We Don’t Need No Enums (in Python)

Last weekend I attended the PyGrunn conference, back in the good ol’ Netherlands. It was a very enjoyable and instructive event, featuring not only a few local speakers but also some prominent figures from the Python community – like Kenneth Reitz or Armin Ronacher. Overall, it was a weekend of some great pythonic fun.

…Except for a one small detail. As I’ve learned there, Python will apparently get to have enums in the 3.4 version of the language. To say that this was baffling to me would be a severe understatement. Not only I see very little need for such a feature, but I also have serious doubts whether it fits into the general spirit of Python language.

Why so? It’s mostly because of the main purpose of enumeration types, derived from their usage in many languages that already have them as a feature. That purpose is to turn arbitrary data – mostly integers and strings – into well-known, reliable entities that can be safely manipulated inside our programs. Enums act as border guardians, filtering out unexpected data and converting expected data into its safe representation.

What’s safety in this context? It’s type safety, of course. Thanks to enumeration types, we can be certain that a particular value belongs to specific and constrained set of elements. They clearly define all the variants that our code should handle, because everything else was already culled at the conversion stage.

Problem is, in Python there is nothing that would guarantee those safety promises are actually fulfilled. True, the basic property of enum types is retained: given an enum object, we know it must belong to a preordained set of entities. But there is nothing that ensures we are dealing with an enum object at all – short of us actually checking that ourselves:

How this is different from a straightforward membership check:

except for the latter looking cleaner and more explicit?…

This saying, I do not claim enums are completely out of place in Python. This is untrue, if simply because of the fact they are easily implemented through a rather simple metaclass. In fact, this is exactly how the proposed enums.Enum base is supposed to work.
At the same time, it is also possible to provide some of the before-mentioned type safety. Just look into various libraries that enhance Python with support for contracts: a form of type safety which is even more powerful than what you’ll find in many statically typed languages. You are free to use them, and you should definitely do, if your project would benefit from such a functionality.

Incidentally, they fit right in with that new & upcoming enumeration types from Python 3.4. It remains to be seen what it means exactly for the overall direction of the language design. But with enums in place, the style of “checked” typing suddenly became a lot more pythonic than it was before.

And I can’t say I like it very much.

One Thing that Git Does Better: Rebranching

Much can be said about similarities between two popular, distributed version control systems: Git and Mercurial. For the most part, choosing between them can be a matter of taste. And because Git seems to have considerably more proponents in the Cool Kids camp, it doesn’t necessarily follow it’s a better option.

But I have found at least one specific and common scenario where Git clearly outshines Hg. Suppose you have coded yourself into a dead end: the feature you planned doesn’t pan out the way you wanted it; or you have some compatibility issues you cannot easily resolve; or you just need to escape the refactoring bathtub.

In any case, you just want to step back a few commits and pretend nothing happened, for now. The mishap might be useful later, though, so it’d be nice if we left it marked for the future.

In Git, this is easily done. You would start by creating a new branch that points to your dead end:

Afterwards, both my_feature and __my_feature__dead_end__ refer to the same, head commit. We would then move the former a little back, sticking it to one of the earlier hashes. Let’s find a suitable target:

If it looks right, we can reset the my_feature branch so it points to this specific commit:

Our final situation would then looks like this:

which is exactly what we wanted. Note how any further commits starting from the referent of my_feature would fork at that point, diverging from development line which has lead us into dead end.

Why the same thing is not so easily done in Mercurial?… In general, this is mostly because of its one fundamental design decision: every commit belongs to one branch, forever and for always. Branch designation is actually part of the changeset’s metadata, just like the commit message or diff. Moving things around – like we did above – is therefore equivalent to changing history and requires tools that are capable of doing so, such as hg strip.

Decorated Functions in C++… Almost

Many languages now include the concept of annotations that can be applied to definitions of functions, classes, or even variables and fields. The term ‘annotation’ comes from Java, while other languages use different names: attributes (C#), decorators (Python), tags (Go), etc.
Besides naming disparities, those features also tend to differ in terms of offered power and flexibility. The Python ones, for example, allow for almost arbitrary transformations, while Go tags are constrained to struct fields and can only consist of text labels. The archetypal annotations from Java lie somewhere in between: they are mostly for storing metadata, but they can also be (pre)processed during compilation or runtime.

Now, what about C++? We know the language has a long history of lacking several critical features (*cough* delegates *cough*), but the recent advent of C++11 fixed quite a few of them all at once.
And at first sight, the lack of annotation support seems to be among them. New standard introduces something called attributes, which appears to fall in into the same conceptual bucket:

That’s misleading, though. Attributes are nothing else than unified syntax for compiler extensions. Until C++11, the job of attributes were done by custom keywords, such as __attribute__ (GCC) or __declspec (Visual C++). Now they should be replaced by the new [[squareBracket]] syntax above.
So there is nothing really new about those attributes. At best, you could compare them to W3C deciding on common syntax for border-radius that forces both -webkit-border-radius and -moz-border-radius to adapt. Most importantly, there is no standard way to define your custom attributes and introspect them later.

That’s a shame. So I thought I could try to fix that, because the case didn’t look completely lost. In fact, there is a precedent for a mainstream language where some people implemented something-kinda-almost-like annotations. That language is JavaScript, where annotations can be realized as functions arranged into a pipeline. Here’s an example from Express framework:

Both loginRequired and cached(...) are functions, tied together by app.get with the actual request handler at the end. They “decorate” that handler, wrapping it inside a code which offers additional functionality.

But that’s JavaScript, with its dynamic typing and callback bonanza. Can we even try to translate the above code into C++?…
Well yes, we actually can! Two new features from C++11 allow us to attempt this: lambda functions and initializer lists. With those two – and a healthy dose of functional programming – we may achieve at least something comparable.

Here Be Dragons: Game from IGK Compo

Last weekend I had the pleasure to attend the game development conference IGK in Siedlce, Poland. Although gamedev is not something I normally do, it was a fun experience.

One thing I was especially looking forward to was the one day-long game programming contest called Compo. Like last year and the one before, I formed a team with Adam “Reg” Sawicki and Krzysztof “Krzysiek K.” Kluczek, guest starring Kamil “Netrix” Szatkowski. That’s four coders in total, so we kinda had some problem with, say, more artistic part of the endeavor :)

Nevertheless, the result was pretty alright: we scored 4th place out of about dozen teams. The theme this time was an “artillery” game with few mandatory features: two types of energy-like resources (HP & MP), achievements and multiplayer gameplay.
We nailed the last one by implementing support for two mice at once. This allowed us to come up with an interesting idea inspired by the Atari game Rampart: two castles that expand and attack each other in a fast-paced duel full of frantic clicking. And because the attackers, or guardians of each castle are dragons, hence the game’s title: Here Be Dragons.

  [2013-04-07] Here Be Dragons (3.2 MiB, 1,725 downloads)

In retrospect, we should probably have narrowed the scope of our project more. Doing it 3D was ambitious in itself, but packing it with all the features we planned the night before turned out to be slightly too much :) In the end we didn’t even have time to code any sound effects or music!… That’s certainly a lesson to learn here.

But all in all, it was great fun. It certainly inspired me to maybe try and brush up my gamedev skills a bit more :)

Unexpectedly Clean Code

There is this quite well known book, titled Clean Code. It is a very insightful work which I wholeheartedly recommend reading for any serious (or semi-serious) programmer.
The premise revolves around the concept of “cleanness” of code, which the author defines in various ways. Mostly it boils down to high signal-to-noise ratio and clear structure, where everything is neatly subdivided into smaller parts.

The idea is very appealing. For some it may even sound like a grand revelation; I know it was almost like that for me. But there is a bigger kind of meta-lesson to be learned here: the one of scope where such great ideas apply – and where they don’t.

You see, the Clean Code ideal works very well for certain kind of languages. The original examples in the book are laid down in Java and this is no coincidence. Java – as well as C, Go and probably few others – is not a very expressive language: lots of detailed busy work is often needed, even for conceptually simple tasks. And if several such tasks are lined up one after another, the reader is likely to drown in small details instead of seeing the bigger picture.

Those details are therefore one of the prime reasons why you may call some code “unclean”. To tidy up, they need to be properly encapsulated, away from a higher level overview. Hence it’s pretty common in Java to see functions like this one:

and think of them as good code, even if such a function is only used once. The goodness comes from the fact that they are relieving their callers from irrelevant loop minutiae, so that it’s easier to see why we need foos to be valid in the first place.

Yet, at the same time, if you saw a completely equivalent Python construct:

you would firstly curse at incompetence and lack of knowledge of whoever wrote it:

and then you would get rid of the function altogether:

Why? Because the language is expressive enough for implementation itself to be almost as readable as the function call. Sure, throw the result of all(...) into a variable for even more self-documenting sweetness, but don’t put it in some far away place behind a standalone function. Such code may or may not be cleaner; it will definitely raise eyebrows, though.

And lack of astonishment is probably the most important metric.

When and What to Bash

Often I advocate using Python for various automation tasks. It’s easy and powerful, especially when you consider how many great libraries – both standard and third party – are available at your fingertips. If asked, I could definitely share few anecdotes on how some .py script saved me a lot of hassle.

So I was a bit surprised to encounter a non-trivial problem where using Python seemed like an overkill. What I needed to do was to parse some text documents; extract specific bits of information from them; download several files through HTTP based on that; unzip them and place their content in designated directory.

Nothing too fancy. Rather simple stuff.

But then I realized that doing all this in Python would result in something like a screen and a half of terse code, full of tedious minutiae.
The parsing part alone would be a triply nested loop, with the first two layers taken by os.walk boilerplate. Next, there would be the joys of urllib2; heaven forbid it turns out I need some headers, cookies or authentication. Finally, I would have to wrap my head around the zipfile module. Oh cool, seems like some StringIO glue might be needed, too!

Granted, I would probably use glob2 for walking the file system, and definitely employ requests for HTTP work. And thus my little script would have external dependencies; isn’t that making it a full-blown program?…

Hey, I didn’t sign up for this! It was supposed to be simple. Why do I need to reimplement grep and curl, anyway? Can’t I just…

…oh wait.

Everybody Should Learn to Code!… Wait, What?

You may have seen this video, starring Mark Zuckerberg, Drew Houston (from Dropbox) and a couple of other tech stars. They promote the Code.org initiative, advocating that every school kid in the U.S. should have programming classes as part of their educational offer.

It’s a recent development, but the whole idea of promoting computer programming among broad audience is in the spotlight for quite some time now. Not only in the U.S., mind you. In Estonia, for example, children are to be offered coding classes starting from early elementary school.

The message seems to be pretty clear: everyone should learn to code, the earlier the better. In the future, it will be an obvious part of basic literacy, like reading and writing natural language. Everyone will get to do some really cool and useful things with their computers.

Sounds great, doesn’t it?…

So why I can’t help but to roll my eyes when I hear about this? Am I just an obnoxious, elitist jerk who doesn’t want others to experience the feeling of empowerment and satisfaction that creating your own computer programs can evoke every so often?… D’oh, I really hope not.

So maybe there are some actual problems with this idea. I would hesitate to say that it just doesn’t, ahem, compute, but I can certainly see a few issues, misconceptions and dubious assumptions.