Update app.py

app.py

@@ -1,17 +1,47 @@
 import gradio as gr
+import requests
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
 import matplotlib.dates as mdates
 from io import BytesIO
+from datetime import datetime
 from PIL import Image
-import requests
 
-# ------------------- Indicator Calculations -------------------
+def get_price_data(symbol="BTCUSDT", interval="1h", limit=100):
+    url = f"https://api.mexc.com/api/v3/klines?symbol={symbol}&interval={interval}&limit={limit}"
+    response = requests.get(url)
+    data = response.json()
+    df = pd.DataFrame(data, columns=[
+        'timestamp', 'open', 'high', 'low', 'close', 'volume',
+        'close_time', 'quote_asset_volume', 'number_of_trades',
+        'taker_buy_base_vol', 'taker_buy_quote_vol', 'ignore'
+    ])
+    df['timestamp'] = pd.to_datetime(df['timestamp'], unit='ms')
+    df = df[['timestamp', 'open', 'high', 'low', 'close', 'volume']].astype(float)
+    return df
 
-def calculate_ema(df, period):
+def calculate_ema(df, period=20):
     return df['close'].ewm(span=period, adjust=False).mean()
 
+def calculate_supertrend(df, period=10, multiplier=3):
+    hl2 = (df['high'] + df['low']) / 2
+    atr = df['high'].rolling(period).max() - df['low'].rolling(period).min()
+    atr = atr.rolling(period).mean()
+    upper_band = hl2 + (multiplier * atr)
+    lower_band = hl2 - (multiplier * atr)
+    supertrend = [True] * len(df)
+
+    for i in range(1, len(df)):
+        if df['close'][i] > upper_band[i - 1]:
+            supertrend[i] = True
+        elif df['close'][i] < lower_band[i - 1]:
+            supertrend[i] = False
+        else:
+            supertrend[i] = supertrend[i - 1]
+
+    return pd.Series(supertrend)
+
 def calculate_rsi(df, period=14):
     delta = df['close'].diff()
     gain = delta.clip(lower=0)
@@ -21,21 +51,6 @@ def calculate_rsi(df, period=14):
     rs = avg_gain / avg_loss
     return 100 - (100 / (1 + rs))
 
-def calculate_supertrend(df, period=10, multiplier=3):
-    hl2 = (df['high'] + df['low']) / 2
-    atr = df['high'].rolling(period).max() - df['low'].rolling(period).min()
-    upperband = hl2 + (multiplier * atr)
-    lowerband = hl2 - (multiplier * atr)
-    trend = [True] * len(df)
-    for i in range(1, len(df)):
-        if df['close'].iloc[i] > upperband.iloc[i - 1]:
-            trend[i] = True
-        elif df['close'].iloc[i] < lowerband.iloc[i - 1]:
-            trend[i] = False
-        else:
-            trend[i] = trend[i - 1]
-    return trend
-
 def detect_rsi_divergence(df):
     df['rsi'] = calculate_rsi(df)
     df['bullish_div'] = False
@@ -53,11 +68,8 @@ def detect_rsi_divergence(df):
             df['rsi'].iloc[i] < df['rsi'].iloc[i - 1] < df['rsi'].iloc[i - 2]
         ):
             df.at[df.index[i], 'bearish_div'] = True
-
     return df
 
-# ------------------- Signal Generator -------------------
-
 def generate_combined_signal(df):
     df['ema_50'] = calculate_ema(df, 50)
     df['ema_200'] = calculate_ema(df, 200)
@@ -86,33 +98,28 @@ def generate_combined_signal(df):
         signal += " + 📉 Bearish RSI Divergence"
     return signal
 
-# ------------------- Chart Plotting -------------------
-
 def plot_chart(df):
-    df = df.tail(50).copy()
     df['timestamp'] = pd.to_datetime(df['timestamp'])
-
     fig, ax = plt.subplots(figsize=(10, 5))
 
-    for _, row in df.iterrows():
-        color = 'green' if row['close'] >= row['open'] else 'red'
-        ax.plot([row['timestamp'], row['timestamp']], [row['low'], row['high']], color='black')
-        ax.plot([row['timestamp'], row['timestamp']], [row['open'], row['close']], color=color, linewidth=5)
+    for i in range(len(df)):
+        color = 'green' if df['close'].iloc[i] >= df['open'].iloc[i] else 'red'
+        ax.plot([df['timestamp'].iloc[i]] * 2, [df['low'].iloc[i], df['high'].iloc[i]], color='black')
+        ax.plot([df['timestamp'].iloc[i]] * 2, [df['open'].iloc[i], df['close'].iloc[i]], color=color, linewidth=5)
 
-    ax.plot(df['timestamp'], df['ema_50'], label='EMA 50', color='blue', linewidth=1)
-    ax.plot(df['timestamp'], df['ema_200'], label='EMA 200', color='orange', linewidth=1)
+    ax.plot(df['timestamp'], calculate_ema(df, 50), label="EMA 50", color='blue')
+    ax.plot(df['timestamp'], calculate_ema(df, 200), label="EMA 200", color='orange')
 
     for i in range(len(df)):
-        if df['bullish_div'].iloc[i]:
+        if 'bullish_div' in df.columns and df['bullish_div'].iloc[i]:
             ax.annotate('↑', (df['timestamp'].iloc[i], df['low'].iloc[i] - 1), color='green', fontsize=12, ha='center')
-        if df['bearish_div'].iloc[i]:
+        if 'bearish_div' in df.columns and df['bearish_div'].iloc[i]:
             ax.annotate('↓', (df['timestamp'].iloc[i], df['high'].iloc[i] + 1), color='red', fontsize=12, ha='center')
 
-    ax.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M'))
-    ax.xaxis.set_major_locator(mdates.AutoDateLocator())
+    ax.xaxis.set_major_formatter(mdates.DateFormatter('%m-%d %H:%M'))
+    ax.legend()
     plt.xticks(rotation=45)
-    plt.title('Candlestick Chart with Indicators')
-    plt.legend()
+    plt.title("MEXC Price Chart")
     plt.tight_layout()
 
     buf = BytesIO()
@@ -121,34 +128,25 @@ def plot_chart(df):
     plt.close(fig)
     return Image.open(buf)
 
-# ------------------- Binance Data Fetching -------------------
-
-def fetch_binance_data(symbol='BTCUSDT', interval='15m', limit=100):
-    url = f"https://api.binance.com/api/v3/klines?symbol={symbol}&interval={interval}&limit={limit}"
-    response = requests.get(url)
-    if response.status_code != 200:
-        raise Exception(f"Binance API error: {response.status_code}")
-
-    data = response.json()
-    df = pd.DataFrame(data, columns=['timestamp', 'open', 'high', 'low', 'close', 'volume', '_', '_', '_', '_', '_', '_'])
-    df['timestamp'] = pd.to_datetime(df['timestamp'], unit='ms')
-    df[['open', 'high', 'low', 'close', 'volume']] = df[['open', 'high', 'low', 'close', 'volume']].astype(float)
-    return df
-
-# ------------------- Gradio UI -------------------
-
-def analyze(symbol):
-    df = fetch_binance_data(symbol=symbol.upper())
-    signal = generate_combined_signal(df)
-    chart = plot_chart(df)
-    return signal, chart
-
-symbols = ['BTCUSDT', 'ETHUSDT', 'BNBUSDT', 'SOLUSDT', 'MATICUSDT']
-
-dropdown = gr.Dropdown(choices=symbols, label="Select Trading Pair", value='BTCUSDT')
-output_text = gr.Textbox(label="Signal")
-output_chart = gr.Image(label="Chart")
-
-app = gr.Interface(fn=analyze, inputs=dropdown, outputs=[output_text, output_chart], title="Crypto Signal Generator", live=True)
-
-app.launch()
+def analyze(symbol, interval):
+    try:
+        df = get_price_data(symbol.upper(), interval)
+        signal = generate_combined_signal(df)
+        chart = plot_chart(df)
+        return signal, chart
+    except Exception as e:
+        return f"❌ Error: {e}", None
+
+symbol_input = gr.Textbox(label="Symbol", value="BTCUSDT")
+interval_input = gr.Dropdown(["1m", "5m", "15m", "1h", "4h", "1d"], label="Interval", value="1h")
+
+iface = gr.Interface(
+    fn=analyze,
+    inputs=[symbol_input, interval_input],
+    outputs=["text", "image"],
+    title="📊 Crypto Signal Generator",
+    description="EMA + SuperTrend + RSI Divergence on MEXC Data"
+)
+
+if __name__ == "__main__":
+    iface.launch()