rust-android-gradle VS hashbrown

I thought for a second you meant physical rust... Anyway, rust doesn't have any benefits in FTC. If you really needed to use it you could try to use this but you still won't have any way of using the FTC SDK as it was built for java(at least without porting it to rust which will be a ton of work).

Is there any easy way to do this? I've seen this plugin as well, but it looks pretty much the same

That's significantly better than the C world where each project comes bundled with a bespoke build system that nobody else uses. I'm also not convinced that cargo present a significant barrier to interop. There's a Rust plugin for gradle (https://github.com/mozilla/rust-android-gradle) which bridges between gradle and Cargo. Looks simple enough to me.

rust-android-gradle to hook cargo into Android Gradle project

This works great for android https://github.com/mozilla/rust-android-gradle

The mozilla gradle plugin makes compiling and packaging rust libraries quite painless. The jni-crate can be used on Android as well.

That's because you're looking at a wrapper around the actual implementation (which lives in an external package). Notice "use hashbrown::hash_map as base;" at the top.

There's far more unsafe there: https://github.com/rust-lang/hashbrown/blob/f2e62124cd947b5e...

You might want to check out how popular ecosystem crates do some of these things. Particularly relevant to you are probably crates providing collections, such as smallvec, hashbrown, or indexmap.

https://github.com/topics/swisstable

rust-lang/hashbrown: https://github.com/rust-lang/hashbrown

CuPy has array but not yet hashmaps, or (GPU) SIMD FWICS?

NumPy does SIMD:

Thanks, great point indeed. I am looking into this https://github.com/rust-lang/hashbrown

The way I think about it -- rather naively, I suppose -- is that I care more about the references cells make to each other than the actual grid of cells displayed on a table. The latter feels more like a "view" of the data than an actual data structure?

This also seems to align with the relative priority of (sorted from highest to lowest): figuring out the order of evaluation, calculating those evaluations, and finally displaying the results of the evaluation

updated std's hashbrown dependency to 0.14 which contains some optimizations

The std hashmap is actually very fast and uses state of the art hashmap design, namely because it's implemented by hashbrown

I believe Rust uses hashbrown as the underlying implementation now. This just calculates the number of buckets based on the number of items requested:

https://github.com/rust-lang/hashbrown/blob/009969a860290849...

Is it really the case that rehashing can guarantee that the number of buckets allocated will be sufficient for any given set of keys? In principle you could fail to rehash in a way that reduces collisions after k attempted rehashings.

For example, since the hashbrown crate is marked with #![no_std], it can be used as a dependency for the standard library.

To implement something that cannot be expressed in safe Rust, or at least cannot be expressed succinctly in safe Rust, like fundamental datastructures. The hashbrown crate contains a lot of unsafe code, but it's such high quality that it's now the backing implementation for std::collections::HashMap.