Memory use and speed of JSON parsers - Memory use is often overlooked when people compare JSON libraries
Memory use and speed of JSON parsers 22 November 2015 (updated 15 December 2015) Note TL;DR: In decode oriented use-case with big payloads JSON decoders often use disproportionate amounts of memory. I gave up on JSON and switched to Msgpack. You should draw your own conclusions by running the test code yourself. ⸻ Based on various feedback [*] I've did the benchmarks again, using ru_maxrss instead
Pjson by igorgue
pjson Like python -mjson.tool but with moar colors (and less conf) Usage ⚡ echo '{"json":"obj"}' | pjson { "json": "obj" } Looks Like This Image for the haters: Small retina display images are fucking huge. Example With Curl ⚡ curl https://github.com/igorgue.json | pjson Install Install pygments: ⚡ pip install pjson MFW I did This Project
Not Overlooking Much » Blog Archive » Choosing a Python JSON Translator
This is a draft for comments. I already know it needs further work. Among other things, I plan to move this off WordPress so that the data are more generally usable. I noticed publication of python-cjson recently. I wondered whether the claimed 10 to 200 times speed increase was real. It was reasonable to expect that a “C” back end would make a difference. So, a few lines of code later, here is
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GitHub - mre/hyperjson: 🐍 A hyper-fast Python module for reading/writing JSON data using Rust's serde-json.
