min() & max() vs sorted()

[Tim Peters]

[MRAB]
>>> Some time after reading about Python 2.5 and how the built-in functions
>>> 'min' and 'max' will be getting a new 'key' argument, I wondered how
>>> they would treat those cases where the keys were the same, for example:
>>>
>>> L = ["four", "five"]
>>> print min(L, key = len), max(L, key = len)
>>>
>>> The result is:
>>>
>>> ('four', 'four')

[Tim Peters]
>> min() and max() both work left-to-right, and return the minimal or
>> maximal element at the smallest index.

[MRAB]
> It doesn't say that in the documentation.

Right, the /language/ doesn't define anything about which specific
minimal or maximal element is returned.  Since you specifically
mentioned Python 2.5, I figured you were asking about CPython -- which
has always behaved in the way I explained.

>>> I would've thought that min(...) should return the same as
>>> sorted(...)[0] (which it does)

>> It does, but only because Python's sort is stable, so that minimal
>> elements retain their original relative order.  That implies that the
>> minimal element with smallest original index will end up at index 0
>> after sorting.

>>> and that max(...) should return the same as sorted(...)[-1] (which
it doesn't).

>> Right -- although I don't know why you'd expect that.

> Strings have index(), find(), etc which work left-to-right and
> rindex(), rfind(), etc which work right-to-left.
>
> Lists have index() but not rindex().
>
> I just thought that if min() and max() work left-to-right then for
> completeness there should also be rmin() and rmax(); alternatively,
> min() should return sorted()[0] and max() should return sorted()[-1]
> for symmetry (my personal preference).

If you were to make either of those a feature request, I don't expect
they'd gain traction -- I expect "who cares?" would be the common
challenge, and "I do" wouldn't silence it ;-)  Compelling use cases
sometimes work to get a new feature, but "completeness" or "symmetry"
almost never do on their own (they function more as sanity checks on
proposed solutions to use cases).