This document provides an overview of the key topics and tools needed for programming without prior experience, summarized in 3 sentences: It discusses editors/IDEs, revision control, testing, debugging, common errors, performance, libraries, documentation, getting help, practicing, and answers questions about programming. Popular editors mentioned include TextEdit, Notepad, EMACS, and vim, while revision control tools include GIT and Mercurial. The document emphasizes using libraries, writing tests, avoiding errors, and getting help from documentation and online communities like StackOverflow.

1. Everything you need to know
about programming
Without any programming
Danny Mulligan
danny@dannymulligan.com

2. Overview
• Editors/IDEs • Libraries
• Revision Control • Documentation
• Testing • Getting help
• Debugging • Practicing
• Common errors • Q&A
• Performance

3. Editors/IDEs
• Use what you already know
• Use something simple
• Use something that everybody else is using
• Learn to walk before you learn to run
• The right choice for an expert is probably not
the right choice for you (at least right now)
• Learn to type
• Learn keyboard short cuts

4. Editors/IDEs
• Common editor choices
– Textedit (standard on Macs)
– Notepad (standard on Window)
– EMACS http://emacsformacosx.com/
– vim https://code.google.com/p/macvim/
– Notepad++ http://notepad-plus-plus.org/
– BBEdit http://www.barebones.com/products/bbedit/index.html
– TextMate http://macromates.com/
• IDEs and other stuff you might try
– Eclipse http://www.eclipse.org/
– Pycharm https://www.jetbrains.com/pycharm/
– Spyder IDE https://code.google.com/p/spyderlib/
– iPython http://ipython.org/ (iPython notebooks are great!)
– iTerm 2 http://www.iterm2.com/ (Replacement for Mac’s terminal)
– 10 Fast Fingers http://10fastfingers.com/

5. Revision Control
• Absolutely essential for teams
• A good idea for you
• Unfortunately, not the simplest stuff to master
• Popular tools: GIT, Hg, SVN, CVS,
Perforce, Visual SourceSafe
• GitHib https://github.com/
– Allows you to share code easily
– Windows app http://windows.github.com/
– Mac app http://mac.github.com/
• Related #1: when was your last backup?
• Related #2: bug tracking is important too (especially for teams)

6. Testing
• How do you know if you code has any bugs?
– Easy = it has bugs, you haven’t found them yet
• Writing tests is every bit as important as writing code
– Pro move = write the tests FIRST!
• Keep the test code after you’ve written it
• Unit tests & regression tests
• Write defensive code (use assert statements)
• Testing your code is a HARD problem, don’t
underestimate it
• Dividing coding and testing between multiple people
can help

7. Example of unit tests

8. Debugging
• Print statements – show you what’s going on
• Assert statements – verify your assumptions
• Fancy debuggers – less useful than you’d think
• Write documentation on your code
• Code reviews - explain the code to someone else
• Avoid putting the bugs in in the first place
– Shorter code has fewer bugs
– Simpler code has fewer bugs
– Code that’s not there has 0 bugs = use the libraries

9. Common Errors
• Off by 1 errors (AKA fencepost errors)
• = vs. ==
• Logical (and, or) vs. bitwise (&, |) operators, (use logical almost always)
• integers vs. floats
a = 5/(1/3) # a should be equal to 15, or is it?
• Integer or float?
a = 1/3; b = 3/9; c = a/b; print c # c is equal to 1, right?
• Floats are imprecise
a = 2.15*3; b = 6.45; print (a == b) # True or False?
• Division by zero
• Logic errors – easy to make mistakes with nested if statements
• Are you working with a copy, or the original object?
colors = [‘red’, ‘green’, ‘blue’]
b = colors; b[0] = ‘black’
print colors # Did colors change?
• Inadequate or no error handling
• Complexity is the enemy of correctness

10. Performance
• Your performance matters a LOT more than
the computer’s performance
• So don’t worry about performance

11. Performance optimization
• Simple is usually faster
• Use library functions whenever you can
• Use the pareto principle, AKA the 80/20 rule
– Profile first, optimize later
– “premature optimization is the root of all evil”
• If you MUST optimize for performance
– Do easy optimizations first
– Your brain is the best optimization tool
– Make sure you don’t break your program in the
process

12. Libraries
• Learn what is in the standard library
• Get the documentation
• Some important libraries:
– Python Standard Library: by far the most important
– Python Image Library: image manipulation
– Matplotlib: charts & graphs
– Numpy: high performance data processing
– Django: web framework
– Scikit-learn: machine learning
– Pandas: data analysis
– NLTK: natural language

13. Python Standard Library
• string – Common string operations
• re – Regular expression operators
• math – Mathematical functions
• csv – CSV File Reading and Writing
• datetime – Basic data and time types
• random – Generate pseudo-random numbers
• itertools – Functions creating iterators for efficient looping
• collections – High-performance container datatypes
• os – Miscellaneous operating system interfaces
• threading – Higher-level threading interface
• pdb – The Python Debugger
• profile & cProfile – Profiling tools
• test – Regression tests package for Python

14. Documentation
• Python docs online at
http://docs.python.org/2/library/
• I keep PDFs of the Python docs on my laptop
http://docs.python.org/2/download.html
• The standard docs include a nice Tutorial
• “The Python Library Reference” is by far the
most useful doc
– 1,457 pages, but do not read (except the ToC)
– Look up what you need when you need it

15. Getting help
• Read the docs, read other people’s code
• Google your question, look for similar code
• When you google, you will often end up on StackOverflow
– Best site for programming questions http://stackoverflow.com
• Watch tutorials on YouTube - examples
– 3 hour iPython tutorial
https://www.youtube.com/watch?v=2G5YTlheCbw
– 83 video playlist from PyCon 2012
https://www.youtube.com/playlist?list=PL2814D3290BAA8837
– 30 minute overview of Pandas
https://www.youtube.com/watch?v=qbYYamU42Sw
– 3 hour tutorial on Pandas
https://www.youtube.com/watch?v=w26x-z-BdWQ

16. Practicing
• How do you get better at golf?
– Read a book or play golf?
• How do you get better at programming?
– Use it in your job
– Solve some real world problems
– Read other people’s code
• Some real world programming exercises
– Coding Bat http://codingbat.com/python
– Project Euler https://projecteuler.net/

17. Q&A