Introduction¶

Simple microbenchmarking of Python snippets, powered by Google Benchmark.

mew is a small Python library and CLI for writing microbenchmarks the way you write tests. Decorate a function, run mew, get reliable timings — backed by Google Benchmark, built with nanobind.

import mew


@mew.benchmark
def bench_sorted(state: mew.State) -> None:
    data = list(range(1000, 0, -1))
    for _ in state:
        sorted(data)

$ mew run
mew · host=laptop cpus=10 @ 3200MHz scaling=enabled
Benchmark                              │       Iters │           Real │            CPU
─────────────────────────────────────────────────────────────────────────────────────
benchmarks/bench_sort.py::bench_sorted │   1,000,000 │      32.10 ns │      32.05 ns

At a glance¶

Decorate

@mew.benchmark, @mew.parametrize, @mew.product — register one benchmark or a family.

Writing benchmarks

Run

mew run discovers bench_*.py files, runs them with Google Benchmark, and streams results to the terminal, JSON, or Parquet.

Command-line interface

Profile

--sample for pyinstrument CPU sampling, --profile-memory for memray allocations, or mew profile for native C frames via Instruments / py-spy / perf.

CPU profiling

Compare

mew compare baseline.json head.json --fail-on-regression 5 for CI regression gates with an allowlist.

Comparisons and regression gating

Table of Contents¶

Getting started

User guide

Reference

Development