A tight (display ...) loop used to fire one postMessage per display call — main thread couldn't even register click events because the message queue grew faster than it could drain. Fox saw this as "the tab just keeps looping when I leave it" — the tab-switch click never reached setActiveTab so autoPauseTab never fired, and the worker kept running until it finished on its own. Now the worker accumulates chunks into a local string buffer and postMessages a single chunk-batch message when the buffer hits 64KB or 4096 newlines. The 'done'/'error' path drains whatever's left before signalling so the last lines still reach the UI. Main thread handlers (repl + playground) split the batch back into the same text+eol sequence the live streaming row expects. Adds RAF coalescing on the receive side too: attachStreaming now batches DOM textContent / appendChild updates into one requestAnimationFrame tick so the 60 Hz repaint budget is shared across all chunks that landed in that window. finalize() drains the RAF buffer synchronously before the streamed-vs-expected match check so error-on-cancel keeps the most recent lines. |
||
|---|---|---|
| asm | ||
| c | ||
| docs | ||
| examples | ||
| factory | ||
| proof | ||
| quantum | ||
| tests | ||
| wasm | ||
| whitepaper | ||
| www | ||
| .gitignore | ||
| .gitlab-ci.yml | ||
| bench.py | ||
| cl-compat.lsp | ||
| CLAUDE.md | ||
| friction.sh | ||
| lumbda.py | ||
| Makefile | ||
| README.md | ||
| stdlib.lsp | ||
| tests.py | ||
Lumbda
A Lisp/Scheme-derived, just-in-time lambda language. Four implementation tiers with MOAD defect isolation. Workloads migrate across basic UNIX systems.
Four implementation tiers sharing one wire format — Scheme source itself:
- Python bytecode VM — reference, full first-class continuations
- C tree-walker + bytecode VM — portable C, JSON portal
- C + x86_64 JIT — pattern-matched native code, 7–10× faster than CPython
- Pure x86_64 assembly — 22 KB stripped, zero libc, 14 syscalls
Feedback is the primitive across four scopes: continuations within a process, portal files across processes, S-expressions across implementations, TCP sockets across machines.
Home: lumbda.com
λ> (define (fib n)
(let loop ((a 0) (b 1) (i 0))
(if (= i n) a (loop b (+ a b) (+ i 1)))))
λ> (map fib (iota 10))
(0 1 1 2 3 5 8 13 21 34)
Usage
python3 lumbda.py # interactive REPL
python3 lumbda.py script.lsp # run a file
python3 lumbda.py -e '(+ 1 2)' # eval an expression
python3 lumbda.py --fast script.lsp # auto-compile (7-19x faster)
Bytecode compiler
Lumbda includes a stack-based bytecode compiler and VM. Enable it with --fast or (auto-compile! #t):
python3 lumbda.py --fast examples/fibonacci.lsp
(auto-compile! #t)
(define (ack m n)
(cond ((= m 0) (+ n 1))
((= n 0) (ack (- m 1) 1))
(else (ack (- m 1) (ack m (- n 1))))))
(compiled? ack) ; => #t
(ack 3 4) ; => 125
The compiler handles: if, begin, and, or, when, unless, cond, define, set!, lambda, let, named-let, let*, letrec, do, call/cc, function calls with tail-call optimization. Macros are expanded at compile time. 20 specialized opcodes for hot builtins (+, -, *, =, <, car, cdr, cons, null?, etc.) avoid function call overhead.
Features:
- Explicit frame stack — compiled-to-compiled calls don't grow the Python stack
- Full continuations —
call/ccsupports upward continuations; generators work - Constant folding —
(+ 1 2)folds to3at compile time - Peephole optimizer — eliminates dead code (VOID+POP, JUMP-to-next)
(disassemble proc)— inspect generated bytecode
What's implemented
Core language
- Full lexical scoping and closures
- Tail-call optimization (TCO) — deep recursion never blows the stack
- Hygienic macros via
syntax-ruleswith ellipsis (...) support define-macro/defmacrofor procedural macroscall/cc— full continuations (escape + upward) in compiled codevalues/call-with-valuesdynamic-wind,guard,with-exception-handlerquasiquote/unquote/unquote-splicingwith proper nesting- R7RS internal defines with letrec* body semantics
- R7RS error objects
- Exact rational arithmetic —
(/ 1 3)→1/3,(+ 1/4 3/4)→1 - String ports —
open-input-stringopen-output-stringreadon ports - Mutable strings —
string-set!string-fill!string-copy! - Module system —
module/importwith export lists define-record-typewith(inherit parent)for single-inheritance- Pretty-print —
pp/pretty-print - Tracing —
(trace fn)/(untrace fn)
Special forms
define set! lambda λ if cond case and or when unless
begin let let* letrec letrec* named-let do
quasiquote define-macro define-syntax syntax-rules
let-syntax letrec-syntax apply eval values call/cc
dynamic-wind guard parameterize load error
module import define-record-type
Built-ins
- Arithmetic:
+-*/quotientremaindermoduloexptsqrtabsfloorceilingroundtruncateminmaxgcdlcmlogexptrig functions,numeratordenominator - Rationals:
(/ 1 3)→1/3, literal1/3syntax,exact/inexactconversion - Comparison:
=<><=>=zero?positive?negative?odd?even? - Pairs & lists:
conscarcdrlistlengthappendreversemapfor-eachfilterfold-leftfold-rightreduceanyeverysortpartitionfindtakedropzipflattenand more - SRFI-1:
lastfirst–fifthdeletelset-unionlset-intersectionlset-differenceunfoldlist-tabulate - Strings:
string-lengthstring-refstring-set!substringstring-appendstring-copystring-copy!string-fill!string->liststring->numberformatand more - Characters:
char->integerinteger->charchar-alphabetic?char-upcasechar-downcase - Vectors:
make-vectorvectorvector-refvector-set!vector-copyvector-copy! - Hash tables:
make-hash-tablehash-table-set!hash-table-refhash-table-keyshash-table-valueshash-table-walkand more - I/O:
displaywritenewlinereadread-charread-lineopen-input-stringopen-output-stringwith-output-to-string - File system:
file-exists?delete-filerename-filedirectory-filescurrent-directory - System:
command-lineget-environment-variablecurrent-timeexit - Python interop:
py-evalpy-execpy-importpy-callpy-attr - Compiler:
compilecompiled?disassembleauto-compile!
Standard library (stdlib.lsp)
Additional macros, string/list/numeric/tree utilities, alist/hash helpers, simple object system, SRFI-2/8/64 test framework.
Examples
python3 lumbda.py --fast examples/fibonacci.lsp
python3 lumbda.py --fast examples/generator.lsp
python3 lumbda.py --fast examples/mergesort.lsp
python3 lumbda.py examples/objects.lsp
;; Generator using full continuations
(auto-compile! #t)
(define (make-gen thunk)
(let ((k #f) (done #f))
(lambda ()
(if done 'done
(call/cc (lambda (return)
(if k (k return)
(begin (thunk (lambda (val)
(call/cc (lambda (next)
(set! k next) (return val)))))
(set! done #t) (return 'done)))))))))
(define counter (make-gen (lambda (yield)
(let loop ((i 0)) (yield i) (loop (+ i 1))))))
(counter) ; => 0
(counter) ; => 1
(counter) ; => 2
Running tests & benchmarks
make test # run 529 tests
make test-verbose # verbose output
make bench # compare interpreter vs bytecode vs CPython
make lint # syntax check all Python files
Portal — machine state migration
Serialize a running VM mid-computation, transfer to another machine, resume:
# Machine A: start a long computation with checkpoints
python3 lumbda.py --fast examples/portal-prime.lsp
# saves prime-state.portal at checkpoint
# Machine B: resume from checkpoint
python3 lumbda.py --portal-resume prime-state.portal
# continues from exact instruction
The portal captures the full env chain, compiled procedures, continuations, and frame stack as JSON. 16KB for a primality test in progress.
EML universality proof
The proof/ directory contains a formal verification that eml(x,y) = exp(x) - ln(y)
with constant 1 generates all elementary functions (arXiv:2603.21852v2).
Three approaches, benchmarked:
| Approach | Time | Guarantee |
|---|---|---|
| Python (numerical) | 0.04s | 1e-10 tolerance |
| Lumbda (numerical) | 59s | 1e-10 tolerance |
| Lean 4 (formal proof) | 1.5s | kernel-verified |
The formal proof is 40x faster than brute-force search with infinitely stronger
guarantees. See proof/benchmark_results.md for the full analysis — including
why this is MOAD-0001 (the sedimentary defect) at the proof methodology layer.
File layout
lumbda.py interpreter + bytecode compiler (one file, ~3200 lines)
stdlib.lsp extended standard library
tests.py test suite (571 tests)
bench.py benchmarks vs CPython
examples/ example programs
proof/ EML universality proof (Python, Scheme, Lean 4)
Makefile make test / make bench / make repl