Make `email.message.Message.__contains__` faster

[sobolevn]

Right now the implementation of Message.__contains__ looks like this:

cpython/Lib/email/message.py

Lines 450 to 451 in 2f2fa03

	def __contains__(self, name):
	return name.lower() in [k.lower() for k, v in self._headers]

There are several problems here:

1. We build intermediate structure (list in this case)
2. We use list for in operation, which is slow

The fastest way to do check if actually have this item is simply by:

    def __contains__(self, name):
        name_lower = name.lower()
        for k, v in self._headers:
            if name_lower == k.lower():
                return True
        return False

We do not create any intermediate lists / sets. And we even don't iterate longer than needed.
This change makes in check twice as fast.

Microbenchmark

Before

» pyperf timeit --setup 'import email; m = email.message_from_file(open("Lib/test/test_email/data/msg_01.txt"))' '"from" in m'
.....................
Mean +- std dev: 1.40 us +- 0.14 us

pyperf timeit --setup 'import email; m = email.message_from_file(open("Lib/test/test_email/data/msg_01.txt"))' '"missing" in m'
.....................
Mean +- std dev: 1.42 us +- 0.06 us

After

» pyperf timeit --setup 'import email; m = email.message_from_file(open("Lib/test/test_email/data/msg_01.txt"))' '"missing" in m'
.....................
Mean +- std dev: 904 ns +- 55 ns

» pyperf timeit --setup 'import email; m = email.message_from_file(open("Lib/test/test_email/data/msg_01.txt"))' '"from" in m'
.....................
Mean +- std dev: 715 ns +- 24 ns

The second case is now twice as fast.
It probably also consumes less memory now, but I don't think it is very significant.

Importance

Since EmailMessage (a subclass of Message) is quite widely used by users and 3rd party libs, I think it is important to be included.

And since the patch is quite simple and pure-python, I think the risks are very low.

Linked PRs

• gh-100792: Make email.message.Message.__contains__ twice as fast #100793

[pochmann]

We use list for in operation, which is slow

I'd say it's one of the fastest linear searches you can do.

What times do you get if you simply change the listcomp to a genexp, i.e., just change [/] to (/)?

return name.lower() in map(str.lower, self) might also be good.

Btw in "After," you switched the order of the two benchmarks, better use the same as in "Before".

[sobolevn]

What times do you get if you simply change the listcomp to a genexp, i.e., just change [/] to (/)?

» pyperf timeit --setup 'import email; m = email.message_from_file(open("Lib/test/test_email/data/msg_01.txt"))' '"from" in m'
.....................
Mean +- std dev: 1.71 us +- 0.04 us

and

» pyperf timeit --setup 'import email; m = email.message_from_file(open("Lib/test/test_email/data/msg_01.txt"))' '"missing" in m'
.....................
Mean +- std dev: 1.79 us +- 0.02 us

return name.lower() in map(str.lower, self) might also be good.

Nope:

» pyperf timeit --setup 'import email; m = email.message_from_file(open("Lib/test/test_email/data/msg_01.txt"))' '"from" in m'
.....................
Mean +- std dev: 1.74 us +- 0.02 us

» pyperf timeit --setup 'import email; m = email.message_from_file(open("Lib/test/test_email/data/msg_01.txt"))' '"missing" in m'
.....................
Mean +- std dev: 1.69 us +- 0.02 us

[pochmann]

Hmm, I hoped the "from" search would be good. Odd that it's slower than the "missing" search in the map solution.