Word frequency

Tokenise a 1 MiB ASCII corpus and count word occurrences into a hash map.

Runtime · median per inner-loop window

median of 7 runs

Native Gocompiled

19.1 ms0.15×

Pipitbytecode VM

131 msbaseline

CPython 3.14bytecode VM

289 ms2.20×

PyPy 7.3tracing JIT

50.7 ms0.39×

Ttengobytecode VM

930 ms7.07×

Sscriggobytecode VM

444 ms3.38×

Mmvmbytecode VM

631 ms4.80×

YyaegiAST walker

442 ms3.36×

Runner	N	Compile	Runtime	P95	Stddev	RSS	vs pipit	Status
Native Gocompiled	7	108 ms	19.1 ms	19.4 ms	200 µs	125 MiB	0.15×	OK
Pipitbytecode VM	7	1.76 ms	131 ms	173 ms	15.6 ms	98 MiB	1.00×	OK
CPython 3.14bytecode VM	7	565 µs	289 ms	299 ms	3.66 ms	n/a	2.20×	OK
PyPy 7.3tracing JIT	7	412 µs	50.7 ms	54.1 ms	3.36 ms	n/a	0.39×	OK
tengobytecode VM	7	429 µs	930 ms	986 ms	27.9 ms	190 MiB	7.07×	OK
scriggobytecode VM	7	735 µs	444 ms	475 ms	18.8 ms	109 MiB	3.38×	OK
mvmbytecode VM	7	555 µs	631 ms	665 ms	19.2 ms	191 MiB	4.80×	OK
yaegiAST walker	7	516 µs	442 ms	492 ms	20.7 ms	109 MiB	3.36×	OK

Workload & symmetry rules

Workload

Read a 1 MiB lorem corpus. Tokenise on whitespace + ASCII punctuation. Count occurrences in a map. Print the top-10 by frequency.

Source code