> For the complete documentation index, see [llms.txt](https://syl1.gitbook.io/julia-language-a-concise-tutorial/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://syl1.gitbook.io/julia-language-a-concise-tutorial/useful-packages/14-sympy.md).

# SymPy

## SymPy

[`SymPy`](https://github.com/JuliaPy/SymPy.jl) is a wrapper to the Python SymPy library for symbolic computation: solve equations (or system of equations), simplify them, find derivates or integrals...

An overview of its capabilities can be found on the following notebook:

[http://nbviewer.jupyter.org/github/sylvaticus/juliatutorial/blob/master/assets/Symbolic computation.ipynb](http://nbviewer.jupyter.org/github/sylvaticus/juliatutorial/blob/master/assets/Symbolic%20computation.ipynb)

Some additional notes to that notebook:

* You can plot a function that includes symbols, e.g.:  `plot(2x,0,1)` plots `y=2x` in the \[0,1] range
* For the infinity symbol use either `oo` or `Inf` (eventually with + or -)

## Other Mathematical packages

* Numerical integration of definite integrals (univariate): ([QuadGK Package](https://github.com/JuliaMath/QuadGK.jl): `quadgk(x->2x,0,2)`)

*While an updated, expanded and revised version of this chapter is available in "Chapter 10 - Mathematical Libraries" of* [*Antonello Lobianco (2019), "Julia Quick Syntax Reference", Apress*](https://julia-book.com)*, this tutorial remains in active development.*


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