PHP's array_slice vs Python's splitting arrays - php

Question

Some background
I was having a go at the common "MaxProfit" programming challenge. It basically goes like this:
Given a zero-indexed array A consisting of N integers containing daily
prices of a stock share for a period of N consecutive days, returns
the maximum possible profit from one transaction during this period.
I was quite pleased with this PHP algorithm I came up, having avoided the naive brute-force attempt:
public function maxProfit($prices)
{
$maxProfit = 0;
$key = 0;
$n = count($prices);
while ($key < $n - 1) {
$buyPrice = $prices[$key];
$maxFuturePrice = max( array_slice($prices, $key+1) );
$profit = $maxFuturePrice - $buyPrice;
if ($profit > $maxProfit) $maxProfit = $profit;
$key++;
}
return $maxProfit;
}
However, having tested my solution it seems to perform badly performance-wise, perhaps even in O(n2) time.
I did a bit of reading around the subject and discovered a very similar python solution. Python has some quite handy array abilities which allow splitting an array with a a[s : e] syntax, unlike in PHP where I used the array_slice function. I decided this must be the bottleneck so I did some tests:
Tests
PHP array_slice()
$n = 10000;
$a = range(0,$n);
$start = microtime(1);
foreach ($a as $key => $elem) {
$subArray = array_slice($a, $key);
}
$end = microtime(1);
echo sprintf("Time taken: %sms", round(1000 * ($end - $start), 4)) . PHP_EOL;
Results:
$ php phpSlice.php
Time taken: 4473.9199ms
Time taken: 4474.633ms
Time taken: 4499.434ms
Python a[s : e]
import time
n = 10000
a = range(0, n)
start = time.time()
for key, elem in enumerate(a):
subArray = a[key : ]
end = time.time()
print "Time taken: {0}ms".format(round(1000 * (end - start), 4))
Results:
$ python pySlice.py
Time taken: 213.202ms
Time taken: 212.198ms
Time taken: 215.7381ms
Time taken: 213.8121ms
Question
Why is PHP's array_slice() around 20x less efficient than Python?
Is there an equivalently efficient method in PHP that achieves the above and thus hopefully makes my maxProfit algorithm run in O(N) time? Edit I realise my implementation above is not actually O(N), but my question still stands regarding the efficiency of slicing arrays.

Answer 1

I don't really know, but PHP's arrays are messed up hybrid monsters, maybe that's why. Python's lists are really just lists, not at the same time dictionaries, so they might be simpler/faster because of that.
Yes, do an actual O(n) solution. Your solution isn't just slow because PHP's slicing is apparently slow, it's slow because you obviously have an O(n^2) algorithm. Just walk over the array once, keep track of the minimum price found so far, and check it with the current price. Not something like max over half the array in every single loop iteration.