I remain captivated by the ideals of Literate Programming. My fork of PyLit (https://github.com/slott56/PyLit-3) coupled with Sphinx seems to handle LP programming in a very elegant way.

It works like this.

1. Write RST files describing the problem and the solution. This includes the actual implementation code …

Let me gripe about this for a moment.

sys.exit()

The use case for this function is limited. Very, very limited.

Every place that this appears (except for one) is going to lead to reusability issues.

Consider some obscure little function, deep within the app.

def deep_within_the_app(x, y, zed …

Or. Why I Hate Windows. For Mac OS X, you download XCode (for free) and you can build anything. For Linux, you use some kind of yum or rpm installer for the developer tools, and you can build anything. For Windows... Pre-built binaries. 😂 And a hope that the version numbers …

The conventional wisdom on class design is to model real-world things. This is the Domain-Driven Design Approach. It's what we used to teach as Rumbaugh's OMT (prior to the Three Amigos creating UML.)

The idea is simple: Look at the real world objects. Describe them. Classes will have attributes and …

Seems silly at first.

http://blogs.perceptionsystem.com/infographic/java-vs-python-programming-language-productive

It's mostly true. It's also incomplete.

For example, "no tuples in Java" ignores http://commons.apache.org/proper/commons-lang/apidocs/org/apache/commons/lang3/tuple/package-summary.html.

It seems like the only interesting takeaway from the infographic is that Java …

We have three major tiers of configuration for applications. Within each tier, we have sub-tiers, larding on yet more complexity. The organization of the layers is a bit fungible, too. Making good choices can be rather complex because there are so many variations on the theme of "configuration". The desktop …

New from Packt Publishing: Functional Python Programming. Also here on Amazon. The fun part is covering generator functions, iterators, and higher-order functions in some real depth. There's a lot of powerful programming techniques available. What's challenging is reconciling Python's approach to FP with languages that are purely functional like Haskell …

The context is an ongoing question about optimization -- not my strong suit -- and the SciPy algorithms for this. See Scipy.optimization.anneal Problems for some additional confusion over simple things.

The new quote is this:

However, firing up Python, NumPy, SciPy and figuring out which solver to use is not …

Read this: The Most Diabolical Python Antipattern. Now you've been told. You no longer have any excuses. [Link fixed.]

Three terms that seem to cause confusion: Idempotence, Hysteresis and Deterministic. The subject came up during my webcast on the Five Kinds of Python Functions. We can use all three terms to describe a function. Two of them are relevant to common design questions in software. The third is a …