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Learning python I encountered the following problem. I already have some list with integer numbers (for example initial_list). Then I'm trying to create list (for example result) with following numbers pattern:

result[len(result) - 1] = 1
result[i] = result[i + 1] * initial_list[i]

Example:

initial_list = [2, 2, 2, 2, 3, 2, 2]
result = [192, 96, 48, 24, 12, 4, 2, 1]

Here is my first implementation:

import numpy as np
initial_list = [2, 2, 2, 2, 3, 2, 2]
result = [1]
for number in reversed(initial_list):
    result.append(result[-1] * number)
result = np.array(result[::-1])

Here is my second implementation:

import numpy as np
initial_list = [2, 2, 2, 2, 3, 2, 2]
result = np.ones(len(initial_list) + 1)
for i, number in enumerate(reversed(initial_list)):
    result[len(result) - i - 2] = result[len(result) - i - 1] * number

I guess second one is much better because it does not contain append method and initialize list with concrete size. Also result = np.ones(len(initial_list) + 1) consists with float point number which is not correct. I wonder whether there is a simpler version of the implementation of this algorithm.

After that algorithm I'm creating OrderedDict:

from collections import OrderedDict
ordered_dict = OrderedDict(zip(other_list, result))

Maybe I can reverse result list during creating OrderedDict for O(1) "on fly" like reversed works in for looping, so that I can simplify algorithm above.

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  • what is the algorithm supposed to do? Commented Jun 28, 2015 at 22:16
  • @PadraicCunningham It should create list from initial list with patter that mentioned above:result[len(result) - 1] = 1, result[i] = result[i + 1] * initial_list[i] Commented Jun 28, 2015 at 22:18
  • I think a list comprehension would be a good idea, but I'm having trouble figuring out your algorithm. For instance, result[len(result) - 1] = 1 only makes sense if result has some data in it. What does result look like at the beginning? Commented Jun 28, 2015 at 22:21
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    @Quill Maybe I misunderstood? I read the "I wonder whether there is a simpler version of the implementation of this algorithm." part specifically and thought that it would make more sense there since it seems to be a problem of code optimization. In the on-topic section, it seems to say that "Best practices and design pattern usage" are on-topic "for feedback on a specific working piece of code from your project". Clearly, you would know better than me what is off-topic, but I just don't understand why you believe so. Commented Jun 28, 2015 at 23:30
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    You'd be correct, it seems, thank for you reading the on-topic section, and help center guidelines. OP, feel free to take this to Code Review if you please. Commented Jun 28, 2015 at 23:33

3 Answers 3

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4

If numpy is an option, you can do it with cumprod:

import numpy as np

initial_list = [2, 2, 2, 2, 3, 2, 2]

>> np.append(np.cumprod(initial_list[:: -1])[:: -1], [1])
array([192,  96,  48,  24,  12,   4,   2,   1])
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3 Comments

numpy is definitely an option, they are using it ;)
@PadraicCunningham :-) Right you are. Thanks!
@AmiTavory In a single line, that is what I need. Thanks!
3

You can use itertools.accumulate and operator.mul

>>> from itertools import accumulate
>>> from operator import mul
>>> a = [2, 2, 2, 2, 3, 2, 2]
>>> list(accumulate(reversed(a + [1]), mul))[::-1]
[192, 96, 48, 24, 12, 4, 2, 1]
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1 Comment

Nice combination of itertools + operator.
0

Why can't you just do

result = [0] * len(initial_list)
result[-1] = 1
for i in xrange(len(result) - 2, -1, -1):
  result[i] = result[i + 1] * initial_list[i]
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