On Mon, Jan 17, 2022 at 3:50 AM Steven D'Aprano <st...@pearwood.info> wrote:
> If you saw this code in a review:
>
> t = tuple([1, 2, 3, 4, 5])
>
> would you say "that is okay, because the name lookup is smaller than the
> cost of building the list"?
>
> I wouldn't. I would change the code to `(1, 2, 3, 4, 5)`.
>
Of course, everyone would -- because tuple displays already exist. I'd
suggest refactoring that code even if the compiler could completely
optimize it away.
Would you let:
l = list([1, 2, 3, 4, 5])
pass code review either? even if there were no performance penalty? I
wouldn't, because it's redundant, not because it's slower.
Also that pattern is actually very common for types that aren't built-in
(or even in the stdlib).
It's always kind of bugged me that I need to write:
arr = np.array([1, 2, 3, 4])
And I'm creating a list just so I can pass it to the array constructor. But
in practice, it's not a performance problem at all.
And in code in the wild, I'll bet numpy arrays are used orders of
magnitude more than frozen sets ;-)
Sometimes, now, the compiler *pessimizes* the construction of the frozen
> set. See b.p.o #46393.
>
yup. Using a 'constant' frozenset is slower than 'constant' set, when doing
not much else:
In [29]: def setfun():
...: s = {1, 3, 5, 2}
...: i = 3
...: if i in s:
...: return 'yes'
...:
In [30]: def fsetfun():
...: s = frozenset((1, 3, 5, 2))
...: i = 3
...: if i in s:
...: return 'yes'
...:
In [31]: %timeit setfun()
194 ns ± 10.6 ns per loop (mean ± std. dev. of 7 runs, 10000000 loops each)
In [32]: %timeit fsetfun()
286 ns ± 2.72 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)
But: would you notice if that function did any real work?
And I think we could call this one of the many micro-optimizations we have
in Python:
Don't use a frozenset as a constant when a regular set will do.
So it comes down to how often frozen sets as constants are required.
-CHB
--
Christopher Barker, PhD (Chris)
Python Language Consulting
- Teaching
- Scientific Software Development
- Desktop GUI and Web Development
- wxPython, numpy, scipy, Cython
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