Interfacing Python with C/C++

Integrating Python with C/C++ opens up significant opportunities for improving the performance of your machine learning applications. As you work with increasingly sophisticated models and larger datasets, efficiency becomes critical. Python's simplicity and readability often come with limitations in execution speed, especially for computationally demanding tasks. By combining Python with C or C++, you can tap into the speed and capabilities of these compiled languages to optimize your code.

In this chapter, you'll look into the important techniques for interfacing Python with C/C++ to enhance performance. You'll investigate the use of native C libraries and the creation of Python extensions using C or C++. This knowledge allows you to execute critical sections of your code much faster while maintaining Python's overall simplicity for less intensive tasks. Additionally, you'll learn about the tools and libraries that facilitate this integration, such as Cython and the Python C API. By the end of this chapter, you'll be equipped with the skills to blend Python's ease of use with the raw capabilities of C/C++, creating high-performance applications that meet the demanding needs of modern machine learning.