Improve performance of dataclasses.asdict by caching field names #138232
Description
Feature or enhancement
Proposal:
About 8 years ago @ericvsmith asked:
Line 1381 in c779f23
By caching the field names of a dataclass on the class the performance improves:
asdict: Mean +- std dev: [main] 2.33 us +- 0.14 us -> [pr] 1.65 us +- 0.08 us: 1.41x faster
astuple: Mean +- std dev: [main] 2.77 us +- 0.15 us -> [pr] 2.15 us +- 0.09 us: 1.29x faster
f.__getstate__(): Mean +- std dev: [main] 941 ns +- 64 ns -> [pr] 360 ns +- 18 ns: 2.61x faster
Benchmark hidden because not significant (1): instance creation
Geometric mean: 1.47x faster
Test script
(executed on non-pgo build)
import pyperf
setup = """
from dataclasses import dataclass, asdict, astuple
from pickle import dumps
@dataclass
class Simple:
i : int
s : str
l : list
s = Simple(10, 'hi', [3, 1, 4, 1])
@dataclass(frozen=True, slots=True)
class Frozen:
i : int
s : str
l : list
f = Frozen(10, 'hi', [3, 1, 4, 1])
f.__getstate__()
"""
runner = pyperf.Runner()
runner.timeit(name="instance creation", stmt="Simple(10, 'hi', [3, 1, 4, 1])", setup=setup)
runner.timeit(name="asdict", stmt="asdict(s)", setup=setup)
runner.timeit(name="astuple", stmt="astuple(s)", setup=setup)
runner.timeit(name="f.__getstate__()", stmt="f.__getstate__()", setup=setup)
The main downside of caching the field names is that (per dataclass, not per instance) we have an additional private field on the class with a list of strings.
Has this already been discussed elsewhere?
No response given
Links to previous discussion of this feature:
No response