Add and update itertools recipes.
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@ -455,7 +455,7 @@ loops that truncate the stream.
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def product(*args, repeat=1):
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# product('ABCD', 'xy') --> Ax Ay Bx By Cx Cy Dx Dy
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# product(range(2), repeat=3) --> 000 001 010 011 100 101 110 111
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pools = map(tuple, args) * repeat
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pools = [tuple(pool) for pool in args] * repeat
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result = [[]]
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for pool in pools:
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result = [x+[y] for x in result for y in pool]
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@ -617,7 +617,8 @@ which incur interpreter overhead.
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return sum(map(operator.mul, vec1, vec2))
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def flatten(listOfLists):
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return list(chain.from_iterable(listOfLists))
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"Flatten one level of nesting"
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return chain.from_iterable(listOfLists)
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def repeatfunc(func, times=None, *args):
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"""Repeat calls to func with specified arguments.
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@ -703,6 +704,27 @@ which incur interpreter overhead.
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except exception:
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pass
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def random_product(*args, repeat=1):
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"Random selection from itertools.product(*args, **kwds)"
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pools = [tuple(pool) for pool in args] * repeat
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return [random.choice(pool) for pool in pools]
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def random_permuation(iterable, r=None):
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"Random selection from itertools.permutations(iterable, r)"
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pool = tuple(iterable)
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r = len(pool) if r is None else r
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return random.sample(pool, r)
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def random_combination(iterable, r):
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"Random selection from itertools.combinations(iterable, r)"
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pool = tuple(iterable)
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return sorted(random.sample(pool, r), key=pool.index)
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def random_combination_with_replacement(iterable, r):
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"Random selection from itertools.combinations_with_replacement(iterable, r)"
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pool = tuple(iterable)
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return sorted(map(random.choice, repeat(pool, r)), key=pool.index)
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Note, many of the above recipes can be optimized by replacing global lookups
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with local variables defined as default values. For example, the
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*dotproduct* recipe can be written as::
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