High-level data structures in Hare March 26, 2021 by Drew DeVault

Hare does not support generics, and our approach to data structures is much like C: DIY. Hare supports the following basic data structures:

That’s the complete list of aggregate type classes defined by the specification. You can build arbitrarily complex data structures out of these, but, like C, Hare puts the ball in your court. For most of your application’s day-to-day data processing needs, these types are sufficient, shunting data from A to B without much fuss. For most of your data processing, these limitations will not be your bottleneck, and simpler (but slower) data structures won’t have much of an impact on your program.

But sometimes data structures are your bottleneck. Most programs are primarily dealing with two or three important ideas that their data is modeled around. For these, it’s likely that the application of a higher-level data structure will provide a meaningful impact to your program. Instead of providing such data structures in the standard library (or even, through generics, in third-party libraries), Hare leaves this work to you.

If the absence of a particular data structure truly is your application’s bottleneck, then writing it yourself may ultimately be the better approach. You’ll have to familiarize yourself with the data structures and algorithms that manipulate them, so you can have an intimate understanding of the processes most important to your application. You can also tune and tweak them to keep it lean and mean within your use-case, only making them as complex as your application calls for.

For example, let’s look at the Hare build driver module cache. The build driver is responsible for collecting input files, resolving their dependencies, and producing a plan for compiling your program. Because one module could be included several times by successive transitive dependencies, and we want to avoid scheduling it to be built several times (that’d be O(nc), yikes), we need a cache. A hash map is suitable for this. So we define the data structures like so:

type plan = struct {
	// ...
	modmap: [64][]modcache,

type modcache = struct {
	hash: u32,
	task: *task,
	ident: ast::ident,
	version: module::version,

We keep this as simple as possible. If we had a more sophisticated use-case, we may want to add dynamic re-hashing, and indeed, such a change would not be too terribly difficult. 64 buckets is sufficient for this use-case, and waste not, want not.

The standard library provides hash::fnv, which is a good algorithm to use to produce hashes for our map. We’re keying this map based on the module identifier (ast::ident), so we need to write a function which hashes an identifier.

fn ident_hash(ident: ast::ident) u32 = {
	let hash = fnv::fnv32a();
	for (let i = 0z; i < len(ident); i += 1) {
		hash::write(hash, strings::toutf8(ident[i]));
		hash::write(hash, [0]);
	return fnv::sum32(hash);

Then, we need some code to fetch items from the map, or insert them if not already present. For this, we simply take the hash of the identifier modulo the length of our module cache to identify a bucket to use. Then we iterate over the slice in that bucket until we find a matching module. If there’s no matching module, we schedule the object for the build and add it to the module cache for next time.

fn sched_module(plan: *plan, ident: ast::ident, link: *[]*task) *task = {
	let hash = ident_hash(ident);
	let bucket = &plan.modmap[hash % len(plan.modmap)];
	for (let i = 0z; i < len(*bucket); i += 1) {
		if (bucket[i].hash == hash) {
			return bucket[i].task;

	// ...

	let obj = sched_hare_object(plan, ver, ident, depends...);
	append(bucket, modcache {
		hash = hash,
		task = obj,
		ident = ident,
		version = ver,
	return obj;

That’s all there is to it. Hare doesn’t provide us with a generic hash map, but we were able to build one ourselves in just a few lines of code. A hash map is one of the simpler data structures we could have shown here, but even for more complex ones, you’ll generally find that it’s not too difficult to implement them yourself in Hare. In exchange for a little more of your time, we can offer you a simpler language, the experience and understanding that comes with implementing the data structures yourself, and the advantages of an implementation tuned precisely to your specific application’s needs.