Python __iter__() performance: iter() vs yield from vs for

benchmark_iter.py

#!/usr/bin/env python3
# Iter vs Yield vs For
# Copyright (C) 2021 Rodrigo Silva (MestreLion) <linux@rodrigosilva.com>
# License: GPLv3 or later, at your choice. See <http://www.gnu.org/licenses/gpl>

import collections.abc
import timeit

class Base(collections.abc.MutableMapping):
    def __init__(self, items: dict = None): self._items: dict = items or {}
    def __getitem__(self, key): return self._items[key]
    def __len__(self): return len(self._items)
    def __setitem__(self, key, value): self._items[key] = value
    def __delitem__(self, key): del self._items[key]
    def __contains__(self, key): return key in self._items  # optional
    def __str__(self): return self.__class__.__name__
    def __iter__(self): raise NotImplementedError

class Iter(Base):
    def __iter__(self): return iter(self._items)

class Yield(Base):
    def __iter__(self): return (yield from self._items)

class For(Base):
    def __iter__(self):
        for _ in self._items: yield _

def iterate(i):
    for _ in i: pass

d = {f"{k:03}": k for k in range(10)}

print("Benchmarking __iter__")
for cls in (Iter, Yield, For):
    iterator = cls(d)
    name = str(iterator)
    t = timeit.timeit(lambda: iterate(iterator))
    print(f"{name:5}: {t}")

# Benchmarking __iter__
# Iter : 0.3709624619805254
# Yield: 0.626235187985003
# For  : 0.656251213978976