Quill VS Sequel

https://github.com/zio/zio-quill

This library does exactly what you prescribe. Pretty sure under the hood it's using macros with string templates

But I can connect to Postgress with something like Quill and run sophisticated queries to fetch data. Which then got me thinking, what is the difference between using Spark to connect to the database and using something like Quill or your normal pure JDBC driver?

Just as an example, say you are using quill ( https://getquill.io/ ) to query your database.

I think Quill is the closest to your request: https://github.com/zio/zio-quill

If this still looks like too much hassle, you can always go a bit higher-level and use something like Quill, which is also a powerful approach that uses a different, more ORM-like style.

I'm using it mostly for full-stack web development with ScalaJS (https://www.scala-js.org) in the frontend (https://outwatch.github.io/docs/readme.html) and in the backend with AWS lambdas.

The ecosystem is currently in the process of porting all the libraries to Scala 3. So if you're new to Scala, I'd recommend to start with Scala 2, which is rock-solid and already very powerful.

I never worked with SQLAlchemy. But on the scala database side, popular libraries are Doobie (https://tpolecat.github.io/doobie) and Quill (https://getquill.io). Keep in mind that these are for Scala on the JVM. On the ScalaJS side I'm using the javascript library pg. But I'd like to try if it works well with Prisma soon.

The nice thing about ScalaJS is, that you can use Javascript libraries. And if there are typescript facades, then you can transpile these to Scala and use them in a type safe way (https://scalablytyped.org).

I know that libraries like Scodec and shapeless were rewritten practically from scratch for Scala 3, taking advantage of the next syntax and internals, as well as protoquill - a Scala 3 implementation of Quill.

Akka HTTP, Cats, Quill, ninny, Monix Observable, mill.

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.

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Thea answer to your prayers already exists: http://sequel.jeremyevans.net/.

By far the best database toolkit (ORM, query builder, migration engine) I have seen for any programming language.

Ruby sequel (http://sequel.jeremyevans.net/) is the only library where you can combine classic ORM Model bases usage, with a more raw query builder "just get me all the data into plain objects". You'll never need anything again in your career life.

If you want a db tool which can be an ORM for your app, and drop down to a lower level dsl, while targeting specific features of the databases it supports, + having a "composable superset for building queries", there's [ruby sequel](http://sequel.jeremyevans.net/), which is the best tool of the kind you'll get for any proglang. Everything the author wants, minus the typrchecking perhaps, which is IMO shooting at the stars.

I love the Sequel library from Jeremy Evans (so much better than Rails' AREL). I've used it as my ORM-of-choice since 2008. When leveraging Sequel I almost always use the DSL, but there are times that I want to use bare SQL. When that happens, I almost always use HEREDOCs and my own version of String#squish.

sequel is a pretty good option! To use the above snowflake adapter for sequel, you'll have to learn to use sequel (which is pretty easy). https://sequel.jeremyevans.net/