gh-143667: Specialize FOR_ITER for dict.items(), and scalar replace the pair in the JIT

[Fidget-Spinner]

This PR specializes FOR_ITER for iterating dct.items(). Furthermore, in the JIT, it goes one step further by avoiding allocation/reuse/extra writes to the pair tuple entirely. Choosing to scalar replace the tuple on the stack instead.

According to stats, dict items makes up 33% of specialization failures.

Roughly 33% reduction in execution time for iteration through dictionary items in the JIT on microbenchmark:

def testfunc(dct):
    for k, v in dct.items():
        pass

n = 10000000
dct = dict(zip(range(n), range(n)))

import sys
import time
start = time.time()
for _ in range(20):
    testfunc(dct)
end = time.time()
print(end - start)

JIT on on both
Main: 3.54s
This branch: 2.34s

• Issue: Specialize FOR_ITER for dict.items() #143667

[eendebakpt]

Nice work! Would the same approach work for enumerate?

[Fidget-Spinner]

Nice work! Would the same approach work for enumerate?

Yes. I'm hesitant to do it for that though. For enumerate, I'd rather we write a Python equivalent for the JIT and let it specialize on the generators.

[Fidget-Spinner]

@eendebakpt sorry I can't reproduce the speedup on deepcopy anymore. Deepcopy is too unstable on my machine so I have no trust in the results. From what I can see, it's roughly the same speed.