use criterion::{criterion_group, criterion_main, Bencher, Criterion}; use pyo3::prelude::*; use pyo3::types::PySet; use std::collections::{BTreeSet, HashSet}; fn iter_set(b: &mut Bencher) { let gil = Python::acquire_gil(); let py = gil.python(); const LEN: usize = 100_000; let set = PySet::new(py, &(0..LEN).collect::>()).unwrap(); let mut sum = 0; b.iter(|| { for x in set.iter() { let i: u64 = x.extract().unwrap(); sum += i; } }); } fn extract_hashset(b: &mut Bencher) { let gil = Python::acquire_gil(); let py = gil.python(); const LEN: usize = 100_000; let set = PySet::new(py, &(0..LEN).collect::>()).unwrap(); b.iter(|| HashSet::::extract(set)); } fn extract_btreeset(b: &mut Bencher) { let gil = Python::acquire_gil(); let py = gil.python(); const LEN: usize = 100_000; let set = PySet::new(py, &(0..LEN).collect::>()).unwrap(); b.iter(|| BTreeSet::::extract(set)); } #[cfg(feature = "hashbrown")] fn extract_hashbrown_set(b: &mut Bencher) { let gil = Python::acquire_gil(); let py = gil.python(); const LEN: usize = 100_000; let set = PySet::new(py, &(0..LEN).collect::>()).unwrap(); b.iter(|| hashbrown::HashSet::::extract(set)); } fn criterion_benchmark(c: &mut Criterion) { c.bench_function("iter_set", iter_set); c.bench_function("extract_hashset", extract_hashset); c.bench_function("extract_btreeset", extract_btreeset); #[cfg(feature = "hashbrown")] c.bench_function("extract_hashbrown_set", extract_hashbrown_set); } criterion_group!(benches, criterion_benchmark); criterion_main!(benches);