Update app/daily.py

app/daily.py

@@ -8,12 +8,12 @@ from .common import wrap_html
 import plotly.graph_objects as go
 import plotly.express as px
 import plotly.io as pio
+from plotly.subplots import make_subplots
 
-# ===========================================================
-# RAW DAILY FETCHER
-# ===========================================================
+# =========================
+# DAILY DATA FETCH
+# =========================
 def daily(symbol, date_end, date_start):
-    """Fetch daily OHLCV from Yahoo Finance."""
     start = dt.strptime(date_start, "%d-%m-%Y").strftime("%Y-%m-%d")
     end = dt.strptime(date_end, "%d-%m-%Y").strftime("%Y-%m-%d")
     df = yf.download(symbol + ".NS", start=start, end=end)
@@ -23,72 +23,10 @@ def daily(symbol, date_end, date_start):
     df.index.name = "Date"
     return df
 
-# ===========================================================
-# CANDLESTICK + VOLUME
-# ===========================================================
-def plot_candlestick(df, symbol):
-    fig = go.Figure()
-
-    fig.add_trace(go.Candlestick(
-        x=df['Date'],
-        open=df['Open'],
-        high=df['High'],
-        low=df['Low'],
-        close=df['Close'],
-        name='Price',
-        increasing_line_color='green',
-        decreasing_line_color='red'
-    ))
-
-    fig.add_trace(go.Bar(
-        x=df['Date'],
-        y=df['Volume'],
-        name='Volume',
-        yaxis='y2',
-        marker_color='blue',
-        opacity=0.3
-    ))
-
-    fig.update_layout(
-        title=f'{symbol} Daily Candlestick',
-        xaxis_rangeslider_visible=False,
-        yaxis=dict(title='Price'),
-        yaxis2=dict(title='Volume', overlaying='y', side='right', showgrid=False),
-        legend=dict(orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1)
-    )
-
-    # Include Plotly JS only once
-    return pio.to_html(fig, full_html=False, include_plotlyjs='cdn')
-
-# ===========================================================
-# ADDITIONAL ANALYSIS CHARTS
-# ===========================================================
-def plot_analysis_charts(df, symbol):
-    charts = ""
-
-    # 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)
-
-    # 20 & 50-day moving averages
-    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)
-
-    # Daily % change
-    df['Change %'] = ((df['Close'] - df['Open']) / df['Open'] * 100).round(2)
-    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 DASHBOARD
-# ===========================================================
+# =========================
+# DASHBOARD
+# =========================
 def fetch_daily(symbol, date_end, date_start):
-    """Return HTML table + candlestick + analysis charts."""
     key = f"daily_{symbol}"
     if persist.exists(key, "html"):
         cached = persist.load(key, "html")
@@ -105,18 +43,15 @@ def fetch_daily(symbol, date_end, date_start):
             if col in df.columns:
                 df[col] = pd.to_numeric(df[col], errors='coerce')
 
-        # Drop rows with missing OHLCV
         df = df.dropna(subset=["Open","High","Low","Close","Volume"]).reset_index()
-
-        # Format date
         df["Date"] = pd.to_datetime(df["Date"], errors='coerce')
         df = df.dropna(subset=["Date"]).reset_index(drop=True)
         df["Date"] = df["Date"].dt.strftime("%d-%b-%Y")
-
-        # Daily change %
         df["Change %"] = ((df["Close"] - df["Open"]) / df["Open"] * 100).round(2)
 
-        # Build HTML table with improved header CSS
+        # -------------------------
+        # HTML Table
+        # -------------------------
         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 += '''
@@ -126,16 +61,13 @@ def fetch_daily(symbol, date_end, date_start):
                 background: linear-gradient(to right,#1a4f8a,#4a7ac7);
                 color:white;
                 font-weight:bold;
-                text-align:center;
-            ">
+                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></thead><tbody>'
-
         for idx, r in df.iterrows():
             row_color = "#e8f5e9" if idx % 2 == 0 else "#f5f5f5"
             change_color = "green" if r["Change %"] > 0 else "red" if r["Change %"] < 0 else "black"
-
             html_table += f'<tr style="background:{row_color};">'
             html_table += f'<td>{r["Date"]}</td>'
             html_table += f'<td>{r["Open"]}</td>'
@@ -147,15 +79,51 @@ def fetch_daily(symbol, date_end, date_start):
             html_table += '</tr>'
         html_table += '</tbody></table></div>'
 
-        # Candlestick chart
-        candlestick_html = plot_candlestick(df, symbol)
-
-        # Additional analysis charts
-        analysis_html = plot_analysis_charts(df, symbol)
-
-        # Combine all in dashboard
-        full_html = f'<div id="daily_dashboard">{html_table}{candlestick_html}{analysis_html}</div>'
-
+        # -------------------------
+        # COMBINED PLOTLY FIGURE
+        # -------------------------
+        fig = make_subplots(
+            rows=3, cols=1,
+            shared_xaxes=True,
+            row_heights=[0.5, 0.25, 0.25],
+            vertical_spacing=0.05,
+            subplot_titles=("Candlestick & Volume", "MA20/MA50", "Daily % Change")
+        )
+
+        # Candlestick
+        fig.add_trace(go.Candlestick(
+            x=df['Date'], open=df['Open'], high=df['High'],
+            low=df['Low'], close=df['Close'], name='Price',
+            increasing_line_color='green', decreasing_line_color='red'
+        ), row=1, col=1)
+
+        # Volume as bar
+        fig.add_trace(go.Bar(
+            x=df['Date'], y=df['Volume'], name='Volume',
+            marker_color='blue', opacity=0.3
+        ), row=1, col=1)
+
+        # MA20 & MA50
+        df['MA20'] = df['Close'].rolling(20).mean()
+        df['MA50'] = df['Close'].rolling(50).mean()
+        fig.add_trace(go.Scatter(x=df['Date'], y=df['Close'], mode='lines', name='Close'), row=2, col=1)
+        fig.add_trace(go.Scatter(x=df['Date'], y=df['MA20'], mode='lines', name='MA20'), row=2, col=1)
+        fig.add_trace(go.Scatter(x=df['Date'], y=df['MA50'], mode='lines', name='MA50'), row=2, col=1)
+
+        # Daily % change
+        fig.add_trace(go.Bar(
+            x=df['Date'], y=df['Change %'], name='Change %',
+            marker_color=df['Change %'].apply(lambda x: 'green' if x>0 else 'red')
+        ), row=3, col=1)
+
+        fig.update_layout(height=900, showlegend=True, xaxis_rangeslider_visible=False)
+
+        plot_html = pio.to_html(fig, full_html=False, include_plotlyjs='cdn')
+
+        # -------------------------
+        # COMBINE TABLE + CHART
+        # -------------------------
+        full_html = f'<div id="daily_dashboard">{html_table}{plot_html}</div>'
         persist.save(key, full_html, "html")
         return full_html