Here are some references on software development techniques and patterns to help write better code. They are intended for the casual programmer, and certainly not an advanced developer.
They are listed in order of difficulty.
These are the original notes from Greg Wilson’s course on software engineering at the university of Toronto. This course is specifically intended for scientists, but not computer science students. It is very basic and does not cover design issues.
A tutorial introduction to Python
This tutorial is easier to follow than Guido’s tutorial, thought it does not go as much in depth.
Python Essential Reference
These are two chapters out of David Beazley’s excellent book Python Essential Reference. They allow to understand more deeply how python works. I strongly recommend this book to anybody serious about python.
An Introduction to Regular Expressions
If you are going to do any sort of text manipulation, you absolutely need to know how to use regular expressions: powerful search and replace patterns.
Software design for maintainability
A case of shameless plug: this is a post that I wrote a few years ago. I think that it is still relevant.
Writing a graphical application for scientific programming using TraitsUI
Building interactive graphical application is a difficult problem. I have found that the traitsUI module provides a great answer to this problem. This is a tutorial intended for the non programmer.
An introduction to Python iterators
This article may not be terribly easy to follow, but iterator are a great feature of Python, so this is definitely worth reading.
Functional programming is a programming style where mathematical functions are successively applied to immutable objects to go from the inputs of the program to its outputs in a succession of transformation. It is appreciated by some because it is easy to analyze and prove. In certain cases it can be very readable.
Patterns in Python
This document exposes a few design patterns in Python. Design patterns are solutions to recurring development problems using object oriented programming. I suggest this reading only if you are familiar with OOP.
Jeff Knupp’s post, a summary of his book:
The scipy-lectures chapter on advanced Python:
General Object-Oriented programming advice
Designing Object-oriented code actually requires some care: when you are building your set of abstractions, you are designing the world in which you are going to be condemned to living (or actually coding). I would advice people to keep things as simple as possible, and follow the SOLID principles:
Using decorators to do meta-programming in Python
A very beautiful article for the advanced python user. Meta-programming is a programming technique that involves changing the program at the run-time. This allows to add new abstractions to the code the programmer writes, thus creating a “meta-language”. This article shows this very well.
A Primer on Python Metaclass Programming
Metaclasses allow to define new style of objects, that can have different calling, creation or inheritance rules. This is way over my head, but I am referencing it here for the record.
Iterators in Python
Learn to use the itertools (but don’t abuse them)!
Related to the producer/consumer problem with iterators, see: