How to Install and Run Jupylet

If you are new to Python, I recommend that you install and use the Miniconda Python distribution.

On Windows – download and run the 64-bit installer for Python 3.10. Once Miniconda is installed press the ⊞ Winkey and then type Miniconda and press the Enter key. This should open a small window that programmers call console or shell in which you can enter commands and run programs.

On macOS with Intel processor – download and run “Miniconda3 macOS Intel x86 64-bit pkg” for Python 3.10. Once installed click the Spotlight icon 🔍 and in the search field type terminal and press the Enter key to open the console.

On macOS with M1 processor – download and run “Miniconda3 macOS Apple M1 64-bit pkg” for Python 3.10. Once installed click the Spotlight icon 🔍 and in the search field type terminal and press the Enter key to open the console. Then you need to run the following two commands:

conda install -c conda-forge numpy "libblas=*=*accelerate"
pip install --pre -i scipy

On Linux – download “Miniconda3 Linux 64-bit”. This should download the file Install it by running the following command in a bash shell (once installed start a new bash shell):


Once Miniconda is installed it is time to install jupylet by typing the following command in the console:

pip install jupylet

Next, to run the example notebooks download the jupylet source code. If you have Git installed type the following command:

git clone

Alternatively, you can download the source code with the following command:

python -m jupylet download

Next, enter the jupylet/examples/ directory with the change directory command:

cd jupylet/examples/

And start a jupyter notebook with:

jupyter notebook 11-spaceship.ipynb

Run the notebook by following the instructions in the notebook and a game canvas should appear with the spaceship example:


Alternatively, you can run the same game as a Python script from the console with:


The Python Programming Language

Python is an awesome programming language. It is both simple for kids to learn and powerful enough to be one of the most popular programming languages among computer scientists and programmers.

However, this reference guide is not designed to teach the Python programming language. If you don’t already have a working knowlege of Python and how to use it to program, I would like to suggest a few resources that may help you get started:

  • Microsoft’s introduction to Python - Microsoft has a long tradition of publishing good guides to programming languages and this tutorial appears to be in line with this tradition. However, their Azure Cloud Shell is unfortunately a distraction. You would be better off trying out their exercises in Python’s own online shell.

  • Python’s own tutorial - Perhaps not as didactic as Microsoft’s guide, but it is a good idea to get familiar with Python’s official documentation.

  • Mike Dane’s Learn Python Yotube tutorial - Appears to be a good didactic introduction to Python.

These guides will instruct you how to start a python interpreter where you can type and run Python code. You may do that, but once you gain a little bit of confidence or if you feel adventurous try starting a Jupyter notebook instead of a simple python interpreter.

To do that start the Miniconda Prompt as explained above, then change directory into the jupylet/examples/ directory and start a new notebook by typing:

jupyter notebook 01-hello-world.ipynb

Jupyter Notebooks

Jupyter notebooks are awesome but they can be a little confusing at first. Here are a few resources that explain how to use them:

  • examples/01-hello-world.ipynb notebook contains a basic introduction to Jupyter notebooks. Check it out.

  • Running Code - This is a Jupyter notebook explaining how to use Jupyter notebooks 🙂. It is in fact a live notebook running in a web service called mybinder. The first time you click it may take a moment to start, so give it a moment. Since it is “live” you can play around with it. It works!

  • Jupyter’s documentation - There’s a whole lot of text in there.