feat: OpenBB Investment Analysis API

REST API wrapping OpenBB SDK for stock data, sentiment analysis,
technical indicators, macro data, and rule-based portfolio analysis.

- Stock data via yfinance (quote, profile, metrics, financials, historical, news)
- News sentiment via Alpha Vantage (per-article, per-ticker scores)
- Analyst data via Finnhub (recommendations, insider trades, upgrades)
- Macro data via FRED (Fed rate, CPI, GDP, unemployment, treasury yields)
- Technical indicators via openbb-technical (RSI, MACD, SMA, EMA, Bollinger)
- Rule-based portfolio analysis engine (BUY_MORE/HOLD/SELL)
- Stock discovery (gainers, losers, active, undervalued, growth)
- 102 tests, all passing

mappers.py

@@ -0,0 +1,68 @@
+"""Shared mapping functions from raw dicts to response models."""
+
+from typing import Any
+
+from models import (
+    DiscoverItem,
+    MetricsResponse,
+    ProfileResponse,
+    QuoteResponse,
+)
+
+
+def quote_from_dict(symbol: str, data: dict[str, Any]) -> QuoteResponse:
+    return QuoteResponse(
+        symbol=symbol,
+        name=data.get("name"),
+        price=data.get("last_price") or data.get("close"),
+        change=data.get("change"),
+        change_percent=data.get("change_percent"),
+        volume=data.get("volume"),
+        market_cap=data.get("market_cap"),
+        currency=data.get("currency"),
+    )
+
+
+def profile_from_dict(symbol: str, data: dict[str, Any]) -> ProfileResponse:
+    return ProfileResponse(
+        symbol=symbol,
+        name=data.get("name"),
+        sector=data.get("sector"),
+        industry=data.get("industry"),
+        country=data.get("country"),
+        description=data.get("long_description") or data.get("description"),
+        website=data.get("website"),
+        employees=data.get("full_time_employees") or data.get("employees"),
+    )
+
+
+def metrics_from_dict(symbol: str, data: dict[str, Any]) -> MetricsResponse:
+    return MetricsResponse(
+        symbol=symbol,
+        pe_ratio=data.get("pe_ratio"),
+        pb_ratio=data.get("pb_ratio"),
+        ps_ratio=data.get("ps_ratio"),
+        peg_ratio=data.get("peg_ratio"),
+        roe=data.get("roe") or data.get("return_on_equity"),
+        roa=data.get("roa") or data.get("return_on_assets"),
+        dividend_yield=data.get("dividend_yield"),
+        beta=data.get("beta"),
+        eps=data.get("eps_ttm") or data.get("eps"),
+        revenue_growth=data.get("revenue_growth"),
+        earnings_growth=data.get("earnings_growth"),
+    )
+
+
+def discover_item_from_dict(data: dict[str, Any]) -> DiscoverItem:
+    return DiscoverItem(
+        symbol=data.get("symbol"),
+        name=data.get("name"),
+        price=data.get("price") or data.get("last_price"),
+        change_percent=data.get("change_percent") or data.get("percent_change"),
+        volume=data.get("volume"),
+        market_cap=data.get("market_cap"),
+    )
+
+
+def discover_items_from_list(items: list[dict[str, Any]]) -> list[dict[str, Any]]:
+    return [discover_item_from_dict(item).model_dump() for item in items]