Async Ruby VS Sequel

Async is a composable asynchronous I/O framework for Ruby. It allows you to do things concurrently using Fibers. Since 3.0, Ruby has a fiber scheduler and Ruby core supports it. This means you can have non-blocking I/O without much effort, for example, when using Net::HTTP. If you perform a blocking operation, such as an HTTP call, inside a fiber, it will immediately yield so that another fiber can become active and do some useful work instead of blocking and waiting for the HTTP call to complete.

The Async gem is the natural successor, It's actively maintained, and allows you write synchronous code is if it wasn't non-blocking, and most libraries don't need any special support for Async (exceptions are gems with C extensions that do I/O and DB libraries with connection pooling that would otherwise be thread-based).

https://github.com/socketry/async uses coroutines and I think in general it’s been a great model with very few downsides in practice.

There's async I/O. Here's a library that leans on Ruby 3's fiber scheduler.

Hey folks, wanted to show this off and get feedback. Still early/experimental but there are quite a few concepts I'm excited about here. This project came about while writing a program in Go and loving its approach to concurrency. Being a long-time Rubyist I immediately started to think about what similar concepts might look like in Ruby.

I set out with two main design constraints:

1. Lightweight: I didn't want routines to be backed by fibers or threads. Having been involved some in the async project (https://github.com/socketry/async), I had some experience using fibers for concurrency but was curious if they could be avoided.

2. Explicitness: Routine behavior must be written to describe exactly how it is to behave. I always felt like concurrent code was hard to fully understand because of the indirection involved. On the spectrum between tedium and magical I wanted to err more on the side of tedium with Goru.

Goru routines are just blocks that are called once for every tick of the reactor. It is up to the developer to implement behavior in terms of a state machine, where on each tick the routine takes some action and then updates the state of the routine for the next tick. This fulfills both design constraints:

1. Because routines are just blocks, they weigh in at about ~345 bytes of memory overhead.

2. Routine behavior is explicit because it is written as a state machine inside the block.

Couple more features worth noting:

* Goru includes channels for buffered reading/writing (similar to channels in Go).

* Goru ships with primitives for non-blocking IO to easily build things like http servers.

Curious your thoughts!

For those who are interested here is the question.

Welcome! Ruby isn't exactly "dying", but the hype/popularity is definitely fading. This is primarily because Ruby is no longer "new", most of Ruby's popularity came from Rails, and now Rails is no longer the "new hotness". However, Ruby still has lots of awesome features and lots of awesome other libraries and frameworks, such as the new fancy irb gem that uses reline, nokogiri, chunky_png, the async gems, Dragon Ruby, SciRuby, Ronin, and the new Hanami web framework.

In Github, there is a Async Gem(https://github.com/socketry/async).

While Ruby is not this famous anymore, I still wanted the stack in my architecture. I eschewed Ruby on Rails in favor of the leaner Sinatra framework. I use sequel for database access. The dynamic nature of the language was a bit of a hurdle, which is why it took me more time to develop my service than with Go.

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.