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Exceptions slow in 3.11, depending on location #109181

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@pochmann

Description

@pochmann
Issue body actions

Bug report

Bug description:

(From Discourse)

Consider these two functions:

def short():
    try:
        if 0 == 1:
            unreached
        raise RuntimeError
    except RuntimeError:
        pass

def long():
    try:
        if 0 == 1:
            unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached
            unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached
            unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached
            unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached
            unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached
            unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached
            unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached
            unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached
            unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached
            unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached
        raise RuntimeError
    except RuntimeError:
        pass

The only difference is that long() has 100 unreached statements instead of just one. But it takes much longer in Python 3.11 (and a bit longer in Python 3.10). Times from @jamestwebber (here):

Python: 3.11.5 | packaged by conda-forge | (main, Aug 27 2023, 03:34:09) [GCC 12.3.0]
 176.5 ±  0.4 ns  short
 644.7 ±  0.6 ns  long

Python: 3.10.12 | packaged by conda-forge | (main, Jun 23 2023, 22:40:32) [GCC 12.3.0]
 150.7 ±  0.1 ns  short
 167.0 ±  0.2 ns  long

Why? Shouldn't it just jump over them all and be just as fast as short()?

Benchmark script

Attempt This Online!):

from timeit import timeit
from time import perf_counter as time
from statistics import mean, stdev
import sys


def short():
    try:
        if 0 == 1:
            unreached
        raise RuntimeError
    except RuntimeError:
        pass


def long():
    try:
        if 0 == 1:
            unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached
            unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached
            unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached
            unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached
            unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached
            unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached
            unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached
            unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached
            unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached
            unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached; unreached
        raise RuntimeError
    except RuntimeError:
        pass


funcs = short, long

for _ in range(3):
    times = {f: [] for f in funcs}
    def stats(f):
        ts = [t * 1e9 for t in sorted(times[f])[:5]]
        return f'{mean(ts):6.1f} ± {stdev(ts):4.1f} ns '
    for _ in range(100):
        for f in funcs:
            t = timeit(f, number=10**4) / 1e4
            times[f].append(t)
    for f in sorted(funcs, key=stats):
        print(stats(f), f.__name__)
    print()

print('Python:', sys.version)

In fact it takes time linear in how many unreached statements there are. Times for 100 to 100000 unreached statements (on one line, before the try):

   100     2.6 μs
  1000    24.3 μs
 10000   253.3 μs
100000  2786.2 μs
Benchmark script
from time import perf_counter as time
from timeit import repeat

for e in range(2, 6):
    n = 10 ** e
    exec(f'''def f():
        if 0 == 1:
            {'unreached;' * n}
        try:
            raise RuntimeError
        except RuntimeError:
            pass''')
    number = 10**6 // n
    t = min(repeat(f, number=number)) / number
    print(f'{n:6} {t * 1e6 :7.1f} μs')

Attempt This Online!

The slowness happens when the unreached statements are anywhere before the raise, and not when they're anywhere after the raise (demo). So it seems what matters is location of the raise in the function. Long code before it somehow makes it slow.

This has a noticeable impact on real code I wrote (assuming I pinpointed the issue correctly): two solutions for a task, and one was oddly slower (~760 vs ~660 ns) despite executing the exact same sequence of bytecode operations. Just one jump length differed, leading to a raise at a larger address.

Benchmark script with those two solutions and the relevant test case:

The functions shall return the one item from the iterable, or raise an exception if there are fewer or more than one. Testing with an empty iterable, both get the iterator, iterate it (nothing, since it's empty), then raise. The relevant difference appears to be that the slower one has the raise written at the bottom, whereas the faster one has it near the top.

Sample times:

 664.4 ±  8.6 ns  one_sequential
 762.1 ± 28.8 ns  one_nested

Python: 3.11.4 (main, Jun 24 2023, 10:18:04) [GCC 13.1.1 20230429]

Code:

from timeit import timeit
from statistics import mean, stdev
from itertools import repeat, starmap, islice
import sys


def one_nested(iterable, too_short=None, too_long=None):
    it = iter(iterable)
    for first in it:
        for second in it:
            raise too_long or ValueError(
                'Expected exactly one item in iterable, but',
                f'got {first!r}, {second!r}, and perhaps more.'
            )
        return first
    raise too_short or ValueError('too few items in iterable (expected 1)')


def one_sequential(iterable, too_short=None, too_long=None):
    it = iter(iterable)

    for first in it:
        break
    else:
        raise too_short or ValueError('too few items in iterable (expected 1)')

    for second in it:
        raise too_long or ValueError(
            'Expected exactly one item in iterable, but '
            f'got {first!r}, {second!r}, and perhaps more.'
        )

    return first


funcs = one_nested, one_sequential

def empty(f):
    iterable = iter(())
    too_short = RuntimeError()
    for _ in repeat(None, 10**4):
        try:
            f(iterable, too_short)
        except RuntimeError:
            pass

for case in empty,:

    times = {f: [] for f in funcs}
    def stats(f):
        ts = [t * 1e9 for t in sorted(times[f])[:5]]
        return f'{mean(ts):6.1f} ± {stdev(ts):4.1f} ns '
    for _ in range(100):
        for f in funcs:
            t = timeit(lambda: case(f), number=1) / 1e4
            times[f].append(t)
    for f in sorted(funcs, key=stats):
        print(stats(f), f.__name__)
    print()

print('Python:', sys.version)

Attempt This Online!

CPython versions tested on:

3.10, 3.11

Operating systems tested on:

Linux, macOS

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    3.11only security fixesonly security fixes3.12only security fixesonly security fixes3.13bugs and security fixesbugs and security fixesinterpreter-core(Objects, Python, Grammar, and Parser dirs)(Objects, Python, Grammar, and Parser dirs)performancePerformance or resource usagePerformance or resource usagetype-bugAn unexpected behavior, bug, or errorAn unexpected behavior, bug, or error

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