On Thu, Jan 5, 2017 at 4:00 AM Matt Gilson <m...@getpattern.com> wrote:
> But, I think that the problem with adding `__hash__` to
> collections.abc.Iterable is that not all iterables are immutable -- And if
> they aren't immutable, then allowing them to be hashed is likely to be a
> pretty bad idea...
>
Good point. A better option is to add collections.abc.ImmutableIterable
that derives from Iterable and provides __hash__. Since tuple inherits
from it, it can choose to delegate up. Then I think everyone is happy.
>
> I'm still having a hard time being convinced that this is very much of an
> optimization at all ...
>
> If you start hashing tuples that are large enough that memory is a
> concern, then that's going to also take a *really* long time and probably
> be prohibitive anyway. Just for kicks, I decided to throw together a
> simple script to time how much penalty you pay for hashing a tuple:
>
> class F(object):
> def __init__(self, arg):
> self.arg = arg
>
> def __hash__(self):
> return hash(tuple(self.arg))
>
>
> class T(object):
> def __init__(self, arg):
> self.arg = tuple(arg)
>
> def __hash__(self):
> return hash(self.arg)
>
>
> class C(object):
> def __init__(self, arg):
> self.arg = tuple(arg)
> self._hash = None
>
> def __hash__(self):
> if self._hash is None:
> self._hash = hash(tuple(self.arg))
> return self._hash
>
> import timeit
>
> print(timeit.timeit('hash(f)', 'from __main__ import F; f =
> F(list(range(500)))'))
> print(timeit.timeit('hash(t)', 'from __main__ import T; t =
> T(list(range(500)))'))
> print(timeit.timeit('hash(c)', 'from __main__ import C; c =
> C(list(range(500)))'))
>
> results = []
> for i in range(1, 11):
> n = i * 100
> t1 = timeit.timeit('hash(f)', 'from __main__ import F; f =
> F(list(range(%d)))' % i)
> t2 = timeit.timeit('hash(t)', 'from __main__ import T; t =
> T(list(range(%d)))' % i)
> results.append(t1/t2)
> print(results)
>
>
> F is going to create a new tuple each time and then hash it. T already
> has a tuple, so we'll only pay the cost of hashing a tuple, not the cost of
> constructing a tuple and C caches the hash value and re-uses it once it is
> known. C is the winner by a factor of 10 or more (no surprise there). But
> the real interesting thing is that the the ratio of the timing results from
> hashing `F` vs. `T` is relatively constant in the range of my test (up to
> 1000 elements) and that ratio's value is approximately 1.3. For most
> applications, that seems reasonable. If you really need a speed-up, then I
> suppose you could recode the thing in Cython and see what happens, but I
> doubt that will be frequently necessary. If you _do_ code it up in Cython,
> put it up on Pypi and see if people use it...
>
>
> On Wed, Jan 4, 2017 at 5:04 PM, Neil Girdhar <mistersh...@gmail.com>
> wrote:
>
> Couldn't you add __hash__ to collections.abc.Iterable ? Essentially,
> expose __hash__ there; then all iterables automatically have a default hash
> that hashes their ordered contents.
>
> On Wednesday, January 4, 2017 at 7:37:26 PM UTC-5, Steven D'Aprano wrote:
>
> On Wed, Jan 04, 2017 at 04:38:05PM -0500, j...@math.brown.edu wrote:
> > Instead of the proposals like "hash.from_iterable()", would it make
> sense
> > to allow tuple.__hash__() to accept any iterable, when called as a
> > classmethod?
>
> The public API for calculating the hash of something is to call the
> hash() builtin function on some object, e.g. to call tuple.__hash__ you
> write hash((a, b, c)). The __hash__ dunder method is implementation, not
> interface, and normally shouldn't be called directly.
>
> Unless I'm missing something obvious, your proposal would require the
> caller to call the dunder methods directly:
>
> class X:
> def __hash__(self):
> return tuple.__hash__(iter(self))
>
> I consider that a poor interface design.
>
> But even if we decide to make an exception in this case, tuple.__hash__
> is currently an ordinary instance method right now. There's probably
> code that relies on that fact and expects that:
>
> tuple.__hash__((a, b, c))
>
> is currently the same as
>
> (a, b, c).__hash__()
>
>
> (Starting with the hash() builtin itself, I expect, although that is
> easy enough to fix if needed.) Your proposal will break backwards
> compatibility, as it requires a change in semantics:
>
> (1) (a, b, c).__hash__() must keep the current behaviour, which
> means behaving like a bound instance method;
>
> (2) But tuple.__hash__ will no longer return an unbound method (actually
> a function object, but the difference is unimportant) and instead will
> return something that behaves like a bound class method.
>
> Here's an implementation which does this:
>
> http://code.activestate.com/recipes/577030-dualmethod-descriptor/
>
> so such a thing is possible. But it breaks backwards-compatability and
> introduces something which I consider to be an unclean API (calling a
> dunder method directly). Unless there's a *really* strong advantage to
>
> tuple.__hash__(...)
>
> over
>
> hash.from_iterable(...)
>
> (or equivalent), I would be against this change.
>
>
>
> > (And similarly with frozenset.__hash__(), so that the fast C
> > implementation of that algorithm could be used, rather than the slow
> > collections.Set._hash() implementation. Then the duplicated
> implementation
> > in _collections_abc.py's Set._hash() could be removed completely,
> > delegating to frozenset.__hash__() instead.)
>
> This is a good point. Until now, I've been assuming that
> hash.from_iterable should consider order. But frozenset shows us that
> sometimes the hash should *not* consider order.
>
> This hints that perhaps the hash.from_iterable() should have its own
> optional dunder method. Or maybe we need two functions: an ordered
> version and an unordered version.
>
> Hmmm... just tossing out a wild idea here... let's get rid of the dunder
> method part of your suggestion, and add new public class methods to
> tuple and frozenset:
>
> tuple.hash_from_iter(iterable)
> frozenset.hash_from_iter(iterable)
>
>
> That gets rid of all the objections about backwards compatibility, since
> these are new methods. They're not dunder names, so there are no
> objections to being used as part of the public API.
>
> A possible objection is the question, is this functionality *actually*
> important enough to bother?
>
> Another possible objection: are these methods part of the sequence/set
> API? If not, do they really belong on the tuple/frozenset? Maybe they
> belong elsewhere?
>
>
>
> > Would this API more cleanly communicate the algorithm being used and the
> > implementation,
>
> No. If you want to communicate the algorithm being used, write some
> documentation.
>
> Seriously, the public API doesn't communicate the algorithm used for the
> implementation. How can it? We can keep the same interface and change
> the implementation, or change the interface and keep the implementation.
> The two are (mostly) independent.
>
>
>
> > while making a smaller increase in API surface area
> > compared to introducing a new function?
>
> It's difficult to quantify "API surface area". On the one hand, we have
> the addition of one or two new functions or methods. Contrast with:
>
> * introducing a new kind of method into the built-ins (one which
> behaves like a classmethod when called from the class, and like
> an instance method when called from an instance);
>
> * changing tuple.__hash__ from an ordinary method to one of the
> above special methods;
>
> * and likewise for frozenset.__hash__;
>
> * change __hash__ from "only used as implementation, not as
> interface" to "sometimes used as interface".
>
>
> To me, adding one or two new methods/functions is the smaller, or at
> least less disruptive, change.
>
>
>
> --
> Steve
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>
>
> --
>
> [image: pattern-sig.png]
>
> Matt Gilson // SOFTWARE ENGINEER
>
> E: m...@getpattern.com // P: 603.892.7736 <(603)%20892-7736>
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