Learning Python - Mark Lutz [279]
print(mymapPad(S1, S2, pad=99))
Both of the functions coded here work on any type of iterable object, because they run their arguments through the list built-in to force result generation (e.g., files would work as arguments, in addition to sequences like strings). Notice the use of the all and any built-ins here—these return True if all and any items in an iterable are True (or equivalently, nonempty), respectively. These built-ins are used to stop looping when any or all of the listified arguments become empty after deletions.
Also note the use of the Python 3.0 keyword-only argument, pad; unlike the 2.6 map, our version will allow any pad object to be specified (if you’re using 2.6, use a **kargs form to support this option instead; see Chapter 18 for details). When these functions are run, the following results are printed—a zip, and two padding maps:
[('a', 'x'), ('b', 'y'), ('c', 'z')]
[('a', 'x'), ('b', 'y'), ('c', 'z'), (None, '1'), (None, '2'), (None, '3')]
[('a', 'x'), ('b', 'y'), ('c', 'z'), (99, '1'), (99, '2'), (99, '3')]
These functions aren’t amenable to list comprehension translation because their loops are too specific. As before, though, while our zip and map workalikes currently build and return result lists, it’s just as easy to turn them into generators with yield so that they each return one piece of their result set at a time. The results are the same as before, but we need to use list again to force the generators to yield their values for display:
# Using generators: yield
def myzip(*seqs):
seqs = [list(S) for S in seqs]
while all(seqs):
yield tuple(S.pop(0) for S in seqs)
def mymapPad(*seqs, pad=None):
seqs = [list(S) for S in seqs]
while any(seqs):
yield tuple((S.pop(0) if S else pad) for S in seqs)
S1, S2 = 'abc', 'xyz123'
print(list(myzip(S1, S2)))
print(list(mymapPad(S1, S2)))
print(list(mymapPad(S1, S2, pad=99)))
Finally, here’s an alternative implementation of our zip and map emulators—rather than deleting arguments from lists with the pop method, the following versions do their job by calculating the minimum and maximum argument lengths. Armed with these lengths, it’s easy to code nested list comprehensions to step through argument index ranges:
# Alternate implementation with lengths
def myzip(*seqs):
minlen = min(len(S) for S in seqs)
return [tuple(S[i] for S in seqs) for i in range(minlen)]
def mymapPad(*seqs, pad=None):
maxlen = max(len(S) for S in seqs)
index = range(maxlen)
return [tuple((S[i] if len(S) > i else pad) for S in seqs) for i in index]
S1, S2 = 'abc', 'xyz123'
print(myzip(S1, S2))
print(mymapPad(S1, S2))
print(mymapPad(S1, S2, pad=99))
Because these use len and indexing, they assume that arguments are sequences or similar, not arbitrary iterables. The outer comprehensions here step through argument index ranges, and the inner comprehensions (passed to tuple) step through the passed-in sequences to pull out arguments in parallel. When they’re run, the results are as before.
Most strikingly, generators and iterators seem to run rampant in this example. The arguments passed to min and max are generator expressions, which run to completion before the nested comprehensions begin iterating. Moreover, the nested list comprehensions employ two levels of delayed evaluation—the Python 3.0 range built-in is an iterable, as is the generator expression argument to tuple.
In fact, no results are produced here until the square brackets of the list comprehensions request values to place in the result list—they force the comprehensions and generators to run. To turn these functions themselves into generators instead of list builders, use parentheses instead of square brackets again. Here’s the case for our zip:
# Using generators: (...)
def myzip(*seqs):
minlen = min(len(S) for S in seqs)
return (tuple(S[i] for S in seqs) for i in range(minlen))
print(list(myzip(S1, S2)))
In this case, it takes a list call to activate the generators and iterators to produce their results. Experiment with these on your own for more details.