v0.9.5: The Voltron Update — modular architecture, stable IDs, parallelized boot

- Parallelized startup (60s → 15s) via ThreadPoolExecutor
- Adaptive polling engine with ETag caching (no more bbox interrupts)
- useCallback optimization for interpolation functions
- Sliding LAYERS/INTEL edge panels replace bulky Record Panel
- Modular fetcher architecture (flights, geo, infrastructure, financial, earth_observation)
- Stable entity IDs for GDELT & News popups (PR #63, credit @csysp)
- Admin auth (X-Admin-Key), rate limiting (slowapi), auto-updater
- Docker Swarm secrets support, env_check.py validation
- 85+ vitest tests, CI pipeline, geoJSON builder extraction
- Server-side viewport bbox filtering reduces payloads 80%+

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

Former-commit-id: f2883150b5bc78ebc139d89cc966a76f7d7c0408

backend/services/fetchers/financial.py

@@ -0,0 +1,58 @@
+"""Financial data fetchers — defense stocks and oil prices.
+
+Uses yfinance for ticker data with concurrent execution for performance.
+"""
+import logging
+import concurrent.futures
+import yfinance as yf
+from services.fetchers._store import latest_data, _data_lock, _mark_fresh
+from services.fetchers.retry import with_retry
+
+logger = logging.getLogger(__name__)
+
+
+def _fetch_single_ticker(symbol: str, period: str = "2d"):
+    """Fetch a single yfinance ticker. Returns (symbol, data_dict) or (symbol, None)."""
+    try:
+        ticker = yf.Ticker(symbol)
+        hist = ticker.history(period=period)
+        if len(hist) >= 1:
+            current_price = hist['Close'].iloc[-1]
+            prev_close = hist['Close'].iloc[0] if len(hist) > 1 else current_price
+            change_percent = ((current_price - prev_close) / prev_close) * 100 if prev_close else 0
+            return symbol, {
+                "price": round(float(current_price), 2),
+                "change_percent": round(float(change_percent), 2),
+                "up": bool(change_percent >= 0)
+            }
+    except Exception as e:
+        logger.warning(f"Could not fetch data for {symbol}: {e}")
+    return symbol, None
+
+
+@with_retry(max_retries=1, base_delay=1)
+def fetch_defense_stocks():
+    tickers = ["RTX", "LMT", "NOC", "GD", "BA", "PLTR"]
+    try:
+        with concurrent.futures.ThreadPoolExecutor(max_workers=4) as pool:
+            results = pool.map(lambda t: _fetch_single_ticker(t, "2d"), tickers)
+        stocks_data = {sym: data for sym, data in results if data}
+        with _data_lock:
+            latest_data['stocks'] = stocks_data
+        _mark_fresh("stocks")
+    except Exception as e:
+        logger.error(f"Error fetching stocks: {e}")
+
+
+@with_retry(max_retries=1, base_delay=1)
+def fetch_oil_prices():
+    tickers = {"WTI Crude": "CL=F", "Brent Crude": "BZ=F"}
+    try:
+        with concurrent.futures.ThreadPoolExecutor(max_workers=2) as pool:
+            results = pool.map(lambda item: (_fetch_single_ticker(item[1], "5d")[1], item[0]), tickers.items())
+        oil_data = {name: data for data, name in results if data}
+        with _data_lock:
+            latest_data['oil'] = oil_data
+        _mark_fresh("oil")
+    except Exception as e:
+        logger.error(f"Error fetching oil: {e}")