Finally, note that Jupyter notebooks are not the only way to write and run Python code — the examples provided in the text Computational Physics use a much more bare-bones IDLE command line editor (familiar to many beginning computer science students) and advanced Python programmers  often prefer a MATLAB® style interface such as Spyder (again with the 'py') that combines an editor for writing Python programs (ending in .py) with an interactive Python command line — and the  Python examples provided here will run in any of these environments.  But this also means you can run the Python examples provided in Computational Physics  or other guides to scientific programming in Python within Jupyter notebooks!    

Try it out!

On a webserver
Jupyter notebooks are viewed and run  using a web browser such as Firefox (just like this article in Authorea). That means they can also be run on a webserver that you access from a web browser and, as a result, it isn't necessary to have Python installed on your own computer (provided you have internet access and all the Python packages you wish to use are already installed on the webserver). 
To try out the  Python programs presented here  using a Jupyter webserver hosted by Authorea, click the  </> Code button found to the left of many of the figures in this guide. This will reveal the  .ipynb Jupyter notebook (and associated data files) containing the Python code used to generate that figure. Clicking on the notebook file name will launch the notebook in a new tab or window within your web browser . The notebook can then be run as usual. This will work for all but the examples using the aptly named Python packages Pint and Uncertainties for numerical calculations using units and/or uncertainties, as those packages are not currently available on the Authorea Jupyter webserver (but maybe someday?).
Many schools host and configure their own Jupyter webservers for Python programming by their students. For example, Smith College physics students can upload and run any of the Jupyter notebooks included in this guide on the webserver https://jove.smith.edu, as  this particular webserver has all the packages used here preinstalled. (Note to Smith students: the https is required. Contact the course instructor for an account). 
On your own computer
If you are interested in installing and running Python on your own computer, see section \ref{662059} for instructions.
Navigation Tip: For a handy table of contents, select Table of Contents from the Document ▾ pull down menu (upper left of this page).  Clicking on an item in the table of contents will take you to that section.