ci: fix lint baseline and stabilize failing main tests

src/strategy/models.py

@@ -8,12 +8,12 @@ Defines the data contracts for the proactive strategy system:
 from __future__ import annotations
 
 from datetime import UTC, date, datetime
-from enum import Enum
+from enum import StrEnum
 
 from pydantic import BaseModel, Field, field_validator
 
 
-class ScenarioAction(str, Enum):
+class ScenarioAction(StrEnum):
     """Actions that can be taken by scenarios."""
 
     BUY = "BUY"
@@ -22,7 +22,7 @@ class ScenarioAction(str, Enum):
     REDUCE_ALL = "REDUCE_ALL"
 
 
-class MarketOutlook(str, Enum):
+class MarketOutlook(StrEnum):
     """AI's assessment of market direction."""
 
     BULLISH = "bullish"
@@ -32,7 +32,7 @@ class MarketOutlook(str, Enum):
     BEARISH = "bearish"
 
 
-class PlaybookStatus(str, Enum):
+class PlaybookStatus(StrEnum):
     """Lifecycle status of a playbook."""
 
     PENDING = "pending"

src/strategy/playbook_store.py

@@ -6,7 +6,6 @@ Designed for the pre-market strategy system (one playbook per market per day).
 
 from __future__ import annotations
 
-import json
 import logging
 import sqlite3
 from datetime import date
@@ -53,8 +52,10 @@ class PlaybookStore:
         row_id = cursor.lastrowid or 0
         logger.info(
             "Saved playbook for %s/%s (%d stocks, %d scenarios)",
-            playbook.date, playbook.market,
-            playbook.stock_count, playbook.scenario_count,
+            playbook.date,
+            playbook.market,
+            playbook.stock_count,
+            playbook.scenario_count,
         )
         return row_id
 

src/strategy/position_state_machine.py

@@ -6,10 +6,10 @@ State progression is monotonic (promotion-only) except terminal EXITED.
 from __future__ import annotations
 
 from dataclasses import dataclass
-from enum import Enum
+from enum import StrEnum
 
 
-class PositionState(str, Enum):
+class PositionState(StrEnum):
     HOLDING = "HOLDING"
     BE_LOCK = "BE_LOCK"
     ARMED = "ARMED"
@@ -40,12 +40,7 @@ def evaluate_exit_first(inp: StateTransitionInput) -> bool:
 
     EXITED must be evaluated before any promotion.
     """
-    return (
-        inp.hard_stop_hit
-        or inp.trailing_stop_hit
-        or inp.model_exit_signal
-        or inp.be_lock_threat
-    )
+    return inp.hard_stop_hit or inp.trailing_stop_hit or inp.model_exit_signal or inp.be_lock_threat
 
 
 def promote_state(current: PositionState, inp: StateTransitionInput) -> PositionState:

src/strategy/pre_market_planner.py

@@ -124,12 +124,14 @@ class PreMarketPlanner:
 
             # 4. Parse response
             playbook = self._parse_response(
-                decision.rationale, today, market, candidates, cross_market,
+                decision.rationale,
+                today,
+                market,
+                candidates,
+                cross_market,
                 current_holdings=current_holdings,
             )
-            playbook_with_tokens = playbook.model_copy(
-                update={"token_count": decision.token_count}
-            )
+            playbook_with_tokens = playbook.model_copy(update={"token_count": decision.token_count})
             logger.info(
                 "Generated playbook for %s: %d stocks, %d scenarios, %d tokens",
                 market,
@@ -146,7 +148,9 @@ class PreMarketPlanner:
             return self._empty_playbook(today, market)
 
     def build_cross_market_context(
-        self, target_market: str, today: date | None = None,
+        self,
+        target_market: str,
+        today: date | None = None,
     ) -> CrossMarketContext | None:
         """Build cross-market context from the other market's L6 data.
 
@@ -192,7 +196,9 @@ class PreMarketPlanner:
         )
 
     def build_self_market_scorecard(
-        self, market: str, today: date | None = None,
+        self,
+        market: str,
+        today: date | None = None,
     ) -> dict[str, Any] | None:
         """Build previous-day scorecard for the same market."""
         if today is None:
@@ -320,18 +326,18 @@ class PreMarketPlanner:
             f"{context_text}\n"
             f"## Instructions\n"
             f"Return a JSON object with this exact structure:\n"
-            f'{{\n'
+            f"{{\n"
             f'  "market_outlook": "bullish|neutral_to_bullish|neutral'
             f'|neutral_to_bearish|bearish",\n'
             f'  "global_rules": [\n'
             f'    {{"condition": "portfolio_pnl_pct < -2.0",'
             f' "action": "REDUCE_ALL", "rationale": "..."}}\n'
-            f'  ],\n'
+            f"  ],\n"
             f'  "stocks": [\n'
-            f'    {{\n'
+            f"    {{\n"
             f'      "stock_code": "...",\n'
             f'      "scenarios": [\n'
-            f'        {{\n'
+            f"        {{\n"
             f'          "condition": {{"rsi_below": 30, "volume_ratio_above": 2.0,'
             f' "unrealized_pnl_pct_above": 3.0, "holding_days_above": 5}},\n'
             f'          "action": "BUY|SELL|HOLD",\n'
@@ -340,11 +346,11 @@ class PreMarketPlanner:
             f'          "stop_loss_pct": -2.0,\n'
             f'          "take_profit_pct": 3.0,\n'
             f'          "rationale": "..."\n'
-            f'        }}\n'
-            f'      ]\n'
-            f'    }}\n'
-            f'  ]\n'
-            f'}}\n\n'
+            f"        }}\n"
+            f"      ]\n"
+            f"    }}\n"
+            f"  ]\n"
+            f"}}\n\n"
             f"Rules:\n"
             f"- Max {max_scenarios} scenarios per stock\n"
             f"- Candidates list is the primary source for BUY candidates\n"
@@ -575,8 +581,7 @@ class PreMarketPlanner:
                         stop_loss_pct=-3.0,
                         take_profit_pct=5.0,
                         rationale=(
-                            f"Rule-based BUY: oversold signal, "
-                            f"RSI={c.rsi:.0f} (fallback planner)"
+                            f"Rule-based BUY: oversold signal, RSI={c.rsi:.0f} (fallback planner)"
                         ),
                     )
                 )

src/strategy/scenario_engine.py

@@ -107,7 +107,9 @@ class ScenarioEngine:
         # 2. Find stock playbook
         stock_pb = playbook.get_stock_playbook(stock_code)
         if stock_pb is None:
-            logger.debug("No playbook for %s — defaulting to %s", stock_code, playbook.default_action)
+            logger.debug(
+                "No playbook for %s — defaulting to %s", stock_code, playbook.default_action
+            )
             return ScenarioMatch(
                 stock_code=stock_code,
                 matched_scenario=None,
@@ -135,7 +137,9 @@ class ScenarioEngine:
                 )
 
         # 4. No match — default action
-        logger.debug("No scenario matched for %s — defaulting to %s", stock_code, playbook.default_action)
+        logger.debug(
+            "No scenario matched for %s — defaulting to %s", stock_code, playbook.default_action
+        )
         return ScenarioMatch(
             stock_code=stock_code,
             matched_scenario=None,
@@ -198,17 +202,27 @@ class ScenarioEngine:
             checks.append(price is not None and price < condition.price_below)
 
         price_change_pct = self._safe_float(market_data.get("price_change_pct"))
-        if condition.price_change_pct_above is not None or condition.price_change_pct_below is not None:
+        if (
+            condition.price_change_pct_above is not None
+            or condition.price_change_pct_below is not None
+        ):
             if "price_change_pct" not in market_data:
                 self._warn_missing_key("price_change_pct")
         if condition.price_change_pct_above is not None:
-            checks.append(price_change_pct is not None and price_change_pct > condition.price_change_pct_above)
+            checks.append(
+                price_change_pct is not None and price_change_pct > condition.price_change_pct_above
+            )
         if condition.price_change_pct_below is not None:
-            checks.append(price_change_pct is not None and price_change_pct < condition.price_change_pct_below)
+            checks.append(
+                price_change_pct is not None and price_change_pct < condition.price_change_pct_below
+            )
 
         # Position-aware conditions
         unrealized_pnl_pct = self._safe_float(market_data.get("unrealized_pnl_pct"))
-        if condition.unrealized_pnl_pct_above is not None or condition.unrealized_pnl_pct_below is not None:
+        if (
+            condition.unrealized_pnl_pct_above is not None
+            or condition.unrealized_pnl_pct_below is not None
+        ):
             if "unrealized_pnl_pct" not in market_data:
                 self._warn_missing_key("unrealized_pnl_pct")
         if condition.unrealized_pnl_pct_above is not None:
@@ -227,15 +241,9 @@ class ScenarioEngine:
             if "holding_days" not in market_data:
                 self._warn_missing_key("holding_days")
         if condition.holding_days_above is not None:
-            checks.append(
-                holding_days is not None
-                and holding_days > condition.holding_days_above
-            )
+            checks.append(holding_days is not None and holding_days > condition.holding_days_above)
         if condition.holding_days_below is not None:
-            checks.append(
-                holding_days is not None
-                and holding_days < condition.holding_days_below
-            )
+            checks.append(holding_days is not None and holding_days < condition.holding_days_below)
 
         return len(checks) > 0 and all(checks)
 
@@ -295,9 +303,15 @@ class ScenarioEngine:
             details["volume_ratio"] = self._safe_float(market_data.get("volume_ratio"))
         if condition.price_above is not None or condition.price_below is not None:
             details["current_price"] = self._safe_float(market_data.get("current_price"))
-        if condition.price_change_pct_above is not None or condition.price_change_pct_below is not None:
+        if (
+            condition.price_change_pct_above is not None
+            or condition.price_change_pct_below is not None
+        ):
             details["price_change_pct"] = self._safe_float(market_data.get("price_change_pct"))
-        if condition.unrealized_pnl_pct_above is not None or condition.unrealized_pnl_pct_below is not None:
+        if (
+            condition.unrealized_pnl_pct_above is not None
+            or condition.unrealized_pnl_pct_below is not None
+        ):
             details["unrealized_pnl_pct"] = self._safe_float(market_data.get("unrealized_pnl_pct"))
         if condition.holding_days_above is not None or condition.holding_days_below is not None:
             details["holding_days"] = self._safe_float(market_data.get("holding_days"))