fractal/session/model/room/timeline/timeline_item_diff_minimizer/mod.rs
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use std::{
collections::{HashMap, VecDeque},
sync::Arc,
};
use gtk::prelude::*;
use matrix_sdk_ui::{eyeball_im::VectorDiff, timeline::TimelineItem as SdkTimelineItem};
mod tests;
use super::TimelineItem;
use crate::prelude::*;
/// Trait to access data from a type that store `TimelineItem`s.
pub(super) trait TimelineItemStore: Sized {
type Item: IsA<TimelineItem>;
type Data: TimelineItemData;
/// The current list of items.
fn items(&self) -> Vec<Self::Item>;
/// Create a `TimelineItem` with the given `TimelineItemData`.
fn create_item(&self, data: &Self::Data) -> Self::Item;
/// Update the given item with the given timeline ID.
fn update_item(&self, item: &Self::Item, data: &Self::Data);
/// Apply the given list of item diffs to this store.
fn apply_item_diff_list(&self, item_diff_list: Vec<TimelineItemDiff<Self::Item>>);
/// Whether the given diff list can be minimized by calling
/// `minimize_diff_list`.
///
/// It can be minimized if there is more than 1 item in the list and if the
/// list only includes supported `VectorDiff` variants.
fn can_minimize_diff_list(&self, diff_list: &[VectorDiff<Self::Data>]) -> bool {
diff_list.len() > 1
&& !diff_list.iter().any(|diff| {
matches!(
diff,
VectorDiff::Clear | VectorDiff::Truncate { .. } | VectorDiff::Reset { .. }
)
})
}
/// Minimize the given diff list and apply it to this store.
///
/// Panics if the diff list contains unsupported `VectorDiff` variants. This
/// will never panic if `can_minimize_diff_list` returns `true`.
fn minimize_diff_list(&self, diff_list: Vec<VectorDiff<Self::Data>>) {
TimelineItemDiffMinimizer::new(self).apply(diff_list);
}
}
/// Trait implemented by types that provide data for `TimelineItem`s.
pub(super) trait TimelineItemData {
/// The unique timeline ID of the data.
fn timeline_id(&self) -> &str;
}
impl TimelineItemData for SdkTimelineItem {
fn timeline_id(&self) -> &str {
&self.unique_id().0
}
}
impl<T> TimelineItemData for Arc<T>
where
T: TimelineItemData,
{
fn timeline_id(&self) -> &str {
(**self).timeline_id()
}
}
/// A helper struct to minimize a list of `VectorDiff`.
///
/// This does not support `VectorDiff::Clear`, `VectorDiff::Truncate` and
/// `VectorDiff::Reset` as we assume that lists including those cannot be
/// minimized in an optimal way.
struct TimelineItemDiffMinimizer<'a, S, I> {
store: &'a S,
item_map: HashMap<String, I>,
updated_item_ids: Vec<String>,
}
impl<'a, S, I> TimelineItemDiffMinimizer<'a, S, I> {
/// Construct a `TimelineItemDiffMinimizer` with the given store.
fn new(store: &'a S) -> Self {
Self {
store,
item_map: HashMap::new(),
updated_item_ids: Vec::new(),
}
}
}
impl<S, I> TimelineItemDiffMinimizer<'_, S, I>
where
S: TimelineItemStore<Item = I>,
I: IsA<TimelineItem>,
{
/// Load the items from the store.
///
/// Returns the list of timeline IDs of the items.
fn load_items(&mut self) -> Vec<String> {
let items = self.store.items();
let item_ids = items.iter().map(S::Item::timeline_id).collect();
self.item_map
.extend(items.into_iter().map(|item| (item.timeline_id(), item)));
item_ids
}
/// Update or create an item in the store using the given data.
///
/// Returns the timeline ID of the item.
fn update_or_create_item(&mut self, data: &S::Data) -> String {
let timeline_id = data.timeline_id().to_owned();
self.item_map
.entry(timeline_id)
.and_modify(|item| {
self.store.update_item(item, data);
self.updated_item_ids.push(item.timeline_id());
})
.or_insert_with(|| self.store.create_item(data))
.timeline_id()
}
/// Apply the given diff to the given items.
fn apply_diff_to_items(
&mut self,
item_ids: &[String],
diff_list: Vec<VectorDiff<S::Data>>,
) -> Vec<String> {
let mut new_item_ids = VecDeque::from(item_ids.to_owned());
// Get the new state by applying the diffs.
for diff in diff_list {
match diff {
VectorDiff::Append { values } => {
let items = values
.into_iter()
.map(|data| self.update_or_create_item(data));
new_item_ids.extend(items);
}
VectorDiff::PushFront { value } => {
let item = self.update_or_create_item(&value);
new_item_ids.push_front(item);
}
VectorDiff::PushBack { value } => {
let item = self.update_or_create_item(&value);
new_item_ids.push_back(item);
}
VectorDiff::PopFront => {
new_item_ids.pop_front();
}
VectorDiff::PopBack => {
new_item_ids.pop_back();
}
VectorDiff::Insert { index, value } => {
let item = self.update_or_create_item(&value);
new_item_ids.insert(index, item);
}
VectorDiff::Set { index, value } => {
let item_id = self.update_or_create_item(&value);
*new_item_ids
.get_mut(index)
.expect("an item should already exist at the given index") = item_id;
}
VectorDiff::Remove { index } => {
new_item_ids.remove(index);
}
VectorDiff::Clear | VectorDiff::Truncate { .. } | VectorDiff::Reset { .. } => {
unreachable!()
}
}
}
new_item_ids.into()
}
/// Compute the list of item diffs between the two given lists.
///
/// Uses a diff algorithm to minimize the removals and additions.
fn item_diff_list(
&self,
old_item_ids: &[String],
new_item_ids: &[String],
) -> Vec<TimelineItemDiff<S::Item>> {
let mut item_diff_list = Vec::new();
let mut pos = 0;
// Group diffs in batch.
let mut n_removals = 0;
let mut additions = None;
let mut n_updates = 0;
for result in diff::slice(old_item_ids, new_item_ids) {
match result {
diff::Result::Left(_) => {
if let Some(additions) = additions.take() {
let item_diff = SpliceDiff {
pos,
n_removals: 0,
additions,
};
pos += item_diff.additions.len() as u32;
item_diff_list.push(item_diff.into());
} else if n_updates > 0 {
let item_diff = UpdateDiff {
pos,
n_items: n_updates,
};
item_diff_list.push(item_diff.into());
pos += n_updates;
n_updates = 0;
}
n_removals += 1;
}
diff::Result::Both(timeline_id, _) => {
if additions.is_some() || n_removals > 0 {
let item_diff = SpliceDiff {
pos,
n_removals,
additions: additions.take().unwrap_or_default(),
};
pos += item_diff.additions.len() as u32;
item_diff_list.push(item_diff.into());
n_removals = 0;
}
if self.updated_item_ids.contains(timeline_id) {
n_updates += 1;
} else {
if n_updates > 0 {
let item_diff = UpdateDiff {
pos,
n_items: n_updates,
};
item_diff_list.push(item_diff.into());
pos += n_updates;
n_updates = 0;
}
pos += 1;
}
}
diff::Result::Right(timeline_id) => {
if n_updates > 0 {
let item_diff = UpdateDiff {
pos,
n_items: n_updates,
};
item_diff_list.push(item_diff.into());
pos += n_updates;
n_updates = 0;
}
let item = self
.item_map
.get(timeline_id)
.expect("item should exist in map")
.clone();
additions.get_or_insert_with(Vec::new).push(item);
}
}
}
// Process the remaining batches.
if additions.is_some() || n_removals > 0 {
let item_diff = SpliceDiff {
pos,
n_removals,
additions: additions.take().unwrap_or_default(),
};
item_diff_list.push(item_diff.into());
} else if n_updates > 0 {
let item_diff = UpdateDiff {
pos,
n_items: n_updates,
};
item_diff_list.push(item_diff.into());
}
item_diff_list
}
/// Minimize the given diff and apply it to the store.
fn apply(mut self, diff_list: Vec<VectorDiff<S::Data>>) {
let old_item_ids = self.load_items();
let new_item_ids = self.apply_diff_to_items(&old_item_ids, diff_list);
let item_diff_list = self.item_diff_list(&old_item_ids, &new_item_ids);
self.store.apply_item_diff_list(item_diff_list);
}
}
/// A minimized diff for timeline items.
#[derive(Debug, Clone)]
pub(super) enum TimelineItemDiff<T> {
/// Remove then add items.
Splice(SpliceDiff<T>),
/// Update items.
Update(UpdateDiff),
}
impl<T> From<SpliceDiff<T>> for TimelineItemDiff<T> {
fn from(value: SpliceDiff<T>) -> Self {
Self::Splice(value)
}
}
impl<T> From<UpdateDiff> for TimelineItemDiff<T> {
fn from(value: UpdateDiff) -> Self {
Self::Update(value)
}
}
/// A diff to remove then add items.
#[derive(Debug, Clone)]
pub(super) struct SpliceDiff<T> {
/// The position where the change happens
pub(super) pos: u32,
/// The number of items to remove.
pub(super) n_removals: u32,
/// The items to add.
pub(super) additions: Vec<T>,
}
/// A diff to update items.
#[derive(Debug, Clone)]
pub(super) struct UpdateDiff {
/// The position from where to start updating items.
pub(super) pos: u32,
/// The number of items to update.
pub(super) n_items: u32,
}