# Find the highest product of three numbers in a list (Python)

I wrote the below as a solution to:

### Problem

Find the highest product of three numbers in a list

### Constraints

• Is the input a list of integers?
• Yes
• Can we get negative inputs?
• Yes
• Can there be duplicate entries in the input?
• Yes
• Will there always be at least three integers?
• No
• Can we assume the inputs are valid?
• No, check for None input
• Can we assume this fits memory?
• Yes

### Solution

from functools import reduce
from typing import List, Set, Callable

class Solution(object):

def max_prod_three(self, array: List[int]) -> int:
if array is None:
raise TypeError("array cannot be None")
if len(array) < 3:
raise ValueError("array must have at least 3 elements")
pos: List[int] = [n for n in array if n >= 0]
neg: List[int] = [n for n in array if n < 0]
pos_len: int = len(pos)
neg_len: int = len(neg)

candidates: Set[int] = set()
mult: Callable[[int, int], int] = lambda x,y:x*y

# possible combinations are:
# ---, --+, -+-, +--, -++, +-+, ++-, +++
# but order does not matter, so left with:
# --- -> -  : len(neg) >= 3, will never be the max if len(pos) > = 3, if len(pos) < 3,
#                            max will be with 3 lowest absolute values
# --+ -> +  : len(neg) >= 2, len(pos) >= 1, will be the max if  exists -- > any ++
# -++ -> -  : len(neg) >= 1, len(pos) >= 2, will never be the max if len(pos >= 3,
#                            if len(pos) == 2, max will be with lowest absolute value
# +++ -> +  : len(pos) >= 3, max is with 3 highest values

if neg_len >= 3 and pos_len < 3:
if neg_len >= 2 and pos_len >= 1:
candidates.add(reduce(mult, sorted(neg)[:2] + [max(pos)]))
if neg_len >= 1 and pos_len == 2:
candidates.add(reduce(mult, sorted(neg)[-1:] + pos))
if pos_len >= 3:

return max(candidates)


Please could I get some feedback on it? In particular:

• Readability and does the comment make it clear what the code is doing?
• Pythonic-ness
• Typing - I have not really used typing before. Is using it on every variable worth doing, or overkill? If you know of a good resource to help a beginner, please add a link, thanks :)
• Complexity - how would I calculate this in big-0 notation? The provided solution here is O(n) for time and O(1) space, but this runs much faster than that (~10x faster for list of 7,000 entries, ~2x faster for very small lists). Notice I loop over the array twice (to separate -ve and +ve numbers), while the solution given only loops over it once, but with quite a few min/max ops within that loop. As I understand it, my code is also O(n) (since O(2n) == O(n)). But if that is correct, how is the time taken so different?
• Lastly, this is not written to be production code of course. But, what would/could I add to it for some hypothetical production use case?
• Just to make the last question clearer, I am asking "If this were production code, what should or could I add that is currently missing?" Jul 22, 2021 at 12:49
• sorted() is $O(nlog(n))$, so is your code. Try to sort each array once. Jul 22, 2021 at 13:03

Regarding readability, I'd say typing variables makes them harder to read. As is:

mult = lambda x, y: x * y


I can already tell its a function with two arguments that returns their product. I think this just adds noise to that:

mult: Callable[[int, int], int] = lambda x, y: x * y


Also, these lines are kind of hard to read (there is a lot going on in each line, plus they have duplicated code):

candidates: Set[int] = set()
mult: Callable[[int, int], int] = lambda x,y:x*y

if neg_len >= 3 and pos_len < 3:
if neg_len >= 2 and pos_len >= 1:
candidates.add(reduce(mult, sorted(neg)[:2] + [max(pos)]))
if neg_len >= 1 and pos_len == 2:
candidates.add(reduce(mult, sorted(neg)[-1:] + pos))
if pos_len >= 3:

return max(candidates)


You could change them to something like:

candidates_groups = []

if neg_len >= 3 and pos_len < 3:

if neg_len >= 2 and pos_len >= 1:

if neg_len >= 1 and pos_len == 2:

if pos_len >= 3:

# reduce is cool, but this is more readable
candidates = [cand[0] * cand[1] * cand[2] for cand in candidates_groups]

return max(candidates)


Then regarding your answer's Big-O notation, as @Pavlo Slavynsky said, sorting a list is already O(nlog(n)), so that is your codes time complexity. Regarding space complexity, you store all of the values in the input in a new list, so that would make it O(n).

A few points:

1. Why is your max_prod_three function in a class at all? It seems to me like it would be fine in the global namespace.
2. Why write your own mult function when you can just import mul from the operator module in the standard library?
3. I agree with @m-alorda on the type hints being a bit overkill. I'm a big fan of type hints, but they do make the code less legible, and a lot of yours are unnecessary. Type hints are only useful when they tell IDEs and/or other programmers things about your code that wouldn't otherwise be obvious. A call to len() is never going to return a value that isn't an integer, and any IDE or python programmer worth its/their salt will know that. So annotating the return value of a call to len() as being an integer doesn't add any non-obvious information to the code, and just clutters it up a little.
• This was an answer to a code challenge. It already provided the Solution class and function signature - just like on Leetcode. Good point about the mul operator, thanks! Also good advice on the type hints - seems restricting them to function args and return type is best, with occasional use where they clarify something not obvious is best. Jul 30, 2021 at 11:04