NetHack VS PostgreSQL

Yes and still under active development [1]! We also just finished the 2024 November NetHack Tournament (TNNT) [2]! I played in the tournament for the first time this year. I had one near-win with a very challenging Monk (I was doing a bunch of conducts [3]) who unfortunately died to the infamous Wizard of Yendor (Rodney as we call him). I also had a winning run with a Wizard which unfortunately finished a few hours after the deadline at the end of the tournament, so sadly that one didn't count!

Next year I hope to have a bit more time to play so that I can record a win in regulation time!

[1] https://github.com/nethack/nethack

[2] https://tnnt.org

[3] https://nethackwiki.com/wiki/Conduct

download NetHack sources (https://github.com/NetHack/NetHack -> Code -> Download ZIP, unpack them on your computer)

My configuration of Eglot is simple: (use-package eglot :hook (c-mode . eglot-ensure)). And it works for a single c file. But when I use this setup to read the code of NetHack, it doesn't work for linting and definition finding (M-.), even though eglot connection has no problem. I observed the same problems when reading the code of SQLite. Some specific problems I observed:

Since nethack 3.1.0, the source for nethack's "bestiary" has been dat/data.base, in plain text, processed into a file named "data" when building the program. The unprocessed file intended for the nethack's next version can be seen at https://github.com/NetHack/NetHack/blob/NetHack-3.7/dat/data.base (it's quite long).

I am not really 100% sure what you are looking for. Are you looking for the actual picture? It is built during compilation from this uuencoded file https://github.com/NetHack/NetHack/blob/NetHack-3.7/win/win32/splash.uu

xNetHack is based on NetHack 3.7.0, and there was a bug (now fixed) in NetHack 3.7.0 that caused stair destinations to be messed up after a game is recovered. I wonder that has happened here: perhaps you are playing a version of xNetHack that inherited the bug from NetHack 3.7.0, this is a recovered game.

They won't be afraid of music in 3.7.

This is a bug that was fixed in the upcoming 3.7, in this commit. Basically, if the random filler created a space that was made inaccessible by the fixed level design getting overlaid on top of the random filler, a door could be created to make that space accessible.

There is not a comprehensive list of changes in existence. This one comes close but doesn't contain everything https://github.com/NetHack/NetHack/blob/NetHack-3.7/doc/fixes3-7-0.txt

PostgreSQL as database

> As introduced in the previous chapters, all identifers are hashed, thus we can also hash the known keywords at startup and make comparing them very fast.

One trick that postgres uses [1][2] is perfect hashing [3]. Since you know in advance what your keywords are, you can design such hashing functions that for each w(i) in list of i keywords W, h(w(i)) = i. It essentially means no collisions and it's O(i) for the memory requirement.

[1] https://github.com/postgres/postgres/blob/master/src/tools/P...

[2] https://github.com/postgres/postgres/blob/master/src/tools/g...

[3] https://en.wikipedia.org/wiki/Perfect_hash_function

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PostgreSQL supports two ways to store structured data in a column: JSON and JSONB.

On PostgreSQL create a database. In this tutorial, we will name it imageboard.

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The following commit was added to the PostgreSQL master branch (REL_18_BETA1):

We got a database for free when we provisioned last time, but if we want to target another database, we can surely do that as the service at this time of writing supports transforming to flavors of Postgres as well.  For this we will outline how to wrangle an external database, via Amazon RDS, and connect it to the service.

This quick start guide gets you up and running with Quarkus on macOS, including necessary tools. You will build a basic database application using Quarkus, Java 17, PostgreSQL, and Hibernate ORM Panache. While Hibernate ORM is the standard, powerful Jakarta Persistence implementation capable of complex mappings, it doesn't always make the most common tasks trivial. Hibernate ORM with Panache is Quarkus's solution to this, focusing specifically on making your data entities and repositories simple, straightforward, and fun to write by reducing boilerplate code for common persistence operations.