SymPy is an open-sourcePythonlibrary for symbolic computation. It provides computer algebra capabilities either as a standalone application, as a library to other applications, or live on the web as SymPy Live[2] or SymPy Gamma.[3] SymPy is simple to install and to inspect because it is written entirely in Python with few dependencies.[4][5][6] This ease of access combined with a simple and extensible code base in a well known language make SymPy a computer algebra system with a relatively low barrier to entry.
SymPy is free software and is licensed under the 3-clause BSD. The lead developers are Ondřej Čertík and Aaron Meurer. It was started in 2005 by Ondřej Čertík.[7]
Features
The SymPy library is split into a core with many optional modules.
Currently, the core of SymPy has around 260,000 lines of code[8] (it also includes a comprehensive set of self-tests: over 100,000 lines in 350 files as of version 0.7.5), and its capabilities include:[4][5][9][10][11]
SymEngine: a rewriting of SymPy's core in C++, in order to increase its performance. Work is currently in progress[as of?] to make SymEngine the underlying engine of Sage too.[14]
LaTeX Expression project: Easy LaTeX typesetting of algebraic expressions in symbolic form with automatic substitution and result computation.[21]
Symbolic statistical modeling: Adding statistical operations to complex physical models.[22]
Diofant: a fork of SymPy, started by Sergey B Kirpichev[23]
Dependencies
Since version 1.0, SymPy has the mpmath package as a dependency.
There are several optional dependencies that can enhance its capabilities:
gmpy: If gmpy is installed, SymPy's polynomial module will automatically use it for faster ground types. This can provide a several times boost in performance of certain operations.
matplotlib: If matplotlib is installed, SymPy can use it for plotting.
