HTTP Parser VS RE2

It looks not too different from the majority of HTTP parsers out there written in C. Here is an example of NodeJS [0].

[0] https://github.com/nodejs/http-parser/blob/main/http_parser....

NodeJS's HTTP parser used to be a handwritten C lib: http-parser

Whoa, I didn't know that! But yeah, it seems like https://github.com/nodejs/http-parser is based on nginx. It now uses https://github.com/nodejs/llhttp but has some of the same legacy.

On the other hand, deno's HTTP stuff is built on top of Hyper, a Rust library https://github.com/hyperium/hyper

Boost.Beast has its own HTTP parser[0], during the development of which Vinnie Falco (the principle author of Beast) found many bugs/inconsistencies in Node.js's own parser[1]

[0] https://www.boost.org/doc/libs/develop/libs/beast/doc/html/b...

[1] https://github.com/nodejs/http-parser/issues?q=is%3Aissue+au...

For cases where it is necessary to pass local information to/from a callback, the http_parser object's data field can be used.

Legacy HTTP/1.1 suffers a few issues, see the current RFC errata:

https://www.rfc-editor.org/errata_search.php?rfc=7230&rec_st...

There are issues particularly around how whitespace and obsolete line folding should be handled

https://github.com/nodejs/http-parser/issues?q=is%3Aissue+wh...

https://github.com/httpwg/http-core/issues/53

It's not as trivial as a few string splits.

There's picohttpparser and the one used in node.js: https://github.com/nodejs/http-parser

Looking at the benchmark where C++ is worst compared to other languages, it's depending on the library used. I would guess if they used Google's re2 Regex library instead of Boost's, the result would be different.

https://github.com/google/re2

https://github.com/greensoftwarelab/Energy-Languages/blob/ma...

That page says it just includes "some of the most common special characters", and following the link to the Examples page in turn includes a link to the full list.

Python uses backtracking, so this probably isn't O(n), especially with the ability to choose the dictionary.

But with there are non-backtracking matchers which would make this O(n). Here's re2 from https://github.com/google/re2 :

  >>> import re2

RE2 is a Google regular expression library

google's regex library: https://github.com/google/re2

I am currently working with Regex, specifically Re2, and was wondering if there is a real difference between the above expressions for repeated sub-regex.

I ported Google RE2, a regular expression library, to SPVM as Resource::Re2, and created SPVM::Regex, a wrapper for it.

I searched for I found that there is a Perl compatible regular expression called Google RE2. It is written in C++, and with Google RE2, I can use Perl-compatible regular expressions as a library.

Yes, but there is an interesting clarification here. RE2 has used the "caching" approach documented in the Ruby bug ticket linked for quite some time (since its birth?): https://github.com/google/re2/blob/954656f47fe8fb505d4818da1...

It is mentioned only briefly in Cox's article on regex matching in the wild. Look for the word "bitstate": https://swtch.com/~rsc/regexp/regexp3.html

I didn't know Perl had implemented this trick too.

The paper[1] cited in the Ruby bug ticket was published very recently. When I first read the Ruby bug ticket, I immediately wondered how they sidestepped the memory use problem. The paper's abstract seems to suggest there is some technique for doing so, as it rebuffs the idea of doing "full" memoization. Alas, I do not have access the paper. (Which is fucking ridiculous.)

[1]: https://ieeexplore.ieee.org/abstract/document/9519427