A table with these columns might be helpful for performance comparisons: [
structure,
operation,
big_o,
keyset, # signed ints, randstrs
timeit_output,
system_load,
architecture, # x86_84, aarch64
os,
]
Does anyone have a recommendation for a tool that stores such benchmark
data in JSON and merges the e.g. per-arch output?
Are there URIs for Big-O notation that could be added as e.g. structured
attributes in docstrings or annotations?
I just added a ._repr_html_() method to the tabulate package so that, in
addition to the many excellent ASCII formats tabulate prints,
tabulate.tabulate(data, tablefmt='html') displays an html-escaped table in
Jupyter notebooks? It's not yet released, so you'd need to
`pip install -e git+
https://github.com/astanin/python-tabulate@master#egg=tabulate`
On Tue, Dec 24, 2019, 3:53 AM Larry Hastings wrote:
>
> On 12/23/19 8:09 PM, Kyle Stanley wrote:
>
>
> Chris Angelico wrote:
> > I think this is an artifact of Python not having an empty set literal.
> > [snip]
> > When both use the constructor call or both use a literal, the
> > difference is far smaller. I'd call this one a wash.
>
> Ah, good catch. I hadn't considered that it would make a substantial
> difference, but that makes sense. Here's an additional comparison between
> "{}" and "dict()" to confirm it:
>
> >>> timeit.timeit("{}", number=100_000_000)
> 2.1038335599987477
> >>> timeit.timeit("dict()", number=100_000_000)
> 10.22558353268
>
>
> We could also go the other way with it, set / dict-map-to-dontcare with
> one element, because that way we *can* have a set literal:
>
> >>> timeit.timeit("set()", number=100_000_000)
> 8.579900023061782
> >>> timeit.timeit("dict()", number=100_000_000)
> 10.473437276901677
> >>> timeit.timeit("{0}", number=100_000_000)
> 5.969995185965672
> >>> timeit.timeit("{0:0}", number=100_000_000)
> 6.24465325800702
>
> (ran all four of those just so you see a relative sense on my laptop,
> which I guess is only slghtly slower than Kyle's)
>
>
> Happy holidays,
>
>
> */arry*
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