>>> for item in data.items(): item[0], item[1]
874 µs ± 21.5 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)
>>> for key, value in data.items(): key, value
524 µs ± 4.26 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)
>>> for item in items_tuple(data): item.key, item.value

5.82 ms ± 117 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)

Thanks for sharing the results, in particular the amount of difference between "for item in data.items(): item[0], item[1]" and "for key in data.items(): key, value" is a bit surprising to me. I'd have assumed they'd be a bit closer in performance. I expected the named tuple to be significantly slower than the other two, but not quite by that much. Good to know.

I'm -1 on the proposal overall. It's not a bad idea, but in practice it would likely be too much of a detriment to performance and backwards compatibility to "dict.items()". I wouldn't be opposed to considering a different method though, such as "dict.named_items()" or something similar that allowed usage of "item.key" and "item.value".