Deploy pro trading signals with futures & forex

README.md

@@ -1,15 +1,10 @@
 ---
-title: TradingProSignals
-emoji: 🏃
-colorFrom: purple
-colorTo: gray
-sdk: gradio
-sdk_version: 6.14.0
-python_version: '3.13'
+title: Pro Trading Signals
+emoji: 📈
+colorFrom: green
+colorTo: blue
+sdk: streamlit
 app_file: app.py
 pinned: false
 license: mit
-short_description: Trading Signals with professional analyzer
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---

app.py

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+"""
+XAUUSD Pro Trading Signals - Fast Live Data Version
+"""
+
+import streamlit as st
+import pandas as pd
+import yfinance as yf
+from datetime import datetime
+import time
+
+st.set_page_config(
+    page_title="XAUUSD Pro Trader",
+    page_icon="📈",
+    layout="centered",
+    initial_sidebar_state="collapsed"
+)
+
+st.markdown("""
+<style>
+    .main-title { font-size: 2.5rem; font-weight: bold; color: #FFD700; text-align: center; }
+    .signal-box { background: #1a1a1a; border-radius: 15px; padding: 25px; margin: 10px 0; }
+    .prob-big { font-size: 4rem; font-weight: bold; text-align: center; }
+    .buy-signal { color: #00E676; }
+    .sell-signal { color: #FF5252; }
+    .wait-signal { color: #FFD740; }
+    .stSelectbox { color: white; }
+    div[data-baseweb="select"] > div { background: #1F2937 !important; }
+</style>
+""", unsafe_allow_html=True)
+
+st.markdown('<h1 class="main-title">📈 XAUUSD PRO TRADER</h1>', unsafe_allow_html=True)
+st.markdown('<p style="text-align:center;color:#888;">Live Futures & Forex Signals • Ultra Fast</p>', unsafe_allow_html=True)
+
+PAIRS = {
+    "🥇 Gold Futures (GC)": {"sym": "GC=F", "type": "futures", "name": "Gold"},
+    "🥈 Silver Futures (SI)": {"sym": "SI=F", "type": "futures", "name": "Silver"},
+    "🛢️ Crude Oil (WTI)": {"sym": "CL=F", "type": "futures", "name": "Crude Oil"},
+    "⛽ Natural Gas": {"sym": "NG=F", "type": "futures", "name": "Natural Gas"},
+    "🌽 Corn Futures": {"sym": "ZC=F", "type": "futures", "name": "Corn"},
+    "🌾 Wheat Futures": {"sym": "ZW=F", "type": "futures", "name": "Wheat"},
+    "EUR/USD": {"sym": "EURUSD=X", "type": "forex", "name": "EUR/USD"},
+    "GBP/USD": {"sym": "GBPUSD=X", "type": "forex", "name": "GBP/USD"},
+    "USD/JPY": {"sym": "USDJPY=X", "type": "forex", "name": "USD/JPY"},
+    "USD/CHF": {"sym": "USDCHF=X", "type": "forex", "name": "USD/CHF"},
+    "AUD/USD": {"sym": "AUDUSD=X", "type": "forex", "name": "AUD/USD"},
+    "USD/CAD": {"sym": "USDCAD=X", "type": "forex", "name": "USD/CAD"},
+    "BTC/USD": {"sym": "BTC-USD", "type": "crypto", "name": "Bitcoin"},
+    "ETH/USD": {"sym": "ETH-USD", "type": "crypto", "name": "Ethereum"},
+}
+
+TIMEFRAMES = {
+    "1 Min": {"interval": "1m", "period": "1d"},
+    "5 Min": {"interval": "5m", "period": "5d"},
+    "15 Min": {"interval": "15m", "period": "5d"},
+    "30 Min": {"interval": "30m", "period": "10d"},
+    "1 Hour": {"interval": "1h", "period": "30d"},
+    "4 Hour": {"interval": "4h", "period": "60d"},
+    "Daily": {"interval": "1d", "period": "180d"},
+}
+
+col1, col2, col3 = st.columns([2, 2, 1])
+with col1:
+    selected_pair = st.selectbox("📊 Asset", list(PAIRS.keys()), label_visibility="collapsed")
+with col2:
+    selected_tf = st.selectbox("⏱ Timeframe", list(TIMEFRAMES.keys()), label_visibility="collapsed")
+with col3:
+    st.write("")
+    analyze_btn = st.button("⚡ ANALYZE", use_container_width=True)
+
+if analyze_btn:
+    with st.spinner("📡 Fetching live data..."):
+        try:
+            start_time = time.time()
+            pair_info = PAIRS[selected_pair]
+            sym = pair_info["sym"]
+            tf = TIMEFRAMES[selected_tf]
+            
+            ticker = yf.Ticker(sym)
+            df = ticker.history(period=tf["period"], interval=tf["interval"])
+            
+            if df.empty or len(df) < 20:
+                st.error("❌ No data available. Try different timeframe.")
+            else:
+                close = df['Close']
+                
+                df['sma9'] = close.rolling(9).mean()
+                df['sma21'] = close.rolling(21).mean()
+                df['sma50'] = close.rolling(50).mean()
+                df['ema8'] = close.ewm(span=8, adjust=False).mean()
+                df['ema21'] = close.ewm(span=21, adjust=False).mean()
+                
+                delta = close.diff()
+                gain = delta.clip(lower=0)
+                loss = (-delta).clip(lower=0)
+                avg_gain = gain.ewm(alpha=1/14, adjust=False).mean()
+                avg_loss = loss.ewm(alpha=1/14, adjust=False).mean()
+                rs = avg_gain / loss.replace(0, 1e-12)
+                df['rsi'] = 100 - (100 / (1 + rs))
+                
+                ema12 = close.ewm(span=12, adjust=False).mean()
+                ema26 = close.ewm(span=26, adjust=False).mean()
+                df['macd'] = ema12 - ema26
+                df['macd_signal'] = df['macd'].ewm(span=9, adjust=False).mean()
+                df['macd_hist'] = df['macd'] - df['macd_signal']
+                
+                high = df['High']
+                low = df['Low']
+                prev_close = close.shift(1)
+                tr = pd.concat([high - low, (high - prev_close).abs(), (low - prev_close).abs()], axis=1).max(axis=1)
+                df['atr'] = tr.ewm(alpha=1/14, adjust=False).mean()
+                
+                up_move = high.diff()
+                down_move = -low.diff()
+                plus_dm = ((up_move > down_move) & (up_move > 0)) * up_move
+                minus_dm = ((down_move > up_move) & (down_move > 0)) * down_move
+                tr_s = tr.ewm(alpha=1/14, adjust=False).mean()
+                p_dm_s = plus_dm.ewm(alpha=1/14, adjust=False).mean()
+                m_dm_s = minus_dm.ewm(alpha=1/14, adjust=False).mean()
+                tr_safe = tr_s.replace(0, 1e-12)
+                df['plus_di'] = 100 * (p_dm_s / tr_safe)
+                df['minus_di'] = 100 * (m_dm_s / tr_safe)
+                di_sum = (df['plus_di'] + df['minus_di']).replace(0, 1e-12)
+                dx = 100 * (df['plus_di'] - df['minus_di']).abs() / di_sum
+                df['adx'] = dx.ewm(alpha=1/14, adjust=False).mean()
+                
+                last = df.iloc[-1]
+                price = float(last['Close'])
+                atr = float(last['atr'])
+                
+                score_buy = 0
+                score_sell = 0
+                reasons = []
+                
+                if price > last['sma50']:
+                    score_buy += 1
+                    reasons.append("✓ Price > SMA50")
+                else:
+                    score_sell += 1
+                    reasons.append("✗ Price < SMA50")
+                
+                if last['sma21'] > last['sma50']:
+                    score_buy += 1
+                    reasons.append("✓ SMA21 > SMA50")
+                else:
+                    score_sell += 1
+                    reasons.append("✗ SMA21 < SMA50")
+                
+                if last['ema8'] > last['ema21']:
+                    score_buy += 1
+                    reasons.append("✓ EMA8 > EMA21")
+                else:
+                    score_sell += 1
+                    reasons.append("✗ EMA8 < EMA21")
+                
+                if last['macd'] > last['macd_signal']:
+                    score_buy += 1
+                    reasons.append("✓ MACD bullish")
+                else:
+                    score_sell += 1
+                    reasons.append("✗ MACD bearish")
+                
+                if last['macd_hist'] > 0:
+                    score_buy += 1
+                    reasons.append("✓ MACD histogram +")
+                else:
+                    score_sell += 1
+                    reasons.append("✗ MACD histogram -")
+                
+                rsi = last['rsi']
+                if 50 < rsi < 70:
+                    score_buy += 1
+                    reasons.append(f"✓ RSI healthy ({rsi:.0f})")
+                elif 30 < rsi < 50:
+                    score_sell += 1
+                    reasons.append(f"✗ RSI weak ({rsi:.0f})")
+                elif rsi >= 70:
+                    score_sell += 1
+                    reasons.append(f"⚠ RSI overbought")
+                elif rsi <= 30:
+                    score_buy += 1
+                    reasons.append(f"✓ RSI oversold")
+                
+                adx = last['adx']
+                if adx > 20:
+                    if last['plus_di'] > last['minus_di']:
+                        score_buy += 2
+                        reasons.append(f"✓ Strong uptrend (ADX:{adx:.0f})")
+                    else:
+                        score_sell += 2
+                        reasons.append(f"✗ Strong downtrend (ADX:{adx:.0f})")
+                else:
+                    reasons.append(f"○ Ranging market")
+                
+                if score_buy >= 5:
+                    prob = min(95, 55 + (score_buy * 7))
+                    action = "🟢 BUY"
+                    color_class = "buy-signal"
+                    tp = round(price + (atr * 2), 2)
+                    sl = round(price - (atr * 1), 2)
+                elif score_sell >= 5:
+                    prob = min(95, 55 + (score_sell * 7))
+                    action = "🔴 SELL"
+                    color_class = "sell-signal"
+                    tp = round(price - (atr * 2), 2)
+                    sl = round(price + (atr * 1), 2)
+                else:
+                    prob = max(40, 50 + (score_buy - score_sell) * 5)
+                    action = "🟡 WAIT"
+                    color_class = "wait-signal"
+                    tp = sl = round(price, 2)
+                
+                fetch_time = round(time.time() - start_time, 2)
+                
+                st.markdown(f"""
+                <div class="signal-box">
+                    <h2 class="{color_class}" style="text-align:center;">{action}</h2>
+                    <h1 class="prob-big {color_class}">{prob}%</h1>
+                    <p style="text-align:center;color:#888;">WIN PROBABILITY • {fetch_time}s</p>
+                    <hr style="border-color:#333;">
+                    <div style="display:flex;justify-content:space-around;text-align:center;">
+                        <div>
+                            <p style="color:#888;">CURRENT PRICE</p>
+                            <h3>${price:.2f}</h3>
+                        </div>
+                        <div>
+                            <p style="color:#00E676;">TAKE PROFIT</p>
+                            <h3>${tp:.2f}</h3>
+                        </div>
+                        <div>
+                            <p style="color:#FF5252;">STOP LOSS</p>
+                            <h3>${sl:.2f}</h3>
+                        </div>
+                    </div>
+                    <hr style="border-color:#333;">
+                    <h4 style="color:#FFD700;">📊 TECHNICAL ANALYSIS</h4>
+                    <p style="font-family:monospace;color:#ccc;">{chr(10).join(reasons)}</p>
+                    <p style="color:#888;text-align:center;">{selected_pair} • {selected_tf} • {datetime.now().strftime('%H:%M:%S')}</p>
+                </div>
+                """, unsafe_allow_html=True)
+                
+        except Exception as e:
+            st.error(f"Error: {str(e)}")
+
+st.markdown("---")
+st.markdown('<p style="text-align:center;color:#555;font-size:12px;">XAUUSD Pro Trader • Futures & Forex Signals</p>', unsafe_allow_html=True)

requirements.txt

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+streamlit
+pandas
+yfinance