Browse Source

extracted from storm repo, refactored formula

refactoring
Sebastian Junges 8 years ago
commit
0c79aba2c7
  1. 64
      CMakeLists.txt
  2. 3
      lib/.gitignore
  3. 70
      lib/stormpy/__init__.py
  4. 2
      lib/stormpy/expressions/__init__.py
  5. 2
      lib/stormpy/info/__init__.py
  6. 2
      lib/stormpy/logic/__init__.py
  7. 3
      lib/stormpy/storage/__init__.py
  8. 36
      lib/stormpy/storage/action.py
  9. 34
      lib/stormpy/storage/state.py
  10. 32
      resources/pybind11/.appveyor.yml
  11. 35
      resources/pybind11/.gitignore
  12. 3
      resources/pybind11/.gitmodules
  13. 112
      resources/pybind11/.travis.yml
  14. 184
      resources/pybind11/CMakeLists.txt
  15. 37
      resources/pybind11/CONTRIBUTING.md
  16. 36
      resources/pybind11/LICENSE
  17. 2
      resources/pybind11/MANIFEST.in
  18. 123
      resources/pybind11/README.md
  19. 11
      resources/pybind11/docs/_static/theme_overrides.css
  20. 81
      resources/pybind11/docs/advanced/cast/chrono.rst
  21. 85
      resources/pybind11/docs/advanced/cast/custom.rst
  22. 50
      resources/pybind11/docs/advanced/cast/eigen.rst
  23. 113
      resources/pybind11/docs/advanced/cast/functional.rst
  24. 41
      resources/pybind11/docs/advanced/cast/index.rst
  25. 144
      resources/pybind11/docs/advanced/cast/overview.rst
  26. 154
      resources/pybind11/docs/advanced/cast/stl.rst
  27. 634
      resources/pybind11/docs/advanced/classes.rst
  28. 142
      resources/pybind11/docs/advanced/exceptions.rst
  29. 311
      resources/pybind11/docs/advanced/functions.rst
  30. 229
      resources/pybind11/docs/advanced/misc.rst
  31. 13
      resources/pybind11/docs/advanced/pycpp/index.rst
  32. 299
      resources/pybind11/docs/advanced/pycpp/numpy.rst
  33. 96
      resources/pybind11/docs/advanced/pycpp/object.rst
  34. 57
      resources/pybind11/docs/advanced/pycpp/utilities.rst
  35. 143
      resources/pybind11/docs/advanced/smart_ptrs.rst
  36. 287
      resources/pybind11/docs/basics.rst
  37. 90
      resources/pybind11/docs/benchmark.py
  38. 99
      resources/pybind11/docs/benchmark.rst
  39. 222
      resources/pybind11/docs/changelog.rst
  40. 410
      resources/pybind11/docs/classes.rst
  41. 53
      resources/pybind11/docs/compiling.rst
  42. 308
      resources/pybind11/docs/conf.py
  43. 251
      resources/pybind11/docs/faq.rst
  44. 45
      resources/pybind11/docs/index.rst
  45. 93
      resources/pybind11/docs/intro.rst
  46. 20
      resources/pybind11/docs/limitations.rst
  47. BIN
      resources/pybind11/docs/pybind11-logo.png
  48. BIN
      resources/pybind11/docs/pybind11_vs_boost_python1.png
  49. 427
      resources/pybind11/docs/pybind11_vs_boost_python1.svg
  50. BIN
      resources/pybind11/docs/pybind11_vs_boost_python2.png
  51. 427
      resources/pybind11/docs/pybind11_vs_boost_python2.svg
  52. 247
      resources/pybind11/docs/reference.rst
  53. 22
      resources/pybind11/docs/release.rst
  54. 362
      resources/pybind11/include/pybind11/attr.h
  55. 1464
      resources/pybind11/include/pybind11/cast.h
  56. 160
      resources/pybind11/include/pybind11/chrono.h
  57. 560
      resources/pybind11/include/pybind11/common.h
  58. 47
      resources/pybind11/include/pybind11/complex.h
  59. 177
      resources/pybind11/include/pybind11/descr.h
  60. 239
      resources/pybind11/include/pybind11/eigen.h
  61. 105
      resources/pybind11/include/pybind11/eval.h
  62. 79
      resources/pybind11/include/pybind11/functional.h
  63. 1169
      resources/pybind11/include/pybind11/numpy.h
  64. 154
      resources/pybind11/include/pybind11/operators.h
  65. 65
      resources/pybind11/include/pybind11/options.h
  66. 1735
      resources/pybind11/include/pybind11/pybind11.h
  67. 899
      resources/pybind11/include/pybind11/pytypes.h
  68. 256
      resources/pybind11/include/pybind11/stl.h
  69. 541
      resources/pybind11/include/pybind11/stl_bind.h
  70. 53
      resources/pybind11/include/pybind11/typeid.h
  71. 11
      resources/pybind11/pybind11/__init__.py
  72. 2
      resources/pybind11/pybind11/_version.py
  73. 11
      resources/pybind11/setup.cfg
  74. 74
      resources/pybind11/setup.py
  75. 111
      resources/pybind11/tests/CMakeLists.txt
  76. 227
      resources/pybind11/tests/conftest.py
  77. 249
      resources/pybind11/tests/constructor_stats.h
  78. 175
      resources/pybind11/tests/object.h
  79. 45
      resources/pybind11/tests/pybind11_tests.cpp
  80. 12
      resources/pybind11/tests/pybind11_tests.h
  81. 62
      resources/pybind11/tests/test_alias_initialization.cpp
  82. 79
      resources/pybind11/tests/test_alias_initialization.py
  83. 117
      resources/pybind11/tests/test_buffers.cpp
  84. 57
      resources/pybind11/tests/test_buffers.py
  85. 149
      resources/pybind11/tests/test_callbacks.cpp
  86. 98
      resources/pybind11/tests/test_callbacks.py
  87. 59
      resources/pybind11/tests/test_chrono.cpp
  88. 116
      resources/pybind11/tests/test_chrono.py
  89. 68
      resources/pybind11/tests/test_class_args.cpp
  90. 6
      resources/pybind11/tests/test_class_args.py
  91. 55
      resources/pybind11/tests/test_constants_and_functions.cpp
  92. 21
      resources/pybind11/tests/test_constants_and_functions.py
  93. 41
      resources/pybind11/tests/test_copy_move_policies.cpp
  94. 15
      resources/pybind11/tests/test_copy_move_policies.py
  95. 53
      resources/pybind11/tests/test_docstring_options.cpp
  96. 32
      resources/pybind11/tests/test_docstring_options.py
  97. 134
      resources/pybind11/tests/test_eigen.cpp
  98. 135
      resources/pybind11/tests/test_eigen.py
  99. 68
      resources/pybind11/tests/test_enum.cpp
  100. 108
      resources/pybind11/tests/test_enum.py

64
CMakeLists.txt

@ -0,0 +1,64 @@
cmake_minimum_required(VERSION 3.0.0)
project(pystorm)
find_package(storm REQUIRED)
add_subdirectory(resources/pybind11)
file(GLOB_RECURSE STORM_CORE_SOURCES ${CMAKE_CURRENT_SOURCE_DIR}/src/core/*.cpp)
pybind11_add_module(stormpy.core ${CMAKE_CURRENT_SOURCE_DIR}/src/mod_core.cpp ${STORM_CORE_SOURCES})
target_include_directories(stormpy.core PUBLIC ${CMAKE_CURRENT_SOURCE_DIR} ${storm_INCLUDE_DIR})
target_link_libraries(stormpy.core PRIVATE storm)
file(GLOB_RECURSE STORM_INFO_SOURCES ${CMAKE_CURRENT_SOURCE_DIR}/src/info/*.cpp)
pybind11_add_module(stormpy.info ${CMAKE_CURRENT_SOURCE_DIR}/src/mod_info.cpp ${STORM_INFO_SOURCES})
target_include_directories(stormpy.info PUBLIC ${CMAKE_CURRENT_SOURCE_DIR} ${storm_INCLUDE_DIR})
target_link_libraries(stormpy.info PRIVATE storm)
file(GLOB_RECURSE STORM_EXPRESSIONS_SOURCES ${CMAKE_CURRENT_SOURCE_DIR}/src/expressions/*.cpp)
pybind11_add_module(stormpy.expressions ${CMAKE_CURRENT_SOURCE_DIR}/src/mod_expressions.cpp ${STORM_EXPRESSIONS_SOURCES})
target_include_directories(stormpy.expressions PUBLIC ${CMAKE_CURRENT_SOURCE_DIR} ${storm_INCLUDE_DIR})
target_link_libraries(stormpy.expressions PRIVATE storm)
file(GLOB_RECURSE STORM_LOGIC_SOURCES ${CMAKE_CURRENT_SOURCE_DIR}/src/logic/*.cpp)
pybind11_add_module(stormpy.logic ${CMAKE_CURRENT_SOURCE_DIR}/src/mod_logic.cpp ${STORM_LOGIC_SOURCES})
target_include_directories(stormpy.logic PUBLIC ${CMAKE_CURRENT_SOURCE_DIR} ${storm_INCLUDE_DIR})
target_link_libraries(stormpy.logic PRIVATE storm)
file(GLOB_RECURSE STORM_STORAGE_SOURCES ${CMAKE_CURRENT_SOURCE_DIR}/src/storage/*.cpp)
pybind11_add_module(stormpy.storage ${CMAKE_CURRENT_SOURCE_DIR}/src/mod_storage.cpp ${STORM_STORAGE_SOURCES})
target_include_directories(stormpy.storage PUBLIC ${CMAKE_CURRENT_SOURCE_DIR} ${storm_INCLUDE_DIR})
target_link_libraries(stormpy.storage PRIVATE storm)
#set(STORMPY_OUTPUT_DIR "${PROJECT_BINARY_DIR}/stormpy")
#set(STORMPY_SOURCE_DIR "${PROJECT_SOURCE_DIR}/stormpy")
#
#if(STORM_HAVE_CLN)
# set(STORMPY_USE_CLN 1)
#else()
# set(STORMPY_USE_CLN 0)
#endif()
#
## Set configuration file
#get_directory_property(STORMPY_INCLUDE_DIRS_PROP INCLUDE_DIRECTORIES)
#foreach(arg ${STORMPY_INCLUDE_DIRS_PROP})
# set(STORMPY_INCLUDE_DIRS "${STORMPY_INCLUDE_DIRS}${sep}${arg}")
# set(sep ":")
#endforeach()
#set(STORMPY_COMPILE_ARGS ${CMAKE_CXX_FLAGS})
#set(STORMPY_LIBRARY_DIRS "${PROJECT_BINARY_DIR}/src/storm")
#set(STORMPY_RPATH "${PROJECT_BINARY_DIR}/src/storm")
#configure_file (
# "${PROJECT_SOURCE_DIR}/stormpy/setup.cfg.in"
# "${PROJECT_SOURCE_DIR}/stormpy/setup.cfg"
#)
#

3
lib/.gitignore

@ -0,0 +1,3 @@
*.so
__pycache__/
stormpy.egg-info/

70
lib/stormpy/__init__.py

@ -0,0 +1,70 @@
"""
It looks like you want to know about 'stormpy'.
_.-;:q=._
.' j=""^k;:\.
; .F ";`Y
,;.J_ ;'j
,-;"^7F : .F _________________
,-'-_<. ;gj. _.,---""'' .'
; _,._`\. : `T"5, ;
: `?8w7 `J ,-'" -^q. ` ;
\;._ _,=' ; n58L Y. .'
F;"; .' k_ `^' j' ;
J;:: ; "y:-=' ;
L;;== |:; jT\ ;
L;:;J J:L 7:;' _ ;
I;|:.L |:k J:.' , ' . ;
|;J:.| ;.I F.: . :
;J;:L:: |.| |.J , ' ` ; ;
.' J:`J.`. :.J |. L . ; ;
; L :k:`._ ,',j J; | ` , ; ;
.' I :`=.:."_".' L J `.'
.' |.: `"-=-' |.J ;
_.-' `: : ;:; _ ;
_.-'" J: : /.;' ; ;
='_ k;.\. _.;:Y' , .'
`"---..__ `Y;."-=';:=' , .'
`""--..__ `"==="' - .'
``""---...__ itz .-'
``""---'
"""
from . import core
from .core import *
from . import storage
from .storage import *
core.set_up("")
def build_model(program, formulae):
intermediate = core._build_model(program, formulae)
assert not intermediate.supports_parameters
if intermediate.model_type == ModelType.DTMC:
return intermediate.as_dtmc()
elif intermediate.model_type == ModelType.MDP:
return intermediate.as_mdp()
else:
raise RuntimeError("Not supported non-parametric model constructed")
def build_parametric_model(program, formulae):
intermediate = core._build_parametric_model(program, formulae)
assert intermediate.supports_parameters
if intermediate.model_type == ModelType.DTMC:
return intermediate.as_pdtmc()
elif intermediate.model_type == ModelType.MDP:
return intermediate.as_pmdp()
else:
raise RuntimeError("Not supported parametric model constructed")
def perform_bisimulation(model, formula, bisimulation_type):
if model.supports_parameters:
return core._perform_parametric_bisimulation(model, formula, bisimulation_type)
else:
return core._perform_bisimulation(model, formula, bisimulation_type)
def model_checking(model, formula):
if model.supports_parameters:
return core._parametric_model_checking(model, formula)
else:
return core._model_checking(model, formula)

2
lib/stormpy/expressions/__init__.py

@ -0,0 +1,2 @@
from . import expressions
from .expressions import *

2
lib/stormpy/info/__init__.py

@ -0,0 +1,2 @@
from . import info
from .info import *

2
lib/stormpy/logic/__init__.py

@ -0,0 +1,2 @@
from . import logic
from .logic import *

3
lib/stormpy/storage/__init__.py

@ -0,0 +1,3 @@
from . import storage
from .storage import *
from . import state,action

36
lib/stormpy/storage/action.py

@ -0,0 +1,36 @@
class Action:
""" Represents an action in the model """
def __init__(self, row_group_start, row_group_end, row, model):
""" Initialize
:param row_group_start: Start index of the row group in the matrix
:param row_group_end: End index of the row group in the matrix
:param row: Index of the corresponding row in the matrix
:param model: Corresponding model
"""
self.row_group_start = row_group_start
self.row_group_end = row_group_end
self.row = row - 1
self.model = model
assert row >= -1 and row + row_group_start <= row_group_end
def __iter__(self):
return self
def __next__(self):
if self.row + self.row_group_start >= self.row_group_end - 1:
raise StopIteration
else:
self.row += 1
return self
def __str__(self):
return "{}".format(self.row)
def transitions(self):
""" Get transitions associated with the action
:return List of tranistions
"""
row = self.row_group_start + self.row
#return self.model.transition_matrix().get_row(self.row_group_start + self.row)
return self.model.transition_matrix.row_iter(row, row)

34
lib/stormpy/storage/state.py

@ -0,0 +1,34 @@
from . import action
class State:
""" Represents a state in the model """
def __init__(self, id, model):
""" Initialize
:param id: Id of the state
:param model: Corresponding model
"""
self.id = id - 1
self.model = model
def __iter__(self):
return self
def __next__(self):
if self.id >= self.model.nr_states - 1:
raise StopIteration
else:
self.id += 1
return self
def __str__(self):
return "{}".format(self.id)
def actions(self):
""" Get actions associated with the state
:return List of actions
"""
row_group_indices = self.model.transition_matrix._row_group_indices
start = row_group_indices[self.id]
end = row_group_indices[self.id+1]
return action.Action(start, end, 0, self.model)

32
resources/pybind11/.appveyor.yml

@ -0,0 +1,32 @@
version: 1.0.{build}
os: Visual Studio 2015
test: off
platform:
- x86
- x64
environment:
matrix:
- CONDA: 27
- CONDA: 35
install:
- ps: |
if ($env:PLATFORM -eq "x64") { $env:CMAKE_ARCH = "x64" }
if ($env:PYTHON) {
if ($env:PLATFORM -eq "x64") { $env:PYTHON = "$env:PYTHON-x64" }
$env:PATH = "C:\Python$env:PYTHON\;C:\Python$env:PYTHON\Scripts\;$env:PATH"
pip install --disable-pip-version-check --user --upgrade pip wheel
pip install pytest numpy scipy
} elseif ($env:CONDA) {
if ($env:CONDA -eq "27") { $env:CONDA = "" }
if ($env:PLATFORM -eq "x64") { $env:CONDA = "$env:CONDA-x64" }
$env:PATH = "C:\Miniconda$env:CONDA\;C:\Miniconda$env:CONDA\Scripts\;$env:PATH"
conda install -y -q pytest numpy scipy
}
- ps: |
Start-FileDownload 'http://bitbucket.org/eigen/eigen/get/3.3.0.zip'
7z x 3.3.0.zip -y > $null
$env:CMAKE_INCLUDE_PATH = "eigen-eigen-26667be4f70b"
build_script:
- cmake -A "%CMAKE_ARCH%" -DPYBIND11_WERROR=ON
- set MSBuildLogger="C:\Program Files\AppVeyor\BuildAgent\Appveyor.MSBuildLogger.dll"
- cmake --build . --config Release --target pytest -- /v:m /logger:%MSBuildLogger%

35
resources/pybind11/.gitignore

@ -0,0 +1,35 @@
CMakeCache.txt
CMakeFiles
Makefile
cmake_install.cmake
.DS_Store
*.so
*.pyd
*.dll
*.sln
*.sdf
*.opensdf
*.vcxproj
*.filters
example.dir
Win32
x64
Release
Debug
.vs
CTestTestfile.cmake
Testing
autogen
MANIFEST
/.ninja_*
/*.ninja
/docs/.build
*.py[co]
*.egg-info
*~
.DS_Store
/dist
/build
/cmake/
.cache/
sosize-*.txt

3
resources/pybind11/.gitmodules

@ -0,0 +1,3 @@
[submodule "tools/clang"]
path = tools/clang
url = https://github.com/wjakob/clang-cindex-python3

112
resources/pybind11/.travis.yml

@ -0,0 +1,112 @@
language: cpp
sudo: false
matrix:
include:
- os: linux
env: PYTHON=2.7 CPP=11 GCC=4.8
addons:
apt:
sources: [ubuntu-toolchain-r-test, kubuntu-backports]
packages: [g++-4.8, cmake]
- os: linux
env: PYTHON=3.5 CPP=11 GCC=4.8
addons:
apt:
sources: [ubuntu-toolchain-r-test, kubuntu-backports, deadsnakes]
packages: [g++-4.8, cmake, python3.5-dev]
- sudo: true
services: docker
env: PYTHON=2.7 CPP=14 GCC=6
- sudo: true
services: docker
env: PYTHON=3.5 CPP=14 GCC=6 DEBUG=1
- os: osx
osx_image: xcode7.3
env: PYTHON=2.7 CPP=14 CLANG
- os: osx
osx_image: xcode7.3
env: PYTHON=3.5 CPP=14 CLANG
# A barebones build makes sure everything still works without optional deps (numpy/scipy/eigen)
# and also tests the automatic discovery functions in CMake (Python version, C++ standard).
- os: linux
env: BAREBONES
addons:
apt:
sources: [ubuntu-toolchain-r-test, kubuntu-backports]
packages: [g++-4.8, cmake]
install: pip install pytest
# Documentation build:
- os: linux
language: docs
env: DOCS STYLE LINT
install: pip install sphinx sphinx_rtd_theme flake8 pep8-naming
script:
- make -C docs html SPHINX_OPTIONS=-W
- tools/check-style.sh
- flake8
cache:
directories:
- $HOME/.cache/pip
- $HOME/Library/Caches/pip
before_install:
- |
# Configure build variables
if [ "$TRAVIS_OS_NAME" = "linux" ]; then
if [ -z "$GCC" ]; then export GCC=4.8; fi
export CXX=g++-$GCC CC=gcc-$GCC;
if [ "$GCC" = "6" ]; then export DOCKER=debian:testing CXX=g++ CC=gcc; fi
elif [ "$TRAVIS_OS_NAME" = "osx" ]; then
export CXX=clang++ CC=clang;
fi
if [ -n "$CPP" ]; then export CPP=-std=c++$CPP; fi
if [ "${PYTHON:0:1}" = "3" ]; then export PY=3; fi
if [ -n "$DEBUG" ]; then export CMAKE_EXTRA_ARGS="-DCMAKE_BUILD_TYPE=Debug"; fi
- |
# Initialize enviornment
if [ -n "$DOCKER" ]; then
docker pull $DOCKER
export containerid=$(docker run --detach --tty \
--volume="$PWD":/pybind11 --workdir=/pybind11 \
--env="CC=$CC" --env="CXX=$CXX" --env="DEBIAN_FRONTEND=$DEBIAN_FRONTEND" \
--env=GCC_COLORS=\ \
$DOCKER)
docker exec --tty "$containerid" sh -c 'for s in 0 15; do sleep $s; apt-get update && apt-get -qy dist-upgrade && break; done'
export SCRIPT_RUN_PREFIX="docker exec --tty $containerid"
else
if [ "$TRAVIS_OS_NAME" = "linux" ]; then
pip install --user --upgrade pip virtualenv
virtualenv -p python$PYTHON venv
elif [ "$TRAVIS_OS_NAME" = "osx" ]; then
if [ "$PY" = "3" ]; then
brew update; brew install python$PY;
else
curl -fsSL -O https://bootstrap.pypa.io/get-pip.py
sudo -H python get-pip.py
fi
pip$PY install --user --upgrade pip virtualenv
python$PY -m virtualenv venv
fi
source venv/bin/activate
fi
install:
- |
# Install dependencies
if [ -n "$DOCKER" ]; then
docker exec --tty "$containerid" sh -c "for s in 0 15; do sleep \$s; apt-get -qy --no-install-recommends install \
python$PYTHON-dev python$PY-pytest python$PY-scipy \
libeigen3-dev cmake make g++ && break; done"
else
pip install numpy scipy pytest
wget -q -O eigen.tar.gz https://bitbucket.org/eigen/eigen/get/3.3.0.tar.gz
tar xzf eigen.tar.gz
export CMAKE_EXTRA_ARGS="${CMAKE_EXTRA_ARGS} -DCMAKE_INCLUDE_PATH=$PWD/eigen-eigen-26667be4f70b"
fi
script:
- $SCRIPT_RUN_PREFIX cmake ${CMAKE_EXTRA_ARGS}
-DPYBIND11_PYTHON_VERSION=$PYTHON
-DPYBIND11_CPP_STANDARD=$CPP
-DPYBIND11_WERROR=ON
- $SCRIPT_RUN_PREFIX make pytest -j 2
after_script:
- if [ -n "$DOCKER" ]; then docker stop "$containerid"; docker rm "$containerid"; fi

184
resources/pybind11/CMakeLists.txt

@ -0,0 +1,184 @@
# CMakeLists.txt -- Build system for the pybind11 modules
#
# Copyright (c) 2015 Wenzel Jakob <wenzel@inf.ethz.ch>
#
# All rights reserved. Use of this source code is governed by a
# BSD-style license that can be found in the LICENSE file.
cmake_minimum_required(VERSION 2.8.12)
project(pybind11)
# Check if pybind11 is being used directly or via add_subdirectory
set(PYBIND11_MASTER_PROJECT OFF)
if (CMAKE_CURRENT_SOURCE_DIR STREQUAL CMAKE_SOURCE_DIR)
set(PYBIND11_MASTER_PROJECT ON)
endif()
option(PYBIND11_INSTALL "Install pybind11 header files?" ${PYBIND11_MASTER_PROJECT})
option(PYBIND11_TEST "Build pybind11 test suite?" ${PYBIND11_MASTER_PROJECT})
option(PYBIND11_WERROR "Report all warnings as errors" OFF)
# Add a CMake parameter for choosing a desired Python version
set(PYBIND11_PYTHON_VERSION "" CACHE STRING "Python version to use for compiling modules")
list(APPEND CMAKE_MODULE_PATH "${CMAKE_CURRENT_LIST_DIR}/tools")
set(Python_ADDITIONAL_VERSIONS 3.4 3.5 3.6 3.7)
find_package(PythonLibsNew ${PYBIND11_PYTHON_VERSION} REQUIRED)
include(CheckCXXCompilerFlag)
if(NOT MSVC AND NOT PYBIND11_CPP_STANDARD)
check_cxx_compiler_flag("-std=c++14" HAS_CPP14_FLAG)
check_cxx_compiler_flag("-std=c++11" HAS_CPP11_FLAG)
if (HAS_CPP14_FLAG)
set(PYBIND11_CPP_STANDARD -std=c++14)
elseif (HAS_CPP11_FLAG)
set(PYBIND11_CPP_STANDARD -std=c++11)
else()
message(FATAL_ERROR "Unsupported compiler -- pybind11 requires C++11 support!")
endif()
set(PYBIND11_CPP_STANDARD ${PYBIND11_CPP_STANDARD} CACHE STRING
"C++ standard flag, e.g. -std=c++11 or -std=c++14. Defaults to latest available." FORCE)
endif()
# Cache variables so pybind11_add_module can be used in parent projects
set(PYBIND11_INCLUDE_DIR "${CMAKE_CURRENT_LIST_DIR}/include" CACHE INTERNAL "")
set(PYTHON_INCLUDE_DIRS ${PYTHON_INCLUDE_DIRS} CACHE INTERNAL "")
set(PYTHON_LIBRARIES ${PYTHON_LIBRARIES} CACHE INTERNAL "")
set(PYTHON_MODULE_PREFIX ${PYTHON_MODULE_PREFIX} CACHE INTERNAL "")
set(PYTHON_MODULE_EXTENSION ${PYTHON_MODULE_EXTENSION} CACHE INTERNAL "")
# Build a Python extension module:
# pybind11_add_module(<name> source1 [source2 ...])
#
function(pybind11_add_module target_name)
add_library(${target_name} MODULE ${ARGN})
target_include_directories(${target_name}
PRIVATE ${PYBIND11_INCLUDE_DIR}
PRIVATE ${PYTHON_INCLUDE_DIRS})
# The prefix and extension are provided by FindPythonLibsNew.cmake
set_target_properties(${target_name} PROPERTIES PREFIX "${PYTHON_MODULE_PREFIX}")
set_target_properties(${target_name} PROPERTIES SUFFIX "${PYTHON_MODULE_EXTENSION}")
if(WIN32 OR CYGWIN)
# Link against the Python shared library on Windows
target_link_libraries(${target_name} PRIVATE ${PYTHON_LIBRARIES})
elseif(APPLE)
# It's quite common to have multiple copies of the same Python version
# installed on one's system. E.g.: one copy from the OS and another copy
# that's statically linked into an application like Blender or Maya.
# If we link our plugin library against the OS Python here and import it
# into Blender or Maya later on, this will cause segfaults when multiple
# conflicting Python instances are active at the same time (even when they
# are of the same version).
# Windows is not affected by this issue since it handles DLL imports
# differently. The solution for Linux and Mac OS is simple: we just don't
# link against the Python library. The resulting shared library will have
# missing symbols, but that's perfectly fine -- they will be resolved at
# import time.
target_link_libraries(${target_name} PRIVATE "-undefined dynamic_lookup")
endif()
if(NOT MSVC)
# Make sure C++11/14 are enabled
target_compile_options(${target_name} PUBLIC ${PYBIND11_CPP_STANDARD})
# Enable link time optimization and set the default symbol
# visibility to hidden (very important to obtain small binaries)
string(TOUPPER "${CMAKE_BUILD_TYPE}" U_CMAKE_BUILD_TYPE)
if (NOT ${U_CMAKE_BUILD_TYPE} MATCHES DEBUG)
# Check for Link Time Optimization support (GCC/Clang)
check_cxx_compiler_flag("-flto" HAS_LTO_FLAG)
if(HAS_LTO_FLAG AND NOT CYGWIN)
target_compile_options(${target_name} PRIVATE -flto)
endif()
# Intel equivalent to LTO is called IPO
if(CMAKE_CXX_COMPILER_ID MATCHES "Intel")
check_cxx_compiler_flag("-ipo" HAS_IPO_FLAG)
if(HAS_IPO_FLAG)
target_compile_options(${target_name} PRIVATE -ipo)
endif()
endif()
# Default symbol visibility
target_compile_options(${target_name} PRIVATE "-fvisibility=hidden")
# Strip unnecessary sections of the binary on Linux/Mac OS
if(CMAKE_STRIP)
if(APPLE)
add_custom_command(TARGET ${target_name} POST_BUILD
COMMAND ${CMAKE_STRIP} -u -r $<TARGET_FILE:${target_name}>)
else()
add_custom_command(TARGET ${target_name} POST_BUILD
COMMAND ${CMAKE_STRIP} $<TARGET_FILE:${target_name}>)
endif()
endif()
endif()
elseif(MSVC)
# /MP enables multithreaded builds (relevant when there are many files), /bigobj is
# needed for bigger binding projects due to the limit to 64k addressable sections
target_compile_options(${target_name} PRIVATE /MP /bigobj)
# Enforce link time code generation on MSVC, except in debug mode
target_compile_options(${target_name} PRIVATE $<$<NOT:$<CONFIG:Debug>>:/GL>)
# Fancy generator expressions don't work with linker flags, for reasons unknown
set_property(TARGET ${target_name} APPEND_STRING PROPERTY LINK_FLAGS_RELEASE /LTCG)
set_property(TARGET ${target_name} APPEND_STRING PROPERTY LINK_FLAGS_MINSIZEREL /LTCG)
set_property(TARGET ${target_name} APPEND_STRING PROPERTY LINK_FLAGS_RELWITHDEBINFO /LTCG)
endif()
endfunction()
# Compile with compiler warnings turned on
function(pybind11_enable_warnings target_name)
if(MSVC)
target_compile_options(${target_name} PRIVATE /W4)
else()
target_compile_options(${target_name} PRIVATE -Wall -Wextra -Wconversion)
endif()
if(PYBIND11_WERROR)
if(MSVC)
target_compile_options(${target_name} PRIVATE /WX)
else()
target_compile_options(${target_name} PRIVATE -Werror)
endif()
endif()
endfunction()
set(PYBIND11_HEADERS
include/pybind11/attr.h
include/pybind11/cast.h
include/pybind11/chrono.h
include/pybind11/common.h
include/pybind11/complex.h
include/pybind11/descr.h
include/pybind11/options.h
include/pybind11/eigen.h
include/pybind11/eval.h
include/pybind11/functional.h
include/pybind11/numpy.h
include/pybind11/operators.h
include/pybind11/pybind11.h
include/pybind11/pytypes.h
include/pybind11/stl.h
include/pybind11/stl_bind.h
include/pybind11/typeid.h
)
string(REPLACE "include/" "${CMAKE_CURRENT_SOURCE_DIR}/include/"
PYBIND11_HEADERS "${PYBIND11_HEADERS}")
if (PYBIND11_TEST)
add_subdirectory(tests)
endif()
if (PYBIND11_INSTALL)
install(FILES ${PYBIND11_HEADERS} DESTINATION include/pybind11)
endif()

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Thank you for your interest in this project! Please refer to the following
sections on how to contribute code and bug reports.
### Reporting bugs
At the moment, this project is run in the spare time of a single person
([Wenzel Jakob](http://rgl.epfl.ch/people/wjakob)) with very limited resources
for issue tracker tickets. Thus, before submitting a question or bug report,
please take a moment of your time and ensure that your issue isn't already
discussed in the project documentation provided at
[http://pybind11.readthedocs.org/en/latest](http://pybind11.readthedocs.org/en/latest).
Assuming that you have identified a previously unknown problem or an important
question, it's essential that you submit a self-contained and minimal piece of
code that reproduces the problem. In other words: no external dependencies,
isolate the function(s) that cause breakage, submit matched and complete C++
and Python snippets that can be easily compiled and run on my end.
## Pull requests
Contributions are submitted, reviewed, and accepted using Github pull requests.
Please refer to [this
article](https://help.github.com/articles/using-pull-requests) for details and
adhere to the following rules to make the process as smooth as possible:
* Make a new branch for every feature you're working on.
* Make small and clean pull requests that are easy to review but make sure they
do add value by themselves.
* Add tests for any new functionality and run the test suite (``make pytest``)
to ensure that no existing features break.
* This project has a strong focus on providing general solutions using a
minimal amount of code, thus small pull requests are greatly preferred.
### License
pybind11 is provided under a BSD-style license that can be found in the
``LICENSE`` file. By using, distributing, or contributing to this project, you
agree to the terms and conditions of this license.

36
resources/pybind11/LICENSE

@ -0,0 +1,36 @@
Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>, All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
1. Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
3. Neither the name of the copyright holder nor the names of its contributors
may be used to endorse or promote products derived from this software
without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
You are under no obligation whatsoever to provide any bug fixes, patches, or
upgrades to the features, functionality or performance of the source code
("Enhancements") to anyone; however, if you choose to make your Enhancements
available either publicly, or directly to the author of this software, without
imposing a separate written license agreement for such Enhancements, then you
hereby grant the following license: a non-exclusive, royalty-free perpetual
license to install, use, modify, prepare derivative works, incorporate into
other computer software, distribute, and sublicense such enhancements or
derivative works thereof, in binary and source code form.

2
resources/pybind11/MANIFEST.in

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include include/pybind11/*.h
include LICENSE README.md CONTRIBUTING.md

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resources/pybind11/README.md

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![pybind11 logo](https://github.com/pybind/pybind11/raw/master/docs/pybind11-logo.png)
# pybind11 — Seamless operability between C++11 and Python
[![Documentation Status](https://readthedocs.org/projects/pybind11/badge/?version=latest)](http://pybind11.readthedocs.org/en/latest/?badge=latest)
[![Build Status](https://travis-ci.org/pybind/pybind11.svg?branch=master)](https://travis-ci.org/pybind/pybind11)
[![Build status](https://ci.appveyor.com/api/projects/status/riaj54pn4h08xy40?svg=true)](https://ci.appveyor.com/project/wjakob/pybind11)
**pybind11** is a lightweight header-only library that exposes C++ types in Python
and vice versa, mainly to create Python bindings of existing C++ code. Its
goals and syntax are similar to the excellent
[Boost.Python](http://www.boost.org/doc/libs/1_58_0/libs/python/doc/) library
by David Abrahams: to minimize boilerplate code in traditional extension
modules by inferring type information using compile-time introspection.
The main issue with Boost.Python—and the reason for creating such a similar
project—is Boost. Boost is an enormously large and complex suite of utility
libraries that works with almost every C++ compiler in existence. This
compatibility has its cost: arcane template tricks and workarounds are
necessary to support the oldest and buggiest of compiler specimens. Now that
C++11-compatible compilers are widely available, this heavy machinery has
become an excessively large and unnecessary dependency.
Think of this library as a tiny self-contained version of Boost.Python with
everything stripped away that isn't relevant for binding generation. Without
comments, the core header files only require ~2.5K lines of code and depend on
Python (2.7 or 3.x) and the C++ standard library. This compact implementation
was possible thanks to some of the new C++11 language features (specifically:
tuples, lambda functions and variadic templates). Since its creation, this
library has grown beyond Boost.Python in many ways, leading to dramatically
simpler binding code in many common situations.
Tutorial and reference documentation is provided at
[http://pybind11.readthedocs.org/en/latest](http://pybind11.readthedocs.org/en/latest).
A PDF version of the manual is available
[here](https://media.readthedocs.org/pdf/pybind11/latest/pybind11.pdf).
## Core features
pybind11 can map the following core C++ features to Python
- Functions accepting and returning custom data structures per value, reference, or pointer
- Instance methods and static methods
- Overloaded functions
- Instance attributes and static attributes
- Arbitrary exception types
- Enumerations
- Callbacks
- Iterators and ranges
- Custom operators
- Single and multiple inheritance
- STL data structures
- Iterators and ranges
- Smart pointers with reference counting like ``std::shared_ptr``
- Internal references with correct reference counting
- C++ classes with virtual (and pure virtual) methods can be extended in Python
## Goodies
In addition to the core functionality, pybind11 provides some extra goodies:
- pybind11 uses C++11 move constructors and move assignment operators whenever
possible to efficiently transfer custom data types.
- It is possible to bind C++11 lambda functions with captured variables. The
lambda capture data is stored inside the resulting Python function object.
- It's easy to expose the internal storage of custom data types through
Pythons' buffer protocols. This is handy e.g. for fast conversion between
C++ matrix classes like Eigen and NumPy without expensive copy operations.
- pybind11 can automatically vectorize functions so that they are transparently
applied to all entries of one or more NumPy array arguments.
- Python's slice-based access and assignment operations can be supported with
just a few lines of code.
- Everything is contained in just a few header files; there is no need to link
against any additional libraries.
- Binaries are generally smaller by a factor of at least 2 compared to
equivalent bindings generated by Boost.Python. A recent pybind11 conversion
of PyRosetta, an enormous Boost.Python binding project,
[reported](http://graylab.jhu.edu/RosettaCon2016/PyRosetta-4.pdf) a binary
size reduction of **5.4x** and compile time reduction by **5.8x**.
- When supported by the compiler, two new C++14 features (relaxed constexpr and
return value deduction) are used to precompute function signatures at compile
time, leading to smaller binaries.
- With little extra effort, C++ types can be pickled and unpickled similar to
regular Python objects.
## Supported compilers
1. Clang/LLVM (any non-ancient version with C++11 support)
2. GCC (any non-ancient version with C++11 support)
3. Microsoft Visual Studio 2015 or newer
4. Intel C++ compiler 16 or newer (15 with a [workaround](https://github.com/pybind/pybind11/issues/276))
5. Cygwin/GCC (tested on 2.5.1)
## About
This project was created by [Wenzel Jakob](https://www.mitsuba-renderer.org/~wenzel/).
Significant features and/or improvements to the code were contributed by
Jonas Adler,
Sylvain Corlay,
Trent Houliston,
Axel Huebl,
@hulucc,
Sergey Lyskov
Johan Mabille,
Tomasz Miąsko,
Dean Moldovan,
Ben Pritchard,
Jason Rhinelander,
Boris Schäling,
Pim Schellart, and
Ivan Smirnov.
### License
pybind11 is provided under a BSD-style license that can be found in the
``LICENSE`` file. By using, distributing, or contributing to this project,
you agree to the terms and conditions of this license.

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.wy-table-responsive table td,
.wy-table-responsive table th {
white-space: initial !important;
}
.rst-content table.docutils td {
vertical-align: top !important;
}
div[class^='highlight'] pre {
white-space: pre;
white-space: pre-wrap;
}

81
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Chrono
======
When including the additional header file :file:`pybind11/chrono.h` conversions
from C++11 chrono datatypes to python datetime objects are automatically enabled.
This header also enables conversions of python floats (often from sources such
as `time.monotonic()`, `time.perf_counter()` and `time.process_time()`) into
durations.
An overview of clocks in C++11
------------------------------
A point of confusion when using these conversions is the differences between
clocks provided in C++11. There are three clock types defined by the C++11
standard and users can define their own if needed. Each of these clocks have
different properties and when converting to and from python will give different
results.
The first clock defined by the standard is ``std::chrono::system_clock``. This
clock measures the current date and time. However, this clock changes with to
updates to the operating system time. For example, if your time is synchronised
with a time server this clock will change. This makes this clock a poor choice
for timing purposes but good for measuring the wall time.
The second clock defined in the standard is ``std::chrono::steady_clock``.
This clock ticks at a steady rate and is never adjusted. This makes it excellent
for timing purposes, however the value in this clock does not correspond to the
current date and time. Often this clock will be the amount of time your system
has been on, although it does not have to be. This clock will never be the same
clock as the system clock as the system clock can change but steady clocks
cannot.
The third clock defined in the standard is ``std::chrono::high_resolution_clock``.
This clock is the clock that has the highest resolution out of the clocks in the
system. It is normally a typedef to either the system clock or the steady clock
but can be its own independent clock. This is important as when using these
conversions as the types you get in python for this clock might be different
depending on the system.
If it is a typedef of the system clock, python will get datetime objects, but if
it is a different clock they will be timedelta objects.
Provided conversions
--------------------
.. rubric:: C++ to Python
- ``std::chrono::system_clock::time_point````datetime.datetime``
System clock times are converted to python datetime instances. They are
in the local timezone, but do not have any timezone information attached
to them (they are naive datetime objects).
- ``std::chrono::duration````datetime.timedelta``
Durations are converted to timedeltas, any precision in the duration
greater than microseconds is lost by rounding towards zero.
- ``std::chrono::[other_clocks]::time_point````datetime.timedelta``
Any clock time that is not the system clock is converted to a time delta.
This timedelta measures the time from the clocks epoch to now.
.. rubric:: Python to C++
- ``datetime.datetime````std::chrono::system_clock::time_point``
Date/time objects are converted into system clock timepoints. Any
timezone information is ignored and the type is treated as a naive
object.
- ``datetime.timedelta````std::chrono::duration``
Time delta are converted into durations with microsecond precision.
- ``datetime.timedelta````std::chrono::[other_clocks]::time_point``
Time deltas that are converted into clock timepoints are treated as
the amount of time from the start of the clocks epoch.
- ``float````std::chrono::duration``
Floats that are passed to C++ as durations be interpreted as a number of
seconds. These will be converted to the duration using ``duration_cast``
from the float.
- ``float````std::chrono::[other_clocks]::time_point``
Floats that are passed to C++ as time points will be interpreted as the
number of seconds from the start of the clocks epoch.

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Custom type casters
===================
In very rare cases, applications may require custom type casters that cannot be
expressed using the abstractions provided by pybind11, thus requiring raw
Python C API calls. This is fairly advanced usage and should only be pursued by
experts who are familiar with the intricacies of Python reference counting.
The following snippets demonstrate how this works for a very simple ``inty``
type that that should be convertible from Python types that provide a
``__int__(self)`` method.
.. code-block:: cpp
struct inty { long long_value; };
void print(inty s) {
std::cout << s.long_value << std::endl;
}
The following Python snippet demonstrates the intended usage from the Python side:
.. code-block:: python
class A:
def __int__(self):
return 123
from example import print
print(A())
To register the necessary conversion routines, it is necessary to add
a partial overload to the ``pybind11::detail::type_caster<T>`` template.
Although this is an implementation detail, adding partial overloads to this
type is explicitly allowed.
.. code-block:: cpp
namespace pybind11 { namespace detail {
template <> struct type_caster<inty> {
public:
/**
* This macro establishes the name 'inty' in
* function signatures and declares a local variable
* 'value' of type inty
*/
PYBIND11_TYPE_CASTER(inty, _("inty"));
/**
* Conversion part 1 (Python->C++): convert a PyObject into a inty
* instance or return false upon failure. The second argument
* indicates whether implicit conversions should be applied.
*/
bool load(handle src, bool) {
/* Extract PyObject from handle */
PyObject *source = src.ptr();
/* Try converting into a Python integer value */
PyObject *tmp = PyNumber_Long(source);
if (!tmp)
return false;
/* Now try to convert into a C++ int */
value.long_value = PyLong_AsLong(tmp);
Py_DECREF(tmp);
/* Ensure return code was OK (to avoid out-of-range errors etc) */
return !(value.long_value == -1 && !PyErr_Occurred());
}
/**
* Conversion part 2 (C++ -> Python): convert an inty instance into
* a Python object. The second and third arguments are used to
* indicate the return value policy and parent object (for
* ``return_value_policy::reference_internal``) and are generally
* ignored by implicit casters.
*/
static handle cast(inty src, return_value_policy /* policy */, handle /* parent */) {
return PyLong_FromLong(src.long_value);
}
};
}} // namespace pybind11::detail
.. warning::
When using custom type casters, it's important to declare them consistently
in every compilation unit of the Python extension module. Otherwise,
undefined behavior can ensue.

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Eigen
=====
`Eigen <http://eigen.tuxfamily.org>`_ is C++ header-based library for dense and
sparse linear algebra. Due to its popularity and widespread adoption, pybind11
provides transparent conversion support between Eigen and Scientific Python linear
algebra data types.
Specifically, when including the optional header file :file:`pybind11/eigen.h`,
pybind11 will automatically and transparently convert
1. Static and dynamic Eigen dense vectors and matrices to instances of
``numpy.ndarray`` (and vice versa).
2. Returned matrix expressions such as blocks (including columns or rows) and
diagonals will be converted to ``numpy.ndarray`` of the expression
values.
3. Returned matrix-like objects such as Eigen::DiagonalMatrix or
Eigen::SelfAdjointView will be converted to ``numpy.ndarray`` containing the
expressed value.
4. Eigen sparse vectors and matrices to instances of
``scipy.sparse.csr_matrix``/``scipy.sparse.csc_matrix`` (and vice versa).
This makes it possible to bind most kinds of functions that rely on these types.
One major caveat are functions that take Eigen matrices *by reference* and modify
them somehow, in which case the information won't be propagated to the caller.
.. code-block:: cpp
/* The Python bindings of these functions won't replicate
the intended effect of modifying the function arguments */
void scale_by_2(Eigen::Vector3f &v) {
v *= 2;
}
void scale_by_2(Eigen::Ref<Eigen::MatrixXd> &v) {
v *= 2;
}
To see why this is, refer to the section on :ref:`opaque` (although that
section specifically covers STL data types, the underlying issue is the same).
The :ref:`numpy` sections discuss an efficient alternative for exposing the
underlying native Eigen types as opaque objects in a way that still integrates
with NumPy and SciPy.
.. seealso::
The file :file:`tests/test_eigen.cpp` contains a complete example that
shows how to pass Eigen sparse and dense data types in more detail.

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Functional
##########
The following features must be enabled by including :file:`pybind11/functional.h`.
Callbacks and passing anonymous functions
=========================================
The C++11 standard brought lambda functions and the generic polymorphic
function wrapper ``std::function<>`` to the C++ programming language, which
enable powerful new ways of working with functions. Lambda functions come in
two flavors: stateless lambda function resemble classic function pointers that
link to an anonymous piece of code, while stateful lambda functions
additionally depend on captured variables that are stored in an anonymous
*lambda closure object*.
Here is a simple example of a C++ function that takes an arbitrary function
(stateful or stateless) with signature ``int -> int`` as an argument and runs
it with the value 10.
.. code-block:: cpp
int func_arg(const std::function<int(int)> &f) {
return f(10);
}
The example below is more involved: it takes a function of signature ``int -> int``
and returns another function of the same kind. The return value is a stateful
lambda function, which stores the value ``f`` in the capture object and adds 1 to
its return value upon execution.
.. code-block:: cpp
std::function<int(int)> func_ret(const std::function<int(int)> &f) {
return [f](int i) {
return f(i) + 1;
};
}
This example demonstrates using python named parameters in C++ callbacks which
requires using ``py::cpp_function`` as a wrapper. Usage is similar to defining
methods of classes:
.. code-block:: cpp
py::cpp_function func_cpp() {
return py::cpp_function([](int i) { return i+1; },
py::arg("number"));
}
After including the extra header file :file:`pybind11/functional.h`, it is almost
trivial to generate binding code for all of these functions.
.. code-block:: cpp
#include <pybind11/functional.h>
PYBIND11_PLUGIN(example) {
py::module m("example", "pybind11 example plugin");
m.def("func_arg", &func_arg);
m.def("func_ret", &func_ret);
m.def("func_cpp", &func_cpp);
return m.ptr();
}
The following interactive session shows how to call them from Python.
.. code-block:: pycon
$ python
>>> import example
>>> def square(i):
... return i * i
...
>>> example.func_arg(square)
100L
>>> square_plus_1 = example.func_ret(square)
>>> square_plus_1(4)
17L
>>> plus_1 = func_cpp()
>>> plus_1(number=43)
44L
.. warning::
Keep in mind that passing a function from C++ to Python (or vice versa)
will instantiate a piece of wrapper code that translates function
invocations between the two languages. Naturally, this translation
increases the computational cost of each function call somewhat. A
problematic situation can arise when a function is copied back and forth
between Python and C++ many times in a row, in which case the underlying
wrappers will accumulate correspondingly. The resulting long sequence of
C++ -> Python -> C++ -> ... roundtrips can significantly decrease
performance.
There is one exception: pybind11 detects case where a stateless function
(i.e. a function pointer or a lambda function without captured variables)
is passed as an argument to another C++ function exposed in Python. In this
case, there is no overhead. Pybind11 will extract the underlying C++
function pointer from the wrapped function to sidestep a potential C++ ->
Python -> C++ roundtrip. This is demonstrated in :file:`tests/test_callbacks.cpp`.
.. note::
This functionality is very useful when generating bindings for callbacks in
C++ libraries (e.g. GUI libraries, asynchronous networking libraries, etc.).
The file :file:`tests/test_callbacks.cpp` contains a complete example
that demonstrates how to work with callbacks and anonymous functions in
more detail.

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Type conversions
################
Apart from enabling cross-language function calls, a fundamental problem
that a binding tool like pybind11 must address is to provide access to
native Python types in C++ and vice versa. There are three fundamentally
different ways to do this—which approach is preferable for a particular type
depends on the situation at hand.
1. Use a native C++ type everywhere. In this case, the type must be wrapped
using pybind11-generated bindings so that Python can interact with it.
2. Use a native Python type everywhere. It will need to be wrapped so that
C++ functions can interact with it.
3. Use a native C++ type on the C++ side and a native Python type on the
Python side. pybind11 refers to this as a *type conversion*.
Type conversions are the most "natural" option in the sense that native
(non-wrapped) types are used everywhere. The main downside is that a copy
of the data must be made on every Python ↔ C++ transition: this is
needed since the C++ and Python versions of the same type generally won't
have the same memory layout.
pybind11 can perform many kinds of conversions automatically. An overview
is provided in the table ":ref:`conversion_table`".
The following subsections discuss the differences between these options in more
detail. The main focus in this section is on type conversions, which represent
the last case of the above list.
.. toctree::
:maxdepth: 1
overview
stl
functional
chrono
eigen
custom

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Overview
########
.. rubric:: 1. Native type in C++, wrapper in Python
Exposing a custom C++ type using :class:`py::class_` was covered in detail
in the :doc:`/classes` section. There, the underlying data structure is
always the original C++ class while the :class:`py::class_` wrapper provides
a Python interface. Internally, when an object like this is sent from C++ to
Python, pybind11 will just add the outer wrapper layer over the native C++
object. Getting it back from Python is just a matter of peeling off the
wrapper.
.. rubric:: 2. Wrapper in C++, native type in Python
This is the exact opposite situation. Now, we have a type which is native to
Python, like a ``tuple`` or a ``list``. One way to get this data into C++ is
with the :class:`py::object` family of wrappers. These are explained in more
detail in the :doc:`/advanced/pycpp/object` section. We'll just give a quick
example here:
.. code-block:: cpp
void print_list(py::list my_list) {
for (auto item : my_list)
std::cout << item << " ";
}
.. code-block:: pycon
>>> print_list([1, 2, 3])
1 2 3
The Python ``list`` is not converted in any way -- it's just wrapped in a C++
:class:`py::list` class. At its core it's still a Python object. Copying a
:class:`py::list` will do the usual reference-counting like in Python.
Returning the object to Python will just remove the thin wrapper.
.. rubric:: 3. Converting between native C++ and Python types
In the previous two cases we had a native type in one language and a wrapper in
the other. Now, we have native types on both sides and we convert between them.
.. code-block:: cpp
void print_vector(const std::vector<int> &v) {
for (auto item : v)
std::cout << item << "\n";
}
.. code-block:: pycon
>>> print_vector([1, 2, 3])
1 2 3
In this case, pybind11 will construct a new ``std::vector<int>`` and copy each
element from the Python ``list``. The newly constructed object will be passed
to ``print_vector``. The same thing happens in the other direction: a new
``list`` is made to match the value returned from C++.
Lots of these conversions are supported out of the box, as shown in the table
below. They are very convenient, but keep in mind that these conversions are
fundamentally based on copying data. This is perfectly fine for small immutable
types but it may become quite expensive for large data structures. This can be
avoided by overriding the automatic conversion with a custom wrapper (i.e. the
above-mentioned approach 1). This requires some manual effort and more details
are available in the :ref:`opaque` section.
.. _conversion_table:
List of all builtin conversions
-------------------------------
The following basic data types are supported out of the box (some may require
an additional extension header to be included). To pass other data structures
as arguments and return values, refer to the section on binding :ref:`classes`.
+------------------------------------+---------------------------+-------------------------------+
| Data type | Description | Header file |
+====================================+===========================+===============================+
| ``int8_t``, ``uint8_t`` | 8-bit integers | :file:`pybind11/pybind11.h` |
+------------------------------------+---------------------------+-------------------------------+
| ``int16_t``, ``uint16_t`` | 16-bit integers | :file:`pybind11/pybind11.h` |
+------------------------------------+---------------------------+-------------------------------+
| ``int32_t``, ``uint32_t`` | 32-bit integers | :file:`pybind11/pybind11.h` |
+------------------------------------+---------------------------+-------------------------------+
| ``int64_t``, ``uint64_t`` | 64-bit integers | :file:`pybind11/pybind11.h` |
+------------------------------------+---------------------------+-------------------------------+
| ``ssize_t``, ``size_t`` | Platform-dependent size | :file:`pybind11/pybind11.h` |
+------------------------------------+---------------------------+-------------------------------+
| ``float``, ``double`` | Floating point types | :file:`pybind11/pybind11.h` |
+------------------------------------+---------------------------+-------------------------------+
| ``bool`` | Two-state Boolean type | :file:`pybind11/pybind11.h` |
+------------------------------------+---------------------------+-------------------------------+
| ``char`` | Character literal | :file:`pybind11/pybind11.h` |
+------------------------------------+---------------------------+-------------------------------+
| ``wchar_t`` | Wide character literal | :file:`pybind11/pybind11.h` |
+------------------------------------+---------------------------+-------------------------------+
| ``const char *`` | UTF-8 string literal | :file:`pybind11/pybind11.h` |
+------------------------------------+---------------------------+-------------------------------+
| ``const wchar_t *`` | Wide string literal | :file:`pybind11/pybind11.h` |
+------------------------------------+---------------------------+-------------------------------+
| ``std::string`` | STL dynamic UTF-8 string | :file:`pybind11/pybind11.h` |
+------------------------------------+---------------------------+-------------------------------+
| ``std::wstring`` | STL dynamic wide string | :file:`pybind11/pybind11.h` |
+------------------------------------+---------------------------+-------------------------------+
| ``std::pair<T1, T2>`` | Pair of two custom types | :file:`pybind11/pybind11.h` |
+------------------------------------+---------------------------+-------------------------------+
| ``std::tuple<...>`` | Arbitrary tuple of types | :file:`pybind11/pybind11.h` |
+------------------------------------+---------------------------+-------------------------------+
| ``std::reference_wrapper<...>`` | Reference type wrapper | :file:`pybind11/pybind11.h` |
+------------------------------------+---------------------------+-------------------------------+
| ``std::complex<T>`` | Complex numbers | :file:`pybind11/complex.h` |
+------------------------------------+---------------------------+-------------------------------+
| ``std::array<T, Size>`` | STL static array | :file:`pybind11/stl.h` |
+------------------------------------+---------------------------+-------------------------------+
| ``std::vector<T>`` | STL dynamic array | :file:`pybind11/stl.h` |
+------------------------------------+---------------------------+-------------------------------+
| ``std::list<T>`` | STL linked list | :file:`pybind11/stl.h` |
+------------------------------------+---------------------------+-------------------------------+
| ``std::map<T1, T2>`` | STL ordered map | :file:`pybind11/stl.h` |
+------------------------------------+---------------------------+-------------------------------+
| ``std::unordered_map<T1, T2>`` | STL unordered map | :file:`pybind11/stl.h` |
+------------------------------------+---------------------------+-------------------------------+
| ``std::set<T>`` | STL ordered set | :file:`pybind11/stl.h` |
+------------------------------------+---------------------------+-------------------------------+
| ``std::unordered_set<T>`` | STL unordered set | :file:`pybind11/stl.h` |
+------------------------------------+---------------------------+-------------------------------+
| ``std::optional<T>`` | STL optional type (C++17) | :file:`pybind11/stl.h` |
+------------------------------------+---------------------------+-------------------------------+
| ``std::experimental::optional<T>`` | STL optional type (exp.) | :file:`pybind11/stl.h` |
+------------------------------------+---------------------------+-------------------------------+
| ``std::function<...>`` | STL polymorphic function | :file:`pybind11/functional.h` |
+------------------------------------+---------------------------+-------------------------------+
| ``std::chrono::duration<...>`` | STL time duration | :file:`pybind11/chrono.h` |
+------------------------------------+---------------------------+-------------------------------+
| ``std::chrono::time_point<...>`` | STL date/time | :file:`pybind11/chrono.h` |
+------------------------------------+---------------------------+-------------------------------+
| ``Eigen::Matrix<...>`` | Eigen: dense matrix | :file:`pybind11/eigen.h` |
+------------------------------------+---------------------------+-------------------------------+
| ``Eigen::Map<...>`` | Eigen: mapped memory | :file:`pybind11/eigen.h` |
+------------------------------------+---------------------------+-------------------------------+
| ``Eigen::SparseMatrix<...>`` | Eigen: sparse matrix | :file:`pybind11/eigen.h` |
+------------------------------------+---------------------------+-------------------------------+

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STL containers
##############
Automatic conversion
====================
When including the additional header file :file:`pybind11/stl.h`, conversions
between ``std::vector<>``, ``std::list<>``, ``std::set<>``, and ``std::map<>``
and the Python ``list``, ``set`` and ``dict`` data structures are automatically
enabled. The types ``std::pair<>`` and ``std::tuple<>`` are already supported
out of the box with just the core :file:`pybind11/pybind11.h` header.
The major downside of these implicit conversions is that containers must be
converted (i.e. copied) on every Python->C++ and C++->Python transition, which
can have implications on the program semantics and performance. Please read the
next sections for more details and alternative approaches that avoid this.
.. note::
Arbitrary nesting of any of these types is possible.
.. seealso::
The file :file:`tests/test_python_types.cpp` contains a complete
example that demonstrates how to pass STL data types in more detail.
.. _opaque:
Making opaque types
===================
pybind11 heavily relies on a template matching mechanism to convert parameters
and return values that are constructed from STL data types such as vectors,
linked lists, hash tables, etc. This even works in a recursive manner, for
instance to deal with lists of hash maps of pairs of elementary and custom
types, etc.
However, a fundamental limitation of this approach is that internal conversions
between Python and C++ types involve a copy operation that prevents
pass-by-reference semantics. What does this mean?
Suppose we bind the following function
.. code-block:: cpp
void append_1(std::vector<int> &v) {
v.push_back(1);
}
and call it from Python, the following happens:
.. code-block:: pycon
>>> v = [5, 6]
>>> append_1(v)
>>> print(v)
[5, 6]
As you can see, when passing STL data structures by reference, modifications
are not propagated back the Python side. A similar situation arises when
exposing STL data structures using the ``def_readwrite`` or ``def_readonly``
functions:
.. code-block:: cpp
/* ... definition ... */
class MyClass {
std::vector<int> contents;
};
/* ... binding code ... */
py::class_<MyClass>(m, "MyClass")
.def(py::init<>)
.def_readwrite("contents", &MyClass::contents);
In this case, properties can be read and written in their entirety. However, an
``append`` operation involving such a list type has no effect:
.. code-block:: pycon
>>> m = MyClass()
>>> m.contents = [5, 6]
>>> print(m.contents)
[5, 6]
>>> m.contents.append(7)
>>> print(m.contents)
[5, 6]
Finally, the involved copy operations can be costly when dealing with very
large lists. To deal with all of the above situations, pybind11 provides a
macro named ``PYBIND11_MAKE_OPAQUE(T)`` that disables the template-based
conversion machinery of types, thus rendering them *opaque*. The contents of
opaque objects are never inspected or extracted, hence they *can* be passed by
reference. For instance, to turn ``std::vector<int>`` into an opaque type, add
the declaration
.. code-block:: cpp
PYBIND11_MAKE_OPAQUE(std::vector<int>);
before any binding code (e.g. invocations to ``class_::def()``, etc.). This
macro must be specified at the top level (and outside of any namespaces), since
it instantiates a partial template overload. If your binding code consists of
multiple compilation units, it must be present in every file preceding any
usage of ``std::vector<int>``. Opaque types must also have a corresponding
``class_`` declaration to associate them with a name in Python, and to define a
set of available operations, e.g.:
.. code-block:: cpp
py::class_<std::vector<int>>(m, "IntVector")
.def(py::init<>())
.def("clear", &std::vector<int>::clear)
.def("pop_back", &std::vector<int>::pop_back)
.def("__len__", [](const std::vector<int> &v) { return v.size(); })
.def("__iter__", [](std::vector<int> &v) {
return py::make_iterator(v.begin(), v.end());
}, py::keep_alive<0, 1>()) /* Keep vector alive while iterator is used */
// ....
The ability to expose STL containers as native Python objects is a fairly
common request, hence pybind11 also provides an optional header file named
:file:`pybind11/stl_bind.h` that does exactly this. The mapped containers try
to match the behavior of their native Python counterparts as much as possible.
The following example showcases usage of :file:`pybind11/stl_bind.h`:
.. code-block:: cpp
// Don't forget this
#include <pybind11/stl_bind.h>
PYBIND11_MAKE_OPAQUE(std::vector<int>);
PYBIND11_MAKE_OPAQUE(std::map<std::string, double>);
// ...
// later in binding code:
py::bind_vector<std::vector<int>>(m, "VectorInt");
py::bind_map<std::map<std::string, double>>(m, "MapStringDouble");
Please take a look at the :ref:`macro_notes` before using the
``PYBIND11_MAKE_OPAQUE`` macro.
.. seealso::
The file :file:`tests/test_opaque_types.cpp` contains a complete
example that demonstrates how to create and expose opaque types using
pybind11 in more detail.
The file :file:`tests/test_stl_binders.cpp` shows how to use the
convenience STL container wrappers.

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Classes
#######
This section presents advanced binding code for classes and it is assumed
that you are already familiar with the basics from :doc:`/classes`.
.. _overriding_virtuals:
Overriding virtual functions in Python
======================================
Suppose that a C++ class or interface has a virtual function that we'd like to
to override from within Python (we'll focus on the class ``Animal``; ``Dog`` is
given as a specific example of how one would do this with traditional C++
code).
.. code-block:: cpp
class Animal {
public:
virtual ~Animal() { }
virtual std::string go(int n_times) = 0;
};
class Dog : public Animal {
public:
std::string go(int n_times) override {
std::string result;
for (int i=0; i<n_times; ++i)
result += "woof! ";
return result;
}
};
Let's also suppose that we are given a plain function which calls the
function ``go()`` on an arbitrary ``Animal`` instance.
.. code-block:: cpp
std::string call_go(Animal *animal) {
return animal->go(3);
}
Normally, the binding code for these classes would look as follows:
.. code-block:: cpp
PYBIND11_PLUGIN(example) {
py::module m("example", "pybind11 example plugin");
py::class_<Animal> animal(m, "Animal");
animal
.def("go", &Animal::go);
py::class_<Dog>(m, "Dog", animal)
.def(py::init<>());
m.def("call_go", &call_go);
return m.ptr();
}
However, these bindings are impossible to extend: ``Animal`` is not
constructible, and we clearly require some kind of "trampoline" that
redirects virtual calls back to Python.
Defining a new type of ``Animal`` from within Python is possible but requires a
helper class that is defined as follows:
.. code-block:: cpp
class PyAnimal : public Animal {
public:
/* Inherit the constructors */
using Animal::Animal;
/* Trampoline (need one for each virtual function) */
std::string go(int n_times) override {
PYBIND11_OVERLOAD_PURE(
std::string, /* Return type */
Animal, /* Parent class */
go, /* Name of function */
n_times /* Argument(s) */
);
}
};
The macro :func:`PYBIND11_OVERLOAD_PURE` should be used for pure virtual
functions, and :func:`PYBIND11_OVERLOAD` should be used for functions which have
a default implementation. There are also two alternate macros
:func:`PYBIND11_OVERLOAD_PURE_NAME` and :func:`PYBIND11_OVERLOAD_NAME` which
take a string-valued name argument between the *Parent class* and *Name of the
function* slots. This is useful when the C++ and Python versions of the
function have different names, e.g. ``operator()`` vs ``__call__``.
The binding code also needs a few minor adaptations (highlighted):
.. code-block:: cpp
:emphasize-lines: 4,6,7
PYBIND11_PLUGIN(example) {
py::module m("example", "pybind11 example plugin");
py::class_<Animal, PyAnimal /* <--- trampoline*/> animal(m, "Animal");
animal
.def(py::init<>())
.def("go", &Animal::go);
py::class_<Dog>(m, "Dog", animal)
.def(py::init<>());
m.def("call_go", &call_go);
return m.ptr();
}
Importantly, pybind11 is made aware of the trampoline helper class by
specifying it as an extra template argument to :class:`class_`. (This can also
be combined with other template arguments such as a custom holder type; the
order of template types does not matter). Following this, we are able to
define a constructor as usual.
Note, however, that the above is sufficient for allowing python classes to
extend ``Animal``, but not ``Dog``: see ref:`virtual_and_inheritance` for the
necessary steps required to providing proper overload support for inherited
classes.
The Python session below shows how to override ``Animal::go`` and invoke it via
a virtual method call.
.. code-block:: pycon
>>> from example import *
>>> d = Dog()
>>> call_go(d)
u'woof! woof! woof! '
>>> class Cat(Animal):
... def go(self, n_times):
... return "meow! " * n_times
...
>>> c = Cat()
>>> call_go(c)
u'meow! meow! meow! '
Please take a look at the :ref:`macro_notes` before using this feature.
.. note::
When the overridden type returns a reference or pointer to a type that
pybind11 converts from Python (for example, numeric values, std::string,
and other built-in value-converting types), there are some limitations to
be aware of:
- because in these cases there is no C++ variable to reference (the value
is stored in the referenced Python variable), pybind11 provides one in
the PYBIND11_OVERLOAD macros (when needed) with static storage duration.
Note that this means that invoking the overloaded method on *any*
instance will change the referenced value stored in *all* instances of
that type.
- Attempts to modify a non-const reference will not have the desired
effect: it will change only the static cache variable, but this change
will not propagate to underlying Python instance, and the change will be
replaced the next time the overload is invoked.
.. seealso::
The file :file:`tests/test_virtual_functions.cpp` contains a complete
example that demonstrates how to override virtual functions using pybind11
in more detail.
.. _virtual_and_inheritance:
Combining virtual functions and inheritance
===========================================
When combining virtual methods with inheritance, you need to be sure to provide
an override for each method for which you want to allow overrides from derived
python classes. For example, suppose we extend the above ``Animal``/``Dog``
example as follows:
.. code-block:: cpp
class Animal {
public:
virtual std::string go(int n_times) = 0;
virtual std::string name() { return "unknown"; }
};
class Dog : public class Animal {
public:
std::string go(int n_times) override {
std::string result;
for (int i=0; i<n_times; ++i)
result += bark() + " ";
return result;
}
virtual std::string bark() { return "woof!"; }
};
then the trampoline class for ``Animal`` must, as described in the previous
section, override ``go()`` and ``name()``, but in order to allow python code to
inherit properly from ``Dog``, we also need a trampoline class for ``Dog`` that
overrides both the added ``bark()`` method *and* the ``go()`` and ``name()``
methods inherited from ``Animal`` (even though ``Dog`` doesn't directly
override the ``name()`` method):
.. code-block:: cpp
class PyAnimal : public Animal {
public:
using Animal::Animal; // Inherit constructors
std::string go(int n_times) override { PYBIND11_OVERLOAD_PURE(std::string, Animal, go, n_times); }
std::string name() override { PYBIND11_OVERLOAD(std::string, Animal, name, ); }
};
class PyDog : public Dog {
public:
using Dog::Dog; // Inherit constructors
std::string go(int n_times) override { PYBIND11_OVERLOAD_PURE(std::string, Dog, go, n_times); }
std::string name() override { PYBIND11_OVERLOAD(std::string, Dog, name, ); }
std::string bark() override { PYBIND11_OVERLOAD(std::string, Dog, bark, ); }
};
A registered class derived from a pybind11-registered class with virtual
methods requires a similar trampoline class, *even if* it doesn't explicitly
declare or override any virtual methods itself:
.. code-block:: cpp
class Husky : public Dog {};
class PyHusky : public Husky {
using Dog::Dog; // Inherit constructors
std::string go(int n_times) override { PYBIND11_OVERLOAD_PURE(std::string, Husky, go, n_times); }
std::string name() override { PYBIND11_OVERLOAD(std::string, Husky, name, ); }
std::string bark() override { PYBIND11_OVERLOAD(std::string, Husky, bark, ); }
};
There is, however, a technique that can be used to avoid this duplication
(which can be especially helpful for a base class with several virtual
methods). The technique involves using template trampoline classes, as
follows:
.. code-block:: cpp
template <class AnimalBase = Animal> class PyAnimal : public AnimalBase {
using AnimalBase::AnimalBase; // Inherit constructors
std::string go(int n_times) override { PYBIND11_OVERLOAD_PURE(std::string, AnimalBase, go, n_times); }
std::string name() override { PYBIND11_OVERLOAD(std::string, AnimalBase, name, ); }
};
template <class DogBase = Dog> class PyDog : public PyAnimal<DogBase> {
using PyAnimal<DogBase>::PyAnimal; // Inherit constructors
// Override PyAnimal's pure virtual go() with a non-pure one:
std::string go(int n_times) override { PYBIND11_OVERLOAD(std::string, DogBase, go, n_times); }
std::string bark() override { PYBIND11_OVERLOAD(std::string, DogBase, bark, ); }
};
This technique has the advantage of requiring just one trampoline method to be
declared per virtual method and pure virtual method override. It does,
however, require the compiler to generate at least as many methods (and
possibly more, if both pure virtual and overridden pure virtual methods are
exposed, as above).
The classes are then registered with pybind11 using:
.. code-block:: cpp
py::class_<Animal, PyAnimal<>> animal(m, "Animal");
py::class_<Dog, PyDog<>> dog(m, "Dog");
py::class_<Husky, PyDog<Husky>> husky(m, "Husky");
// ... add animal, dog, husky definitions
Note that ``Husky`` did not require a dedicated trampoline template class at
all, since it neither declares any new virtual methods nor provides any pure
virtual method implementations.
With either the repeated-virtuals or templated trampoline methods in place, you
can now create a python class that inherits from ``Dog``:
.. code-block:: python
class ShihTzu(Dog):
def bark(self):
return "yip!"
.. seealso::
See the file :file:`tests/test_virtual_functions.cpp` for complete examples
using both the duplication and templated trampoline approaches.
Extended trampoline class functionality
=======================================
The trampoline classes described in the previous sections are, by default, only
initialized when needed. More specifically, they are initialized when a python
class actually inherits from a registered type (instead of merely creating an
instance of the registered type), or when a registered constructor is only
valid for the trampoline class but not the registered class. This is primarily
for performance reasons: when the trampoline class is not needed for anything
except virtual method dispatching, not initializing the trampoline class
improves performance by avoiding needing to do a run-time check to see if the
inheriting python instance has an overloaded method.
Sometimes, however, it is useful to always initialize a trampoline class as an
intermediate class that does more than just handle virtual method dispatching.
For example, such a class might perform extra class initialization, extra
destruction operations, and might define new members and methods to enable a
more python-like interface to a class.
In order to tell pybind11 that it should *always* initialize the trampoline
class when creating new instances of a type, the class constructors should be
declared using ``py::init_alias<Args, ...>()`` instead of the usual
``py::init<Args, ...>()``. This forces construction via the trampoline class,
ensuring member initialization and (eventual) destruction.
.. seealso::
See the file :file:`tests/test_alias_initialization.cpp` for complete examples
showing both normal and forced trampoline instantiation.
.. _custom_constructors:
Custom constructors
===================
The syntax for binding constructors was previously introduced, but it only
works when a constructor with the given parameters actually exists on the C++
side. To extend this to more general cases, let's take a look at what actually
happens under the hood: the following statement
.. code-block:: cpp
py::class_<Example>(m, "Example")
.def(py::init<int>());
is short hand notation for
.. code-block:: cpp
py::class_<Example>(m, "Example")
.def("__init__",
[](Example &instance, int arg) {
new (&instance) Example(arg);
}
);
In other words, :func:`init` creates an anonymous function that invokes an
in-place constructor. Memory allocation etc. is already take care of beforehand
within pybind11.
.. _classes_with_non_public_destructors:
Non-public destructors
======================
If a class has a private or protected destructor (as might e.g. be the case in
a singleton pattern), a compile error will occur when creating bindings via
pybind11. The underlying issue is that the ``std::unique_ptr`` holder type that
is responsible for managing the lifetime of instances will reference the
destructor even if no deallocations ever take place. In order to expose classes
with private or protected destructors, it is possible to override the holder
type via a holder type argument to ``class_``. Pybind11 provides a helper class
``py::nodelete`` that disables any destructor invocations. In this case, it is
crucial that instances are deallocated on the C++ side to avoid memory leaks.
.. code-block:: cpp
/* ... definition ... */
class MyClass {
private:
~MyClass() { }
};
/* ... binding code ... */
py::class_<MyClass, std::unique_ptr<MyClass, py::nodelete>>(m, "MyClass")
.def(py::init<>)
Implicit conversions
====================
Suppose that instances of two types ``A`` and ``B`` are used in a project, and
that an ``A`` can easily be converted into an instance of type ``B`` (examples of this
could be a fixed and an arbitrary precision number type).
.. code-block:: cpp
py::class_<A>(m, "A")
/// ... members ...
py::class_<B>(m, "B")
.def(py::init<A>())
/// ... members ...
m.def("func",
[](const B &) { /* .... */ }
);
To invoke the function ``func`` using a variable ``a`` containing an ``A``
instance, we'd have to write ``func(B(a))`` in Python. On the other hand, C++
will automatically apply an implicit type conversion, which makes it possible
to directly write ``func(a)``.
In this situation (i.e. where ``B`` has a constructor that converts from
``A``), the following statement enables similar implicit conversions on the
Python side:
.. code-block:: cpp
py::implicitly_convertible<A, B>();
.. note::
Implicit conversions from ``A`` to ``B`` only work when ``B`` is a custom
data type that is exposed to Python via pybind11.
.. _static_properties:
Static properties
=================
The section on :ref:`properties` discussed the creation of instance properties
that are implemented in terms of C++ getters and setters.
Static properties can also be created in a similar way to expose getters and
setters of static class attributes. It is important to note that the implicit
``self`` argument also exists in this case and is used to pass the Python
``type`` subclass instance. This parameter will often not be needed by the C++
side, and the following example illustrates how to instantiate a lambda getter
function that ignores it:
.. code-block:: cpp
py::class_<Foo>(m, "Foo")
.def_property_readonly_static("foo", [](py::object /* self */) { return Foo(); });
Operator overloading
====================
Suppose that we're given the following ``Vector2`` class with a vector addition
and scalar multiplication operation, all implemented using overloaded operators
in C++.
.. code-block:: cpp
class Vector2 {
public:
Vector2(float x, float y) : x(x), y(y) { }
Vector2 operator+(const Vector2 &v) const { return Vector2(x + v.x, y + v.y); }
Vector2 operator*(float value) const { return Vector2(x * value, y * value); }
Vector2& operator+=(const Vector2 &v) { x += v.x; y += v.y; return *this; }
Vector2& operator*=(float v) { x *= v; y *= v; return *this; }
friend Vector2 operator*(float f, const Vector2 &v) {
return Vector2(f * v.x, f * v.y);
}
std::string toString() const {
return "[" + std::to_string(x) + ", " + std::to_string(y) + "]";
}
private:
float x, y;
};
The following snippet shows how the above operators can be conveniently exposed
to Python.
.. code-block:: cpp
#include <pybind11/operators.h>
PYBIND11_PLUGIN(example) {
py::module m("example", "pybind11 example plugin");
py::class_<Vector2>(m, "Vector2")
.def(py::init<float, float>())
.def(py::self + py::self)
.def(py::self += py::self)
.def(py::self *= float())
.def(float() * py::self)
.def("__repr__", &Vector2::toString);
return m.ptr();
}
Note that a line like
.. code-block:: cpp
.def(py::self * float())
is really just short hand notation for
.. code-block:: cpp
.def("__mul__", [](const Vector2 &a, float b) {
return a * b;
}, py::is_operator())
This can be useful for exposing additional operators that don't exist on the
C++ side, or to perform other types of customization. The ``py::is_operator``
flag marker is needed to inform pybind11 that this is an operator, which
returns ``NotImplemented`` when invoked with incompatible arguments rather than
throwing a type error.
.. note::
To use the more convenient ``py::self`` notation, the additional
header file :file:`pybind11/operators.h` must be included.
.. seealso::
The file :file:`tests/test_operator_overloading.cpp` contains a
complete example that demonstrates how to work with overloaded operators in
more detail.
Pickling support
================
Python's ``pickle`` module provides a powerful facility to serialize and
de-serialize a Python object graph into a binary data stream. To pickle and
unpickle C++ classes using pybind11, two additional functions must be provided.
Suppose the class in question has the following signature:
.. code-block:: cpp
class Pickleable {
public:
Pickleable(const std::string &value) : m_value(value) { }
const std::string &value() const { return m_value; }
void setExtra(int extra) { m_extra = extra; }
int extra() const { return m_extra; }
private:
std::string m_value;
int m_extra = 0;
};
The binding code including the requisite ``__setstate__`` and ``__getstate__`` methods [#f3]_
looks as follows:
.. code-block:: cpp
py::class_<Pickleable>(m, "Pickleable")
.def(py::init<std::string>())
.def("value", &Pickleable::value)
.def("extra", &Pickleable::extra)
.def("setExtra", &Pickleable::setExtra)
.def("__getstate__", [](const Pickleable &p) {
/* Return a tuple that fully encodes the state of the object */
return py::make_tuple(p.value(), p.extra());
})
.def("__setstate__", [](Pickleable &p, py::tuple t) {
if (t.size() != 2)
throw std::runtime_error("Invalid state!");
/* Invoke the in-place constructor. Note that this is needed even
when the object just has a trivial default constructor */
new (&p) Pickleable(t[0].cast<std::string>());
/* Assign any additional state */
p.setExtra(t[1].cast<int>());
});
An instance can now be pickled as follows:
.. code-block:: python
try:
import cPickle as pickle # Use cPickle on Python 2.7
except ImportError:
import pickle
p = Pickleable("test_value")
p.setExtra(15)
data = pickle.dumps(p, 2)
Note that only the cPickle module is supported on Python 2.7. The second
argument to ``dumps`` is also crucial: it selects the pickle protocol version
2, since the older version 1 is not supported. Newer versions are also fine—for
instance, specify ``-1`` to always use the latest available version. Beware:
failure to follow these instructions will cause important pybind11 memory
allocation routines to be skipped during unpickling, which will likely lead to
memory corruption and/or segmentation faults.
.. seealso::
The file :file:`tests/test_pickling.cpp` contains a complete example
that demonstrates how to pickle and unpickle types using pybind11 in more
detail.
.. [#f3] http://docs.python.org/3/library/pickle.html#pickling-class-instances
Multiple Inheritance
====================
pybind11 can create bindings for types that derive from multiple base types
(aka. *multiple inheritance*). To do so, specify all bases in the template
arguments of the ``class_`` declaration:
.. code-block:: cpp
py::class_<MyType, BaseType1, BaseType2, BaseType3>(m, "MyType")
...
The base types can be specified in arbitrary order, and they can even be
interspersed with alias types and holder types (discussed earlier in this
document)---pybind11 will automatically find out which is which. The only
requirement is that the first template argument is the type to be declared.
There are two caveats regarding the implementation of this feature:
1. When only one base type is specified for a C++ type that actually has
multiple bases, pybind11 will assume that it does not participate in
multiple inheritance, which can lead to undefined behavior. In such cases,
add the tag ``multiple_inheritance``:
.. code-block:: cpp
py::class_<MyType, BaseType2>(m, "MyType", py::multiple_inheritance());
The tag is redundant and does not need to be specified when multiple base
types are listed.
2. As was previously discussed in the section on :ref:`overriding_virtuals`, it
is easy to create Python types that derive from C++ classes. It is even
possible to make use of multiple inheritance to declare a Python class which
has e.g. a C++ and a Python class as bases. However, any attempt to create a
type that has *two or more* C++ classes in its hierarchy of base types will
fail with a fatal error message: ``TypeError: multiple bases have instance
lay-out conflict``. Core Python types that are implemented in C (e.g.
``dict``, ``list``, ``Exception``, etc.) also fall under this combination
and cannot be combined with C++ types bound using pybind11 via multiple
inheritance.

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Exceptions
##########
Built-in exception translation
==============================
When C++ code invoked from Python throws an ``std::exception``, it is
automatically converted into a Python ``Exception``. pybind11 defines multiple
special exception classes that will map to different types of Python
exceptions:
.. tabularcolumns:: |p{0.5\textwidth}|p{0.45\textwidth}|
+--------------------------------------+------------------------------+
| C++ exception type | Python exception type |
+======================================+==============================+
| :class:`std::exception` | ``RuntimeError`` |
+--------------------------------------+------------------------------+
| :class:`std::bad_alloc` | ``MemoryError`` |
+--------------------------------------+------------------------------+
| :class:`std::domain_error` | ``ValueError`` |
+--------------------------------------+------------------------------+
| :class:`std::invalid_argument` | ``ValueError`` |
+--------------------------------------+------------------------------+
| :class:`std::length_error` | ``ValueError`` |
+--------------------------------------+------------------------------+
| :class:`std::out_of_range` | ``ValueError`` |
+--------------------------------------+------------------------------+
| :class:`std::range_error` | ``ValueError`` |
+--------------------------------------+------------------------------+
| :class:`pybind11::stop_iteration` | ``StopIteration`` (used to |
| | implement custom iterators) |
+--------------------------------------+------------------------------+
| :class:`pybind11::index_error` | ``IndexError`` (used to |
| | indicate out of bounds |
| | accesses in ``__getitem__``, |
| | ``__setitem__``, etc.) |
+--------------------------------------+------------------------------+
| :class:`pybind11::value_error` | ``ValueError`` (used to |
| | indicate wrong value passed |
| | in ``container.remove(...)`` |
+--------------------------------------+------------------------------+
| :class:`pybind11::key_error` | ``KeyError`` (used to |
| | indicate out of bounds |
| | accesses in ``__getitem__``, |
| | ``__setitem__`` in dict-like |
| | objects, etc.) |
+--------------------------------------+------------------------------+
| :class:`pybind11::error_already_set` | Indicates that the Python |
| | exception flag has already |
| | been initialized |
+--------------------------------------+------------------------------+
When a Python function invoked from C++ throws an exception, it is converted
into a C++ exception of type :class:`error_already_set` whose string payload
contains a textual summary.
There is also a special exception :class:`cast_error` that is thrown by
:func:`handle::call` when the input arguments cannot be converted to Python
objects.
Registering custom translators
==============================
If the default exception conversion policy described above is insufficient,
pybind11 also provides support for registering custom exception translators.
To register a simple exception conversion that translates a C++ exception into
a new Python exception using the C++ exception's ``what()`` method, a helper
function is available:
.. code-block:: cpp
py::register_exception<CppExp>(module, "PyExp");
This call creates a Python exception class with the name ``PyExp`` in the given
module and automatically converts any encountered exceptions of type ``CppExp``
into Python exceptions of type ``PyExp``.
When more advanced exception translation is needed, the function
``py::register_exception_translator(translator)`` can be used to register
functions that can translate arbitrary exception types (and which may include
additional logic to do so). The function takes a stateless callable (e.g. a
function pointer or a lambda function without captured variables) with the call
signature ``void(std::exception_ptr)``.
When a C++ exception is thrown, the registered exception translators are tried
in reverse order of registration (i.e. the last registered translator gets the
first shot at handling the exception).
Inside the translator, ``std::rethrow_exception`` should be used within
a try block to re-throw the exception. One or more catch clauses to catch
the appropriate exceptions should then be used with each clause using
``PyErr_SetString`` to set a Python exception or ``ex(string)`` to set
the python exception to a custom exception type (see below).
To declare a custom Python exception type, declare a ``py::exception`` variable
and use this in the associated exception translator (note: it is often useful
to make this a static declaration when using it inside a lambda expression
without requiring capturing).
The following example demonstrates this for a hypothetical exception classes
``MyCustomException`` and ``OtherException``: the first is translated to a
custom python exception ``MyCustomError``, while the second is translated to a
standard python RuntimeError:
.. code-block:: cpp
static py::exception<MyCustomException> exc(m, "MyCustomError");
py::register_exception_translator([](std::exception_ptr p) {
try {
if (p) std::rethrow_exception(p);
} catch (const MyCustomException &e) {
exc(e.what());
} catch (const OtherException &e) {
PyErr_SetString(PyExc_RuntimeError, e.what());
}
});
Multiple exceptions can be handled by a single translator, as shown in the
example above. If the exception is not caught by the current translator, the
previously registered one gets a chance.
If none of the registered exception translators is able to handle the
exception, it is handled by the default converter as described in the previous
section.
.. seealso::
The file :file:`tests/test_exceptions.cpp` contains examples
of various custom exception translators and custom exception types.
.. note::
You must call either ``PyErr_SetString`` or a custom exception's call
operator (``exc(string)``) for every exception caught in a custom exception
translator. Failure to do so will cause Python to crash with ``SystemError:
error return without exception set``.
Exceptions that you do not plan to handle should simply not be caught, or
may be explicity (re-)thrown to delegate it to the other,
previously-declared existing exception translators.

311
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@ -0,0 +1,311 @@
Functions
#########
Before proceeding with this section, make sure that you are already familiar
with the basics of binding functions and classes, as explained in :doc:`/basics`
and :doc:`/classes`. The following guide is applicable to both free and member
functions, i.e. *methods* in Python.
Return value policies
=====================
Python and C++ use fundamentally different ways of managing the memory and
lifetime of objects managed by them. This can lead to issues when creating
bindings for functions that return a non-trivial type. Just by looking at the
type information, it is not clear whether Python should take charge of the
returned value and eventually free its resources, or if this is handled on the
C++ side. For this reason, pybind11 provides a several `return value policy`
annotations that can be passed to the :func:`module::def` and
:func:`class_::def` functions. The default policy is
:enum:`return_value_policy::automatic`.
Return value policies are tricky, and it's very important to get them right.
Just to illustrate what can go wrong, consider the following simple example:
.. code-block:: cpp
/* Function declaration */
Data *get_data() { return _data; /* (pointer to a static data structure) */ }
...
/* Binding code */
m.def("get_data", &get_data); // <-- KABOOM, will cause crash when called from Python
What's going on here? When ``get_data()`` is called from Python, the return
value (a native C++ type) must be wrapped to turn it into a usable Python type.
In this case, the default return value policy (:enum:`return_value_policy::automatic`)
causes pybind11 to assume ownership of the static ``_data`` instance.
When Python's garbage collector eventually deletes the Python
wrapper, pybind11 will also attempt to delete the C++ instance (via ``operator
delete()``) due to the implied ownership. At this point, the entire application
will come crashing down, though errors could also be more subtle and involve
silent data corruption.
In the above example, the policy :enum:`return_value_policy::reference` should have
been specified so that the global data instance is only *referenced* without any
implied transfer of ownership, i.e.:
.. code-block:: cpp
m.def("get_data", &get_data, return_value_policy::reference);
On the other hand, this is not the right policy for many other situations,
where ignoring ownership could lead to resource leaks.
As a developer using pybind11, it's important to be familiar with the different
return value policies, including which situation calls for which one of them.
The following table provides an overview of available policies:
.. tabularcolumns:: |p{0.5\textwidth}|p{0.45\textwidth}|
+--------------------------------------------------+----------------------------------------------------------------------------+
| Return value policy | Description |
+==================================================+============================================================================+
| :enum:`return_value_policy::take_ownership` | Reference an existing object (i.e. do not create a new copy) and take |
| | ownership. Python will call the destructor and delete operator when the |
| | object's reference count reaches zero. Undefined behavior ensues when the |
| | C++ side does the same, or when the data was not dynamically allocated. |
+--------------------------------------------------+----------------------------------------------------------------------------+
| :enum:`return_value_policy::copy` | Create a new copy of the returned object, which will be owned by Python. |
| | This policy is comparably safe because the lifetimes of the two instances |
| | are decoupled. |
+--------------------------------------------------+----------------------------------------------------------------------------+
| :enum:`return_value_policy::move` | Use ``std::move`` to move the return value contents into a new instance |
| | that will be owned by Python. This policy is comparably safe because the |
| | lifetimes of the two instances (move source and destination) are decoupled.|
+--------------------------------------------------+----------------------------------------------------------------------------+
| :enum:`return_value_policy::reference` | Reference an existing object, but do not take ownership. The C++ side is |
| | responsible for managing the object's lifetime and deallocating it when |
| | it is no longer used. Warning: undefined behavior will ensue when the C++ |
| | side deletes an object that is still referenced and used by Python. |
+--------------------------------------------------+----------------------------------------------------------------------------+
| :enum:`return_value_policy::reference_internal` | Indicates that the lifetime of the return value is tied to the lifetime |
| | of a parent object, namely the implicit ``this``, or ``self`` argument of |
| | the called method or property. Internally, this policy works just like |
| | :enum:`return_value_policy::reference` but additionally applies a |
| | ``keep_alive<0, 1>`` *call policy* (described in the next section) that |
| | prevents the parent object from being garbage collected as long as the |
| | return value is referenced by Python. This is the default policy for |
| | property getters created via ``def_property``, ``def_readwrite``, etc. |
+--------------------------------------------------+----------------------------------------------------------------------------+
| :enum:`return_value_policy::automatic` | This is the default return value policy, which falls back to the policy |
| | :enum:`return_value_policy::take_ownership` when the return value is a |
| | pointer. Otherwise, it uses :enum:`return_value::move` or |
| | :enum:`return_value::copy` for rvalue and lvalue references, respectively. |
| | See above for a description of what all of these different policies do. |
+--------------------------------------------------+----------------------------------------------------------------------------+
| :enum:`return_value_policy::automatic_reference` | As above, but use policy :enum:`return_value_policy::reference` when the |
| | return value is a pointer. This is the default conversion policy for |
| | function arguments when calling Python functions manually from C++ code |
| | (i.e. via handle::operator()). You probably won't need to use this. |
+--------------------------------------------------+----------------------------------------------------------------------------+
Return value policies can also be applied to properties:
.. code-block:: cpp
class_<MyClass>(m, "MyClass")
.def_property("data", &MyClass::getData, &MyClass::setData,
py::return_value_policy::copy);
Technically, the code above applies the policy to both the getter and the
setter function, however, the setter doesn't really care about *return*
value policies which makes this a convenient terse syntax. Alternatively,
targeted arguments can be passed through the :class:`cpp_function` constructor:
.. code-block:: cpp
class_<MyClass>(m, "MyClass")
.def_property("data"
py::cpp_function(&MyClass::getData, py::return_value_policy::copy),
py::cpp_function(&MyClass::setData)
);
.. warning::
Code with invalid return value policies might access unitialized memory or
free data structures multiple times, which can lead to hard-to-debug
non-determinism and segmentation faults, hence it is worth spending the
time to understand all the different options in the table above.
.. note::
One important aspect of the above policies is that they only apply to
instances which pybind11 has *not* seen before, in which case the policy
clarifies essential questions about the return value's lifetime and
ownership. When pybind11 knows the instance already (as identified by its
type and address in memory), it will return the existing Python object
wrapper rather than creating a new copy.
.. note::
The next section on :ref:`call_policies` discusses *call policies* that can be
specified *in addition* to a return value policy from the list above. Call
policies indicate reference relationships that can involve both return values
and parameters of functions.
.. note::
As an alternative to elaborate call policies and lifetime management logic,
consider using smart pointers (see the section on :ref:`smart_pointers` for
details). Smart pointers can tell whether an object is still referenced from
C++ or Python, which generally eliminates the kinds of inconsistencies that
can lead to crashes or undefined behavior. For functions returning smart
pointers, it is not necessary to specify a return value policy.
.. _call_policies:
Additional call policies
========================
In addition to the above return value policies, further `call policies` can be
specified to indicate dependencies between parameters. There is currently just
one policy named ``keep_alive<Nurse, Patient>``, which indicates that the
argument with index ``Patient`` should be kept alive at least until the
argument with index ``Nurse`` is freed by the garbage collector. Argument
indices start at one, while zero refers to the return value. For methods, index
``1`` refers to the implicit ``this`` pointer, while regular arguments begin at
index ``2``. Arbitrarily many call policies can be specified. When a ``Nurse``
with value ``None`` is detected at runtime, the call policy does nothing.
This feature internally relies on the ability to create a *weak reference* to
the nurse object, which is permitted by all classes exposed via pybind11. When
the nurse object does not support weak references, an exception will be thrown.
Consider the following example: here, the binding code for a list append
operation ties the lifetime of the newly added element to the underlying
container:
.. code-block:: cpp
py::class_<List>(m, "List")
.def("append", &List::append, py::keep_alive<1, 2>());
.. note::
``keep_alive`` is analogous to the ``with_custodian_and_ward`` (if Nurse,
Patient != 0) and ``with_custodian_and_ward_postcall`` (if Nurse/Patient ==
0) policies from Boost.Python.
.. seealso::
The file :file:`tests/test_keep_alive.cpp` contains a complete example
that demonstrates using :class:`keep_alive` in more detail.
.. _python_objects_as_args:
Python objects as arguments
===========================
pybind11 exposes all major Python types using thin C++ wrapper classes. These
wrapper classes can also be used as parameters of functions in bindings, which
makes it possible to directly work with native Python types on the C++ side.
For instance, the following statement iterates over a Python ``dict``:
.. code-block:: cpp
void print_dict(py::dict dict) {
/* Easily interact with Python types */
for (auto item : dict)
std::cout << "key=" << item.first << ", "
<< "value=" << item.second << std::endl;
}
It can be exported:
.. code-block:: cpp
m.def("print_dict", &print_dict);
And used in Python as usual:
.. code-block:: pycon
>>> print_dict({'foo': 123, 'bar': 'hello'})
key=foo, value=123
key=bar, value=hello
For more information on using Python objects in C++, see :doc:`/advanced/pycpp/index`.
Accepting \*args and \*\*kwargs
===============================
Python provides a useful mechanism to define functions that accept arbitrary
numbers of arguments and keyword arguments:
.. code-block:: python
def generic(*args, **kwargs):
... # do something with args and kwargs
Such functions can also be created using pybind11:
.. code-block:: cpp
void generic(py::args args, py::kwargs kwargs) {
/// .. do something with args
if (kwargs)
/// .. do something with kwargs
}
/// Binding code
m.def("generic", &generic);
The class ``py::args`` derives from ``py::tuple`` and ``py::kwargs`` derives
from ``py::dict``. Note that the ``kwargs`` argument is invalid if no keyword
arguments were actually provided. Please refer to the other examples for
details on how to iterate over these, and on how to cast their entries into
C++ objects. A demonstration is also available in
``tests/test_kwargs_and_defaults.cpp``.
.. warning::
Unlike Python, pybind11 does not allow combining normal parameters with the
``args`` / ``kwargs`` special parameters.
Default arguments revisited
===========================
The section on :ref:`default_args` previously discussed basic usage of default
arguments using pybind11. One noteworthy aspect of their implementation is that
default arguments are converted to Python objects right at declaration time.
Consider the following example:
.. code-block:: cpp
py::class_<MyClass>("MyClass")
.def("myFunction", py::arg("arg") = SomeType(123));
In this case, pybind11 must already be set up to deal with values of the type
``SomeType`` (via a prior instantiation of ``py::class_<SomeType>``), or an
exception will be thrown.
Another aspect worth highlighting is that the "preview" of the default argument
in the function signature is generated using the object's ``__repr__`` method.
If not available, the signature may not be very helpful, e.g.:
.. code-block:: pycon
FUNCTIONS
...
| myFunction(...)
| Signature : (MyClass, arg : SomeType = <SomeType object at 0x101b7b080>) -> NoneType
...
The first way of addressing this is by defining ``SomeType.__repr__``.
Alternatively, it is possible to specify the human-readable preview of the
default argument manually using the ``arg_v`` notation:
.. code-block:: cpp
py::class_<MyClass>("MyClass")
.def("myFunction", py::arg_v("arg", SomeType(123), "SomeType(123)"));
Sometimes it may be necessary to pass a null pointer value as a default
argument. In this case, remember to cast it to the underlying type in question,
like so:
.. code-block:: cpp
py::class_<MyClass>("MyClass")
.def("myFunction", py::arg("arg") = (SomeType *) nullptr);

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Miscellaneous
#############
.. _macro_notes:
General notes regarding convenience macros
==========================================
pybind11 provides a few convenience macros such as
:func:`PYBIND11_MAKE_OPAQUE` and :func:`PYBIND11_DECLARE_HOLDER_TYPE`, and
``PYBIND11_OVERLOAD_*``. Since these are "just" macros that are evaluated
in the preprocessor (which has no concept of types), they *will* get confused
by commas in a template argument such as ``PYBIND11_OVERLOAD(MyReturnValue<T1,
T2>, myFunc)``. In this case, the preprocessor assumes that the comma indicates
the beginning of the next parameter. Use a ``typedef`` to bind the template to
another name and use it in the macro to avoid this problem.
Global Interpreter Lock (GIL)
=============================
The classes :class:`gil_scoped_release` and :class:`gil_scoped_acquire` can be
used to acquire and release the global interpreter lock in the body of a C++
function call. In this way, long-running C++ code can be parallelized using
multiple Python threads. Taking :ref:`overriding_virtuals` as an example, this
could be realized as follows (important changes highlighted):
.. code-block:: cpp
:emphasize-lines: 8,9,33,34
class PyAnimal : public Animal {
public:
/* Inherit the constructors */
using Animal::Animal;
/* Trampoline (need one for each virtual function) */
std::string go(int n_times) {
/* Acquire GIL before calling Python code */
py::gil_scoped_acquire acquire;
PYBIND11_OVERLOAD_PURE(
std::string, /* Return type */
Animal, /* Parent class */
go, /* Name of function */
n_times /* Argument(s) */
);
}
};
PYBIND11_PLUGIN(example) {
py::module m("example", "pybind11 example plugin");
py::class_<Animal, PyAnimal> animal(m, "Animal");
animal
.def(py::init<>())
.def("go", &Animal::go);
py::class_<Dog>(m, "Dog", animal)
.def(py::init<>());
m.def("call_go", [](Animal *animal) -> std::string {
/* Release GIL before calling into (potentially long-running) C++ code */
py::gil_scoped_release release;
return call_go(animal);
});
return m.ptr();
}
Binding sequence data types, iterators, the slicing protocol, etc.
==================================================================
Please refer to the supplemental example for details.
.. seealso::
The file :file:`tests/test_sequences_and_iterators.cpp` contains a
complete example that shows how to bind a sequence data type, including
length queries (``__len__``), iterators (``__iter__``), the slicing
protocol and other kinds of useful operations.
Partitioning code over multiple extension modules
=================================================
It's straightforward to split binding code over multiple extension modules,
while referencing types that are declared elsewhere. Everything "just" works
without any special precautions. One exception to this rule occurs when
extending a type declared in another extension module. Recall the basic example
from Section :ref:`inheritance`.
.. code-block:: cpp
py::class_<Pet> pet(m, "Pet");
pet.def(py::init<const std::string &>())
.def_readwrite("name", &Pet::name);
py::class_<Dog>(m, "Dog", pet /* <- specify parent */)
.def(py::init<const std::string &>())
.def("bark", &Dog::bark);
Suppose now that ``Pet`` bindings are defined in a module named ``basic``,
whereas the ``Dog`` bindings are defined somewhere else. The challenge is of
course that the variable ``pet`` is not available anymore though it is needed
to indicate the inheritance relationship to the constructor of ``class_<Dog>``.
However, it can be acquired as follows:
.. code-block:: cpp
py::object pet = (py::object) py::module::import("basic").attr("Pet");
py::class_<Dog>(m, "Dog", pet)
.def(py::init<const std::string &>())
.def("bark", &Dog::bark);
Alternatively, you can specify the base class as a template parameter option to
``class_``, which performs an automated lookup of the corresponding Python
type. Like the above code, however, this also requires invoking the ``import``
function once to ensure that the pybind11 binding code of the module ``basic``
has been executed:
.. code-block:: cpp
py::module::import("basic");
py::class_<Dog, Pet>(m, "Dog")
.def(py::init<const std::string &>())
.def("bark", &Dog::bark);
Naturally, both methods will fail when there are cyclic dependencies.
Note that compiling code which has its default symbol visibility set to
*hidden* (e.g. via the command line flag ``-fvisibility=hidden`` on GCC/Clang) can interfere with the
ability to access types defined in another extension module. Workarounds
include changing the global symbol visibility (not recommended, because it will
lead unnecessarily large binaries) or manually exporting types that are
accessed by multiple extension modules:
.. code-block:: cpp
#ifdef _WIN32
# define EXPORT_TYPE __declspec(dllexport)
#else
# define EXPORT_TYPE __attribute__ ((visibility("default")))
#endif
class EXPORT_TYPE Dog : public Animal {
...
};
Note also that it is possible (although would rarely be required) to share arbitrary
C++ objects between extension modules at runtime. Internal library data is shared
between modules using capsule machinery [#f6]_ which can be also utilized for
storing, modifying and accessing user-defined data. Note that an extension module
will "see" other extensions' data if and only if they were built with the same
pybind11 version. Consider the following example:
.. code-block:: cpp
auto data = (MyData *) py::get_shared_data("mydata");
if (!data)
data = (MyData *) py::set_shared_data("mydata", new MyData(42));
If the above snippet was used in several separately compiled extension modules,
the first one to be imported would create a ``MyData`` instance and associate
a ``"mydata"`` key with a pointer to it. Extensions that are imported later
would be then able to access the data behind the same pointer.
.. [#f6] https://docs.python.org/3/extending/extending.html#using-capsules
Generating documentation using Sphinx
=====================================
Sphinx [#f4]_ has the ability to inspect the signatures and documentation
strings in pybind11-based extension modules to automatically generate beautiful
documentation in a variety formats. The python_example repository [#f5]_ contains a
simple example repository which uses this approach.
There are two potential gotchas when using this approach: first, make sure that
the resulting strings do not contain any :kbd:`TAB` characters, which break the
docstring parsing routines. You may want to use C++11 raw string literals,
which are convenient for multi-line comments. Conveniently, any excess
indentation will be automatically be removed by Sphinx. However, for this to
work, it is important that all lines are indented consistently, i.e.:
.. code-block:: cpp
// ok
m.def("foo", &foo, R"mydelimiter(
The foo function
Parameters
----------
)mydelimiter");
// *not ok*
m.def("foo", &foo, R"mydelimiter(The foo function
Parameters
----------
)mydelimiter");
By default, pybind11 automatically generates and prepends a signature to the docstring of a function
registered with ``module::def()`` and ``class_::def()``. Sometimes this
behavior is not desirable, because you want to provide your own signature or remove
the docstring completely to exclude the function from the Sphinx documentation.
The class ``options`` allows you to selectively suppress auto-generated signatures:
.. code-block:: cpp
PYBIND11_PLUGIN(example) {
py::module m("example", "pybind11 example plugin");
py::options options;
options.disable_function_signatures();
m.def("add", [](int a, int b) { return a + b; }, "A function which adds two numbers");
return m.ptr();
}
Note that changes to the settings affect only function bindings created during the
lifetime of the ``options`` instance. When it goes out of scope at the end of the module's init function,
the default settings are restored to prevent unwanted side effects.
.. [#f4] http://www.sphinx-doc.org
.. [#f5] http://github.com/pybind/python_example

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Python C++ interface
####################
pybind11 exposes Python types and functions using thin C++ wrappers, which
makes it possible to conveniently call Python code from C++ without resorting
to Python's C API.
.. toctree::
:maxdepth: 2
object
numpy
utilities

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.. _numpy:
NumPy
#####
Buffer protocol
===============
Python supports an extremely general and convenient approach for exchanging
data between plugin libraries. Types can expose a buffer view [#f2]_, which
provides fast direct access to the raw internal data representation. Suppose we
want to bind the following simplistic Matrix class:
.. code-block:: cpp
class Matrix {
public:
Matrix(size_t rows, size_t cols) : m_rows(rows), m_cols(cols) {
m_data = new float[rows*cols];
}
float *data() { return m_data; }
size_t rows() const { return m_rows; }
size_t cols() const { return m_cols; }
private:
size_t m_rows, m_cols;
float *m_data;
};
The following binding code exposes the ``Matrix`` contents as a buffer object,
making it possible to cast Matrices into NumPy arrays. It is even possible to
completely avoid copy operations with Python expressions like
``np.array(matrix_instance, copy = False)``.
.. code-block:: cpp
py::class_<Matrix>(m, "Matrix")
.def_buffer([](Matrix &m) -> py::buffer_info {
return py::buffer_info(
m.data(), /* Pointer to buffer */
sizeof(float), /* Size of one scalar */
py::format_descriptor<float>::format(), /* Python struct-style format descriptor */
2, /* Number of dimensions */
{ m.rows(), m.cols() }, /* Buffer dimensions */
{ sizeof(float) * m.rows(), /* Strides (in bytes) for each index */
sizeof(float) }
);
});
The snippet above binds a lambda function, which can create ``py::buffer_info``
description records on demand describing a given matrix. The contents of
``py::buffer_info`` mirror the Python buffer protocol specification.
.. code-block:: cpp
struct buffer_info {
void *ptr;
size_t itemsize;
std::string format;
int ndim;
std::vector<size_t> shape;
std::vector<size_t> strides;
};
To create a C++ function that can take a Python buffer object as an argument,
simply use the type ``py::buffer`` as one of its arguments. Buffers can exist
in a great variety of configurations, hence some safety checks are usually
necessary in the function body. Below, you can see an basic example on how to
define a custom constructor for the Eigen double precision matrix
(``Eigen::MatrixXd``) type, which supports initialization from compatible
buffer objects (e.g. a NumPy matrix).
.. code-block:: cpp
/* Bind MatrixXd (or some other Eigen type) to Python */
typedef Eigen::MatrixXd Matrix;
typedef Matrix::Scalar Scalar;
constexpr bool rowMajor = Matrix::Flags & Eigen::RowMajorBit;
py::class_<Matrix>(m, "Matrix")
.def("__init__", [](Matrix &m, py::buffer b) {
typedef Eigen::Stride<Eigen::Dynamic, Eigen::Dynamic> Strides;
/* Request a buffer descriptor from Python */
py::buffer_info info = b.request();
/* Some sanity checks ... */
if (info.format != py::format_descriptor<Scalar>::format())
throw std::runtime_error("Incompatible format: expected a double array!");
if (info.ndim != 2)
throw std::runtime_error("Incompatible buffer dimension!");
auto strides = Strides(
info.strides[rowMajor ? 0 : 1] / sizeof(Scalar),
info.strides[rowMajor ? 1 : 0] / sizeof(Scalar));
auto map = Eigen::Map<Matrix, 0, Strides>(
static_cat<Scalar *>(info.ptr), info.shape[0], info.shape[1], strides);
new (&m) Matrix(map);
});
For reference, the ``def_buffer()`` call for this Eigen data type should look
as follows:
.. code-block:: cpp
.def_buffer([](Matrix &m) -> py::buffer_info {
return py::buffer_info(
m.data(), /* Pointer to buffer */
sizeof(Scalar), /* Size of one scalar */
/* Python struct-style format descriptor */
py::format_descriptor<Scalar>::format(),
/* Number of dimensions */
2,
/* Buffer dimensions */
{ (size_t) m.rows(),
(size_t) m.cols() },
/* Strides (in bytes) for each index */
{ sizeof(Scalar) * (rowMajor ? m.cols() : 1),
sizeof(Scalar) * (rowMajor ? 1 : m.rows()) }
);
})
For a much easier approach of binding Eigen types (although with some
limitations), refer to the section on :doc:`/advanced/cast/eigen`.
.. seealso::
The file :file:`tests/test_buffers.cpp` contains a complete example
that demonstrates using the buffer protocol with pybind11 in more detail.
.. [#f2] http://docs.python.org/3/c-api/buffer.html
Arrays
======
By exchanging ``py::buffer`` with ``py::array`` in the above snippet, we can
restrict the function so that it only accepts NumPy arrays (rather than any
type of Python object satisfying the buffer protocol).
In many situations, we want to define a function which only accepts a NumPy
array of a certain data type. This is possible via the ``py::array_t<T>``
template. For instance, the following function requires the argument to be a
NumPy array containing double precision values.
.. code-block:: cpp
void f(py::array_t<double> array);
When it is invoked with a different type (e.g. an integer or a list of
integers), the binding code will attempt to cast the input into a NumPy array
of the requested type. Note that this feature requires the
:file:``pybind11/numpy.h`` header to be included.
Data in NumPy arrays is not guaranteed to packed in a dense manner;
furthermore, entries can be separated by arbitrary column and row strides.
Sometimes, it can be useful to require a function to only accept dense arrays
using either the C (row-major) or Fortran (column-major) ordering. This can be
accomplished via a second template argument with values ``py::array::c_style``
or ``py::array::f_style``.
.. code-block:: cpp
void f(py::array_t<double, py::array::c_style | py::array::forcecast> array);
The ``py::array::forcecast`` argument is the default value of the second
template parameter, and it ensures that non-conforming arguments are converted
into an array satisfying the specified requirements instead of trying the next
function overload.
Structured types
================
In order for ``py::array_t`` to work with structured (record) types, we first need
to register the memory layout of the type. This can be done via ``PYBIND11_NUMPY_DTYPE``
macro which expects the type followed by field names:
.. code-block:: cpp
struct A {
int x;
double y;
};
struct B {
int z;
A a;
};
PYBIND11_NUMPY_DTYPE(A, x, y);
PYBIND11_NUMPY_DTYPE(B, z, a);
/* now both A and B can be used as template arguments to py::array_t */
Vectorizing functions
=====================
Suppose we want to bind a function with the following signature to Python so
that it can process arbitrary NumPy array arguments (vectors, matrices, general
N-D arrays) in addition to its normal arguments:
.. code-block:: cpp
double my_func(int x, float y, double z);
After including the ``pybind11/numpy.h`` header, this is extremely simple:
.. code-block:: cpp
m.def("vectorized_func", py::vectorize(my_func));
Invoking the function like below causes 4 calls to be made to ``my_func`` with
each of the array elements. The significant advantage of this compared to
solutions like ``numpy.vectorize()`` is that the loop over the elements runs
entirely on the C++ side and can be crunched down into a tight, optimized loop
by the compiler. The result is returned as a NumPy array of type
``numpy.dtype.float64``.
.. code-block:: pycon
>>> x = np.array([[1, 3],[5, 7]])
>>> y = np.array([[2, 4],[6, 8]])
>>> z = 3
>>> result = vectorized_func(x, y, z)
The scalar argument ``z`` is transparently replicated 4 times. The input
arrays ``x`` and ``y`` are automatically converted into the right types (they
are of type ``numpy.dtype.int64`` but need to be ``numpy.dtype.int32`` and
``numpy.dtype.float32``, respectively)
Sometimes we might want to explicitly exclude an argument from the vectorization
because it makes little sense to wrap it in a NumPy array. For instance,
suppose the function signature was
.. code-block:: cpp
double my_func(int x, float y, my_custom_type *z);
This can be done with a stateful Lambda closure:
.. code-block:: cpp
// Vectorize a lambda function with a capture object (e.g. to exclude some arguments from the vectorization)
m.def("vectorized_func",
[](py::array_t<int> x, py::array_t<float> y, my_custom_type *z) {
auto stateful_closure = [z](int x, float y) { return my_func(x, y, z); };
return py::vectorize(stateful_closure)(x, y);
}
);
In cases where the computation is too complicated to be reduced to
``vectorize``, it will be necessary to create and access the buffer contents
manually. The following snippet contains a complete example that shows how this
works (the code is somewhat contrived, since it could have been done more
simply using ``vectorize``).
.. code-block:: cpp
#include <pybind11/pybind11.h>
#include <pybind11/numpy.h>
namespace py = pybind11;
py::array_t<double> add_arrays(py::array_t<double> input1, py::array_t<double> input2) {
auto buf1 = input1.request(), buf2 = input2.request();
if (buf1.ndim != 1 || buf2.ndim != 1)
throw std::runtime_error("Number of dimensions must be one");
if (buf1.size != buf2.size)
throw std::runtime_error("Input shapes must match");
/* No pointer is passed, so NumPy will allocate the buffer */
auto result = py::array_t<double>(buf1.size);
auto buf3 = result.request();
double *ptr1 = (double *) buf1.ptr,
*ptr2 = (double *) buf2.ptr,
*ptr3 = (double *) buf3.ptr;
for (size_t idx = 0; idx < buf1.shape[0]; idx++)
ptr3[idx] = ptr1[idx] + ptr2[idx];
return result;
}
PYBIND11_PLUGIN(test) {
py::module m("test");
m.def("add_arrays", &add_arrays, "Add two NumPy arrays");
return m.ptr();
}
.. seealso::
The file :file:`tests/test_numpy_vectorize.cpp` contains a complete
example that demonstrates using :func:`vectorize` in more detail.

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Python types
############
Available wrappers
==================
All major Python types are available as thin C++ wrapper classes. These
can also be used as function parameters -- see :ref:`python_objects_as_args`.
Available types include :class:`handle`, :class:`object`, :class:`bool_`,
:class:`int_`, :class:`float_`, :class:`str`, :class:`bytes`, :class:`tuple`,
:class:`list`, :class:`dict`, :class:`slice`, :class:`none`, :class:`capsule`,
:class:`iterable`, :class:`iterator`, :class:`function`, :class:`buffer`,
:class:`array`, and :class:`array_t`.
Casting back and forth
======================
In this kind of mixed code, it is often necessary to convert arbitrary C++
types to Python, which can be done using :func:`py::cast`:
.. code-block:: cpp
MyClass *cls = ..;
py::object obj = py::cast(cls);
The reverse direction uses the following syntax:
.. code-block:: cpp
py::object obj = ...;
MyClass *cls = obj.cast<MyClass *>();
When conversion fails, both directions throw the exception :class:`cast_error`.
Calling Python functions
========================
It is also possible to call python functions via ``operator()``.
.. code-block:: cpp
py::function f = <...>;
py::object result_py = f(1234, "hello", some_instance);
MyClass &result = result_py.cast<MyClass>();
Keyword arguments are also supported. In Python, there is the usual call syntax:
.. code-block:: python
def f(number, say, to):
... # function code
f(1234, say="hello", to=some_instance) # keyword call in Python
In C++, the same call can be made using:
.. code-block:: cpp
using pybind11::literals; // to bring in the `_a` literal
f(1234, "say"_a="hello", "to"_a=some_instance); // keyword call in C++
Unpacking of ``*args`` and ``**kwargs`` is also possible and can be mixed with
other arguments:
.. code-block:: cpp
// * unpacking
py::tuple args = py::make_tuple(1234, "hello", some_instance);
f(*args);
// ** unpacking
py::dict kwargs = py::dict("number"_a=1234, "say"_a="hello", "to"_a=some_instance);
f(**kwargs);
// mixed keywords, * and ** unpacking
py::tuple args = py::make_tuple(1234);
py::dict kwargs = py::dict("to"_a=some_instance);
f(*args, "say"_a="hello", **kwargs);
Generalized unpacking according to PEP448_ is also supported:
.. code-block:: cpp
py::dict kwargs1 = py::dict("number"_a=1234);
py::dict kwargs2 = py::dict("to"_a=some_instance);
f(**kwargs1, "say"_a="hello", **kwargs2);
.. seealso::
The file :file:`tests/test_python_types.cpp` contains a complete
example that demonstrates passing native Python types in more detail. The
file :file:`tests/test_callbacks.cpp` presents a few examples of calling
Python functions from C++, including keywords arguments and unpacking.
.. _PEP448: https://www.python.org/dev/peps/pep-0448/

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Utilities
#########
Using Python's print function in C++
====================================
The usual way to write output in C++ is using ``std::cout`` while in Python one
would use ``print``. Since these methods use different buffers, mixing them can
lead to output order issues. To resolve this, pybind11 modules can use the
:func:`py::print` function which writes to Python's ``sys.stdout`` for consistency.
Python's ``print`` function is replicated in the C++ API including optional
keyword arguments ``sep``, ``end``, ``file``, ``flush``. Everything works as
expected in Python:
.. code-block:: cpp
py::print(1, 2.0, "three"); // 1 2.0 three
py::print(1, 2.0, "three", "sep"_a="-"); // 1-2.0-three
auto args = py::make_tuple("unpacked", true);
py::print("->", *args, "end"_a="<-"); // -> unpacked True <-
Evaluating Python expressions from strings and files
====================================================
pybind11 provides the :func:`eval` and :func:`eval_file` functions to evaluate
Python expressions and statements. The following example illustrates how they
can be used.
Both functions accept a template parameter that describes how the argument
should be interpreted. Possible choices include ``eval_expr`` (isolated
expression), ``eval_single_statement`` (a single statement, return value is
always ``none``), and ``eval_statements`` (sequence of statements, return value
is always ``none``).
.. code-block:: cpp
// At beginning of file
#include <pybind11/eval.h>
...
// Evaluate in scope of main module
py::object scope = py::module::import("__main__").attr("__dict__");
// Evaluate an isolated expression
int result = py::eval("my_variable + 10", scope).cast<int>();
// Evaluate a sequence of statements
py::eval<py::eval_statements>(
"print('Hello')\n"
"print('world!');",
scope);
// Evaluate the statements in an separate Python file on disk
py::eval_file("script.py", scope);

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Smart pointers
##############
std::unique_ptr
===============
Given a class ``Example`` with Python bindings, it's possible to return
instances wrapped in C++11 unique pointers, like so
.. code-block:: cpp
std::unique_ptr<Example> create_example() { return std::unique_ptr<Example>(new Example()); }
.. code-block:: cpp
m.def("create_example", &create_example);
In other words, there is nothing special that needs to be done. While returning
unique pointers in this way is allowed, it is *illegal* to use them as function
arguments. For instance, the following function signature cannot be processed
by pybind11.
.. code-block:: cpp
void do_something_with_example(std::unique_ptr<Example> ex) { ... }
The above signature would imply that Python needs to give up ownership of an
object that is passed to this function, which is generally not possible (for
instance, the object might be referenced elsewhere).
std::shared_ptr
===============
The binding generator for classes, :class:`class_`, can be passed a template
type that denotes a special *holder* type that is used to manage references to
the object. If no such holder type template argument is given, the default for
a type named ``Type`` is ``std::unique_ptr<Type>``, which means that the object
is deallocated when Python's reference count goes to zero.
It is possible to switch to other types of reference counting wrappers or smart
pointers, which is useful in codebases that rely on them. For instance, the
following snippet causes ``std::shared_ptr`` to be used instead.
.. code-block:: cpp
py::class_<Example, std::shared_ptr<Example> /* <- holder type */> obj(m, "Example");
Note that any particular class can only be associated with a single holder type.
One potential stumbling block when using holder types is that they need to be
applied consistently. Can you guess what's broken about the following binding
code?
.. code-block:: cpp
class Child { };
class Parent {
public:
Parent() : child(std::make_shared<Child>()) { }
Child *get_child() { return child.get(); } /* Hint: ** DON'T DO THIS ** */
private:
std::shared_ptr<Child> child;
};
PYBIND11_PLUGIN(example) {
py::module m("example");
py::class_<Child, std::shared_ptr<Child>>(m, "Child");
py::class_<Parent, std::shared_ptr<Parent>>(m, "Parent")
.def(py::init<>())
.def("get_child", &Parent::get_child);
return m.ptr();
}
The following Python code will cause undefined behavior (and likely a
segmentation fault).
.. code-block:: python
from example import Parent
print(Parent().get_child())
The problem is that ``Parent::get_child()`` returns a pointer to an instance of
``Child``, but the fact that this instance is already managed by
``std::shared_ptr<...>`` is lost when passing raw pointers. In this case,
pybind11 will create a second independent ``std::shared_ptr<...>`` that also
claims ownership of the pointer. In the end, the object will be freed **twice**
since these shared pointers have no way of knowing about each other.
There are two ways to resolve this issue:
1. For types that are managed by a smart pointer class, never use raw pointers
in function arguments or return values. In other words: always consistently
wrap pointers into their designated holder types (such as
``std::shared_ptr<...>``). In this case, the signature of ``get_child()``
should be modified as follows:
.. code-block:: cpp
std::shared_ptr<Child> get_child() { return child; }
2. Adjust the definition of ``Child`` by specifying
``std::enable_shared_from_this<T>`` (see cppreference_ for details) as a
base class. This adds a small bit of information to ``Child`` that allows
pybind11 to realize that there is already an existing
``std::shared_ptr<...>`` and communicate with it. In this case, the
declaration of ``Child`` should look as follows:
.. _cppreference: http://en.cppreference.com/w/cpp/memory/enable_shared_from_this
.. code-block:: cpp
class Child : public std::enable_shared_from_this<Child> { };
.. _smart_pointers:
Custom smart pointers
=====================
pybind11 supports ``std::unique_ptr`` and ``std::shared_ptr`` right out of the
box. For any other custom smart pointer, transparent conversions can be enabled
using a macro invocation similar to the following. It must be declared at the
level before any binding code:
.. code-block:: cpp
PYBIND11_DECLARE_HOLDER_TYPE(T, SmartPtr<T>);
The first argument of :func:`PYBIND11_DECLARE_HOLDER_TYPE` should be a
placeholder name that is used as a template parameter of the second argument.
Thus, feel free to use any identifier, but use it consistently on both sides;
also, don't use the name of a type that already exists in your codebase.
Please take a look at the :ref:`macro_notes` before using this feature.
.. seealso::
The file :file:`tests/test_smart_ptr.cpp` contains a complete example
that demonstrates how to work with custom reference-counting holder types
in more detail.

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.. _basics:
First steps
###########
This sections demonstrates the basic features of pybind11. Before getting
started, make sure that development environment is set up to compile the
included set of test cases.
Compiling the test cases
========================
Linux/MacOS
-----------
On Linux you'll need to install the **python-dev** or **python3-dev** packages as
well as **cmake**. On Mac OS, the included python version works out of the box,
but **cmake** must still be installed.
After installing the prerequisites, run
.. code-block:: bash
mkdir build
cd build
cmake ..
make pytest -j 4
The last line will both compile and run the tests.
Windows
-------
On Windows, only **Visual Studio 2015** and newer are supported since pybind11 relies
on various C++11 language features that break older versions of Visual Studio.
To compile and run the tests:
.. code-block:: batch
mkdir build
cd build
cmake ..
cmake --build . --config Release --target pytest
This will create a Visual Studio project, compile and run the target, all from the
command line.
.. Note::
If all tests fail, make sure that the Python binary and the testcases are compiled
for the same processor type and bitness (i.e. either **i386** or **x86_64**). You
can specify **x86_64** as the target architecture for the generated Visual Studio
project using ``cmake -A x64 ..``.
.. seealso::
Advanced users who are already familiar with Boost.Python may want to skip
the tutorial and look at the test cases in the :file:`tests` directory,
which exercise all features of pybind11.
Header and namespace conventions
================================
For brevity, all code examples assume that the following two lines are present:
.. code-block:: cpp
#include <pybind11/pybind11.h>
namespace py = pybind11;
Some features may require additional headers, but those will be specified as needed.
Creating bindings for a simple function
=======================================
Let's start by creating Python bindings for an extremely simple function, which
adds two numbers and returns their result:
.. code-block:: cpp
int add(int i, int j) {
return i + j;
}
For simplicity [#f1]_, we'll put both this function and the binding code into
a file named :file:`example.cpp` with the following contents:
.. code-block:: cpp
#include <pybind11/pybind11.h>
int add(int i, int j) {
return i + j;
}
namespace py = pybind11;
PYBIND11_PLUGIN(example) {
py::module m("example", "pybind11 example plugin");
m.def("add", &add, "A function which adds two numbers");
return m.ptr();
}
.. [#f1] In practice, implementation and binding code will generally be located
in separate files.
The :func:`PYBIND11_PLUGIN` macro creates a function that will be called when an
``import`` statement is issued from within Python. The next line creates a
module named ``example`` (with the supplied docstring). The method
:func:`module::def` generates binding code that exposes the
``add()`` function to Python. The last line returns the internal Python object
associated with ``m`` to the Python interpreter.
.. note::
Notice how little code was needed to expose our function to Python: all
details regarding the function's parameters and return value were
automatically inferred using template metaprogramming. This overall
approach and the used syntax are borrowed from Boost.Python, though the
underlying implementation is very different.
pybind11 is a header-only-library, hence it is not necessary to link against
any special libraries (other than Python itself). On Windows, use the CMake
build file discussed in section :ref:`cmake`. On Linux and Mac OS, the above
example can be compiled using the following command
.. code-block:: bash
$ c++ -O3 -shared -std=c++11 -I <path-to-pybind11>/include `python-config --cflags --ldflags` example.cpp -o example.so
In general, it is advisable to include several additional build parameters
that can considerably reduce the size of the created binary. Refer to section
:ref:`cmake` for a detailed example of a suitable cross-platform CMake-based
build system.
Assuming that the created file :file:`example.so` (:file:`example.pyd` on Windows)
is located in the current directory, the following interactive Python session
shows how to load and execute the example.
.. code-block:: pycon
$ python
Python 2.7.10 (default, Aug 22 2015, 20:33:39)
[GCC 4.2.1 Compatible Apple LLVM 7.0.0 (clang-700.0.59.1)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import example
>>> example.add(1, 2)
3L
>>>
.. _keyword_args:
Keyword arguments
=================
With a simple modification code, it is possible to inform Python about the
names of the arguments ("i" and "j" in this case).
.. code-block:: cpp
m.def("add", &add, "A function which adds two numbers",
py::arg("i"), py::arg("j"));
:class:`arg` is one of several special tag classes which can be used to pass
metadata into :func:`module::def`. With this modified binding code, we can now
call the function using keyword arguments, which is a more readable alternative
particularly for functions taking many parameters:
.. code-block:: pycon
>>> import example
>>> example.add(i=1, j=2)
3L
The keyword names also appear in the function signatures within the documentation.
.. code-block:: pycon
>>> help(example)
....
FUNCTIONS
add(...)
Signature : (i: int, j: int) -> int
A function which adds two numbers
A shorter notation for named arguments is also available:
.. code-block:: cpp
// regular notation
m.def("add1", &add, py::arg("i"), py::arg("j"));
// shorthand
using namespace pybind11::literals;
m.def("add2", &add, "i"_a, "j"_a);
The :var:`_a` suffix forms a C++11 literal which is equivalent to :class:`arg`.
Note that the literal operator must first be made visible with the directive
``using namespace pybind11::literals``. This does not bring in anything else
from the ``pybind11`` namespace except for literals.
.. _default_args:
Default arguments
=================
Suppose now that the function to be bound has default arguments, e.g.:
.. code-block:: cpp
int add(int i = 1, int j = 2) {
return i + j;
}
Unfortunately, pybind11 cannot automatically extract these parameters, since they
are not part of the function's type information. However, they are simple to specify
using an extension of :class:`arg`:
.. code-block:: cpp
m.def("add", &add, "A function which adds two numbers",
py::arg("i") = 1, py::arg("j") = 2);
The default values also appear within the documentation.
.. code-block:: pycon
>>> help(example)
....
FUNCTIONS
add(...)
Signature : (i: int = 1, j: int = 2) -> int
A function which adds two numbers
The shorthand notation is also available for default arguments:
.. code-block:: cpp
// regular notation
m.def("add1", &add, py::arg("i") = 1, py::arg("j") = 2);
// shorthand
m.def("add2", &add, "i"_a=1, "j"_a=2);
Exporting variables
===================
To expose a value from C++, use the ``attr`` function to register it in a module
as shown below. Built-in types and general objects (more on that later) can be
converted using the function ``py::cast``.
.. code-block:: cpp
PYBIND11_PLUGIN(example) {
py::module m("example", "pybind11 example plugin");
m.attr("the_answer") = py::cast(42);
m.attr("what") = py::cast("World");
return m.ptr();
}
These are then accessible from Python:
.. code-block:: pycon
>>> import example
>>> example.the_answer
42
>>> example.what
'World'
.. _supported_types:
Supported data types
====================
A large number of data types are supported out of the box and can be used
seamlessly as functions arguments, return values or with ``py::cast`` in general.
For a full overview, see the :doc:`advanced/cast/index` section.

90
resources/pybind11/docs/benchmark.py

@ -0,0 +1,90 @@
import random
import os
import time
import datetime as dt
nfns = 4 # Functions per class
nargs = 4 # Arguments per function
def generate_dummy_code_pybind11(nclasses=10):
decl = ""
bindings = ""
for cl in range(nclasses):
decl += "class cl%03i;\n" % cl
decl += '\n'
for cl in range(nclasses):
decl += "class cl%03i {\n" % cl
decl += "public:\n"
bindings += ' py::class_<cl%03i>(m, "cl%03i")\n' % (cl, cl)
for fn in range(nfns):
ret = random.randint(0, nclasses - 1)
params = [random.randint(0, nclasses - 1) for i in range(nargs)]
decl += " cl%03i *fn_%03i(" % (ret, fn)
decl += ", ".join("cl%03i *" % p for p in params)
decl += ");\n"
bindings += ' .def("fn_%03i", &cl%03i::fn_%03i)\n' % \
(fn, cl, fn)
decl += "};\n\n"
bindings += ' ;\n'
result = "#include <pybind11/pybind11.h>\n\n"
result += "namespace py = pybind11;\n\n"
result += decl + '\n'
result += "PYBIND11_PLUGIN(example) {\n"
result += " py::module m(\"example\");"
result += bindings
result += " return m.ptr();"
result += "}"
return result
def generate_dummy_code_boost(nclasses=10):
decl = ""
bindings = ""
for cl in range(nclasses):
decl += "class cl%03i;\n" % cl
decl += '\n'
for cl in range(nclasses):
decl += "class cl%03i {\n" % cl
decl += "public:\n"
bindings += ' py::class_<cl%03i>("cl%03i")\n' % (cl, cl)
for fn in range(nfns):
ret = random.randint(0, nclasses - 1)
params = [random.randint(0, nclasses - 1) for i in range(nargs)]
decl += " cl%03i *fn_%03i(" % (ret, fn)
decl += ", ".join("cl%03i *" % p for p in params)
decl += ");\n"
bindings += ' .def("fn_%03i", &cl%03i::fn_%03i, py::return_value_policy<py::manage_new_object>())\n' % \
(fn, cl, fn)
decl += "};\n\n"
bindings += ' ;\n'
result = "#include <boost/python.hpp>\n\n"
result += "namespace py = boost::python;\n\n"
result += decl + '\n'
result += "BOOST_PYTHON_MODULE(example) {\n"
result += bindings
result += "}"
return result
for codegen in [generate_dummy_code_pybind11, generate_dummy_code_boost]:
print ("{")
for i in range(0, 10):
nclasses = 2 ** i
with open("test.cpp", "w") as f:
f.write(codegen(nclasses))
n1 = dt.datetime.now()
os.system("g++ -Os -shared -rdynamic -undefined dynamic_lookup "
"-fvisibility=hidden -std=c++14 test.cpp -I include "
"-I /System/Library/Frameworks/Python.framework/Headers -o test.so")
n2 = dt.datetime.now()
elapsed = (n2 - n1).total_seconds()
size = os.stat('test.so').st_size
print(" {%i, %f, %i}," % (nclasses * nfns, elapsed, size))
print ("}")

99
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@ -0,0 +1,99 @@
Benchmark
=========
The following is the result of a synthetic benchmark comparing both compilation
time and module size of pybind11 against Boost.Python. A detailed report about a
Boost.Python to pybind11 conversion of a real project is available here: [#f1]_.
.. [#f1] http://graylab.jhu.edu/RosettaCon2016/PyRosetta-4.pdf
Setup
-----
A python script (see the ``docs/benchmark.py`` file) was used to generate a set
of files with dummy classes whose count increases for each successive benchmark
(between 1 and 2048 classes in powers of two). Each class has four methods with
a randomly generated signature with a return value and four arguments. (There
was no particular reason for this setup other than the desire to generate many
unique function signatures whose count could be controlled in a simple way.)
Here is an example of the binding code for one class:
.. code-block:: cpp
...
class cl034 {
public:
cl279 *fn_000(cl084 *, cl057 *, cl065 *, cl042 *);
cl025 *fn_001(cl098 *, cl262 *, cl414 *, cl121 *);
cl085 *fn_002(cl445 *, cl297 *, cl145 *, cl421 *);
cl470 *fn_003(cl200 *, cl323 *, cl332 *, cl492 *);
};
...
PYBIND11_PLUGIN(example) {
py::module m("example");
...
py::class_<cl034>(m, "cl034")
.def("fn_000", &cl034::fn_000)
.def("fn_001", &cl034::fn_001)
.def("fn_002", &cl034::fn_002)
.def("fn_003", &cl034::fn_003)
...
return m.ptr();
}
The Boost.Python version looks almost identical except that a return value
policy had to be specified as an argument to ``def()``. For both libraries,
compilation was done with
.. code-block:: bash
Apple LLVM version 7.0.2 (clang-700.1.81)
and the following compilation flags
.. code-block:: bash
g++ -Os -shared -rdynamic -undefined dynamic_lookup -fvisibility=hidden -std=c++14
Compilation time
----------------
The following log-log plot shows how the compilation time grows for an
increasing number of class and function declarations. pybind11 includes many
fewer headers, which initially leads to shorter compilation times, but the
performance is ultimately fairly similar (pybind11 is 19.8 seconds faster for
the largest largest file with 2048 classes and a total of 8192 methods -- a
modest **1.2x** speedup relative to Boost.Python, which required 116.35
seconds).
.. only:: not latex
.. image:: pybind11_vs_boost_python1.svg
.. only:: latex
.. image:: pybind11_vs_boost_python1.png
Module size
-----------
Differences between the two libraries become much more pronounced when
considering the file size of the generated Python plugin: for the largest file,
the binary generated by Boost.Python required 16.8 MiB, which was **2.17
times** / **9.1 megabytes** larger than the output generated by pybind11. For
very small inputs, Boost.Python has an edge in the plot below -- however, note
that it stores many definitions in an external library, whose size was not
included here, hence the comparison is slightly shifted in Boost.Python's
favor.
.. only:: not latex
.. image:: pybind11_vs_boost_python2.svg
.. only:: latex
.. image:: pybind11_vs_boost_python2.png

222
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@ -0,0 +1,222 @@
.. _changelog:
Changelog
#########
Starting with version 1.8, pybind11 releases use a
[semantic versioning](http://semver.org) policy.
Breaking changes queued for v2.0.0 (Not yet released)
-----------------------------------------------------
* Redesigned virtual call mechanism and user-facing syntax (see
https://github.com/pybind/pybind11/commit/86d825f3302701d81414ddd3d38bcd09433076bc)
* Remove ``handle.call()`` method
1.9.0 (Not yet released)
------------------------
* Queued changes: map indexing suite, documentation for indexing suites.
* Mapping a stateless C++ function to Python and back is now "for free" (i.e. no call overheads)
* Support for translation of arbitrary C++ exceptions to Python counterparts
* Added ``eval`` and ``eval_file`` functions for evaluating expressions and
statements from a string or file
* eigen.h type converter fixed for non-contiguous arrays (e.g. slices)
* Print more informative error messages when ``make_tuple()`` or ``cast()`` fail
* ``std::enable_shared_from_this<>`` now also works for ``const`` values
* A return value policy can now be passed to ``handle::operator()``
* ``make_iterator()`` improvements for better compatibility with various types
(now uses prefix increment operator); it now also accepts iterators with
different begin/end types as long as they are equality comparable.
* ``arg()`` now accepts a wider range of argument types for default values
* Added ``py::repr()`` function which is equivalent to Python's builtin ``repr()``.
* Added support for registering structured dtypes via ``PYBIND11_NUMPY_DTYPE()`` macro.
* Added ``PYBIND11_STR_TYPE`` macro which maps to the ``builtins.str`` type.
* Added a simplified ``buffer_info`` constructor for 1-dimensional buffers.
* Format descriptor strings should now be accessed via ``format_descriptor::format()``
(for compatibility purposes, the old syntax ``format_descriptor::value`` will still
work for non-structured data types).
* Added a class wrapping NumPy array descriptors: ``dtype``.
* Added buffer/NumPy support for ``char[N]`` and ``std::array<char, N>`` types.
* ``array`` gained new constructors accepting dtype objects.
* Added constructors for ``array`` and ``array_t`` explicitly accepting shape and
strides; if strides are not provided, they are deduced assuming C-contiguity.
Also added simplified constructors for 1-dimensional case.
* Added constructors for ``str`` from ``bytes`` and for ``bytes`` from ``str``.
This will do the UTF-8 decoding/encoding as required.
* Added constructors for ``str`` and ``bytes`` from zero-terminated char pointers,
and from char pointers and length.
* Added ``memoryview`` wrapper type which is constructible from ``buffer_info``.
* New syntax to call a Python function from C++ using keyword arguments and unpacking,
e.g. ``foo(1, 2, "z"_a=3)`` or ``bar(1, *args, "z"_a=3, **kwargs)``.
* Added ``py::print()`` function which replicates Python's API and writes to Python's
``sys.stdout`` by default (as opposed to C's ``stdout`` like ``std::cout``).
* Added ``py::dict`` keyword constructor:``auto d = dict("number"_a=42, "name"_a="World");``
* Added ``py::str::format()`` method and ``_s`` literal:
``py::str s = "1 + 2 = {}"_s.format(3);``
* Attribute and item accessors now have a more complete interface which makes it possible
to chain attributes ``obj.attr("a")[key].attr("b").attr("method")(1, 2, 3)```.
* Added built-in support for ``std::shared_ptr`` holder type. There is no more need
to do it manually via ``PYBIND11_DECLARE_HOLDER_TYPE(T, std::shared_ptr<T>)``.
* Default return values policy changes: non-static properties now use ``reference_internal``
and static properties use ``reference`` (previous default was ``automatic``, i.e. ``copy``).
* Support for ``std::experimental::optional<T>`` and ``std::optional<T>`` (C++17).
* Various minor improvements of library internals (no user-visible changes)
1.8.1 (July 12, 2016)
----------------------
* Fixed a rare but potentially very severe issue when the garbage collector ran
during pybind11 type creation.
1.8.0 (June 14, 2016)
----------------------
* Redesigned CMake build system which exports a convenient
``pybind11_add_module`` function to parent projects.
* ``std::vector<>`` type bindings analogous to Boost.Python's ``indexing_suite``
* Transparent conversion of sparse and dense Eigen matrices and vectors (``eigen.h``)
* Added an ``ExtraFlags`` template argument to the NumPy ``array_t<>`` wrapper
to disable an enforced cast that may lose precision, e.g. to create overloads
for different precisions and complex vs real-valued matrices.
* Prevent implicit conversion of floating point values to integral types in
function arguments
* Fixed incorrect default return value policy for functions returning a shared
pointer
* Don't allow registering a type via ``class_`` twice
* Don't allow casting a ``None`` value into a C++ lvalue reference
* Fixed a crash in ``enum_::operator==`` that was triggered by the ``help()`` command
* Improved detection of whether or not custom C++ types can be copy/move-constructed
* Extended ``str`` type to also work with ``bytes`` instances
* Added a ``"name"_a`` user defined string literal that is equivalent to ``py::arg("name")``.
* When specifying function arguments via ``py::arg``, the test that verifies
the number of arguments now runs at compile time.
* Added ``[[noreturn]]`` attribute to ``pybind11_fail()`` to quench some
compiler warnings
* List function arguments in exception text when the dispatch code cannot find
a matching overload
* Added ``PYBIND11_OVERLOAD_NAME`` and ``PYBIND11_OVERLOAD_PURE_NAME`` macros which
can be used to override virtual methods whose name differs in C++ and Python
(e.g. ``__call__`` and ``operator()``)
* Various minor ``iterator`` and ``make_iterator()`` improvements
* Transparently support ``__bool__`` on Python 2.x and Python 3.x
* Fixed issue with destructor of unpickled object not being called
* Minor CMake build system improvements on Windows
* New ``pybind11::args`` and ``pybind11::kwargs`` types to create functions which
take an arbitrary number of arguments and keyword arguments
* New syntax to call a Python function from C++ using ``*args`` and ``*kwargs``
* The functions ``def_property_*`` now correctly process docstring arguments (these
formerly caused a segmentation fault)
* Many ``mkdoc.py`` improvements (enumerations, template arguments, ``DOC()``
macro accepts more arguments)
* Cygwin support
* Documentation improvements (pickling support, ``keep_alive``, macro usage)
1.7 (April 30, 2016)
----------------------
* Added a new ``move`` return value policy that triggers C++11 move semantics.
The automatic return value policy falls back to this case whenever a rvalue
reference is encountered
* Significantly more general GIL state routines that are used instead of
Python's troublesome ``PyGILState_Ensure`` and ``PyGILState_Release`` API
* Redesign of opaque types that drastically simplifies their usage
* Extended ability to pass values of type ``[const] void *``
* ``keep_alive`` fix: don't fail when there is no patient
* ``functional.h``: acquire the GIL before calling a Python function
* Added Python RAII type wrappers ``none`` and ``iterable``
* Added ``*args`` and ``*kwargs`` pass-through parameters to
``pybind11.get_include()`` function
* Iterator improvements and fixes
* Documentation on return value policies and opaque types improved
1.6 (April 30, 2016)
----------------------
* Skipped due to upload to PyPI gone wrong and inability to recover
(https://github.com/pypa/packaging-problems/issues/74)
1.5 (April 21, 2016)
----------------------
* For polymorphic types, use RTTI to try to return the closest type registered with pybind11
* Pickling support for serializing and unserializing C++ instances to a byte stream in Python
* Added a convenience routine ``make_iterator()`` which turns a range indicated
by a pair of C++ iterators into a iterable Python object
* Added ``len()`` and a variadic ``make_tuple()`` function
* Addressed a rare issue that could confuse the current virtual function
dispatcher and another that could lead to crashes in multi-threaded
applications
* Added a ``get_include()`` function to the Python module that returns the path
of the directory containing the installed pybind11 header files
* Documentation improvements: import issues, symbol visibility, pickling, limitations
* Added casting support for ``std::reference_wrapper<>``
1.4 (April 7, 2016)
--------------------------
* Transparent type conversion for ``std::wstring`` and ``wchar_t``
* Allow passing ``nullptr``-valued strings
* Transparent passing of ``void *`` pointers using capsules
* Transparent support for returning values wrapped in ``std::unique_ptr<>``
* Improved docstring generation for compatibility with Sphinx
* Nicer debug error message when default parameter construction fails
* Support for "opaque" types that bypass the transparent conversion layer for STL containers
* Redesigned type casting interface to avoid ambiguities that could occasionally cause compiler errors
* Redesigned property implementation; fixes crashes due to an unfortunate default return value policy
* Anaconda package generation support
1.3 (March 8, 2016)
--------------------------
* Added support for the Intel C++ compiler (v15+)
* Added support for the STL unordered set/map data structures
* Added support for the STL linked list data structure
* NumPy-style broadcasting support in ``pybind11::vectorize``
* pybind11 now displays more verbose error messages when ``arg::operator=()`` fails
* pybind11 internal data structures now live in a version-dependent namespace to avoid ABI issues
* Many, many bugfixes involving corner cases and advanced usage
1.2 (February 7, 2016)
--------------------------
* Optional: efficient generation of function signatures at compile time using C++14
* Switched to a simpler and more general way of dealing with function default
arguments. Unused keyword arguments in function calls are now detected and
cause errors as expected
* New ``keep_alive`` call policy analogous to Boost.Python's ``with_custodian_and_ward``
* New ``pybind11::base<>`` attribute to indicate a subclass relationship
* Improved interface for RAII type wrappers in ``pytypes.h``
* Use RAII type wrappers consistently within pybind11 itself. This
fixes various potential refcount leaks when exceptions occur
* Added new ``bytes`` RAII type wrapper (maps to ``string`` in Python 2.7)
* Made handle and related RAII classes const correct, using them more
consistently everywhere now
* Got rid of the ugly ``__pybind11__`` attributes on the Python side---they are
now stored in a C++ hash table that is not visible in Python
* Fixed refcount leaks involving NumPy arrays and bound functions
* Vastly improved handling of shared/smart pointers
* Removed an unnecessary copy operation in ``pybind11::vectorize``
* Fixed naming clashes when both pybind11 and NumPy headers are included
* Added conversions for additional exception types
* Documentation improvements (using multiple extension modules, smart pointers,
other minor clarifications)
* unified infrastructure for parsing variadic arguments in ``class_`` and cpp_function
* Fixed license text (was: ZLIB, should have been: 3-clause BSD)
* Python 3.2 compatibility
* Fixed remaining issues when accessing types in another plugin module
* Added enum comparison and casting methods
* Improved SFINAE-based detection of whether types are copy-constructible
* Eliminated many warnings about unused variables and the use of ``offsetof()``
* Support for ``std::array<>`` conversions
1.1 (December 7, 2015)
--------------------------
* Documentation improvements (GIL, wrapping functions, casting, fixed many typos)
* Generalized conversion of integer types
* Improved support for casting function objects
* Improved support for ``std::shared_ptr<>`` conversions
* Initial support for ``std::set<>`` conversions
* Fixed type resolution issue for types defined in a separate plugin module
* Cmake build system improvements
* Factored out generic functionality to non-templated code (smaller code size)
* Added a code size / compile time benchmark vs Boost.Python
* Added an appveyor CI script
1.0 (October 15, 2015)
------------------------
* Initial release

410
resources/pybind11/docs/classes.rst

@ -0,0 +1,410 @@
.. _classes:
Object-oriented code
####################
Creating bindings for a custom type
===================================
Let's now look at a more complex example where we'll create bindings for a
custom C++ data structure named ``Pet``. Its definition is given below:
.. code-block:: cpp
struct Pet {
Pet(const std::string &name) : name(name) { }
void setName(const std::string &name_) { name = name_; }
const std::string &getName() const { return name; }
std::string name;
};
The binding code for ``Pet`` looks as follows:
.. code-block:: cpp
#include <pybind11/pybind11.h>
namespace py = pybind11;
PYBIND11_PLUGIN(example) {
py::module m("example", "pybind11 example plugin");
py::class_<Pet>(m, "Pet")
.def(py::init<const std::string &>())
.def("setName", &Pet::setName)
.def("getName", &Pet::getName);
return m.ptr();
}
:class:`class_` creates bindings for a C++ `class` or `struct`-style data
structure. :func:`init` is a convenience function that takes the types of a
constructor's parameters as template arguments and wraps the corresponding
constructor (see the :ref:`custom_constructors` section for details). An
interactive Python session demonstrating this example is shown below:
.. code-block:: pycon
% python
>>> import example
>>> p = example.Pet('Molly')
>>> print(p)
<example.Pet object at 0x10cd98060>
>>> p.getName()
u'Molly'
>>> p.setName('Charly')
>>> p.getName()
u'Charly'
.. seealso::
Static member functions can be bound in the same way using
:func:`class_::def_static`.
Keyword and default arguments
=============================
It is possible to specify keyword and default arguments using the syntax
discussed in the previous chapter. Refer to the sections :ref:`keyword_args`
and :ref:`default_args` for details.
Binding lambda functions
========================
Note how ``print(p)`` produced a rather useless summary of our data structure in the example above:
.. code-block:: pycon
>>> print(p)
<example.Pet object at 0x10cd98060>
To address this, we could bind an utility function that returns a human-readable
summary to the special method slot named ``__repr__``. Unfortunately, there is no
suitable functionality in the ``Pet`` data structure, and it would be nice if
we did not have to change it. This can easily be accomplished by binding a
Lambda function instead:
.. code-block:: cpp
py::class_<Pet>(m, "Pet")
.def(py::init<const std::string &>())
.def("setName", &Pet::setName)
.def("getName", &Pet::getName)
.def("__repr__",
[](const Pet &a) {
return "<example.Pet named '" + a.name + "'>";
}
);
Both stateless [#f1]_ and stateful lambda closures are supported by pybind11.
With the above change, the same Python code now produces the following output:
.. code-block:: pycon
>>> print(p)
<example.Pet named 'Molly'>
.. _properties:
Instance and static fields
==========================
We can also directly expose the ``name`` field using the
:func:`class_::def_readwrite` method. A similar :func:`class_::def_readonly`
method also exists for ``const`` fields.
.. code-block:: cpp
py::class_<Pet>(m, "Pet")
.def(py::init<const std::string &>())
.def_readwrite("name", &Pet::name)
// ... remainder ...
This makes it possible to write
.. code-block:: pycon
>>> p = example.Pet('Molly')
>>> p.name
u'Molly'
>>> p.name = 'Charly'
>>> p.name
u'Charly'
Now suppose that ``Pet::name`` was a private internal variable
that can only be accessed via setters and getters.
.. code-block:: cpp
class Pet {
public:
Pet(const std::string &name) : name(name) { }
void setName(const std::string &name_) { name = name_; }
const std::string &getName() const { return name; }
private:
std::string name;
};
In this case, the method :func:`class_::def_property`
(:func:`class_::def_property_readonly` for read-only data) can be used to
provide a field-like interface within Python that will transparently call
the setter and getter functions:
.. code-block:: cpp
py::class_<Pet>(m, "Pet")
.def(py::init<const std::string &>())
.def_property("name", &Pet::getName, &Pet::setName)
// ... remainder ...
.. seealso::
Similar functions :func:`class_::def_readwrite_static`,
:func:`class_::def_readonly_static` :func:`class_::def_property_static`,
and :func:`class_::def_property_readonly_static` are provided for binding
static variables and properties. Please also see the section on
:ref:`static_properties` in the advanced part of the documentation.
Dynamic attributes
==================
Native Python classes can pick up new attributes dynamically:
.. code-block:: pycon
>>> class Pet:
... name = 'Molly'
...
>>> p = Pet()
>>> p.name = 'Charly' # overwrite existing
>>> p.age = 2 # dynamically add a new attribute
By default, classes exported from C++ do not support this and the only writable
attributes are the ones explicitly defined using :func:`class_::def_readwrite`
or :func:`class_::def_property`.
.. code-block:: cpp
py::class_<Pet>(m, "Pet")
.def(py::init<>())
.def_readwrite("name", &Pet::name);
Trying to set any other attribute results in an error:
.. code-block:: pycon
>>> p = example.Pet()
>>> p.name = 'Charly' # OK, attribute defined in C++
>>> p.age = 2 # fail
AttributeError: 'Pet' object has no attribute 'age'
To enable dynamic attributes for C++ classes, the :class:`py::dynamic_attr` tag
must be added to the :class:`py::class_` constructor:
.. code-block:: cpp
py::class_<Pet>(m, "Pet", py::dynamic_attr())
.def(py::init<>())
.def_readwrite("name", &Pet::name);
Now everything works as expected:
.. code-block:: pycon
>>> p = example.Pet()
>>> p.name = 'Charly' # OK, overwrite value in C++
>>> p.age = 2 # OK, dynamically add a new attribute
>>> p.__dict__ # just like a native Python class
{'age': 2}
Note that there is a small runtime cost for a class with dynamic attributes.
Not only because of the addition of a ``__dict__``, but also because of more
expensive garbage collection tracking which must be activated to resolve
possible circular references. Native Python classes incur this same cost by
default, so this is not anything to worry about. By default, pybind11 classes
are more efficient than native Python classes. Enabling dynamic attributes
just brings them on par.
.. _inheritance:
Inheritance
===========
Suppose now that the example consists of two data structures with an
inheritance relationship:
.. code-block:: cpp
struct Pet {
Pet(const std::string &name) : name(name) { }
std::string name;
};
struct Dog : Pet {
Dog(const std::string &name) : Pet(name) { }
std::string bark() const { return "woof!"; }
};
There are two different ways of indicating a hierarchical relationship to
pybind11: the first specifies the C++ base class as an extra template
parameter of the :class:`class_`:
.. code-block:: cpp
py::class_<Pet>(m, "Pet")
.def(py::init<const std::string &>())
.def_readwrite("name", &Pet::name);
// Method 1: template parameter:
py::class_<Dog, Pet /* <- specify C++ parent type */>(m, "Dog")
.def(py::init<const std::string &>())
.def("bark", &Dog::bark);
Alternatively, we can also assign a name to the previously bound ``Pet``
:class:`class_` object and reference it when binding the ``Dog`` class:
.. code-block:: cpp
py::class_<Pet> pet(m, "Pet");
pet.def(py::init<const std::string &>())
.def_readwrite("name", &Pet::name);
// Method 2: pass parent class_ object:
py::class_<Dog>(m, "Dog", pet /* <- specify Python parent type */)
.def(py::init<const std::string &>())
.def("bark", &Dog::bark);
Functionality-wise, both approaches are equivalent. Afterwards, instances will
expose fields and methods of both types:
.. code-block:: pycon
>>> p = example.Dog('Molly')
>>> p.name
u'Molly'
>>> p.bark()
u'woof!'
Overloaded methods
==================
Sometimes there are several overloaded C++ methods with the same name taking
different kinds of input arguments:
.. code-block:: cpp
struct Pet {
Pet(const std::string &name, int age) : name(name), age(age) { }
void set(int age) { age = age; }
void set(const std::string &name) { name = name; }
std::string name;
int age;
};
Attempting to bind ``Pet::set`` will cause an error since the compiler does not
know which method the user intended to select. We can disambiguate by casting
them to function pointers. Binding multiple functions to the same Python name
automatically creates a chain of function overloads that will be tried in
sequence.
.. code-block:: cpp
py::class_<Pet>(m, "Pet")
.def(py::init<const std::string &, int>())
.def("set", (void (Pet::*)(int)) &Pet::set, "Set the pet's age")
.def("set", (void (Pet::*)(const std::string &)) &Pet::set, "Set the pet's name");
The overload signatures are also visible in the method's docstring:
.. code-block:: pycon
>>> help(example.Pet)
class Pet(__builtin__.object)
| Methods defined here:
|
| __init__(...)
| Signature : (Pet, str, int) -> NoneType
|
| set(...)
| 1. Signature : (Pet, int) -> NoneType
|
| Set the pet's age
|
| 2. Signature : (Pet, str) -> NoneType
|
| Set the pet's name
.. note::
To define multiple overloaded constructors, simply declare one after the
other using the ``.def(py::init<...>())`` syntax. The existing machinery
for specifying keyword and default arguments also works.
Enumerations and internal types
===============================
Let's now suppose that the example class contains an internal enumeration type,
e.g.:
.. code-block:: cpp
struct Pet {
enum Kind {
Dog = 0,
Cat
};
Pet(const std::string &name, Kind type) : name(name), type(type) { }
std::string name;
Kind type;
};
The binding code for this example looks as follows:
.. code-block:: cpp
py::class_<Pet> pet(m, "Pet");
pet.def(py::init<const std::string &, Pet::Kind>())
.def_readwrite("name", &Pet::name)
.def_readwrite("type", &Pet::type);
py::enum_<Pet::Kind>(pet, "Kind")
.value("Dog", Pet::Kind::Dog)
.value("Cat", Pet::Kind::Cat)
.export_values();
To ensure that the ``Kind`` type is created within the scope of ``Pet``, the
``pet`` :class:`class_` instance must be supplied to the :class:`enum_`.
constructor. The :func:`enum_::export_values` function exports the enum entries
into the parent scope, which should be skipped for newer C++11-style strongly
typed enums.
.. code-block:: pycon
>>> p = Pet('Lucy', Pet.Cat)
>>> p.type
Kind.Cat
>>> int(p.type)
1L
.. note::
When the special tag ``py::arithmetic()`` is specified to the ``enum_``
constructor, pybind11 creates an enumeration that also supports rudimentary
arithmetic and bit-level operations like comparisons, and, or, xor, negation,
etc.
.. code-block:: cpp
py::enum_<Pet::Kind>(pet, "Kind", py::arithmetic())
...
By default, these are omitted to conserve space.
.. [#f1] Stateless closures are those with an empty pair of brackets ``[]`` as the capture object.

53
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@ -0,0 +1,53 @@
Build systems
#############
Building with setuptools
========================
For projects on PyPI, building with setuptools is the way to go. Sylvain Corlay
has kindly provided an example project which shows how to set up everything,
including automatic generation of documentation using Sphinx. Please refer to
the [python_example]_ repository.
.. [python_example] https://github.com/pybind/python_example
Building with cppimport
========================
cppimport is a small Python import hook that determines whether there is a C++
source file whose name matches the requested module. If there is, the file is
compiled as a Python extension using pybind11 and placed in the same folder as
the C++ source file. Python is then able to find the module and load it.
.. [cppimport] https://github.com/tbenthompson/cppimport
.. _cmake:
Building with CMake
===================
For C++ codebases that have an existing CMake-based build system, a Python
extension module can be created with just a few lines of code:
.. code-block:: cmake
cmake_minimum_required(VERSION 2.8.12)
project(example)
add_subdirectory(pybind11)
pybind11_add_module(example example.cpp)
This assumes that the pybind11 repository is located in a subdirectory named
:file:`pybind11` and that the code is located in a file named :file:`example.cpp`.
The CMake command ``add_subdirectory`` will import a function with the signature
``pybind11_add_module(<name> source1 [source2 ...])``. It will take care of all
the details needed to build a Python extension module on any platform.
The target Python version can be selected by setting the ``PYBIND11_PYTHON_VERSION``
variable before adding the pybind11 subdirectory. Alternatively, an exact Python
installation can be specified by setting ``PYTHON_EXECUTABLE``.
A working sample project, including a way to invoke CMake from :file:`setup.py` for
PyPI integration, can be found in the [cmake_example]_ repository.
.. [cmake_example] https://github.com/pybind/cmake_example

308
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@ -0,0 +1,308 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# pybind11 documentation build configuration file, created by
# sphinx-quickstart on Sun Oct 11 19:23:48 2015.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# All configuration values have a default; values that are commented out
# serve to show the default.
import sys
import os
import shlex
# If extensions (or modules to document with autodoc) are in another directory,
# add these directories to sys.path here. If the directory is relative to the
# documentation root, use os.path.abspath to make it absolute, like shown here.
#sys.path.insert(0, os.path.abspath('.'))
# -- General configuration ------------------------------------------------
# If your documentation needs a minimal Sphinx version, state it here.
#needs_sphinx = '1.0'
# Add any Sphinx extension module names here, as strings. They can be
# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
# ones.
extensions = []
# Add any paths that contain templates here, relative to this directory.
templates_path = ['.templates']
# The suffix(es) of source filenames.
# You can specify multiple suffix as a list of string:
# source_suffix = ['.rst', '.md']
source_suffix = '.rst'
# The encoding of source files.
#source_encoding = 'utf-8-sig'
# The master toctree document.
master_doc = 'index'
# General information about the project.
project = 'pybind11'
copyright = '2015, Wenzel Jakob'
author = 'Wenzel Jakob'
# The version info for the project you're documenting, acts as replacement for
# |version| and |release|, also used in various other places throughout the
# built documents.
#
# The short X.Y version.
version = '1.9'
# The full version, including alpha/beta/rc tags.
release = '1.9.dev0'
# The language for content autogenerated by Sphinx. Refer to documentation
# for a list of supported languages.
#
# This is also used if you do content translation via gettext catalogs.
# Usually you set "language" from the command line for these cases.
language = None
# There are two options for replacing |today|: either, you set today to some
# non-false value, then it is used:
#today = ''
# Else, today_fmt is used as the format for a strftime call.
#today_fmt = '%B %d, %Y'
# List of patterns, relative to source directory, that match files and
# directories to ignore when looking for source files.
exclude_patterns = ['.build', 'release.rst']
# The reST default role (used for this markup: `text`) to use for all
# documents.
#default_role = None
# If true, '()' will be appended to :func: etc. cross-reference text.
#add_function_parentheses = True
# If true, the current module name will be prepended to all description
# unit titles (such as .. function::).
#add_module_names = True
# If true, sectionauthor and moduleauthor directives will be shown in the
# output. They are ignored by default.
#show_authors = False
# The name of the Pygments (syntax highlighting) style to use.
#pygments_style = 'monokai'
# A list of ignored prefixes for module index sorting.
#modindex_common_prefix = []
# If true, keep warnings as "system message" paragraphs in the built documents.
#keep_warnings = False
# If true, `todo` and `todoList` produce output, else they produce nothing.
todo_include_todos = False
# -- Options for HTML output ----------------------------------------------
# The theme to use for HTML and HTML Help pages. See the documentation for
# a list of builtin themes.
on_rtd = os.environ.get('READTHEDOCS', None) == 'True'
if not on_rtd: # only import and set the theme if we're building docs locally
import sphinx_rtd_theme
html_theme = 'sphinx_rtd_theme'
html_theme_path = [sphinx_rtd_theme.get_html_theme_path()]
html_context = {
'css_files': [
'_static/theme_overrides.css'
]
}
else:
html_context = {
'css_files': [
'//media.readthedocs.org/css/sphinx_rtd_theme.css',
'//media.readthedocs.org/css/readthedocs-doc-embed.css',
'_static/theme_overrides.css'
]
}
# Theme options are theme-specific and customize the look and feel of a theme
# further. For a list of options available for each theme, see the
# documentation.
#html_theme_options = {}
# Add any paths that contain custom themes here, relative to this directory.
#html_theme_path = []
# The name for this set of Sphinx documents. If None, it defaults to
# "<project> v<release> documentation".
#html_title = None
# A shorter title for the navigation bar. Default is the same as html_title.
#html_short_title = None
# The name of an image file (relative to this directory) to place at the top
# of the sidebar.
#html_logo = None
# The name of an image file (within the static path) to use as favicon of the
# docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32
# pixels large.
#html_favicon = None
# Add any paths that contain custom static files (such as style sheets) here,
# relative to this directory. They are copied after the builtin static files,
# so a file named "default.css" will overwrite the builtin "default.css".
html_static_path = ['_static']
# Add any extra paths that contain custom files (such as robots.txt or
# .htaccess) here, relative to this directory. These files are copied
# directly to the root of the documentation.
#html_extra_path = []
# If not '', a 'Last updated on:' timestamp is inserted at every page bottom,
# using the given strftime format.
#html_last_updated_fmt = '%b %d, %Y'
# If true, SmartyPants will be used to convert quotes and dashes to
# typographically correct entities.
#html_use_smartypants = True
# Custom sidebar templates, maps document names to template names.
#html_sidebars = {}
# Additional templates that should be rendered to pages, maps page names to
# template names.
#html_additional_pages = {}
# If false, no module index is generated.
#html_domain_indices = True
# If false, no index is generated.
#html_use_index = True
# If true, the index is split into individual pages for each letter.
#html_split_index = False
# If true, links to the reST sources are added to the pages.
#html_show_sourcelink = True
# If true, "Created using Sphinx" is shown in the HTML footer. Default is True.
#html_show_sphinx = True
# If true, "(C) Copyright ..." is shown in the HTML footer. Default is True.
#html_show_copyright = True
# If true, an OpenSearch description file will be output, and all pages will
# contain a <link> tag referring to it. The value of this option must be the
# base URL from which the finished HTML is served.
#html_use_opensearch = ''
# This is the file name suffix for HTML files (e.g. ".xhtml").
#html_file_suffix = None
# Language to be used for generating the HTML full-text search index.
# Sphinx supports the following languages:
# 'da', 'de', 'en', 'es', 'fi', 'fr', 'h', 'it', 'ja'
# 'nl', 'no', 'pt', 'ro', 'r', 'sv', 'tr'
#html_search_language = 'en'
# A dictionary with options for the search language support, empty by default.
# Now only 'ja' uses this config value
#html_search_options = {'type': 'default'}
# The name of a javascript file (relative to the configuration directory) that
# implements a search results scorer. If empty, the default will be used.
#html_search_scorer = 'scorer.js'
# Output file base name for HTML help builder.
htmlhelp_basename = 'pybind11doc'
# -- Options for LaTeX output ---------------------------------------------
latex_elements = {
# The paper size ('letterpaper' or 'a4paper').
#'papersize': 'letterpaper',
# The font size ('10pt', '11pt' or '12pt').
#'pointsize': '10pt',
# Additional stuff for the LaTeX preamble.
'preamble': '\DeclareUnicodeCharacter{00A0}{}',
# Latex figure (float) alignment
#'figure_align': 'htbp',
}
# Grouping the document tree into LaTeX files. List of tuples
# (source start file, target name, title,
# author, documentclass [howto, manual, or own class]).
latex_documents = [
(master_doc, 'pybind11.tex', 'pybind11 Documentation',
'Wenzel Jakob', 'manual'),
]
# The name of an image file (relative to this directory) to place at the top of
# the title page.
# latex_logo = 'pybind11-logo.png'
# For "manual" documents, if this is true, then toplevel headings are parts,
# not chapters.
#latex_use_parts = False
# If true, show page references after internal links.
#latex_show_pagerefs = False
# If true, show URL addresses after external links.
#latex_show_urls = False
# Documents to append as an appendix to all manuals.
#latex_appendices = []
# If false, no module index is generated.
#latex_domain_indices = True
# -- Options for manual page output ---------------------------------------
# One entry per manual page. List of tuples
# (source start file, name, description, authors, manual section).
man_pages = [
(master_doc, 'pybind11', 'pybind11 Documentation',
[author], 1)
]
# If true, show URL addresses after external links.
#man_show_urls = False
# -- Options for Texinfo output -------------------------------------------
# Grouping the document tree into Texinfo files. List of tuples
# (source start file, target name, title, author,
# dir menu entry, description, category)
texinfo_documents = [
(master_doc, 'pybind11', 'pybind11 Documentation',
author, 'pybind11', 'One line description of project.',
'Miscellaneous'),
]
# Documents to append as an appendix to all manuals.
#texinfo_appendices = []
# If false, no module index is generated.
#texinfo_domain_indices = True
# How to display URL addresses: 'footnote', 'no', or 'inline'.
#texinfo_show_urls = 'footnote'
# If true, do not generate a @detailmenu in the "Top" node's menu.
#texinfo_no_detailmenu = False
primary_domain = 'cpp'
highlight_language = 'cpp'

251
resources/pybind11/docs/faq.rst

@ -0,0 +1,251 @@
Frequently asked questions
##########################
"ImportError: dynamic module does not define init function"
===========================================================
1. Make sure that the name specified in ``pybind::module`` and
``PYBIND11_PLUGIN`` is consistent and identical to the filename of the
extension library. The latter should not contain any extra prefixes (e.g.
``test.so`` instead of ``libtest.so``).
2. If the above did not fix your issue, then you are likely using an
incompatible version of Python (for instance, the extension library was
compiled against Python 2, while the interpreter is running on top of some
version of Python 3, or vice versa)
"Symbol not found: ``__Py_ZeroStruct`` / ``_PyInstanceMethod_Type``"
========================================================================
See item 2 of the first answer.
"SystemError: dynamic module not initialized properly"
======================================================
See item 2 of the first answer.
The Python interpreter immediately crashes when importing my module
===================================================================
See item 2 of the first answer.
CMake doesn't detect the right Python version
=============================================
The CMake-based build system will try to automatically detect the installed
version of Python and link against that. When this fails, or when there are
multiple versions of Python and it finds the wrong one, delete
``CMakeCache.txt`` and then invoke CMake as follows:
.. code-block:: bash
cmake -DPYTHON_EXECUTABLE:FILEPATH=<path-to-python-executable> .
Limitations involving reference arguments
=========================================
In C++, it's fairly common to pass arguments using mutable references or
mutable pointers, which allows both read and write access to the value
supplied by the caller. This is sometimes done for efficiency reasons, or to
realize functions that have multiple return values. Here are two very basic
examples:
.. code-block:: cpp
void increment(int &i) { i++; }
void increment_ptr(int *i) { (*i)++; }
In Python, all arguments are passed by reference, so there is no general
issue in binding such code from Python.
However, certain basic Python types (like ``str``, ``int``, ``bool``,
``float``, etc.) are **immutable**. This means that the following attempt
to port the function to Python doesn't have the same effect on the value
provided by the caller -- in fact, it does nothing at all.
.. code-block:: python
def increment(i):
i += 1 # nope..
pybind11 is also affected by such language-level conventions, which means that
binding ``increment`` or ``increment_ptr`` will also create Python functions
that don't modify their arguments.
Although inconvenient, one workaround is to encapsulate the immutable types in
a custom type that does allow modifications.
An other alternative involves binding a small wrapper lambda function that
returns a tuple with all output arguments (see the remainder of the
documentation for examples on binding lambda functions). An example:
.. code-block:: cpp
int foo(int &i) { i++; return 123; }
and the binding code
.. code-block:: cpp
m.def("foo", [](int i) { int rv = foo(i); return std::make_tuple(rv, i); });
How can I reduce the build time?
================================
It's good practice to split binding code over multiple files, as in the
following example:
:file:`example.cpp`:
.. code-block:: cpp
void init_ex1(py::module &);
void init_ex2(py::module &);
/* ... */
PYBIND11_PLUGIN(example) {
py::module m("example", "pybind example plugin");
init_ex1(m);
init_ex2(m);
/* ... */
return m.ptr();
}
:file:`ex1.cpp`:
.. code-block:: cpp
void init_ex1(py::module &m) {
m.def("add", [](int a, int b) { return a + b; });
}
:file:`ex2.cpp`:
.. code-block:: cpp
void init_ex1(py::module &m) {
m.def("sub", [](int a, int b) { return a - b; });
}
:command:`python`:
.. code-block:: pycon
>>> import example
>>> example.add(1, 2)
3
>>> example.sub(1, 1)
0
As shown above, the various ``init_ex`` functions should be contained in
separate files that can be compiled independently from one another, and then
linked together into the same final shared object. Following this approach
will:
1. reduce memory requirements per compilation unit.
2. enable parallel builds (if desired).
3. allow for faster incremental builds. For instance, when a single class
definition is changed, only a subset of the binding code will generally need
to be recompiled.
"recursive template instantiation exceeded maximum depth of 256"
================================================================
If you receive an error about excessive recursive template evaluation, try
specifying a larger value, e.g. ``-ftemplate-depth=1024`` on GCC/Clang. The
culprit is generally the generation of function signatures at compile time
using C++14 template metaprogramming.
How can I create smaller binaries?
==================================
To do its job, pybind11 extensively relies on a programming technique known as
*template metaprogramming*, which is a way of performing computation at compile
time using type information. Template metaprogamming usually instantiates code
involving significant numbers of deeply nested types that are either completely
removed or reduced to just a few instructions during the compiler's optimization
phase. However, due to the nested nature of these types, the resulting symbol
names in the compiled extension library can be extremely long. For instance,
the included test suite contains the following symbol:
.. only:: html
.. code-block:: none
_​_​Z​N​8​p​y​b​i​n​d​1​1​1​2​c​p​p​_​f​u​n​c​t​i​o​n​C​1​I​v​8​E​x​a​m​p​l​e​2​J​R​N​S​t​3​_​_​1​6​v​e​c​t​o​r​I​N​S​3​_​1​2​b​a​s​i​c​_​s​t​r​i​n​g​I​w​N​S​3​_​1​1​c​h​a​r​_​t​r​a​i​t​s​I​w​E​E​N​S​3​_​9​a​l​l​o​c​a​t​o​r​I​w​E​E​E​E​N​S​8​_​I​S​A​_​E​E​E​E​E​J​N​S​_​4​n​a​m​e​E​N​S​_​7​s​i​b​l​i​n​g​E​N​S​_​9​i​s​_​m​e​t​h​o​d​E​A​2​8​_​c​E​E​E​M​T​0​_​F​T​_​D​p​T​1​_​E​D​p​R​K​T​2​_
.. only:: not html
.. code-block:: cpp
__ZN8pybind1112cpp_functionC1Iv8Example2JRNSt3__16vectorINS3_12basic_stringIwNS3_11char_traitsIwEENS3_9allocatorIwEEEENS8_ISA_EEEEEJNS_4nameENS_7siblingENS_9is_methodEA28_cEEEMT0_FT_DpT1_EDpRKT2_
which is the mangled form of the following function type:
.. code-block:: cpp
pybind11::cpp_function::cpp_function<void, Example2, std::__1::vector<std::__1::basic_string<wchar_t, std::__1::char_traits<wchar_t>, std::__1::allocator<wchar_t> >, std::__1::allocator<std::__1::basic_string<wchar_t, std::__1::char_traits<wchar_t>, std::__1::allocator<wchar_t> > > >&, pybind11::name, pybind11::sibling, pybind11::is_method, char [28]>(void (Example2::*)(std::__1::vector<std::__1::basic_string<wchar_t, std::__1::char_traits<wchar_t>, std::__1::allocator<wchar_t> >, std::__1::allocator<std::__1::basic_string<wchar_t, std::__1::char_traits<wchar_t>, std::__1::allocator<wchar_t> > > >&), pybind11::name const&, pybind11::sibling const&, pybind11::is_method const&, char const (&) [28])
The memory needed to store just the mangled name of this function (196 bytes)
is larger than the actual piece of code (111 bytes) it represents! On the other
hand, it's silly to even give this function a name -- after all, it's just a
tiny cog in a bigger piece of machinery that is not exposed to the outside
world. So we'll generally only want to export symbols for those functions which
are actually called from the outside.
This can be achieved by specifying the parameter ``-fvisibility=hidden`` to GCC
and Clang, which sets the default symbol visibility to *hidden*. It's best to
do this only for release builds, since the symbol names can be helpful in
debugging sessions. On Visual Studio, symbols are already hidden by default, so
nothing needs to be done there. Needless to say, this has a tremendous impact
on the final binary size of the resulting extension library.
Another aspect that can require a fair bit of code are function signature
descriptions. pybind11 automatically generates human-readable function
signatures for docstrings, e.g.:
.. code-block:: none
| __init__(...)
| __init__(*args, **kwargs)
| Overloaded function.
|
| 1. __init__(example.Example1) -> NoneType
|
| Docstring for overload #1 goes here
|
| 2. __init__(example.Example1, int) -> NoneType
|
| Docstring for overload #2 goes here
|
| 3. __init__(example.Example1, example.Example1) -> NoneType
|
| Docstring for overload #3 goes here
In C++11 mode, these are generated at run time using string concatenation,
which can amount to 10-20% of the size of the resulting binary. If you can,
enable C++14 language features (using ``-std=c++14`` for GCC/Clang), in which
case signatures are efficiently pre-generated at compile time. Unfortunately,
Visual Studio's C++14 support (``constexpr``) is not good enough as of April
2016, so it always uses the more expensive run-time approach.
Working with ancient Visual Studio 2009 builds on Windows
=========================================================
The official Windows distributions of Python are compiled using truly
ancient versions of Visual Studio that lack good C++11 support. Some users
implicitly assume that it would be impossible to load a plugin built with
Visual Studio 2015 into a Python distribution that was compiled using Visual
Studio 2009. However, no such issue exists: it's perfectly legitimate to
interface DLLs that are built with different compilers and/or C libraries.
Common gotchas to watch out for involve not ``free()``-ing memory region
that that were ``malloc()``-ed in another shared library, using data
structures with incompatible ABIs, and so on. pybind11 is very careful not
to make these types of mistakes.

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.. only: not latex
.. image:: pybind11-logo.png
pybind11 --- Seamless operability between C++11 and Python
==========================================================
.. only: not latex
Contents:
.. toctree::
:maxdepth: 1
intro
changelog
.. toctree::
:caption: The Basics
:maxdepth: 2
basics
classes
compiling
.. toctree::
:caption: Advanced Topics
:maxdepth: 2
advanced/functions
advanced/classes
advanced/exceptions
advanced/smart_ptrs
advanced/cast/index
advanced/pycpp/index
advanced/misc
.. toctree::
:caption: Extra Information
:maxdepth: 1
faq
benchmark
limitations
reference

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.. image:: pybind11-logo.png
About this project
==================
**pybind11** is a lightweight header-only library that exposes C++ types in Python
and vice versa, mainly to create Python bindings of existing C++ code. Its
goals and syntax are similar to the excellent `Boost.Python`_ library by David
Abrahams: to minimize boilerplate code in traditional extension modules by
inferring type information using compile-time introspection.
.. _Boost.Python: http://www.boost.org/doc/libs/release/libs/python/doc/index.html
The main issue with Boost.Python—and the reason for creating such a similar
project—is Boost. Boost is an enormously large and complex suite of utility
libraries that works with almost every C++ compiler in existence. This
compatibility has its cost: arcane template tricks and workarounds are
necessary to support the oldest and buggiest of compiler specimens. Now that
C++11-compatible compilers are widely available, this heavy machinery has
become an excessively large and unnecessary dependency.
Think of this library as a tiny self-contained version of Boost.Python with
everything stripped away that isn't relevant for binding generation. Without
comments, the core header files only require ~2.5K lines of code and depend on
Python (2.7 or 3.x) and the C++ standard library. This compact implementation
was possible thanks to some of the new C++11 language features (specifically:
tuples, lambda functions and variadic templates). Since its creation, this
library has grown beyond Boost.Python in many ways, leading to dramatically
simpler binding code in many common situations.
Core features
*************
The following core C++ features can be mapped to Python
- Functions accepting and returning custom data structures per value, reference, or pointer
- Instance methods and static methods
- Overloaded functions
- Instance attributes and static attributes
- Arbitrary exception types
- Enumerations
- Callbacks
- Iterators and ranges
- Custom operators
- Single and multiple inheritance
- STL data structures
- Iterators and ranges
- Smart pointers with reference counting like ``std::shared_ptr``
- Internal references with correct reference counting
- C++ classes with virtual (and pure virtual) methods can be extended in Python
Goodies
*******
In addition to the core functionality, pybind11 provides some extra goodies:
- It is possible to bind C++11 lambda functions with captured variables. The
lambda capture data is stored inside the resulting Python function object.
- pybind11 uses C++11 move constructors and move assignment operators whenever
possible to efficiently transfer custom data types.
- It's easy to expose the internal storage of custom data types through
Pythons' buffer protocols. This is handy e.g. for fast conversion between
C++ matrix classes like Eigen and NumPy without expensive copy operations.
- pybind11 can automatically vectorize functions so that they are transparently
applied to all entries of one or more NumPy array arguments.
- Python's slice-based access and assignment operations can be supported with
just a few lines of code.
- Everything is contained in just a few header files; there is no need to link
against any additional libraries.
- Binaries are generally smaller by a factor of at least 2 compared to
equivalent bindings generated by Boost.Python. A recent pybind11 conversion
of `PyRosetta`_, an enormous Boost.Python binding project, reported a binary
size reduction of **5.4x** and compile time reduction by **5.8x**.
- When supported by the compiler, two new C++14 features (relaxed constexpr and
return value deduction) are used to precompute function signatures at compile
time, leading to smaller binaries.
- With little extra effort, C++ types can be pickled and unpickled similar to
regular Python objects.
.. _PyRosetta: http://graylab.jhu.edu/RosettaCon2016/PyRosetta-4.pdf
Supported compilers
*******************
1. Clang/LLVM (any non-ancient version with C++11 support)
2. GCC (any non-ancient version with C++11 support)
3. Microsoft Visual Studio 2015 or newer
4. Intel C++ compiler v15 or newer

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Limitations
###########
pybind11 strives to be a general solution to binding generation, but it also has
certain limitations:
- pybind11 casts away ``const``-ness in function arguments and return values.
This is in line with the Python language, which has no concept of ``const``
values. This means that some additional care is needed to avoid bugs that
would be caught by the type checker in a traditional C++ program.
- The NumPy interface ``pybind11::array`` greatly simplifies accessing
numerical data from C++ (and vice versa), but it's not a full-blown array
class like ``Eigen::Array`` or ``boost.multi_array``.
These features could be implemented but would lead to a significant increase in
complexity. I've decided to draw the line here to keep this project simple and
compact. Users who absolutely require these features are encouraged to fork
pybind11.

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.. _reference:
.. warning::
Please be advised that the reference documentation discussing pybind11
internals is currently incomplete. Please refer to the previous sections
and the pybind11 header files for the nitty gritty details.
Reference
#########
Macros
======
.. function:: PYBIND11_PLUGIN(const char *name)
This macro creates the entry point that will be invoked when the Python
interpreter imports a plugin library. Please create a
:class:`module` in the function body and return the pointer to its
underlying Python object at the end.
.. code-block:: cpp
PYBIND11_PLUGIN(example) {
pybind11::module m("example", "pybind11 example plugin");
/// Set up bindings here
return m.ptr();
}
.. _core_types:
Convenience classes for arbitrary Python types
==============================================
Without reference counting
--------------------------
.. class:: handle
The :class:`handle` class is a thin wrapper around an arbitrary Python
object (i.e. a ``PyObject *`` in Python's C API). It does not perform any
automatic reference counting and merely provides a basic C++ interface to
various Python API functions.
.. seealso::
The :class:`object` class inherits from :class:`handle` and adds automatic
reference counting features.
.. function:: handle::handle()
The default constructor creates a handle with a ``nullptr``-valued pointer.
.. function:: handle::handle(const handle&)
Copy constructor
.. function:: handle::handle(PyObject *)
Creates a :class:`handle` from the given raw Python object pointer.
.. function:: PyObject * handle::ptr() const
Return the ``PyObject *`` underlying a :class:`handle`.
.. function:: const handle& handle::inc_ref() const
Manually increase the reference count of the Python object. Usually, it is
preferable to use the :class:`object` class which derives from
:class:`handle` and calls this function automatically. Returns a reference
to itself.
.. function:: const handle& handle::dec_ref() const
Manually decrease the reference count of the Python object. Usually, it is
preferable to use the :class:`object` class which derives from
:class:`handle` and calls this function automatically. Returns a reference
to itself.
.. function:: void handle::ref_count() const
Return the object's current reference count
.. function:: handle handle::get_type() const
Return a handle to the Python type object underlying the instance
.. function detail::accessor handle::operator[](handle key) const
Return an internal functor to invoke the object's sequence protocol.
Casting the returned ``detail::accessor`` instance to a :class:`handle` or
:class:`object` subclass causes a corresponding call to ``__getitem__``.
Assigning a :class:`handle` or :class:`object` subclass causes a call to
``__setitem__``.
.. function detail::accessor handle::operator[](const char *key) const
See the above function (the only difference is that they key is provided as
a string literal).
.. function detail::accessor handle::attr(handle key) const
Return an internal functor to access the object's attributes.
Casting the returned ``detail::accessor`` instance to a :class:`handle` or
:class:`object` subclass causes a corresponding call to ``__getattr``.
Assigning a :class:`handle` or :class:`object` subclass causes a call to
``__setattr``.
.. function detail::accessor handle::attr(const char *key) const
See the above function (the only difference is that they key is provided as
a string literal).
.. function operator handle::bool() const
Return ``true`` when the :class:`handle` wraps a valid Python object.
.. function str handle::str() const
Return a string representation of the object. This is analogous to
the ``str()`` function in Python.
.. function:: template <typename T> T handle::cast() const
Attempt to cast the Python object into the given C++ type. A
:class:`cast_error` will be throw upon failure.
.. function:: template <typename ... Args> object handle::call(Args&&... args) const
Assuming the Python object is a function or implements the ``__call__``
protocol, ``call()`` invokes the underlying function, passing an arbitrary
set of parameters. The result is returned as a :class:`object` and may need
to be converted back into a Python object using :func:`handle::cast`.
When some of the arguments cannot be converted to Python objects, the
function will throw a :class:`cast_error` exception. When the Python
function call fails, a :class:`error_already_set` exception is thrown.
With reference counting
-----------------------
.. class:: object : public handle
Like :class:`handle`, the object class is a thin wrapper around an
arbitrary Python object (i.e. a ``PyObject *`` in Python's C API). In
contrast to :class:`handle`, it optionally increases the object's reference
count upon construction, and it *always* decreases the reference count when
the :class:`object` instance goes out of scope and is destructed. When
using :class:`object` instances consistently, it is much easier to get
reference counting right at the first attempt.
.. function:: object::object(const object &o)
Copy constructor; always increases the reference count
.. function:: object::object(const handle &h, bool borrowed)
Creates a :class:`object` from the given :class:`handle`. The reference
count is only increased if the ``borrowed`` parameter is set to ``true``.
.. function:: object::object(PyObject *ptr, bool borrowed)
Creates a :class:`object` from the given raw Python object pointer. The
reference count is only increased if the ``borrowed`` parameter is set to
``true``.
.. function:: object::object(object &&other)
Move constructor; steals the object from ``other`` and preserves its
reference count.
.. function:: handle object::release()
Resets the internal pointer to ``nullptr`` without without decreasing the
object's reference count. The function returns a raw handle to the original
Python object.
.. function:: object::~object()
Destructor, which automatically calls :func:`handle::dec_ref()`.
Convenience classes for specific Python types
=============================================
.. class:: module : public object
.. function:: module::module(const char *name, const char *doc = nullptr)
Create a new top-level Python module with the given name and docstring
.. function:: module module::def_submodule(const char *name, const char *doc = nullptr)
Create and return a new Python submodule with the given name and docstring.
This also works recursively, i.e.
.. code-block:: cpp
pybind11::module m("example", "pybind11 example plugin");
pybind11::module m2 = m.def_submodule("sub", "A submodule of 'example'");
pybind11::module m3 = m2.def_submodule("subsub", "A submodule of 'example.sub'");
.. cpp:function:: template <typename Func, typename ... Extra> module& module::def(const char *name, Func && f, Extra && ... extra)
Create Python binding for a new function within the module scope. ``Func``
can be a plain C++ function, a function pointer, or a lambda function. For
details on the ``Extra&& ... extra`` argument, see section :ref:`extras`.
.. _extras:
Passing extra arguments to the def function
===========================================
.. class:: arg
.. function:: arg::arg(const char *name)
.. function:: template <typename T> arg_v arg::operator=(T &&value)
.. class:: arg_v : public arg
Represents a named argument with a default value
.. class:: sibling
Used to specify a handle to an existing sibling function; used internally
to implement function overloading in :func:`module::def` and
:func:`class_::def`.
.. function:: sibling::sibling(handle handle)
.. class doc
This is class is internally used by pybind11.
.. function:: doc::doc(const char *value)
Create a new docstring with the specified value
.. class name
This is class is internally used by pybind11.
.. function:: name::name(const char *value)
Used to specify the function name

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To release a new version of pybind11:
- Update the version number and push to pypi
- Update ``pybind11/_version.py`` (set release version, remove 'dev')
- Update version in ``docs/conf.py``
- Tag release date in ``docs/changelog.rst``.
- ``git add`` and ``git commit``.
- if new minor version: ``git checkout -b vX.Y``, ``git push -u origin vX.Y``
- ``git tag -a vX.Y.Z -m 'vX.Y.Z release'``.
- ``git push``
- ``git push --tags``.
- ``python setup.py sdist upload``.
- ``python setup.py bdist_wheel upload``.
- Update conda-forge (https://github.com/conda-forge/pybind11-feedstock) via PR
- change version number in ``recipe/meta.yml``
- update checksum to match the one computed by pypi
- Get back to work
- Update ``_version.py`` (add 'dev' and increment minor).
- Update version in ``docs/conf.py``
- Update version macros in ``include/pybind11/common.h``
- ``git add`` and ``git commit``.
``git push``

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resources/pybind11/include/pybind11/attr.h

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/*
pybind11/pybind11.h: Infrastructure for processing custom
type and function attributes
Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#pragma once
#include "cast.h"
NAMESPACE_BEGIN(pybind11)
/// Annotation for methods
struct is_method { handle class_; is_method(const handle &c) : class_(c) { } };
/// Annotation for operators
struct is_operator { };
/// Annotation for parent scope
struct scope { handle value; scope(const handle &s) : value(s) { } };
/// Annotation for documentation
struct doc { const char *value; doc(const char *value) : value(value) { } };
/// Annotation for function names
struct name { const char *value; name(const char *value) : value(value) { } };
/// Annotation indicating that a function is an overload associated with a given "sibling"
struct sibling { handle value; sibling(const handle &value) : value(value.ptr()) { } };
/// Annotation indicating that a class derives from another given type
template <typename T> struct base {
PYBIND11_DEPRECATED("base<T>() was deprecated in favor of specifying 'T' as a template argument to class_")
base() { }
};
/// Keep patient alive while nurse lives
template <int Nurse, int Patient> struct keep_alive { };
/// Annotation indicating that a class is involved in a multiple inheritance relationship
struct multiple_inheritance { };
/// Annotation which enables dynamic attributes, i.e. adds `__dict__` to a class
struct dynamic_attr { };
/// Annotation to mark enums as an arithmetic type
struct arithmetic { };
NAMESPACE_BEGIN(detail)
/* Forward declarations */
enum op_id : int;
enum op_type : int;
struct undefined_t;
template <op_id id, op_type ot, typename L = undefined_t, typename R = undefined_t> struct op_;
template <typename... Args> struct init;
template <typename... Args> struct init_alias;
inline void keep_alive_impl(int Nurse, int Patient, handle args, handle ret);
/// Internal data structure which holds metadata about a keyword argument
struct argument_record {
const char *name; ///< Argument name
const char *descr; ///< Human-readable version of the argument value
handle value; ///< Associated Python object
argument_record(const char *name, const char *descr, handle value)
: name(name), descr(descr), value(value) { }
};
/// Internal data structure which holds metadata about a bound function (signature, overloads, etc.)
struct function_record {
function_record()
: is_constructor(false), is_stateless(false), is_operator(false),
has_args(false), has_kwargs(false), is_method(false) { }
/// Function name
char *name = nullptr; /* why no C++ strings? They generate heavier code.. */
// User-specified documentation string
char *doc = nullptr;
/// Human-readable version of the function signature
char *signature = nullptr;
/// List of registered keyword arguments
std::vector<argument_record> args;
/// Pointer to lambda function which converts arguments and performs the actual call
handle (*impl) (function_record *, handle, handle, handle) = nullptr;
/// Storage for the wrapped function pointer and captured data, if any
void *data[3] = { };
/// Pointer to custom destructor for 'data' (if needed)
void (*free_data) (function_record *ptr) = nullptr;
/// Return value policy associated with this function
return_value_policy policy = return_value_policy::automatic;
/// True if name == '__init__'
bool is_constructor : 1;
/// True if this is a stateless function pointer
bool is_stateless : 1;
/// True if this is an operator (__add__), etc.
bool is_operator : 1;
/// True if the function has a '*args' argument
bool has_args : 1;
/// True if the function has a '**kwargs' argument
bool has_kwargs : 1;
/// True if this is a method
bool is_method : 1;
/// Number of arguments
uint16_t nargs;
/// Python method object
PyMethodDef *def = nullptr;
/// Python handle to the parent scope (a class or a module)
handle scope;
/// Python handle to the sibling function representing an overload chain
handle sibling;
/// Pointer to next overload
function_record *next = nullptr;
};
/// Special data structure which (temporarily) holds metadata about a bound class
struct type_record {
PYBIND11_NOINLINE type_record() { }
/// Handle to the parent scope
handle scope;
/// Name of the class
const char *name = nullptr;
// Pointer to RTTI type_info data structure
const std::type_info *type = nullptr;
/// How large is the underlying C++ type?
size_t type_size = 0;
/// How large is pybind11::instance<type>?
size_t instance_size = 0;
/// Function pointer to class_<..>::init_holder
void (*init_holder)(PyObject *, const void *) = nullptr;
/// Function pointer to class_<..>::dealloc
void (*dealloc)(PyObject *) = nullptr;
/// List of base classes of the newly created type
list bases;
/// Optional docstring
const char *doc = nullptr;
/// Multiple inheritance marker
bool multiple_inheritance = false;
/// Does the class manage a __dict__?
bool dynamic_attr = false;
PYBIND11_NOINLINE void add_base(const std::type_info *base, void *(*caster)(void *)) {
auto base_info = detail::get_type_info(*base, false);
if (!base_info) {
std::string tname(base->name());
detail::clean_type_id(tname);
pybind11_fail("generic_type: type \"" + std::string(name) +
"\" referenced unknown base type \"" + tname + "\"");
}
bases.append((PyObject *) base_info->type);
if (base_info->type->tp_dictoffset != 0)
dynamic_attr = true;
if (caster)
base_info->implicit_casts.push_back(std::make_pair(type, caster));
}
};
/**
* Partial template specializations to process custom attributes provided to
* cpp_function_ and class_. These are either used to initialize the respective
* fields in the type_record and function_record data structures or executed at
* runtime to deal with custom call policies (e.g. keep_alive).
*/
template <typename T, typename SFINAE = void> struct process_attribute;
template <typename T> struct process_attribute_default {
/// Default implementation: do nothing
static void init(const T &, function_record *) { }
static void init(const T &, type_record *) { }
static void precall(handle) { }
static void postcall(handle, handle) { }
};
/// Process an attribute specifying the function's name
template <> struct process_attribute<name> : process_attribute_default<name> {
static void init(const name &n, function_record *r) { r->name = const_cast<char *>(n.value); }
};
/// Process an attribute specifying the function's docstring
template <> struct process_attribute<doc> : process_attribute_default<doc> {
static void init(const doc &n, function_record *r) { r->doc = const_cast<char *>(n.value); }
};
/// Process an attribute specifying the function's docstring (provided as a C-style string)
template <> struct process_attribute<const char *> : process_attribute_default<const char *> {
static void init(const char *d, function_record *r) { r->doc = const_cast<char *>(d); }
static void init(const char *d, type_record *r) { r->doc = const_cast<char *>(d); }
};
template <> struct process_attribute<char *> : process_attribute<const char *> { };
/// Process an attribute indicating the function's return value policy
template <> struct process_attribute<return_value_policy> : process_attribute_default<return_value_policy> {
static void init(const return_value_policy &p, function_record *r) { r->policy = p; }
};
/// Process an attribute which indicates that this is an overloaded function associated with a given sibling
template <> struct process_attribute<sibling> : process_attribute_default<sibling> {
static void init(const sibling &s, function_record *r) { r->sibling = s.value; }
};
/// Process an attribute which indicates that this function is a method
template <> struct process_attribute<is_method> : process_attribute_default<is_method> {
static void init(const is_method &s, function_record *r) { r->is_method = true; r->scope = s.class_; }
};
/// Process an attribute which indicates the parent scope of a method
template <> struct process_attribute<scope> : process_attribute_default<scope> {
static void init(const scope &s, function_record *r) { r->scope = s.value; }
};
/// Process an attribute which indicates that this function is an operator
template <> struct process_attribute<is_operator> : process_attribute_default<is_operator> {
static void init(const is_operator &, function_record *r) { r->is_operator = true; }
};
/// Process a keyword argument attribute (*without* a default value)
template <> struct process_attribute<arg> : process_attribute_default<arg> {
static void init(const arg &a, function_record *r) {
if (r->is_method && r->args.empty())
r->args.emplace_back("self", nullptr, handle());
r->args.emplace_back(a.name, nullptr, handle());
}
};
/// Process a keyword argument attribute (*with* a default value)
template <> struct process_attribute<arg_v> : process_attribute_default<arg_v> {
static void init(const arg_v &a, function_record *r) {
if (r->is_method && r->args.empty())
r->args.emplace_back("self", nullptr, handle());
if (!a.value) {
#if !defined(NDEBUG)
auto descr = "'" + std::string(a.name) + ": " + a.type + "'";
if (r->is_method) {
if (r->name)
descr += " in method '" + (std::string) str(r->scope) + "." + (std::string) r->name + "'";
else
descr += " in method of '" + (std::string) str(r->scope) + "'";
} else if (r->name) {
descr += " in function named '" + (std::string) r->name + "'";
}
pybind11_fail("arg(): could not convert default keyword argument "
+ descr + " into a Python object (type not registered yet?)");
#else
pybind11_fail("arg(): could not convert default keyword argument "
"into a Python object (type not registered yet?). "
"Compile in debug mode for more information.");
#endif
}
r->args.emplace_back(a.name, a.descr, a.value.inc_ref());
}
};
/// Process a parent class attribute
template <typename T>
struct process_attribute<T, enable_if_t<is_pyobject<T>::value>> : process_attribute_default<handle> {
static void init(const handle &h, type_record *r) { r->bases.append(h); }
};
/// Process a parent class attribute (deprecated, does not support multiple inheritance)
template <typename T>
struct process_attribute<base<T>> : process_attribute_default<base<T>> {
static void init(const base<T> &, type_record *r) { r->add_base(&typeid(T), nullptr); }
};
/// Process a multiple inheritance attribute
template <>
struct process_attribute<multiple_inheritance> : process_attribute_default<multiple_inheritance> {
static void init(const multiple_inheritance &, type_record *r) { r->multiple_inheritance = true; }
};
template <>
struct process_attribute<dynamic_attr> : process_attribute_default<dynamic_attr> {
static void init(const dynamic_attr &, type_record *r) { r->dynamic_attr = true; }
};
/// Process an 'arithmetic' attribute for enums (does nothing here)
template <>
struct process_attribute<arithmetic> : process_attribute_default<arithmetic> {};
/***
* Process a keep_alive call policy -- invokes keep_alive_impl during the
* pre-call handler if both Nurse, Patient != 0 and use the post-call handler
* otherwise
*/
template <int Nurse, int Patient> struct process_attribute<keep_alive<Nurse, Patient>> : public process_attribute_default<keep_alive<Nurse, Patient>> {
template <int N = Nurse, int P = Patient, enable_if_t<N != 0 && P != 0, int> = 0>
static void precall(handle args) { keep_alive_impl(Nurse, Patient, args, handle()); }
template <int N = Nurse, int P = Patient, enable_if_t<N != 0 && P != 0, int> = 0>
static void postcall(handle, handle) { }
template <int N = Nurse, int P = Patient, enable_if_t<N == 0 || P == 0, int> = 0>
static void precall(handle) { }
template <int N = Nurse, int P = Patient, enable_if_t<N == 0 || P == 0, int> = 0>
static void postcall(handle args, handle ret) { keep_alive_impl(Nurse, Patient, args, ret); }
};
/// Recursively iterate over variadic template arguments
template <typename... Args> struct process_attributes {
static void init(const Args&... args, function_record *r) {
int unused[] = { 0, (process_attribute<typename std::decay<Args>::type>::init(args, r), 0) ... };
ignore_unused(unused);
}
static void init(const Args&... args, type_record *r) {
int unused[] = { 0, (process_attribute<typename std::decay<Args>::type>::init(args, r), 0) ... };
ignore_unused(unused);
}
static void precall(handle fn_args) {
int unused[] = { 0, (process_attribute<typename std::decay<Args>::type>::precall(fn_args), 0) ... };
ignore_unused(unused);
}
static void postcall(handle fn_args, handle fn_ret) {
int unused[] = { 0, (process_attribute<typename std::decay<Args>::type>::postcall(fn_args, fn_ret), 0) ... };
ignore_unused(unused);
}
};
/// Check the number of named arguments at compile time
template <typename... Extra,
size_t named = constexpr_sum(std::is_base_of<arg, Extra>::value...),
size_t self = constexpr_sum(std::is_same<is_method, Extra>::value...)>
constexpr bool expected_num_args(size_t nargs) {
return named == 0 || (self + named) == nargs;
}
NAMESPACE_END(detail)
NAMESPACE_END(pybind11)

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/*
pybind11/chrono.h: Transparent conversion between std::chrono and python's datetime
Copyright (c) 2016 Trent Houliston <trent@houliston.me> and
Wenzel Jakob <wenzel.jakob@epfl.ch>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#pragma once
#include "pybind11.h"
#include <cmath>
#include <ctime>
#include <chrono>
#include <datetime.h>
// Backport the PyDateTime_DELTA functions from Python3.3 if required
#ifndef PyDateTime_DELTA_GET_DAYS
#define PyDateTime_DELTA_GET_DAYS(o) (((PyDateTime_Delta*)o)->days)
#endif
#ifndef PyDateTime_DELTA_GET_SECONDS
#define PyDateTime_DELTA_GET_SECONDS(o) (((PyDateTime_Delta*)o)->seconds)
#endif
#ifndef PyDateTime_DELTA_GET_MICROSECONDS
#define PyDateTime_DELTA_GET_MICROSECONDS(o) (((PyDateTime_Delta*)o)->microseconds)
#endif
NAMESPACE_BEGIN(pybind11)
NAMESPACE_BEGIN(detail)
template <typename type> class duration_caster {
public:
typedef typename type::rep rep;
typedef typename type::period period;
typedef std::chrono::duration<uint_fast32_t, std::ratio<86400>> days;
bool load(handle src, bool) {
using namespace std::chrono;
// Lazy initialise the PyDateTime import
if (!PyDateTimeAPI) { PyDateTime_IMPORT; }
if (!src) return false;
// If invoked with datetime.delta object
if (PyDelta_Check(src.ptr())) {
value = type(duration_cast<duration<rep, period>>(
days(PyDateTime_DELTA_GET_DAYS(src.ptr()))
+ seconds(PyDateTime_DELTA_GET_SECONDS(src.ptr()))
+ microseconds(PyDateTime_DELTA_GET_MICROSECONDS(src.ptr()))));
return true;
}
// If invoked with a float we assume it is seconds and convert
else if (PyFloat_Check(src.ptr())) {
value = type(duration_cast<duration<rep, period>>(duration<double>(PyFloat_AsDouble(src.ptr()))));
return true;
}
else return false;
}
// If this is a duration just return it back
static const std::chrono::duration<rep, period>& get_duration(const std::chrono::duration<rep, period> &src) {
return src;
}
// If this is a time_point get the time_since_epoch
template <typename Clock> static std::chrono::duration<rep, period> get_duration(const std::chrono::time_point<Clock, std::chrono::duration<rep, period>> &src) {
return src.time_since_epoch();
}
static handle cast(const type &src, return_value_policy /* policy */, handle /* parent */) {
using namespace std::chrono;
// Use overloaded function to get our duration from our source
// Works out if it is a duration or time_point and get the duration
auto d = get_duration(src);
// Lazy initialise the PyDateTime import
if (!PyDateTimeAPI) { PyDateTime_IMPORT; }
// Declare these special duration types so the conversions happen with the correct primitive types (int)
using dd_t = duration<int, std::ratio<86400>>;
using ss_t = duration<int, std::ratio<1>>;
using us_t = duration<int, std::micro>;
return PyDelta_FromDSU(duration_cast<dd_t>(d).count(),
duration_cast<ss_t>(d % days(1)).count(),
duration_cast<us_t>(d % seconds(1)).count());
}
PYBIND11_TYPE_CASTER(type, _("datetime.timedelta"));
};
// This is for casting times on the system clock into datetime.datetime instances
template <typename Duration> class type_caster<std::chrono::time_point<std::chrono::system_clock, Duration>> {
public:
typedef std::chrono::time_point<std::chrono::system_clock, Duration> type;
bool load(handle src, bool) {
using namespace std::chrono;
// Lazy initialise the PyDateTime import
if (!PyDateTimeAPI) { PyDateTime_IMPORT; }
if (!src) return false;
if (PyDateTime_Check(src.ptr())) {
std::tm cal;
cal.tm_sec = PyDateTime_DATE_GET_SECOND(src.ptr());
cal.tm_min = PyDateTime_DATE_GET_MINUTE(src.ptr());
cal.tm_hour = PyDateTime_DATE_GET_HOUR(src.ptr());
cal.tm_mday = PyDateTime_GET_DAY(src.ptr());
cal.tm_mon = PyDateTime_GET_MONTH(src.ptr()) - 1;
cal.tm_year = PyDateTime_GET_YEAR(src.ptr()) - 1900;
cal.tm_isdst = -1;
value = system_clock::from_time_t(std::mktime(&cal)) + microseconds(PyDateTime_DATE_GET_MICROSECOND(src.ptr()));
return true;
}
else return false;
}
static handle cast(const std::chrono::time_point<std::chrono::system_clock, Duration> &src, return_value_policy /* policy */, handle /* parent */) {
using namespace std::chrono;
// Lazy initialise the PyDateTime import
if (!PyDateTimeAPI) { PyDateTime_IMPORT; }
std::time_t tt = system_clock::to_time_t(src);
// this function uses static memory so it's best to copy it out asap just in case
// otherwise other code that is using localtime may break this (not just python code)
std::tm localtime = *std::localtime(&tt);
// Declare these special duration types so the conversions happen with the correct primitive types (int)
using us_t = duration<int, std::micro>;
return PyDateTime_FromDateAndTime(localtime.tm_year + 1900,
localtime.tm_mon + 1,
localtime.tm_mday,
localtime.tm_hour,
localtime.tm_min,
localtime.tm_sec,
(duration_cast<us_t>(src.time_since_epoch() % seconds(1))).count());
}
PYBIND11_TYPE_CASTER(type, _("datetime.datetime"));
};
// Other clocks that are not the system clock are not measured as datetime.datetime objects
// since they are not measured on calendar time. So instead we just make them timedeltas
// Or if they have passed us a time as a float we convert that
template <typename Clock, typename Duration> class type_caster<std::chrono::time_point<Clock, Duration>>
: public duration_caster<std::chrono::time_point<Clock, Duration>> {
};
template <typename Rep, typename Period> class type_caster<std::chrono::duration<Rep, Period>>
: public duration_caster<std::chrono::duration<Rep, Period>> {
};
NAMESPACE_END(detail)
NAMESPACE_END(pybind11)

560
resources/pybind11/include/pybind11/common.h

@ -0,0 +1,560 @@
/*
pybind11/common.h -- Basic macros
Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#pragma once
#if !defined(NAMESPACE_BEGIN)
# define NAMESPACE_BEGIN(name) namespace name {
#endif
#if !defined(NAMESPACE_END)
# define NAMESPACE_END(name) }
#endif
// Neither MSVC nor Intel support enough of C++14 yet (in particular, as of MSVC 2015 and ICC 17
// beta, neither support extended constexpr, which we rely on in descr.h), so don't enable pybind
// CPP14 features for them.
#if !defined(_MSC_VER) && !defined(__INTEL_COMPILER)
# if __cplusplus >= 201402L
# define PYBIND11_CPP14
# if __cplusplus > 201402L /* Temporary: should be updated to >= the final C++17 value once known */
# define PYBIND11_CPP17
# endif
# endif
#endif
#if !defined(PYBIND11_EXPORT)
# if defined(WIN32) || defined(_WIN32)
# define PYBIND11_EXPORT __declspec(dllexport)
# else
# define PYBIND11_EXPORT __attribute__ ((visibility("default")))
# endif
#endif
#if defined(_MSC_VER)
# define PYBIND11_NOINLINE __declspec(noinline)
#else
# define PYBIND11_NOINLINE __attribute__ ((noinline))
#endif
#if defined(PYBIND11_CPP14)
# define PYBIND11_DEPRECATED(reason) [[deprecated(reason)]]
#elif defined(__clang__)
# define PYBIND11_DEPRECATED(reason) __attribute__((deprecated(reason)))
#elif defined(__GNUG__)
# define PYBIND11_DEPRECATED(reason) __attribute__((deprecated))
#elif defined(_MSC_VER)
# define PYBIND11_DEPRECATED(reason) __declspec(deprecated)
#endif
#define PYBIND11_VERSION_MAJOR 1
#define PYBIND11_VERSION_MINOR 9
#define PYBIND11_VERSION_PATCH dev0
/// Include Python header, disable linking to pythonX_d.lib on Windows in debug mode
#if defined(_MSC_VER)
# define HAVE_ROUND
# pragma warning(push)
# pragma warning(disable: 4510 4610 4512 4005)
# if _DEBUG
# define PYBIND11_DEBUG_MARKER
# undef _DEBUG
# endif
#endif
#include <Python.h>
#include <frameobject.h>
#include <pythread.h>
#if defined(_WIN32) && (defined(min) || defined(max))
# error Macro clash with min and max -- define NOMINMAX when compiling your program on Windows
#endif
#if defined(isalnum)
# undef isalnum
# undef isalpha
# undef islower
# undef isspace
# undef isupper
# undef tolower
# undef toupper
#endif
#if defined(_MSC_VER)
# if defined(PYBIND11_DEBUG_MARKER)
# define _DEBUG
# undef PYBIND11_DEBUG_MARKER
# endif
# pragma warning(pop)
#endif
#include <cstddef>
#include <forward_list>
#include <vector>
#include <string>
#include <stdexcept>
#include <unordered_set>
#include <unordered_map>
#include <memory>
#include <typeindex>
#include <type_traits>
#if PY_MAJOR_VERSION >= 3 /// Compatibility macros for various Python versions
#define PYBIND11_INSTANCE_METHOD_NEW(ptr, class_) PyInstanceMethod_New(ptr)
#define PYBIND11_BYTES_CHECK PyBytes_Check
#define PYBIND11_BYTES_FROM_STRING PyBytes_FromString
#define PYBIND11_BYTES_FROM_STRING_AND_SIZE PyBytes_FromStringAndSize
#define PYBIND11_BYTES_AS_STRING_AND_SIZE PyBytes_AsStringAndSize
#define PYBIND11_BYTES_AS_STRING PyBytes_AsString
#define PYBIND11_LONG_CHECK(o) PyLong_Check(o)
#define PYBIND11_LONG_AS_LONGLONG(o) PyLong_AsLongLong(o)
#define PYBIND11_LONG_AS_UNSIGNED_LONGLONG(o) PyLong_AsUnsignedLongLong(o)
#define PYBIND11_BYTES_NAME "bytes"
#define PYBIND11_STRING_NAME "str"
#define PYBIND11_SLICE_OBJECT PyObject
#define PYBIND11_FROM_STRING PyUnicode_FromString
#define PYBIND11_STR_TYPE ::pybind11::str
#define PYBIND11_OB_TYPE(ht_type) (ht_type).ob_base.ob_base.ob_type
#define PYBIND11_PLUGIN_IMPL(name) \
extern "C" PYBIND11_EXPORT PyObject *PyInit_##name()
#else
#define PYBIND11_INSTANCE_METHOD_NEW(ptr, class_) PyMethod_New(ptr, nullptr, class_)
#define PYBIND11_BYTES_CHECK PyString_Check
#define PYBIND11_BYTES_FROM_STRING PyString_FromString
#define PYBIND11_BYTES_FROM_STRING_AND_SIZE PyString_FromStringAndSize
#define PYBIND11_BYTES_AS_STRING_AND_SIZE PyString_AsStringAndSize
#define PYBIND11_BYTES_AS_STRING PyString_AsString
#define PYBIND11_LONG_CHECK(o) (PyInt_Check(o) || PyLong_Check(o))
#define PYBIND11_LONG_AS_LONGLONG(o) (PyInt_Check(o) ? (long long) PyLong_AsLong(o) : PyLong_AsLongLong(o))
#define PYBIND11_LONG_AS_UNSIGNED_LONGLONG(o) (PyInt_Check(o) ? (unsigned long long) PyLong_AsUnsignedLong(o) : PyLong_AsUnsignedLongLong(o))
#define PYBIND11_BYTES_NAME "str"
#define PYBIND11_STRING_NAME "unicode"
#define PYBIND11_SLICE_OBJECT PySliceObject
#define PYBIND11_FROM_STRING PyString_FromString
#define PYBIND11_STR_TYPE ::pybind11::bytes
#define PYBIND11_OB_TYPE(ht_type) (ht_type).ob_type
#define PYBIND11_PLUGIN_IMPL(name) \
extern "C" PYBIND11_EXPORT PyObject *init##name()
#endif
#if PY_VERSION_HEX >= 0x03050000 && PY_VERSION_HEX < 0x03050200
extern "C" {
struct _Py_atomic_address { void *value; };
PyAPI_DATA(_Py_atomic_address) _PyThreadState_Current;
}
#endif
#define PYBIND11_TRY_NEXT_OVERLOAD ((PyObject *) 1) // special failure return code
#define PYBIND11_STRINGIFY(x) #x
#define PYBIND11_TOSTRING(x) PYBIND11_STRINGIFY(x)
#define PYBIND11_INTERNALS_ID "__pybind11_" \
PYBIND11_TOSTRING(PYBIND11_VERSION_MAJOR) "_" PYBIND11_TOSTRING(PYBIND11_VERSION_MINOR) "__"
#define PYBIND11_PLUGIN(name) \
static PyObject *pybind11_init(); \
PYBIND11_PLUGIN_IMPL(name) { \
int major, minor; \
if (sscanf(Py_GetVersion(), "%i.%i", &major, &minor) != 2) { \
PyErr_SetString(PyExc_ImportError, "Can't parse Python version."); \
return nullptr; \
} else if (major != PY_MAJOR_VERSION || minor != PY_MINOR_VERSION) { \
PyErr_Format(PyExc_ImportError, \
"Python version mismatch: module was compiled for " \
"version %i.%i, while the interpreter is running " \
"version %i.%i.", PY_MAJOR_VERSION, PY_MINOR_VERSION, \
major, minor); \
return nullptr; \
} \
try { \
return pybind11_init(); \
} catch (const std::exception &e) { \
PyErr_SetString(PyExc_ImportError, e.what()); \
return nullptr; \
} \
} \
PyObject *pybind11_init()
NAMESPACE_BEGIN(pybind11)
using ssize_t = Py_ssize_t;
using size_t = std::size_t;
/// Approach used to cast a previously unknown C++ instance into a Python object
enum class return_value_policy : uint8_t {
/** This is the default return value policy, which falls back to the policy
return_value_policy::take_ownership when the return value is a pointer.
Otherwise, it uses return_value::move or return_value::copy for rvalue
and lvalue references, respectively. See below for a description of what
all of these different policies do. */
automatic = 0,
/** As above, but use policy return_value_policy::reference when the return
value is a pointer. This is the default conversion policy for function
arguments when calling Python functions manually from C++ code (i.e. via
handle::operator()). You probably won't need to use this. */
automatic_reference,
/** Reference an existing object (i.e. do not create a new copy) and take
ownership. Python will call the destructor and delete operator when the
objects reference count reaches zero. Undefined behavior ensues when
the C++ side does the same.. */
take_ownership,
/** Create a new copy of the returned object, which will be owned by
Python. This policy is comparably safe because the lifetimes of the two
instances are decoupled. */
copy,
/** Use std::move to move the return value contents into a new instance
that will be owned by Python. This policy is comparably safe because the
lifetimes of the two instances (move source and destination) are
decoupled. */
move,
/** Reference an existing object, but do not take ownership. The C++ side
is responsible for managing the objects lifetime and deallocating it
when it is no longer used. Warning: undefined behavior will ensue when
the C++ side deletes an object that is still referenced and used by
Python. */
reference,
/** This policy only applies to methods and properties. It references the
object without taking ownership similar to the above
return_value_policy::reference policy. In contrast to that policy, the
function or propertys implicit this argument (called the parent) is
considered to be the the owner of the return value (the child).
pybind11 then couples the lifetime of the parent to the child via a
reference relationship that ensures that the parent cannot be garbage
collected while Python is still using the child. More advanced
variations of this scheme are also possible using combinations of
return_value_policy::reference and the keep_alive call policy */
reference_internal
};
/// Information record describing a Python buffer object
struct buffer_info {
void *ptr = nullptr; // Pointer to the underlying storage
size_t itemsize = 0; // Size of individual items in bytes
size_t size = 0; // Total number of entries
std::string format; // For homogeneous buffers, this should be set to format_descriptor<T>::format()
size_t ndim = 0; // Number of dimensions
std::vector<size_t> shape; // Shape of the tensor (1 entry per dimension)
std::vector<size_t> strides; // Number of entries between adjacent entries (for each per dimension)
buffer_info() { }
buffer_info(void *ptr, size_t itemsize, const std::string &format, size_t ndim,
const std::vector<size_t> &shape, const std::vector<size_t> &strides)
: ptr(ptr), itemsize(itemsize), size(1), format(format),
ndim(ndim), shape(shape), strides(strides) {
for (size_t i = 0; i < ndim; ++i)
size *= shape[i];
}
buffer_info(void *ptr, size_t itemsize, const std::string &format, size_t size)
: buffer_info(ptr, itemsize, format, 1, std::vector<size_t> { size },
std::vector<size_t> { itemsize }) { }
explicit buffer_info(Py_buffer *view, bool ownview = true)
: ptr(view->buf), itemsize((size_t) view->itemsize), size(1), format(view->format),
ndim((size_t) view->ndim), shape((size_t) view->ndim), strides((size_t) view->ndim), view(view), ownview(ownview) {
for (size_t i = 0; i < (size_t) view->ndim; ++i) {
shape[i] = (size_t) view->shape[i];
strides[i] = (size_t) view->strides[i];
size *= shape[i];
}
}
buffer_info(const buffer_info &) = delete;
buffer_info& operator=(const buffer_info &) = delete;
buffer_info(buffer_info &&other) {
(*this) = std::move(other);
}
buffer_info& operator=(buffer_info &&rhs) {
ptr = rhs.ptr;
itemsize = rhs.itemsize;
size = rhs.size;
format = std::move(rhs.format);
ndim = rhs.ndim;
shape = std::move(rhs.shape);
strides = std::move(rhs.strides);
std::swap(view, rhs.view);
std::swap(ownview, rhs.ownview);
return *this;
}
~buffer_info() {
if (view && ownview) { PyBuffer_Release(view); delete view; }
}
private:
Py_buffer *view = nullptr;
bool ownview = false;
};
NAMESPACE_BEGIN(detail)
inline static constexpr int log2(size_t n, int k = 0) { return (n <= 1) ? k : log2(n >> 1, k + 1); }
inline std::string error_string();
/// Core part of the 'instance' type which POD (needed to be able to use 'offsetof')
template <typename type> struct instance_essentials {
PyObject_HEAD
type *value;
PyObject *weakrefs;
bool owned : 1;
bool holder_constructed : 1;
};
/// PyObject wrapper around generic types, includes a special holder type that is responsible for lifetime management
template <typename type, typename holder_type = std::unique_ptr<type>> struct instance : instance_essentials<type> {
holder_type holder;
};
struct overload_hash {
inline size_t operator()(const std::pair<const PyObject *, const char *>& v) const {
size_t value = std::hash<const void *>()(v.first);
value ^= std::hash<const void *>()(v.second) + 0x9e3779b9 + (value<<6) + (value>>2);
return value;
}
};
/// Internal data struture used to track registered instances and types
struct internals {
std::unordered_map<std::type_index, void*> registered_types_cpp; // std::type_index -> type_info
std::unordered_map<const void *, void*> registered_types_py; // PyTypeObject* -> type_info
std::unordered_multimap<const void *, void*> registered_instances; // void * -> PyObject*
std::unordered_set<std::pair<const PyObject *, const char *>, overload_hash> inactive_overload_cache;
std::unordered_map<std::type_index, std::vector<bool (*)(PyObject *, void *&)>> direct_conversions;
std::forward_list<void (*) (std::exception_ptr)> registered_exception_translators;
std::unordered_map<std::string, void *> shared_data; // Custom data to be shared across extensions
#if defined(WITH_THREAD)
decltype(PyThread_create_key()) tstate = 0; // Usually an int but a long on Cygwin64 with Python 3.x
PyInterpreterState *istate = nullptr;
#endif
};
/// Return a reference to the current 'internals' information
inline internals &get_internals();
/// Index sequence for convenient template metaprogramming involving tuples
#ifdef PYBIND11_CPP14
using std::index_sequence;
using std::make_index_sequence;
#else
template<size_t ...> struct index_sequence { };
template<size_t N, size_t ...S> struct make_index_sequence_impl : make_index_sequence_impl <N - 1, N - 1, S...> { };
template<size_t ...S> struct make_index_sequence_impl <0, S...> { typedef index_sequence<S...> type; };
template<size_t N> using make_index_sequence = typename make_index_sequence_impl<N>::type;
#endif
/// Strip the class from a method type
template <typename T> struct remove_class { };
template <typename C, typename R, typename... A> struct remove_class<R (C::*)(A...)> { typedef R type(A...); };
template <typename C, typename R, typename... A> struct remove_class<R (C::*)(A...) const> { typedef R type(A...); };
/// Helper template to strip away type modifiers
template <typename T> struct intrinsic_type { typedef T type; };
template <typename T> struct intrinsic_type<const T> { typedef typename intrinsic_type<T>::type type; };
template <typename T> struct intrinsic_type<T*> { typedef typename intrinsic_type<T>::type type; };
template <typename T> struct intrinsic_type<T&> { typedef typename intrinsic_type<T>::type type; };
template <typename T> struct intrinsic_type<T&&> { typedef typename intrinsic_type<T>::type type; };
template <typename T, size_t N> struct intrinsic_type<const T[N]> { typedef typename intrinsic_type<T>::type type; };
template <typename T, size_t N> struct intrinsic_type<T[N]> { typedef typename intrinsic_type<T>::type type; };
template <typename T> using intrinsic_t = typename intrinsic_type<T>::type;
/// Helper type to replace 'void' in some expressions
struct void_type { };
/// Helper template which holds a list of types
template <typename...> struct type_list { };
/// from __cpp_future__ import (convenient aliases from C++14/17)
template <bool B> using bool_constant = std::integral_constant<bool, B>;
template <class T> using negation = bool_constant<!T::value>;
template <bool B, typename T = void> using enable_if_t = typename std::enable_if<B, T>::type;
template <bool B, typename T, typename F> using conditional_t = typename std::conditional<B, T, F>::type;
/// Compile-time integer sum
constexpr size_t constexpr_sum() { return 0; }
template <typename T, typename... Ts>
constexpr size_t constexpr_sum(T n, Ts... ns) { return size_t{n} + constexpr_sum(ns...); }
// Counts the number of types in the template parameter pack matching the predicate
#if !defined(_MSC_VER)
template <template<typename> class Predicate, typename... Ts>
using count_t = std::integral_constant<size_t, constexpr_sum(Predicate<Ts>::value...)>;
#else
// MSVC workaround (2015 Update 3 has issues with some member type aliases and constexpr)
template <template<typename> class Predicate, typename... Ts> struct count_t;
template <template<typename> class Predicate> struct count_t<Predicate> : std::integral_constant<size_t, 0> {};
template <template<typename> class Predicate, class T, class... Ts>
struct count_t<Predicate, T, Ts...> : std::integral_constant<size_t, Predicate<T>::value + count_t<Predicate, Ts...>::value> {};
#endif
/// Return true if all/any Ts satify Predicate<T>
template <template<typename> class Predicate, typename... Ts>
using all_of_t = bool_constant<(count_t<Predicate, Ts...>::value == sizeof...(Ts))>;
template <template<typename> class Predicate, typename... Ts>
using any_of_t = bool_constant<(count_t<Predicate, Ts...>::value > 0)>;
// Extracts the first type from the template parameter pack matching the predicate, or Default if none match.
template <template<class> class Predicate, class Default, class... Ts> struct first_of;
template <template<class> class Predicate, class Default> struct first_of<Predicate, Default> {
using type = Default;
};
template <template<class> class Predicate, class Default, class T, class... Ts>
struct first_of<Predicate, Default, T, Ts...> {
using type = typename std::conditional<
Predicate<T>::value,
T,
typename first_of<Predicate, Default, Ts...>::type
>::type;
};
template <template<class> class Predicate, class Default, class... T> using first_of_t = typename first_of<Predicate, Default, T...>::type;
/// Defer the evaluation of type T until types Us are instantiated
template <typename T, typename... /*Us*/> struct deferred_type { using type = T; };
template <typename T, typename... Us> using deferred_t = typename deferred_type<T, Us...>::type;
template <template<typename...> class Base>
struct is_template_base_of_impl {
template <typename... Us> static std::true_type check(Base<Us...> *);
static std::false_type check(...);
};
/// Check if a template is the base of a type. For example:
/// `is_template_base_of<Base, T>` is true if `struct T : Base<U> {}` where U can be anything
template <template<typename...> class Base, typename T>
#if !defined(_MSC_VER)
using is_template_base_of = decltype(is_template_base_of_impl<Base>::check((T*)nullptr));
#else // MSVC2015 has trouble with decltype in template aliases
struct is_template_base_of : decltype(is_template_base_of_impl<Base>::check((T*)nullptr)) { };
#endif
/// Check if T is std::shared_ptr<U> where U can be anything
template <typename T> struct is_shared_ptr : std::false_type { };
template <typename U> struct is_shared_ptr<std::shared_ptr<U>> : std::true_type { };
/// Ignore that a variable is unused in compiler warnings
inline void ignore_unused(const int *) { }
NAMESPACE_END(detail)
/// Returns a named pointer that is shared among all extension modules (using the same
/// pybind11 version) running in the current interpreter. Names starting with underscores
/// are reserved for internal usage. Returns `nullptr` if no matching entry was found.
inline PYBIND11_NOINLINE void* get_shared_data(const std::string& name) {
auto& internals = detail::get_internals();
auto it = internals.shared_data.find(name);
return it != internals.shared_data.end() ? it->second : nullptr;
}
/// Set the shared data that can be later recovered by `get_shared_data()`.
inline PYBIND11_NOINLINE void *set_shared_data(const std::string& name, void *data) {
detail::get_internals().shared_data[name] = data;
return data;
}
/// Returns a typed reference to a shared data entry (by using `get_shared_data()`) if
/// such entry exists. Otherwise, a new object of default-constructible type `T` is
/// added to the shared data under the given name and a reference to it is returned.
template<typename T> T& get_or_create_shared_data(const std::string& name) {
auto& internals = detail::get_internals();
auto it = internals.shared_data.find(name);
T* ptr = (T*) (it != internals.shared_data.end() ? it->second : nullptr);
if (!ptr) {
ptr = new T();
internals.shared_data[name] = ptr;
}
return *ptr;
}
/// Fetch and hold an error which was already set in Python
class error_already_set : public std::runtime_error {
public:
error_already_set() : std::runtime_error(detail::error_string()) {
PyErr_Fetch(&type, &value, &trace);
}
error_already_set(const error_already_set &) = delete;
error_already_set(error_already_set &&e)
: std::runtime_error(e.what()), type(e.type), value(e.value),
trace(e.trace) { e.type = e.value = e.trace = nullptr; }
inline ~error_already_set(); // implementation in pybind11.h
error_already_set& operator=(const error_already_set &) = delete;
/// Give the error back to Python
void restore() { PyErr_Restore(type, value, trace); type = value = trace = nullptr; }
private:
PyObject *type, *value, *trace;
};
/// C++ bindings of builtin Python exceptions
class builtin_exception : public std::runtime_error {
public:
using std::runtime_error::runtime_error;
virtual void set_error() const = 0; /// Set the error using the Python C API
};
#define PYBIND11_RUNTIME_EXCEPTION(name, type) \
class name : public builtin_exception { public: \
using builtin_exception::builtin_exception; \
name() : name("") { } \
void set_error() const override { PyErr_SetString(type, what()); } \
};
PYBIND11_RUNTIME_EXCEPTION(stop_iteration, PyExc_StopIteration)
PYBIND11_RUNTIME_EXCEPTION(index_error, PyExc_IndexError)
PYBIND11_RUNTIME_EXCEPTION(key_error, PyExc_KeyError)
PYBIND11_RUNTIME_EXCEPTION(value_error, PyExc_ValueError)
PYBIND11_RUNTIME_EXCEPTION(type_error, PyExc_TypeError)
PYBIND11_RUNTIME_EXCEPTION(cast_error, PyExc_RuntimeError) /// Thrown when pybind11::cast or handle::call fail due to a type casting error
PYBIND11_RUNTIME_EXCEPTION(reference_cast_error, PyExc_RuntimeError) /// Used internally
[[noreturn]] PYBIND11_NOINLINE inline void pybind11_fail(const char *reason) { throw std::runtime_error(reason); }
[[noreturn]] PYBIND11_NOINLINE inline void pybind11_fail(const std::string &reason) { throw std::runtime_error(reason); }
/// Format strings for basic number types
#define PYBIND11_DECL_FMT(t, v) template<> struct format_descriptor<t> \
{ static constexpr const char* value = v; /* for backwards compatibility */ \
static std::string format() { return value; } }
template <typename T, typename SFINAE = void> struct format_descriptor { };
template <typename T> struct format_descriptor<T, detail::enable_if_t<std::is_integral<T>::value>> {
static constexpr const char c = "bBhHiIqQ"[detail::log2(sizeof(T))*2 + std::is_unsigned<T>::value];
static constexpr const char value[2] = { c, '\0' };
static std::string format() { return std::string(1, c); }
};
template <typename T> constexpr const char format_descriptor<
T, detail::enable_if_t<std::is_integral<T>::value>>::value[2];
/// RAII wrapper that temporarily clears any Python error state
struct error_scope {
PyObject *type, *value, *trace;
error_scope() { PyErr_Fetch(&type, &value, &trace); }
~error_scope() { PyErr_Restore(type, value, trace); }
};
PYBIND11_DECL_FMT(float, "f");
PYBIND11_DECL_FMT(double, "d");
PYBIND11_DECL_FMT(bool, "?");
/// Dummy destructor wrapper that can be used to expose classes with a private destructor
struct nodelete { template <typename T> void operator()(T*) { } };
NAMESPACE_END(pybind11)

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resources/pybind11/include/pybind11/complex.h

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/*
pybind11/complex.h: Complex number support
Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#pragma once
#include "pybind11.h"
#include <complex>
/// glibc defines I as a macro which breaks things, e.g., boost template names
#ifdef I
# undef I
#endif
NAMESPACE_BEGIN(pybind11)
PYBIND11_DECL_FMT(std::complex<float>, "Zf");
PYBIND11_DECL_FMT(std::complex<double>, "Zd");
NAMESPACE_BEGIN(detail)
template <typename T> class type_caster<std::complex<T>> {
public:
bool load(handle src, bool) {
if (!src)
return false;
Py_complex result = PyComplex_AsCComplex(src.ptr());
if (result.real == -1.0 && PyErr_Occurred()) {
PyErr_Clear();
return false;
}
value = std::complex<T>((T) result.real, (T) result.imag);
return true;
}
static handle cast(const std::complex<T> &src, return_value_policy /* policy */, handle /* parent */) {
return PyComplex_FromDoubles((double) src.real(), (double) src.imag());
}
PYBIND11_TYPE_CASTER(std::complex<T>, _("complex"));
};
NAMESPACE_END(detail)
NAMESPACE_END(pybind11)

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resources/pybind11/include/pybind11/descr.h

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/*
pybind11/descr.h: Helper type for concatenating type signatures
either at runtime (C++11) or compile time (C++14)
Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#pragma once
#include "common.h"
NAMESPACE_BEGIN(pybind11)
NAMESPACE_BEGIN(detail)
#if defined(PYBIND11_CPP14) /* Concatenate type signatures at compile time using C++14 */
template <size_t Size1, size_t Size2> class descr {
template <size_t Size1_, size_t Size2_> friend class descr;
public:
constexpr descr(char const (&text) [Size1+1], const std::type_info * const (&types)[Size2+1])
: descr(text, types,
make_index_sequence<Size1>(),
make_index_sequence<Size2>()) { }
constexpr const char *text() const { return m_text; }
constexpr const std::type_info * const * types() const { return m_types; }
template <size_t OtherSize1, size_t OtherSize2>
constexpr descr<Size1 + OtherSize1, Size2 + OtherSize2> operator+(const descr<OtherSize1, OtherSize2> &other) const {
return concat(other,
make_index_sequence<Size1>(),
make_index_sequence<Size2>(),
make_index_sequence<OtherSize1>(),
make_index_sequence<OtherSize2>());
}
protected:
template <size_t... Indices1, size_t... Indices2>
constexpr descr(
char const (&text) [Size1+1],
const std::type_info * const (&types) [Size2+1],
index_sequence<Indices1...>, index_sequence<Indices2...>)
: m_text{text[Indices1]..., '\0'},
m_types{types[Indices2]..., nullptr } {}
template <size_t OtherSize1, size_t OtherSize2, size_t... Indices1,
size_t... Indices2, size_t... OtherIndices1, size_t... OtherIndices2>
constexpr descr<Size1 + OtherSize1, Size2 + OtherSize2>
concat(const descr<OtherSize1, OtherSize2> &other,
index_sequence<Indices1...>, index_sequence<Indices2...>,
index_sequence<OtherIndices1...>, index_sequence<OtherIndices2...>) const {
return descr<Size1 + OtherSize1, Size2 + OtherSize2>(
{ m_text[Indices1]..., other.m_text[OtherIndices1]..., '\0' },
{ m_types[Indices2]..., other.m_types[OtherIndices2]..., nullptr }
);
}
protected:
char m_text[Size1 + 1];
const std::type_info * m_types[Size2 + 1];
};
template <size_t Size> constexpr descr<Size - 1, 0> _(char const(&text)[Size]) {
return descr<Size - 1, 0>(text, { nullptr });
}
template <size_t Rem, size_t... Digits> struct int_to_str : int_to_str<Rem/10, Rem%10, Digits...> { };
template <size_t...Digits> struct int_to_str<0, Digits...> {
static constexpr auto digits = descr<sizeof...(Digits), 0>({ ('0' + Digits)..., '\0' }, { nullptr });
};
// Ternary description (like std::conditional)
template <bool B, size_t Size1, size_t Size2>
constexpr enable_if_t<B, descr<Size1 - 1, 0>> _(char const(&text1)[Size1], char const(&)[Size2]) {
return _(text1);
}
template <bool B, size_t Size1, size_t Size2>
constexpr enable_if_t<!B, descr<Size2 - 1, 0>> _(char const(&)[Size1], char const(&text2)[Size2]) {
return _(text2);
}
template <size_t Size> auto constexpr _() -> decltype(int_to_str<Size / 10, Size % 10>::digits) {
return int_to_str<Size / 10, Size % 10>::digits;
}
template <typename Type> constexpr descr<1, 1> _() {
return descr<1, 1>({ '%', '\0' }, { &typeid(Type), nullptr });
}
inline constexpr descr<0, 0> concat() { return _(""); }
template <size_t Size1, size_t Size2, typename... Args> auto constexpr concat(descr<Size1, Size2> descr) { return descr; }
template <size_t Size1, size_t Size2, typename... Args> auto constexpr concat(descr<Size1, Size2> descr, Args&&... args) { return descr + _(", ") + concat(args...); }
template <size_t Size1, size_t Size2> auto constexpr type_descr(descr<Size1, Size2> descr) { return _("{") + descr + _("}"); }
#define PYBIND11_DESCR constexpr auto
#else /* Simpler C++11 implementation based on run-time memory allocation and copying */
class descr {
public:
PYBIND11_NOINLINE descr(const char *text, const std::type_info * const * types) {
size_t nChars = len(text), nTypes = len(types);
m_text = new char[nChars];
m_types = new const std::type_info *[nTypes];
memcpy(m_text, text, nChars * sizeof(char));
memcpy(m_types, types, nTypes * sizeof(const std::type_info *));
}
PYBIND11_NOINLINE descr friend operator+(descr &&d1, descr &&d2) {
descr r;
size_t nChars1 = len(d1.m_text), nTypes1 = len(d1.m_types);
size_t nChars2 = len(d2.m_text), nTypes2 = len(d2.m_types);
r.m_text = new char[nChars1 + nChars2 - 1];
r.m_types = new const std::type_info *[nTypes1 + nTypes2 - 1];
memcpy(r.m_text, d1.m_text, (nChars1-1) * sizeof(char));
memcpy(r.m_text + nChars1 - 1, d2.m_text, nChars2 * sizeof(char));
memcpy(r.m_types, d1.m_types, (nTypes1-1) * sizeof(std::type_info *));
memcpy(r.m_types + nTypes1 - 1, d2.m_types, nTypes2 * sizeof(std::type_info *));
delete[] d1.m_text; delete[] d1.m_types;
delete[] d2.m_text; delete[] d2.m_types;
return r;
}
char *text() { return m_text; }
const std::type_info * * types() { return m_types; }
protected:
PYBIND11_NOINLINE descr() { }
template <typename T> static size_t len(const T *ptr) { // return length including null termination
const T *it = ptr;
while (*it++ != (T) 0)
;
return static_cast<size_t>(it - ptr);
}
const std::type_info **m_types = nullptr;
char *m_text = nullptr;
};
/* The 'PYBIND11_NOINLINE inline' combinations below are intentional to get the desired linkage while producing as little object code as possible */
PYBIND11_NOINLINE inline descr _(const char *text) {
const std::type_info *types[1] = { nullptr };
return descr(text, types);
}
template <bool B> PYBIND11_NOINLINE enable_if_t<B, descr> _(const char *text1, const char *) { return _(text1); }
template <bool B> PYBIND11_NOINLINE enable_if_t<!B, descr> _(char const *, const char *text2) { return _(text2); }
template <typename Type> PYBIND11_NOINLINE descr _() {
const std::type_info *types[2] = { &typeid(Type), nullptr };
return descr("%", types);
}
template <size_t Size> PYBIND11_NOINLINE descr _() {
const std::type_info *types[1] = { nullptr };
return descr(std::to_string(Size).c_str(), types);
}
PYBIND11_NOINLINE inline descr concat() { return _(""); }
PYBIND11_NOINLINE inline descr concat(descr &&d) { return d; }
template <typename... Args> PYBIND11_NOINLINE descr concat(descr &&d, Args&&... args) { return std::move(d) + _(", ") + concat(std::forward<Args>(args)...); }
PYBIND11_NOINLINE inline descr type_descr(descr&& d) { return _("{") + std::move(d) + _("}"); }
#define PYBIND11_DESCR ::pybind11::detail::descr
#endif
NAMESPACE_END(detail)
NAMESPACE_END(pybind11)

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resources/pybind11/include/pybind11/eigen.h

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/*
pybind11/eigen.h: Transparent conversion for dense and sparse Eigen matrices
Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#pragma once
#include "numpy.h"
#if defined(__INTEL_COMPILER)
# pragma warning(disable: 1682) // implicit conversion of a 64-bit integral type to a smaller integral type (potential portability problem)
#elif defined(__GNUG__) || defined(__clang__)
# pragma GCC diagnostic push
# pragma GCC diagnostic ignored "-Wconversion"
# pragma GCC diagnostic ignored "-Wdeprecated-declarations"
#endif
#include <Eigen/Core>
#include <Eigen/SparseCore>
#if defined(__GNUG__) || defined(__clang__)
# pragma GCC diagnostic pop
#endif
#if defined(_MSC_VER)
#pragma warning(push)
#pragma warning(disable: 4127) // warning C4127: Conditional expression is constant
#endif
NAMESPACE_BEGIN(pybind11)
NAMESPACE_BEGIN(detail)
template <typename T> using is_eigen_dense = is_template_base_of<Eigen::DenseBase, T>;
template <typename T> using is_eigen_sparse = is_template_base_of<Eigen::SparseMatrixBase, T>;
template <typename T> using is_eigen_ref = is_template_base_of<Eigen::RefBase, T>;
// Test for objects inheriting from EigenBase<Derived> that aren't captured by the above. This
// basically covers anything that can be assigned to a dense matrix but that don't have a typical
// matrix data layout that can be copied from their .data(). For example, DiagonalMatrix and
// SelfAdjointView fall into this category.
template <typename T> using is_eigen_base = bool_constant<
is_template_base_of<Eigen::EigenBase, T>::value
&& !is_eigen_dense<T>::value && !is_eigen_sparse<T>::value
>;
template<typename Type>
struct type_caster<Type, enable_if_t<is_eigen_dense<Type>::value && !is_eigen_ref<Type>::value>> {
typedef typename Type::Scalar Scalar;
static constexpr bool rowMajor = Type::Flags & Eigen::RowMajorBit;
static constexpr bool isVector = Type::IsVectorAtCompileTime;
bool load(handle src, bool) {
auto buf = array_t<Scalar>::ensure(src);
if (!buf)
return false;
if (buf.ndim() == 1) {
typedef Eigen::InnerStride<> Strides;
if (!isVector &&
!(Type::RowsAtCompileTime == Eigen::Dynamic &&
Type::ColsAtCompileTime == Eigen::Dynamic))
return false;
if (Type::SizeAtCompileTime != Eigen::Dynamic &&
buf.shape(0) != (size_t) Type::SizeAtCompileTime)
return false;
Strides::Index n_elts = (Strides::Index) buf.shape(0);
Strides::Index unity = 1;
value = Eigen::Map<Type, 0, Strides>(
buf.mutable_data(),
rowMajor ? unity : n_elts,
rowMajor ? n_elts : unity,
Strides(buf.strides(0) / sizeof(Scalar))
);
} else if (buf.ndim() == 2) {
typedef Eigen::Stride<Eigen::Dynamic, Eigen::Dynamic> Strides;
if ((Type::RowsAtCompileTime != Eigen::Dynamic && buf.shape(0) != (size_t) Type::RowsAtCompileTime) ||
(Type::ColsAtCompileTime != Eigen::Dynamic && buf.shape(1) != (size_t) Type::ColsAtCompileTime))
return false;
value = Eigen::Map<Type, 0, Strides>(
buf.mutable_data(),
typename Strides::Index(buf.shape(0)),
typename Strides::Index(buf.shape(1)),
Strides(buf.strides(rowMajor ? 0 : 1) / sizeof(Scalar),
buf.strides(rowMajor ? 1 : 0) / sizeof(Scalar))
);
} else {
return false;
}
return true;
}
static handle cast(const Type &src, return_value_policy /* policy */, handle /* parent */) {
if (isVector) {
return array(
{ (size_t) src.size() }, // shape
{ sizeof(Scalar) * static_cast<size_t>(src.innerStride()) }, // strides
src.data() // data
).release();
} else {
return array(
{ (size_t) src.rows(), // shape
(size_t) src.cols() },
{ sizeof(Scalar) * static_cast<size_t>(src.rowStride()), // strides
sizeof(Scalar) * static_cast<size_t>(src.colStride()) },
src.data() // data
).release();
}
}
PYBIND11_TYPE_CASTER(Type, _("numpy.ndarray[") + npy_format_descriptor<Scalar>::name() +
_("[") + rows() + _(", ") + cols() + _("]]"));
protected:
template <typename T = Type, enable_if_t<T::RowsAtCompileTime == Eigen::Dynamic, int> = 0>
static PYBIND11_DESCR rows() { return _("m"); }
template <typename T = Type, enable_if_t<T::RowsAtCompileTime != Eigen::Dynamic, int> = 0>
static PYBIND11_DESCR rows() { return _<T::RowsAtCompileTime>(); }
template <typename T = Type, enable_if_t<T::ColsAtCompileTime == Eigen::Dynamic, int> = 0>
static PYBIND11_DESCR cols() { return _("n"); }
template <typename T = Type, enable_if_t<T::ColsAtCompileTime != Eigen::Dynamic, int> = 0>
static PYBIND11_DESCR cols() { return _<T::ColsAtCompileTime>(); }
};
// Eigen::Ref<Derived> satisfies is_eigen_dense, but isn't constructable, so it needs a special
// type_caster to handle argument copying/forwarding.
template <typename CVDerived, int Options, typename StrideType>
struct type_caster<Eigen::Ref<CVDerived, Options, StrideType>> {
protected:
using Type = Eigen::Ref<CVDerived, Options, StrideType>;
using Derived = typename std::remove_const<CVDerived>::type;
using DerivedCaster = type_caster<Derived>;
DerivedCaster derived_caster;
std::unique_ptr<Type> value;
public:
bool load(handle src, bool convert) { if (derived_caster.load(src, convert)) { value.reset(new Type(derived_caster.operator Derived&())); return true; } return false; }
static handle cast(const Type &src, return_value_policy policy, handle parent) { return DerivedCaster::cast(src, policy, parent); }
static handle cast(const Type *src, return_value_policy policy, handle parent) { return DerivedCaster::cast(*src, policy, parent); }
static PYBIND11_DESCR name() { return DerivedCaster::name(); }
operator Type*() { return value.get(); }
operator Type&() { if (!value) pybind11_fail("Eigen::Ref<...> value not loaded"); return *value; }
template <typename _T> using cast_op_type = pybind11::detail::cast_op_type<_T>;
};
// type_caster for special matrix types (e.g. DiagonalMatrix): load() is not supported, but we can
// cast them into the python domain by first copying to a regular Eigen::Matrix, then casting that.
template <typename Type>
struct type_caster<Type, enable_if_t<is_eigen_base<Type>::value && !is_eigen_ref<Type>::value>> {
protected:
using Matrix = Eigen::Matrix<typename Type::Scalar, Eigen::Dynamic, Eigen::Dynamic>;
using MatrixCaster = type_caster<Matrix>;
public:
[[noreturn]] bool load(handle, bool) { pybind11_fail("Unable to load() into specialized EigenBase object"); }
static handle cast(const Type &src, return_value_policy policy, handle parent) { return MatrixCaster::cast(Matrix(src), policy, parent); }
static handle cast(const Type *src, return_value_policy policy, handle parent) { return MatrixCaster::cast(Matrix(*src), policy, parent); }
static PYBIND11_DESCR name() { return MatrixCaster::name(); }
[[noreturn]] operator Type*() { pybind11_fail("Loading not supported for specialized EigenBase object"); }
[[noreturn]] operator Type&() { pybind11_fail("Loading not supported for specialized EigenBase object"); }
template <typename _T> using cast_op_type = pybind11::detail::cast_op_type<_T>;
};
template<typename Type>
struct type_caster<Type, enable_if_t<is_eigen_sparse<Type>::value>> {
typedef typename Type::Scalar Scalar;
typedef typename std::remove_reference<decltype(*std::declval<Type>().outerIndexPtr())>::type StorageIndex;
typedef typename Type::Index Index;
static constexpr bool rowMajor = Type::Flags & Eigen::RowMajorBit;
bool load(handle src, bool) {
if (!src)
return false;
auto obj = reinterpret_borrow<object>(src);
object sparse_module = module::import("scipy.sparse");
object matrix_type = sparse_module.attr(
rowMajor ? "csr_matrix" : "csc_matrix");
if (obj.get_type() != matrix_type.ptr()) {
try {
obj = matrix_type(obj);
} catch (const error_already_set &) {
return false;
}
}
auto values = array_t<Scalar>((object) obj.attr("data"));
auto innerIndices = array_t<StorageIndex>((object) obj.attr("indices"));
auto outerIndices = array_t<StorageIndex>((object) obj.attr("indptr"));
auto shape = pybind11::tuple((pybind11::object) obj.attr("shape"));
auto nnz = obj.attr("nnz").cast<Index>();
if (!values || !innerIndices || !outerIndices)
return false;
value = Eigen::MappedSparseMatrix<Scalar, Type::Flags, StorageIndex>(
shape[0].cast<Index>(), shape[1].cast<Index>(), nnz,
outerIndices.mutable_data(), innerIndices.mutable_data(), values.mutable_data());
return true;
}
static handle cast(const Type &src, return_value_policy /* policy */, handle /* parent */) {
const_cast<Type&>(src).makeCompressed();
object matrix_type = module::import("scipy.sparse").attr(
rowMajor ? "csr_matrix" : "csc_matrix");
array data((size_t) src.nonZeros(), src.valuePtr());
array outerIndices((size_t) (rowMajor ? src.rows() : src.cols()) + 1, src.outerIndexPtr());
array innerIndices((size_t) src.nonZeros(), src.innerIndexPtr());
return matrix_type(
std::make_tuple(data, innerIndices, outerIndices),
std::make_pair(src.rows(), src.cols())
).release();
}
PYBIND11_TYPE_CASTER(Type, _<(Type::Flags & Eigen::RowMajorBit) != 0>("scipy.sparse.csr_matrix[", "scipy.sparse.csc_matrix[")
+ npy_format_descriptor<Scalar>::name() + _("]"));
};
NAMESPACE_END(detail)
NAMESPACE_END(pybind11)
#if defined(_MSC_VER)
#pragma warning(pop)
#endif

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resources/pybind11/include/pybind11/eval.h

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/*
pybind11/exec.h: Support for evaluating Python expressions and statements
from strings and files
Copyright (c) 2016 Klemens Morgenstern <klemens.morgenstern@ed-chemnitz.de> and
Wenzel Jakob <wenzel.jakob@epfl.ch>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#pragma once
#pragma once
#include "pybind11.h"
NAMESPACE_BEGIN(pybind11)
enum eval_mode {
/// Evaluate a string containing an isolated expression
eval_expr,
/// Evaluate a string containing a single statement. Returns \c none
eval_single_statement,
/// Evaluate a string containing a sequence of statement. Returns \c none
eval_statements
};
template <eval_mode mode = eval_expr>
object eval(str expr, object global = object(), object local = object()) {
if (!global) {
global = reinterpret_borrow<object>(PyEval_GetGlobals());
if (!global)
global = dict();
}
if (!local)
local = global;
/* PyRun_String does not accept a PyObject / encoding specifier,
this seems to be the only alternative */
std::string buffer = "# -*- coding: utf-8 -*-\n" + (std::string) expr;
int start;
switch (mode) {
case eval_expr: start = Py_eval_input; break;
case eval_single_statement: start = Py_single_input; break;
case eval_statements: start = Py_file_input; break;
default: pybind11_fail("invalid evaluation mode");
}
PyObject *result = PyRun_String(buffer.c_str(), start, global.ptr(), local.ptr());
if (!result)
throw error_already_set();
return reinterpret_steal<object>(result);
}
template <eval_mode mode = eval_statements>
object eval_file(str fname, object global = object(), object local = object()) {
if (!global) {
global = reinterpret_borrow<object>(PyEval_GetGlobals());
if (!global)
global = dict();
}
if (!local)
local = global;
int start;
switch (mode) {
case eval_expr: start = Py_eval_input; break;
case eval_single_statement: start = Py_single_input; break;
case eval_statements: start = Py_file_input; break;
default: pybind11_fail("invalid evaluation mode");
}
int closeFile = 1;
std::string fname_str = (std::string) fname;
#if PY_VERSION_HEX >= 0x03040000
FILE *f = _Py_fopen_obj(fname.ptr(), "r");
#elif PY_VERSION_HEX >= 0x03000000
FILE *f = _Py_fopen(fname.ptr(), "r");
#else
/* No unicode support in open() :( */
auto fobj = reinterpret_steal<object>(PyFile_FromString(
const_cast<char *>(fname_str.c_str()),
const_cast<char*>("r")));
FILE *f = nullptr;
if (fobj)
f = PyFile_AsFile(fobj.ptr());
closeFile = 0;
#endif
if (!f) {
PyErr_Clear();
pybind11_fail("File \"" + fname_str + "\" could not be opened!");
}
PyObject *result = PyRun_FileEx(f, fname_str.c_str(), start, global.ptr(),
local.ptr(), closeFile);
if (!result)
throw error_already_set();
return reinterpret_steal<object>(result);
}
NAMESPACE_END(pybind11)

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resources/pybind11/include/pybind11/functional.h

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/*
pybind11/functional.h: std::function<> support
Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#pragma once
#include "pybind11.h"
#include <functional>
NAMESPACE_BEGIN(pybind11)
NAMESPACE_BEGIN(detail)
template <typename Return, typename... Args> struct type_caster<std::function<Return(Args...)>> {
typedef std::function<Return(Args...)> type;
typedef typename std::conditional<std::is_same<Return, void>::value, void_type, Return>::type retval_type;
public:
bool load(handle src_, bool) {
if (src_.is_none())
return true;
src_ = detail::get_function(src_);
if (!src_ || !PyCallable_Check(src_.ptr()))
return false;
/*
When passing a C++ function as an argument to another C++
function via Python, every function call would normally involve
a full C++ -> Python -> C++ roundtrip, which can be prohibitive.
Here, we try to at least detect the case where the function is
stateless (i.e. function pointer or lambda function without
captured variables), in which case the roundtrip can be avoided.
*/
if (PyCFunction_Check(src_.ptr())) {
auto c = reinterpret_borrow<capsule>(PyCFunction_GetSelf(src_.ptr()));
auto rec = (function_record *) c;
using FunctionType = Return (*) (Args...);
if (rec && rec->is_stateless && rec->data[1] == &typeid(FunctionType)) {
struct capture { FunctionType f; };
value = ((capture *) &rec->data)->f;
return true;
}
}
auto src = reinterpret_borrow<object>(src_);
value = [src](Args... args) -> Return {
gil_scoped_acquire acq;
object retval(src(std::move(args)...));
/* Visual studio 2015 parser issue: need parentheses around this expression */
return (retval.template cast<Return>());
};
return true;
}
template <typename Func>
static handle cast(Func &&f_, return_value_policy policy, handle /* parent */) {
if (!f_)
return none().inc_ref();
auto result = f_.template target<Return (*)(Args...)>();
if (result)
return cpp_function(*result, policy).release();
else
return cpp_function(std::forward<Func>(f_), policy).release();
}
PYBIND11_TYPE_CASTER(type, _("Callable[[") +
argument_loader<Args...>::arg_names() + _("], ") +
type_caster<retval_type>::name() +
_("]"));
};
NAMESPACE_END(detail)
NAMESPACE_END(pybind11)

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resources/pybind11/include/pybind11/numpy.h
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/*
pybind11/operator.h: Metatemplates for operator overloading
Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#pragma once
#include "pybind11.h"
#if defined(__clang__) && !defined(__INTEL_COMPILER)
# pragma clang diagnostic ignored "-Wunsequenced" // multiple unsequenced modifications to 'self' (when using def(py::self OP Type()))
#endif
NAMESPACE_BEGIN(pybind11)
NAMESPACE_BEGIN(detail)
/// Enumeration with all supported operator types
enum op_id : int {
op_add, op_sub, op_mul, op_div, op_mod, op_divmod, op_pow, op_lshift,
op_rshift, op_and, op_xor, op_or, op_neg, op_pos, op_abs, op_invert,
op_int, op_long, op_float, op_str, op_cmp, op_gt, op_ge, op_lt, op_le,
op_eq, op_ne, op_iadd, op_isub, op_imul, op_idiv, op_imod, op_ilshift,
op_irshift, op_iand, op_ixor, op_ior, op_complex, op_bool, op_nonzero,
op_repr, op_truediv
};
enum op_type : int {
op_l, /* base type on left */
op_r, /* base type on right */
op_u /* unary operator */
};
struct self_t { };
static const self_t self = self_t();
/// Type for an unused type slot
struct undefined_t { };
/// Don't warn about an unused variable
inline self_t __self() { return self; }
/// base template of operator implementations
template <op_id, op_type, typename B, typename L, typename R> struct op_impl { };
/// Operator implementation generator
template <op_id id, op_type ot, typename L, typename R> struct op_ {
template <typename Class, typename... Extra> void execute(Class &cl, const Extra&... extra) const {
typedef typename Class::type Base;
typedef typename std::conditional<std::is_same<L, self_t>::value, Base, L>::type L_type;
typedef typename std::conditional<std::is_same<R, self_t>::value, Base, R>::type R_type;
typedef op_impl<id, ot, Base, L_type, R_type> op;
cl.def(op::name(), &op::execute, is_operator(), extra...);
}
template <typename Class, typename... Extra> void execute_cast(Class &cl, const Extra&... extra) const {
typedef typename Class::type Base;
typedef typename std::conditional<std::is_same<L, self_t>::value, Base, L>::type L_type;
typedef typename std::conditional<std::is_same<R, self_t>::value, Base, R>::type R_type;
typedef op_impl<id, ot, Base, L_type, R_type> op;
cl.def(op::name(), &op::execute_cast, is_operator(), extra...);
}
};
#define PYBIND11_BINARY_OPERATOR(id, rid, op, expr) \
template <typename B, typename L, typename R> struct op_impl<op_##id, op_l, B, L, R> { \
static char const* name() { return "__" #id "__"; } \
static auto execute(const L &l, const R &r) -> decltype(expr) { return (expr); } \
static B execute_cast(const L &l, const R &r) { return B(expr); } \
}; \
template <typename B, typename L, typename R> struct op_impl<op_##id, op_r, B, L, R> { \
static char const* name() { return "__" #rid "__"; } \
static auto execute(const R &r, const L &l) -> decltype(expr) { return (expr); } \
static B execute_cast(const R &r, const L &l) { return B(expr); } \
}; \
inline op_<op_##id, op_l, self_t, self_t> op(const self_t &, const self_t &) { \
return op_<op_##id, op_l, self_t, self_t>(); \
} \
template <typename T> op_<op_##id, op_l, self_t, T> op(const self_t &, const T &) { \
return op_<op_##id, op_l, self_t, T>(); \
} \
template <typename T> op_<op_##id, op_r, T, self_t> op(const T &, const self_t &) { \
return op_<op_##id, op_r, T, self_t>(); \
}
#define PYBIND11_INPLACE_OPERATOR(id, op, expr) \
template <typename B, typename L, typename R> struct op_impl<op_##id, op_l, B, L, R> { \
static char const* name() { return "__" #id "__"; } \
static auto execute(L &l, const R &r) -> decltype(expr) { return expr; } \
static B execute_cast(L &l, const R &r) { return B(expr); } \
}; \
template <typename T> op_<op_##id, op_l, self_t, T> op(const self_t &, const T &) { \
return op_<op_##id, op_l, self_t, T>(); \
}
#define PYBIND11_UNARY_OPERATOR(id, op, expr) \
template <typename B, typename L> struct op_impl<op_##id, op_u, B, L, undefined_t> { \
static char const* name() { return "__" #id "__"; } \
static auto execute(const L &l) -> decltype(expr) { return expr; } \
static B execute_cast(const L &l) { return B(expr); } \
}; \
inline op_<op_##id, op_u, self_t, undefined_t> op(const self_t &) { \
return op_<op_##id, op_u, self_t, undefined_t>(); \
}
PYBIND11_BINARY_OPERATOR(sub, rsub, operator-, l - r)
PYBIND11_BINARY_OPERATOR(add, radd, operator+, l + r)
PYBIND11_BINARY_OPERATOR(mul, rmul, operator*, l * r)
#if PY_MAJOR_VERSION >= 3
PYBIND11_BINARY_OPERATOR(truediv, rtruediv, operator/, l / r)
#else
PYBIND11_BINARY_OPERATOR(div, rdiv, operator/, l / r)
#endif
PYBIND11_BINARY_OPERATOR(mod, rmod, operator%, l % r)
PYBIND11_BINARY_OPERATOR(lshift, rlshift, operator<<, l << r)
PYBIND11_BINARY_OPERATOR(rshift, rrshift, operator>>, l >> r)
PYBIND11_BINARY_OPERATOR(and, rand, operator&, l & r)
PYBIND11_BINARY_OPERATOR(xor, rxor, operator^, l ^ r)
PYBIND11_BINARY_OPERATOR(eq, eq, operator==, l == r)
PYBIND11_BINARY_OPERATOR(ne, ne, operator!=, l != r)
PYBIND11_BINARY_OPERATOR(or, ror, operator|, l | r)
PYBIND11_BINARY_OPERATOR(gt, lt, operator>, l > r)
PYBIND11_BINARY_OPERATOR(ge, le, operator>=, l >= r)
PYBIND11_BINARY_OPERATOR(lt, gt, operator<, l < r)
PYBIND11_BINARY_OPERATOR(le, ge, operator<=, l <= r)
//PYBIND11_BINARY_OPERATOR(pow, rpow, pow, std::pow(l, r))
PYBIND11_INPLACE_OPERATOR(iadd, operator+=, l += r)
PYBIND11_INPLACE_OPERATOR(isub, operator-=, l -= r)
PYBIND11_INPLACE_OPERATOR(imul, operator*=, l *= r)
PYBIND11_INPLACE_OPERATOR(idiv, operator/=, l /= r)
PYBIND11_INPLACE_OPERATOR(imod, operator%=, l %= r)
PYBIND11_INPLACE_OPERATOR(ilshift, operator<<=, l <<= r)
PYBIND11_INPLACE_OPERATOR(irshift, operator>>=, l >>= r)
PYBIND11_INPLACE_OPERATOR(iand, operator&=, l &= r)
PYBIND11_INPLACE_OPERATOR(ixor, operator^=, l ^= r)
PYBIND11_INPLACE_OPERATOR(ior, operator|=, l |= r)
PYBIND11_UNARY_OPERATOR(neg, operator-, -l)
PYBIND11_UNARY_OPERATOR(pos, operator+, +l)
PYBIND11_UNARY_OPERATOR(abs, abs, std::abs(l))
PYBIND11_UNARY_OPERATOR(invert, operator~, (~l))
PYBIND11_UNARY_OPERATOR(bool, operator!, !!l)
PYBIND11_UNARY_OPERATOR(int, int_, (int) l)
PYBIND11_UNARY_OPERATOR(float, float_, (double) l)
#undef PYBIND11_BINARY_OPERATOR
#undef PYBIND11_INPLACE_OPERATOR
#undef PYBIND11_UNARY_OPERATOR
NAMESPACE_END(detail)
using detail::self;
NAMESPACE_END(pybind11)

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resources/pybind11/include/pybind11/options.h

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/*
pybind11/options.h: global settings that are configurable at runtime.
Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#pragma once
#include "common.h"
NAMESPACE_BEGIN(pybind11)
class options {
public:
// Default RAII constructor, which leaves settings as they currently are.
options() : previous_state(global_state()) {}
// Class is non-copyable.
options(const options&) = delete;
options& operator=(const options&) = delete;
// Destructor, which restores settings that were in effect before.
~options() {
global_state() = previous_state;
}
// Setter methods (affect the global state):
options& disable_user_defined_docstrings() & { global_state().show_user_defined_docstrings = false; return *this; }
options& enable_user_defined_docstrings() & { global_state().show_user_defined_docstrings = true; return *this; }
options& disable_function_signatures() & { global_state().show_function_signatures = false; return *this; }
options& enable_function_signatures() & { global_state().show_function_signatures = true; return *this; }
// Getter methods (return the global state):
static bool show_user_defined_docstrings() { return global_state().show_user_defined_docstrings; }
static bool show_function_signatures() { return global_state().show_function_signatures; }
// This type is not meant to be allocated on the heap.
void* operator new(size_t) = delete;
private:
struct state {
bool show_user_defined_docstrings = true; //< Include user-supplied texts in docstrings.
bool show_function_signatures = true; //< Include auto-generated function signatures in docstrings.
};
static state &global_state() {
static state instance;
return instance;
}
state previous_state;
};
NAMESPACE_END(pybind11)

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resources/pybind11/include/pybind11/pybind11.h
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resources/pybind11/include/pybind11/pytypes.h

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/*
pybind11/typeid.h: Convenience wrapper classes for basic Python types
Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#pragma once
#include "common.h"
#include <utility>
#include <type_traits>
NAMESPACE_BEGIN(pybind11)
/* A few forward declarations */
class handle; class object;
class str; class iterator;
struct arg; struct arg_v;
NAMESPACE_BEGIN(detail)
class args_proxy;
inline bool isinstance_generic(handle obj, const std::type_info &tp);
// Accessor forward declarations
template <typename Policy> class accessor;
namespace accessor_policies {
struct obj_attr;
struct str_attr;
struct generic_item;
struct sequence_item;
struct list_item;
struct tuple_item;
}
using obj_attr_accessor = accessor<accessor_policies::obj_attr>;
using str_attr_accessor = accessor<accessor_policies::str_attr>;
using item_accessor = accessor<accessor_policies::generic_item>;
using sequence_accessor = accessor<accessor_policies::sequence_item>;
using list_accessor = accessor<accessor_policies::list_item>;
using tuple_accessor = accessor<accessor_policies::tuple_item>;
/// Tag and check to identify a class which implements the Python object API
class pyobject_tag { };
template <typename T> using is_pyobject = std::is_base_of<pyobject_tag, T>;
/// Mixin which adds common functions to handle, object and various accessors.
/// The only requirement for `Derived` is to implement `PyObject *Derived::ptr() const`.
template <typename Derived>
class object_api : public pyobject_tag {
const Derived &derived() const { return static_cast<const Derived &>(*this); }
public:
iterator begin() const;
iterator end() const;
item_accessor operator[](handle key) const;
item_accessor operator[](const char *key) const;
obj_attr_accessor attr(handle key) const;
str_attr_accessor attr(const char *key) const;
args_proxy operator*() const;
template <typename T> bool contains(T &&key) const;
template <return_value_policy policy = return_value_policy::automatic_reference, typename... Args>
object operator()(Args &&...args) const;
template <return_value_policy policy = return_value_policy::automatic_reference, typename... Args>
PYBIND11_DEPRECATED("call(...) was deprecated in favor of operator()(...)")
object call(Args&&... args) const;
bool is_none() const { return derived().ptr() == Py_None; }
PYBIND11_DEPRECATED("Instead of obj.str(), use py::str(obj)")
pybind11::str str() const;
int ref_count() const { return static_cast<int>(Py_REFCNT(derived().ptr())); }
handle get_type() const;
};
NAMESPACE_END(detail)
/// Holds a reference to a Python object (no reference counting)
class handle : public detail::object_api<handle> {
public:
handle() = default;
handle(PyObject *ptr) : m_ptr(ptr) { }
PyObject *ptr() const { return m_ptr; }
PyObject *&ptr() { return m_ptr; }
const handle& inc_ref() const { Py_XINCREF(m_ptr); return *this; }
const handle& dec_ref() const { Py_XDECREF(m_ptr); return *this; }
template <typename T> T cast() const;
explicit operator bool() const { return m_ptr != nullptr; }
bool operator==(const handle &h) const { return m_ptr == h.m_ptr; }
bool operator!=(const handle &h) const { return m_ptr != h.m_ptr; }
PYBIND11_DEPRECATED("Use handle::operator bool() instead")
bool check() const { return m_ptr != nullptr; }
protected:
PyObject *m_ptr = nullptr;
};
/// Holds a reference to a Python object (with reference counting)
class object : public handle {
public:
object() = default;
PYBIND11_DEPRECATED("Use reinterpret_borrow<object>() or reinterpret_steal<object>()")
object(handle h, bool is_borrowed) : handle(h) { if (is_borrowed) inc_ref(); }
object(const object &o) : handle(o) { inc_ref(); }
object(object &&other) noexcept { m_ptr = other.m_ptr; other.m_ptr = nullptr; }
~object() { dec_ref(); }
handle release() {
PyObject *tmp = m_ptr;
m_ptr = nullptr;
return handle(tmp);
}
object& operator=(const object &other) {
other.inc_ref();
dec_ref();
m_ptr = other.m_ptr;
return *this;
}
object& operator=(object &&other) noexcept {
if (this != &other) {
handle temp(m_ptr);
m_ptr = other.m_ptr;
other.m_ptr = nullptr;
temp.dec_ref();
}
return *this;
}
// Calling cast() on an object lvalue just copies (via handle::cast)
template <typename T> T cast() const &;
// Calling on an object rvalue does a move, if needed and/or possible
template <typename T> T cast() &&;
protected:
// Tags for choosing constructors from raw PyObject *
struct borrowed_t { }; static constexpr borrowed_t borrowed{};
struct stolen_t { }; static constexpr stolen_t stolen{};
template <typename T> friend T reinterpret_borrow(handle);
template <typename T> friend T reinterpret_steal(handle);
public:
// Only accessible from derived classes and the reinterpret_* functions
object(handle h, borrowed_t) : handle(h) { inc_ref(); }
object(handle h, stolen_t) : handle(h) { }
};
/** The following functions don't do any kind of conversion, they simply declare
that a PyObject is a certain type and borrow or steal the reference. */
template <typename T> T reinterpret_borrow(handle h) { return {h, object::borrowed}; }
template <typename T> T reinterpret_steal(handle h) { return {h, object::stolen}; }
/// Check if `obj` is an instance of type `T`
template <typename T, detail::enable_if_t<std::is_base_of<object, T>::value, int> = 0>
bool isinstance(handle obj) { return T::_check(obj); }
template <typename T, detail::enable_if_t<!std::is_base_of<object, T>::value, int> = 0>
bool isinstance(handle obj) { return detail::isinstance_generic(obj, typeid(T)); }
template <> inline bool isinstance<handle>(handle obj) = delete;
template <> inline bool isinstance<object>(handle obj) { return obj.ptr() != nullptr; }
inline bool hasattr(handle obj, handle name) {
return PyObject_HasAttr(obj.ptr(), name.ptr()) == 1;
}
inline bool hasattr(handle obj, const char *name) {
return PyObject_HasAttrString(obj.ptr(), name) == 1;
}
inline object getattr(handle obj, handle name) {
PyObject *result = PyObject_GetAttr(obj.ptr(), name.ptr());
if (!result) { throw error_already_set(); }
return reinterpret_steal<object>(result);
}
inline object getattr(handle obj, const char *name) {
PyObject *result = PyObject_GetAttrString(obj.ptr(), name);
if (!result) { throw error_already_set(); }
return reinterpret_steal<object>(result);
}
inline object getattr(handle obj, handle name, handle default_) {
if (PyObject *result = PyObject_GetAttr(obj.ptr(), name.ptr())) {
return reinterpret_steal<object>(result);
} else {
PyErr_Clear();
return reinterpret_borrow<object>(default_);
}
}
inline object getattr(handle obj, const char *name, handle default_) {
if (PyObject *result = PyObject_GetAttrString(obj.ptr(), name)) {
return reinterpret_steal<object>(result);
} else {
PyErr_Clear();
return reinterpret_borrow<object>(default_);
}
}
inline void setattr(handle obj, handle name, handle value) {
if (PyObject_SetAttr(obj.ptr(), name.ptr(), value.ptr()) != 0) { throw error_already_set(); }
}
inline void setattr(handle obj, const char *name, handle value) {
if (PyObject_SetAttrString(obj.ptr(), name, value.ptr()) != 0) { throw error_already_set(); }
}
NAMESPACE_BEGIN(detail)
inline handle get_function(handle value) {
if (value) {
#if PY_MAJOR_VERSION >= 3
if (PyInstanceMethod_Check(value.ptr()))
value = PyInstanceMethod_GET_FUNCTION(value.ptr());
#endif
if (PyMethod_Check(value.ptr()))
value = PyMethod_GET_FUNCTION(value.ptr());
}
return value;
}
template <typename Policy>
class accessor : public object_api<accessor<Policy>> {
using key_type = typename Policy::key_type;
public:
accessor(handle obj, key_type key) : obj(obj), key(std::move(key)) { }
void operator=(const accessor &a) && { std::move(*this).operator=(handle(a)); }
void operator=(const accessor &a) & { operator=(handle(a)); }
void operator=(const object &o) && { std::move(*this).operator=(handle(o)); }
void operator=(const object &o) & { operator=(handle(o)); }
void operator=(handle value) && { Policy::set(obj, key, value); }
void operator=(handle value) & { get_cache() = reinterpret_borrow<object>(value); }
template <typename T = Policy>
PYBIND11_DEPRECATED("Use of obj.attr(...) as bool is deprecated in favor of pybind11::hasattr(obj, ...)")
explicit operator enable_if_t<std::is_same<T, accessor_policies::str_attr>::value ||
std::is_same<T, accessor_policies::obj_attr>::value, bool>() const {
return hasattr(obj, key);
}
template <typename T = Policy>
PYBIND11_DEPRECATED("Use of obj[key] as bool is deprecated in favor of obj.contains(key)")
explicit operator enable_if_t<std::is_same<T, accessor_policies::generic_item>::value, bool>() const {
return obj.contains(key);
}
operator object() const { return get_cache(); }
PyObject *ptr() const { return get_cache().ptr(); }
template <typename T> T cast() const { return get_cache().template cast<T>(); }
private:
object &get_cache() const {
if (!cache) { cache = Policy::get(obj, key); }
return cache;
}
private:
handle obj;
key_type key;
mutable object cache;
};
NAMESPACE_BEGIN(accessor_policies)
struct obj_attr {
using key_type = object;
static object get(handle obj, handle key) { return getattr(obj, key); }
static void set(handle obj, handle key, handle val) { setattr(obj, key, val); }
};
struct str_attr {
using key_type = const char *;
static object get(handle obj, const char *key) { return getattr(obj, key); }
static void set(handle obj, const char *key, handle val) { setattr(obj, key, val); }
};
struct generic_item {
using key_type = object;
static object get(handle obj, handle key) {
PyObject *result = PyObject_GetItem(obj.ptr(), key.ptr());
if (!result) { throw error_already_set(); }
return reinterpret_steal<object>(result);
}
static void set(handle obj, handle key, handle val) {
if (PyObject_SetItem(obj.ptr(), key.ptr(), val.ptr()) != 0) { throw error_already_set(); }
}
};
struct sequence_item {
using key_type = size_t;
static object get(handle obj, size_t index) {
PyObject *result = PySequence_GetItem(obj.ptr(), static_cast<ssize_t>(index));
if (!result) { throw error_already_set(); }
return reinterpret_borrow<object>(result);
}
static void set(handle obj, size_t index, handle val) {
// PySequence_SetItem does not steal a reference to 'val'
if (PySequence_SetItem(obj.ptr(), static_cast<ssize_t>(index), val.ptr()) != 0) {
throw error_already_set();
}
}
};
struct list_item {
using key_type = size_t;
static object get(handle obj, size_t index) {
PyObject *result = PyList_GetItem(obj.ptr(), static_cast<ssize_t>(index));
if (!result) { throw error_already_set(); }
return reinterpret_borrow<object>(result);
}
static void set(handle obj, size_t index, handle val) {
// PyList_SetItem steals a reference to 'val'
if (PyList_SetItem(obj.ptr(), static_cast<ssize_t>(index), val.inc_ref().ptr()) != 0) {
throw error_already_set();
}
}
};
struct tuple_item {
using key_type = size_t;
static object get(handle obj, size_t index) {
PyObject *result = PyTuple_GetItem(obj.ptr(), static_cast<ssize_t>(index));
if (!result) { throw error_already_set(); }
return reinterpret_borrow<object>(result);
}
static void set(handle obj, size_t index, handle val) {
// PyTuple_SetItem steals a reference to 'val'
if (PyTuple_SetItem(obj.ptr(), static_cast<ssize_t>(index), val.inc_ref().ptr()) != 0) {
throw error_already_set();
}
}
};
NAMESPACE_END(accessor_policies)
struct dict_iterator {
public:
explicit dict_iterator(handle dict = handle(), ssize_t pos = -1) : dict(dict), pos(pos) { }
dict_iterator& operator++() {
if (!PyDict_Next(dict.ptr(), &pos, &key.ptr(), &value.ptr()))
pos = -1;
return *this;
}
std::pair<handle, handle> operator*() const {
return std::make_pair(key, value);
}
bool operator==(const dict_iterator &it) const { return it.pos == pos; }
bool operator!=(const dict_iterator &it) const { return it.pos != pos; }
private:
handle dict, key, value;
ssize_t pos = 0;
};
inline bool PyIterable_Check(PyObject *obj) {
PyObject *iter = PyObject_GetIter(obj);
if (iter) {
Py_DECREF(iter);
return true;
} else {
PyErr_Clear();
return false;
}
}
inline bool PyNone_Check(PyObject *o) { return o == Py_None; }
inline bool PyUnicode_Check_Permissive(PyObject *o) { return PyUnicode_Check(o) || PYBIND11_BYTES_CHECK(o); }
class kwargs_proxy : public handle {
public:
explicit kwargs_proxy(handle h) : handle(h) { }
};
class args_proxy : public handle {
public:
explicit args_proxy(handle h) : handle(h) { }
kwargs_proxy operator*() const { return kwargs_proxy(*this); }
};
/// Python argument categories (using PEP 448 terms)
template <typename T> using is_keyword = std::is_base_of<arg, T>;
template <typename T> using is_s_unpacking = std::is_same<args_proxy, T>; // * unpacking
template <typename T> using is_ds_unpacking = std::is_same<kwargs_proxy, T>; // ** unpacking
template <typename T> using is_positional = bool_constant<
!is_keyword<T>::value && !is_s_unpacking<T>::value && !is_ds_unpacking<T>::value
>;
template <typename T> using is_keyword_or_ds = bool_constant<
is_keyword<T>::value || is_ds_unpacking<T>::value
>;
// Call argument collector forward declarations
template <return_value_policy policy = return_value_policy::automatic_reference>
class simple_collector;
template <return_value_policy policy = return_value_policy::automatic_reference>
class unpacking_collector;
NAMESPACE_END(detail)
// TODO: After the deprecated constructors are removed, this macro can be simplified by
// inheriting ctors: `using Parent::Parent`. It's not an option right now because
// the `using` statement triggers the parent deprecation warning even if the ctor
// isn't even used.
#define PYBIND11_OBJECT_COMMON(Name, Parent, CheckFun) \
public: \
PYBIND11_DEPRECATED("Use reinterpret_borrow<"#Name">() or reinterpret_steal<"#Name">()") \
Name(handle h, bool is_borrowed) : Parent(is_borrowed ? Parent(h, borrowed) : Parent(h, stolen)) { } \
Name(handle h, borrowed_t) : Parent(h, borrowed) { } \
Name(handle h, stolen_t) : Parent(h, stolen) { } \
PYBIND11_DEPRECATED("Use py::isinstance<py::python_type>(obj) instead") \
bool check() const { return m_ptr != nullptr && (bool) CheckFun(m_ptr); } \
static bool _check(handle h) { return h.ptr() != nullptr && CheckFun(h.ptr()); }
#define PYBIND11_OBJECT_CVT(Name, Parent, CheckFun, ConvertFun) \
PYBIND11_OBJECT_COMMON(Name, Parent, CheckFun) \
/* This is deliberately not 'explicit' to allow implicit conversion from object: */ \
Name(const object &o) : Parent(ConvertFun(o.ptr()), stolen) { if (!m_ptr) throw error_already_set(); }
#define PYBIND11_OBJECT(Name, Parent, CheckFun) \
PYBIND11_OBJECT_COMMON(Name, Parent, CheckFun) \
/* This is deliberately not 'explicit' to allow implicit conversion from object: */ \
Name(const object &o) : Parent(o) { } \
Name(object &&o) : Parent(std::move(o)) { }
#define PYBIND11_OBJECT_DEFAULT(Name, Parent, CheckFun) \
PYBIND11_OBJECT(Name, Parent, CheckFun) \
Name() : Parent() { }
class iterator : public object {
public:
/** Caveat: copying an iterator does not (and cannot) clone the internal
state of the Python iterable */
PYBIND11_OBJECT_DEFAULT(iterator, object, PyIter_Check)
iterator& operator++() {
if (m_ptr)
advance();
return *this;
}
/** Caveat: this postincrement operator does not (and cannot) clone the
internal state of the Python iterable. It should only be used to
retrieve the current iterate using <tt>operator*()</tt> */
iterator operator++(int) {
iterator rv(*this);
rv.value = value;
if (m_ptr)
advance();
return rv;
}
bool operator==(const iterator &it) const { return *it == **this; }
bool operator!=(const iterator &it) const { return *it != **this; }
handle operator*() const {
if (!ready && m_ptr) {
auto& self = const_cast<iterator &>(*this);
self.advance();
self.ready = true;
}
return value;
}
private:
void advance() { value = reinterpret_steal<object>(PyIter_Next(m_ptr)); }
private:
object value = {};
bool ready = false;
};
class iterable : public object {
public:
PYBIND11_OBJECT_DEFAULT(iterable, object, detail::PyIterable_Check)
};
class bytes;
class str : public object {
public:
PYBIND11_OBJECT_CVT(str, object, detail::PyUnicode_Check_Permissive, raw_str)
str(const char *c, size_t n)
: object(PyUnicode_FromStringAndSize(c, (ssize_t) n), stolen) {
if (!m_ptr) pybind11_fail("Could not allocate string object!");
}
// 'explicit' is explicitly omitted from the following constructors to allow implicit conversion to py::str from C++ string-like objects
str(const char *c = "")
: object(PyUnicode_FromString(c), stolen) {
if (!m_ptr) pybind11_fail("Could not allocate string object!");
}
str(const std::string &s) : str(s.data(), s.size()) { }
explicit str(const bytes &b);
explicit str(handle h) : object(raw_str(h.ptr()), stolen) { }
operator std::string() const {
object temp = *this;
if (PyUnicode_Check(m_ptr)) {
temp = reinterpret_steal<object>(PyUnicode_AsUTF8String(m_ptr));
if (!temp)
pybind11_fail("Unable to extract string contents! (encoding issue)");
}
char *buffer;
ssize_t length;
if (PYBIND11_BYTES_AS_STRING_AND_SIZE(temp.ptr(), &buffer, &length))
pybind11_fail("Unable to extract string contents! (invalid type)");
return std::string(buffer, (size_t) length);
}
template <typename... Args>
str format(Args &&...args) const {
return attr("format")(std::forward<Args>(args)...);
}
private:
/// Return string representation -- always returns a new reference, even if already a str
static PyObject *raw_str(PyObject *op) {
PyObject *str_value = PyObject_Str(op);
#if PY_MAJOR_VERSION < 3
if (!str_value) throw error_already_set();
PyObject *unicode = PyUnicode_FromEncodedObject(str_value, "utf-8", nullptr);
Py_XDECREF(str_value); str_value = unicode;
#endif
return str_value;
}
};
inline namespace literals {
/// String literal version of str
inline str operator"" _s(const char *s, size_t size) { return {s, size}; }
}
class bytes : public object {
public:
PYBIND11_OBJECT(bytes, object, PYBIND11_BYTES_CHECK)
// Allow implicit conversion:
bytes(const char *c = "")
: object(PYBIND11_BYTES_FROM_STRING(c), stolen) {
if (!m_ptr) pybind11_fail("Could not allocate bytes object!");
}
bytes(const char *c, size_t n)
: object(PYBIND11_BYTES_FROM_STRING_AND_SIZE(c, (ssize_t) n), stolen) {
if (!m_ptr) pybind11_fail("Could not allocate bytes object!");
}
// Allow implicit conversion:
bytes(const std::string &s) : bytes(s.data(), s.size()) { }
explicit bytes(const pybind11::str &s);
operator std::string() const {
char *buffer;
ssize_t length;
if (PYBIND11_BYTES_AS_STRING_AND_SIZE(m_ptr, &buffer, &length))
pybind11_fail("Unable to extract bytes contents!");
return std::string(buffer, (size_t) length);
}
};
inline bytes::bytes(const pybind11::str &s) {
object temp = s;
if (PyUnicode_Check(s.ptr())) {
temp = reinterpret_steal<object>(PyUnicode_AsUTF8String(s.ptr()));
if (!temp)
pybind11_fail("Unable to extract string contents! (encoding issue)");
}
char *buffer;
ssize_t length;
if (PYBIND11_BYTES_AS_STRING_AND_SIZE(temp.ptr(), &buffer, &length))
pybind11_fail("Unable to extract string contents! (invalid type)");
auto obj = reinterpret_steal<object>(PYBIND11_BYTES_FROM_STRING_AND_SIZE(buffer, length));
if (!obj)
pybind11_fail("Could not allocate bytes object!");
m_ptr = obj.release().ptr();
}
inline str::str(const bytes& b) {
char *buffer;
ssize_t length;
if (PYBIND11_BYTES_AS_STRING_AND_SIZE(b.ptr(), &buffer, &length))
pybind11_fail("Unable to extract bytes contents!");
auto obj = reinterpret_steal<object>(PyUnicode_FromStringAndSize(buffer, (ssize_t) length));
if (!obj)
pybind11_fail("Could not allocate string object!");
m_ptr = obj.release().ptr();
}
class none : public object {
public:
PYBIND11_OBJECT(none, object, detail::PyNone_Check)
none() : object(Py_None, borrowed) { }
};
class bool_ : public object {
public:
PYBIND11_OBJECT_CVT(bool_, object, PyBool_Check, raw_bool)
bool_() : object(Py_False, borrowed) { }
// Allow implicit conversion from and to `bool`:
bool_(bool value) : object(value ? Py_True : Py_False, borrowed) { }
operator bool() const { return m_ptr && PyLong_AsLong(m_ptr) != 0; }
private:
/// Return the truth value of an object -- always returns a new reference
static PyObject *raw_bool(PyObject *op) {
const auto value = PyObject_IsTrue(op);
if (value == -1) return nullptr;
return handle(value ? Py_True : Py_False).inc_ref().ptr();
}
};
class int_ : public object {
public:
PYBIND11_OBJECT_CVT(int_, object, PYBIND11_LONG_CHECK, PyNumber_Long)
int_() : object(PyLong_FromLong(0), stolen) { }
// Allow implicit conversion from C++ integral types:
template <typename T,
detail::enable_if_t<std::is_integral<T>::value, int> = 0>
int_(T value) {
if (sizeof(T) <= sizeof(long)) {
if (std::is_signed<T>::value)
m_ptr = PyLong_FromLong((long) value);
else
m_ptr = PyLong_FromUnsignedLong((unsigned long) value);
} else {
if (std::is_signed<T>::value)
m_ptr = PyLong_FromLongLong((long long) value);
else
m_ptr = PyLong_FromUnsignedLongLong((unsigned long long) value);
}
if (!m_ptr) pybind11_fail("Could not allocate int object!");
}
template <typename T,
detail::enable_if_t<std::is_integral<T>::value, int> = 0>
operator T() const {
if (sizeof(T) <= sizeof(long)) {
if (std::is_signed<T>::value)
return (T) PyLong_AsLong(m_ptr);
else
return (T) PyLong_AsUnsignedLong(m_ptr);
} else {
if (std::is_signed<T>::value)
return (T) PYBIND11_LONG_AS_LONGLONG(m_ptr);
else
return (T) PYBIND11_LONG_AS_UNSIGNED_LONGLONG(m_ptr);
}
}
};
class float_ : public object {
public:
PYBIND11_OBJECT_CVT(float_, object, PyFloat_Check, PyNumber_Float)
// Allow implicit conversion from float/double:
float_(float value) : object(PyFloat_FromDouble((double) value), stolen) {
if (!m_ptr) pybind11_fail("Could not allocate float object!");
}
float_(double value = .0) : object(PyFloat_FromDouble((double) value), stolen) {
if (!m_ptr) pybind11_fail("Could not allocate float object!");
}
operator float() const { return (float) PyFloat_AsDouble(m_ptr); }
operator double() const { return (double) PyFloat_AsDouble(m_ptr); }
};
class weakref : public object {
public:
PYBIND11_OBJECT_DEFAULT(weakref, object, PyWeakref_Check)
explicit weakref(handle obj, handle callback = {})
: object(PyWeakref_NewRef(obj.ptr(), callback.ptr()), stolen) {
if (!m_ptr) pybind11_fail("Could not allocate weak reference!");
}
};
class slice : public object {
public:
PYBIND11_OBJECT_DEFAULT(slice, object, PySlice_Check)
slice(ssize_t start_, ssize_t stop_, ssize_t step_) {
int_ start(start_), stop(stop_), step(step_);
m_ptr = PySlice_New(start.ptr(), stop.ptr(), step.ptr());
if (!m_ptr) pybind11_fail("Could not allocate slice object!");
}
bool compute(size_t length, size_t *start, size_t *stop, size_t *step,
size_t *slicelength) const {
return PySlice_GetIndicesEx((PYBIND11_SLICE_OBJECT *) m_ptr,
(ssize_t) length, (ssize_t *) start,
(ssize_t *) stop, (ssize_t *) step,
(ssize_t *) slicelength) == 0;
}
};
class capsule : public object {
public:
PYBIND11_OBJECT_DEFAULT(capsule, object, PyCapsule_CheckExact)
PYBIND11_DEPRECATED("Use reinterpret_borrow<capsule>() or reinterpret_steal<capsule>()")
capsule(PyObject *ptr, bool is_borrowed) : object(is_borrowed ? object(ptr, borrowed) : object(ptr, stolen)) { }
explicit capsule(const void *value, void (*destruct)(PyObject *) = nullptr)
: object(PyCapsule_New(const_cast<void*>(value), nullptr, destruct), stolen) {
if (!m_ptr) pybind11_fail("Could not allocate capsule object!");
}
template <typename T> operator T *() const {
T * result = static_cast<T *>(PyCapsule_GetPointer(m_ptr, nullptr));
if (!result) pybind11_fail("Unable to extract capsule contents!");
return result;
}
};
class tuple : public object {
public:
PYBIND11_OBJECT_CVT(tuple, object, PyTuple_Check, PySequence_Tuple)
explicit tuple(size_t size = 0) : object(PyTuple_New((ssize_t) size), stolen) {
if (!m_ptr) pybind11_fail("Could not allocate tuple object!");
}
size_t size() const { return (size_t) PyTuple_Size(m_ptr); }
detail::tuple_accessor operator[](size_t index) const { return {*this, index}; }
};
class dict : public object {
public:
PYBIND11_OBJECT_CVT(dict, object, PyDict_Check, raw_dict)
dict() : object(PyDict_New(), stolen) {
if (!m_ptr) pybind11_fail("Could not allocate dict object!");
}
template <typename... Args,
typename = detail::enable_if_t<detail::all_of_t<detail::is_keyword_or_ds, Args...>::value>,
// MSVC workaround: it can't compile an out-of-line definition, so defer the collector
typename collector = detail::deferred_t<detail::unpacking_collector<>, Args...>>
explicit dict(Args &&...args) : dict(collector(std::forward<Args>(args)...).kwargs()) { }
size_t size() const { return (size_t) PyDict_Size(m_ptr); }
detail::dict_iterator begin() const { return (++detail::dict_iterator(*this, 0)); }
detail::dict_iterator end() const { return detail::dict_iterator(); }
void clear() const { PyDict_Clear(ptr()); }
bool contains(handle key) const { return PyDict_Contains(ptr(), key.ptr()) == 1; }
bool contains(const char *key) const { return PyDict_Contains(ptr(), pybind11::str(key).ptr()) == 1; }
private:
/// Call the `dict` Python type -- always returns a new reference
static PyObject *raw_dict(PyObject *op) {
if (PyDict_Check(op))
return handle(op).inc_ref().ptr();
return PyObject_CallFunctionObjArgs((PyObject *) &PyDict_Type, op, nullptr);
}
};
class sequence : public object {
public:
PYBIND11_OBJECT(sequence, object, PySequence_Check)
size_t size() const { return (size_t) PySequence_Size(m_ptr); }
detail::sequence_accessor operator[](size_t index) const { return {*this, index}; }
};
class list : public object {
public:
PYBIND11_OBJECT_CVT(list, object, PyList_Check, PySequence_List)
explicit list(size_t size = 0) : object(PyList_New((ssize_t) size), stolen) {
if (!m_ptr) pybind11_fail("Could not allocate list object!");
}
size_t size() const { return (size_t) PyList_Size(m_ptr); }
detail::list_accessor operator[](size_t index) const { return {*this, index}; }
void append(handle h) const { PyList_Append(m_ptr, h.ptr()); }
};
class args : public tuple { PYBIND11_OBJECT_DEFAULT(args, tuple, PyTuple_Check) };
class kwargs : public dict { PYBIND11_OBJECT_DEFAULT(kwargs, dict, PyDict_Check) };
class set : public object {
public:
PYBIND11_OBJECT_CVT(set, object, PySet_Check, PySet_New)
set() : object(PySet_New(nullptr), stolen) {
if (!m_ptr) pybind11_fail("Could not allocate set object!");
}
size_t size() const { return (size_t) PySet_Size(m_ptr); }
bool add(const object &object) const { return PySet_Add(m_ptr, object.ptr()) == 0; }
void clear() const { PySet_Clear(m_ptr); }
};
class function : public object {
public:
PYBIND11_OBJECT_DEFAULT(function, object, PyCallable_Check)
bool is_cpp_function() const {
handle fun = detail::get_function(m_ptr);
return fun && PyCFunction_Check(fun.ptr());
}
};
class buffer : public object {
public:
PYBIND11_OBJECT_DEFAULT(buffer, object, PyObject_CheckBuffer)
buffer_info request(bool writable = false) {
int flags = PyBUF_STRIDES | PyBUF_FORMAT;
if (writable) flags |= PyBUF_WRITABLE;
Py_buffer *view = new Py_buffer();
if (PyObject_GetBuffer(m_ptr, view, flags) != 0)
throw error_already_set();
return buffer_info(view);
}
};
class memoryview : public object {
public:
explicit memoryview(const buffer_info& info) {
static Py_buffer buf { };
// Py_buffer uses signed sizes, strides and shape!..
static std::vector<Py_ssize_t> py_strides { };
static std::vector<Py_ssize_t> py_shape { };
buf.buf = info.ptr;
buf.itemsize = (Py_ssize_t) info.itemsize;
buf.format = const_cast<char *>(info.format.c_str());
buf.ndim = (int) info.ndim;
buf.len = (Py_ssize_t) info.size;
py_strides.clear();
py_shape.clear();
for (size_t i = 0; i < info.ndim; ++i) {
py_strides.push_back((Py_ssize_t) info.strides[i]);
py_shape.push_back((Py_ssize_t) info.shape[i]);
}
buf.strides = py_strides.data();
buf.shape = py_shape.data();
buf.suboffsets = nullptr;
buf.readonly = false;
buf.internal = nullptr;
m_ptr = PyMemoryView_FromBuffer(&buf);
if (!m_ptr)
pybind11_fail("Unable to create memoryview from buffer descriptor");
}
PYBIND11_OBJECT_CVT(memoryview, object, PyMemoryView_Check, PyMemoryView_FromObject)
};
inline size_t len(handle h) {
ssize_t result = PyObject_Length(h.ptr());
if (result < 0)
pybind11_fail("Unable to compute length of object");
return (size_t) result;
}
inline str repr(handle h) {
PyObject *str_value = PyObject_Repr(h.ptr());
if (!str_value) throw error_already_set();
#if PY_MAJOR_VERSION < 3
PyObject *unicode = PyUnicode_FromEncodedObject(str_value, "utf-8", nullptr);
Py_XDECREF(str_value); str_value = unicode;
if (!str_value) throw error_already_set();
#endif
return reinterpret_steal<str>(str_value);
}
NAMESPACE_BEGIN(detail)
template <typename D> iterator object_api<D>::begin() const {
return reinterpret_steal<iterator>(PyObject_GetIter(derived().ptr()));
}
template <typename D> iterator object_api<D>::end() const {
return {};
}
template <typename D> item_accessor object_api<D>::operator[](handle key) const {
return {derived(), reinterpret_borrow<object>(key)};
}
template <typename D> item_accessor object_api<D>::operator[](const char *key) const {
return {derived(), pybind11::str(key)};
}
template <typename D> obj_attr_accessor object_api<D>::attr(handle key) const {
return {derived(), reinterpret_borrow<object>(key)};
}
template <typename D> str_attr_accessor object_api<D>::attr(const char *key) const {
return {derived(), key};
}
template <typename D> args_proxy object_api<D>::operator*() const {
return args_proxy(derived().ptr());
}
template <typename D> template <typename T> bool object_api<D>::contains(T &&key) const {
return attr("__contains__")(std::forward<T>(key)).template cast<bool>();
}
template <typename D>
pybind11::str object_api<D>::str() const { return pybind11::str(derived()); }
template <typename D>
handle object_api<D>::get_type() const { return (PyObject *) Py_TYPE(derived().ptr()); }
NAMESPACE_END(detail)
NAMESPACE_END(pybind11)

256
resources/pybind11/include/pybind11/stl.h

@ -0,0 +1,256 @@
/*
pybind11/stl.h: Transparent conversion for STL data types
Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#pragma once
#include "pybind11.h"
#include <set>
#include <unordered_set>
#include <map>
#include <unordered_map>
#include <iostream>
#include <list>
#if defined(_MSC_VER)
#pragma warning(push)
#pragma warning(disable: 4127) // warning C4127: Conditional expression is constant
#endif
#ifdef __has_include
// std::optional (but including it in c++14 mode isn't allowed)
# if defined(PYBIND11_CPP17) && __has_include(<optional>)
# include <optional>
# define PYBIND11_HAS_OPTIONAL 1
# endif
// std::experimental::optional (but not allowed in c++11 mode)
# if defined(PYBIND11_CPP14) && __has_include(<experimental/optional>)
# include <experimental/optional>
# if __cpp_lib_experimental_optional // just in case
# define PYBIND11_HAS_EXP_OPTIONAL 1
# endif
# endif
#endif
NAMESPACE_BEGIN(pybind11)
NAMESPACE_BEGIN(detail)
template <typename Type, typename Key> struct set_caster {
using type = Type;
using key_conv = make_caster<Key>;
bool load(handle src, bool convert) {
if (!isinstance<pybind11::set>(src))
return false;
auto s = reinterpret_borrow<pybind11::set>(src);
value.clear();
key_conv conv;
for (auto entry : s) {
if (!conv.load(entry, convert))
return false;
value.insert(cast_op<Key>(conv));
}
return true;
}
static handle cast(const type &src, return_value_policy policy, handle parent) {
pybind11::set s;
for (auto const &value: src) {
auto value_ = reinterpret_steal<object>(key_conv::cast(value, policy, parent));
if (!value_ || !s.add(value_))
return handle();
}
return s.release();
}
PYBIND11_TYPE_CASTER(type, _("Set[") + key_conv::name() + _("]"));
};
template <typename Type, typename Key, typename Value> struct map_caster {
using type = Type;
using key_conv = make_caster<Key>;
using value_conv = make_caster<Value>;
bool load(handle src, bool convert) {
if (!isinstance<dict>(src))
return false;
auto d = reinterpret_borrow<dict>(src);
key_conv kconv;
value_conv vconv;
value.clear();
for (auto it : d) {
if (!kconv.load(it.first.ptr(), convert) ||
!vconv.load(it.second.ptr(), convert))
return false;
value.emplace(cast_op<Key>(kconv), cast_op<Value>(vconv));
}
return true;
}
static handle cast(const type &src, return_value_policy policy, handle parent) {
dict d;
for (auto const &kv: src) {
auto key = reinterpret_steal<object>(key_conv::cast(kv.first, policy, parent));
auto value = reinterpret_steal<object>(value_conv::cast(kv.second, policy, parent));
if (!key || !value)
return handle();
d[key] = value;
}
return d.release();
}
PYBIND11_TYPE_CASTER(type, _("Dict[") + key_conv::name() + _(", ") + value_conv::name() + _("]"));
};
template <typename Type, typename Value> struct list_caster {
using type = Type;
using value_conv = make_caster<Value>;
bool load(handle src, bool convert) {
if (!isinstance<sequence>(src))
return false;
auto s = reinterpret_borrow<sequence>(src);
value_conv conv;
value.clear();
reserve_maybe(s, &value);
for (auto it : s) {
if (!conv.load(it, convert))
return false;
value.push_back(cast_op<Value>(conv));
}
return true;
}
template <typename T = Type,
enable_if_t<std::is_same<decltype(std::declval<T>().reserve(0)), void>::value, int> = 0>
void reserve_maybe(sequence s, Type *) { value.reserve(s.size()); }
void reserve_maybe(sequence, void *) { }
static handle cast(const Type &src, return_value_policy policy, handle parent) {
list l(src.size());
size_t index = 0;
for (auto const &value: src) {
auto value_ = reinterpret_steal<object>(value_conv::cast(value, policy, parent));
if (!value_)
return handle();
PyList_SET_ITEM(l.ptr(), index++, value_.release().ptr()); // steals a reference
}
return l.release();
}
PYBIND11_TYPE_CASTER(Type, _("List[") + value_conv::name() + _("]"));
};
template <typename Type, typename Alloc> struct type_caster<std::vector<Type, Alloc>>
: list_caster<std::vector<Type, Alloc>, Type> { };
template <typename Type, typename Alloc> struct type_caster<std::list<Type, Alloc>>
: list_caster<std::list<Type, Alloc>, Type> { };
template <typename Type, size_t Size> struct type_caster<std::array<Type, Size>> {
using array_type = std::array<Type, Size>;
using value_conv = make_caster<Type>;
bool load(handle src, bool convert) {
if (!isinstance<list>(src))
return false;
auto l = reinterpret_borrow<list>(src);
if (l.size() != Size)
return false;
value_conv conv;
size_t ctr = 0;
for (auto it : l) {
if (!conv.load(it, convert))
return false;
value[ctr++] = cast_op<Type>(conv);
}
return true;
}
static handle cast(const array_type &src, return_value_policy policy, handle parent) {
list l(Size);
size_t index = 0;
for (auto const &value: src) {
auto value_ = reinterpret_steal<object>(value_conv::cast(value, policy, parent));
if (!value_)
return handle();
PyList_SET_ITEM(l.ptr(), index++, value_.release().ptr()); // steals a reference
}
return l.release();
}
PYBIND11_TYPE_CASTER(array_type, _("List[") + value_conv::name() + _("[") + _<Size>() + _("]]"));
};
template <typename Key, typename Compare, typename Alloc> struct type_caster<std::set<Key, Compare, Alloc>>
: set_caster<std::set<Key, Compare, Alloc>, Key> { };
template <typename Key, typename Hash, typename Equal, typename Alloc> struct type_caster<std::unordered_set<Key, Hash, Equal, Alloc>>
: set_caster<std::unordered_set<Key, Hash, Equal, Alloc>, Key> { };
template <typename Key, typename Value, typename Compare, typename Alloc> struct type_caster<std::map<Key, Value, Compare, Alloc>>
: map_caster<std::map<Key, Value, Compare, Alloc>, Key, Value> { };
template <typename Key, typename Value, typename Hash, typename Equal, typename Alloc> struct type_caster<std::unordered_map<Key, Value, Hash, Equal, Alloc>>
: map_caster<std::unordered_map<Key, Value, Hash, Equal, Alloc>, Key, Value> { };
// This type caster is intended to be used for std::optional and std::experimental::optional
template<typename T> struct optional_caster {
using value_conv = make_caster<typename T::value_type>;
static handle cast(const T& src, return_value_policy policy, handle parent) {
if (!src)
return none().inc_ref();
return value_conv::cast(*src, policy, parent);
}
bool load(handle src, bool convert) {
if (!src) {
return false;
} else if (src.is_none()) {
value = {}; // nullopt
return true;
}
value_conv inner_caster;
if (!inner_caster.load(src, convert))
return false;
value.emplace(cast_op<typename T::value_type>(inner_caster));
return true;
}
PYBIND11_TYPE_CASTER(T, _("Optional[") + value_conv::name() + _("]"));
};
#if PYBIND11_HAS_OPTIONAL
template<typename T> struct type_caster<std::optional<T>>
: public optional_caster<std::optional<T>> {};
template<> struct type_caster<std::nullopt_t>
: public void_caster<std::nullopt_t> {};
#endif
#if PYBIND11_HAS_EXP_OPTIONAL
template<typename T> struct type_caster<std::experimental::optional<T>>
: public optional_caster<std::experimental::optional<T>> {};
template<> struct type_caster<std::experimental::nullopt_t>
: public void_caster<std::experimental::nullopt_t> {};
#endif
NAMESPACE_END(detail)
inline std::ostream &operator<<(std::ostream &os, const handle &obj) {
os << (std::string) str(obj);
return os;
}
NAMESPACE_END(pybind11)
#if defined(_MSC_VER)
#pragma warning(pop)
#endif

541
resources/pybind11/include/pybind11/stl_bind.h

@ -0,0 +1,541 @@
/*
pybind11/std_bind.h: Binding generators for STL data types
Copyright (c) 2016 Sergey Lyskov and Wenzel Jakob
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#pragma once
#include "common.h"
#include "operators.h"
#include <algorithm>
#include <sstream>
NAMESPACE_BEGIN(pybind11)
NAMESPACE_BEGIN(detail)
/* SFINAE helper class used by 'is_comparable */
template <typename T> struct container_traits {
template <typename T2> static std::true_type test_comparable(decltype(std::declval<const T2 &>() == std::declval<const T2 &>())*);
template <typename T2> static std::false_type test_comparable(...);
template <typename T2> static std::true_type test_value(typename T2::value_type *);
template <typename T2> static std::false_type test_value(...);
template <typename T2> static std::true_type test_pair(typename T2::first_type *, typename T2::second_type *);
template <typename T2> static std::false_type test_pair(...);
static constexpr const bool is_comparable = std::is_same<std::true_type, decltype(test_comparable<T>(nullptr))>::value;
static constexpr const bool is_pair = std::is_same<std::true_type, decltype(test_pair<T>(nullptr, nullptr))>::value;
static constexpr const bool is_vector = std::is_same<std::true_type, decltype(test_value<T>(nullptr))>::value;
static constexpr const bool is_element = !is_pair && !is_vector;
};
/* Default: is_comparable -> std::false_type */
template <typename T, typename SFINAE = void>
struct is_comparable : std::false_type { };
/* For non-map data structures, check whether operator== can be instantiated */
template <typename T>
struct is_comparable<
T, enable_if_t<container_traits<T>::is_element &&
container_traits<T>::is_comparable>>
: std::true_type { };
/* For a vector/map data structure, recursively check the value type (which is std::pair for maps) */
template <typename T>
struct is_comparable<T, enable_if_t<container_traits<T>::is_vector>> {
static constexpr const bool value =
is_comparable<typename T::value_type>::value;
};
/* For pairs, recursively check the two data types */
template <typename T>
struct is_comparable<T, enable_if_t<container_traits<T>::is_pair>> {
static constexpr const bool value =
is_comparable<typename T::first_type>::value &&
is_comparable<typename T::second_type>::value;
};
/* Fallback functions */
template <typename, typename, typename... Args> void vector_if_copy_constructible(const Args &...) { }
template <typename, typename, typename... Args> void vector_if_equal_operator(const Args &...) { }
template <typename, typename, typename... Args> void vector_if_insertion_operator(const Args &...) { }
template <typename, typename, typename... Args> void vector_modifiers(const Args &...) { }
template<typename Vector, typename Class_>
void vector_if_copy_constructible(enable_if_t<
std::is_copy_constructible<Vector>::value &&
std::is_copy_constructible<typename Vector::value_type>::value, Class_> &cl) {
cl.def(pybind11::init<const Vector &>(), "Copy constructor");
}
template<typename Vector, typename Class_>
void vector_if_equal_operator(enable_if_t<is_comparable<Vector>::value, Class_> &cl) {
using T = typename Vector::value_type;
cl.def(self == self);
cl.def(self != self);
cl.def("count",
[](const Vector &v, const T &x) {
return std::count(v.begin(), v.end(), x);
},
arg("x"),
"Return the number of times ``x`` appears in the list"
);
cl.def("remove", [](Vector &v, const T &x) {
auto p = std::find(v.begin(), v.end(), x);
if (p != v.end())
v.erase(p);
else
throw pybind11::value_error();
},
arg("x"),
"Remove the first item from the list whose value is x. "
"It is an error if there is no such item."
);
cl.def("__contains__",
[](const Vector &v, const T &x) {
return std::find(v.begin(), v.end(), x) != v.end();
},
arg("x"),
"Return true the container contains ``x``"
);
}
// Vector modifiers -- requires a copyable vector_type:
// (Technically, some of these (pop and __delitem__) don't actually require copyability, but it seems
// silly to allow deletion but not insertion, so include them here too.)
template <typename Vector, typename Class_>
void vector_modifiers(enable_if_t<std::is_copy_constructible<typename Vector::value_type>::value, Class_> &cl) {
using T = typename Vector::value_type;
using SizeType = typename Vector::size_type;
using DiffType = typename Vector::difference_type;
cl.def("append",
[](Vector &v, const T &value) { v.push_back(value); },
arg("x"),
"Add an item to the end of the list");
cl.def("__init__", [](Vector &v, iterable it) {
new (&v) Vector();
try {
v.reserve(len(it));
for (handle h : it)
v.push_back(h.cast<T>());
} catch (...) {
v.~Vector();
throw;
}
});
cl.def("extend",
[](Vector &v, const Vector &src) {
v.reserve(v.size() + src.size());
v.insert(v.end(), src.begin(), src.end());
},
arg("L"),
"Extend the list by appending all the items in the given list"
);
cl.def("insert",
[](Vector &v, SizeType i, const T &x) {
v.insert(v.begin() + (DiffType) i, x);
},
arg("i") , arg("x"),
"Insert an item at a given position."
);
cl.def("pop",
[](Vector &v) {
if (v.empty())
throw pybind11::index_error();
T t = v.back();
v.pop_back();
return t;
},
"Remove and return the last item"
);
cl.def("pop",
[](Vector &v, SizeType i) {
if (i >= v.size())
throw pybind11::index_error();
T t = v[i];
v.erase(v.begin() + (DiffType) i);
return t;
},
arg("i"),
"Remove and return the item at index ``i``"
);
cl.def("__setitem__",
[](Vector &v, SizeType i, const T &t) {
if (i >= v.size())
throw pybind11::index_error();
v[i] = t;
}
);
/// Slicing protocol
cl.def("__getitem__",
[](const Vector &v, slice slice) -> Vector * {
size_t start, stop, step, slicelength;
if (!slice.compute(v.size(), &start, &stop, &step, &slicelength))
throw pybind11::error_already_set();
Vector *seq = new Vector();
seq->reserve((size_t) slicelength);
for (size_t i=0; i<slicelength; ++i) {
seq->push_back(v[start]);
start += step;
}
return seq;
},
arg("s"),
"Retrieve list elements using a slice object"
);
cl.def("__setitem__",
[](Vector &v, slice slice, const Vector &value) {
size_t start, stop, step, slicelength;
if (!slice.compute(v.size(), &start, &stop, &step, &slicelength))
throw pybind11::error_already_set();
if (slicelength != value.size())
throw std::runtime_error("Left and right hand size of slice assignment have different sizes!");
for (size_t i=0; i<slicelength; ++i) {
v[start] = value[i];
start += step;
}
},
"Assign list elements using a slice object"
);
cl.def("__delitem__",
[](Vector &v, SizeType i) {
if (i >= v.size())
throw pybind11::index_error();
v.erase(v.begin() + DiffType(i));
},
"Delete the list elements at index ``i``"
);
cl.def("__delitem__",
[](Vector &v, slice slice) {
size_t start, stop, step, slicelength;
if (!slice.compute(v.size(), &start, &stop, &step, &slicelength))
throw pybind11::error_already_set();
if (step == 1 && false) {
v.erase(v.begin() + (DiffType) start, v.begin() + DiffType(start + slicelength));
} else {
for (size_t i = 0; i < slicelength; ++i) {
v.erase(v.begin() + DiffType(start));
start += step - 1;
}
}
},
"Delete list elements using a slice object"
);
}
// If the type has an operator[] that doesn't return a reference (most notably std::vector<bool>),
// we have to access by copying; otherwise we return by reference.
template <typename Vector> using vector_needs_copy = bool_constant<
!std::is_same<decltype(std::declval<Vector>()[typename Vector::size_type()]), typename Vector::value_type &>::value>;
// The usual case: access and iterate by reference
template <typename Vector, typename Class_>
void vector_accessor(enable_if_t<!vector_needs_copy<Vector>::value, Class_> &cl) {
using T = typename Vector::value_type;
using SizeType = typename Vector::size_type;
using ItType = typename Vector::iterator;
cl.def("__getitem__",
[](Vector &v, SizeType i) -> T & {
if (i >= v.size())
throw pybind11::index_error();
return v[i];
},
return_value_policy::reference_internal // ref + keepalive
);
cl.def("__iter__",
[](Vector &v) {
return pybind11::make_iterator<
return_value_policy::reference_internal, ItType, ItType, T&>(
v.begin(), v.end());
},
keep_alive<0, 1>() /* Essential: keep list alive while iterator exists */
);
}
// The case for special objects, like std::vector<bool>, that have to be returned-by-copy:
template <typename Vector, typename Class_>
void vector_accessor(enable_if_t<vector_needs_copy<Vector>::value, Class_> &cl) {
using T = typename Vector::value_type;
using SizeType = typename Vector::size_type;
using ItType = typename Vector::iterator;
cl.def("__getitem__",
[](const Vector &v, SizeType i) -> T {
if (i >= v.size())
throw pybind11::index_error();
return v[i];
}
);
cl.def("__iter__",
[](Vector &v) {
return pybind11::make_iterator<
return_value_policy::copy, ItType, ItType, T>(
v.begin(), v.end());
},
keep_alive<0, 1>() /* Essential: keep list alive while iterator exists */
);
}
template <typename Vector, typename Class_> auto vector_if_insertion_operator(Class_ &cl, std::string const &name)
-> decltype(std::declval<std::ostream&>() << std::declval<typename Vector::value_type>(), void()) {
using size_type = typename Vector::size_type;
cl.def("__repr__",
[name](Vector &v) {
std::ostringstream s;
s << name << '[';
for (size_type i=0; i < v.size(); ++i) {
s << v[i];
if (i != v.size() - 1)
s << ", ";
}
s << ']';
return s.str();
},
"Return the canonical string representation of this list."
);
}
NAMESPACE_END(detail)
//
// std::vector
//
template <typename Vector, typename holder_type = std::unique_ptr<Vector>, typename... Args>
pybind11::class_<Vector, holder_type> bind_vector(pybind11::module &m, std::string const &name, Args&&... args) {
using Class_ = pybind11::class_<Vector, holder_type>;
Class_ cl(m, name.c_str(), std::forward<Args>(args)...);
cl.def(pybind11::init<>());
// Register copy constructor (if possible)
detail::vector_if_copy_constructible<Vector, Class_>(cl);
// Register comparison-related operators and functions (if possible)
detail::vector_if_equal_operator<Vector, Class_>(cl);
// Register stream insertion operator (if possible)
detail::vector_if_insertion_operator<Vector, Class_>(cl, name);
// Modifiers require copyable vector value type
detail::vector_modifiers<Vector, Class_>(cl);
// Accessor and iterator; return by value if copyable, otherwise we return by ref + keep-alive
detail::vector_accessor<Vector, Class_>(cl);
cl.def("__bool__",
[](const Vector &v) -> bool {
return !v.empty();
},
"Check whether the list is nonempty"
);
cl.def("__len__", &Vector::size);
#if 0
// C++ style functions deprecated, leaving it here as an example
cl.def(pybind11::init<size_type>());
cl.def("resize",
(void (Vector::*) (size_type count)) & Vector::resize,
"changes the number of elements stored");
cl.def("erase",
[](Vector &v, SizeType i) {
if (i >= v.size())
throw pybind11::index_error();
v.erase(v.begin() + i);
}, "erases element at index ``i``");
cl.def("empty", &Vector::empty, "checks whether the container is empty");
cl.def("size", &Vector::size, "returns the number of elements");
cl.def("push_back", (void (Vector::*)(const T&)) &Vector::push_back, "adds an element to the end");
cl.def("pop_back", &Vector::pop_back, "removes the last element");
cl.def("max_size", &Vector::max_size, "returns the maximum possible number of elements");
cl.def("reserve", &Vector::reserve, "reserves storage");
cl.def("capacity", &Vector::capacity, "returns the number of elements that can be held in currently allocated storage");
cl.def("shrink_to_fit", &Vector::shrink_to_fit, "reduces memory usage by freeing unused memory");
cl.def("clear", &Vector::clear, "clears the contents");
cl.def("swap", &Vector::swap, "swaps the contents");
cl.def("front", [](Vector &v) {
if (v.size()) return v.front();
else throw pybind11::index_error();
}, "access the first element");
cl.def("back", [](Vector &v) {
if (v.size()) return v.back();
else throw pybind11::index_error();
}, "access the last element ");
#endif
return cl;
}
//
// std::map, std::unordered_map
//
NAMESPACE_BEGIN(detail)
/* Fallback functions */
template <typename, typename, typename... Args> void map_if_insertion_operator(const Args &...) { }
template <typename, typename, typename... Args> void map_assignment(const Args &...) { }
// Map assignment when copy-assignable: just copy the value
template <typename Map, typename Class_>
void map_assignment(enable_if_t<std::is_copy_assignable<typename Map::mapped_type>::value, Class_> &cl) {
using KeyType = typename Map::key_type;
using MappedType = typename Map::mapped_type;
cl.def("__setitem__",
[](Map &m, const KeyType &k, const MappedType &v) {
auto it = m.find(k);
if (it != m.end()) it->second = v;
else m.emplace(k, v);
}
);
}
// Not copy-assignable, but still copy-constructible: we can update the value by erasing and reinserting
template<typename Map, typename Class_>
void map_assignment(enable_if_t<
!std::is_copy_assignable<typename Map::mapped_type>::value &&
std::is_copy_constructible<typename Map::mapped_type>::value,
Class_> &cl) {
using KeyType = typename Map::key_type;
using MappedType = typename Map::mapped_type;
cl.def("__setitem__",
[](Map &m, const KeyType &k, const MappedType &v) {
// We can't use m[k] = v; because value type might not be default constructable
auto r = m.emplace(k, v);
if (!r.second) {
// value type is not copy assignable so the only way to insert it is to erase it first...
m.erase(r.first);
m.emplace(k, v);
}
}
);
}
template <typename Map, typename Class_> auto map_if_insertion_operator(Class_ &cl, std::string const &name)
-> decltype(std::declval<std::ostream&>() << std::declval<typename Map::key_type>() << std::declval<typename Map::mapped_type>(), void()) {
cl.def("__repr__",
[name](Map &m) {
std::ostringstream s;
s << name << '{';
bool f = false;
for (auto const &kv : m) {
if (f)
s << ", ";
s << kv.first << ": " << kv.second;
f = true;
}
s << '}';
return s.str();
},
"Return the canonical string representation of this map."
);
}
NAMESPACE_END(detail)
template <typename Map, typename holder_type = std::unique_ptr<Map>, typename... Args>
pybind11::class_<Map, holder_type> bind_map(module &m, const std::string &name, Args&&... args) {
using KeyType = typename Map::key_type;
using MappedType = typename Map::mapped_type;
using Class_ = pybind11::class_<Map, holder_type>;
Class_ cl(m, name.c_str(), std::forward<Args>(args)...);
cl.def(pybind11::init<>());
// Register stream insertion operator (if possible)
detail::map_if_insertion_operator<Map, Class_>(cl, name);
cl.def("__bool__",
[](const Map &m) -> bool { return !m.empty(); },
"Check whether the map is nonempty"
);
cl.def("__iter__",
[](Map &m) { return pybind11::make_key_iterator(m.begin(), m.end()); },
pybind11::keep_alive<0, 1>() /* Essential: keep list alive while iterator exists */
);
cl.def("items",
[](Map &m) { return pybind11::make_iterator(m.begin(), m.end()); },
pybind11::keep_alive<0, 1>() /* Essential: keep list alive while iterator exists */
);
cl.def("__getitem__",
[](Map &m, const KeyType &k) -> MappedType & {
auto it = m.find(k);
if (it == m.end())
throw pybind11::key_error();
return it->second;
},
return_value_policy::reference_internal // ref + keepalive
);
// Assignment provided only if the type is copyable
detail::map_assignment<Map, Class_>(cl);
cl.def("__delitem__",
[](Map &m, const KeyType &k) {
auto it = m.find(k);
if (it == m.end())
throw pybind11::key_error();
return m.erase(it);
}
);
cl.def("__len__", &Map::size);
return cl;
}
NAMESPACE_END(pybind11)

53
resources/pybind11/include/pybind11/typeid.h

@ -0,0 +1,53 @@
/*
pybind11/typeid.h: Compiler-independent access to type identifiers
Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#pragma once
#include <cstdio>
#include <cstdlib>
#if defined(__GNUG__)
#include <cxxabi.h>
#endif
NAMESPACE_BEGIN(pybind11)
NAMESPACE_BEGIN(detail)
/// Erase all occurrences of a substring
inline void erase_all(std::string &string, const std::string &search) {
for (size_t pos = 0;;) {
pos = string.find(search, pos);
if (pos == std::string::npos) break;
string.erase(pos, search.length());
}
}
PYBIND11_NOINLINE inline void clean_type_id(std::string &name) {
#if defined(__GNUG__)
int status = 0;
std::unique_ptr<char, void (*)(void *)> res {
abi::__cxa_demangle(name.c_str(), nullptr, nullptr, &status), std::free };
if (status == 0)
name = res.get();
#else
detail::erase_all(name, "class ");
detail::erase_all(name, "struct ");
detail::erase_all(name, "enum ");
#endif
detail::erase_all(name, "pybind11::");
}
NAMESPACE_END(detail)
/// Return a string representation of a C++ type
template <typename T> static std::string type_id() {
std::string name(typeid(T).name());
detail::clean_type_id(name);
return name;
}
NAMESPACE_END(pybind11)

11
resources/pybind11/pybind11/__init__.py

@ -0,0 +1,11 @@
from ._version import version_info, __version__ # noqa: F401 imported but unused
def get_include(*args, **kwargs):
import os
try:
from pip import locations
return os.path.dirname(
locations.distutils_scheme('pybind11', *args, **kwargs)['headers'])
except ImportError:
return 'include'

2
resources/pybind11/pybind11/_version.py

@ -0,0 +1,2 @@
version_info = (1, 9, 'dev0')
__version__ = '.'.join(map(str, version_info))

11
resources/pybind11/setup.cfg

@ -0,0 +1,11 @@
[bdist_wheel]
universal=1
[flake8]
show_source = True
exclude = .git, __pycache__, build, dist, docs, tools, venv
ignore =
# line too long
E501,
# required for pretty matrix formating: multiple spaces after `,` and `[`
E201, E241

74
resources/pybind11/setup.py

@ -0,0 +1,74 @@
#!/usr/bin/env python
# Setup script for PyPI; use CMakeFile.txt to build extension modules
from setuptools import setup
from pybind11 import __version__
setup(
name='pybind11',
version=__version__,
description='Seamless operability between C++11 and Python',
author='Wenzel Jakob',
author_email='wenzel.jakob@epfl.ch',
url='https://github.com/wjakob/pybind11',
download_url='https://github.com/wjakob/pybind11/tarball/v' + __version__,
packages=['pybind11'],
license='BSD',
headers=[
'include/pybind11/attr.h',
'include/pybind11/cast.h',
'include/pybind11/chrono.h',
'include/pybind11/common.h',
'include/pybind11/complex.h',
'include/pybind11/descr.h',
'include/pybind11/eigen.h',
'include/pybind11/eval.h',
'include/pybind11/functional.h',
'include/pybind11/numpy.h',
'include/pybind11/operators.h',
'include/pybind11/options.h',
'include/pybind11/pybind11.h',
'include/pybind11/pytypes.h',
'include/pybind11/stl.h',
'include/pybind11/stl_bind.h',
'include/pybind11/typeid.h',
],
classifiers=[
'Development Status :: 5 - Production/Stable',
'Intended Audience :: Developers',
'Topic :: Software Development :: Libraries :: Python Modules',
'Topic :: Utilities',
'Programming Language :: C++',
'Programming Language :: Python :: 2.7',
'Programming Language :: Python :: 3',
'Programming Language :: Python :: 3.2',
'Programming Language :: Python :: 3.3',
'Programming Language :: Python :: 3.4',
'Programming Language :: Python :: 3.5',
'License :: OSI Approved :: BSD License',
],
keywords='C++11, Python bindings',
long_description="""pybind11 is a lightweight header library that exposes
C++ types in Python and vice versa, mainly to create Python bindings of
existing C++ code. Its goals and syntax are similar to the excellent
Boost.Python library by David Abrahams: to minimize boilerplate code in
traditional extension modules by inferring type information using compile-time
introspection.
The main issue with Boost.Python-and the reason for creating such a similar
project-is Boost. Boost is an enormously large and complex suite of utility
libraries that works with almost every C++ compiler in existence. This
compatibility has its cost: arcane template tricks and workarounds are
necessary to support the oldest and buggiest of compiler specimens. Now that
C++11-compatible compilers are widely available, this heavy machinery has
become an excessively large and unnecessary dependency.
Think of this library as a tiny self-contained version of Boost.Python with
everything stripped away that isn't relevant for binding generation. Without
comments, the core header files only require ~2.5K lines of code and depend on
Python (2.7 or 3.x) and the C++ standard library. This compact implementation
was possible thanks to some of the new C++11 language features (specifically:
tuples, lambda functions and variadic templates). Since its creation, this
library has grown beyond Boost.Python in many ways, leading to dramatically
simpler binding code in many common situations.""")

111
resources/pybind11/tests/CMakeLists.txt

@ -0,0 +1,111 @@
if(NOT CMAKE_BUILD_TYPE AND NOT CMAKE_CONFIGURATION_TYPES)
message(STATUS "Setting tests build type to MinSizeRel as none was specified")
set(CMAKE_BUILD_TYPE MinSizeRel CACHE STRING "Choose the type of build." FORCE)
set_property(CACHE CMAKE_BUILD_TYPE PROPERTY STRINGS "Debug" "Release"
"MinSizeRel" "RelWithDebInfo")
endif()
# Full set of test files (you can override these; see below)
set(PYBIND11_TEST_FILES
test_alias_initialization.cpp
test_buffers.cpp
test_callbacks.cpp
test_chrono.cpp
test_class_args.cpp
test_constants_and_functions.cpp
test_copy_move_policies.cpp
test_docstring_options.cpp
test_eigen.cpp
test_enum.cpp
test_eval.cpp
test_exceptions.cpp
test_inheritance.cpp
test_issues.cpp
test_keep_alive.cpp
test_kwargs_and_defaults.cpp
test_methods_and_attributes.cpp
test_modules.cpp
test_multiple_inheritance.cpp
test_numpy_array.cpp
test_numpy_dtypes.cpp
test_numpy_vectorize.cpp
test_opaque_types.cpp
test_operator_overloading.cpp
test_pickling.cpp
test_python_types.cpp
test_sequences_and_iterators.cpp
test_smart_ptr.cpp
test_stl_binders.cpp
test_virtual_functions.cpp
)
# Invoking cmake with something like:
# cmake -DPYBIND11_TEST_OVERRIDE="test_issues.cpp;test_picking.cpp" ..
# lets you override the tests that get compiled and run. You can restore to all tests with:
# cmake -DPYBIND11_TEST_OVERRIDE= ..
if (PYBIND11_TEST_OVERRIDE)
set(PYBIND11_TEST_FILES ${PYBIND11_TEST_OVERRIDE})
endif()
string(REPLACE ".cpp" ".py" PYBIND11_PYTEST_FILES "${PYBIND11_TEST_FILES}")
# Check if Eigen is available; if not, remove from PYBIND11_TEST_FILES (but
# keep it in PYBIND11_PYTEST_FILES, so that we get the "eigen is not installed"
# skip message).
list(FIND PYBIND11_TEST_FILES test_eigen.cpp PYBIND11_TEST_FILES_EIGEN_I)
if(PYBIND11_TEST_FILES_EIGEN_I GREATER -1)
find_package(Eigen3 QUIET)
if(EIGEN3_FOUND)
message(STATUS "Building tests with Eigen v${EIGEN3_VERSION}")
else()
list(REMOVE_AT PYBIND11_TEST_FILES ${PYBIND11_TEST_FILES_EIGEN_I})
message(STATUS "Building tests WITHOUT Eigen")
endif()
endif()
# Create the binding library
pybind11_add_module(pybind11_tests pybind11_tests.cpp
${PYBIND11_TEST_FILES} ${PYBIND11_HEADERS})
pybind11_enable_warnings(pybind11_tests)
if(EIGEN3_FOUND)
target_include_directories(pybind11_tests PRIVATE ${EIGEN3_INCLUDE_DIR})
target_compile_definitions(pybind11_tests PRIVATE -DPYBIND11_TEST_EIGEN)
endif()
set(testdir ${PROJECT_SOURCE_DIR}/tests)
# Always write the output file directly into the 'tests' directory (even on MSVC)
if(NOT CMAKE_LIBRARY_OUTPUT_DIRECTORY)
set_target_properties(pybind11_tests PROPERTIES LIBRARY_OUTPUT_DIRECTORY ${testdir})
foreach(config ${CMAKE_CONFIGURATION_TYPES})
string(TOUPPER ${config} config)
set_target_properties(pybind11_tests PROPERTIES LIBRARY_OUTPUT_DIRECTORY_${config} ${testdir})
endforeach()
endif()
# Make sure pytest is found or produce a fatal error
if(NOT PYBIND11_PYTEST_FOUND)
execute_process(COMMAND ${PYTHON_EXECUTABLE} -m pytest --version --noconftest OUTPUT_QUIET ERROR_QUIET
RESULT_VARIABLE PYBIND11_EXEC_PYTHON_ERR)
if(PYBIND11_EXEC_PYTHON_ERR)
message(FATAL_ERROR "Running the tests requires pytest. Please install it manually (try: ${PYTHON_EXECUTABLE} -m pip install pytest)")
endif()
set(PYBIND11_PYTEST_FOUND TRUE CACHE INTERNAL "")
endif()
# A single command to compile and run the tests
add_custom_target(pytest COMMAND ${PYTHON_EXECUTABLE} -m pytest -rws ${PYBIND11_PYTEST_FILES}
DEPENDS pybind11_tests WORKING_DIRECTORY ${testdir})
if(PYBIND11_TEST_OVERRIDE)
add_custom_command(TARGET pytest POST_BUILD
COMMAND ${CMAKE_COMMAND} -E echo "Note: not all tests run: -DPYBIND11_TEST_OVERRIDE is in effect")
endif()
# And another to show the .so size and, if a previous size, compare it:
add_custom_command(TARGET pybind11_tests POST_BUILD
COMMAND ${PYTHON_EXECUTABLE} ${CMAKE_SOURCE_DIR}/tools/libsize.py
$<TARGET_FILE:pybind11_tests> ${CMAKE_CURRENT_BINARY_DIR}/sosize-$<TARGET_FILE_NAME:pybind11_tests>.txt)

227
resources/pybind11/tests/conftest.py

@ -0,0 +1,227 @@
"""pytest configuration
Extends output capture as needed by pybind11: ignore constructors, optional unordered lines.
Adds docstring and exceptions message sanitizers: ignore Python 2 vs 3 differences.
"""
import pytest
import textwrap
import difflib
import re
import sys
import contextlib
_unicode_marker = re.compile(r'u(\'[^\']*\')')
_long_marker = re.compile(r'([0-9])L')
_hexadecimal = re.compile(r'0x[0-9a-fA-F]+')
def _strip_and_dedent(s):
"""For triple-quote strings"""
return textwrap.dedent(s.lstrip('\n').rstrip())
def _split_and_sort(s):
"""For output which does not require specific line order"""
return sorted(_strip_and_dedent(s).splitlines())
def _make_explanation(a, b):
"""Explanation for a failed assert -- the a and b arguments are List[str]"""
return ["--- actual / +++ expected"] + [line.strip('\n') for line in difflib.ndiff(a, b)]
class Output(object):
"""Basic output post-processing and comparison"""
def __init__(self, string):
self.string = string
self.explanation = []
def __str__(self):
return self.string
def __eq__(self, other):
# Ignore constructor/destructor output which is prefixed with "###"
a = [line for line in self.string.strip().splitlines() if not line.startswith("###")]
b = _strip_and_dedent(other).splitlines()
if a == b:
return True
else:
self.explanation = _make_explanation(a, b)
return False
class Unordered(Output):
"""Custom comparison for output without strict line ordering"""
def __eq__(self, other):
a = _split_and_sort(self.string)
b = _split_and_sort(other)
if a == b:
return True
else:
self.explanation = _make_explanation(a, b)
return False
class Capture(object):
def __init__(self, capfd):
self.capfd = capfd
self.out = ""
self.err = ""
def __enter__(self):
self.capfd.readouterr()
return self
def __exit__(self, *_):
self.out, self.err = self.capfd.readouterr()
def __eq__(self, other):
a = Output(self.out)
b = other
if a == b:
return True
else:
self.explanation = a.explanation
return False
def __str__(self):
return self.out
def __contains__(self, item):
return item in self.out
@property
def unordered(self):
return Unordered(self.out)
@property
def stderr(self):
return Output(self.err)
@pytest.fixture
def capture(capfd):
"""Extended `capfd` with context manager and custom equality operators"""
return Capture(capfd)
class SanitizedString(object):
def __init__(self, sanitizer):
self.sanitizer = sanitizer
self.string = ""
self.explanation = []
def __call__(self, thing):
self.string = self.sanitizer(thing)
return self
def __eq__(self, other):
a = self.string
b = _strip_and_dedent(other)
if a == b:
return True
else:
self.explanation = _make_explanation(a.splitlines(), b.splitlines())
return False
def _sanitize_general(s):
s = s.strip()
s = s.replace("pybind11_tests.", "m.")
s = s.replace("unicode", "str")
s = _long_marker.sub(r"\1", s)
s = _unicode_marker.sub(r"\1", s)
return s
def _sanitize_docstring(thing):
s = thing.__doc__
s = _sanitize_general(s)
return s
@pytest.fixture
def doc():
"""Sanitize docstrings and add custom failure explanation"""
return SanitizedString(_sanitize_docstring)
def _sanitize_message(thing):
s = str(thing)
s = _sanitize_general(s)
s = _hexadecimal.sub("0", s)
return s
@pytest.fixture
def msg():
"""Sanitize messages and add custom failure explanation"""
return SanitizedString(_sanitize_message)
# noinspection PyUnusedLocal
def pytest_assertrepr_compare(op, left, right):
"""Hook to insert custom failure explanation"""
if hasattr(left, 'explanation'):
return left.explanation
@contextlib.contextmanager
def suppress(exception):
"""Suppress the desired exception"""
try:
yield
except exception:
pass
def pytest_namespace():
"""Add import suppression and test requirements to `pytest` namespace"""
try:
import numpy as np
except ImportError:
np = None
try:
import scipy
except ImportError:
scipy = None
try:
from pybind11_tests import have_eigen
except ImportError:
have_eigen = False
skipif = pytest.mark.skipif
return {
'suppress': suppress,
'requires_numpy': skipif(not np, reason="numpy is not installed"),
'requires_scipy': skipif(not np, reason="scipy is not installed"),
'requires_eigen_and_numpy': skipif(not have_eigen or not np,
reason="eigen and/or numpy are not installed"),
'requires_eigen_and_scipy': skipif(not have_eigen or not scipy,
reason="eigen and/or scipy are not installed"),
}
def _test_import_pybind11():
"""Early diagnostic for test module initialization errors
When there is an error during initialization, the first import will report the
real error while all subsequent imports will report nonsense. This import test
is done early (in the pytest configuration file, before any tests) in order to
avoid the noise of having all tests fail with identical error messages.
Any possible exception is caught here and reported manually *without* the stack
trace. This further reduces noise since the trace would only show pytest internals
which are not useful for debugging pybind11 module issues.
"""
# noinspection PyBroadException
try:
import pybind11_tests # noqa: F401 imported but unused
except Exception as e:
print("Failed to import pybind11_tests from pytest:")
print(" {}: {}".format(type(e).__name__, e))
sys.exit(1)
_test_import_pybind11()

249
resources/pybind11/tests/constructor_stats.h

@ -0,0 +1,249 @@
#pragma once
/*
tests/constructor_stats.h -- framework for printing and tracking object
instance lifetimes in example/test code.
Copyright (c) 2016 Jason Rhinelander <jason@imaginary.ca>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
This header provides a few useful tools for writing examples or tests that want to check and/or
display object instance lifetimes. It requires that you include this header and add the following
function calls to constructors:
class MyClass {
MyClass() { ...; print_default_created(this); }
~MyClass() { ...; print_destroyed(this); }
MyClass(const MyClass &c) { ...; print_copy_created(this); }
MyClass(MyClass &&c) { ...; print_move_created(this); }
MyClass(int a, int b) { ...; print_created(this, a, b); }
MyClass &operator=(const MyClass &c) { ...; print_copy_assigned(this); }
MyClass &operator=(MyClass &&c) { ...; print_move_assigned(this); }
...
}
You can find various examples of these in several of the existing example .cpp files. (Of course
you don't need to add any of the above constructors/operators that you don't actually have, except
for the destructor).
Each of these will print an appropriate message such as:
### MyClass @ 0x2801910 created via default constructor
### MyClass @ 0x27fa780 created 100 200
### MyClass @ 0x2801910 destroyed
### MyClass @ 0x27fa780 destroyed
You can also include extra arguments (such as the 100, 200 in the output above, coming from the
value constructor) for all of the above methods which will be included in the output.
For testing, each of these also keeps track the created instances and allows you to check how many
of the various constructors have been invoked from the Python side via code such as:
from example import ConstructorStats
cstats = ConstructorStats.get(MyClass)
print(cstats.alive())
print(cstats.default_constructions)
Note that `.alive()` should usually be the first thing you call as it invokes Python's garbage
collector to actually destroy objects that aren't yet referenced.
For everything except copy and move constructors and destructors, any extra values given to the
print_...() function is stored in a class-specific values list which you can retrieve and inspect
from the ConstructorStats instance `.values()` method.
In some cases, when you need to track instances of a C++ class not registered with pybind11, you
need to add a function returning the ConstructorStats for the C++ class; this can be done with:
m.def("get_special_cstats", &ConstructorStats::get<SpecialClass>, py::return_value_policy::reference)
Finally, you can suppress the output messages, but keep the constructor tracking (for
inspection/testing in python) by using the functions with `print_` replaced with `track_` (e.g.
`track_copy_created(this)`).
*/
#include "pybind11_tests.h"
#include <unordered_map>
#include <list>
#include <typeindex>
#include <sstream>
class ConstructorStats {
protected:
std::unordered_map<void*, int> _instances; // Need a map rather than set because members can shared address with parents
std::list<std::string> _values; // Used to track values (e.g. of value constructors)
public:
int default_constructions = 0;
int copy_constructions = 0;
int move_constructions = 0;
int copy_assignments = 0;
int move_assignments = 0;
void copy_created(void *inst) {
created(inst);
copy_constructions++;
}
void move_created(void *inst) {
created(inst);
move_constructions++;
}
void default_created(void *inst) {
created(inst);
default_constructions++;
}
void created(void *inst) {
++_instances[inst];
};
void destroyed(void *inst) {
if (--_instances[inst] < 0)
throw std::runtime_error("cstats.destroyed() called with unknown instance; potential double-destruction or a missing cstats.created()");
}
int alive() {
// Force garbage collection to ensure any pending destructors are invoked:
py::module::import("gc").attr("collect")();
int total = 0;
for (const auto &p : _instances) if (p.second > 0) total += p.second;
return total;
}
void value() {} // Recursion terminator
// Takes one or more values, converts them to strings, then stores them.
template <typename T, typename... Tmore> void value(const T &v, Tmore &&...args) {
std::ostringstream oss;
oss << v;
_values.push_back(oss.str());
value(std::forward<Tmore>(args)...);
}
// Move out stored values
py::list values() {
py::list l;
for (const auto &v : _values) l.append(py::cast(v));
_values.clear();
return l;
}
// Gets constructor stats from a C++ type index
static ConstructorStats& get(std::type_index type) {
static std::unordered_map<std::type_index, ConstructorStats> all_cstats;
return all_cstats[type];
}
// Gets constructor stats from a C++ type
template <typename T> static ConstructorStats& get() {
return get(typeid(T));
}
// Gets constructor stats from a Python class
static ConstructorStats& get(py::object class_) {
auto &internals = py::detail::get_internals();
const std::type_index *t1 = nullptr, *t2 = nullptr;
try {
auto *type_info = internals.registered_types_py.at(class_.ptr());
for (auto &p : internals.registered_types_cpp) {
if (p.second == type_info) {
if (t1) {
t2 = &p.first;
break;
}
t1 = &p.first;
}
}
}
catch (std::out_of_range) {}
if (!t1) throw std::runtime_error("Unknown class passed to ConstructorStats::get()");
auto &cs1 = get(*t1);
// If we have both a t1 and t2 match, one is probably the trampoline class; return whichever
// has more constructions (typically one or the other will be 0)
if (t2) {
auto &cs2 = get(*t2);
int cs1_total = cs1.default_constructions + cs1.copy_constructions + cs1.move_constructions + (int) cs1._values.size();
int cs2_total = cs2.default_constructions + cs2.copy_constructions + cs2.move_constructions + (int) cs2._values.size();
if (cs2_total > cs1_total) return cs2;
}
return cs1;
}
};
// To track construction/destruction, you need to call these methods from the various
// constructors/operators. The ones that take extra values record the given values in the
// constructor stats values for later inspection.
template <class T> void track_copy_created(T *inst) { ConstructorStats::get<T>().copy_created(inst); }
template <class T> void track_move_created(T *inst) { ConstructorStats::get<T>().move_created(inst); }
template <class T, typename... Values> void track_copy_assigned(T *, Values &&...values) {
auto &cst = ConstructorStats::get<T>();
cst.copy_assignments++;
cst.value(std::forward<Values>(values)...);
}
template <class T, typename... Values> void track_move_assigned(T *, Values &&...values) {
auto &cst = ConstructorStats::get<T>();
cst.move_assignments++;
cst.value(std::forward<Values>(values)...);
}
template <class T, typename... Values> void track_default_created(T *inst, Values &&...values) {
auto &cst = ConstructorStats::get<T>();
cst.default_created(inst);
cst.value(std::forward<Values>(values)...);
}
template <class T, typename... Values> void track_created(T *inst, Values &&...values) {
auto &cst = ConstructorStats::get<T>();
cst.created(inst);
cst.value(std::forward<Values>(values)...);
}
template <class T, typename... Values> void track_destroyed(T *inst) {
ConstructorStats::get<T>().destroyed(inst);
}
template <class T, typename... Values> void track_values(T *, Values &&...values) {
ConstructorStats::get<T>().value(std::forward<Values>(values)...);
}
/// Don't cast pointers to Python, print them as strings
inline const char *format_ptrs(const char *p) { return p; }
template <typename T>
py::str format_ptrs(T *p) { return "{:#x}"_s.format(reinterpret_cast<std::uintptr_t>(p)); }
template <typename T>
auto format_ptrs(T &&x) -> decltype(std::forward<T>(x)) { return std::forward<T>(x); }
template <class T, typename... Output>
void print_constr_details(T *inst, const std::string &action, Output &&...output) {
py::print("###", py::type_id<T>(), "@", format_ptrs(inst), action,
format_ptrs(std::forward<Output>(output))...);
}
// Verbose versions of the above:
template <class T, typename... Values> void print_copy_created(T *inst, Values &&...values) { // NB: this prints, but doesn't store, given values
print_constr_details(inst, "created via copy constructor", values...);
track_copy_created(inst);
}
template <class T, typename... Values> void print_move_created(T *inst, Values &&...values) { // NB: this prints, but doesn't store, given values
print_constr_details(inst, "created via move constructor", values...);
track_move_created(inst);
}
template <class T, typename... Values> void print_copy_assigned(T *inst, Values &&...values) {
print_constr_details(inst, "assigned via copy assignment", values...);
track_copy_assigned(inst, values...);
}
template <class T, typename... Values> void print_move_assigned(T *inst, Values &&...values) {
print_constr_details(inst, "assigned via move assignment", values...);
track_move_assigned(inst, values...);
}
template <class T, typename... Values> void print_default_created(T *inst, Values &&...values) {
print_constr_details(inst, "created via default constructor", values...);
track_default_created(inst, values...);
}
template <class T, typename... Values> void print_created(T *inst, Values &&...values) {
print_constr_details(inst, "created", values...);
track_created(inst, values...);
}
template <class T, typename... Values> void print_destroyed(T *inst, Values &&...values) { // Prints but doesn't store given values
print_constr_details(inst, "destroyed", values...);
track_destroyed(inst);
}
template <class T, typename... Values> void print_values(T *inst, Values &&...values) {
print_constr_details(inst, ":", values...);
track_values(inst, values...);
}

175
resources/pybind11/tests/object.h

@ -0,0 +1,175 @@
#if !defined(__OBJECT_H)
#define __OBJECT_H
#include <atomic>
#include "constructor_stats.h"
/// Reference counted object base class
class Object {
public:
/// Default constructor
Object() { print_default_created(this); }
/// Copy constructor
Object(const Object &) : m_refCount(0) { print_copy_created(this); }
/// Return the current reference count
int getRefCount() const { return m_refCount; };
/// Increase the object's reference count by one
void incRef() const { ++m_refCount; }
/** \brief Decrease the reference count of
* the object and possibly deallocate it.
*
* The object will automatically be deallocated once
* the reference count reaches zero.
*/
void decRef(bool dealloc = true) const {
--m_refCount;
if (m_refCount == 0 && dealloc)
delete this;
else if (m_refCount < 0)
throw std::runtime_error("Internal error: reference count < 0!");
}
virtual std::string toString() const = 0;
protected:
/** \brief Virtual protected deconstructor.
* (Will only be called by \ref ref)
*/
virtual ~Object() { print_destroyed(this); }
private:
mutable std::atomic<int> m_refCount { 0 };
};
// Tag class used to track constructions of ref objects. When we track constructors, below, we
// track and print out the actual class (e.g. ref<MyObject>), and *also* add a fake tracker for
// ref_tag. This lets us check that the total number of ref<Anything> constructors/destructors is
// correct without having to check each individual ref<Whatever> type individually.
class ref_tag {};
/**
* \brief Reference counting helper
*
* The \a ref refeference template is a simple wrapper to store a
* pointer to an object. It takes care of increasing and decreasing
* the reference count of the object. When the last reference goes
* out of scope, the associated object will be deallocated.
*
* \ingroup libcore
*/
template <typename T> class ref {
public:
/// Create a nullptr reference
ref() : m_ptr(nullptr) { print_default_created(this); track_default_created((ref_tag*) this); }
/// Construct a reference from a pointer
ref(T *ptr) : m_ptr(ptr) {
if (m_ptr) ((Object *) m_ptr)->incRef();
print_created(this, "from pointer", m_ptr); track_created((ref_tag*) this, "from pointer");
}
/// Copy constructor
ref(const ref &r) : m_ptr(r.m_ptr) {
if (m_ptr)
((Object *) m_ptr)->incRef();
print_copy_created(this, "with pointer", m_ptr); track_copy_created((ref_tag*) this);
}
/// Move constructor
ref(ref &&r) : m_ptr(r.m_ptr) {
r.m_ptr = nullptr;
print_move_created(this, "with pointer", m_ptr); track_move_created((ref_tag*) this);
}
/// Destroy this reference
~ref() {
if (m_ptr)
((Object *) m_ptr)->decRef();
print_destroyed(this); track_destroyed((ref_tag*) this);
}
/// Move another reference into the current one
ref& operator=(ref&& r) {
print_move_assigned(this, "pointer", r.m_ptr); track_move_assigned((ref_tag*) this);
if (*this == r)
return *this;
if (m_ptr)
((Object *) m_ptr)->decRef();
m_ptr = r.m_ptr;
r.m_ptr = nullptr;
return *this;
}
/// Overwrite this reference with another reference
ref& operator=(const ref& r) {
print_copy_assigned(this, "pointer", r.m_ptr); track_copy_assigned((ref_tag*) this);
if (m_ptr == r.m_ptr)
return *this;
if (m_ptr)
((Object *) m_ptr)->decRef();
m_ptr = r.m_ptr;
if (m_ptr)
((Object *) m_ptr)->incRef();
return *this;
}
/// Overwrite this reference with a pointer to another object
ref& operator=(T *ptr) {
print_values(this, "assigned pointer"); track_values((ref_tag*) this, "assigned pointer");
if (m_ptr == ptr)
return *this;
if (m_ptr)
((Object *) m_ptr)->decRef();
m_ptr = ptr;
if (m_ptr)
((Object *) m_ptr)->incRef();
return *this;
}
/// Compare this reference with another reference
bool operator==(const ref &r) const { return m_ptr == r.m_ptr; }
/// Compare this reference with another reference
bool operator!=(const ref &r) const { return m_ptr != r.m_ptr; }
/// Compare this reference with a pointer
bool operator==(const T* ptr) const { return m_ptr == ptr; }
/// Compare this reference with a pointer
bool operator!=(const T* ptr) const { return m_ptr != ptr; }
/// Access the object referenced by this reference
T* operator->() { return m_ptr; }
/// Access the object referenced by this reference
const T* operator->() const { return m_ptr; }
/// Return a C++ reference to the referenced object
T& operator*() { return *m_ptr; }
/// Return a const C++ reference to the referenced object
const T& operator*() const { return *m_ptr; }
/// Return a pointer to the referenced object
operator T* () { return m_ptr; }
/// Return a const pointer to the referenced object
T* get() { return m_ptr; }
/// Return a pointer to the referenced object
const T* get() const { return m_ptr; }
private:
T *m_ptr;
};
#endif /* __OBJECT_H */

45
resources/pybind11/tests/pybind11_tests.cpp

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/*
tests/pybind11_tests.cpp -- pybind example plugin
Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#include "pybind11_tests.h"
#include "constructor_stats.h"
std::list<std::function<void(py::module &)>> &initializers() {
static std::list<std::function<void(py::module &)>> inits;
return inits;
}
test_initializer::test_initializer(std::function<void(py::module &)> initializer) {
initializers().push_back(std::move(initializer));
}
void bind_ConstructorStats(py::module &m) {
py::class_<ConstructorStats>(m, "ConstructorStats")
.def("alive", &ConstructorStats::alive)
.def("values", &ConstructorStats::values)
.def_readwrite("default_constructions", &ConstructorStats::default_constructions)
.def_readwrite("copy_assignments", &ConstructorStats::copy_assignments)
.def_readwrite("move_assignments", &ConstructorStats::move_assignments)
.def_readwrite("copy_constructions", &ConstructorStats::copy_constructions)
.def_readwrite("move_constructions", &ConstructorStats::move_constructions)
.def_static("get", (ConstructorStats &(*)(py::object)) &ConstructorStats::get, py::return_value_policy::reference_internal);
}
PYBIND11_PLUGIN(pybind11_tests) {
py::module m("pybind11_tests", "pybind example plugin");
bind_ConstructorStats(m);
for (const auto &initializer : initializers())
initializer(m);
if (!py::hasattr(m, "have_eigen")) m.attr("have_eigen") = py::cast(false);
return m.ptr();
}

12
resources/pybind11/tests/pybind11_tests.h

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#pragma once
#include <pybind11/pybind11.h>
#include <functional>
#include <list>
namespace py = pybind11;
using namespace pybind11::literals;
class test_initializer {
public:
test_initializer(std::function<void(py::module &)> initializer);
};

62
resources/pybind11/tests/test_alias_initialization.cpp

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/*
tests/test_alias_initialization.cpp -- test cases and example of different trampoline
initialization modes
Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>, Jason Rhinelander <jason@imaginary.ca>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#include "pybind11_tests.h"
test_initializer alias_initialization([](py::module &m) {
// don't invoke Python dispatch classes by default when instantiating C++ classes that were not
// extended on the Python side
struct A {
virtual ~A() {}
virtual void f() { py::print("A.f()"); }
};
struct PyA : A {
PyA() { py::print("PyA.PyA()"); }
~PyA() { py::print("PyA.~PyA()"); }
void f() override {
py::print("PyA.f()");
PYBIND11_OVERLOAD(void, A, f);
}
};
auto call_f = [](A *a) { a->f(); };
py::class_<A, PyA>(m, "A")
.def(py::init<>())
.def("f", &A::f);
m.def("call_f", call_f);
// ... unless we explicitly request it, as in this example:
struct A2 {
virtual ~A2() {}
virtual void f() { py::print("A2.f()"); }
};
struct PyA2 : A2 {
PyA2() { py::print("PyA2.PyA2()"); }
~PyA2() { py::print("PyA2.~PyA2()"); }
void f() override {
py::print("PyA2.f()");
PYBIND11_OVERLOAD(void, A2, f);
}
};
py::class_<A2, PyA2>(m, "A2")
.def(py::init_alias<>())
.def("f", &A2::f);
m.def("call_f", [](A2 *a2) { a2->f(); });
});

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resources/pybind11/tests/test_alias_initialization.py

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import gc
def test_alias_delay_initialization1(capture):
"""A only initializes its trampoline class when we inherit from it; if we just
create and use an A instance directly, the trampoline initialization is bypassed
and we only initialize an A() instead (for performance reasons).
"""
from pybind11_tests import A, call_f
class B(A):
def __init__(self):
super(B, self).__init__()
def f(self):
print("In python f()")
# C++ version
with capture:
a = A()
call_f(a)
del a
gc.collect()
assert capture == "A.f()"
# Python version
with capture:
b = B()
call_f(b)
del b
gc.collect()
assert capture == """
PyA.PyA()
PyA.f()
In python f()
PyA.~PyA()
"""
def test_alias_delay_initialization2(capture):
"""A2, unlike the above, is configured to always initialize the alias; while
the extra initialization and extra class layer has small virtual dispatch
performance penalty, it also allows us to do more things with the trampoline
class such as defining local variables and performing construction/destruction.
"""
from pybind11_tests import A2, call_f
class B2(A2):
def __init__(self):
super(B2, self).__init__()
def f(self):
print("In python B2.f()")
# No python subclass version
with capture:
a2 = A2()
call_f(a2)
del a2
gc.collect()
assert capture == """
PyA2.PyA2()
PyA2.f()
A2.f()
PyA2.~PyA2()
"""
# Python subclass version
with capture:
b2 = B2()
call_f(b2)
del b2
gc.collect()
assert capture == """
PyA2.PyA2()
PyA2.f()
In python B2.f()
PyA2.~PyA2()
"""

117
resources/pybind11/tests/test_buffers.cpp

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/*
tests/test_buffers.cpp -- supporting Pythons' buffer protocol
Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#include "pybind11_tests.h"
#include "constructor_stats.h"
class Matrix {
public:
Matrix(size_t rows, size_t cols) : m_rows(rows), m_cols(cols) {
print_created(this, std::to_string(m_rows) + "x" + std::to_string(m_cols) + " matrix");
m_data = new float[rows*cols];
memset(m_data, 0, sizeof(float) * rows * cols);
}
Matrix(const Matrix &s) : m_rows(s.m_rows), m_cols(s.m_cols) {
print_copy_created(this, std::to_string(m_rows) + "x" + std::to_string(m_cols) + " matrix");
m_data = new float[m_rows * m_cols];
memcpy(m_data, s.m_data, sizeof(float) * m_rows * m_cols);
}
Matrix(Matrix &&s) : m_rows(s.m_rows), m_cols(s.m_cols), m_data(s.m_data) {
print_move_created(this);
s.m_rows = 0;
s.m_cols = 0;
s.m_data = nullptr;
}
~Matrix() {
print_destroyed(this, std::to_string(m_rows) + "x" + std::to_string(m_cols) + " matrix");
delete[] m_data;
}
Matrix &operator=(const Matrix &s) {
print_copy_assigned(this, std::to_string(m_rows) + "x" + std::to_string(m_cols) + " matrix");
delete[] m_data;
m_rows = s.m_rows;
m_cols = s.m_cols;
m_data = new float[m_rows * m_cols];
memcpy(m_data, s.m_data, sizeof(float) * m_rows * m_cols);
return *this;
}
Matrix &operator=(Matrix &&s) {
print_move_assigned(this, std::to_string(m_rows) + "x" + std::to_string(m_cols) + " matrix");
if (&s != this) {
delete[] m_data;
m_rows = s.m_rows; m_cols = s.m_cols; m_data = s.m_data;
s.m_rows = 0; s.m_cols = 0; s.m_data = nullptr;
}
return *this;
}
float operator()(size_t i, size_t j) const {
return m_data[i*m_cols + j];
}
float &operator()(size_t i, size_t j) {
return m_data[i*m_cols + j];
}
float *data() { return m_data; }
size_t rows() const { return m_rows; }
size_t cols() const { return m_cols; }
private:
size_t m_rows;
size_t m_cols;
float *m_data;
};
test_initializer buffers([](py::module &m) {
py::class_<Matrix> mtx(m, "Matrix");
mtx.def(py::init<size_t, size_t>())
/// Construct from a buffer
.def("__init__", [](Matrix &v, py::buffer b) {
py::buffer_info info = b.request();
if (info.format != py::format_descriptor<float>::format() || info.ndim != 2)
throw std::runtime_error("Incompatible buffer format!");
new (&v) Matrix(info.shape[0], info.shape[1]);
memcpy(v.data(), info.ptr, sizeof(float) * v.rows() * v.cols());
})
.def("rows", &Matrix::rows)
.def("cols", &Matrix::cols)
/// Bare bones interface
.def("__getitem__", [](const Matrix &m, std::pair<size_t, size_t> i) {
if (i.first >= m.rows() || i.second >= m.cols())
throw py::index_error();
return m(i.first, i.second);
})
.def("__setitem__", [](Matrix &m, std::pair<size_t, size_t> i, float v) {
if (i.first >= m.rows() || i.second >= m.cols())
throw py::index_error();
m(i.first, i.second) = v;
})
/// Provide buffer access
.def_buffer([](Matrix &m) -> py::buffer_info {
return py::buffer_info(
m.data(), /* Pointer to buffer */
sizeof(float), /* Size of one scalar */
py::format_descriptor<float>::format(), /* Python struct-style format descriptor */
2, /* Number of dimensions */
{ m.rows(), m.cols() }, /* Buffer dimensions */
{ sizeof(float) * m.rows(), /* Strides (in bytes) for each index */
sizeof(float) }
);
})
;
});

57
resources/pybind11/tests/test_buffers.py

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import pytest
from pybind11_tests import Matrix, ConstructorStats
with pytest.suppress(ImportError):
import numpy as np
@pytest.requires_numpy
def test_to_python():
m = Matrix(5, 5)
assert m[2, 3] == 0
m[2, 3] = 4
assert m[2, 3] == 4
m2 = np.array(m, copy=False)
assert m2.shape == (5, 5)
assert abs(m2).sum() == 4
assert m2[2, 3] == 4
m2[2, 3] = 5
assert m2[2, 3] == 5
cstats = ConstructorStats.get(Matrix)
assert cstats.alive() == 1
del m
assert cstats.alive() == 1
del m2 # holds an m reference
assert cstats.alive() == 0
assert cstats.values() == ["5x5 matrix"]
assert cstats.copy_constructions == 0
# assert cstats.move_constructions >= 0 # Don't invoke any
assert cstats.copy_assignments == 0
assert cstats.move_assignments == 0
@pytest.requires_numpy
def test_from_python():
with pytest.raises(RuntimeError) as excinfo:
Matrix(np.array([1, 2, 3])) # trying to assign a 1D array
assert str(excinfo.value) == "Incompatible buffer format!"
m3 = np.array([[1, 2, 3], [4, 5, 6]]).astype(np.float32)
m4 = Matrix(m3)
for i in range(m4.rows()):
for j in range(m4.cols()):
assert m3[i, j] == m4[i, j]
cstats = ConstructorStats.get(Matrix)
assert cstats.alive() == 1
del m3, m4
assert cstats.alive() == 0
assert cstats.values() == ["2x3 matrix"]
assert cstats.copy_constructions == 0
# assert cstats.move_constructions >= 0 # Don't invoke any
assert cstats.copy_assignments == 0
assert cstats.move_assignments == 0

149
resources/pybind11/tests/test_callbacks.cpp

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/*
tests/test_callbacks.cpp -- callbacks
Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#include "pybind11_tests.h"
#include "constructor_stats.h"
#include <pybind11/functional.h>
py::object test_callback1(py::object func) {
return func();
}
py::tuple test_callback2(py::object func) {
return func("Hello", 'x', true, 5);
}
std::string test_callback3(const std::function<int(int)> &func) {
return "func(43) = " + std::to_string(func(43));
}
std::function<int(int)> test_callback4() {
return [](int i) { return i+1; };
}
py::cpp_function test_callback5() {
return py::cpp_function([](int i) { return i+1; },
py::arg("number"));
}
int dummy_function(int i) { return i + 1; }
int dummy_function2(int i, int j) { return i + j; }
std::function<int(int)> roundtrip(std::function<int(int)> f, bool expect_none = false) {
if (expect_none && f) {
throw std::runtime_error("Expected None to be converted to empty std::function");
}
return f;
}
std::string test_dummy_function(const std::function<int(int)> &f) {
using fn_type = int (*)(int);
auto result = f.target<fn_type>();
if (!result) {
auto r = f(1);
return "can't convert to function pointer: eval(1) = " + std::to_string(r);
} else if (*result == dummy_function) {
auto r = (*result)(1);
return "matches dummy_function: eval(1) = " + std::to_string(r);
} else {
return "argument does NOT match dummy_function. This should never happen!";
}
}
struct Payload {
Payload() {
print_default_created(this);
}
~Payload() {
print_destroyed(this);
}
Payload(const Payload &) {
print_copy_created(this);
}
Payload(Payload &&) {
print_move_created(this);
}
};
/// Something to trigger a conversion error
struct Unregistered {};
test_initializer callbacks([](py::module &m) {
m.def("test_callback1", &test_callback1);
m.def("test_callback2", &test_callback2);
m.def("test_callback3", &test_callback3);
m.def("test_callback4", &test_callback4);
m.def("test_callback5", &test_callback5);
// Test keyword args and generalized unpacking
m.def("test_tuple_unpacking", [](py::function f) {
auto t1 = py::make_tuple(2, 3);
auto t2 = py::make_tuple(5, 6);
return f("positional", 1, *t1, 4, *t2);
});
m.def("test_dict_unpacking", [](py::function f) {
auto d1 = py::dict("key"_a="value", "a"_a=1);
auto d2 = py::dict();
auto d3 = py::dict("b"_a=2);
return f("positional", 1, **d1, **d2, **d3);
});
m.def("test_keyword_args", [](py::function f) {
return f("x"_a=10, "y"_a=20);
});
m.def("test_unpacking_and_keywords1", [](py::function f) {
auto args = py::make_tuple(2);
auto kwargs = py::dict("d"_a=4);
return f(1, *args, "c"_a=3, **kwargs);
});
m.def("test_unpacking_and_keywords2", [](py::function f) {
auto kwargs1 = py::dict("a"_a=1);
auto kwargs2 = py::dict("c"_a=3, "d"_a=4);
return f("positional", *py::make_tuple(1), 2, *py::make_tuple(3, 4), 5,
"key"_a="value", **kwargs1, "b"_a=2, **kwargs2, "e"_a=5);
});
m.def("test_unpacking_error1", [](py::function f) {
auto kwargs = py::dict("x"_a=3);
return f("x"_a=1, "y"_a=2, **kwargs); // duplicate ** after keyword
});
m.def("test_unpacking_error2", [](py::function f) {
auto kwargs = py::dict("x"_a=3);
return f(**kwargs, "x"_a=1); // duplicate keyword after **
});
m.def("test_arg_conversion_error1", [](py::function f) {
f(234, Unregistered(), "kw"_a=567);
});
m.def("test_arg_conversion_error2", [](py::function f) {
f(234, "expected_name"_a=Unregistered(), "kw"_a=567);
});
/* Test cleanup of lambda closure */
m.def("test_cleanup", []() -> std::function<void(void)> {
Payload p;
return [p]() {
/* p should be cleaned up when the returned function is garbage collected */
};
});
/* Test if passing a function pointer from C++ -> Python -> C++ yields the original pointer */
m.def("dummy_function", &dummy_function);
m.def("dummy_function2", &dummy_function2);
m.def("roundtrip", &roundtrip, py::arg("f"), py::arg("expect_none")=false);
m.def("test_dummy_function", &test_dummy_function);
// Export the payload constructor statistics for testing purposes:
m.def("payload_cstats", &ConstructorStats::get<Payload>);
});

98
resources/pybind11/tests/test_callbacks.py

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import pytest
def test_callbacks():
from functools import partial
from pybind11_tests import (test_callback1, test_callback2, test_callback3,
test_callback4, test_callback5)
def func1():
return "func1"
def func2(a, b, c, d):
return "func2", a, b, c, d
def func3(a):
return "func3({})".format(a)
assert test_callback1(func1) == "func1"
assert test_callback2(func2) == ("func2", "Hello", "x", True, 5)
assert test_callback1(partial(func2, 1, 2, 3, 4)) == ("func2", 1, 2, 3, 4)
assert test_callback1(partial(func3, "partial")) == "func3(partial)"
assert test_callback3(lambda i: i + 1) == "func(43) = 44"
f = test_callback4()
assert f(43) == 44
f = test_callback5()
assert f(number=43) == 44
def test_keyword_args_and_generalized_unpacking():
from pybind11_tests import (test_tuple_unpacking, test_dict_unpacking, test_keyword_args,
test_unpacking_and_keywords1, test_unpacking_and_keywords2,
test_unpacking_error1, test_unpacking_error2,
test_arg_conversion_error1, test_arg_conversion_error2)
def f(*args, **kwargs):
return args, kwargs
assert test_tuple_unpacking(f) == (("positional", 1, 2, 3, 4, 5, 6), {})
assert test_dict_unpacking(f) == (("positional", 1), {"key": "value", "a": 1, "b": 2})
assert test_keyword_args(f) == ((), {"x": 10, "y": 20})
assert test_unpacking_and_keywords1(f) == ((1, 2), {"c": 3, "d": 4})
assert test_unpacking_and_keywords2(f) == (
("positional", 1, 2, 3, 4, 5),
{"key": "value", "a": 1, "b": 2, "c": 3, "d": 4, "e": 5}
)
with pytest.raises(TypeError) as excinfo:
test_unpacking_error1(f)
assert "Got multiple values for keyword argument" in str(excinfo.value)
with pytest.raises(TypeError) as excinfo:
test_unpacking_error2(f)
assert "Got multiple values for keyword argument" in str(excinfo.value)
with pytest.raises(RuntimeError) as excinfo:
test_arg_conversion_error1(f)
assert "Unable to convert call argument" in str(excinfo.value)
with pytest.raises(RuntimeError) as excinfo:
test_arg_conversion_error2(f)
assert "Unable to convert call argument" in str(excinfo.value)
def test_lambda_closure_cleanup():
from pybind11_tests import test_cleanup, payload_cstats
test_cleanup()
cstats = payload_cstats()
assert cstats.alive() == 0
assert cstats.copy_constructions == 1
assert cstats.move_constructions >= 1
def test_cpp_function_roundtrip():
"""Test if passing a function pointer from C++ -> Python -> C++ yields the original pointer"""
from pybind11_tests import dummy_function, dummy_function2, test_dummy_function, roundtrip
assert test_dummy_function(dummy_function) == "matches dummy_function: eval(1) = 2"
assert test_dummy_function(roundtrip(dummy_function)) == "matches dummy_function: eval(1) = 2"
assert roundtrip(None, expect_none=True) is None
assert test_dummy_function(lambda x: x + 2) == "can't convert to function pointer: eval(1) = 3"
with pytest.raises(TypeError) as excinfo:
test_dummy_function(dummy_function2)
assert "incompatible function arguments" in str(excinfo.value)
with pytest.raises(TypeError) as excinfo:
test_dummy_function(lambda x, y: x + y)
assert any(s in str(excinfo.value) for s in ("missing 1 required positional argument",
"takes exactly 2 arguments"))
def test_function_signatures(doc):
from pybind11_tests import test_callback3, test_callback4
assert doc(test_callback3) == "test_callback3(arg0: Callable[[int], int]) -> str"
assert doc(test_callback4) == "test_callback4() -> Callable[[int], int]"

59
resources/pybind11/tests/test_chrono.cpp

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/*
tests/test_chrono.cpp -- test conversions to/from std::chrono types
Copyright (c) 2016 Trent Houliston <trent@houliston.me> and
Wenzel Jakob <wenzel.jakob@epfl.ch>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#include "pybind11_tests.h"
#include "constructor_stats.h"
#include <pybind11/chrono.h>
// Return the current time off the wall clock
std::chrono::system_clock::time_point test_chrono1() {
return std::chrono::system_clock::now();
}
// Round trip the passed in system clock time
std::chrono::system_clock::time_point test_chrono2(std::chrono::system_clock::time_point t) {
return t;
}
// Round trip the passed in duration
std::chrono::system_clock::duration test_chrono3(std::chrono::system_clock::duration d) {
return d;
}
// Difference between two passed in time_points
std::chrono::system_clock::duration test_chrono4(std::chrono::system_clock::time_point a, std::chrono::system_clock::time_point b) {
return a - b;
}
// Return the current time off the steady_clock
std::chrono::steady_clock::time_point test_chrono5() {
return std::chrono::steady_clock::now();
}
// Round trip a steady clock timepoint
std::chrono::steady_clock::time_point test_chrono6(std::chrono::steady_clock::time_point t) {
return t;
}
// Roundtrip a duration in microseconds from a float argument
std::chrono::microseconds test_chrono7(std::chrono::microseconds t) {
return t;
}
test_initializer chrono([] (py::module &m) {
m.def("test_chrono1", &test_chrono1);
m.def("test_chrono2", &test_chrono2);
m.def("test_chrono3", &test_chrono3);
m.def("test_chrono4", &test_chrono4);
m.def("test_chrono5", &test_chrono5);
m.def("test_chrono6", &test_chrono6);
m.def("test_chrono7", &test_chrono7);
});

116
resources/pybind11/tests/test_chrono.py

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def test_chrono_system_clock():
from pybind11_tests import test_chrono1
import datetime
# Get the time from both c++ and datetime
date1 = test_chrono1()
date2 = datetime.datetime.today()
# The returned value should be a datetime
assert isinstance(date1, datetime.datetime)
# The numbers should vary by a very small amount (time it took to execute)
diff = abs(date1 - date2)
# There should never be a days/seconds difference
assert diff.days == 0
assert diff.seconds == 0
# We test that no more than about 0.5 seconds passes here
# This makes sure that the dates created are very close to the same
# but if the testing system is incredibly overloaded this should still pass
assert diff.microseconds < 500000
def test_chrono_system_clock_roundtrip():
from pybind11_tests import test_chrono2
import datetime
date1 = datetime.datetime.today()
# Roundtrip the time
date2 = test_chrono2(date1)
# The returned value should be a datetime
assert isinstance(date2, datetime.datetime)
# They should be identical (no information lost on roundtrip)
diff = abs(date1 - date2)
assert diff.days == 0
assert diff.seconds == 0
assert diff.microseconds == 0
def test_chrono_duration_roundtrip():
from pybind11_tests import test_chrono3
import datetime
# Get the difference between two times (a timedelta)
date1 = datetime.datetime.today()
date2 = datetime.datetime.today()
diff = date2 - date1
# Make sure this is a timedelta
assert isinstance(diff, datetime.timedelta)
cpp_diff = test_chrono3(diff)
assert cpp_diff.days == diff.days
assert cpp_diff.seconds == diff.seconds
assert cpp_diff.microseconds == diff.microseconds
def test_chrono_duration_subtraction_equivalence():
from pybind11_tests import test_chrono4
import datetime
date1 = datetime.datetime.today()
date2 = datetime.datetime.today()
diff = date2 - date1
cpp_diff = test_chrono4(date2, date1)
assert cpp_diff.days == diff.days
assert cpp_diff.seconds == diff.seconds
assert cpp_diff.microseconds == diff.microseconds
def test_chrono_steady_clock():
from pybind11_tests import test_chrono5
import datetime
time1 = test_chrono5()
time2 = test_chrono5()
assert isinstance(time1, datetime.timedelta)
assert isinstance(time2, datetime.timedelta)
def test_chrono_steady_clock_roundtrip():
from pybind11_tests import test_chrono6
import datetime
time1 = datetime.timedelta(days=10, seconds=10, microseconds=100)
time2 = test_chrono6(time1)
assert isinstance(time2, datetime.timedelta)
# They should be identical (no information lost on roundtrip)
assert time1.days == time2.days
assert time1.seconds == time2.seconds
assert time1.microseconds == time2.microseconds
def test_floating_point_duration():
from pybind11_tests import test_chrono7
import datetime
# Test using 35.525123 seconds as an example floating point number in seconds
time = test_chrono7(35.525123)
assert isinstance(time, datetime.timedelta)
assert time.seconds == 35
assert 525122 <= time.microseconds <= 525123

68
resources/pybind11/tests/test_class_args.cpp

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/*
tests/test_class_args.cpp -- tests that various way of defining a class work
Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#include "pybind11_tests.h"
template <int N> class BreaksBase {};
template <int N> class BreaksTramp : public BreaksBase<N> {};
// These should all compile just fine:
typedef py::class_<BreaksBase<1>, std::unique_ptr<BreaksBase<1>>, BreaksTramp<1>> DoesntBreak1;
typedef py::class_<BreaksBase<2>, BreaksTramp<2>, std::unique_ptr<BreaksBase<2>>> DoesntBreak2;
typedef py::class_<BreaksBase<3>, std::unique_ptr<BreaksBase<3>>> DoesntBreak3;
typedef py::class_<BreaksBase<4>, BreaksTramp<4>> DoesntBreak4;
typedef py::class_<BreaksBase<5>> DoesntBreak5;
typedef py::class_<BreaksBase<6>, std::shared_ptr<BreaksBase<6>>, BreaksTramp<6>> DoesntBreak6;
typedef py::class_<BreaksBase<7>, BreaksTramp<7>, std::shared_ptr<BreaksBase<7>>> DoesntBreak7;
typedef py::class_<BreaksBase<8>, std::shared_ptr<BreaksBase<8>>> DoesntBreak8;
#define CHECK_BASE(N) static_assert(std::is_same<typename DoesntBreak##N::type, BreaksBase<N>>::value, \
"DoesntBreak" #N " has wrong type!")
CHECK_BASE(1); CHECK_BASE(2); CHECK_BASE(3); CHECK_BASE(4); CHECK_BASE(5); CHECK_BASE(6); CHECK_BASE(7); CHECK_BASE(8);
#define CHECK_ALIAS(N) static_assert(DoesntBreak##N::has_alias && std::is_same<typename DoesntBreak##N::type_alias, BreaksTramp<N>>::value, \
"DoesntBreak" #N " has wrong type_alias!")
#define CHECK_NOALIAS(N) static_assert(!DoesntBreak##N::has_alias && std::is_void<typename DoesntBreak##N::type_alias>::value, \
"DoesntBreak" #N " has type alias, but shouldn't!")
CHECK_ALIAS(1); CHECK_ALIAS(2); CHECK_NOALIAS(3); CHECK_ALIAS(4); CHECK_NOALIAS(5); CHECK_ALIAS(6); CHECK_ALIAS(7); CHECK_NOALIAS(8);
#define CHECK_HOLDER(N, TYPE) static_assert(std::is_same<typename DoesntBreak##N::holder_type, std::TYPE##_ptr<BreaksBase<N>>>::value, \
"DoesntBreak" #N " has wrong holder_type!")
CHECK_HOLDER(1, unique); CHECK_HOLDER(2, unique); CHECK_HOLDER(3, unique); CHECK_HOLDER(4, unique); CHECK_HOLDER(5, unique);
CHECK_HOLDER(6, shared); CHECK_HOLDER(7, shared); CHECK_HOLDER(8, shared);
// There's no nice way to test that these fail because they fail to compile; leave them here,
// though, so that they can be manually tested by uncommenting them (and seeing that compilation
// failures occurs).
// We have to actually look into the type: the typedef alone isn't enough to instantiate the type:
#define CHECK_BROKEN(N) static_assert(std::is_same<typename Breaks##N::type, BreaksBase<-N>>::value, \
"Breaks1 has wrong type!");
//// Two holder classes:
//typedef py::class_<BreaksBase<-1>, std::unique_ptr<BreaksBase<-1>>, std::unique_ptr<BreaksBase<-1>>> Breaks1;
//CHECK_BROKEN(1);
//// Two aliases:
//typedef py::class_<BreaksBase<-2>, BreaksTramp<-2>, BreaksTramp<-2>> Breaks2;
//CHECK_BROKEN(2);
//// Holder + 2 aliases
//typedef py::class_<BreaksBase<-3>, std::unique_ptr<BreaksBase<-3>>, BreaksTramp<-3>, BreaksTramp<-3>> Breaks3;
//CHECK_BROKEN(3);
//// Alias + 2 holders
//typedef py::class_<BreaksBase<-4>, std::unique_ptr<BreaksBase<-4>>, BreaksTramp<-4>, std::shared_ptr<BreaksBase<-4>>> Breaks4;
//CHECK_BROKEN(4);
//// Invalid option (not a subclass or holder)
//typedef py::class_<BreaksBase<-5>, BreaksTramp<-4>> Breaks5;
//CHECK_BROKEN(5);
//// Invalid option: multiple inheritance not supported:
//template <> struct BreaksBase<-8> : BreaksBase<-6>, BreaksBase<-7> {};
//typedef py::class_<BreaksBase<-8>, BreaksBase<-6>, BreaksBase<-7>> Breaks8;
//CHECK_BROKEN(8);
test_initializer class_args([](py::module &m) {
// Just test that this compiled okay
m.def("class_args_noop", []() {});
});

6
resources/pybind11/tests/test_class_args.py

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def test_class_args():
# There's basically nothing to test here; just make sure the code compiled and declared its definition
from pybind11_tests import class_args_noop
class_args_noop()

55
resources/pybind11/tests/test_constants_and_functions.cpp

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/*
tests/test_constants_and_functions.cpp -- global constants and functions, enumerations, raw byte strings
Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#include "pybind11_tests.h"
enum MyEnum { EFirstEntry = 1, ESecondEntry };
std::string test_function1() {
return "test_function()";
}
std::string test_function2(MyEnum k) {
return "test_function(enum=" + std::to_string(k) + ")";
}
std::string test_function3(int i) {
return "test_function(" + std::to_string(i) + ")";
}
py::bytes return_bytes() {
const char *data = "\x01\x00\x02\x00";
return std::string(data, 4);
}
std::string print_bytes(py::bytes bytes) {
std::string ret = "bytes[";
const auto value = static_cast<std::string>(bytes);
for (size_t i = 0; i < value.length(); ++i) {
ret += std::to_string(static_cast<int>(value[i])) + " ";
}
ret.back() = ']';
return ret;
}
test_initializer constants_and_functions([](py::module &m) {
m.attr("some_constant") = py::int_(14);
m.def("test_function", &test_function1);
m.def("test_function", &test_function2);
m.def("test_function", &test_function3);
py::enum_<MyEnum>(m, "MyEnum")
.value("EFirstEntry", EFirstEntry)
.value("ESecondEntry", ESecondEntry)
.export_values();
m.def("return_bytes", &return_bytes);
m.def("print_bytes", &print_bytes);
});

21
resources/pybind11/tests/test_constants_and_functions.py

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def test_constants():
from pybind11_tests import some_constant
assert some_constant == 14
def test_function_overloading():
from pybind11_tests import MyEnum, test_function
assert test_function() == "test_function()"
assert test_function(7) == "test_function(7)"
assert test_function(MyEnum.EFirstEntry) == "test_function(enum=1)"
assert test_function(MyEnum.ESecondEntry) == "test_function(enum=2)"
def test_bytes():
from pybind11_tests import return_bytes, print_bytes
assert print_bytes(return_bytes()) == "bytes[1 0 2 0]"

41
resources/pybind11/tests/test_copy_move_policies.cpp

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/*
tests/test_copy_move_policies.cpp -- 'copy' and 'move'
return value policies
Copyright (c) 2016 Ben North <ben@redfrontdoor.org>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#include "pybind11_tests.h"
template <typename derived>
struct empty {
static const derived& get_one() { return instance_; }
static derived instance_;
};
struct lacking_copy_ctor : public empty<lacking_copy_ctor> {
lacking_copy_ctor() {}
lacking_copy_ctor(const lacking_copy_ctor& other) = delete;
};
template <> lacking_copy_ctor empty<lacking_copy_ctor>::instance_ = {};
struct lacking_move_ctor : public empty<lacking_move_ctor> {
lacking_move_ctor() {}
lacking_move_ctor(const lacking_move_ctor& other) = delete;
lacking_move_ctor(lacking_move_ctor&& other) = delete;
};
template <> lacking_move_ctor empty<lacking_move_ctor>::instance_ = {};
test_initializer copy_move_policies([](py::module &m) {
py::class_<lacking_copy_ctor>(m, "lacking_copy_ctor")
.def_static("get_one", &lacking_copy_ctor::get_one,
py::return_value_policy::copy);
py::class_<lacking_move_ctor>(m, "lacking_move_ctor")
.def_static("get_one", &lacking_move_ctor::get_one,
py::return_value_policy::move);
});

15
resources/pybind11/tests/test_copy_move_policies.py

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import pytest
def test_lacking_copy_ctor():
from pybind11_tests import lacking_copy_ctor
with pytest.raises(RuntimeError) as excinfo:
lacking_copy_ctor.get_one()
assert "the object is non-copyable!" in str(excinfo.value)
def test_lacking_move_ctor():
from pybind11_tests import lacking_move_ctor
with pytest.raises(RuntimeError) as excinfo:
lacking_move_ctor.get_one()
assert "the object is neither movable nor copyable!" in str(excinfo.value)

53
resources/pybind11/tests/test_docstring_options.cpp

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/*
tests/test_docstring_options.cpp -- generation of docstrings and signatures
Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#include "pybind11_tests.h"
struct DocstringTestFoo {
int value;
void setValue(int v) { value = v; }
int getValue() const { return value; }
};
test_initializer docstring_generation([](py::module &m) {
{
py::options options;
options.disable_function_signatures();
m.def("test_function1", [](int, int) {}, py::arg("a"), py::arg("b"));
m.def("test_function2", [](int, int) {}, py::arg("a"), py::arg("b"), "A custom docstring");
options.enable_function_signatures();
m.def("test_function3", [](int, int) {}, py::arg("a"), py::arg("b"));
m.def("test_function4", [](int, int) {}, py::arg("a"), py::arg("b"), "A custom docstring");
options.disable_function_signatures().disable_user_defined_docstrings();
m.def("test_function5", [](int, int) {}, py::arg("a"), py::arg("b"), "A custom docstring");
{
py::options nested_options;
nested_options.enable_user_defined_docstrings();
m.def("test_function6", [](int, int) {}, py::arg("a"), py::arg("b"), "A custom docstring");
}
}
m.def("test_function7", [](int, int) {}, py::arg("a"), py::arg("b"), "A custom docstring");
{
py::options options;
options.disable_user_defined_docstrings();
py::class_<DocstringTestFoo>(m, "DocstringTestFoo", "This is a class docstring")
.def_property("value_prop", &DocstringTestFoo::getValue, &DocstringTestFoo::setValue, "This is a property docstring")
;
}
});

32
resources/pybind11/tests/test_docstring_options.py

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def test_docstring_options():
from pybind11_tests import (test_function1, test_function2, test_function3,
test_function4, test_function5, test_function6,
test_function7, DocstringTestFoo)
# options.disable_function_signatures()
assert not test_function1.__doc__
assert test_function2.__doc__ == "A custom docstring"
# options.enable_function_signatures()
assert test_function3.__doc__ .startswith("test_function3(a: int, b: int) -> None")
assert test_function4.__doc__ .startswith("test_function4(a: int, b: int) -> None")
assert test_function4.__doc__ .endswith("A custom docstring\n")
# options.disable_function_signatures()
# options.disable_user_defined_docstrings()
assert not test_function5.__doc__
# nested options.enable_user_defined_docstrings()
assert test_function6.__doc__ == "A custom docstring"
# RAII destructor
assert test_function7.__doc__ .startswith("test_function7(a: int, b: int) -> None")
assert test_function7.__doc__ .endswith("A custom docstring\n")
# Suppression of user-defined docstrings for non-function objects
assert not DocstringTestFoo.__doc__
assert not DocstringTestFoo.value_prop.__doc__

134
resources/pybind11/tests/test_eigen.cpp

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/*
tests/eigen.cpp -- automatic conversion of Eigen types
Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#include "pybind11_tests.h"
#include <pybind11/eigen.h>
#include <Eigen/Cholesky>
Eigen::VectorXf double_col(const Eigen::VectorXf& x)
{ return 2.0f * x; }
Eigen::RowVectorXf double_row(const Eigen::RowVectorXf& x)
{ return 2.0f * x; }
Eigen::MatrixXf double_mat_cm(const Eigen::MatrixXf& x)
{ return 2.0f * x; }
// Different ways of passing via Eigen::Ref; the first and second are the Eigen-recommended
Eigen::MatrixXd cholesky1(Eigen::Ref<Eigen::MatrixXd> &x) { return x.llt().matrixL(); }
Eigen::MatrixXd cholesky2(const Eigen::Ref<const Eigen::MatrixXd> &x) { return x.llt().matrixL(); }
Eigen::MatrixXd cholesky3(const Eigen::Ref<Eigen::MatrixXd> &x) { return x.llt().matrixL(); }
Eigen::MatrixXd cholesky4(Eigen::Ref<const Eigen::MatrixXd> &x) { return x.llt().matrixL(); }
Eigen::MatrixXd cholesky5(Eigen::Ref<Eigen::MatrixXd> x) { return x.llt().matrixL(); }
Eigen::MatrixXd cholesky6(Eigen::Ref<const Eigen::MatrixXd> x) { return x.llt().matrixL(); }
typedef Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor> MatrixXfRowMajor;
MatrixXfRowMajor double_mat_rm(const MatrixXfRowMajor& x)
{ return 2.0f * x; }
test_initializer eigen([](py::module &m) {
typedef Eigen::Matrix<float, 5, 6, Eigen::RowMajor> FixedMatrixR;
typedef Eigen::Matrix<float, 5, 6> FixedMatrixC;
typedef Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor> DenseMatrixR;
typedef Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic> DenseMatrixC;
typedef Eigen::SparseMatrix<float, Eigen::RowMajor> SparseMatrixR;
typedef Eigen::SparseMatrix<float> SparseMatrixC;
m.attr("have_eigen") = py::cast(true);
// Non-symmetric matrix with zero elements
Eigen::MatrixXf mat(5, 6);
mat << 0, 3, 0, 0, 0, 11, 22, 0, 0, 0, 17, 11, 7, 5, 0, 1, 0, 11, 0,
0, 0, 0, 0, 11, 0, 0, 14, 0, 8, 11;
m.def("double_col", &double_col);
m.def("double_row", &double_row);
m.def("double_mat_cm", &double_mat_cm);
m.def("double_mat_rm", &double_mat_rm);
m.def("cholesky1", &cholesky1);
m.def("cholesky2", &cholesky2);
m.def("cholesky3", &cholesky3);
m.def("cholesky4", &cholesky4);
m.def("cholesky5", &cholesky5);
m.def("cholesky6", &cholesky6);
// Returns diagonals: a vector-like object with an inner stride != 1
m.def("diagonal", [](const Eigen::Ref<const Eigen::MatrixXd> &x) { return x.diagonal(); });
m.def("diagonal_1", [](const Eigen::Ref<const Eigen::MatrixXd> &x) { return x.diagonal<1>(); });
m.def("diagonal_n", [](const Eigen::Ref<const Eigen::MatrixXd> &x, int index) { return x.diagonal(index); });
// Return a block of a matrix (gives non-standard strides)
m.def("block", [](const Eigen::Ref<const Eigen::MatrixXd> &x, int start_row, int start_col, int block_rows, int block_cols) {
return x.block(start_row, start_col, block_rows, block_cols);
});
// Returns a DiagonalMatrix with diagonal (1,2,3,...)
m.def("incr_diag", [](int k) {
Eigen::DiagonalMatrix<int, Eigen::Dynamic> m(k);
for (int i = 0; i < k; i++) m.diagonal()[i] = i+1;
return m;
});
// Returns a SelfAdjointView referencing the lower triangle of m
m.def("symmetric_lower", [](const Eigen::MatrixXi &m) {
return m.selfadjointView<Eigen::Lower>();
});
// Returns a SelfAdjointView referencing the lower triangle of m
m.def("symmetric_upper", [](const Eigen::MatrixXi &m) {
return m.selfadjointView<Eigen::Upper>();
});
m.def("fixed_r", [mat]() -> FixedMatrixR {
return FixedMatrixR(mat);
});
m.def("fixed_c", [mat]() -> FixedMatrixC {
return FixedMatrixC(mat);
});
m.def("fixed_passthrough_r", [](const FixedMatrixR &m) -> FixedMatrixR {
return m;
});
m.def("fixed_passthrough_c", [](const FixedMatrixC &m) -> FixedMatrixC {
return m;
});
m.def("dense_r", [mat]() -> DenseMatrixR {
return DenseMatrixR(mat);
});
m.def("dense_c", [mat]() -> DenseMatrixC {
return DenseMatrixC(mat);
});
m.def("dense_passthrough_r", [](const DenseMatrixR &m) -> DenseMatrixR {
return m;
});
m.def("dense_passthrough_c", [](const DenseMatrixC &m) -> DenseMatrixC {
return m;
});
m.def("sparse_r", [mat]() -> SparseMatrixR {
return Eigen::SparseView<Eigen::MatrixXf>(mat);
});
m.def("sparse_c", [mat]() -> SparseMatrixC {
return Eigen::SparseView<Eigen::MatrixXf>(mat);
});
m.def("sparse_passthrough_r", [](const SparseMatrixR &m) -> SparseMatrixR {
return m;
});
m.def("sparse_passthrough_c", [](const SparseMatrixC &m) -> SparseMatrixC {
return m;
});
});

135
resources/pybind11/tests/test_eigen.py

@ -0,0 +1,135 @@
import pytest
with pytest.suppress(ImportError):
import numpy as np
ref = np.array([[ 0, 3, 0, 0, 0, 11],
[22, 0, 0, 0, 17, 11],
[ 7, 5, 0, 1, 0, 11],
[ 0, 0, 0, 0, 0, 11],
[ 0, 0, 14, 0, 8, 11]])
def assert_equal_ref(mat):
np.testing.assert_array_equal(mat, ref)
def assert_sparse_equal_ref(sparse_mat):
assert_equal_ref(sparse_mat.todense())
@pytest.requires_eigen_and_numpy
def test_fixed():
from pybind11_tests import fixed_r, fixed_c, fixed_passthrough_r, fixed_passthrough_c
assert_equal_ref(fixed_c())
assert_equal_ref(fixed_r())
assert_equal_ref(fixed_passthrough_r(fixed_r()))
assert_equal_ref(fixed_passthrough_c(fixed_c()))
assert_equal_ref(fixed_passthrough_r(fixed_c()))
assert_equal_ref(fixed_passthrough_c(fixed_r()))
@pytest.requires_eigen_and_numpy
def test_dense():
from pybind11_tests import dense_r, dense_c, dense_passthrough_r, dense_passthrough_c
assert_equal_ref(dense_r())
assert_equal_ref(dense_c())
assert_equal_ref(dense_passthrough_r(dense_r()))
assert_equal_ref(dense_passthrough_c(dense_c()))
assert_equal_ref(dense_passthrough_r(dense_c()))
assert_equal_ref(dense_passthrough_c(dense_r()))
@pytest.requires_eigen_and_numpy
def test_nonunit_stride_from_python():
from pybind11_tests import double_row, double_col, double_mat_cm, double_mat_rm
counting_mat = np.arange(9.0, dtype=np.float32).reshape((3, 3))
first_row = counting_mat[0, :]
first_col = counting_mat[:, 0]
assert np.array_equal(double_row(first_row), 2.0 * first_row)
assert np.array_equal(double_col(first_row), 2.0 * first_row)
assert np.array_equal(double_row(first_col), 2.0 * first_col)
assert np.array_equal(double_col(first_col), 2.0 * first_col)
counting_3d = np.arange(27.0, dtype=np.float32).reshape((3, 3, 3))
slices = [counting_3d[0, :, :], counting_3d[:, 0, :], counting_3d[:, :, 0]]
for slice_idx, ref_mat in enumerate(slices):
assert np.array_equal(double_mat_cm(ref_mat), 2.0 * ref_mat)
assert np.array_equal(double_mat_rm(ref_mat), 2.0 * ref_mat)
@pytest.requires_eigen_and_numpy
def test_nonunit_stride_to_python():
from pybind11_tests import diagonal, diagonal_1, diagonal_n, block
assert np.all(diagonal(ref) == ref.diagonal())
assert np.all(diagonal_1(ref) == ref.diagonal(1))
for i in range(-5, 7):
assert np.all(diagonal_n(ref, i) == ref.diagonal(i)), "diagonal_n({})".format(i)
assert np.all(block(ref, 2, 1, 3, 3) == ref[2:5, 1:4])
assert np.all(block(ref, 1, 4, 4, 2) == ref[1:, 4:])
assert np.all(block(ref, 1, 4, 3, 2) == ref[1:4, 4:])
@pytest.requires_eigen_and_numpy
def test_eigen_ref_to_python():
from pybind11_tests import cholesky1, cholesky2, cholesky3, cholesky4, cholesky5, cholesky6
chols = [cholesky1, cholesky2, cholesky3, cholesky4, cholesky5, cholesky6]
for i, chol in enumerate(chols, start=1):
mymat = chol(np.array([[1, 2, 4], [2, 13, 23], [4, 23, 77]]))
assert np.all(mymat == np.array([[1, 0, 0], [2, 3, 0], [4, 5, 6]])), "cholesky{}".format(i)
@pytest.requires_eigen_and_numpy
def test_special_matrix_objects():
from pybind11_tests import incr_diag, symmetric_upper, symmetric_lower
assert np.all(incr_diag(7) == np.diag([1, 2, 3, 4, 5, 6, 7]))
asymm = np.array([[ 1, 2, 3, 4],
[ 5, 6, 7, 8],
[ 9, 10, 11, 12],
[13, 14, 15, 16]])
symm_lower = np.array(asymm)
symm_upper = np.array(asymm)
for i in range(4):
for j in range(i + 1, 4):
symm_lower[i, j] = symm_lower[j, i]
symm_upper[j, i] = symm_upper[i, j]
assert np.all(symmetric_lower(asymm) == symm_lower)
assert np.all(symmetric_upper(asymm) == symm_upper)
@pytest.requires_eigen_and_numpy
def test_dense_signature(doc):
from pybind11_tests import double_col, double_row, double_mat_rm
assert doc(double_col) == "double_col(arg0: numpy.ndarray[float32[m, 1]]) -> numpy.ndarray[float32[m, 1]]"
assert doc(double_row) == "double_row(arg0: numpy.ndarray[float32[1, n]]) -> numpy.ndarray[float32[1, n]]"
assert doc(double_mat_rm) == "double_mat_rm(arg0: numpy.ndarray[float32[m, n]]) -> numpy.ndarray[float32[m, n]]"
@pytest.requires_eigen_and_scipy
def test_sparse():
from pybind11_tests import sparse_r, sparse_c, sparse_passthrough_r, sparse_passthrough_c
assert_sparse_equal_ref(sparse_r())
assert_sparse_equal_ref(sparse_c())
assert_sparse_equal_ref(sparse_passthrough_r(sparse_r()))
assert_sparse_equal_ref(sparse_passthrough_c(sparse_c()))
assert_sparse_equal_ref(sparse_passthrough_r(sparse_c()))
assert_sparse_equal_ref(sparse_passthrough_c(sparse_r()))
@pytest.requires_eigen_and_scipy
def test_sparse_signature(doc):
from pybind11_tests import sparse_passthrough_r, sparse_passthrough_c
assert doc(sparse_passthrough_r) == "sparse_passthrough_r(arg0: scipy.sparse.csr_matrix[float32]) -> scipy.sparse.csr_matrix[float32]"
assert doc(sparse_passthrough_c) == "sparse_passthrough_c(arg0: scipy.sparse.csc_matrix[float32]) -> scipy.sparse.csc_matrix[float32]"

68
resources/pybind11/tests/test_enum.cpp

@ -0,0 +1,68 @@
/*
tests/test_enums.cpp -- enumerations
Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#include "pybind11_tests.h"
enum UnscopedEnum {
EOne = 1,
ETwo
};
enum class ScopedEnum {
Two = 2,
Three
};
enum Flags {
Read = 4,
Write = 2,
Execute = 1
};
class ClassWithUnscopedEnum {
public:
enum EMode {
EFirstMode = 1,
ESecondMode
};
static EMode test_function(EMode mode) {
return mode;
}
};
std::string test_scoped_enum(ScopedEnum z) {
return "ScopedEnum::" + std::string(z == ScopedEnum::Two ? "Two" : "Three");
}
test_initializer enums([](py::module &m) {
m.def("test_scoped_enum", &test_scoped_enum);
py::enum_<UnscopedEnum>(m, "UnscopedEnum", py::arithmetic())
.value("EOne", EOne)
.value("ETwo", ETwo)
.export_values();
py::enum_<ScopedEnum>(m, "ScopedEnum", py::arithmetic())
.value("Two", ScopedEnum::Two)
.value("Three", ScopedEnum::Three);
py::enum_<Flags>(m, "Flags", py::arithmetic())
.value("Read", Flags::Read)
.value("Write", Flags::Write)
.value("Execute", Flags::Execute)
.export_values();
py::class_<ClassWithUnscopedEnum> exenum_class(m, "ClassWithUnscopedEnum");
exenum_class.def_static("test_function", &ClassWithUnscopedEnum::test_function);
py::enum_<ClassWithUnscopedEnum::EMode>(exenum_class, "EMode")
.value("EFirstMode", ClassWithUnscopedEnum::EFirstMode)
.value("ESecondMode", ClassWithUnscopedEnum::ESecondMode)
.export_values();
});

108
resources/pybind11/tests/test_enum.py

@ -0,0 +1,108 @@
import pytest
def test_unscoped_enum():
from pybind11_tests import UnscopedEnum, EOne
assert str(UnscopedEnum.EOne) == "UnscopedEnum.EOne"
assert str(UnscopedEnum.ETwo) == "UnscopedEnum.ETwo"
assert str(EOne) == "UnscopedEnum.EOne"
# no TypeError exception for unscoped enum ==/!= int comparisons
y = UnscopedEnum.ETwo
assert y == 2
assert y != 3
assert int(UnscopedEnum.ETwo) == 2
assert str(UnscopedEnum(2)) == "UnscopedEnum.ETwo"
# order
assert UnscopedEnum.EOne < UnscopedEnum.ETwo
assert UnscopedEnum.EOne < 2
assert UnscopedEnum.ETwo > UnscopedEnum.EOne
assert UnscopedEnum.ETwo > 1
assert UnscopedEnum.ETwo <= 2
assert UnscopedEnum.ETwo >= 2
assert UnscopedEnum.EOne <= UnscopedEnum.ETwo
assert UnscopedEnum.EOne <= 2
assert UnscopedEnum.ETwo >= UnscopedEnum.EOne
assert UnscopedEnum.ETwo >= 1
assert not (UnscopedEnum.ETwo < UnscopedEnum.EOne)
assert not (2 < UnscopedEnum.EOne)
def test_scoped_enum():
from pybind11_tests import ScopedEnum, test_scoped_enum
assert test_scoped_enum(ScopedEnum.Three) == "ScopedEnum::Three"
z = ScopedEnum.Two
assert test_scoped_enum(z) == "ScopedEnum::Two"
# expected TypeError exceptions for scoped enum ==/!= int comparisons
with pytest.raises(TypeError):
assert z == 2
with pytest.raises(TypeError):
assert z != 3
# order
assert ScopedEnum.Two < ScopedEnum.Three
assert ScopedEnum.Three > ScopedEnum.Two
assert ScopedEnum.Two <= ScopedEnum.Three
assert ScopedEnum.Two <= ScopedEnum.Two
assert ScopedEnum.Two >= ScopedEnum.Two
assert ScopedEnum.Three >= ScopedEnum.Two
def test_implicit_conversion():
from pybind11_tests import ClassWithUnscopedEnum
assert str(ClassWithUnscopedEnum.EMode.EFirstMode) == "EMode.EFirstMode"
assert str(ClassWithUnscopedEnum.EFirstMode) == "EMode.EFirstMode"
f = ClassWithUnscopedEnum.test_function
first = ClassWithUnscopedEnum.EFirstMode
second = ClassWithUnscopedEnum.ESecondMode
assert f(first) == 1
assert f(first) == f(first)
assert not f(first) != f(first)
assert f(first) != f(second)
assert not f(first) == f(second)
assert f(first) == int(f(first))
assert not f(first) != int(f(first))
assert f(first) != int(f(second))
assert not f(first) == int(f(second))
# noinspection PyDictCreation
x = {f(first): 1, f(second): 2}
x[f(first)] = 3
x[f(second)] = 4
# Hashing test
assert str(x) == "{EMode.EFirstMode: 3, EMode.ESecondMode: 4}"
def test_binary_operators():
from pybind11_tests import Flags
assert int(Flags.Read) == 4
assert int(Flags.Write) == 2
assert int(Flags.Execute) == 1
assert int(Flags.Read | Flags.Write | Flags.Execute) == 7
assert int(Flags.Read | Flags.Write) == 6
assert int(Flags.Read | Flags.Execute) == 5
assert int(Flags.Write | Flags.Execute) == 3
assert int(Flags.Write | 1) == 3
state = Flags.Read | Flags.Write
assert (state & Flags.Read) != 0
assert (state & Flags.Write) != 0
assert (state & Flags.Execute) == 0
assert (state & 1) == 0
state2 = ~state
assert state2 == -7
assert int(state ^ state2) == -1

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