#![allow(non_snake_case, non_upper_case_globals)] //! This benchmark tests just the overhead of Dioxus itself. //! //! For the JS Framework Benchmark, both the framework and the browser is benchmarked together. Dioxus prepares changes //! to be made, but the change application phase will be just as performant as the vanilla wasm_bindgen code. In essence, //! we are measuring the overhead of Dioxus, not the performance of the "apply" phase. //! //! On my MBP 2019: //! - Dioxus takes 3ms to create 1_000 rows //! - Dioxus takes 30ms to create 10_000 rows //! //! As pure "overhead", these are amazing good numbers, mostly slowed down by hitting the global allocator. //! These numbers don't represent Dioxus with the heuristic engine installed, so I assume it'll be even faster. use criterion::{criterion_group, criterion_main, Criterion}; use dioxus_core as dioxus; use dioxus_core::prelude::*; use dioxus_core_macro::*; use dioxus_html as dioxus_elements; use rand::prelude::*; criterion_group!(mbenches, create_rows); criterion_main!(mbenches); fn create_rows(c: &mut Criterion) { static App: Component<()> = |cx| { let mut rng = SmallRng::from_entropy(); let rows = (0..10_000_usize).map(|f| { let label = Label::new(&mut rng); rsx!(Row { row_id: f, label: label }) }); rsx!(cx, table { tbody { {rows} } }) }; c.bench_function("create rows", |b| { b.iter(|| { let mut dom = VirtualDom::new(App); let g = dom.rebuild(); assert!(g.edits.len() > 1); }) }); } #[derive(PartialEq, Props)] struct RowProps { row_id: usize, label: Label, } fn Row(cx: Scope) -> Element { let [adj, col, noun] = cx.props.label.0; cx.render(rsx! { tr { td { class:"col-md-1", "{cx.props.row_id}" } td { class:"col-md-1", onclick: move |_| { /* run onselect */ } a { class: "lbl", "{adj}" "{col}" "{noun}" } } td { class: "col-md-1" a { class: "remove", onclick: move |_| {/* remove */} span { class: "glyphicon glyphicon-remove remove" aria_hidden: "true" } } } td { class: "col-md-6" } } }) } #[derive(PartialEq)] struct Label([&'static str; 3]); impl Label { fn new(rng: &mut SmallRng) -> Self { Label([ ADJECTIVES.choose(rng).unwrap(), COLOURS.choose(rng).unwrap(), NOUNS.choose(rng).unwrap(), ]) } } static ADJECTIVES: &[&str] = &[ "pretty", "large", "big", "small", "tall", "short", "long", "handsome", "plain", "quaint", "clean", "elegant", "easy", "angry", "crazy", "helpful", "mushy", "odd", "unsightly", "adorable", "important", "inexpensive", "cheap", "expensive", "fancy", ]; static COLOURS: &[&str] = &[ "red", "yellow", "blue", "green", "pink", "brown", "purple", "brown", "white", "black", "orange", ]; static NOUNS: &[&str] = &[ "table", "chair", "house", "bbq", "desk", "car", "pony", "cookie", "sandwich", "burger", "pizza", "mouse", "keyboard", ];