This is the source repository for the paper:
SymPy: symbolic computing in python
This paper has been published in PeerJ Computer Science and can be found at https://peerj.com/articles/cs-103/.
To cite this paper, please use
Meurer A, Smith CP, Paprocki M, Čertík O, Kirpichev SB, Rocklin M, Kumar A, Ivanov S, Moore JK, Singh S, Rathnayake T, Vig S, Granger BE, Muller RP, Bonazzi F, Gupta H, Vats S, Johansson F, Pedregosa F, Curry MJ, Terrel AR, Roučka Š, Saboo A, Fernando I, Kulal S, Cimrman R, Scopatz A. (2017) SymPy: symbolic computing in Python. PeerJ Computer Science 3:e103 https://doi.org/10.7717/peerj-cs.103
Here is the BibTeX entry.
@article{10.7717/peerj-cs.103,
title = {SymPy: symbolic computing in Python},
author = {Meurer, Aaron and Smith, Christopher P. and Paprocki, Mateusz and \v{C}ert\'{i}k, Ond\v{r}ej and Kirpichev, Sergey B. and Rocklin, Matthew and Kumar, AMiT and Ivanov, Sergiu and Moore, Jason K. and Singh, Sartaj and Rathnayake, Thilina and Vig, Sean and Granger, Brian E. and Muller, Richard P. and Bonazzi, Francesco and Gupta, Harsh and Vats, Shivam and Johansson, Fredrik and Pedregosa, Fabian and Curry, Matthew J. and Terrel, Andy R. and Rou\v{c}ka, \v{S}t\v{e}p\'{a}n and Saboo, Ashutosh and Fernando, Isuru and Kulal, Sumith and Cimrman, Robert and Scopatz, Anthony},
year = 2017,
month = jan,
keywords = {Python, Computer algebra system, Symbolics},
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.
},
volume = 3,
pages = {e103},
journal = {PeerJ Computer Science},
issn = {2376-5992},
url = {https://doi.org/10.7717/peerj-cs.103},
doi = {10.7717/peerj-cs.103}
}
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This repository contains or links to all of the information needed to reproduce the results in the paper.
The latest rendered version of the PDF can be viewed via the Travis build:
Latest pdf: paper-master.pdf
A preprint of this paper has been submitted to PeerJ.
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The contents of this repository are dual licensed under the Creative Commons
Attribution 4.0 International
License and the MIT
License. See the LICENSE file for
details.
Install a full LaTeX suite on your preferred operating system. To build the PDF type
make
in the source directory. This will produce paper.pdf, the main paper, and
supplement.pdf, the supplementary material.
Alternatively, you can use docker, see the instructions in our Dockerfile.
You can test all the examples in the paper with
make test
This requires that SymPy 1.0 (exactly) is installed.
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Substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work; AND
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Drafting the work or revising it critically for important intellectual content; AND
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Final approval of the version to be published; AND
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Anyone who satisfies and is willing to accept these responsibilities and commitments is welcome to be an author on this publication.