[issue36781] Optimize sum() for bools

[Serhiy Storchaka]

Serhiy Storchaka  added the comment:

Well, it is good for people who already sum bools. But if you are concerned 
about microoptimization, sum(1 for ... if ...) can be better variant.

--
resolution:  -> fixed
stage: patch review -> resolved
status: open -> closed
versions: +Python 3.9 -Python 3.8

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[issue36781] Optimize sum() for bools

[Vedran Čačić]

Vedran Čačić  added the comment:

I don't think anything _bad_ can happen with that optimization, if it's already 
written. And people (me included) do like to write shorter expressions instead 
of longer ones.

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nosy: +veky

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[issue36781] Optimize sum() for bools

[Dino Viehland]

Dino Viehland  added the comment:

Sorry, it seemed like a perfectly reasonable change when I was looking at the 
PR!

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[issue36781] Optimize sum() for bools

[Serhiy Storchaka]

Serhiy Storchaka  added the comment:

Oh, I was going to withdraw this.

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[issue36781] Optimize sum() for bools

[Dino Viehland]

Dino Viehland  added the comment:


New changeset 88bdb9280b251d753f1b1c8d9183de0fff003622 by Dino Viehland (Serhiy 
Storchaka) in branch 'master':
bpo-36781: Optimize sum() for bools. (#13074)
https://github.com/python/cpython/commit/88bdb9280b251d753f1b1c8d9183de0fff003622


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nosy: +dino.viehland

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[issue36781] Optimize sum() for bools

[Serhiy Storchaka]

Serhiy Storchaka  added the comment:

I am not sure that this optimization should be added. sum(pred(x) for x in 
data) will be always slower than sum(1 for x in data if pred(x)) because more 
items is passed to sun() in the former case. It can be considered as an 
anti-pattern.

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[issue36781] Optimize sum() for bools

[Josh Rosenberg]

Change by Josh Rosenberg :


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nosy: +josh.r

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[issue36781] Optimize sum() for bools

[Serhiy Storchaka]

Change by Serhiy Storchaka :


--
keywords: +patch
pull_requests: +13010
stage:  -> patch review

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[issue36781] Optimize sum() for bools

[Serhiy Storchaka]

New submission from Serhiy Storchaka :

To count the number of items that satisfy certain condition you can use either

sum(1 for x in data if pred(x))

or

sum(pred(x) for x in data)

where pred(x) is a boolean expression.

The latter case is shorter but slower. There are two causes for this:

1. The generator expression needs to generate more items, not only when pred(x) 
is true, but also when pred(x) is false.

2. sum() is optimized for integers and floats, but not for bools.

The first cause is out of the scope of this issue, but sum() can optimized for 
bools.

$ ./python -m timeit -s "a = [True] * 10**6" -- "sum(a)"
Unpatched:  10 loops, best of 5: 22.3 msec per loop
Patched:50 loops, best of 5: 6.26 msec per loop

$ ./python -m timeit -s "a = list(range(10**6))" -- "sum(x % 2 == 0 for x in a)"
Unpatched:  5 loops, best of 5: 89.8 msec per loop
Patched:5 loops, best of 5: 67.5 msec per loop

$ ./python -m timeit -s "a = list(range(10**6))" -- "sum(1 for x in a if x % 2 
== 0)"
5 loops, best of 5: 53.9 msec per loop

--
components: Interpreter Core
messages: 341330
nosy: rhettinger, serhiy.storchaka
priority: normal
severity: normal
status: open
title: Optimize sum() for bools
type: performance
versions: Python 3.8

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