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  SymPy : symbolic computing in Python

Meurer, A., Smith, C. P., Paprocki, M., Čertík, O., Kirpichev, S. B., Rocklin, M., et al. (2017). SymPy: symbolic computing in Python. PeerJ Computer Science, 3: e103. doi:10.7717/peerj-cs.103.

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 Creators:
Meurer, Aaron, Author
Smith, Christopher P., Author
Paprocki, Mateusz, Author
Čertík, Ondřej, Author
Kirpichev, Sergey B., Author
Rocklin, Matthew, Author
Kumar, AMiT, Author
Ivanov, Sergiu, Author
Moore, Jason K., Author
Singh, Sartaj, Author
Rathnayake, Thilina, Author
Vig, Sean, Author
Granger, Brian E., Author
Muller, Richard P., Author
Bonazzi, Francesco1, Author              
Gupta, Harsh, Author
Vats, Shivam, Author
Johansson, Fredrik, Author
Pedregosa, Fabian, Author
Curry, Matthew J., Author
Terrel, Andy R., AuthorRoučka, Štěpán, AuthorSaboo, Ashutosh, AuthorFernando, Isuru, AuthorKulal, Sumith, AuthorCimrman, Robert, AuthorScopatz, Anthony, AuthorHigham, Nick, Contributor more..
Affiliations:
1Thomas Weikl, Theorie & Bio-Systeme, Max Planck Institute of Colloids and Interfaces, Max Planck Society, ou_1863330              

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Free keywords: Python, Computer algebra system, Symbolics, Open Access
 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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 Dates: 2017
 Publication Status: Published in print
 Pages: -
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 Rev. Type: -
 Identifiers: DOI: 10.7717/peerj-cs.103
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Title: PeerJ Computer Science
  Alternative Title : PeerJ Computer Science
Source Genre: Journal
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Publ. Info: San Diego, CA : PeerJ
Pages: - Volume / Issue: 3 Sequence Number: e103 Start / End Page: - Identifier: ISBN: 2376-5992