That was challenging.
I rewrote almost all of my Introduction to Programming book into an iBook. Trimmed it down. Refocused it. Changed from Python 2.6 to 3.2. A complete refactoring from which almost nothing of the original book survives except the goals.
Look for it October 1st in the iTunes bookstore.
Programming for Absolute Beginners: Building Skills in Programming.
[My intent is to have several Building Skills titles. We'll see how far I get.]
The rewrite involved three substantial changes.
- I removed all of the duplicative reference material. The Python library reference is (now) utstandingly good. When I started using Python over ten years ago, it was not very good, and I started writing a Python reference of my own merely to organize the documentation. The books grew from there; the reference aspect is now useless.
- I dropped almost all Python 2 references. There's a little bit of Python 2 history, but that's it. It's time to move forward, now that most of the major packages seem to have made the switch.
- I changed the focus from processing to data.
Processing vs. Data
When looking at a multi-faceted language like Python, it's difficult to know what's the most gentle introduction to software development.
Historically, the procedural, imperative style of programming appears the most appealing. The roots of Python come from procedural programming. It reaches back to Pascal (and even Algol 60) by elegantly restating the core principles of those languages with an easier-to-read syntax.
Indeed, if you read classic foundational CACM articles where essential algorithms were first formally described, they used a neatly typeset variant on Algol that (for the early years of my career) was the gold standard in how code should look. Python follows this tradition nicely.
But.
That doesn't mean that procedural programming is really the absolutely best way to introduce the language.
Data First
I think that it may be possible to introduce the language with a focus on data objects first and the procedural/imperative statements as a secondary consideration.
When it comes to anything beyond trivial Rate-Time-Distance calculations, the data structure matters more than almost any other aspect of the software. The objects, their relationships, their operations and their attributes are core to the problem. The presentation, user actions and persistent representation are secondary considerations after the structure of the data.
It seems like the data structures should "drive" the presentation. The outline of the book should be introductions of each of the important and visible builtin data structures. Additionally, the library extensions that are most often used can be introduced, also.
Definitional features (def, return, yield, class, and the ideas of module and package) are central, but a step behind the builtin data structures.
Procedural features (if, for, while, break, continue, with, etc.) are clearly second-class; they exist only to support access to the data structures. A for statement, makes a "for all" assertion about a data structure. A for with a break (or a while) makes a "there exists" assertion about a data structure. The data is central. The imperative statements are secondary.
Other features (global, nonlocal, del, raise, try, etc.) are tertiary, and exist to create more elegant programs that don't annoy the other developers as much.
This also means that generator expressions and comprehensions are first-class, front-and-center features of the language. This parallels the approach in the
NLTK Book, which puts the focus on generator expressions as a way to clearly state the processing.
Other Forms
Currently, I only have the iBook available.
The iBook Author application can (and does) produce a PDF. I think I may offer that separately through
www.lulu.com.
