feat: cache analysis results alongside audio files

After the first analysis of a WAV/FLAC file, the result is written to
<filename>.analysis.json next to the audio. Subsequent requests with the
same threshold and min_gap parameters return the cached result immediately
without re-reading the audio data. The cache is invalidated automatically
if either parameter changes. Written via temp-then-replace for thread safety.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

README.md

@@ -159,7 +159,7 @@ Shows recordings grouped by day with collapsible sections. Features:
 - **Day groups** — recordings are grouped under a collapsible day heading showing date, file count, total duration, and total size. The most recent day is expanded by default; older days start collapsed. Expanded state is preserved across filter changes.
 - **Day highlights** — click **★ Highlights** on any day heading to run loudness analysis across all WAV/FLAC files in that day and display a combined activity timeline SVG. Orange segments show when loud sections occurred relative to the day's time span; blue shows the file extents. Labels show the start, midpoint, and end times.
 - **Inline playback** — collapsible `▶ Play` button per row; audio loads lazily via a seekable `/stream/` endpoint with HTTP Range support. Metadata is fetched immediately so the duration is visible without pressing play.
-- **Waveform analysis** — on demand per file; computes RMS per 100 ms window and highlights loud sections. Supported for WAV and FLAC (FLAC requires `numpy` + `soundfile`). Pure-Python fallback for WAV when numpy is absent.
+- **Waveform analysis** — on demand per file; computes RMS per 100 ms window and highlights loud sections. Supported for WAV and FLAC (FLAC requires `numpy` + `soundfile`). Pure-Python fallback for WAV when numpy is absent. Results are cached alongside the audio file as `<filename>.analysis.json`; subsequent requests at the same threshold and min-gap settings return instantly without re-reading the audio.
 - **Grace period** — configurable in the controls bar (default 2 s). Loud sections separated by less than this gap are merged into one. Raise this (e.g. to 15–30 s) when a single event generates many timestamps due to brief quiet gaps within it.
 - **Timestamp jump** — after analysis, click any loud-section chip to seek the player to that position and pre-fill the cut panel. Use **J** / **K** keyboard shortcuts to jump to the previous / next section while audio is playing.
 - **Cut & download** — `✂ Cut` button opens the player row and reveals a cut panel. Enter start and end times in `m:ss` or `h:mm:ss` format and click **↓ Download cut** to receive an ffmpeg-trimmed copy without re-encoding. Requires ffmpeg (included in the Docker image).

web.py

@@ -331,6 +331,15 @@ class _Handler(BaseHTTPRequestHandler):
         except Exception:
             pass
 
+        cache_path = path.parent / (path.name + '.analysis.json')
+        try:
+            cached = json.loads(cache_path.read_text('utf-8'))
+            if cached.get('threshold') == threshold and cached.get('min_gap') == min_gap:
+                self._send(200, json.dumps(cached['result']).encode('utf-8'), 'application/json')
+                return
+        except Exception:
+            pass
+
         ext = path.suffix.lower()
         if ext == '.wav':
             result = analyze_wav(path, threshold=threshold, min_gap=min_gap)
@@ -343,6 +352,13 @@ class _Handler(BaseHTTPRequestHandler):
             self._json_err(400, f'Loudness analysis is not available for {ext} files')
             return
 
+        try:
+            tmp = cache_path.with_suffix('.tmp')
+            tmp.write_text(json.dumps({'threshold': threshold, 'min_gap': min_gap, 'result': result}), 'utf-8')
+            os.replace(tmp, cache_path)
+        except Exception:
+            pass
+
         self._send(200, json.dumps(result).encode('utf-8'), 'application/json')
 
     def _api_status(self):