logpaste VS Sequel

FWIW, I've used Litestream on Google Cloud Run and never run into issues, but I haven't pushed it much:

https://github.com/mtlynch/logpaste/blob/master/docs/deploym...

Currently, no. I've implemented that functionality recently in my other tool, LogPaste, so it shouldn't be too hard to reproduce here.

My tool is called LogPaste. It allows users to generate shareable URLs for text files. I use it in my open-source KVM over IP device so that users can easily share diagnostic logs with me.

I designed it with self-hosting in mind, so there are instructions for hosting it under Docker, as well as with several free cloud hosting providers. You can even host the data storage part yourself if you use a solution like Minio.

I still use GCP, but I avoid locking myself into their proprietary infrastructure when I'm writing new stuff. I feel like Google is far too cavalier about deprecating services and forcing their customers to do migration work.

It is hard to replace GCP's managed datastores because I really don't want to maintain my own database server (even if it's a managed service that someone else upgrades for me). So I've stuck to Google Cloud Datastore / Firestore, but I've been experimenting a lot with Litestream[0], and I think that might be my go-to choice in the future instead of proprietary managed datastores.

Litestream continuously streams data from a SQLite database to an S3 backend. It means that you can design your app to use SQLite and then sync the database to any S3 provider. I designed a simple pastebin clone on top of Litestream, and I use it in production for my open source KVM over IP. It's worked great so far, though I'm admittedly putting a pretty gentle workload on it (a handful of requests per day).

[0] https://litestream.io/

[1] https://github.com/mtlynch/logpaste

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/