rand VS fastrand

Making compatibility promises for distributions means they cannot take advantage of potential advancements in the field.

Defining an error type that is meaningful, portable, and compatible with no-std isn't straightforward. If the std lib's getrandom requires std, then just like that, rand and many other crates won't use it anyway. Using io::Result seems to me to face this challenge.

Some wasm targets can’t generate random numbers at all but in the case of the book because you are using wasm in a browser you can use JS to generate random numbers. I believe there’s a way to get the rand crate to use JS as the backend for generating rand but its a bit more convoluted than the easy one-liner that the book suggests.

rand

This uses rand and xcomplex to handle the mathematics, png to write image files, and dialoguer and indicatif for some pretty prompts and progress bars.

You can often achieve this without any unsafe by putting an assert!() on the length before the hot loop. For example, I got rid of some unsafe in rand that way.

This is a widely used method to map random integers to floating point numbers, but it has the disadvantage of wasting 1 bit of float mantissa precision.

On modern CPUs, its computational advantage over full-precision mapping methods, such as multiplication by a float, is not always clear [1].

[1] https://github.com/rust-random/rand/issues/416

In fact, there are a lot of crates in Rust where in other programming languages, it would be included in the standard library. Examples are regex, random number generators, additional iterator methods, macros for other collections, num traits, loggers, HTTP libraries, error handling, async runtimes, serialization and deserialization, date and time, and many more.

On the frontend, while Puzzle Panda is mostly built with Svelte, I do load a small wasm package which exposes a seedable random number generator from fastrand.