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Composition patterns

The shape catalog names the seven building blocks — app locus, namespace locus, service locus, spawned child, @form collection with a domain facade, shape type, free fn. This chapter is the next layer up: the compositions of those blocks that recur in real Hale services, distilled from production use. Reach for one of these when a problem feels like it needs a new language feature — usually it doesn’t, it needs one of these shapes.

The canonical answer to “I have N dynamic, keyed children with their own lifecycles” (and to the rejection of putting loci in a hashmap):

pinned reader ──▶ cooperative manager ──▶ keyed per-entity child
(owns the fd, (accept()s a child (subscribe ... where
publishes events) per new key) key == self.id)
  • A pinned locus owns the blocking input (socket, ring) on its own thread and publishes decoded events onto the bus.

  • A cooperative manager subscribes to “new entity” events and accept()s one child per key. Declare release(c: Child) so each child is reclaimed when its flow ends (otherwise it’s a resident and lives until the manager dissolves — unbounded on a daemon; the compiler warns on that shape).

  • The topic declares its routing field and each child subscribes with a key filter, so the bus delivers only that entity’s traffic:

    topic Update { payload: Tick; keyed_by id; }
    // in the child:
    bus { subscribe Update as on_update where key == self.id; }

    Keys can be scalars or String — a symbol id and a symbol name both work (String keys are hash-gated, so non-matching traffic costs one integer compare per entry).

This gives you per-entity state and lifecycle without a map of loci — the bus is the routing table, keyed. Filtering in the handler instead (if u.id == self.id) is the anti-pattern this composition deletes: it delivers every message to every child and discards N-1 of N.

A special case of the gateway with zero hardcoded topology: the manager doesn’t know its children up front. A subscription triggers the accept():

// manager
bus { subscribe "entity.first_seen" as on_seen of type Seen; }
fn on_seen(s: Seen) {
// First message for this key → spawn its child now.
// Bare instantiation inside a parent method attaches the child:
// it triggers the enclosing accept(c) gatekeeper. `accept` is a
// lifecycle hook the runtime invokes, never a method you call.
Child { id: s.id };
}

The topology grows from the data. Combined with release, children appear on first contact and vanish when their flow ends — the process shape mirrors the live workload with no configuration. (If the manager doesn’t itself accept this child type, the child bubbles to the nearest accepting ancestor.)

3. Hot-path counters & gauges (and the CQRS rejection)

Section titled “3. Hot-path counters & gauges (and the CQRS rejection)”

You will want to write let n = self.metrics.incr("hits") on a hot path. Hale rejects locus methods that return locus values (the “CQRS” shape) — a method call that hands back a live locus reference breaks the closed-world ownership the substrate relies on. The rejection without a replacement strands you, so here is the migration:

  • Pre-allocated handles at boot. Declare the counter/gauge loci as params of the owner, instantiated once at birth — std::metrics::counter(...) as a param default, as Concurrency & placement shows. The hot path mutates in place (self.ticks.inc(), or a plain self.hits = self.hits + 1) — no method returning a locus, no per-call allocation.
  • Bus-routed single-writer store. For shared metrics, publish a MetricUpdate { name, delta } to a single collector locus that owns the store and applies updates in its handler. One writer, no contention.

Either way the hot path does an in-place field write or a publish — never a method that returns a locus.

When you produce data faster than you want to publish it (telemetry, book snapshots), gate the publish behind a time-or-volume trigger rather than publishing per-update:

type Update { delta: Int; }
type Snapshot { total: Int; }
topic Updates { payload: Update; }
topic Snapshots { payload: Snapshot; }
locus Batcher {
params { pending: Int = 0; acc: Int = 0; }
bus {
subscribe Updates as on_update;
publish Snapshots;
}
fn on_update(u: Update) {
self.pending = self.pending + 1;
self.acc = self.acc + u.delta; // accumulate in place
if self.pending >= 100 { self.flush(); } // volume trigger
}
run() { // time trigger
while !self.draining {
std::time::sleep(1s);
if self.pending > 0 { self.flush(); }
}
}
fn flush() {
Snapshots <- Snapshot { total: self.acc };
self.pending = 0;
}
}

The accumulation is in-place; only the flush crosses the bus. This keeps the high-frequency path allocation-free and bounds publish volume independently of input volume.

The zero-copy APIs (StringView, BytesView, a builder’s .view() / .text_view(), the std::json::*_span cursors) hand you a view into a buffer you don’t own. That view is valid only until the next operation that overwrites the buffer — the next recv, the next ring read. Holding it across that boundary reads bytes that are no longer the ones you looked at:

let name = self.rx_buf.text_view(); // view into the receive buffer
self.read_msg(); // ← refills rx_buf
println(name); // ✗ stale view

The rule: a view is valid until the next recv/overwrite; copy out to persist. Materialize it before the boundary:

let name = std::str::clone(self.rx_buf.text_view());
self.read_msg();
println(name); // ✓ owns its own copy

Rendering a view copies it too: to_string(view), "name=" + view and f"{view}" each produce a String of their own, so any of them is as good a copy as std::str::clone.

A builder’s views are panic-guarded: reading one after its BytesBuilder changed exits with a diagnostic rather than reading garbage — violation: StringView read after source BytesBuilder mutated … — instead of a silent corruption. The fix is always to copy out before the overwriting call.

Every production connection locus converges on the same three fields: buffers held as params, reused every frame, never instantiated in a handler:

locus WsConn {
params {
rx_buf: std::bytes::BytesBuilder = ...; // frame reassembly
tx_buf: std::bytes::BytesBuilder = ...; // send assembly
scratch: std::bytes::BytesBuilder = ...; // unmask / inflate
}
fn on_data(...) {
std::io::tcp::recv_into(self.fd, self.rx_buf, 65536);
// parse from self.rx_buf.view() — zero-copy
}
}

The buffer argument is a std::bytes::BytesBuilder and nothing else — recv_into fills the builder’s tail in place, so a Bytes value or a plain Int is not a smaller version of the same thing. Pass one and hale check says so, at the argument:

`std::io::tcp::recv_into` argument 2: expected
`std::bytes::BytesBuilder`, got `Int`

A builder created inside the handler is a fresh heap buffer per message that reclaims only at method return (the compiler warns). Read with .view() / .text_view() and clear the buffer at the start of the next cycle, not the end of this one, so views handed out stay valid between frames. The full hot-path discipline lives in the styleguide §4 and Performance.

When one event reaches N consumers, render the shared payload once at ingest; each consumer adds only its per-consumer delta:

// ingest: render once
self.update_json = render_update(t); // one render
Tick <- Update { json: self.update_json }; // fan out
// each connection: prepend its own seq only
fn on_update(u: Update) { self.send_frame("" + self.seq + u.json); }

N× a tiny prepend beats N× a full render. Pair it with the two-flavor emitter convention: a std::json::Builder version for cold paths (readable, allocating) and a raw-concat _pre version for the hot fan-out — keeping both documents which callers are hot.

One reader locus per source, parked on readiness — never a poll loop with set_recv_timeout:

locus Reader {
params {
port: Int = 0;
src: std::io::udp::Reader =
std::io::udp::Reader { addr: "127.0.0.1", port: self.port, cap: 2048 };
}
run() {
while !self.draining {
let frame = self.src.next() or raise; // parks on EPOLLIN
// decode `frame`, publish what it says
}
}
}
main locus App {
params { r0: Reader = Reader { port: 9000 }; r1: Reader = Reader { port: 9001 }; }
placement {
r0: cooperative(pool = ingest) where async_io;
r1: cooperative(pool = ingest) where async_io;
}
}
fn main() { App { }; }

Each reader’s next() parks its coroutine on EPOLLIN; N readers share one pool worker with microsecond wakes (measured ~4 µs p50). Poll-scanner sleeps accumulate tail-latency debt that looks like a runtime problem but is the sleep schedule. Blocking I/O that can’t park (a TLS handshake, say) goes on pinned instead — see Concurrency & placement.