chore(lint): make the repository ruff-clean under the strict select

Clear the deferred full-repo lint backlog so the whole tree passes the strict
ruff select (E,W,F,I,B,UP,C4,SIM). Mechanical fixes dominate: import sorting,
pep585/604 annotations, dropped dead imports, and whitespace. The few semantic
changes are behavior-preserving: declare __all__ on the agent_utils and
alpha_vantage re-export hubs; expand 'from x import *' to explicit names; use
immutable tuple defaults instead of mutable list defaults; contextlib.suppress
for try/except/pass; and narrow an over-broad assertRaises.

tradingagents/graph/__init__.py

@@ -1,11 +1,11 @@
 # TradingAgents/graph/__init__.py
 
-from .trading_graph import TradingAgentsGraph
 from .conditional_logic import ConditionalLogic
-from .setup import GraphSetup
 from .propagation import Propagator
 from .reflection import Reflector
+from .setup import GraphSetup
 from .signal_processing import SignalProcessor
+from .trading_graph import TradingAgentsGraph
 
 __all__ = [
     "TradingAgentsGraph",

tradingagents/graph/analyst_execution.py

@@ -1,6 +1,6 @@
+from collections.abc import Iterable
 from dataclasses import dataclass
 from time import monotonic
-from typing import Dict, Iterable, List, Optional
 
 
 @dataclass(frozen=True)
@@ -14,11 +14,11 @@ class AnalystNodeSpec:
 
 @dataclass(frozen=True)
 class AnalystExecutionPlan:
-    specs: List[AnalystNodeSpec]
+    specs: list[AnalystNodeSpec]
     concurrency_limit: int
 
 
-ANALYST_NODE_SPECS: Dict[str, AnalystNodeSpec] = {
+ANALYST_NODE_SPECS: dict[str, AnalystNodeSpec] = {
     "market": AnalystNodeSpec(
         key="market",
         agent_node="Market Analyst",
@@ -61,7 +61,7 @@ def build_analyst_execution_plan(
     if concurrency_limit < 1:
         raise ValueError("analyst concurrency limit must be >= 1")
 
-    specs: List[AnalystNodeSpec] = []
+    specs: list[AnalystNodeSpec] = []
     for analyst_key in selected_analysts:
         spec = ANALYST_NODE_SPECS.get(analyst_key)
         if spec is None:
@@ -81,10 +81,10 @@ def get_initial_analyst_node(plan: AnalystExecutionPlan) -> str:
 class AnalystWallTimeTracker:
     def __init__(self, plan: AnalystExecutionPlan):
         self.plan = plan
-        self._started_at: Dict[str, float] = {}
-        self._wall_times: Dict[str, float] = {}
+        self._started_at: dict[str, float] = {}
+        self._wall_times: dict[str, float] = {}
 
-    def mark_started(self, analyst_key: str, started_at: Optional[float] = None) -> None:
+    def mark_started(self, analyst_key: str, started_at: float | None = None) -> None:
         if analyst_key not in ANALYST_NODE_SPECS:
             raise ValueError(f"unknown analyst key: {analyst_key}")
         self._started_at.setdefault(analyst_key, monotonic() if started_at is None else started_at)
@@ -92,7 +92,7 @@ class AnalystWallTimeTracker:
     def mark_completed(
         self,
         analyst_key: str,
-        completed_at: Optional[float] = None,
+        completed_at: float | None = None,
     ) -> None:
         if analyst_key not in ANALYST_NODE_SPECS:
             raise ValueError(f"unknown analyst key: {analyst_key}")
@@ -104,7 +104,7 @@ class AnalystWallTimeTracker:
         finished_at = monotonic() if completed_at is None else completed_at
         self._wall_times[analyst_key] = max(0.0, finished_at - started_at)
 
-    def get_wall_times(self) -> Dict[str, float]:
+    def get_wall_times(self) -> dict[str, float]:
         return dict(self._wall_times)
 
     def format_summary(self) -> str:
@@ -121,8 +121,8 @@ class AnalystWallTimeTracker:
 
 def sync_analyst_tracker_from_chunk(
     tracker: AnalystWallTimeTracker,
-    chunk: Dict[str, str],
-    now: Optional[float] = None,
+    chunk: dict[str, str],
+    now: float | None = None,
 ) -> None:
     current_time = monotonic() if now is None else now
     active_found = False

tradingagents/graph/checkpointer.py

@@ -7,9 +7,9 @@ from __future__ import annotations
 
 import hashlib
 import sqlite3
+from collections.abc import Generator
 from contextlib import contextmanager
 from pathlib import Path
-from typing import Generator
 
 from langgraph.checkpoint.sqlite import SqliteSaver
 

tradingagents/graph/propagation.py

@@ -1,8 +1,8 @@
 # TradingAgents/graph/propagation.py
 
-from typing import Dict, Any, List, Optional
+from typing import Any
+
 from tradingagents.agents.utils.agent_states import (
-    AgentState,
     InvestDebateState,
     RiskDebateState,
 )
@@ -22,7 +22,7 @@ class Propagator:
         asset_type: str = "stock",
         past_context: str = "",
         instrument_context: str = "",
-    ) -> Dict[str, Any]:
+    ) -> dict[str, Any]:
         """Create the initial state for the agent graph.
 
         ``instrument_context`` is the deterministic ticker-identity string
@@ -68,7 +68,7 @@ class Propagator:
             "news_report": "",
         }
 
-    def get_graph_args(self, callbacks: Optional[List] = None) -> Dict[str, Any]:
+    def get_graph_args(self, callbacks: list | None = None) -> dict[str, Any]:
         """Get arguments for the graph invocation.
 
         Args:

tradingagents/graph/setup.py

@@ -1,10 +1,25 @@
 # TradingAgents/graph/setup.py
 
-from typing import Any, Dict
+from typing import Any
+
 from langgraph.graph import END, START, StateGraph
 from langgraph.prebuilt import ToolNode
 
-from tradingagents.agents import *
+from tradingagents.agents import (
+    create_aggressive_debator,
+    create_bear_researcher,
+    create_bull_researcher,
+    create_conservative_debator,
+    create_fundamentals_analyst,
+    create_market_analyst,
+    create_msg_delete,
+    create_neutral_debator,
+    create_news_analyst,
+    create_portfolio_manager,
+    create_research_manager,
+    create_sentiment_analyst,
+    create_trader,
+)
 from tradingagents.agents.utils.agent_states import AgentState
 
 from .analyst_execution import build_analyst_execution_plan
@@ -18,7 +33,7 @@ class GraphSetup:
         self,
         quick_thinking_llm: Any,
         deep_thinking_llm: Any,
-        tool_nodes: Dict[str, ToolNode],
+        tool_nodes: dict[str, ToolNode],
         conditional_logic: ConditionalLogic,
         analyst_concurrency_limit: int = 1,
     ):
@@ -30,7 +45,7 @@ class GraphSetup:
         self.analyst_concurrency_limit = analyst_concurrency_limit
 
     def setup_graph(
-        self, selected_analysts=["market", "social", "news", "fundamentals"]
+        self, selected_analysts=("market", "social", "news", "fundamentals")
     ):
         """Set up and compile the agent workflow graph.
 

tradingagents/graph/trading_graph.py

@@ -1,66 +1,57 @@
 # TradingAgents/graph/trading_graph.py
 
+import json
 import logging
 import os
-from pathlib import Path
-import json
 from datetime import datetime, timedelta
-from typing import Dict, Any, Tuple, List, Optional
+from pathlib import Path
+from typing import Any
 
 import yfinance as yf
-
-logger = logging.getLogger(__name__)
-
 from langgraph.prebuilt import ToolNode
 
-from tradingagents.llm_clients import create_llm_client
-
-from tradingagents.agents import *
-from tradingagents.default_config import DEFAULT_CONFIG
-from tradingagents.agents.utils.memory import TradingMemoryLog
-from tradingagents.dataflows.utils import safe_ticker_component
-from tradingagents.agents.utils.agent_states import (
-    AgentState,
-    InvestDebateState,
-    RiskDebateState,
-)
-from tradingagents.dataflows.config import set_config
-
-# Import the new abstract tool methods from agent_utils
+# Import the abstract tool methods from agent_utils
 from tradingagents.agents.utils.agent_utils import (
     build_instrument_context,
-    resolve_instrument_identity,
-    get_stock_data,
-    get_indicators,
-    get_verified_market_snapshot,
-    get_fundamentals,
     get_balance_sheet,
     get_cashflow,
-    get_income_statement,
-    get_news,
-    get_insider_transactions,
+    get_fundamentals,
     get_global_news,
+    get_income_statement,
+    get_indicators,
+    get_insider_transactions,
     get_macro_indicators,
-    get_prediction_markets
+    get_news,
+    get_prediction_markets,
+    get_stock_data,
+    get_verified_market_snapshot,
+    resolve_instrument_identity,
 )
+from tradingagents.agents.utils.memory import TradingMemoryLog
+from tradingagents.dataflows.config import set_config
+from tradingagents.dataflows.utils import safe_ticker_component
+from tradingagents.default_config import DEFAULT_CONFIG
+from tradingagents.llm_clients import create_llm_client
 
 from .checkpointer import checkpoint_step, clear_checkpoint, get_checkpointer, thread_id
 from .conditional_logic import ConditionalLogic
-from .setup import GraphSetup
 from .propagation import Propagator
 from .reflection import Reflector
+from .setup import GraphSetup
 from .signal_processing import SignalProcessor
 
+logger = logging.getLogger(__name__)
+
 
 class TradingAgentsGraph:
     """Main class that orchestrates the trading agents framework."""
 
     def __init__(
         self,
-        selected_analysts=["market", "social", "news", "fundamentals"],
+        selected_analysts=("market", "social", "news", "fundamentals"),
         debug=False,
-        config: Dict[str, Any] = None,
-        callbacks: Optional[List] = None,
+        config: dict[str, Any] = None,
+        callbacks: list | None = None,
     ):
         """Initialize the trading agents graph and components.
 
@@ -103,7 +94,7 @@ class TradingAgentsGraph:
 
         self.deep_thinking_llm = deep_client.get_llm()
         self.quick_thinking_llm = quick_client.get_llm()
-        
+
         self.memory_log = TradingMemoryLog(self.config)
 
         # Create tool nodes
@@ -138,7 +129,7 @@ class TradingAgentsGraph:
         self.graph = self.workflow.compile()
         self._checkpointer_ctx = None
 
-    def _get_provider_kwargs(self) -> Dict[str, Any]:
+    def _get_provider_kwargs(self) -> dict[str, Any]:
         """Get provider-specific kwargs for LLM client creation."""
         kwargs = {}
         provider = self.config.get("llm_provider", "").lower()
@@ -167,7 +158,7 @@ class TradingAgentsGraph:
 
         return kwargs
 
-    def _create_tool_nodes(self) -> Dict[str, ToolNode]:
+    def _create_tool_nodes(self) -> dict[str, ToolNode]:
         """Create tool nodes for different data sources using abstract methods."""
         return {
             "market": ToolNode(
@@ -233,7 +224,7 @@ class TradingAgentsGraph:
     def _fetch_returns(
         self, ticker: str, trade_date: str, holding_days: int = 5,
         benchmark: str = "SPY",
-    ) -> Tuple[Optional[float], Optional[float], Optional[int]]:
+    ) -> tuple[float | None, float | None, int | None]:
         """Fetch raw and alpha return for ticker over holding_days from trade_date.
 
         ``benchmark`` is the index used as the alpha baseline (resolved by the