pyo3/benches/bench_set.rs

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use criterion::{criterion_group, criterion_main, Bencher, Criterion};
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use pyo3::prelude::*;
use pyo3::types::PySet;
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use std::collections::{BTreeSet, HashSet};
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fn set_new(b: &mut Bencher<'_>) {
Python::with_gil(|py| {
const LEN: usize = 100_000;
// Create Python objects up-front, so that the benchmark doesn't need to include
// the cost of allocating LEN Python integers
let elements: Vec<PyObject> = (0..LEN).into_iter().map(|i| i.into_py(py)).collect();
b.iter(|| {
let pool = unsafe { py.new_pool() };
PySet::new(py, &elements).unwrap();
drop(pool);
});
});
}
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fn iter_set(b: &mut Bencher<'_>) {
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Python::with_gil(|py| {
const LEN: usize = 100_000;
let set = PySet::new(py, &(0..LEN).collect::<Vec<_>>()).unwrap();
let mut sum = 0;
b.iter(|| {
for x in set.iter() {
let i: u64 = x.extract().unwrap();
sum += i;
}
});
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});
}
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fn extract_hashset(b: &mut Bencher<'_>) {
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Python::with_gil(|py| {
const LEN: usize = 100_000;
let set = PySet::new(py, &(0..LEN).collect::<Vec<_>>()).unwrap();
b.iter(|| HashSet::<u64>::extract(set));
});
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}
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fn extract_btreeset(b: &mut Bencher<'_>) {
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Python::with_gil(|py| {
const LEN: usize = 100_000;
let set = PySet::new(py, &(0..LEN).collect::<Vec<_>>()).unwrap();
b.iter(|| BTreeSet::<u64>::extract(set));
});
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}
#[cfg(feature = "hashbrown")]
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fn extract_hashbrown_set(b: &mut Bencher<'_>) {
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Python::with_gil(|py| {
const LEN: usize = 100_000;
let set = PySet::new(py, &(0..LEN).collect::<Vec<_>>()).unwrap();
b.iter(|| hashbrown::HashSet::<u64>::extract(set));
});
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}
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fn criterion_benchmark(c: &mut Criterion) {
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c.bench_function("set_new", set_new);
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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);