As discussed on python-dev, it would be nice to break long_pow()'s reliance on that the number of bits in a CPython long "digit" is a multiple of 5.

Moving to the sliding-window algorithm would do that (it has to be able to cross digit boundaries to fill the current window), and would be better on some other counts too: the precomputed table can be half the size (or we can add an extra bit to the window for the same table size), and it can - depending on exponent bit patterns - sometimes reduce the number of multiplies needed too.

So I intend to do that, and bump the window size from 5 to 6 (which would yield a significant, although modest, speed improvement for giant-exponent cases).

Nope, boosting the window size to 6 doesn't appear to really help at all, at least not on my box. Regardless of the window size, we have to do a bigint square for every bit position in the exponent. I don't know of any way to speed that (short of speeding multiplication, and we already make a special case of squaring).

So that dominates. Even for an exponent of a million solid 1-bits, the overall timing difference appears insignificant.

So I cut the window size back to 5 bits again. That has the benefit of cutting the old table size in half, which also cuts the precomputation time to fill it about in half, which should have some minor benefit for saner (smaller) exponents.

As a sanity check, I also tried cutting the window size to 3 bits. That had an obvious bad timing impact on huge exponents of solid 1 bits.

Since cutting the window size by 1 cut the size of the dynamic precomputed table in half, the overhead of the sliding window method was correspondingly reduced. It can pay off at exponents of half the bit length now, so that threshold was also changed.

New changeset 863729e9c6f599286f98ec37c8716e982c4ca9dd by Tim Peters in branch 'main':
bpo-46218: Change long_pow() to sliding window algorithm (GH-30319)
https://github.com/python/cpython/commit/863729e9c6f599286f98ec37c8716e982c4ca9dd