JSONPath VS jq

Another great alternative is JSONPath[1] which unfortunately not as widely supported and known despite being brilliant!

It's inspired by XPath so it's very familiar instead of a complete new DSL. The killer feature imo is the recursive key lookup so you can write `people..address` and it'll find all "address" keys that descend from "people" anywhere in the JSON. It's by far my favorite parsing language for JSON and I wrote an introduction blog on how to use it in JSON dataset parsing [2] :)

1 - https://github.com/JSONPath-Plus/JSONPath

2 - https://scrapfly.io/blog/parse-json-jsonpath-python/

Thanks, if anyone else is interested there is an explanation of this feature here: https://subtxt.in/library-data/2016/03/28/json_stream_jq And: https://github.com/jqlang/jq/wiki/FAQ#streaming-json-parser

The last time I tried, I think the reason I gave up on JQ for large inputs was that the throughput would max out at 7mb/s whereas the same thing with spark SQL on the same hardware (MacBook) would max out at 250mb/s. So I started looking into using other solutions for big data while I use jq in parallel for small data in multiple files.

I will test it out again cause this was 4-5 years ago when I last tested it, but I believe jaq is still preferred for large inputs. Still I prefer for big data to use Spark/Polars/clickhouse etc.

Looks like you are correct https://github.com/jqlang/jq/blob/ed8f7154f4e3e0a8b01e6778de...

I think like you. But also, one does not necessarily know beforehand that they will want to make money.

Like a project could be born out of pure generosity, but after the happy initial phase the project might get too heavy on the maintenance requirements, causing the author to approach burnout, and possibly deciding that they want to make money to continue pulling the cart forward.

However, here's something I do think: if you create something as Open Source, it should be out of a mentality of goodwill and for the greater good, regardless of how it ends up being used. OSS licenses do mean this with their terms. If you later get tired or burned out, you should just retire and allow the community to keep taking care of it. Just like it happened with the Jq tool [1].

[1]: https://github.com/jqlang/jq/releases/tag/jq-1.7

In this blog we'll see how to upload the JSON directly using PostgreSQL COPY command and using an utility called jq!

And we can then make it easier to find the commit by filtering the response with jq.

Official Documentation: jqlang.github.io/jq

To handle JSON files and JSON outputs in a script or format and highlight it, jq can be very handy. Many command line tools provide a json output, so you don't have to write a custom parser for a table a list in a terminal. Instead of that, you can use jq to get a specific value from the output or even modify the output. For more information, you can visit https://jqlang.github.io/jq/

In some projects I've wanted to use HTTPie to test APIs and jq to work with some JSON data. Nix has been really helpful in managing those dependencies that I can't easily get from npm.