"""Auto-generated example: 0 Float, 1 Categorical (no repeats)."""
import bencher as bn
class CacheBackend(bn.ParametrizedSweep):
"""Compares latency across different cache backends."""
backend = bn.StringSweep(["redis", "memcached", "local"], doc="Cache backend")
latency = bn.ResultFloat(units="ms", doc="Cache lookup latency")
def benchmark(self):
base = {"redis": 1.2, "memcached": 1.5, "local": 0.3}[self.backend]
self.latency = base
def example_sweep_0_float_1_cat_no_repeats(run_cfg: bn.BenchRunCfg | None = None) -> bn.Bench:
"""0 Float, 1 Categorical (no repeats)."""
bench = CacheBackend().to_bench(run_cfg)
bench.plot_sweep(input_vars=['backend'], result_vars=['latency'], description='A 0 float + 1 categorical parameter sweep with a single sample per combination. Bencher calculates the Cartesian product of all input variables and evaluates the benchmark function at each point. With no repeats, each combination appears exactly once -- useful for deterministic functions or quick exploration before committing to longer runs. Categorical-only sweeps produce bar/swarm plots comparing discrete settings.', post_description='Each tab shows a different view of the same data: interactive plots, tabular summaries, and raw data. Use the tabs to explore the sweep results from different angles.')
return bench
if __name__ == "__main__":
bn.run(example_sweep_0_float_1_cat_no_repeats, subsampling_divisions=4)