Interfacing Python with C: A Comprehensive Guide

Python's popularity is not only due to its simplicity and readability but also its ability to interface with lower-level languages like C and C++. This capability allows Python to leverage the speed and efficiency of these languages for performance-critical tasks. In this blog post, we will explore various methods to interface Python with C and C++, including writing Python bindings for a C++ library, using the Python/C API, Cython, and ctypes.

Why Interface Python with C/C++?

Performance: C and C++ are highly efficient languages. Critical sections of code can be implemented in C/C++ and then called from Python, resulting in significant performance gains.

Existing Libraries: Many powerful libraries are written in C/C++. By interfacing Python with these libraries, you can leverage their functionality without rewriting them.

System Programming: C and C++ offer low-level access to system resources, which can be useful for certain applications.

Methods to Interface Python with C/C++

1. Writing Python Bindings for a C++ Library

To interface Python with a C++ library, we can use tools like pybind11 or Boost.Python.

Using `pybind11`

pybind11 is a lightweight header-only library that exposes C++ types in Python and vice versa.

Example:

First, let's consider a simple C++ class:


// example.cpp
#include <pybind11/pybind11.h>

class Example {
public:
    Example(int value) : value(value) {}
    void setValue(int value) { this->value = value; }
    int getValue() const { return value; }
private:
    int value;
};

PYBIND11_MODULE(example, m) {
    pybind11::class_<Example>(m, "Example")
        .def(pybind11::init<int>())
        .def("setValue", &Example::setValue)
        .def("getValue", &Example::getValue);
}

To compile the module, use:


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

Now, you can use this C++ class in Python:


import example

obj = example.Example(42)
print(obj.getValue())  # Output: 42
obj.setValue(84)
print(obj.getValue())  # Output: 84

2. Using the Python/C API

The Python/C API provides a way to write Python extension modules in C. These modules can be imported and used in Python code.

Example:


// example.c
#include <Python.h>

static PyObject* hello(PyObject* self, PyObject* args) {
    printf("Hello, World!\\n");
    Py_RETURN_NONE;
}

static PyMethodDef ExampleMethods[] = {
    {"hello", hello, METH_VARARGS, "Print 'Hello, World!'"},
    {NULL, NULL, 0, NULL}
};

static struct PyModuleDef examplemodule = {
    PyModuleDef_HEAD_INIT,
    "example",
    NULL,
    -1,
    ExampleMethods
};

PyMODINIT_FUNC PyInit_example(void) {
    return PyModule_Create(&examplemodule);
}

Compile the module:


python3 setup.py build_ext --inplace

setup.py:


from distutils.core import setup, Extension

module = Extension('example', sources=['example.c'])

setup(name='example',
      version='1.0',
      description='Example Module',
      ext_modules=[module])

Now, you can use this module in Python:


import example

example.hello()  # Output: Hello, World!

3. Using Cython

Cython is a language that makes writing C extensions for Python as easy as Python itself. It is essentially Python with C data types.

Example:


# example.pyx
def say_hello():
    print("Hello, World!")

Compile the Cython code:


python3 setup.py build_ext --inplace

setup.py:


from setuptools import setup
from Cython.Build import cythonize

setup(
    ext_modules = cythonize("example.pyx")
)

Now, you can use the Cython module in Python:


import example

example.say_hello()  # Output: Hello, World!

4. Using `ctypes`

ctypes is a foreign function library for Python that provides C compatible data types and allows calling functions in DLLs or shared libraries.

Example:

First, create a C library:


// example.c
#include <stdio.h>

void say_hello() {
    printf("Hello, World!\\n");
}

Compile it:


gcc -shared -o libexample.so -fPIC example.c

Now, use ctypes to call this function from Python:


import ctypes

example = ctypes.CDLL('./libexample.so')
example.say_hello()  # Output: Hello, World!

Summary

Method	Programming Language used to write the bindings	Programming Language that the library is used in	Programming Language of the library	Description	Performance	Ease of Use	Use Cases
Python/C API usage 1: extensions for Python Interpreter	Write in C/C++	Use in Python	C/C++	Directly writes Python extension modules in C	High	Moderate	Performance-critical applications, low-level system access
Python/C API usage 2: embed Python into a C/C++ application	Write in C/C++	Use in C/C++	Python	Run Python code within a C/C++ application	Moderate to High	Moderate	Applications requiring both C/C++ performance and Python flexibility
pybind11 or Boost.Python	Write in C++	Use in Python	C/C++	Header-only C++ library that creates Python bindings for C++ code	High	Easy	Interfacing with C++ libraries, performance-critical code
Cython	Write in Cython	Use in Python	C/C++	Superset of Python that compiles to C, allowing easy creation of C extensions	High	Easy	Performance-critical code, extending Python with C functions
ctypes	Write in Python	Use in Python	C/C++	Standard library for calling functions in DLLs/shared libraries from Python	Moderate to High	Easy to Moderate	Interfacing with existing C libraries, simple function calls

Interfacing Python with C and C++ opens up a world of possibilities by combining Python's simplicity with the performance and system-level access of C/C++. Whether you use the Python/C API, pybind11, Cython, or ctypes, you can extend Python's capabilities and optimize your applications. Each method has its strengths and use cases, so choose the one that best fits your project's requirements.

Interfacing Python with C: A Comprehensive Guide

Why Interface Python with C/C++?

Methods to Interface Python with C/C++

1. Writing Python Bindings for a C++ Library

Using pybind11

2. Using the Python/C API

3. Using Cython

4. Using ctypes

Summary

Using `pybind11`

4. Using `ctypes`