visidata VS miller

[4] "Is it possible to "flatten" structured data (like JSON?)": https://github.com/saulpw/visidata/discussions/1605

Visidata - https://visidata.org

You can try Visidata

VisiData is an awesome terminal spreadsheet tool. edbrowse for internet browsing.

Have you ever tried out visidata? It's not vim, but it's a terminal app with vim-like keybindings for visualizing tabular data (and it can convert from other types like json). Not quite a neovim buffer, but you could always open visidata in a new terminal buffer.

If you are a command-line user, try visidata[0]

[0] https://github.com/saulpw/visidata

The datasets will be available as SQLite, JSONL, and CSV. This will be great for sharpening your SQL/Python/VisiData skills.

Help Sarah find the family holiday tapestry before her father notices it's missing! Sharpen your SQL/Python/VisiData skills with Hanukkah of Data.

jq and miller[1] are essential parts of my toolbelt, right up there with awk and vim.

[1]: https://github.com/johnkerl/miller

> This works really well if your problem can be solved in one or two liners.

My personal comfort threshold is around the 100-line mark. It's even possible to write maintainable shell scripts up to 500 lines, but it mostly depends on the problem you're trying to solve, and the discipline of the programmer to follow best practices (use sane defaults, ShellCheck, etc.).

> It go bad very quickly when, say, you have two CSV files and want to join them the sql-way.

In that case we're talking about structured data, and, yeah, Perl or Python would be easier to work with. That said, depending on the complexity of the CSV, you can still go a long way with plain Bash with IFS/read(1) or tr(1) to split CSV columns. This wouldn't be very robust, but there are tools that handle CSV specifically[1], which can be composed in a shell script just fine.

So it's always a balancing act of being productive quickly with a shell script, or reaching out for a programming language once the tools aren't a good fit, or maintenance becomes an issue.

[1]: https://miller.readthedocs.io/

where mlr is from https://github.com/johnkerl/miller

if this class of problems (i.e., csv/tsv data) is your main target you may find miller (https://github.com/johnkerl/miller) much more useful in the long run

That said, you may be interested in Miller (https://github.com/johnkerl/miller) which provides similar capabilities for CSV, JSON, and XML files. It doesn't use a SQL grammar, but that's just the proverbial lipstick on the thing. I'm not the author, but I have used it and I see some parallels in use cases at the very least.

worth giving Miller a shot

CSV utilities (still haven't pick a favorite one...): https://github.com/harelba/q https://github.com/BurntSushi/xsv https://github.com/wireservice/csvkit https://github.com/johnkerl/miller