Credit: Nathaniel Gray
You need to show that Python’s support for the functional programming paradigm is quite a bit better than it might seem at first sight.
Functional programming languages, of which Haskell is a great example, are splendid animals, but Python can hold its own in such company:
def qsort(L): if len(L) <= 1: return L return qsort([lt for lt in L[1:] if lt < L[0]]) + L[0:1] + \ qsort([ge for ge in L[1:] if ge >= L[0]])
In my humble opinion, this is almost as pretty as the Haskell version from http://www.haskell.org:
qsort [] = [] qsort (x:xs) = qsort elts_lt_x ++ [x] ++ qsort elts_ge_x where elts_lt_x = [y | y <- xs, y < x] elts_ge_x = [y | y <- xs, y >= x]
Here’s a test function for the Python version:
def qs_test(length): import random joe = range(length) random.shuffle(joe) qsJoe = qsort(joe) for i in range(len(qsJoe)): assert qsJoe[i] == i, 'qsort is broken at %d!'%i
This is a rather naive implementation of quicksort that illustrates
the expressive power of list comprehensions. Do not use this in real
code! Python’s own built-in sort
is of course much faster and should always be preferred. The only
proper use of this recipe is for impressing friends, particularly
ones who (quite understandably) are enthusiastic about functional
programming, and particularly about the Haskell language.
I cooked up this function after finding the wonderful Haskell quicksort (which I’ve reproduced above) at http://www.haskell.org/aboutHaskell.html. After marveling at the elegance of this code for a while, I realized that list comprehensions made the same thing possible in Python. Not for nothing did we steal list comprehensions right out of Haskell, just Pythonizing them a bit by using keywords rather than punctuation!
Both implementations pivot on the first element of the list and thus have worst-case O(N2) performance for the very common case of sorting an already-sorted list, so you would never want to do this in production code. Because this is just a propaganda thing, though, it doesn’t really matter.
List comprehensions were introduced in Python 2.0, so this recipe’s code will not work on any earlier version. But then, you wouldn’t be trying to impress a friend with a many-years-old version of Python, right?
A less compact version with the same architecture can easily be written to use named local variables and functions for enhanced clarity:
def qsort(L): if not L: return L pivot = L[0] def lt(x, pivot=pivot): return x<pivot def ge(x, pivot=pivot): return x>=pivot return qsort(filter(lt, L[1:]))+[pivot]+qsort(filter(ge, L[1:]))
This one works on old and crusty Python versions, but in Python 2.1
(with a from _ _future_ _ import nested_scopes
)
and later, you can do without the pivot=pivot
trick in the formal argument lists of lt
and
ge
.
The Haskell web site (http://www.haskell.org).
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