Scientific Python Basics

Goals

Despite what the title above might suggest, the purpose of this Software Carpentry bootcamp is not to teach you how to program in Python. While we do love Python for scientific computing, the goals of these modules is actually to teach you the basic, core concepts of programming that transcend languages, how they fit together, and how you can use them to become a better scientist.

By the end of these scientific Python lessons, you will be able to:

1. Describe and distinguish the seven core elements shared by all programming languages.
2. Use Python to write simple programs that use these core elements, using both the core library and scientific packages such as numpy.
3. Make and save simple publication-quality plots using matplotlib.
4. Read, manipulate, and save data files in csv and text formats.
5. Write unit tests to confirm the accuracy of your Python code.
6. Create standalone Python scripts that can be run from the command line.

We (the instructors) recognize that you all unavoidably have come with very different levels of background in Python programming. We expect that some of you might be experienced in basic Python and a few of you of you have experience with additional modules such as numpy and scipy - for those in that category, this section of the workshop may not be as novel as the other sections. However, we hope that the method of presentation will help to solidify your existing knowledge. We also encourage you to take the opportunity to ask the instructors and volunteers about more advanced techniques that you might have heard of but do not know how to use well.

For those who have no (or almost no) background in programming in any language, you may find that these lessons proceed quickly. We encourage you to make liberal use of the helpful volunteers as we proceed through these lessons. You may also wish to consider working together with a partner to complete the exercises as a team.

Regardless of your background, you will probably feel like trying to take in all of this material is like trying to drink from a firehose. That's OK - the idea is to at least introduce you to a wide variety of topics, with the hope that you (a) will get to reinforce the most important concepts during exercises, and (b) will be able to come back to these materials later to continue mastering the concepts.

The Seven Core Concepts

As noted by Greg Wilson (the founder of Software Carpentry), every programming language shares [seven core elements][1]:

1. Individual things (the number 2, the string 'hello', a matplotlib figure)
2. Commands that operate on things (the + symbol, the len function)
3. Groups of things (Python lists, tuples, and dictionaries)
4. Ways to repeat yourself (for and while loops)
5. Ways to make choices (if and try statements)
6. Ways to create chunks (functions, objects/classes, and modules)
7. Ways to combine chunks (function composition)

The lines between these are often blurry in practice - for example, a string in Python actually mixes some characteristics of a thing, a group, and a "chunk". The distinctions between these categories is not particularly relevant to the computer - they are purely a conceptual framework that helps programmers write code that does what they want it to do.

We expect that you'll find the basics of 1 and 2 fairly straightforward. We'll go quickly through those and will spend the most time on items 3-6. We won't really talk about 7, as it is not as common in scientific Python programming as it is in, say, shell scripting (pipes and redirection).

Don't worry if you don't already know what all of the above examples mean - you'll know by the end of this lesson.

Getting the Files

Our Python tutorial during this bootcamp will rely on a number of additional files. The files that you'll need for each lesson are linked below - download these and save them in an easily accessible folder on your hard drive. Make sure that when you save each file in your browser, the appropriate file extention (i.e., .ipynb) is retained.

• Scientific Programming
  • Student Notebook
  • Master Notebook
• Read Write Tutorial
  • Student Notebook
  • Master Notebook
  • File txt, File csv
• Matplotlib
  • Student Notebook
  • Master Notebook
  • Image
• R and Python
  • R and Python tutorial

Starting an IPython Notebook

To learn about these core concepts and the Python language, we'll start off by working within the IPython notebook.

To start up a notebook, open Terminal and navigate to the folder containing the ipynb notebook files that you wish to open (or to any directory in which you'd like to save a new notebook, if you're creating a new notebook from scratch). Once in the directory, run the command ipython notebook, which will launch a local webserver and open your default browser. From there you can open an existing notebook, create a new notebook, and start working.

Note that if you are on a Windows machine, this command may not run under mysysgit or Cygwin. If it doesn't, open a Command Prompt (click on the Start menu and type cmd in the search box for Windows 7, or click on Run then type cmd for Windows XP), navigate to the appropriate directory, and run the command ipython notebook.

Asking Questions

As we go through this lesson, you can ask questions in two ways:

1. If you have a question for me, just raise your hand and ask.
2. If you have a question that you think might be restricted to just you (like something on your computer isn't working), raise your hand an a volunteer will come over to help you individually.

[1]: http://software-carpentry.org/2012/08/applying-pedagogical-principles-in-this-course.html