Update app/daily.py

app/daily.py

@@ -4,30 +4,31 @@ import pandas as pd
 from datetime import datetime as dt
 import traceback
 from . import persist
-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
-
-# =========================
-# DAILY DATA FETCH
-# =========================
+
+# ============================================================
+# DAILY DATA FETCH (DO NOT CHANGE)
+# ============================================================
 def daily(symbol, date_end, date_start):
     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)
+
+    # Flatten multi-index columns
     if isinstance(df.columns, pd.MultiIndex):
         df.columns = df.columns.get_level_values(0)
+
     df.columns.name = None
     df.index.name = "Date"
     return df
 
-# =========================
+
+# ============================================================
 # DASHBOARD
-# =========================
+# ============================================================
 def fetch_daily(symbol, date_end, date_start):
     key = f"daily_{symbol}"
+
     if persist.exists(key, "html"):
         cached = persist.load(key, "html")
         if cached:
@@ -35,97 +36,168 @@ def fetch_daily(symbol, date_end, date_start):
 
     try:
         df = daily(symbol, date_end, date_start)
-        if df.empty:
-            return wrap_html(f"<h1>No daily data for {symbol}</h1>")
-
-        # Ensure numeric columns
-        for col in ["Open","High","Low","Close","Volume"]:
-            if col in df.columns:
-                df[col] = pd.to_numeric(df[col], errors='coerce')
-
-        df = df.dropna(subset=["Open","High","Low","Close","Volume"]).reset_index()
-        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")
-        df["Change %"] = ((df["Close"] - df["Open"]) / df["Open"] * 100).round(2)
-
-        # -------------------------
-        # 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 += '''
-            <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></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>'
-            html_table += f'<td>{r["High"]}</td>'
-            html_table += f'<td>{r["Low"]}</td>'
-            html_table += f'<td>{r["Close"]}</td>'
-            html_table += f'<td>{r["Volume"]}</td>'
-            html_table += f'<td style="color:{change_color}; font-weight:600;">{r["Change %"]}%</td>'
-            html_table += '</tr>'
-        html_table += '</tbody></table></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
+        if df is None or df.empty:
+            return "<h1>No data</h1>"
+
+        # -------------------------------
+        # CLEAN & FORMAT
+        # -------------------------------
+        df = df.reset_index()
+
+        df["Date"] = pd.to_datetime(df["Date"], errors="coerce")
+        df = df.dropna(subset=["Date"])
+
+        for c in ["Open", "High", "Low", "Close", "Volume"]:
+            df[c] = pd.to_numeric(df[c], errors="coerce")
+
+        df = df.dropna()
+        df["DateStr"] = df["Date"].dt.strftime("%d-%b-%Y")
+
+        df["MA20"] = df["Close"].rolling(20).mean()
+        df["MA50"] = df["Close"].rolling(50).mean()
+
+        # -------------------------------
+        # TABLE HTML
+        # -------------------------------
+        table_rows = ""
+        for i, r in df.iterrows():
+            color = "#e8f5e9" if i % 2 == 0 else "#f5f5f5"
+            table_rows += f"""
+            <tr style="background:{color}">
+                <td>{r['DateStr']}</td>
+                <td>{r['Open']:.2f}</td>
+                <td>{r['High']:.2f}</td>
+                <td>{r['Low']:.2f}</td>
+                <td>{r['Close']:.2f}</td>
+                <td>{int(r['Volume'])}</td>
+            </tr>
+            """
+
+        table_html = f"""
+        <div class="table-wrap">
+        <table>
+            <thead>
+                <tr>
+                    <th>Date</th><th>Open</th><th>High</th>
+                    <th>Low</th><th>Close</th><th>Volume</th>
+                </tr>
+            </thead>
+            <tbody>{table_rows}</tbody>
+        </table>
+        </div>
+        """
+
+        # -------------------------------
+        # FULL HTML (IMPORTANT)
+        # -------------------------------
+        html = f"""
+<!DOCTYPE html>
+<html>
+<head>
+<meta charset="utf-8">
+<title>{symbol} Daily Dashboard</title>
+
+<script src="https://cdn.plot.ly/plotly-2.27.0.min.js"></script>
+
+<style>
+body {{
+    font-family: Arial, sans-serif;
+    margin: 10px;
+    background: #f4f6f9;
+}}
+
+.table-wrap {{
+    max-height: 300px;
+    overflow-y: auto;
+    margin-bottom: 20px;
+}}
+
+table {{
+    border-collapse: collapse;
+    width: 100%;
+    background: white;
+}}
+
+th {{
+    position: sticky;
+    top: 0;
+    background: linear-gradient(to right,#1a4f8a,#4a7ac7);
+    color: white;
+    padding: 6px;
+}}
+
+td {{
+    padding: 6px;
+    text-align: right;
+}}
+
+td:first-child {{
+    text-align: left;
+}}
+.chart {{
+    margin-bottom: 30px;
+}}
+</style>
+</head>
+
+<body>
+
+<h2>{symbol} – Daily Price Table</h2>
+{table_html}
+
+<h2>Candlestick & Volume</h2>
+<div id="candle" class="chart"></div>
+
+<h2>Moving Averages</h2>
+<div id="ma" class="chart"></div>
+
+<script>
+const dates = {df["DateStr"].tolist()};
+const openp = {df["Open"].round(2).tolist()};
+const highp = {df["High"].round(2).tolist()};
+const lowp  = {df["Low"].round(2).tolist()};
+const closep= {df["Close"].round(2).tolist()};
+const volume= {df["Volume"].astype(int).tolist()};
+const ma20  = {df["MA20"].round(2).fillna(None).tolist()};
+const ma50  = {df["MA50"].round(2).fillna(None).tolist()};
+
+Plotly.newPlot("candle", [
+    {{
+        x: dates,
+        open: openp,
+        high: highp,
+        low: lowp,
+        close: closep,
+        type: "candlestick",
+        name: "Price"
+    }},
+    {{
+        x: dates,
+        y: volume,
+        type: "bar",
+        yaxis: "y2",
+        name: "Volume",
+        opacity: 0.3
+    }}
+], {{
+    yaxis: {{title: "Price"}},
+    yaxis2: {{overlaying: "y", side: "right", title: "Volume"}},
+    xaxis: {{rangeslider: {{visible:false}}}}
+}});
+
+Plotly.newPlot("ma", [
+    {{x: dates, y: closep, type:"scatter", name:"Close"}},
+    {{x: dates, y: ma20, type:"scatter", name:"MA20"}},
+    {{x: dates, y: ma50, type:"scatter", name:"MA50"}}
+]);
+</script>
+
+</body>
+</html>
+"""
+
+        persist.save(key, html, "html")
+        return html
 
     except Exception as e:
-        return wrap_html(f"<h1>Error fetch_daily: {e}</h1><pre>{traceback.format_exc()}</pre>")
+        return f"<pre>{traceback.format_exc()}</pre>"