Question

Up to this point in time, in Python, I’ve only ever seen list comprehensions that specify the inclusion of one element at time. For example, they’re all in the following form

[f(x) for x in <iterable>]

Is there any way to specify more than one element at a time? For example,

[f(x), g(x) for x in <iterable>]

I’m asking because I want to create a list comprehension that calculates all the divisors of some number x, but I want to do this as efficiently as possible. Right now I’m using the following,

[y for y in range(1,x+1) if x%y == 0]

but I’d like to do something like this,

[y, x/y for y in range(1, sqrt(x)+1) if x%y == 0]

as this would be more efficient. Btw, I have no practical reason for doing this. It’s simply a challenge problem that somebody told me and the goal is to do it with the smallest, most efficient list comprehension possible.

Thanks in advance.

Edit: Ok, it looks like I have to use tuples. I was trying to avoid that though as I’d then have to make another function to flatten the list which would make my solution longer.

Edit 2: Just in case anyone stumbles upon this question, the answer to what I wanted to do in my original question is this:

[y for x in <iterable> for y in f(x), g(x)]

It uses nested for loops in the list comprehension to get the job done.

Answer 1

You can assign to tuples

[(y, x/y) for y in range(1, int(sqrt(x))+1) if x%y == 0]

Not really related to your basic question, but your example: I had to convert the 2nd parameter of range() to an int since sqrt() resulted in a float in my test code.

Update re Edit in post:

To flatten this list of tuples:

In [24]: s
Out[24]: [(1, 20), (2, 10), (4, 5)]

use this:

In [25]: import operator

create a tuple:

In [26]: reduce(operator.add, s, ())
Out[26]: (1, 20, 2, 10, 4, 5)

create a list:

In [27]: list(reduce(operator.add, s, ()))
Out[27]: [1, 20, 2, 10, 4, 5]

Note: In a helpful comment @jamylak points out that reduce and operator.add run order O(N^2), and that using itertools.chain would be much more efficient. This becomes more important as the size of the list grows and should be considered in that case.