Even that list is superfluous; the map function returns a generator, so it's better you just need one number at a time but possibly not the whole list (e.g. loop through results until you find a certain value).
Nope, at least not on my computer. The map solution was ~50% slower than the list comprehensions when run a list with 1 million ints, and almost twice as slow when run on a list with 100k ints.
In fact even using a for loop in the obvious way was slightly faster than map with 1 million elements (about halfway between the map and list comprehension performance wise).
Map without the last list call is however very slightly faster than the equivalent generator comprehension.
That is interesting. It's possible that they have done some optimisations on loops since the last time I measured it, but that was back in Python 2.6 (I think), and map was much faster than a loop (no comprehensions back then), and it was particularly obvious on very high number of input elements.
Also, from your description I suspect that the list() call over a generator might introduce extra overhead, rather than map itself...
Your last comment seems reasonable. I guess the new rule of thumb should be maps are still fast, but only if you want a generator. If you need a list use a list comprehension.
