feat(stats): add v1 immersion stats dashboard (#19)

This commit is contained in:
2026-03-20 02:43:28 -07:00
committed by GitHub
parent 42abdd1268
commit 6749ff843c
555 changed files with 46356 additions and 2553 deletions

View File

@@ -0,0 +1,283 @@
# Renderer Performance Optimizations
**Date:** 2026-03-15
**Status:** Draft
## Goal
Minimize the time between a subtitle line appearing and annotations being displayed. Three optimizations target different pipeline stages to achieve this.
## Current Pipeline (Warm State)
```text
MPV subtitle change (0ms)
-> IPC to main (5ms)
-> Cache check (2ms)
-> [CACHE MISS] Yomitan parser (35-180ms)
-> Parallel: MeCab enrichment (20-80ms) + Frequency lookup (15-50ms)
-> Annotation stage: 4 sequential passes (25-70ms)
-> IPC to renderer (10ms)
-> DOM render: createElement per token (15-50ms)
─────────────────────────────────
Total: ~200-320ms (cache miss)
Total: ~72ms (cache hit)
```
## Target Pipeline
```text
MPV subtitle change (0ms)
-> IPC to main (5ms)
-> Cache check (2ms)
-> [CACHE HIT via prefetch] (0ms)
-> IPC to renderer (10ms)
-> DOM render: cloneNode from template (10-30ms)
─────────────────────────────────
Total: ~30-50ms (prefetch-warmed, normal playback)
[CACHE MISS, e.g. immediate seek]
-> Yomitan parser (35-180ms)
-> Parallel: MeCab enrichment + Frequency lookup
-> Annotation stage: 1 batched pass (10-25ms)
-> IPC to renderer (10ms)
-> DOM render: cloneNode from template (10-30ms)
─────────────────────────────────
Total: ~150-260ms (cache miss, still improved)
```
---
## Optimization 1: Subtitle Prefetching
### Summary
A new `SubtitlePrefetchService` parses external subtitle files and tokenizes upcoming lines in the background before they appear on screen. This converts most cache misses into cache hits during normal playback.
### Scope
External subtitle files only (SRT, VTT, ASS). Embedded subtitle tracks are out of scope since Japanese subtitles are virtually always external files.
### Architecture
#### Subtitle File Parsing
A new cue parser that extracts both timing and text content from subtitle files. The existing `parseSrtOrVttStartTimes` in `subtitle-delay-shift.ts` only extracts timing; this needs a companion that also extracts the dialogue text.
**Parsed cue structure:**
```typescript
interface SubtitleCue {
startTime: number; // seconds
endTime: number; // seconds
text: string; // raw subtitle text
}
```
**Supported formats:**
- SRT/VTT: Regex-based parsing of timing lines + text content between timing blocks.
- ASS: Parse `[Events]` section, extract `Dialogue:` lines, split on the first 9 commas only (ASS v4+ has 10 fields; the last field is Text which can itself contain commas). Strip ASS override tags (`{\...}`) from the text before storing.
ASS text fields contain inline override tags like `{\b1}`, `{\an8}`, `{\fad(200,300)}`. The cue parser strips these during extraction so the tokenizer receives clean text.
#### Prefetch Service Lifecycle
1. **Activation trigger:** When a subtitle track is activated (or changes), check if it's external via MPV's `track-list` property. If `external === true`, read the file via `external-filename` using the existing `loadSubtitleSourceText` infrastructure.
2. **Parse phase:** Parse all cues from the file content. Sort by start time. Store as an ordered array.
3. **Priority window:** Determine the current playback position. Identify the next 10 cues as the priority window.
4. **Priority tokenization:** Tokenize the priority window cues sequentially, storing results into the `SubtitleProcessingController`'s tokenization cache.
5. **Background tokenization:** After the priority window is done, tokenize remaining cues working forward from the current position, then wrapping around to cover earlier cues. The prefetcher stops once it has tokenized all cues or the cache is full (whichever comes first) to avoid wasteful eviction churn. For files with more cues than the cache limit, background tokenization focuses on cues ahead of the current position.
6. **Seek handling:** On seek, re-compute the priority window from the new position. A seek is detected by observing MPV's `time-pos` property and checking if the delta from the last observed position exceeds a threshold (e.g., > 3 seconds forward or any backward jump). The current in-flight tokenization finishes naturally, then the new priority window takes over.
7. **Teardown:** When the subtitle track changes or playback ends, stop all prefetch work and discard state.
#### Live Priority
The prefetcher and live subtitle handler share the Yomitan parser (single-threaded IPC). Live subtitle requests must always take priority. The prefetcher:
- Checks a `paused` flag before each cue tokenization. The live handler sets `paused = true` on subtitle change and clears it after emission.
- Yields between each background cue tokenization (via `setTimeout(0)` or equivalent) so the live handler can set the pause flag between cues.
- When paused, the prefetcher waits (polling the flag on a short interval or awaiting a resume signal) before continuing with the next cue.
#### Cache Integration
The prefetcher calls the same `tokenizeSubtitle` function used by live processing to produce `SubtitleData` results, then stores them into the existing `SubtitleProcessingController` tokenization cache via a new method:
```typescript
// New methods on SubtitleProcessingController
preCacheTokenization: (text: string, data: SubtitleData) => void;
isCacheFull: () => boolean;
```
`preCacheTokenization` uses the same `setCachedTokenization` logic internally (LRU eviction, Map-based storage). `isCacheFull` returns `true` when the cache has reached its limit, allowing the prefetcher to stop background tokenization and avoid wasteful eviction churn.
#### Cache Invalidation
When the user marks a word as known (or any event triggers `invalidateTokenizationCache()`), all cached results are cleared -- including prefetched ones, since they share the same cache. After invalidation, the prefetcher re-computes the priority window from the current playback position and re-tokenizes those cues to restore warm cache state.
#### Error Handling
If the subtitle file is malformed or partially parseable, the cue parser uses what it can extract. A file that yields zero cues disables prefetching silently (falls back to live-only processing). Encoding errors from `loadSubtitleSourceText` are caught and logged; prefetching is skipped for that track.
#### Integration Points
- **MPV property subscriptions:** Needs `track-list` (to detect external subtitle file path) and `time-pos` (to track playback position for window calculation and seek detection).
- **File loading:** Uses existing `loadSubtitleSourceText` dependency.
- **Tokenization:** Calls the same `tokenizeSubtitle` function used by live processing.
- **Cache:** Writes into `SubtitleProcessingController`'s cache.
- **Cache invalidation:** Listens for cache invalidation events to re-prefetch the priority window.
### Files Affected
- **New:** `src/core/services/subtitle-prefetch.ts` -- the prefetch service
- **New:** `src/core/services/subtitle-cue-parser.ts` -- SRT/VTT/ASS cue parser (text + timing)
- **Modified:** `src/core/services/subtitle-processing-controller.ts` -- expose `preCacheTokenization` method
- **Modified:** `src/main.ts` -- wire up the prefetch service, listen to track changes
---
## Optimization 2: Batched Annotation Pass
### Summary
Collapse the 4 sequential annotation passes (`applyKnownWordMarking` -> `applyFrequencyMarking` -> `applyJlptMarking` -> `markNPlusOneTargets`) into a single iteration over the token array, followed by N+1 marking.
**Important context:** Frequency rank _values_ (`token.frequencyRank`) are already assigned at the parser level by `applyFrequencyRanks()` in `tokenizer.ts`, before the annotation stage is called. The annotation stage's `applyFrequencyMarking` only performs POS-based _filtering_ -- clearing `frequencyRank` to `undefined` for tokens that should be excluded (particles, noise tokens, etc.) and normalizing valid ranks. This optimization does not change the parser-level frequency rank assignment; it only batches the annotation-level filtering.
### Current Flow (4 passes, 4 array copies)
```text
tokens (already have frequencyRank values from parser-level applyFrequencyRanks)
-> applyKnownWordMarking() // .map() -> new array
-> applyFrequencyMarking() // .map() -> new array (POS-based filtering only)
-> applyJlptMarking() // .map() -> new array
-> markNPlusOneTargets() // .map() -> new array
```
### Dependency Analysis
All annotations either depend on MeCab POS data or benefit from running after it:
- **Known word marking:** Needs base tokens (surface/headword). No POS dependency, but no reason to run separately.
- **Frequency filtering:** Uses `pos1Exclusions` and `pos2Exclusions` to clear frequency ranks on excluded tokens (particles, noise). Depends on MeCab POS data.
- **JLPT marking:** Uses `shouldIgnoreJlptForMecabPos1` to filter. Depends on MeCab POS data.
- **N+1 marking:** Uses POS exclusion sets to filter candidates. Depends on known word status + MeCab POS.
Since frequency filtering and JLPT marking both depend on POS data from MeCab enrichment, and MeCab enrichment already happens before the annotation stage, all four can run in a single pass after MeCab completes.
### New Flow (1 pass + N+1)
```typescript
function annotateTokens(tokens, deps, options): MergedToken[] {
const pos1Exclusions = resolvePos1Exclusions(options);
const pos2Exclusions = resolvePos2Exclusions(options);
// Single pass: known word + frequency filtering + JLPT computed together
const annotated = tokens.map((token) => {
const isKnown = nPlusOneEnabled
? token.isKnown || computeIsKnown(token, deps)
: false;
// Filter frequency rank using POS exclusions (rank values already set at parser level)
const frequencyRank = frequencyEnabled
? filterFrequencyRank(token, pos1Exclusions, pos2Exclusions)
: undefined;
const jlptLevel = jlptEnabled
? computeJlptLevel(token, deps.getJlptLevel)
: undefined;
return { ...token, isKnown, frequencyRank, jlptLevel };
});
// N+1 must run after known word status is set for all tokens
if (nPlusOneEnabled) {
return markNPlusOneTargets(annotated, minSentenceWords, pos1Exclusions, pos2Exclusions);
}
return annotated;
}
```
### What Changes
- The individual `applyKnownWordMarking`, `applyFrequencyMarking`, `applyJlptMarking` functions are refactored into per-token computation helpers (pure functions that compute a single field). The frequency helper is named `filterFrequencyRank` to clarify it performs POS-based exclusion, not rank computation.
- The `annotateTokens` orchestrator runs one `.map()` call that invokes all three helpers per token.
- `markNPlusOneTargets` remains a separate pass because it needs the full array with `isKnown` set (it examines sentence-level context).
- The parser-level `applyFrequencyRanks()` call in `tokenizer.ts` is unchanged -- it remains a separate step outside the annotation stage.
- Net: 4 array copies + 4 iterations become 1 array copy + 1 iteration + N+1 pass.
### Expected Savings
~15-45ms saved (3 fewer array allocations + 3 fewer full iterations). Annotation drops from ~25-70ms to ~10-25ms.
### Files Affected
- **Modified:** `src/core/services/tokenizer/annotation-stage.ts` -- refactor into batched single-pass
---
## Optimization 3: DOM Template Pooling
### Summary
Replace `document.createElement('span')` calls in the renderer with `templateSpan.cloneNode(false)` from a pre-created template element.
### Current Behavior
In `renderWithTokens` (`subtitle-render.ts`), each render cycle:
1. Clears DOM with `innerHTML = ''`
2. Creates a `DocumentFragment`
3. Calls `document.createElement('span')` for each token (~10-15 per subtitle)
4. Sets `className`, `textContent`, `dataset.*` individually
5. Appends fragment to root
### New Behavior
1. At renderer initialization (`createSubtitleRenderer`), create a single template:
```typescript
const templateSpan = document.createElement('span');
```
2. In `renderWithTokens`, replace every `document.createElement('span')` with:
```typescript
const span = templateSpan.cloneNode(false) as HTMLSpanElement;
```
3. Replace all `innerHTML = ''` calls with `root.replaceChildren()` to avoid the HTML parser invocation on clear. This applies to `renderSubtitle` (primary subtitle root), `renderSecondarySub` (secondary subtitle root), and `renderCharacterLevel` if applicable.
4. Everything else stays the same (setting className, textContent, dataset, appending to fragment).
### Why cloneNode Over Full Node Recycling
Full recycling (collecting old nodes, clearing attributes, reusing them) requires carefully resetting every `dataset.*` property that might have been set on a previous render. This is error-prone -- a stale `data-frequency-rank` from a previous subtitle appearing on a new token would cause incorrect styling. `cloneNode(false)` on a bare template is nearly as fast and produces a clean node every time.
### Expected Savings
`cloneNode(false)` is ~2-3x faster than `createElement` in most browser engines. For 10-15 tokens per subtitle: ~3-8ms saved per render cycle.
### Files Affected
- **Modified:** `src/renderer/subtitle-render.ts` -- template creation + cloneNode usage
---
## Combined Impact Summary
| Scenario | Before | After | Improvement |
|----------|--------|-------|-------------|
| Normal playback (prefetch-warmed) | ~200-320ms | ~30-50ms | ~80-85% |
| Cache hit (repeated subtitle) | ~72ms | ~55-65ms | ~10-20% |
| Cache miss (immediate seek) | ~200-320ms | ~150-260ms | ~20-25% |
---
## Files Summary
### New Files
- `src/core/services/subtitle-prefetch.ts`
- `src/core/services/subtitle-cue-parser.ts`
### Modified Files
- `src/core/services/subtitle-processing-controller.ts` (expose `preCacheTokenization`)
- `src/core/services/tokenizer/annotation-stage.ts` (batched single-pass)
- `src/renderer/subtitle-render.ts` (template cloneNode)
- `src/main.ts` (wire up prefetch service)
### Test Files
- New tests for subtitle cue parser (SRT, VTT, ASS formats)
- New tests for subtitle prefetch service (priority window, seek, pause/resume)
- Updated tests for annotation stage (same behavior, new implementation)
- Updated tests for subtitle render (template cloning)

View File

@@ -0,0 +1,37 @@
<!-- read_when: changing runtime wiring, moving code across layers, or trying to find ownership -->
# Architecture Map
Status: active
Last verified: 2026-03-13
Owner: Kyle Yasuda
Read when: runtime ownership, composition boundaries, or layering questions
SubMiner runs as three cooperating runtimes:
- Electron desktop app in `src/`
- Launcher CLI in `launcher/`
- mpv Lua plugin in `plugin/subminer/`
The desktop app keeps `src/main.ts` as composition root and pushes behavior into small runtime/domain modules.
## Read Next
- [Domains](./domains.md) - who owns what
- [Layering](./layering.md) - how modules should depend on each other
- Public contributor summary: [`docs-site/architecture.md`](../../docs-site/architecture.md)
## Current Shape
- `src/main/` owns composition, runtime setup, IPC wiring, and app lifecycle adapters.
- `src/core/services/` owns focused runtime services plus pure or side-effect-bounded logic.
- `src/renderer/` owns overlay rendering and input behavior.
- `src/config/` owns config definitions, defaults, loading, and resolution.
- `src/main/runtime/composers/` owns larger domain compositions.
## Architecture Intent
- Small units, explicit boundaries
- Composition over monoliths
- Pure helpers where possible
- Stable user behavior while internals evolve

View File

@@ -0,0 +1,38 @@
<!-- read_when: locating ownership for a runtime, feature, or integration -->
# Domain Ownership
Status: active
Last verified: 2026-03-13
Owner: Kyle Yasuda
Read when: you need to find the owner module for a behavior or test surface
## Runtime Domains
- Desktop app runtime: `src/main.ts`, `src/main/`, `src/core/services/`
- Overlay renderer: `src/renderer/`
- Launcher CLI: `launcher/`
- mpv plugin: `plugin/subminer/`
## Product / Integration Domains
- Config system: `src/config/`
- Overlay/window state: `src/core/services/overlay-*`, `src/main/overlay-*.ts`
- MPV runtime and protocol: `src/core/services/mpv*.ts`
- Subtitle/token pipeline: `src/core/services/tokenizer*`, `src/subtitle/`, `src/tokenizers/`
- Anki workflow: `src/anki-integration/`, `src/core/services/anki-jimaku*.ts`
- Immersion tracking: `src/core/services/immersion-tracker/`
- AniList tracking: `src/core/services/anilist/`, `src/main/runtime/composers/anilist-*`
- Jellyfin integration: `src/core/services/jellyfin*.ts`, `src/main/runtime/composers/jellyfin-*`
- Window trackers: `src/window-trackers/`
- Stats app: `stats/`
- Public docs site: `docs-site/`
## Ownership Heuristics
- Runtime wiring or dependency setup: start in `src/main/`
- Business logic or service behavior: start in `src/core/services/`
- UI interaction or overlay DOM behavior: start in `src/renderer/`
- Command parsing or mpv launch flow: start in `launcher/`
- User-facing docs: `docs-site/`
- Internal process/docs: `docs/`

View File

@@ -0,0 +1,33 @@
<!-- read_when: adding dependencies, moving files, or reviewing architecture drift -->
# Layering Rules
Status: active
Last verified: 2026-03-13
Owner: Kyle Yasuda
Read when: deciding whether a dependency direction is acceptable
## Preferred Dependency Flow
1. `src/main.ts`
2. `src/main/` composition and runtime adapters
3. `src/core/services/` focused services
4. `src/core/utils/` and other pure helpers
Renderer, launcher, plugin, and stats each keep their own local layering and should not become a grab bag for unrelated cross-runtime behavior.
## Rules
- Keep `src/main.ts` thin; wire, do not implement.
- Prefer injecting dependencies from `src/main/` instead of reaching outward from core services.
- Keep side effects explicit and close to composition boundaries.
- Put reusable business logic in focused services, not in top-level lifecycle files.
- Keep renderer concerns in `src/renderer/`; avoid leaking DOM behavior into main-process code.
- Treat `launcher/*.ts` as source of truth for the launcher. Never hand-edit `dist/launcher/subminer`.
## Smells
- `main.ts` grows because logic was not extracted
- service reaches directly into unrelated runtime state
- renderer code depends on main-process internals
- docs-site page becomes the only place internal architecture is explained

View File

@@ -0,0 +1,38 @@
# Stats Trends Data Flow
read_when: touching stats trend charts, changing stats API payloads, or debugging dashboard performance
## Summary
Trend charts now consume one chart-oriented backend payload from `/api/stats/trends/dashboard`.
## Why
- remove repeated client-side dataset rebuilding in `TrendsTab`
- collapse multiple network round-trips into one request
- keep heavy chart shaping close to tracker/query logic
## Data Sources
- rollup-backed:
- activity charts
- cumulative watch/cards/tokens/sessions trends
- per-anime watch/cards/tokens/episodes series
- session-metric-backed:
- lookup trends
- lookup rate trends
- watch-time by day-of-week/hour
- vocabulary-backed:
- new-words trend
## Metric Semantics
- subtitle-count stats now use Yomitan merged-token counts as the source of truth
- `tokensSeen` is the only active subtitle-count metric in tracker/session/rollup/query paths
- no whitespace/CJK-character fallback remains in the live stats path
## Contract
The stats UI should treat the trends payload as chart-ready data. Presentation-only work in the client is fine, but rebuilding the main trend datasets from raw sessions should stay out of the render path.
For session detail timelines, omitting `limit` now means "return the full retained session telemetry/history". Explicit `limit` remains available for bounded callers, but the default stats UI path should not trim long sessions to the newest 200 samples.