From: Raymond Hettinger Date: Fri, 2 Apr 2010 06:21:59 +0000 (+0000) Subject: Cleanup itertools recipes X-Git-Tag: v2.6.6rc1~515 X-Git-Url: https://granicus.if.org/sourcecode?a=commitdiff_plain;h=b640bcc32b21c24ced7269cc701a1ccb5569814d;p=python Cleanup itertools recipes --- diff --git a/Doc/library/itertools.rst b/Doc/library/itertools.rst index 993e86ef01..dafeeb1537 100644 --- a/Doc/library/itertools.rst +++ b/Doc/library/itertools.rst @@ -663,7 +663,7 @@ which incur interpreter overhead. def ncycles(iterable, n): "Returns the sequence elements n times" - return chain.from_iterable(repeat(iterable, n)) + return chain.from_iterable(repeat(tuple(iterable), n)) def dotproduct(vec1, vec2): return sum(imap(operator.mul, vec1, vec2)) @@ -782,23 +782,23 @@ which incur interpreter overhead. def random_product(*args, **kwds): "Random selection from itertools.product(*args, **kwds)" pools = map(tuple, args) * kwds.get('repeat', 1) - return map(random.choice, pools) + return tuple(random.choice(pool) for pool in pools) def random_permuation(iterable, r=None): "Random selection from itertools.permutations(iterable, r)" - pool = list(iterable) + pool = tuple(iterable) r = len(pool) if r is None else r - return random.sample(pool, r) + return tuple(random.sample(pool, r)) def random_combination(iterable, r): "Random selection from itertools.combinations(iterable, r)" - pool = list(iterable) - return sorted(random.sample(pool, r), key=pool.index) + pool = tuple(iterable) + return tuple(sorted(random.sample(pool, r), key=pool.index)) def random_combination_with_replacement(iterable, r): "Random selection from itertools.combinations_with_replacement(iterable, r)" - pool = list(iterable) - return sorted(imap(random.choice, [pool]*r), key=pool.index) + pool = tuple(iterable) + return tuple(sorted(imap(random.choice, [pool]*r), key=pool.index)) Note, many of the above recipes can be optimized by replacing global lookups with local variables defined as default values. For example, the