Word frequency

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

Compile time · median (cold)

median of 7 runs

Native Gocompiled

108 ms61.2×

Pipitbytecode VM

1.76 msbaseline

CPython 3.14bytecode VM

565 µs0.32×

PyPy 7.3tracing JIT

412 µs0.23×

Ttengobytecode VM

429 µs0.24×

Sscriggobytecode VM

735 µs0.42×

Mmvmbytecode VM

555 µs0.31×

YyaegiAST walker

516 µs0.29×

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	61.2×	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	0.32×	OK
PyPy 7.3tracing JIT	7	412 µs	50.7 ms	54.1 ms	3.36 ms	n/a	0.23×	OK
tengobytecode VM	7	429 µs	930 ms	986 ms	27.9 ms	190 MiB	0.24×	OK
scriggobytecode VM	7	735 µs	444 ms	475 ms	18.8 ms	109 MiB	0.42×	OK
mvmbytecode VM	7	555 µs	631 ms	665 ms	19.2 ms	191 MiB	0.31×	OK
yaegiAST walker	7	516 µs	442 ms	492 ms	20.7 ms	109 MiB	0.29×	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