I was writing a function in python to extract original values given a list containing cumulative sum values. For eg - Given : cumulative_sum = [1, 3, 6, 10, 15, 21, 28, 36, 45]Output : [1, 2, 3, 4, 5, 6, 7, 8, 9]I came up with two functions A & B and am looking for feedback on them, especially using xrange() vs enumerate().import numpy as npcumulative = np.cumsum(range(1,10))def A(cumulative):    output = [0] * len(cumulative)    for i in xrange(len(cumulative)-1):        output[-(i+1)] = cumulative[-(i+1)] - cumulative[-(i+2)]    output[0] = cumulative[0]return outputdef B(cumulative):    output = [0] * len(cumulative)    for i,e in reversed(list(enumerate(cumulative))):        output[i]=cumulative[i] - cumulative[i-1]    output[0]=cumulative[0]return output
Extracting original values from cumulative sum values
python;beginner;comparative review
Both aren't great. B is really complicated, which is unnecessary. A has this extra negation:output[-(i+1)] = cumulative[-(i+1)] - cumulative[-(i+2)]You could have just used positive indices (why iterate backwards anyway?):output[i+1] = cumulative[i+1] - cumulative[i]I think sort of thing is best accomplished with itertools. In particular, there's a pairwise recipe:def pairwise(iterable):    s -> (s0,s1), (s1,s2), (s2, s3), ...    a, b = tee(iterable)    next(b, None)    return izip(a, b)Which translates directly into what we want to do:def C(cumulative):    yield cumulative[0]    for a, b in pairwise(cumulative):        yield b-aThis returns a generator, instead of a list, but generators are typically far more useful anyway. I feel that this approach makes it much more explicit what it is you're actually doing: you're yielding the first element, and then the pairwise difference between the rest.