Saxon-HE
related_post_gen
| Saxon-HE | related_post_gen | |
|---|---|---|
| 2 | 15 | |
| 72 | 279 | |
| - | - | |
| 3.6 | 9.9 | |
| 12 days ago | about 2 months ago | |
| C++ | ||
| - | MIT 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.
Saxon-HE
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Jaq – A jq clone focused on correctness, speed, and simplicity
Now that is just aggressively dumb: https://github.com/Saxonica/Saxon-HE/tree/SaxonHE12-3/12#sou... and https://github.com/Saxonica/Saxon-HE/tree/SaxonHE12-3/12/sou... (not even the decency to use .gitattributes so it knows the files are binary)
FWIW https://saxonica.plan.io/projects/saxonmirrorhe/repository seems to be the for-real source repo
related_post_gen
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Speed up your code: don't pass structs bigger than 16 bytes on AMD64
Looks like the HO means hand optimized, with special datastructures for this benchmark.
see: https://github.com/jinyus/related_post_gen/#user-content-fn-...
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Benchmarking 20 programming languages on N-queens and matrix multiplication
There is one for data processing here: https://github.com/jinyus/related_post_gen
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The Neat Programming Language
Is it ready for benchmarking? D currently sits at the top of https://github.com/jinyus/related_post_gen and it would be interesting to see how neat stacks up.
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Murder is a pixel art ECS game engine in C#
[2] https://github.com/jinyus/related_post_gen#multicore-results
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Jaq – A jq clone focused on correctness, speed, and simplicity
I think my benchmark[1] would be a great test for this. The jq[2] version takes 50s on my machine.
[1] : https://github.com/jinyus/related_post_gen
[2]: https://github.com/jinyus/related_post_gen/blob/main/jq/rela...
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Gleam vs Erlang vs Go vs Zig vs Rust for data processing
I added gleam to my data processing benchmark and the performance is less than stellar...so I hope someone here can make suggestions to improve it.
- jinyus/related_post_gen: Data Processing benchmark featuring Rust, Go, Swift, Zig, Julia etc.
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Ask HN: What's the big deal with Go (Golang)?
Easy concurrency.
ps: I wrote a data processing benchmark[1] and go is currently leading the charts. I ported it to c++ but it's not performing as expected. Take a look if you have the time.
[1]: https://github.com/jinyus/related_post_gen
- Julia leads Rust,Zig,Go and Java in data processing benchmark
- Julia Ranks First in Data Processing Microbenchmark
What are some alternatives?
gron - Make JSON greppable!
uiua - A stack-based array programming language
jql - A JSON Query Language CLI tool
pspy - Monitor linux processes without root permissions
jq - Command-line JSON processor
ivy - ivy, an APL-like calculator
git-xargs-tasks - Keep git-xargs changes together
BQN - An APL-like programming language. Self-hosted!
jless - jless is a command-line JSON viewer designed for reading, exploring, and searching through JSON data.
cognate - A human readable quasi-concatenative programming language
fq - jq for binary formats - tool, language and decoders for working with binary and text formats