Update app.py

app.py

@@ -4,20 +4,17 @@ import plotly.graph_objs as go
 import pandas as pd
 import ccxt
 from datetime import datetime
+from plotly.subplots import make_subplots
 
-# Initialize exchange
+# Init MEXC
 exchange = ccxt.mexc()
-
-# Fetch available markets and timeframes
 markets = exchange.load_markets()
 symbols = sorted([symbol for symbol in markets if "/USDT" in symbol])
 timeframes = list(exchange.timeframes.keys())
 
-# Default selections
 DEFAULT_SYMBOL = "BTC/USDT"
 DEFAULT_TIMEFRAME = "1h"
 
-# Fetch OHLCV data
 def fetch_ohlcv(symbol, timeframe):
     try:
         ohlcv = exchange.fetch_ohlcv(symbol, timeframe)
@@ -25,94 +22,87 @@ def fetch_ohlcv(symbol, timeframe):
         df["timestamp"] = pd.to_datetime(df["timestamp"], unit="ms")
         return df
     except Exception as e:
-        print(f"❌ Error fetching data: {e}")
+        print(f"❌ Error: {e}")
         return pd.DataFrame()
 
-# Add indicators
 def add_indicators(df):
     df = df.copy()
     df['ema12'] = df['close'].ewm(span=12).mean()
     df['ema26'] = df['close'].ewm(span=26).mean()
     df['macd'] = df['ema12'] - df['ema26']
     df['macd_signal'] = df['macd'].ewm(span=9).mean()
-
+    
     delta = df['close'].diff()
     gain = delta.clip(lower=0)
-    loss = -1 * delta.clip(upper=0)
+    loss = -delta.clip(upper=0)
     avg_gain = gain.rolling(14).mean()
     avg_loss = loss.rolling(14).mean()
     rs = avg_gain / avg_loss
     df['rsi'] = 100 - (100 / (1 + rs))
     return df
 
-# Add signals
 def add_signals(df):
     df['buy'] = (df['macd'] > df['macd_signal']) & (df['macd'].shift(1) <= df['macd_signal'].shift(1)) & (df['rsi'] < 50)
     df['sell'] = (df['macd'] < df['macd_signal']) & (df['macd'].shift(1) >= df['macd_signal'].shift(1)) & (df['rsi'] > 50)
     return df
 
-# Build the chart
 def create_chart(df):
     fig = make_subplots(rows=3, cols=1, shared_xaxes=True,
-                        vertical_spacing=0.02,
-                        row_heights=[0.6, 0.2, 0.2])
+                        vertical_spacing=0.02, row_heights=[0.6, 0.2, 0.2])
 
-    fig.add_trace(go.Candlestick(
-        x=df['timestamp'], open=df['open'], high=df['high'],
-        low=df['low'], close=df['close'],
-        name='Candlesticks'), row=1, col=1)
+    fig.add_trace(go.Candlestick(x=df['timestamp'], open=df['open'], high=df['high'],
+                                 low=df['low'], close=df['close'], name='Candles'), row=1, col=1)
 
-    fig.add_trace(go.Scatter(
-        x=df['timestamp'], y=df['rsi'],
-        line=dict(color='orange'), name='RSI'), row=2, col=1)
+    fig.add_trace(go.Scatter(x=df['timestamp'], y=df['rsi'], name='RSI',
+                             line=dict(color='orange')), row=2, col=1)
 
-    fig.add_trace(go.Scatter(
-        x=df['timestamp'], y=df['macd'], line=dict(color='blue'), name='MACD'), row=3, col=1)
+    fig.add_trace(go.Scatter(x=df['timestamp'], y=df['macd'], name='MACD',
+                             line=dict(color='blue')), row=3, col=1)
 
-    fig.add_trace(go.Scatter(
-        x=df['timestamp'], y=df['macd_signal'], line=dict(color='red'), name='Signal Line'), row=3, col=1)
+    fig.add_trace(go.Scatter(x=df['timestamp'], y=df['macd_signal'], name='MACD Signal',
+                             line=dict(color='red')), row=3, col=1)
 
+    # Signal markers
     buys = df[df['buy']]
     sells = df[df['sell']]
-    fig.add_trace(go.Scatter(x=buys['timestamp'], y=buys['close'], mode='markers', name='Buy',
-                             marker=dict(color='green', size=10, symbol='triangle-up')), row=1, col=1)
-    fig.add_trace(go.Scatter(x=sells['timestamp'], y=sells['close'], mode='markers', name='Sell',
-                             marker=dict(color='red', size=10, symbol='triangle-down')), row=1, col=1)
+    fig.add_trace(go.Scatter(x=buys['timestamp'], y=buys['close'], mode='markers',
+                             name='Buy', marker=dict(color='green', size=10, symbol='triangle-up')), row=1, col=1)
+    fig.add_trace(go.Scatter(x=sells['timestamp'], y=sells['close'], mode='markers',
+                             name='Sell', marker=dict(color='red', size=10, symbol='triangle-down')), row=1, col=1)
 
-    fig.update_layout(height=800, showlegend=True)
+    fig.update_layout(height=800, margin=dict(t=30, b=20), showlegend=True)
     return fig
 
-from plotly.subplots import make_subplots
-
-# Dash app
+# Dash App
 app = dash.Dash(__name__)
-app.title = "MEXC Crypto Signals"
+app.title = "MEXC AI Signals"
 
 app.layout = html.Div([
-    html.H2("📈 MEXC Trading Signal Dashboard"),
+    html.H2("📈 MEXC Crypto Signal Chart", style={'textAlign': 'center'}),
 
     html.Div([
         html.Label("Select Pair:"),
         dcc.Dropdown(id="pair-dropdown", options=[{"label": s, "value": s} for s in symbols],
-                     value=DEFAULT_SYMBOL)
-    ], style={'width': '30%', 'display': 'inline-block'}),
+                     value=DEFAULT_SYMBOL, style={"width": "100%"})
+    ], style={"width": "30%", "display": "inline-block"}),
 
     html.Div([
-        html.Label("Timeframe:"),
+        html.Label("Timeframes:"),
         html.Div([
             html.Button(tf, id={'type': 'tf-button', 'index': tf}, n_clicks=0,
-                        style={"margin": "2px"}) for tf in timeframes
-        ], id='tf-button-row')
-    ], style={'width': '68%', 'display': 'inline-block', 'verticalAlign': 'top'}),
+                        style={"margin": "2px", "width": "50px"}) for tf in timeframes
+        ], id="tf-button-row")
+    ], style={"width": "68%", "display": "inline-block"}),
 
-    dcc.Store(id='selected-timeframe', data=DEFAULT_TIMEFRAME),
+    dcc.Store(id="selected-timeframe", data=DEFAULT_TIMEFRAME),
     dcc.Graph(id="chart", config={"displayModeBar": True}),
+
+    html.Div(id="signal-box", style={"marginTop": "10px", "textAlign": "center", "fontSize": "16px"})
 ])
 
-# Callbacks
 @app.callback(
     Output("selected-timeframe", "data"),
-    Input({'type': 'tf-button', 'index': dash.dependencies.ALL}, 'n_clicks'),
+    Input({'type': 'tf-button', 'index': dash.dependencies.ALL}, 'n_clicks')
 )
 def update_timeframe(n_clicks_list):
     ctx = dash.callback_context
@@ -123,17 +113,24 @@ def update_timeframe(n_clicks_list):
     return timeframe
 
 @app.callback(
-    Output("chart", "figure"),
-    Input("pair-dropdown", "value"),
-    Input("selected-timeframe", "data")
+    [Output("chart", "figure"), Output("signal-box", "children")],
+    [Input("pair-dropdown", "value"), Input("selected-timeframe", "data")]
 )
 def update_chart(symbol, timeframe):
     df = fetch_ohlcv(symbol, timeframe)
     if df.empty:
-        return go.Figure()
+        return go.Figure(), "❌ No data available"
     df = add_indicators(df)
     df = add_signals(df)
-    return create_chart(df)
+
+    latest_signal = "🔍 No recent signal"
+    if df['buy'].iloc[-1]:
+        latest_signal = f"🟢 Latest Signal: BUY at {df['close'].iloc[-1]:.2f} on {df['timestamp'].iloc[-1]}"
+    elif df['sell'].iloc[-1]:
+        latest_signal = f"🔴 Latest Signal: SELL at {df['close'].iloc[-1]:.2f} on {df['timestamp'].iloc[-1]}"
+
+    fig = create_chart(df)
+    return fig, latest_signal
 
 if __name__ == "__main__":
     app.run(host="0.0.0.0", port=7860)