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