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Pybind11 is an open-source C++ library that facilitates the seamless integration of C++ code with Python. It allows you to create Python bindings for C++ functions and classes, enabling you to call C++ code from Python and vice versa. Pybind11 is often used to extend Python with high-performance C++ libraries, wrap existing C++ libraries for Python use, or accelerate Python code by implementing critical parts in C++.

Here are some key features and aspects of Pybind11:

  1. Minimal Boilerplate: Pybind11 is designed to minimize the boilerplate code required to create Python bindings. This makes it easier to write and maintain the interface between C++ and Python.
  2. Automatic Type Conversion: It provides automatic type conversion between C++ and Python data types, reducing the complexity of dealing with data type conversions in the bindings.
  3. STL Support: Pybind11 has built-in support for the Standard Template Library (STL), allowing you to expose containers like vectors and maps to Python with relative ease.
  4. Header-Only Library: Pybind11 is a header-only library, meaning you don’t need to compile it separately; you include the Pybind11 headers in your C++ code, and it becomes part of your project.
  5. Cross-Platform: It is designed to be cross-platform and works on a variety of operating systems and C++ compilers.
  6. Pythonic Syntax: Pybind11 provides a Pythonic syntax for defining C++ functions and classes that can be exposed to Python. This makes the code more readable and maintains the look and feel of Python.
  7. Compatible with Python 2 and 3: Pybind11 is compatible with both Python 2 and Python 3, which can be essential when working with legacy codebases.

Here’s a simple example of how you can use Pybind11 to create a Python binding for a C++ function:

#include <pybind11/pybind11.h>

int add(int a, int b) {
    return a + b;

namespace py = pybind11;

PYBIND11_MODULE(my_module, m) {
    m.def("add", &add, "A function which adds two integers");

In this example, we define a C++ function add and use Pybind11 to expose it to Python as a module named my_module.

To build and use the Python module created with Pybind11, you typically compile it into a shared library (e.g., a .so or .pyd file) and then import it in your Python code.

Pybind11 has gained popularity in the scientific computing and data analysis communities because it allows for the efficient use of existing C++ libraries within Python-based workflows while maintaining the performance benefits of C++.

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