SymPy: Symbolic computing in Python

@article{Meurer2016SymPySC,
  title={SymPy: Symbolic computing in Python},
  author={Aaron Meurer and Christopher P. Smith and Mateusz Paprocki and Ondrej Cert{\'i}k and Sergey B. Kirpichev and Matthew Rocklin and Amit Kumar and Sergiu Ivanov and Jason Keith Moore and Sartaj Singh and Thilina Rathnayake and Sean Vig and Brian E. Granger and Richard P. Muller and Francesco Bonazzi and Harsh Gupta and Shivam Vats and Fredrik Johansson and Fabian Pedregosa and Matthew J. Curry and Andy R. Terrel and {\vS}těp{\'a}n Rou{\vc}ka and Ashutosh Saboo and Isuru Fernando and Sumith Kulal and Robert Cimrman and Anthony M. Scopatz},
  journal={PeerJ Prepr.},
  year={2016},
  volume={4},
  pages={e2083}
}
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 the standard 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… 
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