Update app.py

app.py

@@ -1,120 +1,79 @@
 import panel as pn
 import pandas as pd
 import numpy as np
-import hvplot.pandas  # noqa: F401
-from bokeh.models.formatters import NumeralTickFormatter
-from datetime import datetime, timedelta
+import hvplot.pandas
 import asyncio
-import holoviews as hv
-
-# --- Setup ---
-pn.extension('tabulator', sizing_mode="stretch_width")
-hv.extension("bokeh")
+from datetime import datetime, timedelta
 
-# --- Dummy Data Generation ---
-def generate_dummy_data(n_points=100):
-    """Generates a DataFrame with simulated stock price data."""
-    start_time = datetime.now() - timedelta(minutes=n_points)
-    time_index = pd.date_range(start=start_time, periods=n_points, freq='1min')
-    prices = 100 + np.random.randn(n_points).cumsum()
-    return pd.DataFrame({'Time': time_index, 'Price': prices}).set_index('Time')
+pn.extension('tabulator', 'plotly', sizing_mode="stretch_width")
 
+# --- Dummy Data Generator ---
+def generate_dummy_data(n=100):
+    start = datetime.now() - timedelta(minutes=n)
+    times = [start + timedelta(minutes=i) for i in range(n)]
+    prices = 100 + np.random.randn(n).cumsum()
+    return pd.DataFrame({'Time': times, 'Price': prices}).set_index('Time')
 
-def generate_ai_signal(current_price):
-    """Simple AI logic to generate trading signals."""
-    if current_price % 10 < 3:
+def generate_ai_signal(price):
+    mod = price % 10
+    if mod < 3:
         return 'BUY', 'green'
-    elif current_price % 10 > 7:
+    elif mod > 7:
         return 'SELL', 'red'
     return 'HOLD', 'orange'
 
+data = generate_dummy_data()
+signal, color = generate_ai_signal(data['Price'].iloc[-1])
 
-# --- Initial Data & Signal ---
-df = generate_dummy_data()
-current_signal, signal_color = generate_ai_signal(df['Price'].iloc[-1])
-
-# --- Dashboard Widgets ---
-symbol_input = pn.widgets.TextInput(name='Stock Symbol', value='AI_STOCK', width=150)
-update_interval = pn.widgets.IntSlider(name='Update Interval (s)', start=1, end=10, step=1, value=2, width=200)
+# --- Widgets ---
+symbol_input = pn.widgets.TextInput(name='Stock Symbol', value='AI_STOCK')
+interval_slider = pn.widgets.IntSlider(name='Update Interval (s)', start=1, end=10, step=1, value=2)
 
-signal_indicator = pn.indicators.Number(
+signal_display = pn.indicators.Number(
     name='AI Signal',
     value=0,
-    format=f'{current_signal}',
+    format=signal,
     font_size='36pt',
-    colors=[(9999, signal_color)]
+    colors=[(999, color)]
 )
 
-metrics_data = {
+metrics_table = pn.widgets.Tabulator(pd.DataFrame({
     'Metric': ['Win Rate', 'Profit Factor', 'Sharpe Ratio'],
     'Value': ['62%', '1.85', '1.2']
-}
-metrics_table = pn.widgets.Tabulator(pd.DataFrame(metrics_data), disabled=True, selectable=False)
+}), disabled=True, selectable=False)
 
-# --- Dynamic Price Stream ---
-price_stream_df = df.copy()
-price_stream = hv.streams.Buffer(price_stream_df.reset_index(), length=100)
-
-price_plot = hv.DynamicMap(
-    lambda data: data.hvplot.line(
-        x='Time',
-        y='Price',
-        line_width=3,
-        height=400,
-        xlabel='Time',
-        ylabel='Price',
-        title='Live Stock Price',
-        responsive=True
-    ).opts(yformatter=NumeralTickFormatter(format="0.00")),
-    streams=[price_stream]
-)
+chart = data.hvplot.line(y='Price', title="📈 Live Stock Price", height=400, line_width=3).opts(yformatter="%.2f")
+stream = hvplot.streams.Buffer(data, index=False, length=100)
+chart.update(stream)
 
 # --- Layout ---
 sidebar = pn.Column(
-    "## ⚙️ Controls",
-    symbol_input,
-    update_interval,
-    "## 🤖 AI Analysis",
-    signal_indicator,
-    "## 📈 Performance",
-    metrics_table,
+    "## ⚙️ Controls", symbol_input, interval_slider,
+    "## 🤖 AI Signal", signal_display,
+    "## 📊 Metrics", metrics_table,
     width=300
 )
 
-main = pn.Column(
-    price_plot
-)
+main_area = pn.Column(chart)
 
-dashboard = pn.template.FastListTemplate(
-    site="AI Trading Dashboard",
-    title=lambda: f"Live Analysis for {symbol_input.value}",
+template = pn.template.FastListTemplate(
+    site="AI Trader",
+    title="📊 AI Trading Dashboard",
     sidebar=[sidebar],
-    main=[main]
+    main=[main_area]
 )
 
-# --- Async Update Callback ---
-async def update_data():
-    """Simulate a real-time feed updating price and signal."""
+# --- Async Update Logic ---
+async def updater():
     while True:
-        await asyncio.sleep(update_interval.value)
-
-        last_time = price_stream_df.index[-1]
-        new_time = last_time + timedelta(minutes=1)
-        new_price = price_stream_df['Price'].iloc[-1] + np.random.randn() * 0.5
-        new_row = pd.DataFrame({'Time': [new_time], 'Price': [new_price]})
-
-        # Append to internal df
-        price_stream_df.loc[new_time] = new_price
-
-        # Update stream
-        price_stream.send(new_row)
-
-        # Update AI signal
-        signal, color = generate_ai_signal(new_price)
-        signal_indicator.format = signal
-        signal_indicator.colors = [(9999, color)]
-
-
-# --- Launch ---
-dashboard.servable()
-pn.state.onload(update_data)
+        await asyncio.sleep(interval_slider.value)
+        new_time = data.index[-1] + timedelta(seconds=10)
+        new_price = data['Price'].iloc[-1] + np.random.randn() * 0.5
+        new_df = pd.DataFrame([{'Time': new_time, 'Price': new_price}]).set_index('Time')
+        stream.send(new_df)
+        new_signal, new_color = generate_ai_signal(new_price)
+        signal_display.format = new_signal
+        signal_display.colors = [(999, new_color)]
+
+template.servable()
+pn.state.onload(updater)