Discontinuous slice in python list

Question

I'm looking for an efficient way of achieving this, which I think is a slicing-like operation:

>>> mylist = range(100) >>>magicslicer(mylist, 10, 20) [0,1,2,3,4,5,6,7,8,9,30,31,32,33,34,35,36,37,38,39,60,61,62,63......,97,98,99] 

the idea is: the slicing gets 10 elements, then skips 20 elements, then gets next 10, then skips next 20, and so on.

I think I should not use loops if possible, for the very reason to use slice is (I guess) to do the "extraction" efficiently in a single operation.

Thanks for reading.

Answer 1

itertools.compress (new in 2.7/3.1) nicely supports use cases like this one, especially when combined with itertools.cycle:

from itertools import cycle, compress seq = range(100) criteria = cycle([True]*10 + [False]*20) # Use whatever pattern you like >>> list(compress(seq, criteria)) [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99] 

Python 2.7 timing (relative to Sven's explicit list comprehension):

$ ./python -m timeit -s "a = range(100)" "[x for start in range(0, len(a), 30) for x in a[start:start+10]]" 100000 loops, best of 3: 4.96 usec per loop  $ ./python -m timeit -s "from itertools import cycle, compress" -s "a = range(100)" -s "criteria = cycle([True]*10 + [False]*20)" "list(compress(a, criteria))" 100000 loops, best of 3: 4.76 usec per loop 

Python 3.2 timing (also relative to Sven's explicit list comprehension):

$ ./python -m timeit -s "a = range(100)" "[x for start in range(0, len(a), 30) for x in a[start:start+10]]" 100000 loops, best of 3: 7.41 usec per loop  $ ./python -m timeit -s "from itertools import cycle, compress" -s "a = range(100)" -s "criteria = cycle([True]*10 + [False]*20)" "list(compress(a, criteria))" 100000 loops, best of 3: 4.78 usec per loop 

As can be seen, it doesn't make a great deal of difference relative to the in-line list comprehension in 2.7, but helps significantly in 3.2 by avoiding the overhead of the implicit nested scope.

A similar difference can also be seen in 2.7 if the aim is to iterate over the resulting sequence rather than turn it into a fully realised list:

$ ./python -m timeit -s "a = range(100)" "for x in (x for start in range(0, len(a), 30) for x in a[start:start+10]): pass" 100000 loops, best of 3: 6.82 usec per loop $ ./python -m timeit -s "from itertools import cycle, compress" -s "a = range(100)" -s "criteria = cycle([True]*10 + [False]*20)" "for x in compress(a, criteria): pass" 100000 loops, best of 3: 3.61 usec per loop 

For especially long patterns, it is possible to replace the list in the pattern expression with an expression like chain(repeat(True, 10), repeat(False, 20)) so that it never has to be fully created in memory.