This talk describes the principles for mixing native (C/C++) with Python, using real-world examples. We will demonstrate two typical use cases. Firstly, to speed up the critical part of Python applications (the reason why NumPy is preferred for heavy number crunching). Secondly, to reuse existing native libraries (plain C/C++, CUDA or OpenCL), thus potentially reduce the time-to-deliver.