With Python, we can also run symbolic calculations using SymPy. SymPy is one of the Python libraries that allows users to perform symbolic mathematics. To learn basic features of SymPy, we look at the following resources:

  1. online lecture note 1 written by Dr. Fabian Pedregosa
  2. online lecture note 2, Sympy Lecture note
  3. Chapter 12 of Prof. Fangohr's note


SciPy is a Python package that contains numerous scientific toolboxes that are commonly used in scientific computing community. The SciPy toolboxes includes implementations of numerical interpolation, quadrature rules, optimization, image processing, statistics, special functions, etc. ScyPy offers a set of professionally tested and optimized numerical implementations of mathematical algorithms that are ready-to-use. To see examples of how to use SciPy for scientific computing:

  1. SciPy online note by Gaël Varoquaux, Adrien Chauve, Andre Espaze, Emmanuelle Gouillart, Ralf Gommers
  2. Chapter 16 of Prof. Fangohr's note