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.


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.


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:

cmake_minimum_required(VERSION 2.8.12)

pybind11_add_module(example example.cpp)

This assumes that the pybind11 repository is located in a subdirectory named pybind11 and that the code is located in a file named example.cpp. The CMake command add_subdirectory will import the pybind11 project which provides the pybind11_add_module function. It will take care of all the details needed to build a Python extension module on any platform.

A working sample project, including a way to invoke CMake from for PyPI integration, can be found in the [cmake_example] repository.

[cmake_example](1, 2)


To ease the creation of Python extension modules, pybind11 provides a CMake function with the following signature:

pybind11_add_module(<name> [MODULE | SHARED] [EXCLUDE_FROM_ALL]
                    [NO_EXTRAS] [SYSTEM] [THIN_LTO] source1 [source2 ...])

This function behaves very much like CMake’s builtin add_library (in fact, it’s a wrapper function around that command). It will add a library target called <name> to be built from the listed source files. In addition, it will take care of all the Python-specific compiler and linker flags as well as the OS- and Python-version-specific file extension. The produced target <name> can be further manipulated with regular CMake commands.

MODULE or SHARED may be given to specify the type of library. If no type is given, MODULE is used by default which ensures the creation of a Python-exclusive module. Specifying SHARED will create a more traditional dynamic library which can also be linked from elsewhere. EXCLUDE_FROM_ALL removes this target from the default build (see CMake docs for details).

Since pybind11 is a template library, pybind11_add_module adds compiler flags to ensure high quality code generation without bloat arising from long symbol names and duplication of code in different translation units. It sets default visibility to hidden, which is required for some pybind11 features and functionality when attempting to load multiple pybind11 modules compiled under different pybind11 versions. It also adds additional flags enabling LTO (Link Time Optimization) and strip unneeded symbols. See the FAQ entry for a more detailed explanation. These latter optimizations are never applied in Debug mode. If NO_EXTRAS is given, they will always be disabled, even in Release mode. However, this will result in code bloat and is generally not recommended.

By default, pybind11 and Python headers will be included with -I. In order to include pybind11 as system library, e.g. to avoid warnings in downstream code with warn-levels outside of pybind11’s scope, set the option SYSTEM.

As stated above, LTO is enabled by default. Some newer compilers also support different flavors of LTO such as ThinLTO. Setting THIN_LTO will cause the function to prefer this flavor if available. The function falls back to regular LTO if -flto=thin is not available.

Configuration variables

By default, pybind11 will compile modules with the C++14 standard, if available on the target compiler, falling back to C++11 if C++14 support is not available. Note, however, that this default is subject to change: future pybind11 releases are expected to migrate to newer C++ standards as they become available. To override this, the standard flag can be given explicitly in PYBIND11_CPP_STANDARD:

# Use just one of these:
# GCC/clang:
set(PYBIND11_CPP_STANDARD -std=c++11)
set(PYBIND11_CPP_STANDARD -std=c++14)
set(PYBIND11_CPP_STANDARD -std=c++1z) # Experimental C++17 support
set(PYBIND11_CPP_STANDARD /std:c++14)
set(PYBIND11_CPP_STANDARD /std:c++latest) # Enables some MSVC C++17 features

add_subdirectory(pybind11)  # or find_package(pybind11)

Note that this and all other configuration variables must be set before the call to add_subdirectory or find_package. The variables can also be set when calling CMake from the command line using the -D<variable>=<value> flag.

The target Python version can be selected by setting PYBIND11_PYTHON_VERSION or an exact Python installation can be specified with PYTHON_EXECUTABLE. For example:

# or
cmake -DPYTHON_EXECUTABLE=path/to/python ..

find_package vs. add_subdirectory

For CMake-based projects that don’t include the pybind11 repository internally, an external installation can be detected through find_package(pybind11). See the Config file docstring for details of relevant CMake variables.

cmake_minimum_required(VERSION 2.8.12)

find_package(pybind11 REQUIRED)
pybind11_add_module(example example.cpp)

Note that find_package(pybind11) will only work correctly if pybind11 has been correctly installed on the system, e. g. after downloading or cloning the pybind11 repository :

cd pybind11
mkdir build
cd build
cmake ..
make install

Once detected, the aforementioned pybind11_add_module can be employed as before. The function usage and configuration variables are identical no matter if pybind11 is added as a subdirectory or found as an installed package. You can refer to the same [cmake_example] repository for a full sample project – just swap out add_subdirectory for find_package.

Advanced: interface library target

When using a version of CMake greater than 3.0, pybind11 can additionally be used as a special interface library . The target pybind11::module is available with pybind11 headers, Python headers and libraries as needed, and C++ compile definitions attached. This target is suitable for linking to an independently constructed (through add_library, not pybind11_add_module) target in the consuming project.

cmake_minimum_required(VERSION 3.0)

find_package(pybind11 REQUIRED)  # or add_subdirectory(pybind11)

add_library(example MODULE main.cpp)
target_link_libraries(example PRIVATE pybind11::module)
set_target_properties(example PROPERTIES PREFIX "${PYTHON_MODULE_PREFIX}"
                                         SUFFIX "${PYTHON_MODULE_EXTENSION}")


Since pybind11 is a metatemplate library, it is crucial that certain compiler flags are provided to ensure high quality code generation. In contrast to the pybind11_add_module() command, the CMake interface library only provides the minimal set of parameters to ensure that the code using pybind11 compiles, but it does not pass these extra compiler flags (i.e. this is up to you).

These include Link Time Optimization (-flto on GCC/Clang/ICPC, /GL and /LTCG on Visual Studio) and .OBJ files with many sections on Visual Studio (/bigobj). The FAQ contains an explanation on why these are needed.

Embedding the Python interpreter

In addition to extension modules, pybind11 also supports embedding Python into a C++ executable or library. In CMake, simply link with the pybind11::embed target. It provides everything needed to get the interpreter running. The Python headers and libraries are attached to the target. Unlike pybind11::module, there is no need to manually set any additional properties here. For more information about usage in C++, see Embedding the interpreter.

cmake_minimum_required(VERSION 3.0)

find_package(pybind11 REQUIRED)  # or add_subdirectory(pybind11)

add_executable(example main.cpp)
target_link_libraries(example PRIVATE pybind11::embed)

Building manually

pybind11 is a header-only library, hence it is not necessary to link against any special libraries and there are no intermediate (magic) translation steps.

On Linux, you can compile an example such as the one given in Creating bindings for a simple function using the following command:

$ c++ -O3 -Wall -shared -std=c++11 -fPIC `python3 -m pybind11 --includes` example.cpp -o example`python3-config --extension-suffix`

The flags given here assume that you’re using Python 3. For Python 2, just change the executable appropriately (to python or python2).

The python3 -m pybind11 --includes command fetches the include paths for both pybind11 and Python headers. This assumes that pybind11 has been installed using pip or conda. If it hasn’t, you can also manually specify -I <path-to-pybind11>/include together with the Python includes path python3-config --includes.

Note that Python 2.7 modules don’t use a special suffix, so you should simply use instead of example`python3-config --extension-suffix`. Besides, the --extension-suffix option may or may not be available, depending on the distribution; in the latter case, the module extension can be manually set to .so.

On Mac OS: the build command is almost the same but it also requires passing the -undefined dynamic_lookup flag so as to ignore missing symbols when building the module:

$ c++ -O3 -Wall -shared -std=c++11 -undefined dynamic_lookup `python3 -m pybind11 --includes` example.cpp -o example`python3-config --extension-suffix`

In general, it is advisable to include several additional build parameters that can considerably reduce the size of the created binary. Refer to section Building with CMake for a detailed example of a suitable cross-platform CMake-based build system that works on all platforms including Windows.


On Linux and macOS, it’s better to (intentionally) not link against libpython. The symbols will be resolved when the extension library is loaded into a Python binary. This is preferable because you might have several different installations of a given Python version (e.g. the system-provided Python, and one that ships with a piece of commercial software). In this way, the plugin will work with both versions, instead of possibly importing a second Python library into a process that already contains one (which will lead to a segfault).

Generating binding code automatically

The Binder project is a tool for automatic generation of pybind11 binding code by introspecting existing C++ codebases using LLVM/Clang. See the [binder] documentation for details.