Unfortunately, running it from source is kind of a pain since it has a few dependencies...Happy to boot up a VDE in Linux and create an executable for you if you're interested in playing it sometime outside of rating it. I have included a windows version in my first release on github https://github.com/Larkenx/LispGameJame2018/releases/tag/1.0
larkenx
Creator of
Recent community posts
For those who are interested in checking out my game independent of rating it, feel free to check out my release on github. I have released a windows and OSX version of the game. To install it, download either the osx.dmg or windows.zip, extract it, and run the main executable under the main folder. The version I have up on github is more complete - featuring gems you can collect and "win" the game by collecting all the gems. https://github.com/Larkenx/LispGameJame2018/releases/tag/1.0
My worst moment
I stated the jam two days late, built a prototype in a day, then spent a day learning how to use other parts of the Racket language to do it better, so I threw everything out and started again on ~ Day 5! Realizing that I wouldn’t really have a game but more of a world explorer on the last few days was a bit upsetting
My best moment
Being able to use a third party simplex noise library and generate elevation maps and visualize them in 3D is one of the coolest things I’ve ever done in computer science. Being able to then translate that to a 2D, top-down ASCII view was really rewarding and gives me lots of ideas on how to work with that in the future!
After hitting a road block, I took the backseat for a few days and studied this excellent guide on how to build roguelikes in racket https://blog.jverkamp.com/2013/04/04/racket-roguelike-1-a-gui-screens-i/o-and-yo.... I completely gutted the rendering portion of the tutorial code, but kept a large majority of the procedural map generation, prototypes for tiles & entity structures. in my remaining days of the jam, I'd like to give the game an overall look & feel, as well as some clear and cut win/lose conditions. Here's a GIF of exploring the infinite surface of simplex noise