A quantum physics experiment puzzle (designed with Google's CP-SAT solver)
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.
Very counterintuitively, inserting a third filter between two filters at 90 degrees allows some light shine through!
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:
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!
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 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
This project is part of:
Hack Week 23
Activity
Comments
-
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:
Then literally hammered out holes with a 10mm punch! Worked beautifully.
Then, cut and tested positioning of filter film:
All seems good from the physical realm so far.
Next up: coding to determine per-hole filter positioning!
-
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).
- 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"
-
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...
...and serious gluing of filter films...
...I've got a nice filter set! Notice how filtering of monitor light (which is polarized) changes with rotation!
Now I made four pizzas...
And, in the right order, they will display a programmed X pattern!
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!
-
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!
I am really happy with the result, here they are in all their whiteness:
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!
-
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!
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!
Reply to moio
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:
Then literally hammered out holes with a 10mm punch! Worked beautifully.
Then, cut and tested positioning of filter film:
All seems good from the physical realm so far.
Next up: coding to determine per-hole filter positioning!
# A First Level Header ## A Second Level Header Use one asterisk to *emphasize* Use two asterisks for **strong emphasis** - Use hyphens - for unordereed - lists This is an [link to example.com](http://example.com/) This is an image  This is a user link @hans This is a project link hw#some-cool-title
Reply to moio
Day 2 diary: mostly coding
CP-SAT
Learnt a lot about CP-SAT, evolved some code I had around to handle:
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).
# A First Level Header ## A Second Level Header Use one asterisk to *emphasize* Use two asterisks for **strong emphasis** - Use hyphens - for unordereed - lists This is an [link to example.com](http://example.com/) This is an image  This is a user link @hans This is a project link hw#some-cool-title
Reply to moio
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...
...and serious gluing of filter films...
...I've got a nice filter set! Notice how filtering of monitor light (which is polarized) changes with rotation!
Now I made four pizzas...
And, in the right order, they will display a programmed X pattern!
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!
# A First Level Header ## A Second Level Header Use one asterisk to *emphasize* Use two asterisks for **strong emphasis** - Use hyphens - for unordereed - lists This is an [link to example.com](http://example.com/) This is an image  This is a user link @hans This is a project link hw#some-cool-title
Reply to moio
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!
I am really happy with the result, here they are in all their whiteness:
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!
# A First Level Header ## A Second Level Header Use one asterisk to *emphasize* Use two asterisks for **strong emphasis** - Use hyphens - for unordereed - lists This is an [link to example.com](http://example.com/) This is an image  This is a user link @hans This is a project link hw#some-cool-title
Reply to moio
Day 5 diary: it's a wrap!
Today I created a video to explain progress and results, enjoy!
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!
# A First Level Header ## A Second Level Header Use one asterisk to *emphasize* Use two asterisks for **strong emphasis** - Use hyphens - for unordereed - lists This is an [link to example.com](http://example.com/) This is an image  This is a user link @hans This is a project link hw#some-cool-title
Similar Projects
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
- Find and track the issue with google/nftables
- Revisit and polish the Go or Python code (prefer Go, but possibly depends on implementing missing functionality), primarily the server component
- Finish functionality to interact with nftables sets (retrieving and updating elements), which are of interest for the originating issue
- Align test suite
- 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
Results
- Go nftables issue was related to set elements needing to be added with different start and end addresses - coincidentally, this was recently discovered by someone else, who added a useful helper function for this: https://github.com/google/nftables/pull/342.
Side results
Upon starting to unify the structure and implementing more functionality, missing JSON output support was noticed for some subcommands in libnftables. I am submitting patches as needed:
- https://lore.kernel.org/netfilter-devel/20251203131736.4036382-2-georg@syscid.com/T/#u
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)
Help Create A Chat Control Resistant Turnkey Chatmail/Deltachat Relay Stack - Rootless Podman Compose, OpenSUSE BCI, Hardened, & SELinux by 3nd5h1771fy
Description
The Mission: Decentralized & Sovereign Messaging
FYI: If you have never heard of "Chatmail", you can visit their site here, but simply put it can be thought of as the underlying protocol/platform decentralized messengers like DeltaChat use for their communications. Do not confuse it with the honeypot looking non-opensource paid for prodect with better seo that directs you to chatmailsecure(dot)com
In an era of increasing centralized surveillance by unaccountable bad actors (aka BigTech), "Chat Control," and the erosion of digital privacy, the need for sovereign communication infrastructure is critical. Chatmail is a pioneering initiative that bridges the gap between classic email and modern instant messaging, offering metadata-minimized, end-to-end encrypted (E2EE) communication that is interoperable and open.
However, unless you are a seasoned sysadmin, the current recommended deployment method of a Chatmail relay is rigid, fragile, difficult to properly secure, and effectively takes over the entire host the "relay" is deployed on.
Why This Matters
A simple, host agnostic, reproducible deployment lowers the entry cost for anyone wanting to run a privacy‑preserving, decentralized messaging relay. In an era of perpetually resurrected chat‑control legislation threats, EU digital‑sovereignty drives, and many dangers of using big‑tech messaging platforms (Apple iMessage, WhatsApp, FB Messenger, Instagram, SMS, Google Messages, etc...) for any type of communication, providing an easy‑to‑use alternative empowers:
- Censorship resistance - No single entity controls the relay; operators can spin up new nodes quickly.
- Surveillance mitigation - End‑to‑end OpenPGP encryption ensures relay operators never see plaintext.
- Digital sovereignty - Communities can host their own infrastructure under local jurisdiction, aligning with national data‑policy goals.
By turning the Chatmail relay into a plug‑and‑play container stack, we enable broader adoption, foster a resilient messaging fabric, and give developers, activists, and hobbyists a concrete tool to defend privacy online.
Goals
As I indicated earlier, this project aims to drastically simplify the deployment of Chatmail relay. By converting this architecture into a portable, containerized stack using Podman and OpenSUSE base container images, we can allow anyone to deploy their own censorship-resistant, privacy-preserving communications node in minutes.
Our goal for Hack Week: package every component into containers built on openSUSE/MicroOS base images, initially orchestrated with a single container-compose.yml (podman-compose compatible). The stack will:
- Run on any host that supports Podman (including optimizations and enhancements for SELinux‑enabled systems).
- Allow network decoupling by refactoring configurations to move from file-system constrained Unix sockets to internal TCP networking, allowing containers achieve stricter isolation.
- Utilize Enhanced Security with SELinux by using purpose built utilities such as udica we can quickly generate custom SELinux policies for the container stack, ensuring strict confinement superior to standard/typical Docker deployments.
- Allow the use of bind or remote mounted volumes for shared data (
/var/vmail, DKIM keys, TLS certs, etc.). - Replace the local DNS server requirement with a remote DNS‑provider API for DKIM/TXT record publishing.
By delivering a turnkey, host agnostic, reproducible deployment, we lower the barrier for individuals and small communities to launch their own chatmail relays, fostering a decentralized, censorship‑resistant messaging ecosystem that can serve DeltaChat users and/or future services adopting this protocol
Resources
- The links included above
- https://chatmail.at/doc/relay/
- https://delta.chat/en/help
- Project repo -> https://codeberg.org/EndShittification/containerized-chatmail-relay
Liz - Prompt autocomplete by ftorchia
Description
Liz is the Rancher AI assistant for cluster operations.
Goals
We want to help users when sending new messages to Liz, by adding an autocomplete feature to complete their requests based on the context.
Example:
- User prompt: "Can you show me the list of p"
- Autocomplete suggestion: "Can you show me the list of p...od in local cluster?"
Example:
- User prompt: "Show me the logs of #rancher-"
- Chat console: It shows a drop-down widget, next to the # character, with the list of available pod names starting with "rancher-".
Technical Overview
- The AI agent should expose a new ws/autocomplete endpoint to proxy autocomplete messages to the LLM.
- The UI extension should be able to display prompt suggestions and allow users to apply the autocomplete to the Prompt via keyboard shortcuts.
Resources
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.
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.
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
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)
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)
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.
Kubernetes-Based ML Lifecycle Automation by lmiranda
Description
This project aims to build a complete end-to-end Machine Learning pipeline running entirely on Kubernetes, using Go, and containerized ML components.
The pipeline will automate the lifecycle of a machine learning model, including:
- Data ingestion/collection
- Model training as a Kubernetes Job
- Model artifact storage in an S3-compatible registry (e.g. Minio)
- A Go-based deployment controller that automatically deploys new model versions to Kubernetes using Rancher
- A lightweight inference service that loads and serves the latest model
- Monitoring of model performance and service health through Prometheus/Grafana
The outcome is a working prototype of an MLOps workflow that demonstrates how AI workloads can be trained, versioned, deployed, and monitored using the Kubernetes ecosystem.
Goals
By the end of Hack Week, the project should:
Produce a fully functional ML pipeline running on Kubernetes with:
- Data collection job
- Training job container
- Storage and versioning of trained models
- Automated deployment of new model versions
- Model inference API service
- Basic monitoring dashboards
Showcase a Go-based deployment automation component, which scans the model registry and automatically generates & applies Kubernetes manifests for new model versions.
Enable continuous improvement by making the system modular and extensible (e.g., additional models, metrics, autoscaling, or drift detection can be added later).
Prepare a short demo explaining the end-to-end process and how new models flow through the system.
Resources
Explore LLM evaluation metrics by thbertoldi
Description
Learn the best practices for evaluating LLM performance with an open-source framework such as DeepEval.
Goals
Curate the knowledge learned during practice and present it to colleagues.
-> Maybe publish a blog post on SUSE's blog?
Resources
https://deepeval.com
https://docs.pactflow.io/docs/bi-directional-contract-testing
Gemini-Powered Systemic 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 or Systemic 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
- Write a basic Python script using the Gemini API.
- 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
- Refine the logic to ensure the questions follow a Socratic path (e.g., from symptom-> context -> assumptions -> root cause).
- 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
What are Systemic Questions?
Systemic questions explore the relationships, patterns, and interactions within a system rather than focusing on isolated elements.
In IT, they help uncover hidden dependencies, feedback loops, assumptions, and side-effects during debugging or architecture analysis.
Liz - Prompt autocomplete by ftorchia
Description
Liz is the Rancher AI assistant for cluster operations.
Goals
We want to help users when sending new messages to Liz, by adding an autocomplete feature to complete their requests based on the context.
Example:
- User prompt: "Can you show me the list of p"
- Autocomplete suggestion: "Can you show me the list of p...od in local cluster?"
Example:
- User prompt: "Show me the logs of #rancher-"
- Chat console: It shows a drop-down widget, next to the # character, with the list of available pod names starting with "rancher-".
Technical Overview
- The AI agent should expose a new ws/autocomplete endpoint to proxy autocomplete messages to the LLM.
- The UI extension should be able to display prompt suggestions and allow users to apply the autocomplete to the Prompt via keyboard shortcuts.
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/openorion2by 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 installin bothsignusandsignus-datadirectories. - Run
signus
Further work needed:
Sim racing track database by avicenzi
Description
Do you wonder which tracks are available in each sim racing game? Wonder no more.
Goals
Create a simple website that includes details about sim racing games.
The website should be static and built with Alpine.JS and TailwindCSS. Data should be consumed from JSON, easily done with Alpine.JS.
The main goal is to gather track information, because tracks vary by game. Older games might have older layouts, and newer games might have up-to-date layouts. Some games include historical layouts, some are laser scanned. Many tracks are available as DLCs.
Initially include official tracks from:
- ACC
- iRacing
- PC2
- LMU
- Raceroom
- Rennsport
These games have a short list of tracks and DLCs.
Resources
The hardest part is collecting information about tracks in each game. Active games usually have information on their website or even on Steam. Older games might be on Fandom or a Wiki. Real track information can be extracted from Wikipedia or the track website.
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.