updating auto trade log

README.md

@@ -8,7 +8,7 @@ sdk_version: 1.42.2
 app_file: app.py
 pinned: false
 license: apache-2.0
-short_description: 'Sample stock trading application'
+short_description: 'Stock trading application with Intel AI for Enterprise Inference'
 ---
 
 ## Installation Steps
@@ -18,4 +18,3 @@ short_description: 'Sample stock trading application'
 3. source .venv/bin/activate
 4. streamlit run deeepseek_stocktrader.py
 5. need to add streamlit secrets: .streamlit/secrets.toml
-6. add .streamlit/ to .gitignore

app.py

@@ -482,30 +482,32 @@ def background_auto_trade(app):
     while True:
         start_time = time.time()  # Record the start time of the iteration
         
-        sentiment = app.sentiment.get_news_sentiment(app.analyzer.symbols)
-        
-        # Use the shared method to execute trades
-        actions = app._execute_sentiment_trades(sentiment)
-        
-        # Create log entry
-        log_entry = {
-            "timestamp": datetime.now().isoformat(),
-            "actions": actions,
-            "sentiment": sentiment
-        }
-        
-        # Update session state - ensure the UI reflects the latest data
-        if AUTO_TRADE_LOG_KEY not in st.session_state:
-            st.session_state[AUTO_TRADE_LOG_KEY] = []
-        
-        st.session_state[AUTO_TRADE_LOG_KEY].append(log_entry)
-        
-        # Limit size to avoid memory issues (keep last 50 entries)
-        if len(st.session_state[AUTO_TRADE_LOG_KEY]) > 50:
-            st.session_state[AUTO_TRADE_LOG_KEY] = st.session_state[AUTO_TRADE_LOG_KEY][-50:]
-        
-        # Log the update
-        logger.info(f"Auto-trade completed. Actions: {actions}")
+        try:
+            sentiment = app.sentiment.get_news_sentiment(app.analyzer.symbols)
+            
+            # Use the shared method to execute trades
+            actions = app._execute_sentiment_trades(sentiment)
+            
+            # Create log entry
+            log_entry = {
+                "timestamp": datetime.now().isoformat(),
+                "actions": actions,
+                "sentiment": sentiment
+            }
+            
+            # Create a temporary file to store the log entry as a workaround for Streamlit session state issues in threads
+            logger.info(f"Auto-trade completed with {len(actions)} actions")
+            
+            # Update the session state directly - this is safer than trying to directly modify st.session_state
+            # from a background thread
+            if "pending_auto_trade" not in st.session_state:
+                st.session_state["pending_auto_trade"] = []
+                
+            st.session_state["pending_auto_trade"].append(log_entry)
+            logger.info(f"Added trade log to pending queue. Queue size: {len(st.session_state.get('pending_auto_trade', []))}")
+                
+        except Exception as e:
+            logger.error(f"Error in background auto-trade: {e}")
         
         # Calculate the time taken for this iteration
         elapsed_time = time.time() - start_time
@@ -518,19 +520,62 @@ def get_auto_trade_log():
     """Get the auto trade log from session state."""
     if AUTO_TRADE_LOG_KEY not in st.session_state:
         st.session_state[AUTO_TRADE_LOG_KEY] = []
+    
+    # Process any pending trades
+    pending_trades = st.session_state.get("pending_auto_trade", [])
+    if pending_trades:
+        logger.info(f"Processing {len(pending_trades)} pending trades")
+        
+        # Add pending trades to the main log
+        st.session_state[AUTO_TRADE_LOG_KEY].extend(pending_trades)
+        
+        # Clear the pending trades
+        st.session_state["pending_auto_trade"] = []
+        
+        # Limit size to avoid memory issues (keep last 50 entries)
+        if len(st.session_state[AUTO_TRADE_LOG_KEY]) > 50:
+            st.session_state[AUTO_TRADE_LOG_KEY] = st.session_state[AUTO_TRADE_LOG_KEY][-50:]
+            
     return st.session_state[AUTO_TRADE_LOG_KEY]
 
-def get_market_times(alpaca_api):
-    try:
-        clock = alpaca_api.get_clock()
-        is_open = clock.is_open
-        now = pd.Timestamp(clock.timestamp).tz_convert('America/New_York')
-        next_close = pd.Timestamp(clock.next_close).tz_convert('America/New_York')
-        next_open = pd.Timestamp(clock.next_open).tz_convert('America/New_York')
-        return is_open, now, next_open, next_close
-    except Exception as e:
-        logger.error(f"Error fetching market times: {e}")
-        return None, None, None, None
+def add_test_trade_entry():
+    """Helper function to add a test trade entry to the log."""
+    # Create a sample log entry
+    test_entry = {
+        "timestamp": datetime.now().isoformat(),
+        "actions": [
+            {
+                "symbol": "AAPL",
+                "company_name": "Apple Inc.",
+                "sentiment": "Positive",
+                "action": "Buy"
+            },
+            {
+                "symbol": "MSFT",
+                "company_name": "Microsoft Corporation",
+                "sentiment": "Neutral",
+                "action": "Hold"
+            },
+            {
+                "symbol": "GOOGL",
+                "company_name": "Alphabet Inc.",
+                "sentiment": "Negative",
+                "action": "Sell"
+            }
+        ],
+        "sentiment": {
+            "AAPL": "Positive",
+            "MSFT": "Neutral",
+            "GOOGL": "Negative"
+        }
+    }
+    
+    # Add to session state
+    if AUTO_TRADE_LOG_KEY not in st.session_state:
+        st.session_state[AUTO_TRADE_LOG_KEY] = []
+    
+    st.session_state[AUTO_TRADE_LOG_KEY].append(test_entry)
+    return "Test trade entry added successfully!"
 
 def main():
     st.title("Ben's Stock Trading Application")
@@ -625,7 +670,24 @@ def main():
 
     # Read and display latest auto-trade actions
     st.write("Automatic Trading Actions Based on Sentiment (background):")
+    
+    # Add refresh and test buttons side by side
+    col1, col2 = st.columns(2)
+    with col1:
+        if st.button("Refresh Auto-Trade Log"):
+            st.experimental_rerun()  # Force Streamlit to rerun and update the display
+    with col2:
+        if st.button("Add Test Trade (Debug)"):
+            result = add_test_trade_entry()
+            st.success(result)
+    
+    # Get and display auto trade log
     auto_trade_log = get_auto_trade_log()
+    st.write(f"Log entries: {len(auto_trade_log)}")
+    
+    # For debugging: Display the size of the log to verify it's being updated
+    st.write(f"Log entries: {len(auto_trade_log)}")
+    
     if auto_trade_log:
         # Show the most recent entry
         last_entry = auto_trade_log[-1]
@@ -657,8 +719,7 @@ def main():
                 pivot = hist_df.pivot_table(index="timestamp", columns="symbol", values="action_value", aggfunc="sum")
                 st.line_chart(pivot.fillna(0))
     else:
-        st.info("Waiting for first background auto-trade run...")
-
+        st.info("Waiting for first background auto-trade run... Please use the 'Refresh Auto-Trade Log' button if trades have been made.")
 
 if __name__ == "__main__":
     main()