PyStan on Windows

PyStan is partially supported under Windows with the following caveats:

  • Python 2.7: Doesn’t support parallel sampling. When drawing samples n_jobs=1 must be used)
  • Python 3.5 or higher: Parallel sampling is supported
  • MSVC compiler is not supported.

PyStan requires a working C++ compiler. Configuring such a compiler is typically the most challenging step in getting PyStan running.

PyStan is tested against the mingw-w64 compiler which works on both Python versions (2.7, 3.x) and supports x86 and x64.

Due to problems with MSVC template deduction, functions with Eigen library are failing. Until this and other bugs are fixed no support is provided for Windows + MSVC. Currently, no fix is known for this problem, other than to change the compiler to GCC or clang-cl.

Installing Python

There several ways of installing PyStan on Windows. The following instructions assume you have installed Python as packaged in the Anaconda Python distribution or Miniconda distribution. The Anaconda distribution is well-maintained and includes packages such as Numpy which PyStan requires. The following instructions assume that you are using Windows 7 (Windows 10 disregards user choice and user privacy).

Open Command prompt

All the following commands are written in a command line prompt. You can use one like Anaconda Prompt if you installed Python using Anaconda in the previous step, or Command Prompt which comes with Windows.

Test that the conda package manager is properly installed by typing:

conda info

To update conda package manager to the latest version:

conda update conda

Create a conda virtual environment (optional)

It is a good practice to keep specific projects on their on conda virtual environments to prevent unnecessary package collisions. Create a new conda environment with:

conda create -n stan_env python=3.7

where stan_env is the name of the environment.

After this activate environment with:

conda activate stan_env

or if your conda doesn’t include conda activate use:

activate stan_env

To close the environment type:


Installing C++ compiler

There are several ways to install mingw-w64 compiler toolchain, but in these instructions install compiler with conda package manager which comes with the Anaconda package.

To install mingw-w64 compiler type:

conda install libpython m2w64-toolchain -c msys2

This will install

libpython setups automatically distutils.cfg file, but if that is failed use the following instructions to setup it manually

In PYTHONPATH\\Lib\\distutils create a distutils.cfg file with a text editor (e.g. Notepad) and add the following lines:


To find the correct distutils path, run the following lines in python:

>>> import distutils
>>> print(distutils.__file__)

Install dependencies

It is recommended that on Windows the dependencies are installed with conda and the conda-forge channel. Required dependencies are numpy and cython:

conda install numpy cython -c conda-forge

Optional dependencies are matplotlib, scipy and pandas:

conda install matplotlib scipy pandas -c conda-forge

Installing PyStan

You can install PyStan with either pip (recommended) or conda:

pip install pystan
conda install pystan -c conda-forge

You can verify that everything was installed successfully by opening up the Python terminal (run python from a command prompt) and drawing samples from a very simple model:

>>> import pystan
>>> model_code = 'parameters {real y;} model {y ~ normal(0,1);}'
>>> model = pystan.StanModel(model_code=model_code)
>>> y = model.sampling().extract()['y']
>>> y.mean()  # with luck the result will be near 0


With conda:

conda install numpy cython matplotlib scipy pandas pystan -c conda-forge

With pip:

conda install numpy cython matplotlib scipy pandas -c conda-forge
pip install pystan