Thanks to this tool I never have to remember the arguments to "tar" anymore ✨

🦀 **ouch**: Painless compression and decompression in the terminal - written in Rust.

⭐ GitHub: github.com/ouch-org/ouch

#rustlang #compression #commandline #opensource #tar

Feedback wanted: I made a drop-in JSON replacement that produces smaller payloads. It's for busy programmers who want a quick win. evanhahn.com/jsos-proof-of-con…

It might be a bad idea! Please let me know what you think.

#JSON #compression #programming

Proof of concept: drop-in JSON replacement that produces smaller payloads

What if your JSON payloads got smaller by changing one line of code? I made a proof of concept.

^evanhahn.com

Repeated the #compression #benchmark with the same file on a beefier machine (AMD Ryzen 9 5950X), results are quite identical, except faster overall.

This plot is also interesting:

- #gzip and #lz4 have fixed (!) and very low RAM usage across levels and compression/decompression
- #xz RAM usage scales with the level from a couple of MBs (0) to nearly a GB (9)
- #zstd RAM usage scales weirdly with level but not as extreme as #xz

#Python #matplotlib

First results of my #compression algorithm benchmark run on a 72MB CSV file. It seems #zstd really has something for everybody, though it can't reach #xz's insane (but slow) compression ratios at maximum settings.

This chart includes multithreaded runs for #zstd.

Very interesting! 🧐

gitlab.com/nobodyinperson/comp…

#Python #matplotlib #Jupyter #JupyterLab

My conclusion after all this is that I'll probably use #zstd level 1 (not the default level 3!) for #compression of my #CSV measurement data from now on:

- ultra fast compression and decompression, on par with #lz4
- nearly as good a compression ratio as #gzip level 9
- negligible RAM usage

When I need ultra small files though, e.g. for transfer over a slow connection, I'll keep using #xz level 9.