Scientific Python Primer

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This Python Primer utilizes an IPython notebook kernel running on a computer in the APL and a browser-based IPython notebook front end located on your computer. That is, you don't need any special software just a computer with a web-browser and a SSH client.

You will start your IPython session by establishing a SSH tunnel.

Step 1 SSH into the remote machine and run the IPython web-based environment and direct it to a specific port. The command for this should look something like:

jupyter notebook --no-browser --port=70xx

Step 2 On the local machine you can access this remote port using an SSH tunnel with port forwarding. The command for that will look like:

ssh -N -f -L localhost:70xx:localhost:70xx username@remotemachine

Step 3 Now to use the session all you have to do is (from the local machine) run your preferred web browser with the URL:


SSH Tunnel on Chromebook

Step 1: Open two secure shells. Right click the secure shell icon and open it in window mode. Enter ctrl+shift+n to create a second shell.

Step 2: From secure shell enter username as the user name and host as the host name. Open an ipython notebook with the command

jupyter notebook --no-browser --port=70xx

Step3: In the second shell use the same user name and host name in SSH arguments enter

-L 70xx:localhost:70xx

Step4: Go to http//:localhost:70xx and the ipython notebook should be running.

note: if multiple instances of ipython are running the notebook might not execute commands

note: occasionally the kernel cannot be killed in the shell and must be killed in the system monitor on mother

Textbook for the module

A Primer on Scientific Programming with Python by Hans Petter Langtangen (3rd Edition). Available online through the UO Library. To access it, follow this link:


Intro to Python, Definitions - Chapter 1

Loops, logic, and lists - Chapter 2

Functions - Chapter 3 and NumPy

Input data and error handling - Chapter 4 and PANDAS

Functions on arrays and curve fitting - Chapter 5

String handling, files, and dictionaries - Chapter 6 and PANDAS

Useful Links


NumPy -

codecademy -

Python Flow Visualization -

Chapter 1

Section 1.1: If this is your first time programming anything, begin with 1.1.1. Otherwise, it will suffice to read 1.1.1 for a statement of the problem and skip to 1.1.11. This introduces the syntax for commenting and basic arithmetic operations.

Section 1.2: This will give you relevant vocabulary for talking about Python and programs more generally. If this is not your first time programming, this section should just be skimmed.

Section 1.3: Introduction to potential calculation difficulties, primarily floating point versus integer data.

Section 1.4: Importing mathematical functions from a library.

Section 1.5: Interactive computing. This section will teach you how to have the user input various parameters. IPython is introduced as well.

Section 1.6: Complex numbers in Python.

Section 1.7: Summary

Section 1.8: Suggested exercises: While all are useful (after 1.6), the following will help immensely in debugging. 1.6 - Introduction to basic functions 1.9 - Error Correction 1.17 - Error Finding in a program that uses the quadratic formula