link to video player demoing the result

A quantum physics effect to teach, a puzzle to build, a problem to solve, a tool to learn!

Polarizing filters are plastic films that let light shine through only in a particular direction (angle). Combining two at 90 degrees completely blocks light.

Animation showing two polarizing filters blocking light at 90 degrees

Very counterintuitively, inserting a third filter between two filters at 90 degrees allows some light shine through!

Photo showing two polarizing filters blocking light at 90 degrees with one more in the middle at 45 degrees

This interesting effect can only be explained with quantum physics, as brilliantly explained in this 3Blue1Brown video.

Polarizing filter films are cheap... So I wanted to create a carboard toy to demo this effect in a suprising way to my kids!

A puzzle to build

Idea is to build a puzzle around this weird effect.

I want to build a cardboard octagon with many "windows" (holes), each window covered with one polarizing filter at a certain angle, like this:

An octagon with holes

Stacking multiple such octagons on top of one another will block light in some combination of filters and not others, depending on the individual filter angles. Moreover, rotating octagons in the stack will make the "displayed pattern" change!

An octagon stack

A problem to solve

One a set of "patterns" to display is decided, is it possible to write a program to determine the assignment of filter angles, for each "window" in each octagon, that is able to produce them all?

In principle, yes! In practice, there's an explosion in the number of possible combinations! Eg. 8 angles × 10 windows × 8 slices × 5 octagons × 8⁴ rotation combinations × 5! orderings × 5 upside-down flips is about 8 billion.

...a bit too much for simple for loops! I need a smarter approach.

A tool to learn

Google OR-Tools logo

Google OR-Tools CP-SAT is a powerful constraint programming solver. It can be used to quickly find solutions to huge combinatorial problems - where one has to find one valid assignment to thousands of variables under thousands of constraints within billions of possible combinations (not all of which valid or optimal)!

Solvers are applicable to many problems and are not new in SUSE's tradition - eg. the zypper package manager uses libsolv to compute valid package dependency combinations, and Uyuni uses Optaplanner to compute valid subscription assignments.

CP-SAT is open source, very efficient (actually close to the state of the art in the field) and easily scriptable from Python... a very interesting target to experiment with!

Now I have an excuse to play with this!

Scope of HackWeek

Find a combination that works for a decent example, and actually cut it in cardboard and filters to try it out!

https://github.com/moio/octaopticon

Looking for hackers with the skills:

quantummechanics solvers python python3 ai game games puzzle

This project is part of:

Hack Week 23

Activity

  • about 2 years ago: mkoutny liked this project.
  • about 2 years ago: moio added keyword "quantummechanics" to this project.
  • about 2 years ago: moio added keyword "solvers" to this project.
  • about 2 years ago: moio added keyword "python" to this project.
  • about 2 years ago: moio added keyword "python3" to this project.
  • about 2 years ago: moio added keyword "ai" to this project.
  • about 2 years ago: moio added keyword "game" to this project.
  • about 2 years ago: moio added keyword "games" to this project.
  • about 2 years ago: moio added keyword "puzzle" to this project.
  • about 2 years ago: gfilippetti liked this project.
  • about 2 years ago: digitaltomm liked this project.
  • about 2 years ago: RDiasMateus liked this project.
  • about 2 years ago: aruiz liked this project.
  • about 2 years ago: moio liked this project.
  • about 2 years ago: moio started this project.
  • about 2 years ago: moio originated this project.

  • Comments

    • moio
      about 2 years ago by moio | Reply

      Day 1 diary - the physical prototyping day

      Spent a bit of time into producing good SVGs with Python, then printed them and tried to find dimensions that worked (one big and one small for testing).

      After few iterations decided to go with octagonal stars rather than plain octagons:

      Various cuts and drawings and printouts

      Then literally hammered out holes with a 10mm punch! Worked beautifully.

      One printout with punched holes

      Then, cut and tested positioning of filter film:

      Filter film cut in pieces

      All seems good from the physical realm so far.

      Next up: coding to determine per-hole filter positioning!

    • moio
      about 2 years ago by moio | Reply

      Day 2 diary: mostly coding

      CP-SAT

      Learnt a lot about CP-SAT, evolved some code I had around to handle:

      • a variable number of "pizzas" ("stars with filter windows")
      • a variable number of "slices" ("sectors" of stars)
      • a variable number of "windows" per "slice"
      • a variable number of "angles" filters can be glued on
      • a variable number of "images"

      Difficult part today is the reordering of "pizzas" in the "pizza stack". Giving that ability makes more combinations possible, but indirection has to be dealt with in code.

      Testing

      The good part about this problem is that tests can trivially be randomized, so it's easy to see if produced solutions work or not.

      The bad part is not all randomized problem instances have a solutions. For those who do not, CP-SAT will happily burn CPUs for hours. I added a pretty arbitrary time limit.

      ChatGPT

      I used ChatGPT for the scaffolding work - and was quite happy with it:

      > Set up a new Python 3.9 based project according to current best practices. > > The project must use the ortools library from Google (note that is a wrapper around a C++ library) > > Include support for: linting, dependency management, github codespace, tests, a Dockerfile, github actions on push and PR including and tests and lint, github actions for release of source archive and docker container on ghcr.io > > Also include a scaffolded README and LICENSE (AGPL) > > The project must compile and work cross platform, including Linux x86 and Mac arm. > > Explain every file created step by step and why

      Not a perfect result, but a good result to learn from - faster than stitching together 10 blog posts (for someone not daily into an ecosystem). add-emoji

    • moio
      about 2 years ago by moio | Reply

      Day 3 diary: 3 failures, 1 success

      Failure 1: adding the possibility of re-ordering the stack

      I thought that allowing to re-ordering pizzas in the stack could help with storing more "images" - found out that as not the case. On a large set of pseudorandom tests, only an extra 4 out of 186 could be solved by changing the order. Not worth it, commit reverted.

      Failure 2: going from a SAT problem to an optimization problem

      CP-SAT has the cool ability of allowing to specify an objective function to minimize or maximise - making it simple to reformulate a satisfiability problem in an optimization one. I tried this approach to make the assignments more flexible but failed: I could not find a good way to mix it with the Automaton constraints which I am using to simulate light traveling through a series of filters. Path abandoned for now.

      Failure 3: allowing brighter-than-specified pixels

      This seemed an easy way to enlarge the solution space - interestingly, almost no effect was visible in tests. Sticking for the simpler approach (to match pixel values exactly) for now.

      Success! First small four-pizza prototype works!

      I am happy to report that after some serious hammering and cutting...

      the author hammering on cardboard

      ...and serious gluing of filter films...

      the author gluing filters on the aforementioned hammered cardboard

      ...I've got a nice filter set! Notice how filtering of monitor light (which is polarized) changes with rotation!

      pizza rotation in front of a monitor

      Now I made four pizzas...

      four pizzas ready to play

      And, in the right order, they will display a programmed X pattern!

      four pizzas stacked to display an X

      I was able to "store" 7 patterns in the four pizzas (a "Y", a "q", the "X" above, an "o", an "I", a "c" and a "K").

      Next step: the bigger brother pizza with bigger patterns!

    • moio
      about 2 years ago by moio | Reply

      Day 4 diary: scale up!

      Today I dealt with the bigger version of the puzzle. Software scaled just fine!

      About hardware I was lucky enough to get help from my son across all phases!

      phase 1: hammering phase 2: cutting phase 3: cutting filters phase 4: cutting filters

      I am really happy with the result, here they are in all their whiteness:

      phase 5: finished

      What message did we hid in there? Stay tuned tomorrow for the last demo!

      PS. Thanks to colleague AR about having kids do some of the job - that worked great!

    • moio
      about 2 years ago by moio | Reply

      Day 5 diary: it's a wrap!

      Today I created a video to explain progress and results, enjoy!

      link to video player demoing the result

      Tricky part was to get light right - so that it was clearly visible on video. Ended up with an inverted laptop screen covered with an opaque film - otherwise light comes polarized and all behavior is totally different!

    Similar Projects

    Improvements to osc (especially with regards to the Git workflow) by mcepl

    Description

    There is plenty of hacking on osc, where we could spent some fun time. I would like to see a solution for https://github.com/openSUSE/osc/issues/2006 (which is sufficiently non-serious, that it could be part of HackWeek project).


    Update M2Crypto by mcepl

    There are couple of projects I work on, which need my attention and putting them to shape:

    Goal for this Hackweek

    • Put M2Crypto into better shape (most issues closed, all pull requests processed)
    • More fun to learn jujutsu
    • Play more with Gemini, how much it help (or not).
    • Perhaps, also (just slightly related), help to fix vis to work with LuaJIT, particularly to make vis-lspc working.


    Testing and adding GNU/Linux distributions on Uyuni by juliogonzalezgil

    Join the Gitter channel! https://gitter.im/uyuni-project/hackweek

    Uyuni is a configuration and infrastructure management tool that saves you time and headaches when you have to manage and update tens, hundreds or even thousands of machines. It also manages configuration, can run audits, build image containers, monitor and much more!

    Currently there are a few distributions that are completely untested on Uyuni or SUSE Manager (AFAIK) or just not tested since a long time, and could be interesting knowing how hard would be working with them and, if possible, fix whatever is broken.

    For newcomers, the easiest distributions are those based on DEB or RPM packages. Distributions with other package formats are doable, but will require adapting the Python and Java code to be able to sync and analyze such packages (and if salt does not support those packages, it will need changes as well). So if you want a distribution with other packages, make sure you are comfortable handling such changes.

    No developer experience? No worries! We had non-developers contributors in the past, and we are ready to help as long as you are willing to learn. If you don't want to code at all, you can also help us preparing the documentation after someone else has the initial code ready, or you could also help with testing :-)

    The idea is testing Salt and Salt-ssh clients, but NOT traditional clients, which are deprecated.

    To consider that a distribution has basic support, we should cover at least (points 3-6 are to be tested for both salt minions and salt ssh minions):

    1. Reposync (this will require using spacewalk-common-channels and adding channels to the .ini file)
    2. Onboarding (salt minion from UI, salt minion from bootstrap scritp, and salt-ssh minion) (this will probably require adding OS to the bootstrap repository creator)
    3. Package management (install, remove, update...)
    4. Patching
    5. Applying any basic salt state (including a formula)
    6. Salt remote commands
    7. Bonus point: Java part for product identification, and monitoring enablement
    8. Bonus point: sumaform enablement (https://github.com/uyuni-project/sumaform)
    9. Bonus point: Documentation (https://github.com/uyuni-project/uyuni-docs)
    10. Bonus point: testsuite enablement (https://github.com/uyuni-project/uyuni/tree/master/testsuite)

    If something is breaking: we can try to fix it, but the main idea is research how supported it is right now. Beyond that it's up to each project member how much to hack :-)

    • If you don't have knowledge about some of the steps: ask the team
    • If you still don't know what to do: switch to another distribution and keep testing.

    This card is for EVERYONE, not just developers. Seriously! We had people from other teams helping that were not developers, and added support for Debian and new SUSE Linux Enterprise and openSUSE Leap versions :-)

    Pending

    Debian 13

    The new version of the beloved Debian GNU/Linux OS

    Seems to be a Debian 12 derivative, so adding it could be quite easy.

    • [ ] Reposync (this will require using spacewalk-common-channels and adding channels to the .ini file)
    • W] Onboarding (salt minion from UI, salt minion from bootstrap script, and salt-ssh minion) (this will probably require adding OS to the bootstrap repository creator)
    • [ ] Package management (install, remove, update...)
    • [ ] Patching (if patch information is available, could require writing some code to parse it, but IIRC we have support for Ubuntu already). Probably not for Debian as IIRC we don't support patches yet.
    • [ ] Applying any basic salt state (including a formula)
    • [ ] Salt remote commands
    • [ ] Bonus point: Java part for product identification, and monitoring enablement
    • [ ] Bonus point: sumaform enablement (https://github.com/uyuni-project/sumaform)
    • [ ] Bonus point: Documentation (https://github.com/uyuni-project/uyuni-docs)


    HTTP API for nftables by crameleon

    Background

    The idea originated in https://progress.opensuse.org/issues/164060 and is about building RESTful API which translates authorized HTTP requests to operations in nftables, possibly utilizing libnftables-json(5).

    Originally, I started developing such an interface in Go, utilizing https://github.com/google/nftables. The conversion of string networks to nftables set elements was problematic (unfortunately no record of details), and I started a second attempt in Python, which made interaction much simpler thanks to native nftables Python bindings.

    Goals

    1. Find and track the issue with google/nftables
    2. Revisit and polish the Python code, primarily the server component
    3. Finish functionality to interact with nftables sets (retrieving and updating elements), which are of interest for the originating issue
    4. Align test suite
    5. Packaging

    Resources

    • https://git.netfilter.org/nftables/tree/py/src/nftables.py
    • https://git.com.de/Georg/nftables-http-api (to be moved to GitHub)
    • https://build.opensuse.org/package/show/home:crameleon:containers/pytest-nftables-container


    Improve chore and screen time doc generator script `wochenplaner` by gniebler

    Description

    I wrote a little Python script to generate PDF docs, which can be used to track daily chore completion and screen time usage for several people, with one page per person/week.

    I named this script wochenplaner and have been using it for a few months now.

    It needs some improvements and adjustments in how the screen time should be tracked and how chores are displayed.

    Goals

    • Fix chore field separation lines
    • Change screen time tracking logic from "global" (week-long) to daily subtraction and weekly addition of remainders (more intuitive than current "weekly time budget method)
    • Add logic to fill in chore fields/lines, ideally with pictures, falling back to text.

    Resources

    tbd (Gitlab repo)


    openQA log viewer by mpagot

    Description

    *** Warning: Are You at Risk for VOMIT? ***

    Do you find yourself staring at a screen, your eyes glossing over as thousands of lines of text scroll by? Do you feel a wave of text-based nausea when someone asks you to "just check the logs"?

    You may be suffering from VOMIT (Verbose Output Mental Irritation Toxicity).

    This dangerous, work-induced ailment is triggered by exposure to an overwhelming quantity of log data, especially from parallel systems. The human brain, not designed to mentally process 12 simultaneous autoinst-log.txt files, enters a state of toxic shock. It rejects the "Verbose Output," making it impossible to find the one critical error line buried in a 50,000-line sea of "INFO: doing a thing."

    Before you're forced to rm -rf /var/log in a fit of desperation, we present the digital antacid.

    No panic: we have The openQA Log Visualizer

    This is the UI antidote for handling toxic log environments. It bravely dives into the chaotic, multi-machine mess of your openQA test runs, finds all the related, verbose logs, and force-feeds them into a parser.

    image

    Goals

    Work on the existing POC openqa-log-visualizer about few specific tasks:

    • add support for more type of logs
    • extend the configuration file syntax beyond the actual one
    • work on log parsing performance

    Find some beta-tester and collect feedback and ideas about features

    If time allow for it evaluate other UI frameworks and solutions (something more simple to distribute and run, maybe more low level to gain in performance).

    Resources

    openqa-log-visualizer


    Improve/rework household chore tracker `chorazon` by gniebler

    Description

    I wrote a household chore tracker named chorazon, which is meant to be deployed as a web application in the household's local network.

    It features the ability to set up different (so far only weekly) schedules per task and per person, where tasks may span several days.

    There are "tokens", which can be collected by users. Tasks can (and usually will) have rewards configured where they yield a certain amount of tokens. The idea is that they can later be redeemed for (surprise) gifts, but this is not implemented yet. (So right now one needs to edit the DB manually to subtract tokens when they're redeemed.)

    Days are not rolled over automatically, to allow for task completion control.

    We used it in my household for several months, with mixed success. There are many limitations in the system that would warrant a revisit.

    It's written using the Pyramid Python framework with URL traversal, ZODB as the data store and Web Components for the frontend.

    Goals

    • Add admin screens for users, tasks and schedules
    • Add models, pages etc. to allow redeeming tokens for gifts/surprises
    • …?

    Resources

    tbd (Gitlab repo)


    Improve chore and screen time doc generator script `wochenplaner` by gniebler

    Description

    I wrote a little Python script to generate PDF docs, which can be used to track daily chore completion and screen time usage for several people, with one page per person/week.

    I named this script wochenplaner and have been using it for a few months now.

    It needs some improvements and adjustments in how the screen time should be tracked and how chores are displayed.

    Goals

    • Fix chore field separation lines
    • Change screen time tracking logic from "global" (week-long) to daily subtraction and weekly addition of remainders (more intuitive than current "weekly time budget method)
    • Add logic to fill in chore fields/lines, ideally with pictures, falling back to text.

    Resources

    tbd (Gitlab repo)


    Try AI training with ROCm and LoRA by bmwiedemann

    Description

    I want to setup a Radeon RX 9600 XT 16 GB at home with ROCm on Slowroll.

    Goals

    I want to test how fast AI inference can get with the GPU and if I can use LoRA to re-train an existing free model for some task.

    Resources

    https://rocm.docs.amd.com/en/latest/compatibility/compatibility-matrix.html https://build.opensuse.org/project/show/science:GPU:ROCm https://src.opensuse.org/ROCm/


    Update M2Crypto by mcepl

    There are couple of projects I work on, which need my attention and putting them to shape:

    Goal for this Hackweek

    • Put M2Crypto into better shape (most issues closed, all pull requests processed)
    • More fun to learn jujutsu
    • Play more with Gemini, how much it help (or not).
    • Perhaps, also (just slightly related), help to fix vis to work with LuaJIT, particularly to make vis-lspc working.


    Extended private brain - RAG my own scripts and data into offline LLM AI by tjyrinki_suse

    Description

    For purely studying purposes, I'd like to find out if I could teach an LLM some of my own accumulated knowledge, to use it as a sort of extended brain.

    I might use qwen3-coder or something similar as a starting point.

    Everything would be done 100% offline without network available to the container, since I prefer to see when network is needed, and make it so it's never needed (other than initial downloads).

    Goals

    1. Learn something about RAG, LLM, AI.
    2. Find out if everything works offline as intended.
    3. As an end result have a new way to access my own existing know-how, but so that I can query the wisdom in them.
    4. Be flexible to pivot in any direction, as long as there are new things learned.

    Resources

    To be found on the fly.


    AI-Powered Unit Test Automation for Agama by joseivanlopez

    The Agama project is a multi-language Linux installer that leverages the distinct strengths of several key technologies:

    • Rust: Used for the back-end services and the core HTTP API, providing performance and safety.
    • TypeScript (React/PatternFly): Powers the modern web user interface (UI), ensuring a consistent and responsive user experience.
    • Ruby: Integrates existing, robust YaST libraries (e.g., yast-storage-ng) to reuse established functionality.

    The Problem: Testing Overhead

    Developing and maintaining code across these three languages requires a significant, tedious effort in writing, reviewing, and updating unit tests for each component. This high cost of testing is a drain on developer resources and can slow down the project's evolution.

    The Solution: AI-Driven Automation

    This project aims to eliminate the manual overhead of unit testing by exploring and integrating AI-driven code generation tools. We will investigate how AI can:

    1. Automatically generate new unit tests as code is developed.
    2. Intelligently correct and update existing unit tests when the application code changes.

    By automating this crucial but monotonous task, we can free developers to focus on feature implementation and significantly improve the speed and maintainability of the Agama codebase.

    Goals

    • Proof of Concept: Successfully integrate and demonstrate an authorized AI tool (e.g., gemini-cli) to automatically generate unit tests.
    • Workflow Integration: Define and document a new unit test automation workflow that seamlessly integrates the selected AI tool into the existing Agama development pipeline.
    • Knowledge Sharing: Establish a set of best practices for using AI in code generation, sharing the learned expertise with the broader team.

    Contribution & Resources

    We are seeking contributors interested in AI-powered development and improving developer efficiency. Whether you have previous experience with code generation tools or are eager to learn, your participation is highly valuable.

    If you want to dive deep into AI for software quality, please reach out and join the effort!

    • Authorized AI Tools: Tools supported by SUSE (e.g., gemini-cli)
    • Focus Areas: Rust, TypeScript, and Ruby components within the Agama project.

    Interesting Links


    Gemini-Powered Socratic Bug Evaluation and Management Assistant by rtsvetkov

    Description

    To build a tool or system that takes a raw bug report (including error messages and context) and uses a large language model (LLM) to generate a series of structured, Socratic-style questions designed to guide a the integration and development toward the root cause, rather than just providing a direct, potentially incorrect fix.

    Goals

    Set up a Python environment

    Set the environment and get a Gemini API key. 2. Collect 5-10 realistic bug reports (from open-source projects, personal projects, or public forums like Stack Overflow—include the error message and the initial context).

    Build the Dialogue Loop

    1. Write a basic Python script using the Gemini API.
    2. Implement a simple conversational loop: User Input (Bug) -> AI Output (Question) -> User Input (Answer to AI's question) -> AI Output (Next Question). Code Implementation

    Socratic Strategy Implementation

    1. Refine the logic to ensure the questions follow a Socratic path (e.g., from symptom-> context -> assumptions -> root cause).
    2. Implement Function Calling (an advanced feature of the Gemini API) to suggest specific actions to the user, like "Run a ping test" or "Check the database logs."

    Resources


    Port some classic game to Linux by MDoucha

    Let's pick some old classic game, reverse engineer the data formats and game rules and write an open source engine for it from scratch. Some games from 1990s are simple enough that we could have a playable prototype by the end of the week.

    Write which games you'd like to hack on in the comments. Don't forget to check e.g. on Open Source Game Clones, Github and SourceForge whether the game is ported already.

    Hack Week 25 - TBD

    It's time to pick a game for the upcoming Hack Week. Discuss in the comments what game you'd like to hack!

    Hack Week 24 - Master of Orion II: Battle at Antares & Chaos Overlords

    Work on Master of Orion II continues but we can hack more than one game. Chaos Overlords is a dystopian, lighthearted, cyberpunk turn-based strategy game originally released in 1996 for Windows 95 and Mac OS. The player takes on the role of a Chaos Overlord, attempting to control a city. Gameplay involves hiring mercenary gangs and deploying them on an 8-by-8 grid of city sectors to generate income, occupy sectors and take over the city.

    How to ~~install & play~~ observe the decompilation progress:

    • Clone the Git repository
    • A playable reimplementation does not exist yet, but when it does, it will be linked in the repository mentioned above.

    Further work needed:

    • Analyze the remaining unknown data structures, most of which are related to the AI.
    • Decompile the AI completely. The strong AI is part of the appeal of the game. It cannot be left out.
    • Reimplement the game.

    Hack Week 20, 21, 22 & 23 - Master of Orion II: Battle at Antares

    Master of Orion II is one of the greatest turn-based 4X games of the 1990s. Explore the galaxy, colonize planets, research new technologies, fight space monsters and alien empires and in the end, become the ruler of the galaxy one way or another.

    How to install & play:

    • Clone the Git repository
    • Run ./bootstrap; ./configure; make && make install
    • Copy all *.LBX files from the original Master of Orion II to the installation data directory (/usr/local/share/openorion2 by default)
    • Run openorion2

    Further work needed:

    • Analyze the rest of the original savegame format and a few remaining data files.
    • Implement most of the game. The open source engine currently supports only loading saved games from the original version and viewing the galaxy map, fleet management and list of known planets.

    Hack Week 19 - Signus: The Artifact Wars

    Signus is a Czech turn-based strategy game similar to Panzer General or Battle Isle series. Originally published in 1998 and open-sourced by the original developers in 2003.

    How to install & play:

    • Clone the Git repository
    • Run ./bootstrap; ./configure; make && make install in both signus and signus-data directories.
    • Run signus

    Further work needed:


    Advent of Code: The Diaries by amanzini

    Description

    It was the Night Before Compile Time ...

    Hackweek 25 (December 1-5) perfectly coincides with the first five days of Advent of Code 2025. This project will leverage this overlap to participate in the event in real-time.

    To add a layer of challenge and exploration (in the true spirit of Hackweek), the puzzles will be solved using a non-mainstream, modern language like Ruby, D, Crystal, Gleam or Zig.

    The primary project intent is not just simply to solve the puzzles, but to exercise result sharing and documentation. I'd create a public-facing repository documenting the process. This involves treating each day's puzzle as a mini-project: solving it, then documenting the solution with detailed write-ups, analysis of the language's performance and ergonomics, and visualizations.

                                   |
                                 \ ' /
                               -- (*) --
                                  >*<
                                 >0<@<
                                >>>@<<*
                               >@>*<0<<<
                              >*>>@<<<@<<
                             >@>>0<<<*<<@<
                            >*>>0<<@<<<@<<<
                           >@>>*<<@<>*<<0<*<
             \*/          >0>>*<<@<>0><<*<@<<
         ___\\U//___     >*>>@><0<<*>>@><*<0<<
         |\\ | | \\|    >@>>0<*<0>>@<<0<<<*<@<<
         | \\| | _(UU)_ >((*))_>0><*<0><@<<<0<*<
         |\ \| || / //||.*.*.*.|>>@<<*<<@>><0<<<
         |\\_|_|&&_// ||*.*.*.*|_\\db//_
         """"|'.'.'.|~~|.*.*.*|     ____|_
             |'.'.'.|   ^^^^^^|____|>>>>>>|
             ~~~~~~~~         '""""`------'
    ------------------------------------------------
    This ASCII pic can be found at
    https://asciiart.website/art/1831
    
    

    Goals

    Code, Docs, and Memes: An AoC Story

    • Have fun!

    • Involve more people, play together

    • Solve Days 1-5: Successfully solve both parts of the Advent of Code 2025 puzzles for Days 1-5 using the chosen non-mainstream language.

    • Daily Documentation & Language Review: Publish a detailed write-up for each day. This documentation will include the solution analysis, the chosen algorithm, and specific commentary on the language's ergonomics, performance, and standard library for the given task.