Faster default __reduce__ for classes without __init__

[serhiy-storchaka]

BPO	23419
Nosy	@amauryfa, @pitrou, @avassalotti, @serhiy-storchaka
Files	object_reduce_no_init.patch

^{Note: these values reflect the state of the issue at the time it was migrated and might not reflect the current state.}

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GitHub fields:

assignee = 'https://github.com/serhiy-storchaka'
closed_at = <Date 2015-03-20.16:41:30.434>
created_at = <Date 2015-02-09.11:00:44.020>
labels = ['interpreter-core', 'performance']
title = 'Faster default __reduce__ for classes without __init__'
updated_at = <Date 2015-03-20.16:41:30.433>
user = 'https://github.com/serhiy-storchaka'

bugs.python.org fields:

activity = <Date 2015-03-20.16:41:30.433>
actor = 'serhiy.storchaka'
assignee = 'serhiy.storchaka'
closed = True
closed_date = <Date 2015-03-20.16:41:30.434>
closer = 'serhiy.storchaka'
components = ['Interpreter Core']
creation = <Date 2015-02-09.11:00:44.020>
creator = 'serhiy.storchaka'
dependencies = []
files = ['38052']
hgrepos = []
issue_num = 23419
keywords = ['patch']
message_count = 4.0
messages = ['235600', '238499', '238500', '238701']
nosy_count = 4.0
nosy_names = ['amaury.forgeotdarc', 'pitrou', 'alexandre.vassalotti', 'serhiy.storchaka']
pr_nums = []
priority = 'normal'
resolution = 'rejected'
stage = 'resolved'
status = 'closed'
superseder = None
type = 'performance'
url = 'https://bugs.python.org/issue23419'
versions = ['Python 3.5']

[serhiy-storchaka]

Proposed patch makes faster default __reduce__ implementation for the case when there is no non-trivial __init__ defined (e.g. for named tuples). In this case __reduce__ will return (cls, newargs) instead of (copyreg.__newobj__, (cls,) + newargs).

>>> pickletools.dis(pickletools.optimize(pickle.dumps(turtle.Vec2D(12, 34), 3)))
Before:
    0: \x80 PROTO      3
    2: c    GLOBAL     'turtle Vec2D'
   16: K    BININT1    12
   18: K    BININT1    34
   20: \x86 TUPLE2
   21: \x81 NEWOBJ
   22: .    STOP
After:
    0: \x80 PROTO      3
    2: c    GLOBAL     'turtle Vec2D'
   16: K    BININT1    12
   18: K    BININT1    34
   20: \x86 TUPLE2
   21: R    REDUCE
   22: .    STOP

Pickled size is the same, but pickling is faster. The benefit is in avoiding of importing copyreg.__newobj__ and allocating new tuple (cls,) + newargs.

Microbenchmarks results:

$ ./python -m timeit -s "import pickle; from turtle import Vec2D; a = [Vec2D(i, i+0.1) for i in range(1000)]" -- "pickle.dumps(a)"

Before: 100 loops, best of 3: 16.3 msec per loop
After: 100 loops, best of 3: 15.2 msec per loop

$ ./python -m timeit -s "import copy; from turtle import Vec2D; a = [Vec2D(i, i+0.1) for i in range(1000)]" -- "copy.deepcopy(a)"

Before: 10 loops, best of 3: 96.6 msec per loop
After: 10 loops, best of 3: 88.7 msec per loop

[amauryfa]

But isn't the result different?
NEWOBJ calls cls.__new__() and __init__ is skipped.
REDUCE calls cls(): both __new__ and __init__ are used.

[amauryfa]

Sorry, I missed the important point:
"for classes without __init__"

[serhiy-storchaka]

For a namedtuple such as turtle.Vec2D there is no significant difference in the time of unpickling. But for simpler type it is.

$ ./python -m timeit -s 'import pickle, turtle; global I' -s 'class I(int): pass' -s 'p = pickle.dumps([I(i) for i in range(1000)], 3)' -- 'pickle.loads(p)'

Before: 1000 loops, best of 3: 1.6 msec per loop
After: 1000 loops, best of 3: 1.82 msec per loop

So I withdraw my patch. Unpickling performance is more important than pickling performance, and status quo wins. Sorry for the noise.