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/__init__.py

@@ -1,3 +1,4 @@
+import contextlib
 import warnings
 
 # Load .env files at package import so DEFAULT_CONFIG's env-var overlay
@@ -20,10 +21,8 @@ except ImportError:
 # subclassed warning categories. To suppress a specific warning we must
 # install our filter AFTER langchain-core has installed its own, so import
 # it first. The package is a guaranteed transitive dep via langgraph.
-try:
+with contextlib.suppress(ImportError):
     import langchain_core  # noqa: F401
-except ImportError:
-    pass
 
 # langgraph-checkpoint 4.0.3 calls Reviver() at module load without an
 # explicit allowed_objects, which triggers a noisy pending-deprecation

tradingagents/agents/__init__.py

@@ -1,6 +1,3 @@
-from .utils.agent_utils import create_msg_delete
-from .utils.agent_states import AgentState, InvestDebateState, RiskDebateState
-
 from .analysts.fundamentals_analyst import create_fundamentals_analyst
 from .analysts.market_analyst import create_market_analyst
 from .analysts.news_analyst import create_news_analyst
@@ -8,18 +5,16 @@ from .analysts.sentiment_analyst import (
     create_sentiment_analyst,
     create_social_media_analyst,  # deprecated alias kept for back-compat
 )
-
+from .managers.portfolio_manager import create_portfolio_manager
+from .managers.research_manager import create_research_manager
 from .researchers.bear_researcher import create_bear_researcher
 from .researchers.bull_researcher import create_bull_researcher
-
 from .risk_mgmt.aggressive_debator import create_aggressive_debator
 from .risk_mgmt.conservative_debator import create_conservative_debator
 from .risk_mgmt.neutral_debator import create_neutral_debator
-
-from .managers.research_manager import create_research_manager
-from .managers.portfolio_manager import create_portfolio_manager
-
 from .trader.trader import create_trader
+from .utils.agent_states import AgentState, InvestDebateState, RiskDebateState
+from .utils.agent_utils import create_msg_delete
 
 __all__ = [
     "AgentState",

tradingagents/agents/analysts/fundamentals_analyst.py

@@ -1,14 +1,13 @@
 from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
+
 from tradingagents.agents.utils.agent_utils import (
-    get_instrument_context_from_state,
     get_balance_sheet,
     get_cashflow,
     get_fundamentals,
     get_income_statement,
-    get_insider_transactions,
+    get_instrument_context_from_state,
     get_language_instruction,
 )
-from tradingagents.dataflows.config import get_config
 
 
 def create_fundamentals_analyst(llm):

tradingagents/agents/analysts/market_analyst.py

@@ -1,12 +1,12 @@
 from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
+
 from tradingagents.agents.utils.agent_utils import (
-    get_instrument_context_from_state,
     get_indicators,
+    get_instrument_context_from_state,
     get_language_instruction,
     get_stock_data,
     get_verified_market_snapshot,
 )
-from tradingagents.dataflows.config import get_config
 
 
 def create_market_analyst(llm):

tradingagents/agents/analysts/news_analyst.py

@@ -1,13 +1,13 @@
 from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
+
 from tradingagents.agents.utils.agent_utils import (
-    get_instrument_context_from_state,
     get_global_news,
+    get_instrument_context_from_state,
     get_language_instruction,
     get_macro_indicators,
     get_news,
     get_prediction_markets,
 )
-from tradingagents.dataflows.config import get_config
 
 
 def create_news_analyst(llm):

tradingagents/agents/schemas.py

@@ -19,11 +19,10 @@ so that:
 from __future__ import annotations
 
 from enum import Enum
-from typing import Literal, Optional
+from typing import Literal
 
 from pydantic import BaseModel, Field
 
-
 # ---------------------------------------------------------------------------
 # Shared rating types
 # ---------------------------------------------------------------------------
@@ -124,15 +123,15 @@ class TraderProposal(BaseModel):
             "the research plan. Two to four sentences."
         ),
     )
-    entry_price: Optional[float] = Field(
+    entry_price: float | None = Field(
         default=None,
         description="Optional entry price target in the instrument's quote currency.",
     )
-    stop_loss: Optional[float] = Field(
+    stop_loss: float | None = Field(
         default=None,
         description="Optional stop-loss price in the instrument's quote currency.",
     )
-    position_sizing: Optional[str] = Field(
+    position_sizing: str | None = Field(
         default=None,
         description="Optional sizing guidance, e.g. '5% of portfolio'.",
     )
@@ -196,11 +195,11 @@ class PortfolioDecision(BaseModel):
             "incorporate them; otherwise rely solely on the current analysis."
         ),
     )
-    price_target: Optional[float] = Field(
+    price_target: float | None = Field(
         default=None,
         description="Optional target price in the instrument's quote currency.",
     )
-    time_horizon: Optional[str] = Field(
+    time_horizon: str | None = Field(
         default=None,
         description="Optional recommended holding period, e.g. '3-6 months'.",
     )

tradingagents/agents/utils/agent_states.py

@@ -1,6 +1,7 @@
 from typing import Annotated
-from typing_extensions import TypedDict
+
 from langgraph.graph import MessagesState
+from typing_extensions import TypedDict
 
 
 # Researcher team state

tradingagents/agents/utils/agent_utils.py

@@ -1,37 +1,50 @@
 import functools
 import logging
-from typing import Any, Mapping, Optional
+from collections.abc import Mapping
+from typing import Any
 
 import yfinance as yf
 from langchain_core.messages import HumanMessage, RemoveMessage
 
 # Import tools from separate utility files
-from tradingagents.agents.utils.core_stock_tools import (
-    get_stock_data
-)
-from tradingagents.agents.utils.technical_indicators_tools import (
-    get_indicators
-)
+from tradingagents.agents.utils.core_stock_tools import get_stock_data
 from tradingagents.agents.utils.fundamental_data_tools import (
-    get_fundamentals,
     get_balance_sheet,
     get_cashflow,
-    get_income_statement
+    get_fundamentals,
+    get_income_statement,
 )
+from tradingagents.agents.utils.macro_data_tools import get_macro_indicators
+from tradingagents.agents.utils.market_data_validation_tools import get_verified_market_snapshot
 from tradingagents.agents.utils.news_data_tools import (
-    get_news,
+    get_global_news,
     get_insider_transactions,
-    get_global_news
-)
-from tradingagents.agents.utils.macro_data_tools import (
-    get_macro_indicators
-)
-from tradingagents.agents.utils.prediction_markets_tools import (
-    get_prediction_markets
-)
-from tradingagents.agents.utils.market_data_validation_tools import (
-    get_verified_market_snapshot
+    get_news,
 )
+from tradingagents.agents.utils.prediction_markets_tools import get_prediction_markets
+from tradingagents.agents.utils.technical_indicators_tools import get_indicators
+
+# Public surface: the data tools are imported here so agents and the graph
+# import them from one place, plus the instrument/language helpers defined below.
+__all__ = [
+    "get_stock_data",
+    "get_indicators",
+    "get_fundamentals",
+    "get_balance_sheet",
+    "get_cashflow",
+    "get_income_statement",
+    "get_news",
+    "get_global_news",
+    "get_insider_transactions",
+    "get_macro_indicators",
+    "get_prediction_markets",
+    "get_verified_market_snapshot",
+    "build_instrument_context",
+    "resolve_instrument_identity",
+    "get_instrument_context_from_state",
+    "get_language_instruction",
+    "create_msg_delete",
+]
 
 logger = logging.getLogger(__name__)
 
@@ -52,7 +65,7 @@ def get_language_instruction() -> str:
     return f" Write your entire response in {lang}."
 
 
-def _clean_identity_value(value: Any) -> Optional[str]:
+def _clean_identity_value(value: Any) -> str | None:
     """Return a trimmed string, or None for empty / placeholder-ish values."""
     if not isinstance(value, str):
         return None
@@ -109,7 +122,7 @@ def resolve_instrument_identity(ticker: str) -> dict:
 def build_instrument_context(
     ticker: str,
     asset_type: str = "stock",
-    identity: Optional[Mapping[str, str]] = None,
+    identity: Mapping[str, str] | None = None,
 ) -> str:
     """Describe the exact instrument so agents preserve identity and ticker.
 
@@ -201,4 +214,4 @@ def create_msg_delete():
     return delete_messages
 
 
-        
+

tradingagents/agents/utils/core_stock_tools.py

@@ -1,5 +1,7 @@
-from langchain_core.tools import tool
 from typing import Annotated
+
+from langchain_core.tools import tool
+
 from tradingagents.dataflows.interface import route_to_vendor
 
 

tradingagents/agents/utils/fundamental_data_tools.py

@@ -1,5 +1,7 @@
-from langchain_core.tools import tool
 from typing import Annotated
+
+from langchain_core.tools import tool
+
 from tradingagents.dataflows.interface import route_to_vendor
 
 
@@ -74,4 +76,4 @@ def get_income_statement(
     Returns:
         str: A formatted report containing income statement data
     """
-    return route_to_vendor("get_income_statement", ticker, freq, curr_date)
+    return route_to_vendor("get_income_statement", ticker, freq, curr_date)

tradingagents/agents/utils/memory.py

@@ -1,8 +1,7 @@
 """Append-only markdown decision log for TradingAgents."""
 
-from typing import List, Optional
-from pathlib import Path
 import re
+from pathlib import Path
 
 from tradingagents.agents.utils.rating import parse_rating
 
@@ -51,7 +50,7 @@ class TradingMemoryLog:
 
     # --- Read path (Phase A) ---
 
-    def load_entries(self) -> List[dict]:
+    def load_entries(self) -> list[dict]:
         """Parse all entries from log. Returns list of dicts."""
         if not self._log_path or not self._log_path.exists():
             return []
@@ -64,7 +63,7 @@ class TradingMemoryLog:
                 entries.append(parsed)
         return entries
 
-    def get_pending_entries(self) -> List[dict]:
+    def get_pending_entries(self) -> list[dict]:
         """Return entries with outcome:pending (for Phase B)."""
         return [e for e in self.load_entries() if e.get("pending")]
 
@@ -162,7 +161,7 @@ class TradingMemoryLog:
         tmp_path.write_text(new_text, encoding="utf-8")
         tmp_path.replace(self._log_path)
 
-    def batch_update_with_outcomes(self, updates: List[dict]) -> None:
+    def batch_update_with_outcomes(self, updates: list[dict]) -> None:
         """Apply multiple outcome updates in a single read + atomic write.
 
         Each element of updates must have keys: ticker, trade_date,
@@ -218,7 +217,7 @@ class TradingMemoryLog:
 
     # --- Helpers ---
 
-    def _apply_rotation(self, blocks: List[str]) -> List[str]:
+    def _apply_rotation(self, blocks: list[str]) -> list[str]:
         """Drop oldest resolved blocks when their count exceeds max_entries.
 
         Pending blocks are always kept (they represent unprocessed work).
@@ -247,7 +246,7 @@ class TradingMemoryLog:
             return blocks
 
         to_drop = resolved_count - self._max_entries
-        kept: List[str] = []
+        kept: list[str] = []
         for block, is_resolved in decisions:
             if is_resolved and to_drop > 0:
                 to_drop -= 1
@@ -255,7 +254,7 @@ class TradingMemoryLog:
             kept.append(block)
         return kept
 
-    def _parse_entry(self, raw: str) -> Optional[dict]:
+    def _parse_entry(self, raw: str) -> dict | None:
         lines = raw.strip().splitlines()
         if not lines:
             return None

tradingagents/agents/utils/news_data_tools.py

@@ -1,7 +1,10 @@
+from typing import Annotated
+
 from langchain_core.tools import tool
-from typing import Annotated, Optional
+
 from tradingagents.dataflows.interface import route_to_vendor
 
+
 @tool
 def get_news(
     ticker: Annotated[str, "Ticker symbol"],
@@ -23,8 +26,8 @@ def get_news(
 @tool
 def get_global_news(
     curr_date: Annotated[str, "Current date in yyyy-mm-dd format"],
-    look_back_days: Annotated[Optional[int], "Days to look back; omit to use the configured default"] = None,
-    limit: Annotated[Optional[int], "Max articles to return; omit to use the configured default"] = None,
+    look_back_days: Annotated[int | None, "Days to look back; omit to use the configured default"] = None,
+    limit: Annotated[int | None, "Max articles to return; omit to use the configured default"] = None,
 ) -> str:
     """
     Retrieve global news data.

tradingagents/agents/utils/rating.py

@@ -12,11 +12,9 @@ Centralising it here avoids drift between those call sites.
 from __future__ import annotations
 
 import re
-from typing import Tuple
-
 
 # Canonical, ordered 5-tier scale (most bullish to most bearish).
-RATINGS_5_TIER: Tuple[str, ...] = (
+RATINGS_5_TIER: tuple[str, ...] = (
     "Buy", "Overweight", "Hold", "Underweight", "Sell",
 )
 

tradingagents/agents/utils/structured.py

@@ -19,7 +19,8 @@ all three agents log the same warnings when fallback fires.
 from __future__ import annotations
 
 import logging
-from typing import Any, Callable, Optional, TypeVar
+from collections.abc import Callable
+from typing import Any, TypeVar
 
 from pydantic import BaseModel
 
@@ -28,7 +29,7 @@ logger = logging.getLogger(__name__)
 T = TypeVar("T", bound=BaseModel)
 
 
-def bind_structured(llm: Any, schema: type[T], agent_name: str) -> Optional[Any]:
+def bind_structured(llm: Any, schema: type[T], agent_name: str) -> Any | None:
     """Return ``llm.with_structured_output(schema)`` or ``None`` if unsupported.
 
     Logs a warning when the binding fails so the user understands the agent
@@ -46,7 +47,7 @@ def bind_structured(llm: Any, schema: type[T], agent_name: str) -> Optional[Any]
 
 
 def invoke_structured_or_freetext(
-    structured_llm: Optional[Any],
+    structured_llm: Any | None,
     plain_llm: Any,
     prompt: Any,
     render: Callable[[T], str],

tradingagents/agents/utils/technical_indicators_tools.py

@@ -1,7 +1,10 @@
-from langchain_core.tools import tool
 from typing import Annotated
+
+from langchain_core.tools import tool
+
 from tradingagents.dataflows.interface import route_to_vendor
 
+
 @tool
 def get_indicators(
     symbol: Annotated[str, "ticker symbol of the company"],
@@ -29,4 +32,4 @@ def get_indicators(
             results.append(route_to_vendor("get_indicators", symbol, ind, curr_date, look_back_days))
         except ValueError as e:
             results.append(str(e))
-    return "\n\n".join(results)
+    return "\n\n".join(results)

tradingagents/dataflows/alpha_vantage.py

@@ -1,5 +1,23 @@
-# Import functions from specialized modules
-from .alpha_vantage_stock import get_stock
+# Aggregates the per-category Alpha Vantage implementations into one module the
+# vendor router imports from; the imports below are the public surface.
+from .alpha_vantage_fundamentals import (
+    get_balance_sheet,
+    get_cashflow,
+    get_fundamentals,
+    get_income_statement,
+)
 from .alpha_vantage_indicator import get_indicator
-from .alpha_vantage_fundamentals import get_fundamentals, get_balance_sheet, get_cashflow, get_income_statement
-from .alpha_vantage_news import get_news, get_global_news, get_insider_transactions
+from .alpha_vantage_news import get_global_news, get_insider_transactions, get_news
+from .alpha_vantage_stock import get_stock
+
+__all__ = [
+    "get_balance_sheet",
+    "get_cashflow",
+    "get_fundamentals",
+    "get_income_statement",
+    "get_indicator",
+    "get_global_news",
+    "get_insider_transactions",
+    "get_news",
+    "get_stock",
+]

tradingagents/dataflows/alpha_vantage_indicator.py

@@ -1,4 +1,5 @@
-from .alpha_vantage_common import _make_api_request, AlphaVantageNotConfiguredError
+from .alpha_vantage_common import AlphaVantageNotConfiguredError, _make_api_request
+
 
 def get_indicator(
     symbol: str,
@@ -25,6 +26,7 @@ def get_indicator(
         String containing indicator values and description
     """
     from datetime import datetime
+
     from dateutil.relativedelta import relativedelta
 
     supported_indicators = {
@@ -98,21 +100,7 @@ def get_indicator(
                 "series_type": series_type,
                 "datatype": "csv"
             })
-        elif indicator == "macd":
-            data = _make_api_request("MACD", {
-                "symbol": symbol,
-                "interval": interval,
-                "series_type": series_type,
-                "datatype": "csv"
-            })
-        elif indicator == "macds":
-            data = _make_api_request("MACD", {
-                "symbol": symbol,
-                "interval": interval,
-                "series_type": series_type,
-                "datatype": "csv"
-            })
-        elif indicator == "macdh":
+        elif indicator == "macd" or indicator == "macds" or indicator == "macdh":
             data = _make_api_request("MACD", {
                 "symbol": symbol,
                 "interval": interval,

tradingagents/dataflows/alpha_vantage_news.py

@@ -1,5 +1,6 @@
 from .alpha_vantage_common import _make_api_request, format_datetime_for_api
 
+
 def get_news(ticker, start_date, end_date) -> dict[str, str] | str:
     """Returns live and historical market news & sentiment data from premier news outlets worldwide.
 
@@ -68,4 +69,4 @@ def get_insider_transactions(symbol: str) -> dict[str, str] | str:
         "symbol": symbol,
     }
 
-    return _make_api_request("INSIDER_TRANSACTIONS", params)
+    return _make_api_request("INSIDER_TRANSACTIONS", params)

tradingagents/dataflows/alpha_vantage_stock.py

@@ -1,5 +1,7 @@
 from datetime import datetime
-from .alpha_vantage_common import _make_api_request, _filter_csv_by_date_range
+
+from .alpha_vantage_common import _filter_csv_by_date_range, _make_api_request
+
 
 def get_stock(
     symbol: str,
@@ -35,4 +37,4 @@ def get_stock(
 
     response = _make_api_request("TIME_SERIES_DAILY_ADJUSTED", params)
 
-    return _filter_csv_by_date_range(response, start_date, end_date)
+    return _filter_csv_by_date_range(response, start_date, end_date)

tradingagents/dataflows/config.py

@@ -1,10 +1,9 @@
 from copy import deepcopy
-from typing import Dict, Optional
 
 import tradingagents.default_config as default_config
 
 # Use default config but allow it to be overridden
-_config: Optional[Dict] = None
+_config: dict | None = None
 
 
 def initialize_config():
@@ -14,7 +13,7 @@ def initialize_config():
         _config = deepcopy(default_config.DEFAULT_CONFIG)
 
 
-def set_config(config: Dict):
+def set_config(config: dict):
     """Update the configuration with custom values.
 
     Dict-valued keys (e.g. ``data_vendors``) are merged one level deep so a
@@ -31,7 +30,7 @@ def set_config(config: Dict):
             _config[key] = value
 
 
-def get_config() -> Dict:
+def get_config() -> dict:
     """Get the current configuration."""
     if _config is None:
         initialize_config()

tradingagents/dataflows/market_data_validator.py

@@ -10,7 +10,7 @@ claim. Deterministic, no LLM involved.
 
 from __future__ import annotations
 
-from typing import Iterable, Optional
+from collections.abc import Iterable
 
 import pandas as pd
 from stockstats import wrap
@@ -63,7 +63,7 @@ def build_verified_market_snapshot(
     symbol: str,
     curr_date: str,
     look_back_days: int = 30,
-    indicators: Optional[Iterable[str]] = None,
+    indicators: Iterable[str] | None = None,
 ) -> str:
     """Render a ground-truth snapshot: latest OHLCV row, indicators, recent closes."""
     # `df` keeps the original capitalized OHLCV columns (Open/High/Low/Close/

tradingagents/dataflows/utils.py

@@ -1,10 +1,9 @@
-import os
 import re
-import json
-import pandas as pd
-from datetime import date, timedelta, datetime
+from datetime import date, datetime, timedelta
 from typing import Annotated
 
+import pandas as pd
+
 SavePathType = Annotated[str, "File path to save data. If None, data is not saved."]
 
 # Tickers can contain letters, digits, dot, dash, underscore, caret

tradingagents/dataflows/yfinance_news.py

@@ -1,9 +1,9 @@
 """yfinance-based news data fetching functions."""
 
-from typing import Optional
+import contextlib
+from datetime import datetime
 
 import yfinance as yf
-from datetime import datetime
 from dateutil.relativedelta import relativedelta
 
 from .config import get_config
@@ -28,10 +28,8 @@ def _extract_article_data(article: dict) -> dict:
         pub_date_str = content.get("pubDate", "")
         pub_date = None
         if pub_date_str:
-            try:
+            with contextlib.suppress(ValueError, AttributeError):
                 pub_date = datetime.fromisoformat(pub_date_str.replace("Z", "+00:00"))
-            except (ValueError, AttributeError):
-                pass
 
         return {
             "title": title,
@@ -47,10 +45,8 @@ def _extract_article_data(article: dict) -> dict:
         pub_date = None
         ts = article.get("providerPublishTime")
         if ts:
-            try:
+            with contextlib.suppress(ValueError, OSError, TypeError):
                 pub_date = datetime.fromtimestamp(ts)
-            except (ValueError, OSError, TypeError):
-                pass
         return {
             "title": article.get("title", "No title"),
             "summary": article.get("summary", ""),
@@ -131,8 +127,8 @@ def get_news_yfinance(
 
 def get_global_news_yfinance(
     curr_date: str,
-    look_back_days: Optional[int] = None,
-    limit: Optional[int] = None,
+    look_back_days: int | None = None,
+    limit: int | None = None,
 ) -> str:
     """
     Retrieve global/macro economic news using yfinance Search.

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

tradingagents/llm_clients/anthropic_client.py

@@ -1,5 +1,5 @@
 import re
-from typing import Any, Optional
+from typing import Any
 
 from langchain_anthropic import ChatAnthropic
 
@@ -43,7 +43,7 @@ class NormalizedChatAnthropic(ChatAnthropic):
 class AnthropicClient(BaseLLMClient):
     """Client for Anthropic Claude models."""
 
-    def __init__(self, model: str, base_url: Optional[str] = None, **kwargs):
+    def __init__(self, model: str, base_url: str | None = None, **kwargs):
         super().__init__(model, base_url, **kwargs)
 
     def get_llm(self) -> Any:

tradingagents/llm_clients/api_key_env.py

@@ -11,10 +11,7 @@ prompts for it automatically instead of failing on first API call.
 
 from __future__ import annotations
 
-from typing import Optional
-
-
-PROVIDER_API_KEY_ENV: dict[str, Optional[str]] = {
+PROVIDER_API_KEY_ENV: dict[str, str | None] = {
     "openai":     "OPENAI_API_KEY",
     "anthropic":  "ANTHROPIC_API_KEY",
     "google":     "GOOGLE_API_KEY",
@@ -47,7 +44,7 @@ PROVIDER_API_KEY_ENV: dict[str, Optional[str]] = {
 }
 
 
-def get_api_key_env(provider: str) -> Optional[str]:
+def get_api_key_env(provider: str) -> str | None:
     """Return the env var name for `provider`'s API key, or None if not applicable.
 
     Unknown providers also return None — callers should treat that as

tradingagents/llm_clients/azure_client.py

@@ -1,10 +1,9 @@
 import os
-from typing import Any, Optional
+from typing import Any
 
 from langchain_openai import AzureChatOpenAI
 
 from .base_client import BaseLLMClient, normalize_content
-from .validators import validate_model
 
 _PASSTHROUGH_KWARGS = (
     "timeout", "max_retries", "api_key", "reasoning_effort", "temperature",
@@ -29,7 +28,7 @@ class AzureOpenAIClient(BaseLLMClient):
         OPENAI_API_VERSION: API version (e.g. 2025-03-01-preview)
     """
 
-    def __init__(self, model: str, base_url: Optional[str] = None, **kwargs):
+    def __init__(self, model: str, base_url: str | None = None, **kwargs):
         super().__init__(model, base_url, **kwargs)
 
     def get_llm(self) -> Any:

tradingagents/llm_clients/base_client.py

@@ -1,6 +1,6 @@
-from abc import ABC, abstractmethod
-from typing import Any, Optional
 import warnings
+from abc import ABC, abstractmethod
+from typing import Any
 
 
 def normalize_content(response):
@@ -25,7 +25,7 @@ def normalize_content(response):
 class BaseLLMClient(ABC):
     """Abstract base class for LLM clients."""
 
-    def __init__(self, model: str, base_url: Optional[str] = None, **kwargs):
+    def __init__(self, model: str, base_url: str | None = None, **kwargs):
         self.model = model
         self.base_url = base_url
         self.kwargs = kwargs

tradingagents/llm_clients/capabilities.py

@@ -18,7 +18,6 @@ import re
 from dataclasses import dataclass
 from typing import Literal
 
-
 StructuredMethod = Literal[
     "function_calling",  # uses tools; respects supports_tool_choice
     "json_mode",         # uses response_format={"type":"json_object"}

tradingagents/llm_clients/factory.py

@@ -1,11 +1,11 @@
-from typing import Optional
 
 from .base_client import BaseLLMClient
 
+
 def create_llm_client(
     provider: str,
     model: str,
-    base_url: Optional[str] = None,
+    base_url: str | None = None,
     **kwargs,
 ) -> BaseLLMClient:
     """Create an LLM client for the specified provider.

tradingagents/llm_clients/google_client.py

@@ -1,4 +1,4 @@
-from typing import Any, Optional
+from typing import Any
 
 from langchain_google_genai import ChatGoogleGenerativeAI
 
@@ -20,7 +20,7 @@ class NormalizedChatGoogleGenerativeAI(ChatGoogleGenerativeAI):
 class GoogleClient(BaseLLMClient):
     """Client for Google Gemini models."""
 
-    def __init__(self, model: str, base_url: Optional[str] = None, **kwargs):
+    def __init__(self, model: str, base_url: str | None = None, **kwargs):
         super().__init__(model, base_url, **kwargs)
 
     def get_llm(self) -> Any:

tradingagents/llm_clients/model_catalog.py

@@ -2,14 +2,12 @@
 
 from __future__ import annotations
 
-from typing import Dict, List, Tuple
-
-ModelOption = Tuple[str, str]
-ProviderModeOptions = Dict[str, Dict[str, List[ModelOption]]]
+ModelOption = tuple[str, str]
+ProviderModeOptions = dict[str, dict[str, list[ModelOption]]]
 
 # Providers that serve many / frequently-changing models: offer only "Custom
 # model ID" rather than a list that goes stale.
-_CUSTOM_ONLY: Dict[str, List[ModelOption]] = {
+_CUSTOM_ONLY: dict[str, list[ModelOption]] = {
     "quick": [("Custom model ID", "custom")],
     "deep": [("Custom model ID", "custom")],
 }
@@ -18,7 +16,7 @@ _CUSTOM_ONLY: Dict[str, List[ModelOption]] = {
 # Shared model list for GLM via Z.AI (international) and BigModel (China).
 # Source: docs.z.ai (GLM Coding Plan supported models + LLM guides).
 # All GLM 4.7+ entries support thinking mode via thinking={"type":"enabled"}.
-_GLM_MODELS: Dict[str, List[ModelOption]] = {
+_GLM_MODELS: dict[str, list[ModelOption]] = {
     "quick": [
         ("GLM-5-Turbo - Fast, switchable thinking modes", "glm-5-turbo"),
         ("GLM-4.7 - Previous-gen flagship", "glm-4.7"),
@@ -44,7 +42,7 @@ _GLM_MODELS: Dict[str, List[ModelOption]] = {
 # the backing model. Users who want a specific generation pick it
 # explicitly; users who really want auto-latest can enter the alias via
 # "Custom model ID".
-_QWEN_MODELS: Dict[str, List[ModelOption]] = {
+_QWEN_MODELS: dict[str, list[ModelOption]] = {
     "quick": [
         ("Qwen 3.6 Flash - Latest fast, agentic coding + vision-language", "qwen3.6-flash"),
         ("Qwen 3.5 Flash - Previous-gen fast", "qwen3.5-flash"),
@@ -62,7 +60,7 @@ _QWEN_MODELS: Dict[str, List[ModelOption]] = {
 # Shared model list for MiniMax's global and CN endpoints (same IDs).
 # Full official lineup per platform.minimax.io/docs/api-reference/text-openai-api.
 # All M2.x models share a 204,800-token context window.
-_MINIMAX_MODELS: Dict[str, List[ModelOption]] = {
+_MINIMAX_MODELS: dict[str, list[ModelOption]] = {
     "quick": [
         ("MiniMax-M2.7-highspeed - Faster M2.7, 204K ctx, ~100 TPS", "MiniMax-M2.7-highspeed"),
         ("MiniMax-M2.5-highspeed - Previous-gen highspeed, 204K ctx", "MiniMax-M2.5-highspeed"),
@@ -198,12 +196,12 @@ MODEL_OPTIONS: ProviderModeOptions = {
 }
 
 
-def get_model_options(provider: str, mode: str) -> List[ModelOption]:
+def get_model_options(provider: str, mode: str) -> list[ModelOption]:
     """Return shared model options for a provider and selection mode."""
     return MODEL_OPTIONS[provider.lower()][mode]
 
 
-def get_known_models() -> Dict[str, List[str]]:
+def get_known_models() -> dict[str, list[str]]:
     """Build known model names from the shared CLI catalog."""
     return {
         provider: sorted(

tradingagents/llm_clients/validators.py

@@ -2,7 +2,6 @@
 
 from .model_catalog import get_known_models
 
-
 # Providers whose model names are user-defined (local servers, relays, hosted
 # OpenAI-compatible endpoints serving many models), so any model string is
 # accepted without warning.