SymPy: Symbolic computing in python

Meurer A.; Smith C.P.; Paprocki M.; Čertík O.; Kirpichev S.B.; Rocklin M.; Kumar A.; Ivanov S.; Moore J.K.; Singh S.; Rathnayake T.; Vig S.; Granger B.E.; Muller R.P.; Bonazzi F.; Gupta H.; Vats S.; Johansson F.; Pedregosa F.; Curry M.J.; Terrel A.R.; Roučka Š.; Saboo A.; Fernando I.; Kulal S.; Cimrman R.; Scopatz A.

doi:https://doi.org/10.7287/peerj.preprints.2083

SymPy: Symbolic computing in python

Authors

Meurer A.; Smith C.P.; Paprocki M.; Čertík O.; Kirpichev S.B.; Rocklin M.; Kumar A.; Ivanov S.; Moore J.K.; Singh S.; Rathnayake T.; Vig S.; Granger B.E.; Muller R.P.; Bonazzi F.; Gupta H.; Vats S.; Johansson F.; Pedregosa F.; Curry M.J.; Terrel A.R.; Roučka Š.; Saboo A.; Fernando I.; Kulal S.; Cimrman R.; Scopatz A.

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 domain specific submodules. The supplementary materials provide additional examples and further outline details of the architecture and features of SymPy. © 2017 PeerJ Inc.. All rights reserved.