SymPy: symbolic computing in Python

Aaron Meurer 1 Christopher Smith 2 Mateusz Paprocki 3 Ondřej Čertík 4 Sergey Kirpichev 5 Matthew Rocklin 3 Amit Kumar 6 Sergiu Ivanov 7 Jason Moore 8 Sartaj Singh 9 Thilina Rathnayake 10 Sean Vig 11 Brian Granger 12 Richard Muller 13 Francesco Bonazzi 14 Harsh Gupta 9 Shivam Vats 9 Fredrik Johansson 15 Fabian Pedregosa 16 Matthew Curry 17 Andy Terrel 18 Štěpán Roučka 19 Ashutosh Saboo 20 Isuru Fernando 10 Sumith Kulal 21 Robert Cimrman 22 Anthony Scopatz 1
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.
Type de document :
Article dans une revue
PeerJ Comput.Sci., 2017, 3, pp.e103. 〈10.7717/peerj-cs.103〉
Liste complète des métadonnées
Contributeur : Inspire Hep <>
Soumis le : jeudi 23 novembre 2017 - 11:01:10
Dernière modification le : jeudi 26 avril 2018 - 10:29:04

Lien texte intégral




Aaron Meurer, Christopher Smith, Mateusz Paprocki, Ondřej Čertík, Sergey Kirpichev, et al.. SymPy: symbolic computing in Python. PeerJ Comput.Sci., 2017, 3, pp.e103. 〈10.7717/peerj-cs.103〉. 〈hal-01645958〉



Consultations de la notice