pgloader VS Sequel

No, it's difficult to read, and understand. It's a parenthesis circus, example -

https://github.com/dimitri/pgloader/blob/master/src/sources/...

Examples (for Common Lisp, so not citing Emacs): reddit v1, Google's ITA Software that powers airfare search engines (Kayak, Orbitz…), Postgres' pgloader (http://pgloader.io/), which was re-written from Python to Common Lisp, Opus Modus for music composition, the Maxima CAS, PTC 3D designer CAD software (used by big brands worldwide), Grammarly, Mirai, the 3D editor that designed Gollum's face, the ScoreCloud app that lets you whistle or play an instrument and get the music score,

but also the ACL2 theorem prover, used in the industry since the 90s, NASA's PVS provers and SPIKE scheduler used for Hubble and JWT, many companies in Quantum Computing, companies like SISCOG, who plans the transportation systems of european metropolis' underground since the 80s, Ravenpack who's into big-data analysis for financial services (they might be hiring), Keepit (https://www.keepit.com/), Pocket Change (Japan, https://www.pocket-change.jp/en/), the new Feetr in trading (https://feetr.io/, you can search HN), Airbus, Alstom, Planisware (https://planisware.com),

or also the open-source screenshotbot (https://screenshotbot.io), the Kandria game (https://kandria.com/),

and the companies in https://github.com/azzamsa/awesome-lisp-companies and on LispWorks and Allegro's Success Stories.

https://github.com/tamurashingo/reddit1.0/

http://opusmodus.com/

https://www.ptc.com/en/products/cad/3d-design

http://www.izware.com/mirai

https://apps.apple.com/us/app/scorecloud-express/id566535238

I worked on migrating our MySQL system to PostgreSQL using pgloader ( https://pgloader.io/ ).

There were some hiccups, things that needed clarification in documentation, and some additional processes that needed to be done outside of the system to get everything we need in place, it was a amazing help. Not sure the project would've been possible without it.

Data mapping from PostgreSQL to PostgreSQL as in the article isn't nearly as bad as going between systems. We took a full extended outage and didn't preload any data. There were many dry runs before hand and validation before hand, but the system wasn't so mission critical that we couldn't afford to shutoff the system for a couple of hours.

Initially, I started down the pgloader path, which seemed to be a common approach for the database conversion. However, using my M1-chip MacBook Pro led to some unexpected issues. Instead, I opted to use NMIG to convert MySQL to PostgreSQL. For more information, please check out the “Highlights From the Database Conversion” section below.

I just checked pgloader (which is mostly for heterogeneous database migrations) and it doesn't seem to have any explicit throttling features, either. However, you can set concurrency, number of workers, and batch size.

But do what makes you happy. The best PostgreSQL data loader in the world is written in Common Lisp. Now, CL is a fast and ANSI standardized language with multiple implementations, and was used to create Reddit, but it's hard to call it fashionable.

- [ScoreCloud](https://scorecloud.com/) - A web and mobile application to automatically create music notation from music performance or recordings. Built with LispWorks.

## DB tools

- [Pgloader](https://github.com/dimitri/pgloader/) - Migrate to PostgreSQL in a single command!. [PostgreSQL License]

I would warmly recommend https://pgloader.io but, unfortunately, the Oracle support is still in need of a sponsor :-)

I followed instruction here: https://github.com/dimitri/pgloader/blob/master/INSTALL.md, but can't get pass sbcl requirement.

https://pgloader.io/ There's been a great tool available for this for many years.

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.

```

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.