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Diffstat (limited to 'vendor/unicode-ident/benches/xid.rs')
-rw-r--r-- | vendor/unicode-ident/benches/xid.rs | 124 |
1 files changed, 124 insertions, 0 deletions
diff --git a/vendor/unicode-ident/benches/xid.rs b/vendor/unicode-ident/benches/xid.rs new file mode 100644 index 000000000..040c4e181 --- /dev/null +++ b/vendor/unicode-ident/benches/xid.rs @@ -0,0 +1,124 @@ +// To run: +// +// cargo criterion --features criterion/real_blackbox +// +// This benchmarks each of the different libraries at several ratios of ASCII to +// non-ASCII content. There is one additional benchmark labeled "baseline" which +// just iterates over characters in a string, converting UTF-8 to 32-bit chars. +// +// Criterion will show a time in milliseconds. The non-baseline bench functions +// each make one million function calls (2 calls per character, 500K characters +// in the strings created by gen_string). The "time per call" listed in our +// readme is computed by subtracting this baseline from the other bench +// functions' time, then dividing by one million (ms -> ns). + +#![allow(clippy::needless_pass_by_value)] + +#[path = "../tests/fst/mod.rs"] +mod fst; +#[path = "../tests/roaring/mod.rs"] +mod roaring; +#[path = "../tests/trie/mod.rs"] +mod trie; + +use criterion::{black_box, criterion_group, criterion_main, Criterion}; +use rand::distributions::{Bernoulli, Distribution, Uniform}; +use rand::rngs::SmallRng; +use rand::SeedableRng; +use std::time::Duration; + +fn gen_string(p_nonascii: u32) -> String { + let mut rng = SmallRng::from_seed([b'!'; 32]); + let pick_nonascii = Bernoulli::from_ratio(p_nonascii, 100).unwrap(); + let ascii = Uniform::new_inclusive('\0', '\x7f'); + let nonascii = Uniform::new_inclusive(0x80 as char, char::MAX); + + let mut string = String::new(); + for _ in 0..500_000 { + let distribution = if pick_nonascii.sample(&mut rng) { + nonascii + } else { + ascii + }; + string.push(distribution.sample(&mut rng)); + } + + string +} + +fn bench(c: &mut Criterion, group_name: &str, string: String) { + let mut group = c.benchmark_group(group_name); + group.measurement_time(Duration::from_secs(10)); + group.bench_function("baseline", |b| { + b.iter(|| { + for ch in string.chars() { + black_box(ch); + } + }); + }); + group.bench_function("unicode-ident", |b| { + b.iter(|| { + for ch in string.chars() { + black_box(unicode_ident::is_xid_start(ch)); + black_box(unicode_ident::is_xid_continue(ch)); + } + }); + }); + group.bench_function("unicode-xid", |b| { + b.iter(|| { + for ch in string.chars() { + black_box(unicode_xid::UnicodeXID::is_xid_start(ch)); + black_box(unicode_xid::UnicodeXID::is_xid_continue(ch)); + } + }); + }); + group.bench_function("ucd-trie", |b| { + b.iter(|| { + for ch in string.chars() { + black_box(trie::XID_START.contains_char(ch)); + black_box(trie::XID_CONTINUE.contains_char(ch)); + } + }); + }); + group.bench_function("fst", |b| { + let xid_start_fst = fst::xid_start_fst(); + let xid_continue_fst = fst::xid_continue_fst(); + b.iter(|| { + for ch in string.chars() { + let ch_bytes = (ch as u32).to_be_bytes(); + black_box(xid_start_fst.contains(ch_bytes)); + black_box(xid_continue_fst.contains(ch_bytes)); + } + }); + }); + group.bench_function("roaring", |b| { + let xid_start_bitmap = roaring::xid_start_bitmap(); + let xid_continue_bitmap = roaring::xid_continue_bitmap(); + b.iter(|| { + for ch in string.chars() { + black_box(xid_start_bitmap.contains(ch as u32)); + black_box(xid_continue_bitmap.contains(ch as u32)); + } + }); + }); + group.finish(); +} + +fn bench0(c: &mut Criterion) { + bench(c, "0%-nonascii", gen_string(0)); +} + +fn bench1(c: &mut Criterion) { + bench(c, "1%-nonascii", gen_string(1)); +} + +fn bench10(c: &mut Criterion) { + bench(c, "10%-nonascii", gen_string(10)); +} + +fn bench100(c: &mut Criterion) { + bench(c, "100%-nonascii", gen_string(100)); +} + +criterion_group!(benches, bench0, bench1, bench10, bench100); +criterion_main!(benches); |