# Write bindings

In order to use a C/C++ library in python, you need to write bindings for it.

# Manual bindings

pkpy uses an universal signature to wrap a function pointer as a python function or method that can be called in python code, i.e NativeFuncC.

typedef PyObject* (*NativeFuncC)(VM*, ArgsView);
  • The first argument is the pointer of VM instance.
  • The second argument is an array-like object indicates the arguments list. You can use [] operator to get the element and call size() to get the length of the array.
  • The return value is a PyObject*, which should not be nullptr. If there is no return value, return vm->None.

# Bind a function or method

Use vm->bind to bind a function or method.

  • PyObject* bind(PyObject*, const char* sig, NativeFuncC)
  • PyObject* bind(PyObject*, const char* sig, const char* docstring, NativeFuncC)

vm->bind(obj, "add(a: int, b: int) -> int", [](VM* vm, ArgsView args){
    int a = py_cast<int>(vm, args[0]);
    int b = py_cast<int>(vm, args[1]);
    return py_var(vm, a + b);

// or you can provide a docstring
    "add(a: int, b: int) -> int",
    "add two integers", [](VM* vm, ArgsView args){
    int a = py_cast<int>(vm, args[0]);
    int b = py_cast<int>(vm, args[1]);
    return py_var(vm, a + b);

# How to capture something

By default, the lambda being bound is a C function pointer, you cannot capture anything! The following example does not compile.

int x = 1;
vm->bind(obj, "f() -> int", [x](VM* vm, ArgsView args){
    // error: cannot capture 'x'
    return py_var(vm, x);

I do not encourage you to capture something in a lambda being bound because:

  1. Captured lambda runs slower and causes "code-bloat".
  2. Captured values are unsafe, especially for PyObject* as they could leak by accident.

However, there are 3 ways to capture something when you really need to. The most safe and elegant way is to subclass VM and add a member variable.

class YourVM : public VM{
    int x;
    YourVM() : VM() {}

int main(){
    YourVM* vm = new YourVM();
    vm->x = 1;
    vm->bind(obj, "f() -> int", [](VM* _vm, ArgsView args){
        // do a static_cast and you can get any extra members of YourVM
        YourVM* vm = static_cast<YourVM*>(_vm);
        return py_var(vm, vm->x);
    return 0;

The 2nd way is to use vm->bind's last parameter userdata, you can store a POD type smaller than 8 bytes. And use lambda_get_userdata<T>(args.begin()) to get it inside the lambda body.

int x = 1;
vm->bind(obj, "f() -> int", [](VM* vm, ArgsView args){
    // get the userdata
    int x = lambda_get_userdata<int>(args.begin());
    return py_var(vm, x);
}, x);  // capture x

The 3rd way is to change the macro PK_ENABLE_STD_FUNCTION in config.h:

#define PK_ENABLE_STD_FUNCTION 0   // => 1

Then you can use standard capture list in lambda.

# Bind a struct

Assume you have a struct Point declared as follows.

struct Point{
    int x;
    int y;

You can write a wrapper class wrapped__Point. Add PY_CLASS macro into your wrapper class and implement a static function _register.

Inside the _register function, do bind methods and properties.

PY_CLASS(T, mod, name)

// T is the struct type in cpp
// mod is the module name in python
// name is the class name in python

# Example

struct wrapped__Point{
    // special macro for wrapper class
    PY_CLASS(wrapped__Point, builtins, Point)
    //       ^T              ^module   ^name

    // wrapped value
    Point value;

    // special method _ returns a pointer of the wrapped value
    Point* _() { return &value; }

    // define default constructors
    wrapped__Point() = default;
    wrapped__Point(const wrapped__Point&) = default;

    // define wrapped constructor
    wrapped__Point(Point value){
        this->value = value;

    static void _register(VM* vm, PyObject* mod, PyObject* type){
        // optional macro to enable struct-like methods

        // wrap field x
        PY_FIELD(wrapped__Point, "x", _, x)
        // wrap field y
        PY_FIELD(wrapped__Point, "y", _, y)

        // __init__ method
        vm->bind(type, "__init__(self, x, y)", [](VM* vm, ArgsView args){
            wrapped__Point& self = _py_cast<wrapped__Point&>(vm, args[0]);
            self.value.x = py_cast<int>(vm, args[1]);
            self.value.y = py_cast<int>(vm, args[2]);
            return vm->None;

        // other custom methods
        // ...

int main(){
    VM* vm = new VM();
    // register the wrapper class somewhere
    wrapped__Point::register_class(vm, vm->builtins);

    // use the Point class
    vm->exec("a = Point(1, 2)");
    vm->exec("print(a.x)");         // 1
    vm->exec("print(a.y)");         // 2

    delete vm;
    return 0;

# Handle gc for container types

If your custom type stores PyObject* in its fields, you need to handle gc for them.

struct Container{
    PY_CLASS(Container, builtins, Container)

    PyObject* a;
    std::vector<PyObject*> b;
    // ...

Add a magic method _gc_mark() const to your custom type.

struct Container{
    PY_CLASS(Container, builtins, Container)

    PyObject* a;
    std::vector<PyObject*> b;
    // ...

    void _gc_mark() const{
        // mark a
        if(a) PK_OBJ_MARK(a);

        // mark elements in b
        for(PyObject* obj : b){
            if(obj) PK_OBJ_MARK(obj);

For global objects, use the callback in vm->heap.

void (*_gc_marker_ex)(VM*) = nullptr;

It will be invoked before a GC starts. So you can mark objects inside the callback to keep them alive.

# Others

You may see somewhere in the code that vm->bind_method<> or vm->bind_func<> is used. They are old style binding functions and are deprecated. It is recommended to use vm->bind.

For some magic methods, we provide specialized binding function. They do not take universal function pointer as argument. You need to provide the detailed Type object and the corresponding function pointer.

PyObject* f_add(VM* vm, PyObject* lhs, PyObject* rhs){
    int a = py_cast<int>(vm, lhs);
    int b = py_cast<int>(vm, rhs);
    return py_var(vm, a + b);

vm->bind__add__(vm->tp_int, f_add);

This specialized binding function has optimizations and result in better performance when calling from python code.

For example, vm->bind__add__ is preferred over vm->bind_method<1>(type, "__add__", ...).

# Automatic bindings

pkpy supports automatic binding generation only for C libraries. See pkpy-bindings for details.

It takes a C header file and generates a python module stub (*.pyi) and a C++ binding file (*.cpp).

# Further reading

See random.cpp for an example used by random module.

See collections.cpp for a modern implementation of collections.deque.