# [Python-checkins] r79575 - python/trunk/Doc/library/itertools.rst

raymond.hettinger python-checkins at python.org
Fri Apr 2 08:23:12 CEST 2010

Author: raymond.hettinger
Date: Fri Apr  2 08:23:12 2010
New Revision: 79575

Log:
Cleanup itertools recipes

Modified:
python/trunk/Doc/library/itertools.rst

Modified: python/trunk/Doc/library/itertools.rst
==============================================================================
--- python/trunk/Doc/library/itertools.rst	(original)
+++ python/trunk/Doc/library/itertools.rst	Fri Apr  2 08:23:12 2010
@@ -697,7 +697,7 @@

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))
@@ -794,23 +794,23 @@
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