The SymPy CAS can be installed on virtually any computer with Python 2.6 or above. SymPy does require mpmath Python library to be installed first. The current recommended method of installation is through Anaconda, which includes mpmath, as well as several other useful libraries. Alternatively, executables are available for Windows, and some Linux distributions have SymPy packages available.
SymPy officially supports Python 2.6, 2.7, 3.2, 3.3, 3.4, 3.5, and PyPy.
Anaconda is a free Python distribution from Continuum Analytics that includes SymPy, Matplotlib, IPython, NumPy, and many more useful packages for scientific computing. This is recommended because many nice features of SymPy are only enabled when certain libraries are installed. For example, without Matplotlib, only simple text-based plotting is enabled. With the IPython notebook or qtconsole, you can get nicer \(\LaTeX\) printing by running init_printing().
If you already have Anaconda and want to update SymPy to the latest version, use:
conda update sympy
If you wish to contribute to SymPy or like to get the latest updates as they come, install SymPy from git. To download the repository, execute the following from the command line:
git clone git://github.com/sympy/sympy.git
To update to the latest version, go into your repository and execute:
git pull origin master
If you want to install SymPy, but still want to use the git version, you can run from your repository:
This will cause the installed version to always point to the version in the git directory.
An installation executable (.exe) is available for Windows users at the downloads site. In addition, various Linux distributions have SymPy available as a package. You may also install SymPy from source or using pip.
After installation, it is best to verify that your freshly-installed SymPy works. To do this, start up Python and import the SymPy libraries:
$ python >>> from sympy import *
From here, execute some simple SymPy statements like the ones below:
>>> x = Symbol('x') >>> limit(sin(x)/x, x, 0) 1 >>> integrate(1/x, x) log(x)
For a starter guide on using SymPy effectively, refer to the SymPy Tutorial.
Versions of SymPy prior to 1.0 included mpmath, but it now depends on it as an external dependency. If you installed SymPy with Anaconda, it will already include mpmath. Use:
conda install mpmath
to ensure that it is installed.
If you do not wish to use Anaconda, you can use pip install mpmath.
If you use mpmath via sympy.mpmath in your code, you will need to change this to use just mpmath. If you depend on code that does this that you cannot easily change, you can work around it by doing:
import sys import mpmath sys.modules['sympy.mpmath'] = mpmath
before the code that imports sympy.mpmath. It is recommended to change code that uses sympy.mpmath to use mpmath directly wherever possible.