Detailed Installation Instructions

The following is addressed to an audience who is just getting started with Python and would benefit from additional guidance on how to install PyStan.

Installing PyStan requires installing:

  • Python
  • C++ -compiler
  • Python dependencies
  • PyStan

Prerequisite knowledge

It is highly recommended to know what bash is and the basics of navigating the terminal. You can review or learn it from the Software Carpentry (bash lesson here).

Lessons 1 - 3 are probably the most important.

Installing Python

The easiest way to install Python is to use the Anaconda distribution of python. It can be downloaded here.

This is because PyStan (and many python tools) require packages (aka modules) that have C dependencies. These types of dependencies are unable to be installed (at least easily) using pip, which is a common way to install python packages. Anaconda ships with it’s own package manager (that also plays nicely with pip) called conda, and comes with many of the data analytics packages and dependencies pre-installed.

Don’t worry about Anaconda ruining your current Python installation, it can be easily uninstalled (described below).

Anaconda is not a requirement

Anaconda is not an absolute requirement to get pystan to work. As long as you can get the necessary python dependencies installed, pystan will work. If you want to install Anaconda, follow the Windows, Macs, and Linux instructions below.


After downloading the installer execute the associated shell script. For example, if the file downloaded were named you would enter bash in the directory where you downloaded the file.


After downloading the installer, double click the .pkg file and follow the instructions on the screen. Use all of the defaults for installation.


PyStan on Windows is partially supported. See PyStan on Windows.

The Anaconda installer should be able to be double-clicked and installed. Use all of the defaults for installation except make sure to check Make Anaconda the default Python.

Uninstalling Anaconda

The default location for anaconda can be found in your home directory. Typically this means it in in the ~/anaconda or ~/anaconda3 directory when you open a terminal.

Python dependencies

If you used the Anaconda installer, numpy and cython should already be installed, so additional dependencies should not be needed. However, should you need to install additional dependencies, we can use conda to install them as such:

  • open a terminal
  • type conda install numpy to install numpy or replace numpy with the package you need to install
  • common additional packages include arviz, matplotlib, pandas, scipy

Setting up C++ compiler

PyStan 2.19+ needs a C++14 compatible compiler. For GCC 4.9.3+ and GCC 5+ versions are up-to-date. To update your compiler, follow general instructions given for each platform.

  • Linux: Install compiler with apt/yum
  • Macs: Install latest XCode, or use brew or macports
  • Windows: Follow instructions in PyStan on Windows.

To use gcc/clang compiler from the conda follow instructions in and set-up your CC and CXX environmental variables as given below. Instructions below assume default Anaconda environment. For conda-forge follow installation instructions in

  • open a terminal
  • Linux: conda install gcc_linux-64 gxx_linux-64 -c anaconda
  • Macs: conda install clang_osx-64 clangxx_osx-64 -c anaconda

To check your compiler version

  • Open a terminal
  • Linux: type gcc --version
  • OSX: type clang --version

To use specific C++ compiler (Linux: gcc_linux-64, gxx_linux-64, OSX: clang_osx-64, clangxx_osx-64), either update your CC and CXX environmental variables or set-up your path to include folder containing compilers (e.g.``which gcc_linux-64``)

  • type export CC=gcc_linux-64 and export CXX=g++_linux-64
  • type export PATH=/path/to/Anaconda/bin:$PATH

Conda will create a new name for the compiler. You’ll need to search in the <path to conda>/bin folder to find the name. which python will show this location. For example:

  • Open a terminal
  • OSX: type ls <path to python env>/bin/ | grep clang

You should see two compilers like x86_64-apple-darwin13.4.0-clang and x86_64-apple-darwin13.4.0-clang++.

  • type export CC=x86_64-apple-darwin13.4.0-clang and export CXX=x86_64-apple-darwin13.4.0-clang++

Installing PyStan

Since we have the numpy and cython dependencies we need, we can install the latest version of PyStan using pip. To do so:

  • open a terminal
  • type pip install pystan