[jitl]

I think Ruby is much better at shell script like tasks and interactive / exploratory programming for system tasks compared to Python or Node. Use it as “better bash” or “better Perl” and it’s worth it. I primarily work in a Typescript codebase, but regularly reach for it as a tool to wrangle log data, semi-structured text, or do regex rewrites of a bunch of files.

Ruby is also very fun, probably the most fun language I’ve used regularly. That makes it its own reward.

[callc]

This is very intriguing, could you please elaborate? I have been looking for a better bash for scripting stuff without all the bash and sh-isms and gotchas.

[ignurant]

Some of the most enlightening books I’ve read when I was first learning Ruby were Text Processing in Ruby, and Building Awesome Command Line Apps in Ruby 2. They each reveal certain features and perspectives that work towards this end, such as text parsing moves, Ruby flags to help you build shell 1-liners you can pipe against, and features with stdio beyond just printing to stdout.

Then add in something like Pry or Irb, where you are able to build castles in your sandbox.

Most of my data exploration happens in Pry.

A final book I’ll toss out is Data Science at the Command Line, in particular the first 40 or so pages. They highlight the amount of tooling that exists that’s just python shell scripts posing as bins. (Ruby of course has every bit of the same potential.) I had always been aware of this, but I found the way it was presented to be very inspirational, and largely transformed how I work with data.

A good practical example I use regularly is: I have a project set up that keeps connection strings for ten or so SQL Server DBs that I regularly interact with. I have constants defined to expedite connections. The [Sequel library](https://sequel.jeremyevans.net/) is absolutely delightful to use. I have a `bin/console` file that sets up a pry session hooking up the default environment and tools I like to work with. Now it’s very easy to find tables with certain names, schemas, containing certain data, certain sprocs, mass update definitions across our entire system.

``` # Something failed, and not everything loaded as you expected # explore explore explore…

db::CompetitorPricing.tables

db::CompetitorPricing.tables.grep(/^pricing_/)

latest = DB::CompetitorPricing.tables.grep(/^pricing_/).map {|table| [table, table.max(:create_ts)}

latest = latest.sort_by(&:last)

# serialize to csv, or json, or perhaps copy the data into excel:

Clipboard.copy latest.map{ _1.join("\t")}.join("\n") ```

Just like with work in the shell, you have a really easy time iteratively exploring the problem and building up your answer. The ability to serialize your data you’ve found, and keep your favorite tools in your pocket feels extremely productive. And of course, all of this can be written in ruby 1-liner shell scripts, or more complex shell scripts to pipe in and out of other tools if desired.