style: fix lint and formatting issues across news collector and shared

3 files changed, 31 insertions, 28 deletions

diff --git a/services/strategy-engine/src/strategy_engine/main.py b/services/strategy-engine/src/strategy_engine/main.py
index e9c96b2..5a30766 100644
--- a/services/strategy-engine/src/strategy_engine/main.py
+++ b/services/strategy-engine/src/strategy_engine/main.py
@@ -126,9 +126,9 @@ async def run() -> None:
                 anthropic_model=config.anthropic_model,
                 max_picks=config.selector_max_picks,
             )
-            tasks.append(asyncio.create_task(
-                run_stock_selector(selector, notifier, db, config, log)
-            ))
+            tasks.append(
+                asyncio.create_task(run_stock_selector(selector, notifier, db, config, log))
+            )
             log.info("stock_selector_enabled", time=config.selector_final_time)
 
         await asyncio.gather(*tasks)
diff --git a/services/strategy-engine/src/strategy_engine/stock_selector.py b/services/strategy-engine/src/strategy_engine/stock_selector.py
index e1f2fe7..268d557 100644
--- a/services/strategy-engine/src/strategy_engine/stock_selector.py
+++ b/services/strategy-engine/src/strategy_engine/stock_selector.py
@@ -4,17 +4,14 @@ import json
 import logging
 import re
 from datetime import datetime, timezone
-from decimal import Decimal
-from typing import Optional
 
 import aiohttp
-import pandas as pd
 
 from shared.alpaca import AlpacaClient
 from shared.broker import RedisBroker
 from shared.db import Database
 from shared.models import OrderSide
-from shared.sentiment_models import Candidate, MarketSentiment, SelectedStock, SymbolScore
+from shared.sentiment_models import Candidate, MarketSentiment, SelectedStock
 
 logger = logging.getLogger(__name__)
 
@@ -325,7 +322,9 @@ class StockSelector:
                 ema20 = sum(closes[-20:]) / 20  # simple approximation
                 current_price = closes[-1]
                 if current_price <= ema20:
-                    logger.debug("%s price %.2f <= EMA20 %.2f", candidate.symbol, current_price, ema20)
+                    logger.debug(
+                        "%s price %.2f <= EMA20 %.2f", candidate.symbol, current_price, ema20
+                    )
                     continue
 
                 avg_volume = sum(volumes[:-1]) / max(len(volumes) - 1, 1)
@@ -333,7 +332,9 @@ class StockSelector:
                 if current_volume <= 0.5 * avg_volume:
                     logger.debug(
                         "%s volume %.0f <= 50%% avg %.0f",
-                        candidate.symbol, current_volume, avg_volume,
+                        candidate.symbol,
+                        current_volume,
+                        avg_volume,
                     )
                     continue
 
diff --git a/services/strategy-engine/tests/test_stock_selector.py b/services/strategy-engine/tests/test_stock_selector.py
index a2f5bca..ff9d09c 100644
--- a/services/strategy-engine/tests/test_stock_selector.py
+++ b/services/strategy-engine/tests/test_stock_selector.py
@@ -1,12 +1,8 @@
 """Tests for stock selector engine."""
 
-import pytest
-from unittest.mock import AsyncMock, MagicMock, patch
+from unittest.mock import AsyncMock, MagicMock
 from datetime import datetime, timezone
-from decimal import Decimal
 
-from shared.models import OrderSide
-from shared.sentiment_models import SymbolScore, MarketSentiment, SelectedStock, Candidate
 
 from strategy_engine.stock_selector import (
     SentimentCandidateSource,
@@ -17,10 +13,12 @@ from strategy_engine.stock_selector import (
 
 async def test_sentiment_candidate_source():
     mock_db = MagicMock()
-    mock_db.get_top_symbol_scores = AsyncMock(return_value=[
-        {"symbol": "AAPL", "composite": 0.8, "news_count": 5},
-        {"symbol": "NVDA", "composite": 0.6, "news_count": 3},
-    ])
+    mock_db.get_top_symbol_scores = AsyncMock(
+        return_value=[
+            {"symbol": "AAPL", "composite": 0.8, "news_count": 5},
+            {"symbol": "NVDA", "composite": 0.6, "news_count": 3},
+        ]
+    )
 
     source = SentimentCandidateSource(mock_db)
     candidates = await source.get_candidates()
@@ -64,15 +62,19 @@ def test_parse_llm_selections_with_markdown():
 
 async def test_selector_blocks_on_risk_off():
     mock_db = MagicMock()
-    mock_db.get_latest_market_sentiment = AsyncMock(return_value={
-        "fear_greed": 15,
-        "fear_greed_label": "Extreme Fear",
-        "vix": 35.0,
-        "fed_stance": "neutral",
-        "market_regime": "risk_off",
-        "updated_at": datetime.now(timezone.utc),
-    })
-
-    selector = StockSelector(db=mock_db, broker=MagicMock(), alpaca=MagicMock(), anthropic_api_key="test")
+    mock_db.get_latest_market_sentiment = AsyncMock(
+        return_value={
+            "fear_greed": 15,
+            "fear_greed_label": "Extreme Fear",
+            "vix": 35.0,
+            "fed_stance": "neutral",
+            "market_regime": "risk_off",
+            "updated_at": datetime.now(timezone.utc),
+        }
+    )
+
+    selector = StockSelector(
+        db=mock_db, broker=MagicMock(), alpaca=MagicMock(), anthropic_api_key="test"
+    )
     result = await selector.select()
     assert result == []