Symbolic Computation with Python and SymPy

SymPy is an open-source Computer Algebra System written in Python that enables the manipulation of mathematical expressions in an analytical form. It can be used in a variety of disciplines in engineering and science to perform common analytical computations such as differentiation and integration, simplifying and manipulating expressions for greater insight, solving algebraic and differential equations, plotting, mathematical modeling and more.

Advantages
Lightweight.
Cross-platform.
Customizable.
Flexible: great for interactive use or for building custom applications.
Disadvantages
Steep learning curve.
Missing features and limitations on current features.
Huge documentation.
Unexpected results and/or difficult-to-debug situations.


2 major approaches to learn SymPy

1
Tinkering with our specific mathematical problems and exploring the documentation as we need it.

2
Following the book Symbolic Computation with Python and SymPy


Get your own copy of

Symbolic Computation with Python and SymPy

Printed Book

Ebooks

NB: for publishing reasons, the printed book had to be splitted in two volumes. Vol 1 + Vol 2 = Printed Book.