sympy: symbolic computing in python
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ID: 180359
2017
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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.
| Reference Key |
meurer2017peerjsympy:
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| Authors | ;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 |
| Journal | social cognitive and affective neuroscience |
| Year | 2017 |
| DOI |
10.7717/peerj-cs.103
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| URL | |
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