ryu VS jsoniter-scala

Nah. This is about ryu printf.

> Google put in significant engineering effort into "Ryu", a parsing library for double-precision floating point numbers: https://github.com/ulfjack/ryu

It's not a parsing library, but a printing one, i.e., double -> string. https://github.com/fastfloat/fast_float is a parsing library, i.e., string -> double, not by Google though, but was indeed motivated by parsing JSON fast https://lemire.me/blog/2020/03/10/fast-float-parsing-in-prac...

Me and Ryu agree that the answer should be 0.30000000000000004

Apparently exact minimal float-to-string conversion is more recent than I thought, and many languages used to print more (Python?) or less (PHP) decimal digits than necessary to uniquely identify the bit pattern. Python correctly prints 46000.80 + 553.04 as 46553.840000000004, but I don't know if it ever prints more digits than needed. One recent algorithm for printing floats exactly is https://github.com/ulfjack/ryu, though I'm unaware what's the state-of-the-art (https://github.com/jk-jeon/dragonbox claims to be a benchmark and the best algorithm).

On the huge speedup side, you have the Ryū algorithm for decimal conversion (Video, Source), which is now finding its way in most standard libraries. But it isn't a hack, and a very dense, complex and precise algo, nothing like the fast-and-loose inverse square root.

Used a wizard's magic to print "3.14" faster

Here's a paper that details an optimized algorithm (reference implementation). It also contains a description of a correct, but slow algorithm as well as references to classic papers on the subject. Earlier the classic implementation was the dtoa one included in netlib by David Gay.

At the very core of all these theoretical stuffs, there is the theory of continued fractions. This is an immensely useful monster which I even dare call as the ultimate tool for floating-point formatting/parsing that everyone who wants to contribute in this field should learn. Before I learned continued fractions, my main tool for proving stuffs was the minmax Euclid algorithm (which is one of the greatest contributions of the wonderful Ryu paper), but it turns out that it is actually just a quite straightforward application of the theory of continued fractions. The main role minmax Euclid algorithm played was to estimate the maximum size of possible errors, but with continued fractions it is even possible to find the list of all examples that generate errors above a given threshold. This is something I desperately wanted but really couldn't do back in 2020.

Ryū algorithm, the converse (doubles to strings), is also much faster than using Java's number formatting classes.

https://github.com/ulfjack/ryu/blob/master/src/main/java/inf...

What an amazing step by step explanation!

More than 2 years ago I found that byte array view var handles are quite suitable to cook efficient SWAR routines with Java/Scala.

See a lot of other examples of SWAR usage, like parsing Base16/64 string, java.time.* and number values directly from byte arrays:

https://github.com/plokhotnyuk/jsoniter-scala/blob/master/js...

Afaik dsl-json came up with a lot of improvements and inspired a several other libraries like JsonIter and jsonIter-scala. Jsoniter-scala by u/plokhotnyuk is probably the most optimized JSON library on the JVM at this point, and seems to power most of the Scala ecosystem. Some implementations/optimizations eventually made their way back into Jackson and other libraries.

I was on your place more then 5 years ago, when cut the 1st release of jsoniter-scala.

I've just increased compiler performance in ~1.5x times by adding these JVM options for the code cache

We have our own open-source code-generator that produces Scala code from Smithy. The code module is entirely dependency-free, and the generated code is not biased towards any library, be that http or json. We do however have out-of-the-box integration with jsoniter and http4s.

You can use jsoniter-scala. It is easy to use like upickle.

BTW, jsoniter-scala uses it for faster parsing and serialization using SWAR techniques, like here.

Probably you should have both codecs (for Foo and for its T) are implicitly available in the scope, like it is done in the following test for jsoniter-scala:

BEWARE: uJson is vulnerable under DoS attacks

Please see sources (and GitHub history of development) of jsoniter-scala as an example in the domain of JSON parsing and serialization.