Update daily.py

daily.py

@@ -1,42 +1,40 @@
 # daily.py
-import pandas as pd
 import yfinance as yf
-from common import format_number, format_large_number, html_card, make_table, wrap_html, clean_df
+import pandas as pd
+from common import wrap_plotly_html, make_table
 from indicater import calculate_indicators
 from chart_builder import build_chart
 
 def fetch_daily(symbol):
     """
-    Fetch real daily stock data from Yahoo Finance, calculate indicators,
-    build chart and table, and return full HTML.
+    Fetch daily OHLC + volume data for the past 1 year and render as HTML chart + table
+    with selectable indicators (via script in chart_builder).
     """
+    yfsymbol = f"{symbol}.NS"
     try:
-        # 1. Fetch daily OHLCV data
-        yf_symbol = f"{symbol}.NS"  # NSE stocks; adjust for your exchange
-        df = yf.download(yf_symbol, period="1y", interval="1d", progress=False)
+        # Download daily data
+        df = yf.download(yfsymbol, period="1y", interval="1d").round(2)
+
         if df.empty:
-            return f"<h3>No daily data found for {symbol}</h3>"
+            return f"<h1>No daily data for {symbol}</h1>"
 
-        # 2. Handle multi-level columns (take 0th level)
+        # Handle multilevel columns (take 0th level)
         if isinstance(df.columns, pd.MultiIndex):
             df.columns = df.columns.get_level_values(0)
 
-        df = clean_df(df)
+        # Format table HTML for last 30 rows
+        table_html = make_table(df.tail(30))
 
-        # 3. Calculate indicators
+        # Calculate indicators
         indicators = calculate_indicators(df)
 
-        # 4. Build Plotly chart with indicators
-        chart_html = build_chart(df, indicators, symbol=symbol)
-
-        # 5. Format table
-        table_html = make_table(df)
+        # Build Plotly chart with main + volume subplot + subplots for indicators
+        chart_html = build_chart(df, indicators, symbol)
 
-        # 6. Wrap chart + table in card layout
-        content_html = html_card(f"{symbol} Daily Data", chart_html + table_html)
+        # Wrap chart + table together
+        full_html = wrap_plotly_html(chart_html, table_html)
 
-        # 7. Return full HTML
-        return wrap_html(content_html, title=f"{symbol} Daily Data")
+        return full_html
 
     except Exception as e:
-        return f"<h3>Error fetching daily data for {symbol}:</h3><pre>{e}</pre>"
+        return f"<h1>Error fetching daily data</h1><p>{str(e)}</p>"