From 8d3205043e4f683cc19597e6a2f0e5b7cb9c1314 Mon Sep 17 00:00:00 2001
From: Youssef Aitousarrah <youssef.aitousarrah@gmail.com>
Date: Mon, 16 Feb 2026 13:43:30 -0800
Subject: [PATCH] Update

---
 scripts/run_daily_discovery.py                      |  1 -
 .../dataflows/discovery/scanners/options_flow.py    |  3 +--
 tradingagents/ui/pages/performance.py               | 13 +++----------
 3 files changed, 4 insertions(+), 13 deletions(-)

diff --git a/scripts/run_daily_discovery.py b/scripts/run_daily_discovery.py
index 7936d3ed..d854eb40 100755
--- a/scripts/run_daily_discovery.py
+++ b/scripts/run_daily_discovery.py
@@ -19,7 +19,6 @@ Scheduling (cron):
 """
 
 import argparse
-import json
 import os
 import sys
 from datetime import datetime
diff --git a/tradingagents/dataflows/discovery/scanners/options_flow.py b/tradingagents/dataflows/discovery/scanners/options_flow.py
index 67c267c4..052c9fff 100644
--- a/tradingagents/dataflows/discovery/scanners/options_flow.py
+++ b/tradingagents/dataflows/discovery/scanners/options_flow.py
@@ -76,8 +76,7 @@ class OptionsFlowScanner(BaseScanner):
 
         with ThreadPoolExecutor(max_workers=self.max_workers) as pool:
             futures = {
-                pool.submit(self._analyze_ticker_options, ticker): ticker
-                for ticker in universe
+                pool.submit(self._analyze_ticker_options, ticker): ticker for ticker in universe
             }
             for future in as_completed(futures):
                 try:
diff --git a/tradingagents/ui/pages/performance.py b/tradingagents/ui/pages/performance.py
index 9467cdbd..ec9095be 100644
--- a/tradingagents/ui/pages/performance.py
+++ b/tradingagents/ui/pages/performance.py
@@ -43,15 +43,9 @@ def render() -> None:
     # Weighted averages only over strategies that have evaluated data (non-NaN)
     eval_df = df.dropna(subset=["Win Rate", "Avg Return"])
     eval_trades = eval_df["Count"].sum()
-    avg_wr = (
-        (eval_df["Win Rate"] * eval_df["Count"]).sum() / eval_trades
-        if eval_trades > 0
-        else 0
-    )
+    avg_wr = (eval_df["Win Rate"] * eval_df["Count"]).sum() / eval_trades if eval_trades > 0 else 0
     avg_ret = (
-        (eval_df["Avg Return"] * eval_df["Count"]).sum() / eval_trades
-        if eval_trades > 0
-        else 0
+        (eval_df["Avg Return"] * eval_df["Count"]).sum() / eval_trades if eval_trades > 0 else 0
     )
     n_strategies = len(df)
 
@@ -358,8 +352,7 @@ def _render_recommendation_history(template: dict) -> None:
     # ---- Full history table ----
     st.markdown("<div style='height:1rem;'></div>", unsafe_allow_html=True)
     st.markdown(
-        '<div class="section-title">All Picks '
-        '<span class="accent">// detail table</span></div>',
+        '<div class="section-title">All Picks ' '<span class="accent">// detail table</span></div>',
         unsafe_allow_html=True,
     )
     _render_history_table(filtered)