json-benchmark
ixy-languages
Our great sponsors
json-benchmark | ixy-languages | |
---|---|---|
12 | 30 | |
169 | 2,108 | |
4.7% | 0.4% | |
4.8 | 0.0 | |
about 1 month ago | over 1 year ago | |
C++ | TeX | |
Apache License 2.0 | BSD 2-clause "Simplified" License |
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.
json-benchmark
-
Do You Know How Much Your Computer Can Do in a Second?
I don’t really understand what this is trying to prove:
- you don’t seem to specify the size of the input. This is the most important omission
- you are constructing an optimised representation (in this case, strict with fields in the right places) instead of a generic ‘dumb’ representation that is more like a tree of python dicts
- rust is not a ‘moderately fast language’ imo (though this is not a very important point. It’s more about how optimised the parser is, and I suspect that serde_json is written in an optimised way, but I didn’t look very hard).
I found[1], which gives serde_json to a dom 300-400MB/s on a somewhat old laptop cpu. A simpler implementation runs at 100-200, a very optimised implementation gets 400-800. But I don’t think this does that much to confirm what I said in the comment you replied to. The numbers for simd json are a bit lower than I expected (maybe due to the ‘dom’ part). I think my 50MB/a number was probably a bit off but maybe the python implementation converts json to some C object and then converts that C object to python objects. That might half your throughput (my guess is that this is what the ‘strict parse’ case for rustc_serialise is roughly doing).
[1] https://github.com/serde-rs/json-benchmark
-
Serde Json vs Rapidjson (Rust vs C++)
But the code OP posted deserializes JSON without knowing anything about the structure, which is known to be slow in serde-json and doesn't appear to be the focus for the library. The json and json-deserializer crates should perform much better in that scenario.
- Good example of high performance Rust project without unsafe code?
- I'm a veteran C++ programmer, what can Rust offer me?
-
Rust is just as fast as C/C++
Of course that doesnt mean that in practice the available libraries are as optimized. Did you try actix? It tends to be faster than rocket. Also json-rust and simd-json are usually faster than serde-json, when you don't deserialize a known structure. Here are some benchmarks: https://github.com/serde-rs/json-benchmark
-
Lightweight template-based parser build system. Simple prototyping. Comfortable debugging. Effective developing.
The data for the test is taken from here: https://github.com/serde-rs/json-benchmark/tree/master/data
-
Performance of serde js value conversion and reference types
Here are some benchmarks https://github.com/serde-rs/json-benchmark
-
Serde zero-copy benchmarks?
I found two projects: * https://github.com/djkoloski/rust_serialization_benchmark - doesn't use Serde zero copy * https://github.com/serde-rs/json-benchmark - has copy vs borrowed, but the results were the same for both, so something's off there
-
Android Developers Have A Tough Life
Rust has a good enough standard library (I’d say comparable to C++), that you don’t really need packages for a lot of stuff. Most of my projects have 1 or 2 dependencies. Most of the time I am pulling in a JS parser (serde) and a parallelization library (rayon). These are both high performance libraries that make writing very fast (serde can handle 850 MB/s on a 5 year old laptop cpu per their benchmarks). Rayon is one of the best parallelism libraries I’ve worked with.
ixy-languages
-
The Garbage Collection Handbook, 2nd Edition
Not really, here it is winning hands down over Swift's ARC implementation.
https://github.com/ixy-languages/ixy-languages
- rust devs in a nutshell
-
So what you doing for the weeknd
You laugh, but ... https://github.com/ixy-languages/ixy-languages
-
Blog post: My perspective on RAII and memory management in C++ and Rust
GC'd languages are designed to leverage GCs, meaning they usually allocate a lot. Some of the more recent ones (C#, Go) have ways around it or to limit it, but in your average GC'd language you have to really bend yourself out of shape to limit allocations (IIRC the Ixy effort / study / thing never managed to make the Java hotpath allocation-free).
- “Rust is safe” is not some kind of absolute guarantee of code safety
-
I wrote a database engine in Typescript
It's kind of funny when you see things like this project: https://github.com/ixy-languages/ixy-languages
-
What are my prospects in web programming, if I don't like JS?
like not-even-in-the-same-ballpark faster. In this realworld example (userspace network drivers in managed languages) JS manages about 20-30% of native code performance, python iirc is below 1%
-
Don’t call it a comeback: Why Java is still champ
- Support for generic-aware value types (struct vs. class) and low-level features like stackalloc: very valuable for high-performance scenarios and native FFI. See for instance https://github.com/ixy-languages/ixy-languages. In comparison, Java doesn't even have unsigned integers. Yes, Project Valhalla is coming someday.
As well, debatable to some folks, but: properties (get/set); operator overloading; LINQ > Java streams; extension methods; default parameters; collection initializers; tuples; nullable reference types; a dozen smaller features
- Reference Count, Don't Garbage Collect
-
Why did you switch from another language to Rust? Do you regret not learning it earlier?
Very bottom of this file https://github.com/ixy-languages/ixy-languages/blob/master/Java-garbage-collectors.md
What are some alternatives?
rust_serialization_benchmark - Benchmarks for rust serialization frameworks
ctl - The C Template Library
hjson-rust for serde - Hjson for Rust
cats - Lightweight, modular, and extensible library for functional programming.
simd-json - Rust port of simdjson
redgrep - ♥ Janusz Brzozowski
hyperjson - 🐍 A hyper-fast Python module for reading/writing JSON data using Rust's serde-json.
c-examples - Example C code
MessagePack - MessagePack serializer implementation for Java / msgpack.org[Java]
iced_audio - An extension to the Iced GUI library with useful widgets for audio applications
json - Strongly typed JSON library for Rust
zig - General-purpose programming language and toolchain for maintaining robust, optimal, and reusable software.