sympy: symbolic computing in python

sympy: symbolic computing in python

;Aaron Meurer;Christopher P. Smith;Mateusz Paprocki;Ondřej Čertík;Sergey B. Kirpichev;Matthew Rocklin;AMiT Kumar;Sergiu Ivanov;Jason K. Moore;Sartaj Singh;Thilina Rathnayake;Sean Vig;Brian E. Granger;Richard P. Muller;Francesco Bonazzi;Harsh Gupta;Shivam Vats;Fredrik Johansson;Fabian Pedregosa;Matthew J. Curry;Andy R. Terrel;Štěpán Roučka;Ashutosh Saboo;Isuru Fernando;Sumith Kulal;Robert Cimrman;Anthony Scopatz
social cognitive and affective neuroscience 2017 Vol. 3 pp. e103-
157
meurer2017peerjsympy:

Abstract

SymPy is an open source computer algebra system written in pure Python. It is built with a focus on extensibility and ease of use, through both interactive and programmatic applications. These characteristics have led SymPy to become a popular symbolic library for the scientific Python ecosystem. This paper presents the architecture of SymPy, a description of its features, and a discussion of select submodules. The supplementary material provide additional examples and further outline details of the architecture and features of SymPy.

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