Skip to main content

Undefined Python

Will McGugan has a post about the smell of languages, using an example of code from C that is actually completely undefined: no one knows what it should do. The code in question is this:

int main() { int i = 5; i = ++i + ++i; printf ("%d", i); }
One of the commenters talks about how some constructs in Python can be undefined, but I disagree. My response is below.

There can certainly be some cases where you aren’t sure about things involved in Python, but nothing undefined in the sense that C can be. I can counter the examples given.

“While a list is being sorted, the effect of attempting to mutate, or even inspect, the list is undefined.”

- While the list is being sorted, any inspection or mutation could only be occuring in some other thread. Multiple threads are, by desogn, indeterminable.

“Formfeed characters occurring elsewhere in the leading whitespace have an undefined effect (for instance, they may reset the space count to zero).”

- This is caused by improper formatting of a text file. If the file is not formatted properly, you can’t expect magic its-OK-ness.

“super is undefined for implicit lookups using statements or operators such as “super(C, self)[name]””

- Undefined? I actually don’t agree. At least, not by the term “undefined” as used in this post. implicit lookups like this are looked up on the type of the object in question, which is the super builtin type, in this case. The methods are undefined in the sense that the type does not define them, so they don’t exist. You can’t look them up. This is not “undefined” as in not knowing the behavior.

“If the transformed name is extremely long (longer than 255 characters), implementation defined truncation may happen.”

- This is about private name mangling. The mangled names should be considered an implementation detail, you should never use or try to create the names manually, so any implementation specific differences are completely irrelevant.





Comments

Brian said…
You don't have to be in another thread to mutate a list when sorting. Consider things like the key or cmp arguments to list.sort. These can execute arbitrary code during the sort, so it would be perfectly possible (though rather silly) to give a callback that mutates the list.
stan said…
Suppose you have a special cmp_using_list function which takes a list to define an ordering of arbitrary objects:

>>> cmp_using_list = lambda l,x,y: cmp(l.index(x), l.index(y))
>>> foo, bar, baz = list(), '', dict() # arbitrary objects
>>> ordering = [foo, bar, baz]
>>> mycmp = lambda x,y: cmp_using_list(ordering, x, y)
>>> mycmp(foo,foo)
0
>>> mycmp(foo,bar)
-1
>>> mycmp(baz,foo)
1
>>> sorted([foo, foo, baz, bar, baz, foo], cmp=mycmp)
[[], [], [], '', {}, {}]

So far so good, but now this statement is undefined:

>>> sorted(ordering, cmp=mycmp)

mycmp accesses ordering while ordering is being sorted. Of course, by construction, ordering is already sorted, so this happens to work anyway. (And, from a practical perspective, why would you ever need to do this?)
stan said…
Hah, figures I would screw that example up. Of course, I should be using sort() instead of sorted() as sorted constructs a new list, thereby eliminating the self reference. If you try it, things do blow up:
>>> ordering.sort(cmp=mycmp)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "<stdin>", line 1, in <lambda>
File "<stdin>", line 1, in <lambda>
ValueError: list.index(x): x not in list
Calvin Spealman said…
I found out why Stan's example blows up when I was toying with this myself. It looks like during sorting, the list is empty (at least in 2.5.1 CPython, so don't depend on it). Its probably an implementation that empties the list, holds an array of object pointers, sorts them, and refills the array. I suppose its to avoid the heavy GIL locking that would be needed to continually shift things about inside the list.
Marius Gedminas said…
How about a simple example: the order of keys returned by a_dict.keys() is not defined in Python.

Popular posts from this blog

My Software Job Transition Strategies?

I’ve been spending a good deal of the last two days preparing mentally for starting a whole new challenge as a developer. New things aren’t new to me, but this is different and big enough really call for some Deep Thoughts ™. For one thing, I’ve made a big move from the world of Python web development to totally other Python work and while web development has never been the only thing I do, it has been the only work that paid the bills. That transition isn’t one that bothers me or daunts me, though. Instead, I’m thinking about transitioning to the scope of the work I’m getting into. For a long time, I juggled multiple clients and client projects every day, so no single project usually took up most of my time. Every developer juggles time through the day, but exactly how that works in each company and on each project varies a lot. I was looking for a place that I could really focus in a way that I haven’t for a long time. I think I found that, but now I have to deal with the consequen...

CARDIAC: The Cardboard Computer

I am just so excited about this. CARDIAC. The Cardboard Computer. How cool is that? This piece of history is amazing and better than that: it is extremely accessible. This fantastic design was built in 1969 by David Hagelbarger at Bell Labs to explain what computers were to those who would otherwise have no exposure to them. Miraculously, the CARDIAC (CARDboard Interactive Aid to Computation) was able to actually function as a slow and rudimentary computer.  One of the most fascinating aspects of this gem is that at the time of its publication the scope it was able to demonstrate was actually useful in explaining what a computer was. Could you imagine trying to explain computers today with anything close to the CARDIAC? It had 100 memory locations and only ten instructions. The memory held signed 3-digit numbers (-999 through 999) and instructions could be encoded such that the first digit was the instruction and the second two digits were the address of memory to operat...

The Snake Pit is About to Burst

The signs are all over the place. I can count at least five implementations of Python today: CPython, CL-Python, Jython, IronPython, and PyPy. The use of the language is sky rocketting and set to grab real mind-share as the hype over Ruby subsides. Things are looking good for a favorite green snake and british comedy troop reference, aren't they? Trouble is on the horizon in the very ingredients that could push us into true success. Our community and our very language is in danger of segregation, unless we all do something about it and learn to get along. One of the most visible dangers (to me) is being ignored for various political, cultural, and non-technical reasons. IronPython's users are increasingly pushing IronPython-only recipes, libraries, and tutorials. No one is talking about the transition of the alternative implemenations to CPython 3.0 compatability. To make matters worse, we still can not define the language without refering to an implementation. This is very un...