By using numpy, etc. you're basically _not_ using the interpreter because you're using C/C++/fortran code that's been compiled with python bindings. To combine

By using numpy, etc. you're basically _not_ using the interpreter because you're using C/C++/fortran code that's been compiled with python bindings. To combine both your points, the best approach (if you like python) is to stick with python due to is ease of development and use libraries such as numpy as far as possible. However, if your use case is CPU bound but not served by those libraries, then you'll either need to develop your own extensions or throw away the interpreter altogether (and go with a different language).