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/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.