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

mkdir build
cd build
cmake ..
make check -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:

mkdir build
cd build
cmake ..
cmake --build . --config Release --target check

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 ...

See also

Advanced users who are already familiar with Boost.Python may want to skip the tutorial and look at the test cases in the 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:

#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:

int add(int i, int j) {
    return i + j;
}

For simplicity [1], we’ll put both this function and the binding code into a file named example.cpp with the following contents:

#include <pybind11/pybind11.h>

int add(int i, int j) {
    return i + j;
}

PYBIND11_MODULE(example, m) {
    m.doc() = "pybind11 example plugin"; // optional module docstring

    m.def("add", &add, "A function which adds two numbers");
}
[1]In practice, implementation and binding code will generally be located in separate files.

The PYBIND11_MODULE() macro creates a function that will be called when an import statement is issued from within Python. The module name (example) is given as the first macro argument (it should not be in quotes). The second argument (m) defines a variable of type py::module which is the main interface for creating bindings. The method module::def() generates binding code that exposes the add() function to Python.

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 Building with CMake. On Linux and Mac OS, the above example can be compiled using the following command

$ 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 Building with CMake for a detailed example of a suitable cross-platform CMake-based build system.

Assuming that the created file example.so (example.pyd on Windows) is located in the current directory, the following interactive Python session shows how to load and execute the example.

$ 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 arguments

With a simple modification code, it is possible to inform Python about the names of the arguments (“i” and “j” in this case).

m.def("add", &add, "A function which adds two numbers",
      py::arg("i"), py::arg("j"));

arg is one of several special tag classes which can be used to pass metadata into 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:

>>> import example
>>> example.add(i=1, j=2)
3L

The keyword names also appear in the function signatures within the documentation.

>>> 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:

// 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 _a suffix forms a C++11 literal which is equivalent to 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 arguments

Suppose now that the function to be bound has default arguments, e.g.:

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 arg:

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.

>>> 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:

// 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) are automatically converted when assigned as attributes, and can be explicitly converted using the function py::cast.

PYBIND11_MODULE(example, m) {
    m.attr("the_answer") = 42;
    py::object world = py::cast("World");
    m.attr("what") = world;
}

These are then accessible from Python:

>>> import example
>>> example.the_answer
42
>>> example.what
'World'

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 Type conversions section.