# Does Python optimize low-power functions?

Robert Kern robert.kern at gmail.com
Fri Dec 6 20:12:30 CET 2013

```On 2013-12-06 19:01, Neil Cerutti wrote:
>> The following two functions return the same result:
>>
>>      x**2
>>      x*x
>>
>> But they may be computed in different ways.  The first choice
>> can accommodate non-integer powers and so it would logically
>> proceed by taking a logarithm, multiplying by the power (in
>> this case, 2), and then taking the anti-logarithm.  But for a
>> trivial value for the power like 2, this is clearly a wasteful
>> choice.  Just multiply x by itself, and skip the expensive log
>> and anti-log steps.
>>
>> My question is, what do Python interpreters do with power
>> operators where the power is a small constant, like 2?  Do they
>> know to take the shortcut?
>
> It uses a couple of fast algorithms for computing powers. Here's
> the excerpt with the comments identifying the algorithms used.
>  From longobject.c:
>
> 2873 if (Py_SIZE(b) <= FIVEARY_CUTOFF) {
> 2874         /* Left-to-right binary exponentiation (HAC Algorithm 14.79) */
> ...
> 2886 else {
> 2887         /* Left-to-right 5-ary exponentiation (HAC Algorithm 14.82) */

It's worth noting that the *interpreter* per se is not doing this. The
implementation of the `long` object does this in its implementation of the
`__pow__` method, which the interpreter invokes. Other objects may implement
this differently and use whatever optimizations they like. They may even (ab)use
the syntax for things other than numerical exponentiation where `x**2` is not
equivalent to `x*x`. Since objects are free to do so, the interpreter itself
cannot choose to optimize that exponentiation down to multiplication.

--
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma