About a decade ago, I discovered the concept of Literate Programming. It's seductive. The idea is to write elegant documentation that embeds the actual working code.

For tricky, complex, high-visibility components, a literate programming approach can give people confidence that the software actually works as advertised.

I actually wrote my …

XKCD - http://xkcd.com/710/

http://en.wikipedia.org/wiki/Collatz_conjecture#Syracuse_function

I remember learning about this as an undergrad at Syracuse University in the 70's and didn't think much of it. It was just "one of those things" that I heard about, and perhaps wrote a homework assignment in …

Enterprise Applications really make people sweat. Look at this selection of StackOverflow questions. There are hundreds. People really get worked into a lather over this.

• What makes an application an “enterprise” or “enterprise-level” application?
• Is the LAMP stack appropriate for Enterprise use?
• What is “Enterprise ready”? Can we test for …

A year and change back, I wrote this on "Exploratory Programming".

It turns out that it was a mistake. While the subclass-expansion technique is a cool way to bang out a program incrementally, in the long run, the subclassing is ill-advised.

The more I look at Python generator functions and …

Interesting comments to Splitting Meta-Hairs.

Terms like Scripting, Interpreted and Dynamic are not "marketing terms". New, Improved, All Natural, Visual, Groovy, Lucid, etc., are marketing terms. I regret giving the impression that one should "not to spend time trying to get definitions that are exacting". One absolutely must get definitions …

Recently, I've been involved in some hair-splitting over the nature of Python.

I've described it as "interpreted", "scripting" and "dynamic", all of which seem to be true, but yet each seems to lead to a standard -- and pointless -- dispute.

From time-to-time I hear a few mentions of MapReduce; up until recently, I avoided looking into it.

This month's CACM, however, is chock-full of MapReduce goodness.

After reading some of the articles, I decided to look a little more closely at that approach to handling large datasets.

Completely revised Building Skills in Object-Oriented Design. Cleaned up many of the exercises to make them simpler and more sensible to the n00b designer.

Also, to make it easier to follow, I made use of the Sphinx "ifconfig" feature to separate the text into two parallel editions: a Python edition …

I made some fundamental changes to the text processing pipeline. I think I've corrected all of the typographical and production problems. (Plus, I fixed some content errors, too.)

I've republished the Building Skills in Python, both HTML and PDF.

Hopefully, this is considerably better and more usable.

Next step -- revising …

I've updated Building Skills in Programming -- an introduction to programming for non-programmers.

The entire thing was redone in RST and Sphinx, leading to an easier-to-read, more colorful layout. The cross-references are generally better and more complete. I also get Sphinx's indexing and search capabilities.

Everything was touched, chapters were added …