> I'd like to point out that this uses important improvements over the naive Ziuba's strawman version
The Ziuba version was not "a strawman", it was an example used to trivially generate high in-request CPU load and demonstrate the misbehavior of evented system under this condition.
If you want to compute fibonacci fast, just use Binet's Fibonacci formula, it runs in O(1), then your only issue is that you're going to overflow very fast on doubles (not sure you'll even reach fib 1500). Using decimal, you can probably go higher before reaching your limits (though you'll run out of display space long before that if you print all digits): Python's decimal.Decimal reaches ~fib 4000000000 before an overflow error.
Binet's formula doesn't run in O(1) if you want an exact answer. Using a + b * sqrt(5) representations or floating point with sufficient precision, you can get O(n log n 2^O(log* n)) time (quoting Wikipedia's Furer's algorithm page here). Which beats O(n log n log log n) time, if you were wondering. If something beats that for computing Fibonacci numbers, that'd be pretty cool.
The Ziuba version was not "a strawman", it was an example used to trivially generate high in-request CPU load and demonstrate the misbehavior of evented system under this condition.
If you want to compute fibonacci fast, just use Binet's Fibonacci formula, it runs in O(1), then your only issue is that you're going to overflow very fast on doubles (not sure you'll even reach fib 1500). Using decimal, you can probably go higher before reaching your limits (though you'll run out of display space long before that if you print all digits): Python's decimal.Decimal reaches ~fib 4000000000 before an overflow error.