Скачать или смотреть Conway's Game of Life in Python

Conway's Game of Life, also known simply as Life, is a cellular automaton devised by the British mathematician John Horton Conway in 1970. It is a zero-player game, meaning that its evolution is determined by its initial state, requiring no further input. One interacts with the Game of Life by creating an initial configuration and observing how it evolves. It is Turing complete and can simulate a universal constructor or any other Turing machine.

It's not hard to find examples of implementations of this automaton, pretty much in any language you desire. Since I'm refreshing my Python knowledge, and learning any programming language or framework is more fun with a goal in mind, I decided to take my own swing at it. I quickly ran against the inherent slowness of Python for smaller cell sizes and larger areas, so I decided to implement a number of optimizations. An obvious one was using Numba for the heavy-lifting functions that calculate the next state of the automaton. However, I used several approaches that got me quite a bit further, such as optimizing the search space so I didn't have to inspect all cells in the grid between states, and I took a different approach to the annoying but necessary neighbour-counting. Using line profiler to measure the results of my optimizations, it was clear that these approaches clearly yielded nice results that go further than what just Numba provided. It goes to show that, instead of only relying on (very useful and powerful) libraries out there, thinking about data structures and looking at the problem from multiple angles, does go a long way.

I had a lot of fun with this little project, and will probably evolve it further. It's my re-acquaintance with Python after using it for several AI courses a few years back, but I'm taking a much more serious swing at it at this point. The slower nature of Python compared to the languages I'm used to, coupled with the fact it's such an easy language to get into, put me in a headspace that reminded me of the time I started getting into software development a few decades ago. Back when you couldn't rely on fast hardware to do the work for you. Thinking about algorithms, checking what data structures suit your problem, that's what's infinitely fun to me. Hats off to van Rossum and many others for providing a language where it's fun and painless to quickly prototype and evolve things.

Read about the implementation (soon) on my blog: https://www.peculiar-coding-endeavour...
You can also check out the code on my GitHub, the link to which you'll find on my website.