dragonbox
FrameworkBenchmarks
dragonbox | FrameworkBenchmarks | |
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9 | 366 | |
498 | 7,384 | |
- | 0.4% | |
9.0 | 9.8 | |
5 days ago | 6 days ago | |
C++ | Java | |
Apache License 2.0 | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
dragonbox
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23 years into my career, I still love PHP and JavaScript
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).
- Dragonbox: Fast Float-to-String Conversion
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C++ I wrote a simple and fast formatting library for strings
A recent update to fmt was posted to r/cpp 3 days ago (https://www.reddit.com/r/cpp/comments/vrxkt0/fmt_90_released_with_improvements_to_floating/), and since that's still fresh on people's minds, they'll wonder how yours compares; and they'll probably wonder how it compares in terms of precision, round trip-ability, and performance of DragonBox https://github.com/jk-jeon/dragonbox. By "they", I probably mean "me" :D.
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I created something much faster than a std::string
Existing fast and correct float-to-string implementations are out there. Just use them: https://github.com/jk-jeon/dragonbox. Or maybe use your stdlib if it has good support
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How to read ascii files faster?
Parse floats faster with dragonbox
- Dragonbox 1.1.0 is released (a fast float-to-string conversion algorithm)
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C++20 std::format is already std::regex 2.0 situation.
Even if what you say is true, it makes little sense to not reuse it. There are other concerns here and one of them is code size. But to address the performance issue, fmtlib is doing under 50ns for most fp numbers via dragonbox(https://github.com/jk-jeon/dragonbox has the chart). So still cpu bound, but all FP output is CPU bound. At this point, what prices are we trading for faster?
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First release of dragonbox, a fast float-to-string conversion algorithm, is available
There are some benchmarks in https://github.com/jk-jeon/dragonbox#performance. TL;DR it's faster than other state of the art algorithms like Ryu, Schubfach and variations of Grisu. We saw a nice speed up when switching from Grisu3 to Dragonbox in {fmt}: https://github.com/fmtlib/fmt/pull/1882 and it has been improved even more since then.
FrameworkBenchmarks
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Why choose async/await over threads?
Neat. Thanks for sharing!
Interestingly, may-minihttp is faring very well in the TechEmpower benchmark [1], for whatever those benchmarks are worth. The code is also surprisingly straightforward [2].
[1] https://www.techempower.com/benchmarks/
[2] https://github.com/TechEmpower/FrameworkBenchmarks/blob/mast...
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Ntex: Powerful, pragmatic, fast framework for composable networking services
ntex was formed after a schism in actix-web and Rust safety/unsafety, with ntex allowing more unsafe code for better performance.
ntex is at the top of the TechEmpower benchmarks, although those benchmarks are not apples-to-apples since each uses its own tricks: https://www.techempower.com/benchmarks/#hw=ph&test=fortune&s...
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A decent VS Code and Ruby on Rails setup
Ruby is slow. Very slow. How much you may ask? https://www.techempower.com/benchmarks/#hw=ph&test=fortune&s... fastest Ruby entry is at 272th place. Sure, top entries tend to have questionable benchmark-golfing implementations, but it gives you a good primer on the overhead imposed by Ruby.
It is also not early 00s anymore, when you pick an interpreted language, you are not getting "better productivity and tooling". In fact, most interpreted languages lag behind other major languages significantly in the form of JS/TS, Python and Ruby suffering from different woes when it comes to package management and publishing. I would say only TS/JS manages to stand apart with being tolerable, and Python sometimes too by a virtue of its popularity and the amount of information out there whenever you need to troubleshoot.
If you liked Go but felt it being a too verbose to your liking, give .NET a try. I am advocating for it here on HN mostly for fun but it is, in fact, highly underappreciated, considered unsexy and boring while it's anything but after a complete change of trajectory in the last 3-5 years. It is actually the* stack people secretly want but simply don't know about because it is bundled together with Java in the public perception.
*productive CLI tooling, high performance, works well in a really wide range of workloads from low to high level, by far the best ORM across all languages and back-end framework that is easier to work with than Node.JS while consuming 0.1x resources
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The Erlang Ecosystem [video]
Although that seems to have improved in recent years.
https://www.techempower.com/benchmarks/#hw=ph&test=json§...
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Ruby 3.3
RoR and whatever C++ based web backend there is count as a valid comparison in my book. But comparing the languages itself is maybe a bit off.
On a side note, you can actually compare their performance here if you’re really curious. But take it with a grain of salt since these are synthetic benchmarks.
https://www.techempower.com/benchmarks
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API: Go, .NET, Rust
Most benchmarks you'll find essentially have someone's thumb on the scale (intentionally or unintentionally). Most people won't know the different languages well enough to create comparable implementations and if you let different people create the implementations, cheating happens. The TechEmpower benchmarks aren't bad, but many implementations put their thumb on the scale (https://www.techempower.com/benchmarks). For example, a lot of the Go implementations avoid the GC by pre-allocating/reusing structs or allocate arrays knowing how big they need to be in advance (despite that being against the rules). At some point, it becomes "how many features have you turned off." Some Go http routers (like fasthttp and those built off it like Atreugo and Fiber) aren't actually correct and a lot of people in the Go community discourage their use, but they certainly top the benchmarks. Gin and Echo are usually the ones that are well-respected in the Go community.
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Rage: Fast web framework compatible with Rails
There is certainly a lot of speculation in Techempower benchmarks and top entries can utilize questionable techniques like simply writing a byte array literal to output stream instead of constructing a response, or (in the past) DB query coalescing to work around inherent limitations of the DB in case of Fortunes or DB quries.
And yet, the fastest Ruby entry is at 274th place while Rails is at 427th.
https://www.techempower.com/benchmarks/#hw=ph&test=fortune&s...
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Node.js – v20.8.1
oh what machine? with how many workers? doing what?
search for "node" on this page: https://www.techempower.com/benchmarks/#section=data-r21
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Strong typing, a hill I'm willing to die on
JustJS would like a word https://www.techempower.com/benchmarks/#section=data-r20&tes...
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Rust vs Go: A Hands-On Comparison
In terms of RPS, this web service is more-or-less the fortunes benchmark in the techempower benchmarks, once the data hits the cache: https://www.techempower.com/benchmarks/#section=data-r21
Or, at least, they would be after applying optimizations to them.
In short, both of these would serve more rps than you will likely ever need on even the lowest end virtual machines. The underlying API provider will probably cut you off from querying them before you run out of RPS.
What are some alternatives?
fast_float - Fast and exact implementation of the C++ from_chars functions for number types: 4x to 10x faster than strtod, part of GCC 12 and WebKit/Safari
zio-http - A next-generation Scala framework for building scalable, correct, and efficient HTTP clients and servers
C++ Format - A modern formatting library
drogon - Drogon: A C++14/17 based HTTP web application framework running on Linux/macOS/Unix/Windows [Moved to: https://github.com/drogonframework/drogon]
ryu - Converts floating point numbers to decimal strings
django-ninja - 💨 Fast, Async-ready, Openapi, type hints based framework for building APIs
ryu - Ryu component-based software defined networking framework
LiteNetLib - Lite reliable UDP library for Mono and .NET
dtoa-benchmark - C++ double-to-string conversion benchmark
C++ REST SDK - The C++ REST SDK is a Microsoft project for cloud-based client-server communication in native code using a modern asynchronous C++ API design. This project aims to help C++ developers connect to and interact with services.
itoa - Fast integer to ascii / integer to string conversion
SQLBoiler - Generate a Go ORM tailored to your database schema.