Update app/daily.py

app/daily.py

@@ -7,6 +7,7 @@ from . import persist
 from .common import wrap_html
 import plotly.graph_objects as go
 import plotly.io as pio
+import plotly.express as px
 
 # ===========================================================
 # RAW DAILY FETCHER
@@ -23,7 +24,7 @@ def daily(symbol, date_end, date_start):
     return df
 
 # ===========================================================
-# PLOTLY CANDLESTICK
+# PLOTLY CANDLESTICK + VOLUME
 # ===========================================================
 def plot_candlestick(df, symbol):
     fig = go.Figure()
@@ -40,7 +41,7 @@ def plot_candlestick(df, symbol):
         decreasing_line_color='red'
     ))
 
-    # Volume as bar chart
+    # Volume as bar
     fig.add_trace(go.Bar(
         x=df['Date'],
         y=df['Volume'],
@@ -61,11 +62,36 @@ def plot_candlestick(df, symbol):
 
     return pio.to_html(fig, full_html=False, include_plotlyjs='cdn')
 
+
+# ===========================================================
+# ADDITIONAL ANALYSIS CHARTS
+# ===========================================================
+def plot_analysis_charts(df, symbol):
+    charts = ""
+
+    # 1️⃣ OHLC line chart
+    fig_line = px.line(df, x='Date', y=['Open','High','Low','Close'], title=f'{symbol} OHLC Line Chart')
+    charts += pio.to_html(fig_line, full_html=False, include_plotlyjs=False)
+
+    # 2️⃣ 20-day and 50-day moving average
+    df['MA20'] = df['Close'].rolling(20).mean()
+    df['MA50'] = df['Close'].rolling(50).mean()
+    fig_ma = px.line(df, x='Date', y=['Close','MA20','MA50'], title=f'{symbol} 20 & 50 Day Moving Avg')
+    charts += pio.to_html(fig_ma, full_html=False, include_plotlyjs=False)
+
+    # 3️⃣ Daily change %
+    fig_change = px.bar(df, x='Date', y='Change %', color='Change %', title=f'{symbol} Daily % Change',
+                        color_continuous_scale=['red','green'])
+    charts += pio.to_html(fig_change, full_html=False, include_plotlyjs=False)
+
+    return charts
+
+
 # ===========================================================
-# DAILY TABLE GENERATOR
+# DAILY TABLE + DASHBOARD
 # ===========================================================
 def fetch_daily(symbol, date_end, date_start):
-    """Return HTML table + candlestick chart of daily stock data."""
+    """Return HTML table + candlestick + analysis charts."""
     key = f"daily_{symbol}"
     if persist.exists(key, "html"):
         cached = persist.load(key, "html")
@@ -93,13 +119,21 @@ def fetch_daily(symbol, date_end, date_start):
         # Daily change %
         df["Change %"] = ((df["Close"] - df["Open"]) / df["Open"] * 100).round(2)
 
-        # Build HTML table
+        # Build HTML table with improved header CSS
         html_table = '<div style="max-height:300px; overflow:auto; font-family:Arial,sans-serif; margin-bottom:20px;">'
         html_table += '<table border="1" style="border-collapse:collapse; width:100%;">'
-        html_table += '<thead style="position:sticky; top:0; background:#1a4f8a; color:white;">'
+        html_table += '''
+            <thead style="
+                position:sticky;
+                top:0;
+                background: linear-gradient(to right,#1a4f8a,#4a7ac7);
+                color:white;
+                font-weight:bold;
+                text-align:center;
+            ">
+        '''
         html_table += '<tr><th>Date</th><th>Open</th><th>High</th><th>Low</th>'
-        html_table += '<th>Close</th><th>Volume</th><th>Change %</th></tr>'
-        html_table += '</thead><tbody>'
+        html_table += '<th>Close</th><th>Volume</th><th>Change %</th></tr></thead><tbody>'
 
         for idx, r in df.iterrows():
             row_color = "#e8f5e9" if idx % 2 == 0 else "#f5f5f5"
@@ -116,11 +150,14 @@ def fetch_daily(symbol, date_end, date_start):
             html_table += '</tr>'
         html_table += '</tbody></table></div>'
 
-        # Build candlestick chart
-        chart_html = plot_candlestick(df, symbol)
+        # Candlestick chart
+        candlestick_html = plot_candlestick(df, symbol)
+
+        # Additional analysis charts
+        analysis_html = plot_analysis_charts(df, symbol)
 
-        # Combine
-        full_html = f'<div id="daily_dashboard">{html_table}{chart_html}</div>'
+        # Combine all
+        full_html = f'<div id="daily_dashboard">{html_table}{candlestick_html}{analysis_html}</div>'
 
         persist.save(key, full_html, "html")
         return full_html