russell@unturf.com
f584ad76f2
- auto-compile! parameter: compile defines on the fly for zero-effort speedup - VM optimization: local aliases, inlined truthiness checks (~15% faster) - disassemble builtin: human-readable bytecode listing - call/cc compiled natively in VM (escape-only, no longer falls back to eval) - Makefile: add lint, bench-verbose, clean targets - 518 tests green
449 lines
14 KiB
Python
449 lines
14 KiB
Python
#!/usr/bin/env python3
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"""
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bench.py — benchmarks for uncommonlisp.
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Compares interpreter time against equivalent CPython.
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Usage: python3 bench.py [-v]
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"""
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import sys, time, math
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sys.setrecursionlimit(10000)
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from uncommonlisp import make_global_env, read_all, leval, PRELUDE, show, bc_compile_proc, Proc
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VERBOSE = '-v' in sys.argv
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def fresh():
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g = make_global_env()
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for e in read_all(PRELUDE): leval(e, g)
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return g
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def run(src, env):
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result = None
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for e in read_all(src): result = leval(e, env)
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return result
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def bench(name, lisp_src, python_fn, iters=3):
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"""Time both lisp and python implementations; print results."""
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env = fresh()
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# Warm up
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run(lisp_src, env)
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python_fn()
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# Time Lisp
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lisp_times = []
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for _ in range(iters):
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env2 = fresh()
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t = time.perf_counter()
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result = run(lisp_src, env2)
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lisp_times.append(time.perf_counter() - t)
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lisp_best = min(lisp_times)
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# Time Python
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py_times = []
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for _ in range(iters):
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t = time.perf_counter()
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py_result = python_fn()
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py_times.append(time.perf_counter() - t)
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py_best = min(py_times)
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slowdown = lisp_best / py_best if py_best > 0 else float('inf')
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status = '✓' if result == py_result or str(result) == str(py_result) else '✗'
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print(f'{status} {name:<30} lisp={lisp_best*1000:7.1f}ms py={py_best*1000:7.1f}ms '
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f'ratio={slowdown:5.1f}x')
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if VERBOSE:
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print(f' lisp result: {show(result)!r}')
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print(f' py result: {py_result!r}')
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return lisp_best, py_best
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print('uncommonlisp benchmarks')
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print('=' * 75)
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# ── 1. Fibonacci (iterative, named let) ──────────────────────────────────────
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bench(
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'fib(35) named-let',
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'''
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(define (fib n)
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(let loop ((a 0) (b 1) (i 0))
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(if (= i n) a (loop b (+ a b) (+ i 1)))))
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(fib 35)
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''',
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lambda: (lambda a=0, b=1, i=0, n=35:
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[setattr(sys.modules[__name__], '_fib', None)] and
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(lambda: exec('''
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def _fib(n):
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a, b = 0, 1
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for _ in range(n): a, b = b, a+b
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return a
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''', globals()) or _fib(35))())()
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)
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# Simpler lambda-based benchmark
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def py_fib(n=35):
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a, b = 0, 1
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for _ in range(n): a, b = b, a + b
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return a
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bench(
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'fib(35) iterative',
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'''
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(define (fib n)
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(let loop ((a 0) (b 1) (i 0))
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(if (= i n) a (loop b (+ a b) (+ i 1)))))
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(fib 35)
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''',
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lambda: py_fib(35)
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)
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# ── 2. fib(20) tree-recursive ─────────────────────────────────────────────────
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def py_fib_rec(n):
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if n <= 1: return n
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return py_fib_rec(n-1) + py_fib_rec(n-2)
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bench(
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'fib(20) tree-recursive',
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'''
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(define (fib n)
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(if (<= n 1) n (+ (fib (- n 1)) (fib (- n 2)))))
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(fib 20)
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''',
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lambda: py_fib_rec(20)
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)
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# ── 3. Tak function ───────────────────────────────────────────────────────────
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def py_tak(x, y, z):
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if y >= x: return z
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return py_tak(py_tak(x-1,y,z), py_tak(y-1,z,x), py_tak(z-1,x,y))
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bench(
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'tak(15,10,6)',
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'''
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(define (tak x y z)
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(if (>= y x) z
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(tak (tak (- x 1) y z)
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(tak (- y 1) z x)
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(tak (- z 1) x y))))
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(tak 15 10 6)
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''',
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lambda: py_tak(15, 10, 6)
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)
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# ── 4. Tail-recursive sum ─────────────────────────────────────────────────────
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def py_sum(n):
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acc = 0
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while n > 0: acc += n; n -= 1
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return acc
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bench(
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'sum-to(50000) tail-recursive',
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'''
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(define (sum-to n)
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(let loop ((i n) (acc 0))
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(if (= i 0) acc (loop (- i 1) (+ acc i)))))
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(sum-to 50000)
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''',
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lambda: py_sum(50000)
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)
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# ── 5. List operations ────────────────────────────────────────────────────────
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def py_list_ops():
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lst = list(range(5000))
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lst = list(reversed(lst))
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lst = [x for x in lst if x % 2 == 1]
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lst = [x * x for x in lst]
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return sum(lst)
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bench(
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'list ops (5000 elements)',
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'''
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(define lst (iota 5000))
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(define lst (reverse lst))
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(define lst (filter odd? lst))
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(define lst (map (lambda (x) (* x x)) lst))
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(fold-left + 0 lst)
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''',
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py_list_ops
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)
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# ── 6. Higher-order / closures ────────────────────────────────────────────────
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def py_adder_factory():
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adders = [(lambda n: lambda x: x + n)(i) for i in range(100)]
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return sum(f(10) for f in adders)
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bench(
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'closure factory (100 adders)',
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'''
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(define (make-adder n) (lambda (x) (+ x n)))
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(define adders (map make-adder (iota 100)))
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(fold-left + 0 (map (lambda (f) (f 10)) adders))
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''',
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py_adder_factory
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)
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# ── 7. Hash table ─────────────────────────────────────────────────────────────
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def py_hash_ops():
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h = {}
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for i in range(1000):
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h[i] = i * i
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return sum(h.get(i, 0) for i in range(1000))
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bench(
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'hash-table (1000 set+ref)',
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'''
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(define h (make-hash-table))
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(do ((i 0 (+ i 1))) ((= i 1000))
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(hash-table-set! h i (* i i)))
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(do ((i 0 (+ i 1)) (s 0 (+ s (hash-table-ref/default h i 0))))
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((= i 1000) s))
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''',
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py_hash_ops
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)
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# ── 8. String operations ──────────────────────────────────────────────────────
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def py_string_ops():
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parts = [str(i) for i in range(200)]
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joined = ', '.join(parts)
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return len(joined)
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bench(
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'string-join (200 numbers)',
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'''
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(string-length
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(string-join (map number->string (iota 200)) ", "))
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''',
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py_string_ops
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)
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# ── 9. Ackermann (small) ─────────────────────────────────────────────────────
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def py_ack(m, n):
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if m == 0: return n + 1
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if n == 0: return py_ack(m-1, 1)
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return py_ack(m-1, py_ack(m, n-1))
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bench(
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'ackermann(3,4)',
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'''
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(define (ack m n)
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(cond ((= m 0) (+ n 1))
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((= n 0) (ack (- m 1) 1))
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(else (ack (- m 1) (ack m (- n 1))))))
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(ack 3 4)
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''',
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lambda: py_ack(3, 4)
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)
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# ── 10. Mergesort ─────────────────────────────────────────────────────────────
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def py_msort(lst):
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if len(lst) <= 1: return lst
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mid = len(lst) // 2
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L = py_msort(lst[:mid]); R = py_msort(lst[mid:])
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result = []; i = j = 0
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while i < len(L) and j < len(R):
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if L[i] <= R[j]: result.append(L[i]); i += 1
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else: result.append(R[j]); j += 1
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return result + L[i:] + R[j:]
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bench(
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'mergesort (200 elements)',
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'''
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(define (merge a b)
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(cond ((null? a) b) ((null? b) a)
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((< (car a) (car b)) (cons (car a) (merge (cdr a) b)))
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(else (cons (car b) (merge a (cdr b))))))
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(define (split lst)
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(let loop ((l lst) (a (quote ())) (b (quote ())))
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(if (null? l) (list a b) (loop (cdr l) b (cons (car l) a)))))
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(define (msort lst)
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(if (or (null? lst) (null? (cdr lst))) lst
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(let ((h (split lst)))
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(merge (msort (car h)) (msort (cadr h))))))
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(length (msort (reverse (iota 200))))
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''',
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lambda: len(py_msort(list(range(199, -1, -1))))
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)
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print('=' * 75)
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print('ratio = lisp time / python time (lower is better for lisp)')
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# ═══════════════════════════════════════════════════════════════════════════
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# Compiled (bytecode) benchmarks
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# ═══════════════════════════════════════════════════════════════════════════
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print()
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print('COMPILED (bytecode) benchmarks')
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print('=' * 75)
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def compile_env(env):
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"""Compile all user-defined Procs in env."""
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for k, v in list(env.b.items()):
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if isinstance(v, Proc):
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env.b[k] = bc_compile_proc(v, env)
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def bench_compiled(name, lisp_src, python_fn, iters=3):
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"""Time compiled lisp vs python. Separates definition from invocation."""
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# Parse all expressions; everything except the last is setup (defines)
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exprs = read_all(lisp_src)
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setup_exprs = exprs[:-1]
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call_expr = exprs[-1]
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lisp_times = []
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for _ in range(iters):
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env = fresh()
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for e in setup_exprs: leval(e, env)
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compile_env(env)
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t = time.perf_counter()
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result = leval(call_expr, env)
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lisp_times.append(time.perf_counter() - t)
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lisp_best = min(lisp_times)
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py_times = []
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for _ in range(iters):
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t = time.perf_counter()
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py_result = python_fn()
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py_times.append(time.perf_counter() - t)
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py_best = min(py_times)
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slowdown = lisp_best / py_best if py_best > 0 else float('inf')
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status = '✓' if result == py_result or str(result) == str(py_result) else '✗'
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print(f'{status} {name:<30} bc={lisp_best*1000:7.1f}ms py={py_best*1000:7.1f}ms '
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f'ratio={slowdown:5.1f}x')
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return lisp_best, py_best
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bench_compiled('fib(35) iterative', '''
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(define (fib n)
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(let loop ((a 0) (b 1) (i 0))
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(if (= i n) a (loop b (+ a b) (+ i 1)))))
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(fib 35)
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''', lambda: py_fib(35))
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bench_compiled('fib(20) tree-recursive', '''
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(define (fib n)
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(if (<= n 1) n (+ (fib (- n 1)) (fib (- n 2)))))
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(fib 20)
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''', lambda: py_fib_rec(20))
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bench_compiled('tak(15,10,6)', '''
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(define (tak x y z)
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(if (>= y x) z
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(tak (tak (- x 1) y z)
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(tak (- y 1) z x)
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(tak (- z 1) x y))))
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(tak 15 10 6)
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''', lambda: py_tak(15, 10, 6))
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bench_compiled('sum-to(50000) tail-recursive', '''
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(define (sum-to n)
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(let loop ((i n) (acc 0))
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(if (= i 0) acc (loop (- i 1) (+ acc i)))))
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(sum-to 50000)
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''', lambda: py_sum(50000))
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bench_compiled('list ops (5000 elements)', '''
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(define lst (iota 5000))
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(define lst (reverse lst))
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(define lst (filter odd? lst))
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(define lst (map (lambda (x) (* x x)) lst))
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(fold-left + 0 lst)
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''', py_list_ops)
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bench_compiled('hash-table (1000 set+ref)', '''
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(define h (make-hash-table))
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(do ((i 0 (+ i 1))) ((= i 1000))
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(hash-table-set! h i (* i i)))
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(do ((i 0 (+ i 1)) (s 0 (+ s (hash-table-ref/default h i 0))))
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((= i 1000) s))
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''', py_hash_ops)
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bench_compiled('ackermann(3,4)', '''
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(define (ack m n)
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(cond ((= m 0) (+ n 1))
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((= n 0) (ack (- m 1) 1))
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(else (ack (- m 1) (ack m (- n 1))))))
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(ack 3 4)
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''', lambda: py_ack(3, 4))
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bench_compiled('mergesort (200 elements)', '''
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(define (merge a b)
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(cond ((null? a) b) ((null? b) a)
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((< (car a) (car b)) (cons (car a) (merge (cdr a) b)))
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(else (cons (car b) (merge a (cdr b))))))
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(define (split lst)
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(let loop ((l lst) (a (quote ())) (b (quote ())))
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(if (null? l) (list a b) (loop (cdr l) b (cons (car l) a)))))
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(define (msort lst)
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(if (or (null? lst) (null? (cdr lst))) lst
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(let ((h (split lst)))
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(merge (msort (car h)) (msort (cadr h))))))
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(length (msort (reverse (iota 200))))
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''', lambda: len(py_msort(list(range(199, -1, -1)))))
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print('=' * 75)
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print('ratio = compiled time / python time (lower is better)')
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# ═══════════════════════════════════════════════════════════════════════════
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# Auto-compile mode (zero-effort: just define and go)
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# ═══════════════════════════════════════════════════════════════════════════
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print()
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print('AUTO-COMPILE mode (auto-compile! #t)')
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print('=' * 75)
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from uncommonlisp import _auto_compile
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def bench_auto(name, lisp_src, python_fn, iters=3):
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"""Time auto-compiled lisp vs python. Defines + runs in one pass."""
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exprs = read_all(lisp_src)
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lisp_times = []
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for _ in range(iters):
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env = fresh()
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_auto_compile[0] = True
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for e in exprs[:-1]: leval(e, env)
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t = time.perf_counter()
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result = leval(exprs[-1], env)
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lisp_times.append(time.perf_counter() - t)
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_auto_compile[0] = False
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lisp_best = min(lisp_times)
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py_times = []
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for _ in range(iters):
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t = time.perf_counter()
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py_result = python_fn()
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py_times.append(time.perf_counter() - t)
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py_best = min(py_times)
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slowdown = lisp_best / py_best if py_best > 0 else float('inf')
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status = '✓' if result == py_result or str(result) == str(py_result) else '✗'
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print(f'{status} {name:<30} auto={lisp_best*1000:6.1f}ms py={py_best*1000:6.1f}ms '
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f'ratio={slowdown:5.1f}x')
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return lisp_best, py_best
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bench_auto('fib(35) iterative', '''
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(define (fib n)
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(let loop ((a 0) (b 1) (i 0))
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(if (= i n) a (loop b (+ a b) (+ i 1)))))
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(fib 35)
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''', lambda: py_fib(35))
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bench_auto('fib(20) tree-recursive', '''
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(define (fib n)
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(if (<= n 1) n (+ (fib (- n 1)) (fib (- n 2)))))
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(fib 20)
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''', lambda: py_fib_rec(20))
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bench_auto('sum-to(50000) tail-recursive', '''
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(define (sum-to n)
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(let loop ((i n) (acc 0))
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(if (= i 0) acc (loop (- i 1) (+ acc i)))))
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(sum-to 50000)
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''', lambda: py_sum(50000))
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bench_auto('ackermann(3,4)', '''
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(define (ack m n)
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(cond ((= m 0) (+ n 1))
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((= n 0) (ack (- m 1) 1))
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(else (ack (- m 1) (ack m (- n 1))))))
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(ack 3 4)
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''', lambda: py_ack(3, 4))
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print('=' * 75)
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