There are two different ways to install and use PySB:

  1. Install PySB natively on your computer (recommended).


  2. Download a Docker container with PySB and Jupyter Notebook. If you are familiar with Docker, PySB can be installed from the Docker Hub by typing docker pull pysb/pysb. Further details are below.


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Option 1: Install PySB natively on your computer

  1. Install Anaconda

    Our recommended approach is to use Anaconda, which is a distribution of Python containing most of the numeric and scientific software needed to get started. If you are a Mac or Linux user, have used Python before and are comfortable using pip to install software, you may want to skip this step and use your existing Python installation.

    Anaconda has a simple graphical installer which can be downloaded from - select your operating system and download the 64 bit version. From PySB 2.0, we only support Python 3.x (see the Frequently Asked Questions for specific version support). The default installer options are usually appropriate.

  2. Install PySB

    The installation is very straightforward with conda - type the following in a terminal:

    conda install -c alubbock pysb


    You may wish to use the Anaconda prompt, which sets up the Anaconda paths automatically, rather than the standard command prompt or terminal on your operating system. Otherwise, you may have to use the full path to the conda command each time, and may end up using the system version of Python, rather than the Anaconda one.


    You can also install PySB using pip, but in that case you will need to manually install BioNetGen into the default path for your platform (/usr/local/share/BioNetGen on Mac and Linux, c:\Program Files\BioNetGen on Windows), or set the BNGPATH environment variable to the BioNetGen path on your machine.

  3. Start Python and PySB

    If you installed Python using Anaconda on Windows, search for and select IPython from your Start Menu (Windows). Otherwise, open a terminal and type python to get started (or ipython, if installed).

    You will then be at the Python prompt. Type import pysb to try loading PySB. If no error messages appear and the next Python prompt appears, you have succeeded in installing PySB! You can now proceed to the Tutorial.

Option 2: Docker container with PySB and Jupyter Notebook


Docker is a virtualization platform which encapsulates software within a container. It can be thought of like a virtual machine, only it contains just the application software (and supporting dependencies) and not a full operating system stack.

Install Docker and the PySB software stack

  1. Install Docker

    To use PySB with Docker, first you’ll need to install Docker, which can be obtained from (Windows and Mac). Linux users should use their package manager (e.g. apt-get).

  2. Download the PySB software stack from the Docker Hub

    On the command line, this requires a single command:

    docker pull pysb/pysb

    This only needs to be done once, or when software updates are required.

  3. Start the container

    Start the Docker container with the following command (on Linux, the command may need to be prefixed with sudo):

    docker run -it --rm -p 8888:8888 pysb/pysb

    This starts the PySB Docker container with Jupyter notebook and connects it to port 8888.

  4. Open Jupyter Notebook in a web browser

    Open a web browser of your choice and enter the address http://localhost:8888 in the address bar. You should see a web page with the Jupyter notebook logo. Several example and tutorial notebooks are included to get you started.

Important notes for Docker installations

To see graphics from matplotlib within the Jupyter Notebook, you’ll need to set the following option in your notebooks before calling any plot commands:

%matplotlib inline

Any Jupyter notebooks created will be saved in the container itself, rather than on the host computer. Notebooks can be downloaded using the Jupyter interface, or a directory on the host computer can be shared with the container.

The PySB container builds on the Jupyter SciPy notebook, which contains further information on the options available for the container (such as sharing a directory with the host computer to preserve notebooks, setting a password and more). Documentation from the Jupyter project is available at