[Python-ideas] Add nullifier argument to functools.reduce?

[Bob Ippolito]

Yes, such a 'reduce_with_attractor()' can be easily implemented with
itertools.accumulate. Maybe this would be good to add to the "Itertools
Recipes" section of the docs?



On Sat, Aug 23, 2014 at 10:25 AM, David Mertz <mertz at gnosis.cx> wrote:

> This "nullifier" is mathematically called an "absorbing element", but
> saying an "attractor" might be a little more general.  I.e. think of a
> local optimization problem, where multiple local min/max points might
> occur.  If you reach one, further iteration won't budge from that point,
> even if it's not the "global absorbing element."
>
> However, any such argument--including the much more useful
> sentinel/'stop_on' idea--significantly changes the semantics of reduce.  In
> particular, as is reduce() always consumes its iterator.  Under these
> changes, it may or may not consume the iterator, depending on what elements
> occur.
>
> Given that one can easily write one's own three line wrapper
> 'reduce_with_attractor()' for this special semantics which hasn't been
> given a use case, I can't see a point of including the argument in the
> stdlib.
>
> -1 on proposal.
>
>
>
> On Sat, Aug 23, 2014 at 8:30 AM, Warren Weckesser <
> warren.weckesser at gmail.com> wrote:
>
>> I'd like to add an additional optional argument to functools.reduce.
>> The argument is the "nullifier" of the reducing operation.  It is a value
>> such that function(nullifier, anything) returns nullifier.  For example,
>> if
>> function(x, y) computes x*y, the nullifier is 0.  If function(x, y) is
>> the intersection of the sets x and y, the nullifier is the empty set.
>>
>> The argument would allow reduce to "short circuit" its calculation.   When
>> reduce encounters the nullifier, it can return immediately.  This can
>> provide
>> a significant improvement in performance in some cases.
>>
>> The change is simple.  Here, for example, is  the "rough equivalent" for
>> functools.reduce from the docs:
>>
>>     def reduce(function, iterable, initializer=None):
>>         it = iter(iterable)
>>         if initializer is None:
>>             try:
>>                 initializer = next(it)
>>             except StopIteration:
>>                 raise TypeError('reduce() of empty sequence with no
>> initial value')
>>         accum_value = initializer
>>         for x in it:
>>             accum_value = function(accum_value, x)
>>         return accum_value
>>
>> Here's how it looks with the optional nullifier argument; the only
>> change is the new argument and an 'if' statement in the 'for' loop.
>>
>>     def reduce(function, iterable, initializer=None, nullifier=None):
>>         it = iter(iterable)
>>         if initializer is None:
>>             try:
>>                 initializer = next(it)
>>             except StopIteration:
>>                 raise TypeError('reduce() of empty sequence with no
>> initial value')
>>         accum_value = initializer
>>         for x in it:
>>             if nullifier is not None and accum_value == nullifier:
>>                 break
>>             accum_value = function(accum_value, x)
>>         return accum_value
>>
>> (It might be better to use a distinct singleton for the default
>> value of nullifier, to allow None to be a valid nullifier.)
>>
>> The actual implementation is in the extension module _functoolsmodule.c.
>> It looks like the changes to the C code should be straightforward.
>>
>>
>> Warren
>>
>>
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>
>
>
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