Naming Things (redux)

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The first article (long, long ago) about naming things only scratched the surface. Even with company and language guidelines (or other rules) to help, with so many things to name it’s easy to lose control. Even now, after 44 years of writing code, I still sometimes find myself staring at the screen trying to think of what to name some object.

It’s understandable; there are a lot of things to think about when it comes to a name.

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Calculating Entropy (in Python)

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I’ve been playing with calculating the entropy of a toy system used to illustrate the connection between “disorder” and entropy. (See Entropy 101 and Entropy 102.) I needed to calculate the minimum number of moves required to sort a disordered collection, but that turns out to be an NP problem (no doubt related to Traveling Salesman).

The illustration bridges Boltzmann and Shannon entropy, which got me playing around with the latter, and that led to some practical results. This article describes the code I used mainly as an excuse to try embedding my own colorized source code blocks.

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Building a Turing Machine

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I’m not sure how I got to thinking about Turing Machines (TMs). I was going through some files recently and spent some time looking at busy-beaver.c (from 2017 according to the file date). It contains an implementation of a TM. But something else got me speculating about my own implementation; I just don’t recall what.

I decided to actually write it when it occurred to me that I could use a Python generator to implement the Turing Machine tape. Sadly, I didn’t think of it in time for the trilogy I just published about Python generators (part 1, part 2, part 3).

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Python Tokenize

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Recently I thought to myself, “Hey self… Although I’ve never looked into them, I know Python has tools for parsing Python code. I wonder if they might make generating syntax-highlighted HTML pages of Python scripts pretty easy?”

I found the help page for the tokenize module, and the introduction says it’s “useful for implementing ‘pretty-printers,’ including colorizers for on-screen displays.” That sounds like a strong yes.

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The Synchronization Problem

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One of the great battles programmers fight involves synchronization between two different parts of the code. The most common example of this is what the comments say versus what the code really does. Another common example is the structure of data stored somewhere (like a database) and the code that manipulates it.

A lot of the programmer’s effort and technique is devoted to managing, if not preventing, synchronization issues. The rules encouraging encapsulation, or against global objects, have a lot to do with this goal.

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Python Generators, part 3

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In the last two posts I’ve explored Python generator functions. The first post went over the basics and showed how they return an iterable object usable in for-loops and list constructors. The second post explored how generator functions work in more detail.

This time I’ll wrap it up with some examples that are a bit more involved. If Python generators were a mystery before these three posts, I hope you feel more comfortable with them after!

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Python Generators, part 2

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Last time I began exploring Python generator functions. I mostly covered their basic function as iterables, and why they’re good in for-loops. They’re also good for infinite lists. Much of their value lies in how they defer processing an item until it is actually asked for.

This time I’ll dig into the send method, which allows sending messages to a running generator. I’ll also introduce the yield from statement, which allows us to wrap a generator with another function that also acts like a generator.

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Python Generators, part 1

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Python has a feature called a generator — it’s a way of writing a function that allows that function to trade control back and forth with a calling function. It’s not something one needs often, but it can be very useful in certain situations.

Create a Python generator, firstly, in using yield instead of return and, secondly, by designing the function a little differently from one that generates and then returns a list of items.

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Abusing #define in C

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When I was a callow young programmer learning the ropes and enjoying the sheer power of the C language, I got a bit carried away with the macro pre-processor’s ability to let you redefine the language.

As much fun as that is, and as much as it can make your source code look cool, it’s a really bad idea. At some point the folks in comp.lang.c read me the riot act about it, and they were right.

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The Blessing of Unicode

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Computers process numbers using arithmetic and logic (which amount to the same thing). Processing text, however, requires at least two levels of abstraction. Firstly, a definition of a textual atom — informally a character. Secondly, a definition of a textual unit — typically called a string. A string is an ordered list of characters.

Therein lies a whole field of computer science. From a practical point of view, implementing text has become much easier with Unicode. Different character sets was one of the more awful aspects of dealing with text. (Remember CP-1252?)

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