How can SciPy be fast if it is written in an interpreted language like Python? Actually, the time-critical loops are usually implemented in C or Fortran. Much

How can SciPy be fast if it is written in an interpreted language like Python? Actually, the time-critical loops are usually implemented in C or Fortran. Much of SciPy is a thin layer of code on top of the scientific routines that are freely available at http://www.netlib.org/ http://www.netlib.org/. Netlib is a huge repository of incredibly valuable and robust scientific algorithms written in C and Fortran. It would be silly to rewrite these algorithms and would take years to debug them. SciPy uses a variety of methods to generate “wrappers” around these algorithms so that they can be used in Python. Some wrappers were generated by hand coding them in C. The rest were generated using either SWIG or f2py. Some of the newer contributions to SciPy are either written entirely or wrapped with Cython. A second answer is that for difficult problems, a better algorithm can make a tremendous difference in the time it takes to solve a problem. So using scipy’s built-in algorithms may be much faster than a simple algorithm coded in C. http://www.scipy.org/scipylib/faq.html#how-can-scipy-be-fast-if-it-is-written-in-an-interpreted-language-like-python http://www.scipy.org/scipylib/faq.html#how-can-scipy-be-fast...