py-caskdb VS WebGL-Fluid-Simulation

self plug: I wanted to learn how databases work internally, like how they store and retrieve data, build indexes, etc.

I built an educational KV store to teach someone to write a database from scratch. I have set up this project in TDD fashion with the tests. So, you start with simple functions, pass the tests, and the difficulty level goes up. There are hints if you get stuck. When all the tests pass, you would have written a persistent key-value store in the end.

link: https://github.com/avinassh/py-caskdb

link: https://github.com/avinassh/py-caskdb

If you like databases, you start exploring the internals and start writing one! There is no going back once you dig deep into storage internals, KV stores, and distributed systems.

plug: I made an educational project which can help you write a database in python, from scratch - https://github.com/avinassh/py-caskdb

Build your own disk based KV store

link - https://github.com/avinassh/py-caskdb

It kinda reminds me of this fluid simulation website. The site is about a computer graphics technique that simulates the motion and appearance of fluids such as water, smoke or fire. You can use your mouse to move around the screen to see the simulation, also can change how the fluid simulation works by adjusting the sliders in the control panel next to it.

Typed arrays are essential for web apps that use WebGL and WebGPU. Being able to send this typed data to run computations on the GPU in parallel can give you 1000x speed up.

You can see it in action on this WebGL fluid simulator[0] by PavelDoGreat.

[0] https://github.com/PavelDoGreat/WebGL-Fluid-Simulation

this one is much smoother: https://paveldogreat.github.io/WebGL-Fluid-Simulation/

previously: https://news.ycombinator.com/item?id=34422948

Not a video. WebGL Fluid is the website.

Sure here it is

Off the top of my head I'm thinking of WebGL Fluid Simulation

Here is poor man's stirrer: https://paveldogreat.github.io/WebGL-Fluid-Simulation/