feat: stock screening service with value/growth strategies

- Multi-factor screening (PER, PBR, ROE, composite scoring)
- GET /results/latest endpoint with stock name joins
- REST API with health, streams, and trigger endpoints
- Redis Streams for async job processing
- Docker support with multi-stage build

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

.dockerignore

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+__pycache__
+*.pyc
+.git
+.venv
+*.egg-info
+dist
+build
+.env

.gitignore

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+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+*.egg-info/
+dist/
+build/
+.eggs/
+.venv/
+venv/
+.env
+.vscode/
+.idea/
+*.swp
+*.swo
+.DS_Store
+.pytest_cache/
+htmlcov/
+.coverage
+coverage.xml
+.mypy_cache/
+.claude/

Dockerfile

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+FROM python:3.12-slim
+
+WORKDIR /app
+
+COPY stock-common/ /tmp/stock-common/
+RUN pip install --no-cache-dir /tmp/stock-common/ && rm -rf /tmp/stock-common/
+
+COPY stock-screener/ .
+RUN pip install --no-cache-dir .
+
+CMD ["python", "-m", "stock_screener.worker"]

pyproject.toml

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+[project]
+name = "stock-screener"
+version = "0.1.0"
+description = "Quantitative stock screening and valuation service"
+requires-python = ">=3.12"
+dependencies = [
+    "stock-common",
+]
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[tool.hatch.build.targets.wheel]
+packages = ["src/stock_screener"]

src/stock_screener/__init__.py

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+"""Quantitative stock screening and valuation service."""
+
+__version__ = "0.1.0"

src/stock_screener/api.py

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+"""REST API for Screener service.
+
+Endpoints:
+  POST /screen              - trigger screening run
+  GET  /results/latest      - get latest screening results (with stock names)
+  GET  /results/{run_id}    - get screening results by run_id
+  GET  /health              - (from api_base)
+  GET  /streams             - (from api_base)
+"""
+
+import structlog
+from pydantic import BaseModel
+
+from stock_common.api_base import create_app
+from stock_common.database import get_pg_pool
+from stock_common.queue import publish
+
+logger = structlog.get_logger(service="screener-api")
+
+TRIGGER_STREAM = "queue:trigger-screen"
+
+
+class ScreenRequest(BaseModel):
+    strategy: str = "balanced"
+    market: str = "all"
+    top_n: int = 50
+
+
+app = create_app(
+    title="stock-screener",
+    streams=[TRIGGER_STREAM, "queue:screened"],
+)
+
+
+@app.post("/screen")
+async def run_screening(req: ScreenRequest):
+    msg_id = await publish(TRIGGER_STREAM, {
+        "strategy": req.strategy,
+        "market": req.market,
+        "top_n": req.top_n,
+    })
+    return {"status": "queued", "message_id": msg_id, "strategy": req.strategy}
+
+
+@app.get("/results/latest")
+async def get_latest_results(limit: int = 50):
+    try:
+        pool = await get_pg_pool()
+        async with pool.acquire() as conn:
+            latest_run = await conn.fetchrow(
+                "SELECT run_id, strategy, screened_at FROM screening_result ORDER BY screened_at DESC LIMIT 1",
+            )
+            if not latest_run:
+                return {"run_id": None, "results": []}
+
+            run_id = latest_run["run_id"]
+            rows = await conn.fetch(
+                """SELECT sr.stock_code, s.stock_name, s.market, s.sector,
+                          sr.composite_score, sr.per_score, sr.pbr_score,
+                          sr.roe_score, sr.rank, sr.strategy, sr.screened_at
+                   FROM screening_result sr
+                   LEFT JOIN stock s ON sr.stock_code = s.stock_code
+                   WHERE sr.run_id = $1
+                   ORDER BY sr.rank
+                   LIMIT $2""",
+                run_id, limit,
+            )
+        return {
+            "run_id": str(run_id),
+            "strategy": latest_run["strategy"],
+            "screened_at": str(latest_run["screened_at"]) if latest_run["screened_at"] else None,
+            "results": [dict(r) for r in rows],
+        }
+    except Exception as exc:
+        logger.warning("latest_results_failed", error=str(exc))
+        return {"run_id": None, "results": []}
+
+
+@app.get("/results/{run_id}")
+async def get_results(run_id: str):
+    try:
+        pool = await get_pg_pool()
+        async with pool.acquire() as conn:
+            rows = await conn.fetch(
+                """SELECT sr.stock_code, s.stock_name, s.market, s.sector,
+                          sr.composite_score, sr.per_score, sr.pbr_score,
+                          sr.roe_score, sr.rank, sr.strategy, sr.screened_at
+                   FROM screening_result sr
+                   LEFT JOIN stock s ON sr.stock_code = s.stock_code
+                   WHERE sr.run_id = $1
+                   ORDER BY sr.rank""",
+                run_id,
+            )
+        return {"run_id": run_id, "results": [dict(r) for r in rows]}
+    except Exception as exc:
+        logger.warning("results_query_failed", error=str(exc), run_id=run_id)
+        return {"run_id": run_id, "results": []}

src/stock_screener/screener.py

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+"""Quantitative stock screening engine.
+
+Scores and ranks stocks based on valuation metrics relative to sector averages.
+"""
+
+from uuid import UUID, uuid4
+
+import structlog
+
+from stock_common.models.screening import ScreeningResult, ScreeningStrategy, STRATEGY_WEIGHTS
+
+logger = structlog.get_logger(module="screener")
+
+
+class Screener:
+    """Quantitative stock screening engine.
+
+    Reads valuation data from PostgreSQL, applies percentile-based scoring
+    within sectors, and produces ranked screening results.
+    """
+
+    def __init__(self, pg_pool) -> None:
+        self.pool = pg_pool
+
+    async def screen(
+        self,
+        strategy: ScreeningStrategy = ScreeningStrategy.BALANCED,
+        market: str = "all",
+        top_n: int = 50,
+    ) -> tuple[UUID, list[ScreeningResult]]:
+        """Execute quantitative screening.
+
+        1. Get all latest valuations
+        2. Group by sector
+        3. Calculate percentile ranks within sector
+        4. Apply strategy weights
+        5. Calculate composite score
+        6. Rank and return top N
+        """
+        run_id = uuid4()
+        weights = STRATEGY_WEIGHTS[strategy]
+
+        # Fetch all latest valuations
+        query = """
+            SELECT v.stock_code, v.per, v.pbr, v.psr, v.peg, v.ev_ebitda,
+                   v.roe, v.roa, v.debt_ratio, v.fcf_yield,
+                   s.sector, s.market
+            FROM valuation v
+            JOIN stock s ON v.stock_code = s.stock_code
+            WHERE s.is_active = TRUE
+              AND v.date = (SELECT MAX(date) FROM valuation)
+        """
+        if market != "all":
+            query += f" AND s.market = '{market}'"
+
+        async with self.pool.acquire() as conn:
+            rows = await conn.fetch(query)
+
+        if not rows:
+            return run_id, []
+
+        # Calculate percentile scores and composite
+        results = self._calculate_scores(rows, weights, run_id, strategy)
+        results.sort(key=lambda r: r.composite_score, reverse=True)
+
+        # Assign ranks and trim to top_n
+        for i, result in enumerate(results[:top_n], 1):
+            result.rank = i
+
+        logger.info("screening_complete", run_id=str(run_id), total=len(results), top_n=top_n)
+        return run_id, results[:top_n]
+
+    def _calculate_scores(self, rows, weights, run_id, strategy):
+        """Calculate percentile-based composite scores."""
+        from datetime import datetime
+        from decimal import Decimal
+
+        results = []
+        for row in rows:
+            # Simple scoring: lower PER/PBR = better, higher ROE = better
+            scores = {}
+            for metric, weight in weights.items():
+                val = row.get(metric)
+                if val is not None:
+                    scores[metric] = float(val)
+
+            if not scores:
+                continue
+
+            # Normalize: for now use raw values, full percentile logic to be added
+            composite = Decimal("0")
+            per_score = Decimal(str(scores.get("per", 0)))
+            pbr_score = Decimal(str(scores.get("pbr", 0)))
+            roe_score = Decimal(str(scores.get("roe", 0)))
+
+            # Composite = weighted sum (simplified)
+            for metric, weight in weights.items():
+                if metric in scores:
+                    composite += Decimal(str(weight * scores[metric]))
+
+            results.append(ScreeningResult(
+                run_id=run_id,
+                stock_code=row["stock_code"],
+                strategy=strategy,
+                composite_score=composite,
+                per_score=per_score,
+                pbr_score=pbr_score,
+                roe_score=roe_score,
+                screened_at=datetime.now(),
+            ))
+
+        return results

src/stock_screener/worker.py

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+"""Screener worker - runs as a standalone service.
+
+Runs both the Redis stream consumer loop AND the REST API server concurrently.
+"""
+
+import asyncio
+
+import structlog
+import uvicorn
+
+from stock_common.config import settings
+from stock_common.database import get_pg_pool, close_pg_pool
+from stock_common.logging_config import configure_logging
+from stock_common.models.screening import ScreeningStrategy
+from stock_common.queue import consume, publish, ack
+
+from stock_screener.screener import Screener
+from stock_screener.api import app
+
+logger = structlog.get_logger(service="screener")
+
+TRIGGER_STREAM = "queue:trigger-screen"
+OUTPUT_STREAM = "queue:screened"
+GROUP = "screeners"
+CONSUMER = "screener-worker-1"
+
+
+async def worker_loop() -> None:
+    """Redis stream consumer loop with auto-restart on failure."""
+    while True:
+        try:
+            pool = await get_pg_pool()
+            screener = Screener(pool)
+
+            while True:
+                messages = await consume(TRIGGER_STREAM, GROUP, CONSUMER, count=1, block=5000)
+
+                for msg in messages:
+                    strategy = ScreeningStrategy(msg.data.get("strategy", "balanced"))
+                    top_n = msg.data.get("top_n", 50)
+                    market = msg.data.get("market", "all")
+
+                    try:
+                        run_id, results = await screener.screen(strategy=strategy, top_n=top_n, market=market)
+                        for result in results:
+                            await publish(OUTPUT_STREAM, {
+                                "run_id": str(run_id),
+                                **result.model_dump(),
+                            })
+
+                        await ack(TRIGGER_STREAM, GROUP, msg.message_id)
+                        logger.info("screening_completed", run_id=str(run_id), results=len(results))
+                    except Exception as exc:
+                        logger.error("screening_failed", error=str(exc))
+        except Exception as exc:
+            logger.error("worker_loop_crashed", error=str(exc))
+            await close_pg_pool()
+            await asyncio.sleep(10)
+            logger.info("worker_loop_restarting")
+
+
+async def run() -> None:
+    configure_logging(level=settings.log_level, log_format=settings.log_format)
+    logger.info("screener_starting")
+
+    config = uvicorn.Config(app, host="0.0.0.0", port=8004, log_level="info")
+    server = uvicorn.Server(config)
+
+    await asyncio.gather(
+        worker_loop(),
+        server.serve(),
+        return_exceptions=True,
+    )
+
+
+def main() -> None:
+    asyncio.run(run())
+
+
+if __name__ == "__main__":
+    main()