.. _installation: Installation ------------ The SymPy CAS can be installed on virtually any computer with Python 2.7 or above. SymPy does require `mpmath`_ Python library to be installed first. The recommended method of installation is through Anaconda, which includes mpmath, as well as several other useful libraries. Alternatively, some Linux distributions have SymPy packages available. SymPy officially supports Python 2.7, 3.4, 3.5, 3.6 and PyPy. Anaconda ======== `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 Git === 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 https://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:: python setupegg.py develop This will cause the installed version to always point to the version in the git directory. Other Methods ============= You may also install SymPy using pip or from source. In addition, most Linux and Python distributions have some SymPy version available to install using their package manager. Here is a list of several such Python distributions: * `Anaconda `_ * `Enthought Canopy `_ * `ActivePython `_ * `Spack `_ Run SymPy ========= 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 :ref:`tutorial`. Mpmath ====== 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. Questions ========= If you have a question about installation or SymPy in general, feel free to visit our chat on `Gitter`_. In addition, our `mailing list`_ is an excellent source of community support. If you think there's a bug or you would like to request a feature, please open an `issue ticket`_. .. _downloads site: https://github.com/sympy/sympy/releases .. _Gitter: https://gitter.im/sympy/sympy .. _issue ticket: https://github.com/sympy/sympy/issues .. _mailing list: https://groups.google.com/forum/#!forum/sympy .. _mpmath: http://mpmath.org/