An Introduction to Python Programming for Scientists and Engineers

In Section 22.4.2, we mentioned just-in-time compilation tools such as cython and numba that enable us to write parts of our Python code in another language or convert our Python code into an optimized non-Python version. The goal with using cython and numba is to enable our Python code to run faster. There are times, however, when we have a collection of legacy Fortran or C++ routines – battle-tested and reliable – that we want to use “as-is” from inside Python. The code files already exist external to Python, so we want to compile and wrap them up and expose them to Python to use.