foreach(explode(',' $foo) as $bar) { ... }
vs
$test = explode(',' $foo);
foreach($test as $bar) { ... }
In the first example, does it explode
the $foo
string for each iteration or does PHP keep it in memory exploded in its own temporary variable? From an efficiency point of view, does it make sense to create the extra variable $test
or are both pretty much equal?
I could make an educated guess, but let's try it out!
I figured there were three main ways to approach this.
My hypotheses:
Here's my test script:
<?php
ini_set('memory_limit', '1024M');
$listStr = 'text';
$listStr .= str_repeat(',text', 9999999);
$timeStart = microtime(true);
/*****
* {INSERT LOOP HERE}
*/
$timeEnd = microtime(true);
$timeElapsed = $timeEnd - $timeStart;
printf("Memory used: %s kB\n", memory_get_peak_usage()/1024);
printf("Total time: %s s\n", $timeElapsed);
And here are the three versions:
1)
// explode separately
$arr = explode(',', $listStr);
foreach ($arr as $val) {}
2)
// explode inline-ly
foreach (explode(',', $listStr) as $val) {}
3)
// tokenize
$tok = strtok($listStr, ',');
while ($tok = strtok(',')) {}
Looks like some assumptions were disproven. Don't you love science? :-)
explode()
inline without pre-assignment, it's a fair bit slower for some reason.strtok()
every iteration. More on this below.In terms of number of function calls, explode()
ing really tops tokenizing. O(1) vs O(n)
I added a bonus to the chart where I run method 1) with a function call in the loop. I used strlen($val)
, thinking it would be a relatively similar execution time. That's subject to debate, but I was only trying to make a general point. (I only ran strlen($val)
and ignored its output. I did not assign it to anything, for an assignment would be an additional time-cost.)
// explode separately
$arr = explode(',', $listStr);
foreach ($arr as $val) {strlen($val);}
As you can see from the results table, it then becomes the slowest method of the three.
This is interesting to know, but my suggestion is to do whatever you feel is most readable/maintainable. Only if you're really dealing with a significantly large dataset should you be worried about these micro-optimizations.