization <tt>-D_DEBUG</tt>)
<li>DebugPython (no optimization, <tt>-D_DEBUG
-DBOOST_DEBUG_PYTHON</tt>)
</ul>
<p>When extension modules are built with Visual C++ using
<tt>-D_DEBUG</tt>, Python defaults to <i>force</i> linking with a
special debugging version of the Python DLL. Since this debug DLL
isn't supplied with the default Python installation for Windows,
Boost.Python uses <tt><a href=
"../../../boost/python/detail/wrap_python.hpp">boost/python/detail/wrap_python.hpp</a></tt>
to temporarily undefine <tt>_DEBUG</tt> when <tt>Python.h</tt> is
<tt>#include</tt>d.
<p>If you want the extra runtime checks available with the debugging
version of the library, <tt>#define BOOST_DEBUG_PYTHON</tt> to
re-enable library forcing, and link with the DebugPython version of
<tt>boost_python.lib</tt>. You'll need to get the debugging version
of the Python executable (<tt>python_d.exe</tt>) and DLL
(<tt>python20_d.dll</tt> or <tt>python15_d.dll</tt>). The Python
sources include project files for building these. If you <a href=
"http://www.python.org">download</a> them, change the name of the
top-level directory to <tt>src</tt>, and install it under
<tt>c:\tools\python</tt>, the workspace supplied by Boost.Python will
be able to use it without modification. Just open
<tt>c:\tools\python\src\pcbuild\pcbuild.dsw</tt> and invoke "build
all" to generate all the debugging targets.
<p>If you do not <tt>#define BOOST_DEBUG_PYTHON</tt>, be sure that
any source files <tt>#include &lt;<a href=
"../../../boost/python/detail/wrap_python.hpp">boost/python/detail/wrap_python.hpp</a>&gt;</tt>
instead of the usual <tt>Python.h</tt>, or you will have link
incompatibilities.<br>
<hr>
If your platform isn't directly supported, you can build a static
library from the following source files (in the Boost subdirectory
<tt>libs/python/src</tt>), or compile them directly and link the
resulting objects into your extension module:
<ul>
<li><a href=
"../../../libs/python/src/classes.cpp">classes.cpp</a>
<li><a href=
"../../../libs/python/src/conversions.cpp">conversions.cpp</a>
<li><a href=
"../../../libs/python/src/cross_module.cpp">cross_module.cpp</a>
<li><a href=
"../../../libs/python/src/extension_class.cpp">extension_class.cpp</a>
<li><a href=
"../../../libs/python/src/functions.cpp">functions.cpp</a>
<li><a href=
"../../../libs/python/src/init_function.cpp">init_function.cpp</a>
<li><a href=
"../../../libs/python/src/module_builder.cpp">module_builder.cpp</a>
<li><a href=
"../../../libs/python/src/objects.cpp">objects.cpp</a>
<li><a href=
"../../../libs/python/src/types.cpp">types.cpp</a>
</ul>
<hr>
Next: <a href="enums.html">Wrapping Enums</a> Previous: <a href=
"under-the-hood.html">A Peek Under the Hood</a> Up: <a href=
"index.html">Top</a>
<hr>
<p>&copy; Copyright David Abrahams 2000. Permission to copy, use, modify,
sell and distribute this document is granted provided this copyright
notice appears in all copies. This document is provided ``as is'' without
express or implied warranty, and with no claim as to its suitability for
any purpose.
<p>Updated: Apr 17, 2001 (R.W. Grosse-Kunstleve)
</div>

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@@ -1,566 +0,0 @@
[chapter Building and Testing
[quickbook 1.7]
[authors [Abrahams, David]]
[copyright 2002 - 2015 David Abrahams, Stefan Seefeld]
[id building]
]
[/ Copyright David Abrahams 2006. Distributed under the Boost
/ Software License, Version 1.0. (See accompanying
/ file LICENSE_1_0.txt or copy at
/ http://www.boost.org/LICENSE_1_0.txt)
/]
[section Requirements]
Boost.Python requires [@http://www.python.org/2.2 Python 2.2]
[footnote Note that although we tested earlier versions of Boost.Python
with Python 2.2, and we don't *think* we've done anything to break
compatibility, this release of Boost.Python may not have been tested
with versions of Python earlier than 2.4, so we're not 100% sure that
python 2.2 and 2.3 are supported.] *or* [@http://www.python.org newer].
[endsect]
[section Background]
There are two basic models for combining C++ and Python:
* [@http://www.python.org/doc/current/ext/intro.html extending],
in which the end-user launches the Python interpreter
executable and imports Python “extension modules” written in C++.
Think of taking a library written in C++ and giving it a Python
interface so Python programmers can use it. From Python, these
modules look just like regular Python modules.
* [@http://www.python.org/doc/current/ext/embedding.html embedding],
in which the end-user launches a program written
in C++ that in turn invokes the Python interpreter as a library
subroutine. Think of adding scriptability to an existing
application.
The key distinction between extending and embedding is the location
of the C++ `main()` function: in the Python interpreter executable,
or in some other program, respectively. Note that even when
embedding Python in another program, [@http://www.python.org/doc/current/ext/extending-with-embedding.html extension modules are often
the best way to make C/C++ functionality accessible to Python
code], so the use of extension modules is really at the heart of
both models.
Except in rare cases, extension modules are built as
dynamically-loaded libraries with a single entry point, which means
you can change them without rebuilding either the other extension
modules or the executable containing `main()`.
[endsect]
[section No-Install Quickstart]
There is no need to “install Boost” in order to get started using
Boost.Python. These instructions use _bb_ projects,
which will build those binaries as soon as they're needed. Your
first tests may take a little longer while you wait for
Boost.Python to build, but doing things this way will save you from
worrying about build intricacies like which library binaries to use
for a specific compiler configuration and figuring out the right
compiler options to use yourself.
[note Of course it's possible to use other build systems to
build Boost.Python and its extensions, but they are not
officially supported by Boost. Moreover *99% of all “I can't
build Boost.Python” problems come from trying to use another
build system* without first following these instructions.
If you want to use another system anyway, we suggest that you
follow these instructions, and then invoke `bjam` with the
`-a -o`\ /filename/
options to dump the build commands it executes to a file, so
you can see what your alternate build system needs to do.]
[section Basic Procedure]
1. Get Boost; see sections 1 and 2 of the _gsg_.
2. Get the `bjam` build driver. See section 5 of the _gsg_.
3. cd into the `example/quickstart/` directory of your
Boost.Python installation, which contains a small example project.
4. Invoke `bjam`. Replace the “\ `stage`\ “ argument from the
example invocation from section 5 of the _gsg_ with “\ `test`\ ,“ to
build all the test targets. Also add the argument “\ `--verbose-test`\ ”
to see the output generated by the tests when they are run.
On Windows, your `bjam` invocation might look something like:
``
C:\\...\\quickstart> bjam toolset=msvc --verbose-test test
``
and on Unix variants, perhaps,
``
.../quickstart$ bjam toolset=gcc --verbose-test test
``
[note For the sake of concision, the rest of this guide will use
unix-style forward slashes in pathnames instead of the
backslashes with which Windows users may be more familiar. The forward
slashes should work everywhere except in
[@http://www.boost.org/more/getting_started/windows.html#command-prompt
Command Prompt] windows, where you should use backslashes.]
If you followed this procedure successfully, you will have built an
extension module called `extending` and tested it by running a
Python script called `test_extending.py`. You will also have
built and run a simple application called `embedding` that embeds
python.
[endsect]
[section In Case of Trouble]
If you're seeing lots of compiler and/or linker error messages,
it's probably because Boost.Build is having trouble finding your
Python installation. You might want to pass the
`--debug-configuration` option to `bjam` the first few times
you invoke it, to make sure that Boost.Build is correctly locating
all the parts of your Python installation. If it isn't, consider
[link building.configuring_boost_build Configuring Boost.Build]
as detailed below.
If you're still having trouble, Someone on one of the following
mailing lists may be able to help:
* The _bb_list_ for issues related to Boost.Build
* The _bp_list_ for issues specifically related to Boost.Python
[endsect]
[section In Case Everything Seemed to Work]
Rejoice! If you're new to Boost.Python, at this point it might be
a good idea to ignore build issues for a while and concentrate on
learning the library by going through the _tutorial_ and perhaps
some of the _reference_, trying out what you've
learned about the API by modifying the quickstart project.
[endsect]
[section Modifying the Example Project]
If you're content to keep your extension module forever in one
source file called `extending.cpp`, inside your Boost.Python
distribution, and import it forever as `extending`, then you can
stop here. However, it's likely that you will want to make a few
changes. There are a few things you can do without having to learn
_bb_ in depth.
The project you just built is specified in two files in the current
directory: `boost-build.jam`, which tells `bjam` where it can
find the interpreted code of the Boost build system, and
`Jamroot`, which describes the targets you just built. These
files are heavily commented, so they should be easy to modify.
Take care, however, to preserve whitespace. Punctuation such as
`;` will not be recognized as intended by `bjam` if it is not
surrounded by whitespace.
[section Relocate the Project]
You'll probably want to copy this project elsewhere so you can
change it without modifying your Boost distribution. To do that,
simply
a. copy the entire `example/quickstart/` directory
into a new directory.
b. In the new copies of `boost-build.jam` and `Jamroot`, locate
the relative path near the top of the file that is clearly
marked by a comment, and edit that path so that it refers to the
same directory your Boost distribution as it referred to when
the file was in its original location in the
`example/quickstart/` directory.
For example, if you moved the project from
`/home/dave/boost_1_34_0/libs/python/example/quickstart` to
`/home/dave/my-project`, you could change the first path in
`boost-build.jam` from
``
../../../../tools/build/src
``
to
``
/home/dave/boost_1_34_0/tools/build/src
``
and change the first path in `Jamroot` from
``
../../../..
``
to
``
/home/dave/boost_1_34_0
``
[endsect]
[section Add New or Change Names of Existing Source Files]
The names of additional source files involved in building your
extension module or embedding application can be listed in
`Jamroot` right alongside `extending.cpp` or `embedding.cpp`
respectively. Just be sure to leave whitespace around each
filename:
``
… file1.cpp file2.cpp file3.cpp …
``
Naturally, if you want to change the name of a source file you can
tell Boost.Build about it by editing the name in `Jamroot`.
[endsect]
[section Change the Name of your Extension Module]
The name of the extension module is determined by two things:
# the name in `Jamroot` immediately following `python-extension`, and
# the name passed to `BOOST_PYTHON_MODULE` in `extending.cpp`.
To change the name of the extension module from `extending` to
`hello`, you'd edit `Jamroot`, changing
``
python-extension extending : extending.cpp ;
``
to
``
python-extension hello : extending.cpp ;
``
and you'd edit extending.cpp, changing
``
BOOST_PYTHON_MODULE(extending)
``
to
``
BOOST_PYTHON_MODULE(hello)
``
[endsect]
[endsect]
[endsect]
[section Installing Boost.Python on your System]
Since Boost.Python is a separately-compiled (as opposed to
`header-only`) library, its user relies on the services of a
Boost.Python library binary.
If you need a regular installation of the Boost.Python library
binaries on your system, the _gsg_ will
walk you through the steps of creating one. If building binaries
from source, you might want to supply the `--with-python`
argument to `bjam` (or the `--with-libraries=python` argument
to `configure`), so only the Boost.Python binary will be built,
rather than all the Boost binaries.
[endsect]
[section Configuring Boost.Build]
As described in the [@http://www.boost.org/build/doc/html/bbv2/overview/configuration.html Boost.Build Reference Manual], a file called
`user-config.jam` in your home directory is used to
specify the tools and libraries available to the build system. You
may need to create or edit `user-config.jam` to tell Boost.Build
how to invoke Python, `#include` its headers, and link with its
libraries.
[note If you are using a unix-variant OS and you ran Boost's
`configure` script, it may have generated a
`user-config.jam` for you. [footnote `configure` overwrites the existing
`user-config.jam` in your home directory (if any) after making a backup of
the old version.] If your `configure`\ /\ `make` sequence was successful and
Boost.Python binaries were built, your `user-config.jam` file is probably already
correct.]
If you have one fairly “standard” python installation for your
platform, you might not need to do anything special to describe it. If
you haven't configured python in `user-config.jam` (and you don't
specify `--without-python` on the Boost.Build command line),
Boost.Build will automatically execute the equivalent of
``
import toolset : using ;
using python ;
``
which automatically looks for Python in the most likely places.
However, that only happens when using the Boost.Python project file
(e.g. when referred to by another project as in the quickstart
method). If instead you are linking against separately-compiled
Boost.Python binaries, you should set up a `user-config.jam` file
with at least the minimal incantation above.
[section Python Configuration Parameters]
If you have several versions of Python installed, or Python is
installed in an unusual way, you may want to supply any or all of
the following optional parameters to `using python`.
[variablelist
[[version]
[the version of Python to use. Should be in Major.Minor
format, for example, `2.3`. Do not include the subminor
version (i.e. *not* `2.5.1`). If you have multiple Python
versions installed, the version will usually be the only
configuration argument required.]]
[[cmd-or-prefix]
[preferably, a command that invokes a Python interpreter.
Alternatively, the installation prefix for Python libraries and
header files. Only use the alternative formulation if there is
no appropriate Python executable available.]]
[[*includes*]
[the `#include` paths for Python headers. Normally the correct
path(s) will be automatically deduced from `version` and/or
`cmd-or-prefix`.]]
[[*libraries*]
[the path to Python library binaries. On MacOS/Darwin,
you can also pass the path of the Python framework. Normally the
correct path(s) will be automatically deduced from `version`
and/or `cmd-or-prefix`.]]
[[*condition*]
[if specified, should be a set of Boost.Build
properties that are matched against the build configuration when
Boost.Build selects a Python configuration to use. See examples
below for details.]]
[[*extension-suffix*]
[A string to append to the name of extension
modules before the true filename extension. You almost certainly
don't need to use this. Usually this suffix is only used when
targeting a Windows debug build of Python, and will be set
automatically for you based on the value of the
[link building.python_debugging_builds <python-debugging>] feature.
However, at least one Linux distribution (Ubuntu Feisty Fawn) has
a specially configured [@https://wiki.ubuntu.com/PyDbgBuilds <python-dbg>]
package that claims to use such a suffix.]]
]
[endsect]
[section Examples]
Note that in the examples below, case and *especially whitespace* are
significant.
* If you have both python 2.5 and python 2.4 installed,
`user-config.jam` might contain
``
using python : 2.5 ; # Make both versions of Python available
using python : 2.4 ; # To build with python 2.4, add python=2.4
# to your command line.
``
The first version configured (2.5) becomes the default. To build
against python 2.4, add `python=2.4` to the `bjam` command line.
* If you have python installed in an unusual location, you might
supply the path to the interpreter in the `cmd-or-prefix`
parameter:
``
using python : : /usr/local/python-2.6-beta/bin/python ;
``
* If you have a separate build of Python for use with a particular
toolset, you might supply that toolset in the `condition`
parameter:
``
using python ; # use for most toolsets
# Use with Intel C++ toolset
using python
: # version
: c:\\Devel\\Python-2.5-IntelBuild\\PCBuild\\python # cmd-or-prefix
: # includes
: # libraries
: <toolset>intel # condition
;
``
* If you have downloaded the Python sources and built both the
normal and the [link building.python_debugging_builds "python debugging"]
builds from source on Windows, you might see:
``
using python : 2.5 : C:\\src\\Python-2.5\\PCBuild\\python ;
using python : 2.5 : C:\\src\\Python-2.5\\PCBuild\\python_d
: # includes
: # libs
: <python-debugging>on ;
``
* You can set up your user-config.jam so a bjam built under Windows
can build/test both Windows and Cygwin_ python extensions. Just pass
`<target-os>cygwin` in the `condition` parameter
for the cygwin python installation:
``
# windows installation
using python ;
# cygwin installation
using python : : c:\\cygwin\\bin\\python2.5 : : : <target-os>cygwin ;
``
when you put target-os=cygwin in your build request, it should build
with the cygwin version of python: [#flavor]_
``
bjam target-os=cygwin toolset=gcc
``
This is supposed to work the other way, too (targeting windows
python with a [@http://cygwin.com Cygwin] bjam) but it seems as though the support in
Boost.Build's toolsets for building that way is broken at the
time of this writing.
* Note that because of [@http://zigzag.cs.msu.su/boost.build/wiki/AlternativeSelection
the way Boost.Build currently selects target alternatives], you might have be very
explicit in your build requests. For example, given:
``
using python : 2.5 ; # a regular windows build
using python : 2.4 : : : : <target-os>cygwin ;
``
building with
``
bjam target-os=cygwin
``
will yield an error. Instead, you'll need to write
``
bjam target-os=cygwin/python=2.4
``
[endsect]
[endsect]
[section Choosing a Boost.Python Library Binary]
If—instead of letting Boost.Build construct and link with the right
libraries automatically—you choose to use a pre-built Boost.Python
library, you'll need to think about which one to link with. The
Boost.Python binary comes in both static and dynamic flavors. Take
care to choose the right flavor for your application. [footnote
Information about how to identify the static and dynamic builds of Boost.Python on
[@http://boost.org/more/getting_started/windows.html#library-naming Windows] /
[@http://boost.org/more/getting_started/unix-variants.html#library-naming Unix variants]]
[section The Dynamic Binary]
The dynamic library is the safest and most-versatile choice:
* A single copy of the library code is used by all extension
modules built with a given toolset. [footnote Because of the way most \*nix platforms
share symbols among dynamically-loaded objects, I'm not certain
that extension modules built with different compiler toolsets
will always use different copies of the Boost.Python library
when loaded into the same Python instance. Not using different
libraries could be a good thing if the compilers have compatible
ABIs, because extension modules built with the two libraries
would be interoperable. Otherwise, it could spell disaster,
since an extension module and the Boost.Python library would
have different ideas of such things as class layout. I would
appreciate someone doing the experiment to find out what
happens.]
* The library contains a type conversion registry. Because one
registry is shared among all extension modules, instances of a
class exposed to Python in one dynamically-loaded extension
module can be passed to functions exposed in another such module.
[endsect]
[section The Static Binary]
It might be appropriate to use the static Boost.Python library in
any of the following cases:
* You are _extending_ python and the types exposed in your
dynamically-loaded extension module don't need to be used by any
other Boost.Python extension modules, and you don't care if the
core library code is duplicated among them.
* You are _embedding_ python in your application and either:
* You are targeting a Unix variant OS other than MacOS or AIX,
where the dynamically-loaded extension modules can “see” the
Boost.Python library symbols that are part of the executable.
* Or, you have statically linked some Boost.Python extension
modules into your application and you don't care if any
dynamically-loaded Boost.Python extension modules are able to
use the types exposed by your statically-linked extension
modules (and vice-versa).
[endsect]
[endsect]
[section `#include` Issues]
1. If you should ever have occasion to `#include "python.h"`
directly in a translation unit of a program using Boost.Python,
use `#include "boost/python/detail/wrap_python.hpp"` instead.
It handles several issues necessary for use with Boost.Python,
one of which is mentioned in the next section.
2. Be sure not to `#include` any system headers before
`wrap_python.hpp`. This restriction is actually imposed by
Python, or more properly, by Python's interaction with your
operating system. See
[@http://docs.python.org/ext/simpleExample.html] for details.
[endsect]
[section Python Debugging Builds]
Python can be built in a special “python debugging” configuration
that adds extra checks and instrumentation that can be very useful
for developers of extension modules. The data structures used by
the debugging configuration contain additional members, so *a
Python executable built with python debugging enabled cannot be
used with an extension module or library compiled without it, and
vice-versa.*
Since pre-built “python debugging” versions of the Python
executable and libraries are not supplied with most distributions
of Python, [footnote On Unix and similar platforms, a debugging python and associated libraries are built by adding --with-pydebug when configuring the Python build. On Windows, the debugging version of Python is generated by the "Win32 Debug" target of the Visual Studio project in the PCBuild subdirectory of a full Python source code distribution.] and we didn't want to force our users
to build them, Boost.Build does not automatically enable python
debugging in its `debug` build variant (which is the default).
Instead there is a special build property called
`python-debugging` that, when used as a build property, will
define the right preprocessor symbols and select the right
libraries to link with.
On unix-variant platforms, the debugging versions of Python's data
structures will only be used if the symbol `Py_DEBUG` is defined.
On many windows compilers, when extension modules are built with
the preprocessor symbol `_DEBUG`, Python defaults to force
linking with a special debugging version of the Python DLL. Since
that symbol is very commonly used even when Python is not present,
Boost.Python temporarily undefines `_DEBUG` when `Python.h`
is #included from `boost/python/detail/wrap_python.hpp` - unless
`BOOST_DEBUG_PYTHON` is defined. The upshot is that if you want
“python debugging”and you aren't using Boost.Build, you should make
sure `BOOST_DEBUG_PYTHON` is defined, or python debugging will be
suppressed.
[endsect]
[section Testing Boost.Python]
To run the full test suite for Boost.Python, invoke `bjam` in the
`test` subdirectory of your Boost.Python distribution.
[endsect]
[section Notes for MinGW (and Cygwin with -mno-cygwin) GCC Users]
If you are using a version of Python prior to 2.4.1 with a MinGW
prior to 3.0.0 (with binutils-2.13.90-20030111-1), you will need to
create a MinGW-compatible version of the Python library; the one
shipped with Python will only work with a Microsoft-compatible
linker. Follow the instructions in the “Non-Microsoft” section of
the “Building Extensions: Tips And Tricks” chapter in
[@https://docs.python.org/2/install/index.html Installing Python Modules]
to create `libpythonXX.a`, where `XX` corresponds to the major and minor
version numbers of your Python installation.
[endsect]

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<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.0//EN"
"http://www.w3.org/TR/REC-html40/strict.dtd">
<title>
Comparisons with Other Systems
</title>
<div>
<h1>
<img width="277" height="86" id="_x0000_i1025" align="center"
src="../../../c++boost.gif" alt= "c++boost.gif (8819 bytes)"><br>
Comparisons with
Other Systems
</h1>
<h2>CXX</h2>
<p>
Like Boost.Python, <a href="http://cxx.sourceforge.net/">CXX</a> attempts to
provide a C++-oriented interface to Python. In most cases, as with the
boost library, it relieves the user from worrying about
reference-counts. Both libraries automatically convert thrown C++
exceptions into Python exceptions. As far as I can tell, CXX has no
support for subclassing C++ extension types in Python. An even
more significant difference is that a user's C++ code is still basically
``dealing with Python objects'', though they are wrapped in
C++ classes. This means such jobs as argument parsing and conversion are
still left to be done explicitly by the user.
<p>
CXX claims to interoperate well with the C++ Standard Library
(a.k.a. STL) by providing iterators into Python Lists and Dictionaries,
but the claim is unfortunately unsupportable. The problem is that in
general, access to Python sequence and mapping elements through
iterators requires the use of proxy objects as the return value of
iterator dereference operations. This usage conflicts with the basic
ForwardIterator requirements in <a
href="http://anubis.dkuug.dk/jtc1/sc22/open/n2356/lib-iterators.html#lib.forward.iterators">
section 24.1.3 of the standard</a> (dereferencing must produce a
reference). Although you may be able to use these iterators with some
operations in some standard library implementations, it is neither
guaranteed to work nor portable.
<p>
As far as I can tell, CXX enables one to write what is essentially
idiomatic Python code in C++, manipulating Python objects through the
same fully-generic interfaces we use in Python. While you're hardly
programming directly to the ``bare metal'' with CXX, it basically
presents a ``C++-ized'' version of the Python 'C' API. Some fraction of
that capability is available in Boost.Python through <tt><a
href="../../../boost/python/objects.hpp">boost/python/objects.hpp</a></tt>,
which provides C++ objects corresponding to Python lists, tuples,
strings, and dictionaries, and through <tt><a
href="../../../boost/python/callback.hpp">boost/python/callback.hpp</a></tt>,
which allows you to call back into python with C++ arguments.
<p>
<a href="mailto:dubois1@llnl.gov">Paul F. Dubois</a>, the original
author of CXX, has told me that what I've described is only half of the
picture with CXX, but I never understood his explanation well-enough to
fill in the other half. Here is his response to the commentary above:
<blockquote>
``My intention with CXX was not to do what you are doing. It was to enable a
person to write an extension directly in C++ rather than C. I figured others had
the wrapping business covered. I thought maybe CXX would provide an easier
target language for those making wrappers, but I never explored
that.''<br><i>-<a href="mailto:dubois1@llnl.gov">Paul Dubois</a></i>
</blockquote>
<h2>SWIG</h2>
<p>
<a href= "http://www.swig.org/">SWIG</a> is an impressively mature tool
for exporting an existing ANSI 'C' interface into various scripting
languages. Swig relies on a parser to read your source code and produce
additional source code files which can be compiled into a Python (or
Perl or Tcl) extension module. It has been successfully used to create
many Python extension modules. Like Boost.Python, SWIG is trying to allow an
existing interface to be wrapped with little or no change to the
existing code. The documentation says ``SWIG parses a form of ANSI C
syntax that has been extended with a number of special directives. As a
result, interfaces are usually built by grabbing a header file and
tweaking it a little bit.'' For C++ interfaces, the tweaking has often
proven to amount to more than just a little bit. One user
writes:
<blockquote> ``The problem with swig (when I used it) is that it
couldnt handle templates, didnt do func overloading properly etc. For
ANSI C libraries this was fine. But for usual C++ code this was a
problem. Simple things work. But for anything very complicated (or
realistic), one had to write code by hand. I believe Boost.Python doesn't have
this problem[<a href="#sic">sic</a>]... IMHO overloaded functions are very important to
wrap correctly.''<br><i>-Prabhu Ramachandran</i>
</blockquote>
<p>
By contrast, Boost.Python doesn't attempt to parse C++ - the problem is simply
too complex to do correctly. <a name="sic">Technically</a>, one does
write code by hand to use Boost.Python. The goal, however, has been to make
that code nearly as simple as listing the names of the classes and
member functions you want to expose in Python.
<h2>SIP</h2>
<p>
<a
href="http://www.thekompany.com/projects/pykde/background.php3?dhtml_ok=1">SIP</a>
is a system similar to SWIG, though seemingly more
C++-oriented. The author says that like Boost.Python, SIP supports overriding
extension class member functions in Python subclasses. It appears to
have been designed specifically to directly support some features of
PyQt/PyKDE, which is its primary client. Documentation is almost
entirely missing at the time of this writing, so a detailed comparison
is difficult.
<h2>ILU</h2>
<p>
<a
href="ftp://ftp.parc.xerox.com/pub/ilu/ilu.html">ILU</a>
is a very ambitious project which tries to describe a module's interface
(types and functions) in terms of an <a
href="ftp://ftp.parc.xerox.com/pub/ilu/2.0b1/manual-html/manual_2.html">Interface
Specification Language</a> (ISL) so that it can be uniformly interfaced
to a wide range of computer languages, including Common Lisp, C++, C,
Modula-3, and Python. ILU can parse the ISL to generate a C++ language
header file describing the interface, of which the user is expected to
provide an implementation. Unlike Boost.Python, this means that the system
imposes implementation details on your C++ code at the deepest level. It
is worth noting that some of the C++ names generated by ILU are supposed
to be reserved to the C++ implementation. It is unclear from the
documentation whether ILU supports overriding C++ virtual functions in Python.
<h2>GRAD</h2>
<p>
<a
href="http://www.python.org/workshops/1996-11/papers/GRAD/html/GRADcover.html">GRAD</a>
is another very ambitious project aimed at generating Python wrappers for
interfaces written in ``legacy languages'', among which C++ is the first one
implemented. Like SWIG, it aims to parse source code and automatically
generate wrappers, though it appears to take a more sophisticated approach
to parsing in general and C++ in particular, so it should do a much better
job with C++. It appears to support function overloading. The
documentation is missing a lot of information I'd like to see, so it is
difficult to give an accurate and fair assessment. I am left with the
following questions:
<ul>
<li>Does it support overriding of virtual functions?
<li>What about overriding private or protected virtual functions (the documentation indicates
that only public interfaces are supported)?
<li>Which C++ language constructs are supportd?
<li>Does it support implicit conversions between wrapped C++ classes that have
an inheritance relationship?
<li>Does it support smart pointers?
</ul>
<p>
Anyone in the possession of the answers to these questions will earn my
gratitude for a write-up <code>;-)</code>
<h2>Zope ExtensionClasses</h2>
<p>
<a href="http:http://www.digicool.com/releases/ExtensionClass">
ExtensionClasses in Zope</a> use the same underlying mechanism as Boost.Python
to support subclassing of extension types in Python, including
multiple-inheritance. Both systems support pickling/unpickling of
extension class instances in very similar ways. Both systems rely on the
same ``<a
href="http://www.python.org/workshops/1994-11/BuiltInClasses/Welcome.html">Don
Beaudry Hack</a>'' that also inspired Don's MESS System.
<p>
The major differences are:
<ul>
<li>Zope is entirely 'C' language-based. It doesn't require a C++
compiler, so it's much more portable than Boost.Python, which stresses
the limits of even some modern C++ implementations.
<li>
Boost.Python lifts the burden on the user to parse and convert function
argument types. Zope provides no such facility.
<li>
Boost.Python lifts the burden on the user to maintain Python
reference-counts.
<li>
Boost.Python supports function overloading; Zope does not.
<li>
Boost.Python supplies a simple mechanism for exposing read-only and
read/write access to data members of the wrapped C++ type as Python
attributes.
<li>
Writing a Zope ExtensionClass is significantly more complex than
exposing a C++ class to python using Boost.Python (mostly a summary of the
previous 4 items). <a href=
"http://www.digicool.com/releases/ExtensionClass/MultiMapping.html">A
Zope Example</a> illustrates the differences.
<li>
Zope's ExtensionClasses are specifically motivated by ``the need for a
C-based persistence mechanism''. Boost.Python's are motivated by the desire
to simply reflect a C++ API into Python with as little modification as
possible.
<li>
The following Zope restriction does not apply to Boost.Python: ``At most one
base extension direct or indirect super class may define C data
members. If an extension subclass inherits from multiple base
extension classes, then all but one must be mix-in classes that
provide extension methods but no data.''
<li>
Zope requires use of the somewhat funky inheritedAttribute (search for
``inheritedAttribute'' on <a
href="http://www.digicool.com/releases/ExtensionClass">this page</a>)
method to access base class methods. In Boost.Python, base class methods can
be accessed in the usual way by writing
``<code>BaseClass.method</code>''.
<li>
Zope supplies some creative but esoteric idioms such as <a href=
"http://www.digicool.com/releases/ExtensionClass/Acquisition.html">
Acquisition</a>. No specific support for this is built into Boost.Python.
<li>
Zope's ComputedAttribute support is designed to be used from Python.
<a href="special.html#getter_setter">The analogous feature of
Boost.Python</a> can be used from C++ or Python. The feature is arguably
easier to use in Boost.Python.
</ul>
<p>
Next: <a href="example1.html">A Simple Example Using Boost.Python</a>
Previous: <a href="extending.html">A Brief Introduction to writing Python Extension Modules</a>
Up: <a href="index.html">Top</a>
<p>
&copy; Copyright David Abrahams 2000. Permission to copy, use, modify,
sell and distribute this document is granted provided this copyright
notice appears in all copies. This document is provided ``as is'' without
express or implied warranty, and with no claim as to its suitability
for any purpose.
<p>
Updated: Mar 6, 2001
</div>

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[chapter Configuration
[quickbook 1.7]
[authors [Abrahams, David]]
[copyright 2002 - 2015 David Abrahams, Stefan Seefeld]
[id configuration]
]
[section Configuration]
[section Introduction]
[*Boost.Python] uses several configuration macros in `<boost/config.hpp>`, as well as configuration macros meant to be supplied by the application. These macros are documented here.
[endsect]
[section Application Defined Macros]
These are the macros that may be defined by an application using Boost.Python. Note that if you extend a strict interpretation of the C++ standard to cover dynamic libraries, using different values of these macros when compiling different libraries (including extension modules and the Boost.Python library itself) is a violation of the [link odr ODR]. However, we know of no C++ implementations on which this particular violation is detectable or causes any problems.
[table
[[Macro][Default][Meaning]]
[[BOOST_PYTHON_MAX_ARITY]
[15]
[The maximum arity of any function, member function,
or constructor to be wrapped, invocation of a
Boost.Python function wich is specified as taking
arguments x1, x2,...Xn. This includes, in particular,
callback mechanisms such as object::operator()(...) or call_method<R>(... ).]]
[[BOOST_PYTHON_MAX_BASES][10]
[The maximum number of template arguments to the
`bases<...>` class template, which is used to specify
the bases of a wrapped C++ class..]]
[[BOOST_PYTHON_STATIC_MODULE]
[ /not defined/ ]
[If defined, prevents your module initialization
function from being treated as an exported symbol
on platforms which support that distinction in-code]]
[[BOOST_PYTHON_ENABLE_CDECL]
[ /not defined/ ]
[If defined, allows functions using the `__cdecl`
calling convention to be wrapped.]]
[[BOOST_PYTHON_ENABLE_STDCALL]
[ /not defined/ ]
[If defined, allows functions using the `__stdcall`
calling convention to be wrapped.]]
[[BOOST_PYTHON_ENABLE_FASTCALL]
[ /not defined/ ]
[If defined, allows functions using the `__fastcall`
calling convention to be wrapped.]]
]
[endsect]
[section Library Defined Defined Macros]
These macros are defined by *Boost.Python* and are implementation details of interest only to implementors and those porting to new platforms.
[table
[[Macro][Default][Meaning]]
[[BOOST_PYTHON_TYPE_ID_NAME][ /not defined/ ]
[If defined, this indicates that the type_info comparison across
shared library boundaries does not work on this platform.
In other words, if shared-lib-1 passes `typeid(T)` to a function
in shared-lib-2 which compares it to `typeid(T)`, that comparison
may return `false`. If this macro is #defined, Boost.Python uses
and compares `typeid(T).name()` instead of using and comparing
the `std::type_info` objects directly.]]
[[BOOST_PYTHON_NO_PY_SIGNATURES][ /not defined/ ]
[If defined for a module no pythonic signatures are generated for
the docstrings of the module functions, and no python type is
associated with any of the converters registered by the module.
This also reduces the binary size of the module by about 14%
(gcc compiled).
If defined for the boost_python runtime library, the default for
the `docstring_options.enable_py_signatures()` is set to `false`.]]
[[BOOST_PYTHON_SUPPORTS_PY_SIGNATURES]
[ /defined/ if `BOOST_PYTHON_NO_PY_SIGNATURES` is /undefined/ ]
[This macro is defined to enable a smooth transition from older
Boost.Python versions which do not support pythonic signatures.
For example usage see here.]]
[[BOOST_PYTHON_PY_SIGNATURES_PROPER_INIT_SELF_TYPE][ /not defined/ ]
[If defined the python type of `__init__` method "self" parameters
is properly generated, otherwise object is used. It is undefined by
default because it increases the binary size of the module by about
14% (gcc compiled).]]
]
[endsect]
[endsect]

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<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.0//EN"
"http://www.w3.org/TR/REC-html40/strict.dtd">
<title>Cross-extension-module dependencies</title>
<div>
<img src="../../../c++boost.gif"
alt="c++boost.gif (8819 bytes)"
align="center"
width="277" height="86">
<hr>
<h1>Cross-extension-module dependencies</h1>
It is good programming practice to organize large projects as modules
that interact with each other via well defined interfaces. With
Boost.Python it is possible to reflect this organization at the C++
level at the Python level. This is, each logical C++ module can be
organized as a separate Python extension module.
<p>
At first sight this might seem natural and straightforward. However, it
is a fairly complex problem to establish cross-extension-module
dependencies while maintaining the same ease of use Boost.Python
provides for classes that are wrapped in the same extension module. To
a large extent this complexity can be hidden from the author of a
Boost.Python extension module, but not entirely.
<hr>
<h2>The recipe</h2>
Suppose there is an extension module that exposes certain instances of
the C++ <tt>std::vector</tt> template library such that it can be used
from Python in the following manner:
<pre>
import std_vector
v = std_vector.double([1, 2, 3, 4])
v.push_back(5)
v.size()
</pre>
Suppose the <tt>std_vector</tt> module is done well and reflects all
C++ functions that are useful at the Python level, for all C++ built-in
data types (<tt>std_vector.int</tt>, <tt>std_vector.long</tt>, etc.).
<p>
Suppose further that there is statistic module with a C++ class that
has constructors or member functions that use or return a
<tt>std::vector</tt>. For example:
<pre>
class xy {
public:
xy(const std::vector&lt;double&gt;&amp; x, const std::vector&lt;double&gt;&amp; y) : m_x(x), m_y(y) {}
const std::vector&lt;double&gt;&amp; x() const { return m_x; }
const std::vector&lt;double&gt;&amp; y() const { return m_y; }
double correlation();
private:
std::vector&lt;double&gt; m_x;
std::vector&lt;double&gt; m_y;
}
</pre>
What is more natural than reusing the <tt>std_vector</tt> extension
module to expose these constructors or functions to Python?
<p>
Unfortunately, what seems natural needs a little work in both the
<tt>std_vector</tt> and the <tt>statistics</tt> module.
<p>
In the <tt>std_vector</tt> extension module,
<tt>std::vector&lt;double&gt;</tt> is exposed to Python in the usual
way with the <tt>class_builder&lt;&gt;</tt> template. To also enable the
automatic conversion of <tt>std::vector&lt;double&gt;</tt> function
arguments or return values in other Boost.Python C++ modules, the
converters that convert a <tt>std::vector&lt;double&gt;</tt> C++ object
to a Python object and vice versa (i.e. the <tt>to_python()</tt> and
<tt>from_python()</tt> template functions) have to be exported. For
example:
<pre>
#include &lt;boost/python/cross_module.hpp&gt;
//...
class_builder&lt;std::vector&lt;double&gt; &gt; v_double(std_vector_module, &quot;double&quot;);
export_converters(v_double);
</pre>
In the extension module that wraps <tt>class xy</tt> we can now import
these converters with the <tt>import_converters&lt;&gt;</tt> template.
For example:
<pre>
#include &lt;boost/python/cross_module.hpp&gt;
//...
import_converters&lt;std::vector&lt;double&gt; &gt; v_double_converters(&quot;std_vector&quot;, &quot;double&quot;);
</pre>
That is all. All the attributes that are defined for
<tt>std_vector.double</tt> in the <tt>std_vector</tt> Boost.Python
module will be available for the returned objects of <tt>xy.x()</tt>
and <tt>xy.y()</tt>. Similarly, the constructor for <tt>xy</tt> will
accept objects that were created by the <tt>std_vector</tt>module.
<hr>
<h2>Placement of <tt>import_converters&lt;&gt;</tt> template instantiations</h2>
<tt>import_converts&lt;&gt;</tt> can be viewed as a drop-in replacement
for <tt>class_wrapper&lt;&gt;</tt>, and the recommendations for the
placement of <tt>class_wrapper&lt;&gt;</tt> template instantiations
also apply to to <tt>import_converts&lt;&gt;</tt>. In particular, it is
important that an instantiation of <tt>class_wrapper&lt;&gt;</tt> is
visible to any code which wraps a C++ function with a <tt>T</tt>,
<tt>T*</tt>, const <tt>T&amp;</tt>, etc. parameter or return value.
Therefore you may want to group all <tt>class_wrapper&lt;&gt;</tt> and
<tt>import_converts&lt;&gt;</tt> instantiations at the top of your
module's init function, then <tt>def()</tt> the member functions later
to avoid problems with inter-class dependencies.
<hr>
<h2>Non-copyable types</h2>
<tt>export_converters()</tt> instantiates C++ template functions that
invoke the copy constructor of the wrapped type. For a type that is
non-copyable this will result in compile-time error messages. In such a
case, <tt>export_converters_noncopyable()</tt> can be used to export
the converters that do not involve the copy constructor of the wrapped
type. For example:
<pre>
class_builder&lt;store&gt; py_store(your_module, &quot;store&quot;);
export_converters_noncopyable(py_store);
</pre>
The corresponding <tt>import_converters&lt;&gt;</tt> statement does not
need any special attention:
<pre>
import_converters&lt;store&gt; py_store(&quot;noncopyable_export&quot;, &quot;store&quot;);
</pre>
<hr>
<h2>Python module search path</h2>
The <tt>std_vector</tt> and <tt>statistics</tt> modules can now be used
in the following way:
<pre>
import std_vector
import statistics
x = std_vector.double([1, 2, 3, 4])
y = std_vector.double([2, 4, 6, 8])
xy = statistics.xy(x, y)
xy.correlation()
</pre>
In this example it is clear that Python has to be able to find both the
<tt>std_vector</tt> and the <tt>statistics</tt> extension module. In
other words, both extension modules need to be in the Python module
search path (<tt>sys.path</tt>).
<p>
The situation is not always this obvious. Suppose the
<tt>statistics</tt> module has a <tt>random()</tt> function that
returns a vector of random numbers with a given length:
<pre>
import statistics
x = statistics.random(5)
y = statistics.random(5)
xy = statistics.xy(x, y)
xy.correlation()
</pre>
A naive user will not easily anticipate that the <tt>std_vector</tt>
module is used to pass the <tt>x</tt> and <tt>y</tt> vectors around. If
the <tt>std_vector</tt> module is in the Python module search path,
this form of ignorance is of no harm. On the contrary, we are glad
that we do not have to bother the user with details like this.
<p>
If the <tt>std_vector</tt> module is not in the Python module search
path, a Python exception will be raised:
<pre>
Traceback (innermost last):
File &quot;foo.py&quot;, line 2, in ?
x = statistics.random(5)
ImportError: No module named std_vector
</pre>
As is the case with any system of a non-trivial complexity, it is
important that the setup is consistent and complete.
<hr>
<h2>Two-way module dependencies</h2>
Boost.Python supports two-way module dependencies. This is best
illustrated by a simple example.
<p>
Suppose there is a module <tt>ivect</tt> that implements vectors of
integers, and a similar module <tt>dvect</tt> that implements vectors
of doubles. We want to be able do convert an integer vector to a double
vector and vice versa. For example:
<pre>
import ivect
iv = ivect.ivect((1,2,3,4,5))
dv = iv.as_dvect()
</pre>
The last expression will implicitly import the <tt>dvect</tt> module in
order to enable the conversion of the C++ representation of
<tt>dvect</tt> to a Python object. The analogous is possible for a
<tt>dvect</tt>:
<pre>
import dvect
dv = dvect.dvect((1,2,3,4,5))
iv = dv.as_ivect()
</pre>
Now the <tt>ivect</tt> module is imported implicitly.
<p>
Note that the two-way dependencies are possible because the
dependencies are resolved only when needed. This is, the initialization
of the <tt>ivect</tt> module does not rely on the <tt>dvect</tt>
module, and vice versa. Only if <tt>as_dvect()</tt> or
<tt>as_ivect()</tt> is actually invoked will the corresponding module
be implicitly imported. This also means that, for example, the
<tt>dvect</tt> module does not have to be available at all if
<tt>as_dvect()</tt> is never used.
<hr>
<h2>Clarification of compile-time and link-time dependencies</h2>
Boost.Python's support for resolving cross-module dependencies at
runtime does not imply that compile-time dependencies are eliminated.
For example, the statistics extension module in the example above will
need to <tt>#include &lt;vector&gt;</tt>. This is immediately obvious
from the definition of <tt>class xy</tt>.
<p>
If a library is wrapped that consists of both header files and compiled
components (e.g. <tt>libdvect.a</tt>, <tt>dvect.lib</tt>, etc.), both
the Boost.Python extension module with the
<tt>export_converters()</tt> statement and the module with the
<tt>import_converters&lt;&gt;</tt> statement need to be linked against
the object library. Ideally one would build a shared library (e.g.
<tt>libdvect.so</tt>, <tt>dvect.dll</tt>, etc.). However, this
introduces the issue of having to configure the search path for the
dynamic loading correctly. For small libraries it is therefore often
more convenient to ignore the fact that the object files are loaded
into memory more than once.
<hr>
<h2>Summary of motivation for cross-module support</h2>
The main purpose of Boost.Python's cross-module support is to allow for
a modular system layout. With this support it is straightforward to
reflect C++ code organization at the Python level. Without the
cross-module support, a multi-purpose module like <tt>std_vector</tt>
would be impractical because the entire wrapper code would somehow have
to be duplicated in all extension modules that use it, making them
harder to maintain and harder to build.
<p>
Another motivation for the cross-module support is that two extension
modules that wrap the same class cannot both be imported into Python.
For example, if there are two modules <tt>A</tt> and <tt>B</tt> that
both wrap a given <tt>class X</tt>, this will work:
<pre>
import A
x = A.X()
</pre>
This will also work:
<pre>
import B
x = B.X()
</pre>
However, this will fail:
<pre>
import A
import B
python: /net/cci/rwgk/boost/boost/python/detail/extension_class.hpp:866:
static void boost::python::detail::class_registry&lt;X&gt;::register_class(boost::python::detail::extension_class_base *):
Assertion `static_class_object == 0' failed.
Abort
</pre>
A good solution is to wrap <tt>class X</tt> only once. Depending on the
situation, this could be done by module <tt>A</tt> or <tt>B</tt>, or an
additional small extension module that only wraps and exports
<tt>class X</tt>.
<p>
Finally, there can be important psychological or political reasons for
using the cross-module support. If a group of classes is lumped
together with many others in a huge module, the authors will have
difficulties in being identified with their work. The situation is
much more transparent if the work is represented by a module with a
recognizable name. This is not just a question of strong egos, but also
of getting credit and funding.
<hr>
<h2>Why not use <tt>export_converters()</tt> universally?</h2>
There is some overhead associated with the Boost.Python cross-module
support. Depending on the platform, the size of the code generated by
<tt>export_converters()</tt> is roughly 10%-20% of that generated
by <tt>class_builder&lt;&gt;</tt>. For a large extension module with
many wrapped classes, this could mean a significant difference.
Therefore the general recommendation is to use
<tt>export_converters()</tt> only for classes that are likely to
be used as function arguments or return values in other modules.
<hr>
&copy; Copyright Ralf W. Grosse-Kunstleve 2001. Permission to copy,
use, modify, sell and distribute this document is granted provided this
copyright notice appears in all copies. This document is provided "as
is" without express or implied warranty, and with no claim as to its
suitability for any purpose.
<p>
Updated: April 2001
</div>

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Given a real Python class 'A', a wrapped C++ class 'B', and this definition:
class C(A, B):
def __init__(self):
B.__init__(self)
self.x = 1
...
c = C()
this diagram describes the internal structure of an instance of 'C', including
its inheritance relationships. Note that ExtensionClass<B> is derived from
Class<ExtensionInstance>, and is in fact identical for all intents and purposes.
MetaClass<ExtensionInstance>
+---------+ +---------+
types.ClassType: | | | |
| | | |
| | | |
+---------+ +---------+
^ ^ ^
PyClassObject | ExtensionClass<B> | |
A: +------------+ | B: +------------+ | |
| ob_type -+-+ | ob_type -+-----+ |
| | ()<--+- __bases__ | |
| | | __dict__ -+->{...} |
| | 'B'<-+- __name__ | |
+------------+ +------------+ |
^ ^ |
| | |
+-----+ +-------------+ |
| | |
| | Class<ExtensionInstance> |
| | C: +------------+ |
| | | ob_type -+------------+
tuple:(*, *)<--+- __bases__ |
| __dict__ -+->{__module__, <methods, etc.>}
'C' <-+- __name__ |
+------------+
^ (in case of inheritance from more than one
| extension class, this vector would contain
+---------------+ a pointer to an instance holder for the data
| of each corresponding C++ class)
| ExtensionInstance
| c: +---------------------+ std::vector<InstanceHolderBase>
+----+- __class__ | +---+--
| m_wrapped_objects -+->| * | ...
{'x': 1}<-+- __dict__ | +-|-+--
+---------------------+ | InstanceValueHolder<B>
| +--------------------------------+
+-->| (contains a C++ instance of B) |
+--------------------------------+
In our inheritance test cases in extclass_demo.cpp/test_extclass.py, we have the
following C++ inheritance hierarchy:
+-----+ +----+
| A1 | | A2 |
+-----+ +----+
^ ^ ^ ^ ^
| | | | |
+-----+ | +---------+-----+
| | | |
| +---+----------+
.......!...... | |
: A_callback : +-+--+ +-+--+
:............: | B1 | | B2 |
+----+ +----+
^
|
+-------+---------+
| |
+-+-+ ......!.......
| C | : B_callback :
+---+ :............:
A_callback and B_callback are used as part of the wrapping mechanism but not
represented in Python. C is also not represented in Python but is delivered
there polymorphically through a smart pointer.
This is the data structure in Python.
ExtensionClass<A1>
A1: +------------+
()<--+- __bases__ |
| __dict__ -+->{...}
+------------+
^
| ExtensionInstance
| a1: +---------------------+ vec InstanceValueHolder<A1,A_callback>
+---------+- __class__ | +---+ +---------------------+
| | m_wrapped_objects -+->| *-+-->| contains A_callback |
| +---------------------+ +---+ +---------------------+
|
| ExtensionInstance
| pa1_a1: +---------------------+ vec InstancePtrHolder<auto_ptr<A1>,A1>
+---------+- __class__ | +---+ +---+
| | m_wrapped_objects -+->| *-+-->| *-+-+ A1
| +---------------------+ +---+ +---+ | +---+
| +->| |
| ExtensionInstance +---+
| pb1_a1: +---------------------+ vec InstancePtrHolder<auto_ptr<A1>,A1>
+---------+- __class__ | +---+ +---+
| | m_wrapped_objects -+->| *-+-->| *-+-+ B1
| +---------------------+ +---+ +---+ | +---+
| +->| |
| ExtensionInstance +---+
| pb2_a1: +---------------------+ vec InstancePtrHolder<auto_ptr<A1>,A1>
+---------+- __class__ | +---+ +---+
| | m_wrapped_objects -+->| *-+-->| *-+-+ B2
| +---------------------+ +---+ +---+ | +---+
| +->| |
| +---+
| ExtensionClass<A1>
| A2: +------------+
| ()<--+- __bases__ |
| | __dict__ -+->{...}
| +------------+
| ^
| | ExtensionInstance
| a2: | +---------------------+ vec InstanceValueHolder<A2>
| +-+- __class__ | +---+ +-------------+
| | | m_wrapped_objects -+->| *-+-->| contains A2 |
| | +---------------------+ +---+ +-------------+
| |
| | ExtensionInstance
| pa2_a2: | +---------------------+ vec InstancePtrHolder<auto_ptr<A2>,A2>
| +-+- __class__ | +---+ +---+
| | | m_wrapped_objects -+->| *-+-->| *-+-+ A2
| | +---------------------+ +---+ +---+ | +---+
| | +->| |
| | ExtensionInstance +---+
| pb1_a2: | +---------------------+ vec InstancePtrHolder<auto_ptr<A2>,A2>
| +-+- __class__ | +---+ +---+
| | | m_wrapped_objects -+->| *-+-->| *-+-+ B1
| | +---------------------+ +---+ +---+ | +---+
| | +->| |
| | +---+
| |
| +---------------+------------------------------+
| | |
+------+-------------------------+-|----------------------------+ |
| | | | |
| Class<ExtensionInstance> | | ExtensionClass<B1> | | ExtensionClass<B1>
| DA1: +------------+ | | B1: +------------+ | | B2: +------------+
(*,)<---+- __bases__ | (*,*)<---+- __bases__ | (*,*)<---+- __bases__ |
| __dict__ -+->{...} | __dict__ -+->{...} | __dict__ -+->{...}
+------------+ +------------+ +------------+
^ ^ ^
| ExtensionInstance | |
| da1: +---------------------+ | vec InstanceValueHolder<A1,A_callback>
+-------+- __class__ | | +---+ +---------------------+ |
| m_wrapped_objects -+--|-->| *-+-->| contains A_callback | |
+---------------------+ | +---+ +---------------------+ |
+--------------------------------------+ |
| ExtensionInstance |
b1: | +---------------------+ vec InstanceValueHolder<B1,B_callback> |
+-+- __class__ | +---+ +---------------------+ |
| | m_wrapped_objects -+->| *-+-->| contains B_callback | |
| +---------------------+ +---+ +---------------------+ |
| |
| ExtensionInstance |
pb1_b1: | +---------------------+ vec InstancePtrHolder<auto_ptr<B1>,B1> |
+-+- __class__ | +---+ +---+ |
| | m_wrapped_objects -+->| *-+-->| *-+-+ B1 |
| +---------------------+ +---+ +---+ | +---+ |
| +->| | |
| ExtensionInstance +---+ |
pc_b1: | +---------------------+ vec InstancePtrHolder<auto_ptr<B1>,B1> |
+-+- __class__ | +---+ +---+ |
| | m_wrapped_objects -+->| *-+-->| *-+-+ C |
| +---------------------+ +---+ +---+ | +---+ |
| +->| | |
| +---+ |
| |
| Class<ExtensionInstance> +---------------------------------------+
| DB1: +------------+ | ExtensionInstance
(*,)<---+- __bases__ | a2: | +---------------------+ vec InstanceValueHolder<A2>
| __dict__ -+->{...} +-+- __class__ | +---+ +-------------+
+------------+ | m_wrapped_objects -+->| *-+-->| contains A2 |
^ +---------------------+ +---+ +-------------+
| ExtensionInstance
db1: | +---------------------+ vec InstanceValueHolder<B1,B_callback>
+-+- __class__ | +---+ +----------------------+
| m_wrapped_objects -+-->| *-+-->| contains B1_callback |
+---------------------+ +---+ +----------------------+

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<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.0//EN"
"http://www.w3.org/TR/REC-html40/strict.dtd">
<title>
Wrapping enums
</title>
<div>
<h1>
<img width="277" height="86" id="_x0000_i1025" align="center"
src="../../../c++boost.gif" alt= "c++boost.gif (8819 bytes)"><br>
Wrapping enums
</h1>
<p>Because there is in general no way to deduce that a value of arbitrary type T
is an enumeration constant, the Boost Python Library cannot automatically
convert enum values to and from Python. To handle this case, you need to decide
how you want the enum to show up in Python (since Python doesn't have
enums). Once you have done that, you can write some simple
<code>from_python()</code> and <code>to_python()</code> functions.
<p>If you are satisfied with a Python int as a way to represent your enum
values, we provide a shorthand for these functions. You just need to cause
<code>boost::python::enum_as_int_converters&lt;EnumType&gt;</code> to be
instantiated, where
<code>EnumType</code> is your enumerated type. There are two convenient ways to do this:
<ol>
<li>Explicit instantiation:
<blockquote><pre>
template class boost::python::enum_as_int_converters&lt;my_enum&gt;;
</blockquote></pre>
Some buggy C++ implementations require a class to be instantiated in the same
namespace in which it is defined. In that case, the simple incantation above becomes:
<blockquote>
<pre>
...
} // close my_namespace
// drop into namespace python and explicitly instantiate
namespace boost { namespace python {
template class enum_as_int_converters&lt;my_enum_type&gt;;
}} // namespace boost::python
namespace my_namespace { // re-open my_namespace
...
</pre>
</blockquote>
<li>If you have such an implementation, you may find this technique more convenient
<blockquote><pre>
// instantiate as base class in any namespace
struct EnumTypeConverters
: boost::python::enum_as_int_converters&lt;EnumType&gt;
{
};
</blockquote></pre>
</ol>
<p>Either of the above is equivalent to the following declarations:
<blockquote><pre>
BOOST_PYTHON_BEGIN_CONVERSION_NAMESPACE // this is a gcc 2.95.2 bug workaround
MyEnumType from_python(PyObject* x, boost::python::type&lt;MyEnumType&gt;)
{
return static_cast&lt;MyEnum&gt;(
from_python(x, boost::python::type&lt;long&gt;()));
}
MyEnumType from_python(PyObject* x, boost::python::type&lt;const MyEnumType&amp;&gt;)
{
return static_cast&lt;MyEnum&gt;(
from_python(x, boost::python::type&lt;long&gt;()));
}
PyObject* to_python(MyEnumType x)
{
return to_python(static_cast&lt;long&gt;(x));
}
BOOST_PYTHON_END_CONVERSION_NAMESPACE
</pre></blockquote>
<p>This technique defines the conversions of
<code>MyEnumType</code> in terms of the conversions for the built-in
<code>long</code> type.
You may also want to add a bunch of lines like this to your module
initialization. These bind the corresponding enum values to the appropriate
names so they can be used from Python:
<blockquote><pre>
mymodule.add(boost::python::make_ref(enum_value_1), "enum_value_1");
mymodule.add(boost::python::make_ref(enum_value_2), "enum_value_2");
...
</pre></blockquote>
You can also add these to an extension class definition, if your enum happens to
be local to a class and you want the analogous interface in Python:
<blockquote><pre>
my_class_builder.add(boost::python::to_python(enum_value_1), "enum_value_1");
my_class_builder.add(boost::python::to_python(enum_value_2), "enum_value_2");
...
</pre></blockquote>
<p>
Next: <a href="pointers.html">Pointers and Smart Pointers</a>
Previous: <a href="building.html">Building an Extension Module</a>
Up: <a href="index.html">Top</a>
<p>
&copy; Copyright David Abrahams 2000. Permission to copy, use, modify,
sell and distribute this document is granted provided this copyright
notice appears in all copies. This document is provided ``as
is'' without express or implied warranty, and with no claim as to
its suitability for any purpose.
<p>
Updated: Mar 6, 2001
</div>

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<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.0//EN"
"http://www.w3.org/TR/REC-html40/strict.dtd">
<title>
A Simple Example
</title>
<div>
<h1>
<img width="277" height="86" id="_x0000_i1025" src="../../../c++boost.gif" alt=
"c++boost.gif (8819 bytes)">
</h1>
<h1>
A Simple Example
</h1>
<p>
Suppose we have the following C++ API which we want to expose in
Python:
<blockquote>
<pre>
#include &lt;string&gt;
namespace { // Avoid cluttering the global namespace.
// A couple of simple C++ functions that we want to expose to Python.
std::string greet() { return "hello, world"; }
int square(int number) { return number * number; }
}
</pre>
</blockquote>
<p>
Here is the C++ code for a python module called <tt>getting_started1</tt>
which exposes the API.
<blockquote>
<pre>
#include &lt;boost/python/class_builder.hpp&gt;
namespace python = boost::python;
BOOST_PYTHON_MODULE_INIT(getting_started1)
{
try
{
// Create an object representing this extension module.
python::module_builder this_module("getting_started1");
// Add regular functions to the module.
this_module.def(greet, "greet");
this_module.def(square, "square");
}
catch(...)
{
python::handle_exception(); // Deal with the exception for Python
}
}
</pre>
</blockquote>
<p>
That's it! If we build this shared library and put it on our <code>
PYTHONPATH</code> we can now access our C++ functions from
Python.
<blockquote>
<pre>
&gt;&gt;&gt; import getting_started1
&gt;&gt;&gt; print getting_started1.greet()
hello, world
&gt;&gt;&gt; number = 11
&gt;&gt;&gt; print number, '*', number, '=', getting_started1.square(number)
11 * 11 = 121
</pre>
<p>
Next: <a href="exporting_classes.html">Exporting Classes</a>
Previous: <a href="comparisons.html">Comparisons with other systems</a> Up:
<a href="index.html">Top</a>
<p>
&copy; Copyright David Abrahams 2000. Permission to copy, use, modify,
sell and distribute this document is granted provided this copyright
notice appears in all copies. This document is provided "as is" without
express or implied warranty, and with no claim as to its suitability
for any purpose.
<p>
Updated: Mar 6, 2000
</div>

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<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.0//EN"
"http://www.w3.org/TR/REC-html40/strict.dtd">
<title>
Exporting Classes
</title>
<div>
<h1>
<img width="277" height="86" id="_x0000_i1025" src="../../../c++boost.gif" alt=
"c++boost.gif (8819 bytes)">
</h1>
<h1>
Exporting Classes
</h1>
<p>
Now let's expose a C++ class to Python:
<blockquote><pre>
#include &lt;iostream&gt;
#include &lt;string&gt;
namespace { // Avoid cluttering the global namespace.
// A friendly class.
class hello
{
public:
hello(const std::string&amp; country) { this-&gt;country = country; }
std::string greet() const { return "Hello from " + country; }
private:
std::string country;
};
// A function taking a hello object as an argument.
std::string invite(const hello&amp; w) {
return w.greet() + "! Please come soon!";
}
}
</blockquote></pre> <p>
To expose the class, we use a <tt>class_builder</tt> in addition to the
<tt>module_builder</tt> from the previous example. Class member functions
are exposed by using the <tt>def()</tt> member function on the
<tt>class_builder</tt>:
<blockquote><pre>
#include &lt;boost/python/class_builder.hpp&gt;
namespace python = boost::python;
BOOST_PYTHON_MODULE_INIT(getting_started2)
{
try
{
// Create an object representing this extension module.
python::module_builder this_module("getting_started2");
// Create the Python type object for our extension class.
python::class_builder&lt;hello&gt; hello_class(this_module, "hello");
// Add the __init__ function.
hello_class.def(python::constructor&lt;std::string&gt;());
// Add a regular member function.
hello_class.def(&amp;hello::greet, "greet");
// Add invite() as a regular function to the module.
this_module.def(invite, "invite");
// Even better, invite() can also be made a member of hello_class!!!
hello_class.def(invite, "invite");
}
catch(...)
{
python::handle_exception(); // Deal with the exception for Python
}
}
</blockquote></pre>
<p>
Now we can use the class normally from Python:
<blockquote><pre>
&gt;&gt;&gt; from getting_started2 import *
&gt;&gt;&gt; hi = hello('California')
&gt;&gt;&gt; hi.greet()
'Hello from California'
&gt;&gt;&gt; invite(hi)
'Hello from California! Please come soon!'
&gt;&gt;&gt; hi.invite()
'Hello from California! Please come soon!'
</blockquote></pre>
Notes:<ul>
<li> We expose the class' constructor by calling <tt>def()</tt> on the
<tt>class_builder</tt> with an argument whose type is
<tt>constructor&lt;</tt><i>params</i><tt>&gt;</tt>, where <i>params</i>
matches the list of constructor argument types:
<li>Regular member functions are defined by calling <tt>def()</tt> with a
member function pointer and its Python name:
<li>Any function added to a class whose initial argument matches the class (or
any base) will act like a member function in Python.
</ul>
<p>
We can even make a subclass of <code>hello.world</code>:
<blockquote><pre>
&gt;&gt;&gt; class wordy(hello):
... def greet(self):
... return hello.greet(self) + ', where the weather is fine'
...
&gt;&gt;&gt; hi2 = wordy('Florida')
&gt;&gt;&gt; hi2.greet()
'Hello from Florida, where the weather is fine'
&gt;&gt;&gt; invite(hi2)
'Hello from Florida! Please come soon!'
</blockquote></pre>
<p>
Pretty cool! You can't do that with an ordinary Python extension type!
Of course, you may now have a slightly empty feeling in the pit of
your little pythonic stomach. Perhaps you wanted to see the following
<tt>wordy</tt> invitation:
<blockquote><pre>
'Hello from Florida, where the weather is fine! Please come soon!'
</blockquote></pre>
After all, <tt>invite</tt> calls <tt>hello::greet()</tt>, and you
reimplemented that in your Python subclass, <tt>wordy</tt>. If so, <a
href= "overriding.html">read on</a>...
<p>
Next: <a href="overriding.html">Overridable virtual functions</a>
Previous: <a href="example1.html">A Simple Example</a> Up:
<a href="index.html">Top</a>
<p>
&copy; Copyright David Abrahams 2000. Permission to copy, use, modify,
sell and distribute this document is granted provided this copyright
notice appears in all copies. This document is provided "as is" without
express or implied warranty, and with no claim as to its suitability
for any purpose.
<p>
Updated: Mar 6, 2001
</div>

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<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 3.2//EN">
<meta http-equiv="Content-Type" content="text/html; charset=windows-1252">
<title>
A Brief Introduction to writing Python extension modules
</title>
<h1>
<img src="../../../c++boost.gif" alt="c++boost.gif (8819 bytes)" align="center"
width="277" height="86">
</h1>
<h1>
A Brief Introduction to writing Python extension modules
</h1>
<p>
Interfacing any language to Python involves building a module which can
be loaded by the Python interpreter, but which isn't written in Python.
This is known as an <em>extension module</em>. Many of the <a href=
"http://www.python.org/doc/current/lib/lib.html">built-in Python
libraries</a> are constructed in 'C' this way; Python even supplies its
<a href="http://www.python.org/doc/current/lib/types.html">fundamental
types</a> using the same mechanism. An extension module can be statically
linked with the Python interpreter, but it more commonly resides in a
shared library or DLL.
<p>
As you can see from <a href=
"http://www.python.org/doc/current/ext/ext.html"> The Python Extending
and Embedding Tutorial</a>, writing an extension module normally means
worrying about
<ul>
<li>
<a href="http://www.python.org/doc/current/ext/refcounts.html">
maintaining reference counts</a>
<li>
<a href="http://www.python.org/doc/current/ext/callingPython.html"> how
to call back into Python</a>
<li>
<a href="http://www.python.org/doc/current/ext/parseTuple.html">
function argument parsing and typechecking</a>
</ul>
This last item typically occupies a great deal of code in an extension
module. Remember that Python is a completely dynamic language. A callable
object receives its arguments in a tuple; it is up to that object to extract
those arguments from the tuple, check their types, and raise appropriate
exceptions. There are numerous other tedious details that need to be
managed; too many to mention here. The Boost Python Library is designed to
lift most of that burden.<br>
<br>
<p>
Another obstacle that most people run into eventually when extending
Python is that there's no way to make a true Python class in an extension
module. The typical solution is to create a new Python type in the
extension module, and then write an additional module in 100% Python. The
Python module defines a Python class which dispatches to an instance of
the extension type, which it contains. This allows users to write
subclasses of the class in the Python module, almost as though they were
sublcassing the extension type. Aside from being tedious, it's not really
the same as having a true class, because there's no way for the user to
override a method of the extension type which is called from the
extension module. Boost.Python solves this problem by taking advantage of <a
href="http://www.python.org/doc/essays/metaclasses/">Python's metaclass
feature</a> to provide objects which look, walk, and hiss almost exactly
like regular Python classes. Boost.Python classes are actually cleaner than
Python classes in some subtle ways; a more detailed discussion will
follow (someday).</p>
<p>Next: <a href="comparisons.html">Comparisons with Other Systems</a> Up: <a
href="index.html">Top</a> </p>
<p>
&copy; Copyright David Abrahams 2000. Permission to copy, use, modify,
sell and distribute this document is granted provided this copyright
notice appears in all copies. This document is provided "as is" without
express or implied warranty, and with no claim as to its suitability for
any purpose.</p>

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@@ -1,83 +0,0 @@
# -*- python -*-
#
# Copyright (c) 2016 Stefan Seefeld
# All rights reserved.
#
# Distributed under the Boost Software License, Version 1.0.
# (See accompanying file LICENSE_1_0.txt or copy at
# http://www.boost.org/LICENSE_1_0.txt)
from faber.tools.xslt import xsltflags
from faber.tools.boost import quickbook, boostbook
from faber.artefacts import html
from glob import glob as G
from os import makedirs
from os.path import relpath, dirname, exists
from shutil import copyfile
def glob(pattern):
prefix = srcdir + '/'
p = len(prefix)+1
return [f[p:] for f in G(prefix + pattern)]
class make_html(action):
def __init__(self):
action.__init__(self, 'make_html', self.process)
def map(self, fs):
return boostbook.html.map(fs)
def process(self, target, source):
boostbook.html(target, source[0:1])
for s in source[1:]:
t = target[0]._filename + relpath(s._filename, srcdir)
d = dirname(t)
if not exists(d):
makedirs(d)
copyfile(s._filename, t)
sphinx_build = action('sphinx-build', 'sphinx-build -b html $(>) $(<)')
rst2html = action('rst2html', 'rst2html --trim-footnote-reference-space --footnote-references=superscript --stylesheet=$(>:D)/rst.css $(>) $(<)')
python_bbk = rule(quickbook.process, 'python.bbk', 'python.qbk',
dependencies=['release_notes.qbk',
'building.qbk',
'configuration.qbk',
'suport.qbk',
'faq.qbk',
'glossary.qbk'])
tutorial_bbk = rule(quickbook.process, 'tutorial.bbk', 'tutorial.qbk')
reference_bbk = rule(quickbook.process, 'reference.bbk', 'reference.qbk')
python_db = rule(boostbook.db, 'python.db', python_bbk)
tutorial_db = rule(boostbook.db, 'tutorial.db', tutorial_bbk)
reference_db = rule(boostbook.db, 'reference.db', reference_bbk)
python = html.dir(make_html(), 'html', [python_db, 'boostbook.css'] + glob('/images/*.*') + glob('/images/callouts/*.*'),
features=xsltflags('--stringparam generate.toc "library nop; chaper toc; section toc;"',
'--stringparam html.stylesheet boostbook.css',
'--stringparam boost.image.src images/bpl.png',
'--stringparam boost.graphics.root images/',
'--stringparam boost.defaults none',
'--param toc.max.depth 3',
'--param toc.section.depth 2',
'--param chunk.section.depth 1'))
tutorial = html.dir(boostbook.html, 'html/tutorial', tutorial_db, dependencies=[python],
features=xsltflags('--stringparam html.stylesheet ../boostbook.css',
'--stringparam boost.image.src ../images/bpl.png',
'--stringparam boost.graphics.root ../images/'))
reference = html.dir(boostbook.html, 'html/reference', reference_db, dependencies=[python],
features=xsltflags('--stringparam html.stylesheet ../boostbook.css',
'--stringparam boost.image.src ../images/bpl.png',
'--stringparam boost.graphics.root ../images/'))
numpy = rule(sphinx_build, 'html/numpy', 'numpy', attrs=always, dependencies=[python])
article = rule(rst2html, 'html/article.html', 'article.rst')
html = alias('html', [python, tutorial, reference, numpy, article])
default = html

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@@ -1,736 +0,0 @@
[chapter Frequently Asked Questions (FAQs)
[quickbook 1.7]
[id faq]
]
[section How can I wrap a function which takes a function pointer as an argument?]
If what you're trying to do is something like this:
``
typedef boost::function<void (string s) > funcptr;
void foo(funcptr fp)
{
fp("hello,world!");
}
BOOST_PYTHON_MODULE(test)
{
def("foo",foo);
}
``
And then:
``
>>> def hello(s):
... print s
...
>>> foo(hello)
hello, world!
``
The short answer is: "you can't". This is not a
Boost.Python limitation so much as a limitation of C++. The
problem is that a Python function is actually data, and the only
way of associating data with a C++ function pointer is to store it
in a static variable of the function. The problem with that is
that you can only associate one piece of data with every C++
function, and we have no way of compiling a new C++ function
on-the-fly for every Python function you decide to pass
to `foo`. In other words, this could work if the C++
function is always going to invoke the /same/ Python
function, but you probably don't want that.
If you have the luxury of changing the C++ code you're
wrapping, pass it an `object` instead and call that;
the overloaded function call operator will invoke the Python
function you pass it behind the `object`.
[endsect]
[section I'm getting the "attempt to return dangling reference" error.
What am I doing wrong?]
That exception is protecting you from causing a nasty crash. It usually
happens in response to some code like this:
``
period const &get_floating_frequency() const
{
return boost::python::call_method<period const &>(
m_self,"get_floating_frequency");
}
``
And you get:
``
ReferenceError: Attempt to return dangling reference to object of type:
class period
``
In this case, the Python method invoked by `call_method`
constructs a new Python object. You're trying to return a reference to a
C++ object (an instance of `class period`) contained within
and owned by that Python object. Because the called method handed back a
brand new object, the only reference to it is held for the duration of
`get_floating_frequency()` above. When the function returns,
the Python object will be destroyed, destroying the instance of
`class period`, and leaving the returned reference dangling.
That's already undefined behavior, and if you try to do anything with
that reference you're likely to cause a crash. Boost.Python detects this
situation at runtime and helpfully throws an exception instead of letting
you do that.
[endsect]
[section Is `return_internal_reference` efficient?]
[*Q:] /I have an object composed of 12 doubles. A `const&` to
this object is returned by a member function of another class. From the
viewpoint of using the returned object in Python I do not care if I get
a copy or a reference to the returned object. In Boost.Python I have the
choice of using `copy_const_reference` or `return_internal_reference`.
Are there considerations that would lead me to prefer one over the other,
such as size of generated code or memory overhead?/
[*A:] `copy_const_reference` will make an instance with storage
for one of your objects, `size = base_size + 12 * sizeof(double)`.
`return_internal_reference` will make an instance with storage for a
pointer to one of your objects, `size = base_size + sizeof(void*)`.
However, it will also create a weak reference object which goes in the
source object's weakreflist and a special callback object to manage the
lifetime of the internally-referenced object. My guess?
`copy_const_reference` is your friend here, resulting in less overall
memory use and less fragmentation, also probably fewer total
cycles.
[endsect]
[section How can I wrap functions which take C++ containers as arguments?]
Ralf W. Grosse-Kunstleve provides these notes:
# Using the regular `class_<>` wrapper:
``
class_<std::vector<double> >("std_vector_double")
.def(...)
...
;
``
This can be moved to a template so that several types (`double`, `int`,
`long`, etc.) can be wrapped with the same code. This technique is used
in the file `scitbx/include/scitbx/array_family/boost_python/flex_wrapper.h`
in the "scitbx" package. The file could easily be modified for
wrapping `std::vector<>` instantiations.
This type of C++/Python binding is most suitable for containers
that may contain a large number of elements (>10000).
# Using custom rvalue converters. Boost.Python "rvalue converters"
match function signatures such as:
``
void foo(std::vector<double> const &array); // pass by const-reference
void foo(std::vector<double> array); // pass by value
``
Some custom rvalue converters are implemented in the file
`scitbx/include/scitbx/boost_python/container_conversions.h`
This code can be used to convert from C++ container types such as
`std::vector<>` or `std::list<>` to Python tuples and vice
versa. A few simple examples can be found in the file
`scitbx/array_family/boost_python/regression_test_module.cpp`
Automatic C++ container <-> Python tuple conversions are most
suitable for containers of moderate size. These converters generate
significantly less object code compared to alternative 1 above.
A disadvantage of using alternative 2 is that operators such as
arithmetic +,-,*,/,% are not available. It would be useful to have custom
rvalue converters that convert to a "math_array" type instead of tuples.
This is currently not implemented but is possible within the framework of
Boost.Python V2 as it will be released in the next couple of weeks. [ed.:
this was posted on 2002/03/10]
It would also be useful to also have "custom lvalue converters" such
as `std::vector<>` <-> Python list. These converters would
support the modification of the Python list from C++. For example:
C++:
``
void foo(std::vector<double> &array)
{
for(std::size_t i=0;i&lt;array.size();i++) {
array[i] *= 2;
}
}
``
Python: [python]
``
>>> l = [1, 2, 3]
>>> foo(l)
>>> print l
[2, 4, 6]
``
Custom lvalue converters require changes to the Boost.Python core library
and are currently not available.
P.S.:
The "scitbx" files referenced above are available via anonymous
CVS:
``
cvs -d:pserver:anonymous@cvs.cctbx.sourceforge.net:/cvsroot/cctbx login
cvs -d:pserver:anonymous@cvs.cctbx.sourceforge.net:/cvsroot/cctbx co scitbx
``
[endsect]
[section fatal error C1204:Compiler limit:internal structure overflow]
[*Q:] /I get this error message when compiling a large source file. What can I do?/
[*A:] You have two choices:
# Upgrade your compiler (preferred)
# Break your source file up into multiple translation units.
`my_module.cpp`: [c++]
``
...
void more_of_my_module();
BOOST_PYTHON_MODULE(my_module)
{
def("foo", foo);
def("bar", bar);
...
more_of_my_module();
}
``
`more_of_my_module.cpp`:
``
void more_of_my_module()
{
def("baz", baz);
...
}
``
If you find that a `class_<...>` declaration
can't fit in a single source file without triggering the error, you
can always pass a reference to the `class_` object to a
function in another source file, and call some of its member
functions (e.g. `.def(...)`) in the auxilliary source
file:
`more_of_my_class.cpp`:
``
void more_of_my_class(class&lt;my_class&gt;&amp; x)
{
x
.def("baz", baz)
.add_property("xx", &my_class::get_xx, &my_class::set_xx)
;
...
}
``
[endsect]
[section How do I debug my Python extensions?]
Greg Burley gives the following answer for Unix GCC users:
[:Once you have created a boost python extension for your c++ library or
class, you may need to debug the code. Afterall this is one of the
reasons for wrapping the library in python. An expected side-effect or
benefit of using BPL is that debugging should be isolated to the c++
library that is under test, given that python code is minimal and
boost::python either works or it doesn't. (ie. While errors can occur
when the wrapping method is invalid, most errors are caught by the
compiler ;-).
The basic steps required to initiate a gdb session to debug a c++
library via python are shown here. Note, however that you should start
the gdb session in the directory that contains your BPL my_ext.so
module.
``
(gdb) target exec python
(gdb) run
>>> from my_ext import *
>>> [C-c]
(gdb) break MyClass::MyBuggyFunction
(gdb) cont
>>> pyobj = MyClass()
>>> pyobj.MyBuggyFunction()
Breakpoint 1, MyClass::MyBuggyFunction ...
Current language: auto; currently c++
(gdb) do debugging stuff
``
]
Greg's approach works even better using Emacs' "gdb"
command, since it will show you each line of source as you step through it.
On *Windows*, my favorite debugging solution is the debugger that
comes with Microsoft Visual C++ 7. This debugger seems to work with code
generated by all versions of Microsoft and Metrowerks toolsets; it's rock
solid and "just works" without requiring any special tricks from the
user.
Raoul Gough has provided the following for gdb on Windows:
[:gdb support for Windows DLLs has improved lately, so it is
now possible to debug Python extensions using a few
tricks. Firstly, you will need an up-to-date gdb with support
for minimal symbol extraction from a DLL. Any gdb from version 6
onwards, or Cygwin gdb-20030214-1 and onwards should do. A
suitable release will have a section in the gdb.info file under
Configuration - Native - Cygwin Native -
Non-debug DLL symbols. Refer to that info section for more
details of the procedures outlined here.
Secondly, it seems necessary to set a breakpoint in the
Python interpreter, rather than using ^C to break execution. A
good place to set this breakpoint is PyOS_Readline, which will
stop execution immediately before reading each interactive
Python command. You have to let Python start once under the
debugger, so that it loads its own DLL, before you can set the
breakpoint:
``
$ gdb python
GNU gdb 2003-09-02-cvs (cygwin-special)
[...]
(gdb) run
Starting program: /cygdrive/c/Python22/python.exe
Python 2.2.2 (#37, Oct 14 2002, 17:02:34) [MSC 32 bit (Intel)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> ^Z
Program exited normally.
(gdb) break *&PyOS_Readline
Breakpoint 1 at 0x1e04eff0
(gdb) run
Starting program: /cygdrive/c/Python22/python.exe
Python 2.2.2 (#37, Oct 14 2002, 17:02:34) [MSC 32 bit (Intel)] on win32
Type "help", "copyright", "credits" or "license" for more information.
Breakpoint 1, 0x1e04eff0 in python22!PyOS_Readline ()
from /cygdrive/c/WINNT/system32/python22.dll
(gdb) cont
Continuing.
>>> from my_ext import *
Breakpoint 1, 0x1e04eff0 in python22!PyOS_Readline ()
from /cygdrive/c/WINNT/system32/python22.dll
(gdb) # my_ext now loaded (with any debugging symbols it contains)
``
]
[h2 Debugging extensions through Boost.Build]
If you are launching your extension module tests with _bb_ using the
`boost-python-runtest` rule, you can ask it to launch your
debugger for you by adding "--debugger=/debugger/" to your bjam
command-line:
``
bjam -sTOOLS=vc7.1 "--debugger=devenv /debugexe" test
bjam -sTOOLS=gcc -sPYTHON_LAUNCH=gdb test
``
It can also be extremely useful to add the `-d+2` option when
you run your test, because Boost.Build will then show you the exact
commands it uses to invoke it. This will invariably involve setting up
PYTHONPATH and other important environment variables such as
LD_LIBRARY_PATH which may be needed by your debugger in order to get
things to work right.
[endsect]
[section Why doesn't my `*=` operator work?]
[*Q:] ['I have exported my class to python, with many overloaded
operators. it works fine for me except the `*=`
operator. It always tells me "can't multiply sequence with non int
type". If I use `p1.__imul__(p2)` instead of
`p1 *= p2`, it successfully executes my code. What's
wrong with me?]
[*A:] There's nothing wrong with you. This is a bug in Python
2.2. You can see the same effect in Pure Python (you can learn a lot
about what's happening in Boost.Python by playing with new-style
classes in Pure Python).
``
>>> class X(object):
... def __imul__(self, x):
... print 'imul'
...
>>> x = X()
>>> x *= 1
``
To cure this problem, all you need to do is upgrade your Python to
version 2.2.1 or later.
[endsect]
[section Does Boost.Python work with Mac OS X?]
It is known to work under 10.2.8 and 10.3 using
Apple's gcc 3.3 compiler:
``gcc (GCC) 3.3 20030304 (Apple Computer, Inc. build 1493)``
Under 10.2.8 get the August 2003 gcc update (free at [@http://connect.apple.com]).
Under 10.3 get the Xcode Tools v1.0 (also free).
Python 2.3 is required. The Python that ships with 10.3 is
fine. Under 10.2.8 use these commands to install Python
as a framework:
``./configure --enable-framework
make
make frameworkinstall``
The last command requires root privileges because the target
directory is `/Library/Frameworks/Python.framework/Versions/2.3`.
However, the installation does not interfere with the Python
version that ships with 10.2.8.
It is also crucial to increase the `stacksize` before
starting compilations, e.g.:
``limit stacksize 8192k``
If the `stacksize` is too small the build might crash with
internal compiler errors.
Sometimes Apple's compiler exhibits a bug by printing an error
like the following while compiling a
`boost::python::class_<your_type>`
template instantiation:
``
.../inheritance.hpp:44: error: cannot
dynamic_cast `p' (of type `struct cctbx::boost_python::<unnamed>::add_pair*
') to type `void*' (source type is not polymorphic)
``
We do not know a general workaround, but if the definition of
`your_type` can be modified the following was found
to work in all cases encountered so far:
``
struct your_type
{
// before defining any member data
#if defined(__MACH__) &amp;&amp; defined(__APPLE_CC__) &amp;&amp; __APPLE_CC__ == 1493
bool dummy_;
#endif
// now your member data, e.g.
double x;
int j;
// etc.
};
``
[endsect]
[section How can I find the existing PyObject that holds a C++ object?]
[: "I am wrapping a function that always returns a pointer to an
already-held C++ object."]
One way to do that is to hijack the mechanisms used for wrapping a class
with virtual functions. If you make a wrapper class with an initial
PyObject* constructor argument and store that PyObject* as "self", you
can get back to it by casting down to that wrapper type in a thin wrapper
function. For example:
``
class X { X(int); virtual ~X(); ... };
X* f(); // known to return Xs that are managed by Python objects
// wrapping code
struct X_wrap : X
{
X_wrap(PyObject* self, int v) : self(self), X(v) {}
PyObject* self;
};
handle<> f_wrap()
{
X_wrap* xw = dynamic_cast<X_wrap*>(f());
assert(xw != 0);
return handle<>(borrowed(xw->self));
}
...
def("f", f_wrap());
class_<X,X_wrap,boost::noncopyable>("X", init<int>())
...
;
``
Of course, if X has no virtual functions you'll have to use
`static_cast` instead of `dynamic_cast` with no
runtime check that it's valid. This approach also only works if the
`X` object was constructed from Python, because
`X`\ s constructed from C++ are of course never
`X_wrap` objects.
Another approach to this requires you to change your C++ code a bit;
if that's an option for you it might be a better way to go. work we've
been meaning to get to anyway. When a `shared_ptr<X>` is
converted from Python, the shared_ptr actually manages a reference to the
containing Python object. When a shared_ptr<X> is converted back to
Python, the library checks to see if it's one of those "Python object
managers" and if so just returns the original Python object. So you could
just write `object(p)` to get the Python object back. To
exploit this you'd have to be able to change the C++ code you're wrapping
so that it deals with shared_ptr instead of raw pointers.
There are other approaches too. The functions that receive the Python
object that you eventually want to return could be wrapped with a thin
wrapper that records the correspondence between the object address and
its containing Python object, and you could have your f_wrap function
look in that mapping to get the Python object out.
[endsect]
[section How can I wrap a function which needs to take ownership of a raw pointer?]
[*Q:] Part of an API that I'm wrapping goes something like this:
``
struct A {}; struct B { void add( A* ); }
where B::add() takes ownership of the pointer passed to it.
``
However:
``
a = mod.A()
b = mod.B()
b.add( a )
del a
del b
# python interpreter crashes
# later due to memory corruption.
``
Even binding the lifetime of a to b via `with_custodian_and_ward` doesn't prevent
the python object a from ultimately trying to delete the object it's pointing to.
Is there a way to accomplish a 'transfer-of-ownership' of a wrapped C++ object?
--Bruce Lowery
Yes: Make sure the C++ object is held by auto_ptr:
``
class_<A, std::auto_ptr<A> >("A")
...
;
``
Then make a thin wrapper function which takes an auto_ptr parameter:
``
void b_insert(B &b, std::auto_ptr<A> a)
{
b.insert(a.get());
a.release();
}
``
Wrap that as B.add. Note that pointers returned via `manage_new_object`
will also be held by `auto_ptr`, so this transfer-of-ownership
will also work correctly.
[endsect]
[section Compilation takes too much time and eats too much memory!
What can I do to make it faster?]
Please refer to the `Reducing Compiling Time` section in the _tutorial_.
[endsect]
[section How do I create sub-packages using Boost.Python?]
Please refer to the `Creating Packages` section in the _tutorial_.
[endsect]
[section error C2064: term does not evaluate to a function taking 2 arguments]
/Niall Douglas provides these notes:/
If you see Microsoft Visual C++ 7.1 (MS Visual Studio .NET 2003) issue
an error message like the following it is most likely due to a bug
in the compiler:
``
boost\boost\python\detail\invoke.hpp(76):
error C2064: term does not evaluate to a function taking 2 arguments"
``
This message is triggered by code like the following:
``
#include <boost/python.hpp>
using namespace boost::python;
class FXThread
{
public:
bool setAutoDelete(bool doso) throw();
};
void Export_FXThread()
{
class_< FXThread >("FXThread")
.def("setAutoDelete", &amp;FXThread::setAutoDelete)
;
}
``
The bug is related to the `throw()` modifier.
As a workaround cast off the modifier. E.g.:
``
.def("setAutoDelete", (bool (FXThread::*)(bool)) &FXThread::setAutoDelete)
``
(The bug has been reported to Microsoft.)
[endsect]
[section How can I automatically convert my custom string type to and from a Python string?]
/Ralf W. Grosse-Kunstleve provides these notes:/
Below is a small, self-contained demo extension module that shows
how to do this. Here is the corresponding trivial test:
``
import custom_string
assert custom_string.hello() == "Hello world."
assert custom_string.size("california") == 10
``
If you look at the code you will find:
* A custom `to_python` converter (easy):
`custom_string_to_python_str`
*A custom lvalue converter (needs more code):
`custom_string_from_python_str`
The custom converters are registered in the global Boost.Python
registry near the top of the module initialization function. Once
flow control has passed through the registration code the automatic
conversions from and to Python strings will work in any module
imported in the same process.
``
#include <boost/python/module.hpp>
#include <boost/python/def.hpp>
#include <boost/python/to_python_converter.hpp>
namespace sandbox { namespace {
class custom_string
{
public:
custom_string() {}
custom_string(std::string const &value) : value_(value) {}
std::string const &value() const { return value_; }
private:
std::string value_;
};
struct custom_string_to_python_str
{
static PyObject* convert(custom_string const &s)
{
return boost::python::incref(boost::python::object(s.value()).ptr());
}
};
struct custom_string_from_python_str
{
custom_string_from_python_str()
{
boost::python::converter::registry::push_back(
&convertible,
&construct,
boost::python::type_id<custom_string>());
}
static void* convertible(PyObject* obj_ptr)
{
if (!PyString_Check(obj_ptr)) return 0;
return obj_ptr;
}
static void construct(
PyObject* obj_ptr,
boost::python::converter::rvalue_from_python_stage1_data* data)
{
const char* value = PyString_AsString(obj_ptr);
if (value == 0) boost::python::throw_error_already_set();
void* storage = (
(boost::python::converter::rvalue_from_python_storage<custom_string>*)
data)->storage.bytes;
new (storage) custom_string(value);
data->convertible = storage;
}
};
custom_string hello() { return custom_string("Hello world."); }
std::size_t size(custom_string const &s) { return s.value().size(); }
void init_module()
{
using namespace boost::python;
boost::python::to_python_converter<
custom_string,
custom_string_to_python_str>();
custom_string_from_python_str();
def("hello", hello);
def("size", size);
}
}} // namespace sandbox::<anonymous>
BOOST_PYTHON_MODULE(custom_string)
{
sandbox::init_module();
}
``
[endsect]
[section Why is my automatic to-python conversion not being found?]
/Niall Douglas provides these notes:/
If you define custom converters similar to the ones
shown above the `def_readonly()` and `def_readwrite()`
member functions provided by `boost::python::class_` for
direct access to your member data will not work as expected.
This is because `def_readonly("bar",&foo::bar)` is
equivalent to:
``
.add_property("bar", make_getter(&foo::bar, return_internal_reference()))
``
Similarly, `def_readwrite("bar",&foo::bar)` is
equivalent to:
``
.add_property("bar", make_getter(&foo::bar, return_internal_reference()),
make_setter(&foo::bar, return_internal_reference())
``
In order to define return value policies compatible with the
custom conversions replace `def_readonly()` and
`def_readwrite()` by `add_property()`. E.g.:
``
.add_property("bar", make_getter(&foo::bar, return_value_policy<return_by_value>()),
make_setter(&foo::bar, return_value_policy<return_by_value>()))
``
[endsect]
[section Is Boost.Python thread-aware/compatible with multiple interpreters?]
/Niall Douglas provides these notes:/
The quick answer to this is: no.
The longer answer is that it can be patched to be so, but it's
complex. You will need to add custom lock/unlock wrapping of every
time your code enters Boost.Python (particularly every virtual
function override) plus heavily modify
`boost/python/detail/invoke.hpp` with custom unlock/lock
wrapping of every time Boost.Python enters your code. You must
furthermore take care to /not/ unlock/lock when Boost.Python
is invoking iterator changes via `invoke.hpp`.
There is a patched `invoke.hpp` posted on the C++-SIG
mailing list archives and you can find a real implementation of all
the machinery necessary to fully implement this in the TnFOX
project at [@http://sourceforge.net/projects/tnfox/ this]
SourceForge project location.
[endsect]

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@@ -1,38 +0,0 @@
[chapter Glossary
[quickbook 1.7]
[id glossary]
]
[variablelist
[[arity [#arity]]
[The number of argumnts accepted by a function or member function.
Unless otherwise specified, the hidden `this` argument to member
functions is not counted when specifying arity.]]
[[ntbs [#ntbs]]
[Null-Terminated Byte String, or 'C'-string. C++ string literals are *ntbs*\ es.
An *ntbs* must never be null.]]
[[raise [#raise]]
[Exceptions in Python are "raised", not "thrown", as they are in C++.
When this documentation says that some Python exception is "raised" in
the context of C++ code, it means that the corresponding Python exception
is set via the [@http://www.python.org/doc/current/api/exceptionHandling.html Python/'C' API],
and `throw_error_already_set()` is called.]]
[[POD [#pod]]
[A technical term from the C++ standard. Short for "Plain Ol'Data":
A POD-struct is an aggregate class that has no non-static data members
of type pointer to member, non-POD-struct, non-POD-union (or array of such
types) or reference, and has no user-defined copy assign- ment operator and
no user-defined destructor. Similarly, a POD-union is an aggregate union that
has no non-static data members of type pointer to member, non-POD-struct,
non-POD-union (or array of such types) or reference, and has no
user-defined copy assignment operator and no user-defined destructor. A
POD class is a class that is either a POD-struct or a POD-union. An
aggregate is an array or a class (clause 9) with no user-declared
constructors (12.1), no private or protected non-static data members
(clause 11), no base classes (clause 10), and no virtual functions
(10.3).]]
[[ODR [#odr]]
[The "One Definition Rule", which says that any entity in a C++ program must have
the same definition in all translation units (object files) which make up a program.]]
]

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@@ -1,66 +0,0 @@
/*=============================================================================
Copyright 2002 William E. Kempf
Distributed under the Boost Software License, Version 1.0. (See accompany-
ing file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
=============================================================================*/
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.footnote
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TEXT-DECORATION: none;
}
.function-semantics
{
CLEAR: left;
}

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@@ -1,700 +0,0 @@
/*=============================================================================
Copyright (c) 2004 Joel de Guzman
http://spirit.sourceforge.net/
Copyright 2013 Niall Douglas additions for colors and alignment.
Copyright 2013 Paul A. Bristow additions for more colors and alignments.
Distributed under the Boost Software License, Version 1.0. (See accompany-
ing file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
=============================================================================*/
/*=============================================================================
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text-align: left
}
/*=============================================================================
Colors
=============================================================================*/
@media screen
{
body {
background-color: #FFFFFF;
color: #000000;
}
/* Syntax Highlighting */
.keyword { color: #0000AA; }
.identifier { color: #000000; }
.special { color: #707070; }
.preprocessor { color: #402080; }
.char { color: teal; }
.comment { color: #800000; }
.string { color: teal; }
.number { color: teal; }
.white_bkd { background-color: #FFFFFF; }
.dk_grey_bkd { background-color: #999999; }
/* Links */
a, a .keyword, a .identifier, a .special, a .preprocessor
a .char, a .comment, a .string, a .number
{
color: #005a9c;
}
a:visited, a:visited .keyword, a:visited .identifier,
a:visited .special, a:visited .preprocessor a:visited .char,
a:visited .comment, a:visited .string, a:visited .number
{
color: #9c5a9c;
}
h1 a, h2 a, h3 a, h4 a, h5 a, h6 a,
h1 a:hover, h2 a:hover, h3 a:hover, h4 a:hover, h5 a:hover, h6 a:hover,
h1 a:visited, h2 a:visited, h3 a:visited, h4 a:visited, h5 a:visited, h6 a:visited
{
text-decoration: none; /* no underline */
color: #000000;
}
/* Copyright, Legal Notice */
.copyright
{
color: #666666;
font-size: small;
}
div div.legalnotice p
{
color: #666666;
}
/* Program listing */
pre.synopsis
{
border: 1px solid #DCDCDC;
}
.programlisting,
.screen
{
border: 1px solid #DCDCDC;
}
td .programlisting,
td .screen
{
border: 0px solid #DCDCDC;
}
/* Blurbs */
div.note,
div.tip,
div.important,
div.caution,
div.warning,
p.blurb
{
border: 1px solid #DCDCDC;
}
/* Table of contents */
div.toc
{
border: 1px solid #DCDCDC;
}
/* Tables */
div.informaltable table tr td,
div.table table tr td
{
border: 1px solid #DCDCDC;
}
div.informaltable table tr th,
div.table table tr th
{
background-color: #F0F0F0;
border: 1px solid #DCDCDC;
}
.copyright-footer
{
color: #8F8F8F;
}
/* Misc */
span.highlight
{
color: #00A000;
}
}
@media print
{
/* Links */
a
{
color: black;
}
a:visited
{
color: black;
}
.spirit-nav
{
display: none;
}
/* Program listing */
pre.synopsis
{
border: 1px solid gray;
}
.programlisting,
.screen
{
border: 1px solid gray;
}
td .programlisting,
td .screen
{
border: 0px solid #DCDCDC;
}
/* Table of contents */
div.toc
{
border: 1px solid gray;
}
.informaltable table,
.table table
{
border: 1px solid gray;
border-collapse: collapse;
}
/* Tables */
div.informaltable table tr td,
div.table table tr td
{
border: 1px solid gray;
}
div.informaltable table tr th,
div.table table tr th
{
border: 1px solid gray;
}
table.simplelist tr td
{
border: none !important;
}
/* Misc */
span.highlight
{
font-weight: bold;
}
}
/*=============================================================================
Images
=============================================================================*/
span.inlinemediaobject img
{
vertical-align: middle;
}
/*==============================================================================
Super and Subscript: style so that line spacing isn't effected, see
http://www.adobe.com/cfusion/communityengine/index.cfm?event=showdetails&productId=1&postId=5341
==============================================================================*/
sup,
sub {
height: 0;
line-height: 1;
vertical-align: baseline;
position: relative;
}
/* For internet explorer: */
* html sup,
* html sub {
vertical-align: bottom;
}
sup {
bottom: 1ex;
}
sub {
top: .5ex;
}
/*==============================================================================
Indexes: pretty much the same as the TOC.
==============================================================================*/
.index
{
font-size: 80%;
padding-top: 0px;
padding-bottom: 0px;
margin-top: 0px;
margin-bottom: 0px;
margin-left: 0px;
}
.index ul
{
padding-left: 3em;
}
.index p
{
padding: 2px;
margin: 2px;
}
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{
font-weight: bold;
}
.index em
{
font-weight: bold;
}
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Alignment and coloring use 'role' feature, available from Quickbook 1.6 up.
Added from Niall Douglas for role color and alignment.
http://article.gmane.org/gmane.comp.lib.boost.devel/243318
*/
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span.aligncenter
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span.alignright
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/* alignleft is the default. */
span.alignleft
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display: inline-block; width: 100%; text-align: left;
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/* alignjustify stretches the word spacing so that each line has equal width
within a chosen fraction of page width (here arbitrarily 20%).
*Not* useful inside table items as the column width remains the total string width.
Nor very useful, except to temporarily restrict the width.
*/
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display: inline-block; width: 20%; text-align: justify;
}
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Names at http://www.w3.org/TR/2002/WD-css3-color-20020219/ 4.3. X11 color keywords.
Quickbook Usage: [role red Some red text]
*/
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span.green { color: green; }
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span.yellow { color: yellow; }
span.magenta { color: magenta; }
span.indigo { color: #4B0082; }
span.cyan { color: cyan; }
span.purple { color: purple; }
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margin-bottom: 1em }
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clear: right }
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font-size: medium }
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div.system-message {
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div.system-message p.system-message-title {
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div.topic {
margin: 2em }
h1.section-subtitle, h2.section-subtitle, h3.section-subtitle,
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h1.title {
text-align: center }
h2.subtitle {
text-align: center }
hr.docutils {
width: 75% }
img.align-left {
clear: left }
img.align-right {
clear: right }
ol.simple, ul.simple {
margin-bottom: 1em }
ol.arabic {
list-style: decimal }
ol.loweralpha {
list-style: lower-alpha }
ol.upperalpha {
list-style: upper-alpha }
ol.lowerroman {
list-style: lower-roman }
ol.upperroman {
list-style: upper-roman }
p.attribution {
text-align: right ;
margin-left: 50% }
p.caption {
font-style: italic }
p.credits {
font-style: italic ;
font-size: smaller }
p.label {
white-space: nowrap }
p.rubric {
font-weight: bold ;
font-size: larger ;
color: maroon ;
text-align: center }
p.sidebar-title {
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font-weight: bold ;
font-size: larger }
p.sidebar-subtitle {
font-family: sans-serif ;
font-weight: bold }
p.topic-title {
font-weight: bold }
pre.address {
margin-bottom: 0 ;
margin-top: 0 ;
font-family: serif ;
font-size: 100% }
pre.literal-block, pre.doctest-block {
margin-left: 2em ;
margin-right: 2em }
span.classifier {
font-family: sans-serif ;
font-style: oblique }
span.classifier-delimiter {
font-family: sans-serif ;
font-weight: bold }
span.interpreted {
font-family: sans-serif }
span.option {
white-space: nowrap }
span.pre {
white-space: pre }
span.problematic {
color: red }
span.section-subtitle {
/* font-size relative to parent (h1..h6 element) */
font-size: 80% }
table.citation {
border-left: solid 1px gray;
margin-left: 1px }
table.docinfo {
margin: 2em 4em }
table.docutils {
margin-top: 0.5em ;
margin-bottom: 0.5em }
table.footnote {
border-left: solid 1px black;
margin-left: 1px }
table.docutils td, table.docutils th,
table.docinfo td, table.docinfo th {
padding-left: 0.5em ;
padding-right: 0.5em ;
vertical-align: top }
table.docutils th.field-name, table.docinfo th.docinfo-name {
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text-align: left ;
white-space: nowrap ;
padding-left: 0 }
h1 tt.docutils, h2 tt.docutils, h3 tt.docutils,
h4 tt.docutils, h5 tt.docutils, h6 tt.docutils {
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