Step 1 of the GC effort. Each tier loader now exposes heapStats():
- asm-wasm — lumbda_heap_used / lumbda_heap_total wat exports
- c-wasm — emscripten linear memory size (no free path right now,
so used = total; documented in the loader)
- python — pyodide module linear memory size; CPython GC cycles
this naturally
Worker handles a "heap" message kind that round-trips the active tab's
loaded tiers; repl tabbar shows a compact "py 12M · c 32M · asm 4M"
strip next to the buttons. Polls every 2s.
Doesn't solve the leak — just makes pressure visible so the user knows
when to use "reboot tier". Real GC (Cheney over the WAT bump allocator,
Boehm-em or custom mark-sweep for c-wasm) coming next.
Interactive REPL at lumbda.com/repl with:
- multi-tab sessions (click + to add, × to close, double-click to rename)
- per-tab tier selector (python/c/asm/all-three race)
- persistent transcripts encrypted in localStorage via Web Crypto
(PBKDF2 + AES-GCM, vault id = SHA-256(password || device-salt) —
same pattern as unsandbox's vault-encryption-design.md, native
crypto.subtle API instead of CryptoJS)
- ephemeral mode (skip vault, transcripts vanish on reload)
- one worker per (tab × tier) — state persists across evals in a tab
- reboot tier button (terminate this tab's worker, fresh state next eval)
- cancel button (kills the running worker in active tab)
Home page now links to both /playground/ and /repl/.
Tier state itself does NOT persist across reloads — the transcript does,
but defines/set!/hash-tables vanish with the worker. Portal save/resume
in WAT (deferred) will let a tier session survive close+reopen.
