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author | Georg Brandl <georg@python.org> | 2005-08-24 09:02:29 (GMT) |
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committer | Georg Brandl <georg@python.org> | 2005-08-24 09:02:29 (GMT) |
commit | 52715f69e7d57e189109a6092f093c8ce9d70abc (patch) | |
tree | 90b95899915b9a4b8a3e0aa10d15b577ec987b76 /Lib | |
parent | d35edda68245a7ab5f74c0f94ab13f6574df6a4e (diff) | |
download | cpython-52715f69e7d57e189109a6092f093c8ce9d70abc.zip cpython-52715f69e7d57e189109a6092f093c8ce9d70abc.tar.gz cpython-52715f69e7d57e189109a6092f093c8ce9d70abc.tar.bz2 |
[ 1113421 ] New tutorial tests in test_generators.py
Diffstat (limited to 'Lib')
-rw-r--r-- | Lib/test/test_generators.py | 78 |
1 files changed, 78 insertions, 0 deletions
diff --git a/Lib/test/test_generators.py b/Lib/test/test_generators.py index a77e958..fb88ffa 100644 --- a/Lib/test/test_generators.py +++ b/Lib/test/test_generators.py @@ -649,6 +649,84 @@ Ye olde Fibonacci generator, LazyList style. >>> firstn(iter(fib), 17) [1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584] >>> fib.close() + + +Running after your tail with itertools.tee (new in version 2.4) + +The algorithms "m235" (Hamming) and Fibonacci presented above are both +examples of a whole family of FP (functional programming) algorithms +where a function produces and returns a list while the production algorithm +suppose the list as already produced by recursively calling itself. +For these algorithms to work, they must: + +- produce at least a first element without presupposing the existence of + the rest of the list +- produce their elements in a lazy manner + +To work efficiently, the beginning of the list must not be recomputed over +and over again. This is ensured in most FP languages as a built-in feature. +In python, we have to explicitly maintain a list of already computed results +and abandon genuine recursivity. + +This is what had been attempted above with the LazyList class. One problem +with that class is that it keeps a list of all of the generated results and +therefore continually grows. This partially defeats the goal of the generator +concept, viz. produce the results only as needed instead of producing them +all and thereby wasting memory. + +Thanks to itertools.tee, it is now clear "how to get the internal uses of +m235 to share a single generator". + +>>> from itertools import tee +>>> def m235(): +... def _m235(): +... yield 1 +... for n in merge(times(2, m2), +... merge(times(3, m3), +... times(5, m5))): +... yield n +... m2, m3, m5, mRes = tee(_m235(), 4) +... return mRes + +>>> it = m235() +>>> for i in range(5): +... print firstn(it, 15) +[1, 2, 3, 4, 5, 6, 8, 9, 10, 12, 15, 16, 18, 20, 24] +[25, 27, 30, 32, 36, 40, 45, 48, 50, 54, 60, 64, 72, 75, 80] +[81, 90, 96, 100, 108, 120, 125, 128, 135, 144, 150, 160, 162, 180, 192] +[200, 216, 225, 240, 243, 250, 256, 270, 288, 300, 320, 324, 360, 375, 384] +[400, 405, 432, 450, 480, 486, 500, 512, 540, 576, 600, 625, 640, 648, 675] + +The "tee" function does just what we want. It internally keeps a generated +result for as long as it has not been "consumed" from all of the duplicated +iterators, whereupon it is deleted. You can therefore print the hamming +sequence during hours without increasing memory usage, or very little. + +The beauty of it is that recursive running after their tail FP algorithms +are quite straightforwardly expressed with this Python idiom. + + +Ye olde Fibonacci generator, tee style. + +>>> def fib(): +... +... def _isum(g, h): +... while 1: +... yield g.next() + h.next() +... +... def _fib(): +... yield 1 +... yield 2 +... fibTail.next() # throw first away +... for res in _isum(fibHead, fibTail): +... yield res +... +... fibHead, fibTail, fibRes = tee(_fib(), 3) +... return fibRes + +>>> firstn(fib(), 17) +[1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584] + """ # syntax_tests mostly provokes SyntaxErrors. Also fiddling with #if 0 |