jellex VS flatterer

You could do something like this in pure python without the json loading boilerplate with jello[0]. An interactive TUI for jello called jellex[1} is also available. (I am the author)

[0] https://github.com/kellyjonbrazil/jello

[1] https://github.com/kellyjonbrazil/jellex

Also, Jellex is a TUI front-end to Jello that helps with interactively querying the JSON.

I wrote something similar to this to query JSON and JSON lines with python instead of awk for text. It’s called Jellex (Jello Explorer) which is a TUI front-end to Jello. Jello is a python analog to JQ.

https://github.com/kellyjonbrazil/jellex

There's a new TUI for jello now called jellex that can help you create your jello python filters faster and easier.

I made this TUI app using prompt-toolkit

This tool was built for this purpose https://github.com/kindly/flatterer

I have been working on this Rust based JSON flattener (https://github.com/kindly/flatterer) to XLSX/CSV/SQLITE/PARQUET/POSTGRES for about 2 years. I finally made a WASM based one for CSV/XLSX which is really easy to play with. You can use it via a url (if the data has CORS headers), for example https://lite.flatterer.dev?url=https%3A%2F%2Fdummyjson.com%2....

The main difference with other converters/flatteners is that for one-to-many relationships (lists of objects in JSON) it produces a multi table output with keys to help join the tables together. Essentially produces a relational schema, along with some type information, of the JSON provided. For simple non-nested JSON it works too, but is a bit overkill.

Its all opensource and free, and I think that it will become more and more useful as JSON/Graphql APIs proliferate.

flatterer is the easiest option and will do this for you. It will also load the data into a sqlite or postgres database for you.

I have also written something similar but higher level flatterer which is python but is a binding to libflatterer. Its main difference is when there is a list of objects it treats it a one to many and creates a separate CSV file.

flatterer (github) is designed for this.

This looks great and using duckdb as a backend us a great choice. For JSON I suggest using flatterer https://flatterer.opendata.coop/ . Which will convert most JSON into CSV/Parquet with very little technical knowledge.

My project flatterer (used for flattening JSON into tables) also is mainly a python cli/libarary but is written in Rust for speed/memory efficiency and better concurrency.

I have been working on a similar tool for the last while called flatterer (github). It has a similar aim and works with most kinds of JSON well (but not very well with top level objects like yours).

You could try Option B with flatterer https://flatterer.opendata.coop/ which purpose is to convert nested JSON into other formats without a schema upfront including parquet.

flatterer docs (github)