The following features must be enabled by including 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.

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.

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:

py::cpp_function func_cpp() {
    return py::cpp_function([](int i) { return i+1; },

After including the extra header file pybind11/functional.h, it is almost trivial to generate binding code for all of these functions.

#include <pybind11/functional.h>

PYBIND11_MODULE(example, m) {
    m.def("func_arg", &func_arg);
    m.def("func_ret", &func_ret);
    m.def("func_cpp", &func_cpp);

The following interactive session shows how to call them from Python.

$ python
>>> import example
>>> def square(i):
...     return i * i
>>> example.func_arg(square)
>>> square_plus_1 = example.func_ret(square)
>>> square_plus_1(4)
>>> plus_1 = func_cpp()
>>> plus_1(number=43)


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 tests/test_callbacks.cpp.


This functionality is very useful when generating bindings for callbacks in C++ libraries (e.g. GUI libraries, asynchronous networking libraries, etc.).

The file tests/test_callbacks.cpp contains a complete example that demonstrates how to work with callbacks and anonymous functions in more detail.