app.py

# -*- coding: utf-8 -*-
"""
HUGGING FACE SPACE: BINANCE SPOT TRADING SIMULATOR
✅ Fixed: Gradio Timer Compatible | No API Key | Rule-Based
"""
import os, time, json, threading, logging, requests, pandas as pd
from datetime import datetime, timezone
from pathlib import Path
import gradio as gr

# ==========================================
# KONFIGURASI
# ==========================================
CONFIG = {
    "WATCHLIST": ["BTCUSDT", "ETHUSDT", "SOLUSDT", "BNBUSDT", "XRPUSDT", "LINKUSDT"],
    "INTERVAL": "1h",
    "RISK_PCT": 0.01,
    "MAX_DAILY_TRADES": 2,
    "DAILY_LOSS_LIMIT": -0.03,
    "DAILY_PROFIT_LOCK": 0.05,
    "AI_THRESHOLD": 70,
    "TP1": 0.03, "TP1_SHARE": 0.3,
    "TP2": 0.05, "TP2_SHARE": 0.3,
    "TP3_SHARE": 0.4,
    "TRAIL_PCT": 0.02,
    "TELEGRAM_TOKEN": os.getenv("TELEGRAM_TOKEN", ""),
    "TELEGRAM_CHAT_ID": os.getenv("TELEGRAM_CHAT_ID", "")
}

STATE_FILE = "sim_state.json"
logging.basicConfig(level=logging.INFO, format="%(message)s")

# ==========================================
# STATE MANAGEMENT
# ==========================================
def load_state():
    if os.path.exists(STATE_FILE):
        with open(STATE_FILE) as f: 
            return json.load(f)
    return {
        "date": datetime.now(timezone.utc).strftime("%Y-%m-%d"),
        "balance": 1000.0, "trades": 0, "daily_pnl": 0.0,
        "positions": [], "logs": []
    }

def save_state(s):
    with open(STATE_FILE, "w") as f: 
        json.dump(s, f, indent=2)

# ==========================================
# PUBLIC BINANCE FETCHER (NO API KEY)
# ==========================================
def fetch_klines(sym, interval="1h", limit=100):
    try:
        r = requests.get("https://api.binance.com/api/v3/klines",
                         params={"symbol": sym, "interval": interval, "limit": limit}, timeout=10)
        r.raise_for_status()
        d = r.json()
        df = pd.DataFrame(d, columns=["ts","o","h","l","c","v"] + ["_"]*6)
        df["ts"] = pd.to_datetime(df["ts"], unit="ms")
        for c in "o h l c v".split(): 
            df[c] = df[c].astype(float)
        return df[["ts","o","h","l","c","v"]]
    except Exception as e:
        return pd.DataFrame()

# ==========================================
# INDIKATOR & AI SCORE
# ==========================================
def add_ema(df, periods=[20, 50]):
    for p in periods: 
        df[f"ema_{p}"] = df["c"].ewm(span=p, adjust=False).mean()
    return df

def calc_ai_score(df):
    if len(df) < 50: 
        return 0
    trend = 30 if df["ema_20"].iloc[-1] > df["ema_50"].iloc[-1] else 0
    vol_ma = df["v"].rolling(20).mean().iloc[-1]
    vol_ratio = df["v"].iloc[-1] / max(vol_ma, 1e-9)
    vol = min(vol_ratio * 10, 40) if vol_ratio > 1 else 0
    mom = min((df["c"].iloc[-1] / df["c"].iloc[-5] - 1) * 1000, 30)
    return max(0, min(100, trend + vol + mom))

# ==========================================
# TELEGRAM ALERT
# ==========================================
def tg_send(txt):
    if not CONFIG["TELEGRAM_TOKEN"] or not CONFIG["TELEGRAM_CHAT_ID"]: 
        return
    try:
        requests.post(f"https://api.telegram.org/bot{CONFIG['TELEGRAM_TOKEN']}/sendMessage",
                      json={"chat_id": CONFIG["TELEGRAM_CHAT_ID"], "text": txt, "parse_mode": "HTML"}, timeout=5)
    except: 
        pass

def tg_fmt(emoji, title, msg):
    return f"{emoji} <b>{title}</b>\n{msg}\n⏰ {datetime.now(timezone.utc).strftime('%H:%M UTC')}"

# ==========================================
# SIMULATION ENGINE
# ==========================================
class SimEngine:
    def __init__(self):
        self.state = load_state()
        self._lock = threading.Lock()
        self._running = False
        self._stop = threading.Event()
        self._thread = None

    def start(self):
        if self._running: 
            return "⚠️ Sudah berjalan"
        self._running = True
        self._stop.clear()
        self._thread = threading.Thread(target=self._loop, daemon=True)
        self._thread.start()
        return "✅ Simulator Started"

    def stop(self):
        self._stop.set()
        self._running = False
        return "⏹ Simulator Stopped"

    def _reset_daily(self):
        today = datetime.now(timezone.utc).strftime("%Y-%m-%d")
        if self.state["date"] != today:
            with self._lock:
                self.state.update({"date": today, "trades": 0, "daily_pnl": 0.0, "positions": []})
                save_state(self.state)

    def _can_trade(self):
        with self._lock:
            if self.state["trades"] >= CONFIG["MAX_DAILY_TRADES"]: 
                return False, "Max 2 trade/hari"
            if self.state["daily_pnl"] <= CONFIG["DAILY_LOSS_LIMIT"]: 
                return False, "Daily Loss Limit -3%"
            if self.state["daily_pnl"] >= CONFIG["DAILY_PROFIT_LOCK"]: 
                return False, "Profit Lock +5%"
            return True, "OK"

    def _check_positions(self):
        with self._lock:
            for p in self.state["positions"][:]:
                sym = p["symbol"]
                df = fetch_klines(sym, CONFIG["INTERVAL"], limit=1)
                if df.empty: 
                    continue
                price = df["c"].iloc[-1]
                pnl = (price - p["entry"]) / p["entry"]
                if price > p["trail_h"]: 
                    p["trail_h"] = price

                if pnl >= CONFIG["TP1"] and not p["tp1"]:
                    p["tp1"] = True
                    self._add_log(f"💰 TP1 {sym} +3% (30% closed)")
                    tg_send(tg_fmt("💰", f"TP1 {sym}", f"+3% | 30% closed | Virtual"))
                if pnl >= CONFIG["TP2"] and not p["tp2"]:
                    p["tp2"] = True
                    self._add_log(f"💰 TP2 {sym} +5% (30% closed)")
                    tg_send(tg_fmt("💰", f"TP2 {sym}", f"+5% | 30% closed | Virtual"))

                trail_sl = p["trail_h"] * (1 - CONFIG["TRAIL_PCT"])
                if price <= max(trail_sl, p["sl"]):
                    close_share = CONFIG["TP3_SHARE"] if p["tp2"] else 1.0
                    pnl_real = pnl * close_share
                    self.state["daily_pnl"] += pnl_real
                    self.state["balance"] *= (1 + pnl_real)
                    self._add_log(f"📉 EXIT {sym} | PnL: {pnl:.2%} | Balance: ${self.state['balance']:.2f}")
                    tg_send(tg_fmt("📉", f"EXIT {sym}", f"PnL: {pnl:.2%} | Virtual"))
                    self.state["positions"].remove(p)
                    save_state(self.state)
                elif price <= p["sl"]:
                    pnl_real = pnl
                    self.state["daily_pnl"] += pnl_real
                    self.state["balance"] *= (1 + pnl_real)
                    self._add_log(f"⛔ SL {sym} -2% | Balance: ${self.state['balance']:.2f}")
                    tg_send(tg_fmt("⛔", f"SL {sym}", f"Loss: -2% | Virtual"))
                    self.state["positions"].remove(p)
                    save_state(self.state)

    def _loop(self):
        tg_send(tg_fmt("🚀", "System Started", "Simulator Mode (No API Key)"))
        while not self._stop.is_set():
            try:
                self._reset_daily()
                ok, reason = self._can_trade()
                if not ok:
                    time.sleep(60)
                    continue

                # BTC Filter
                btc = add_ema(fetch_klines("BTCUSDT", CONFIG["INTERVAL"]))
                if btc.empty or btc["ema_20"].iloc[-1] <= btc["ema_50"].iloc[-1]:
                    time.sleep(60)
                    continue

                # Scan Watchlist
                for sym in CONFIG["WATCHLIST"]:
                    if sym == "BTCUSDT" or self._stop.is_set(): 
                        continue
                    df = add_ema(fetch_klines(sym, CONFIG["INTERVAL"]))
                    if df.empty: 
                        continue
                    score = calc_ai_score(df)
                    vol_ma = df["v"].rolling(20).mean().iloc[-1]
                    vol_r = df["v"].iloc[-1] / max(vol_ma, 1e-9)
                    if not (df["ema_20"].iloc[-1] > df["ema_50"].iloc[-1] and vol_r > 1.2 and score > CONFIG["AI_THRESHOLD"]):
                        continue

                    price = df["c"].iloc[-1]
                    sl = price * 0.98
                    risk_usd = self.state["balance"] * CONFIG["RISK_PCT"]
                    qty = (risk_usd / (price - sl)) / price if price > sl else 0

                    with self._lock:
                        self.state["positions"].append({
                            "symbol": sym, "entry": price, "qty": qty, "sl": sl,
                            "tp1": False, "tp2": False, "trail_h": price
                        })
                        self.state["trades"] += 1
                        save_state(self.state)
                    self._add_log(f"📥 ENTRY {sym} @ {price:.2f} | Risk: 1% | SL: {sl:.2f}")
                    tg_send(tg_fmt("📥", f"ENTRY {sym}", f"Price: {price:.2f} | Qty: {qty:.4f} | Virtual"))
                    break  # Anti overtrading

                self._check_positions()
                time.sleep(300)
            except Exception as e:
                self._add_log(f"⚠️ {str(e)}")
                time.sleep(60)
        self._add_log("🛑 System Stopped")

    def _add_log(self, msg):
        ts = datetime.now().strftime("%H:%M:%S")
        with self._lock:
            self.state["logs"].append(f"[{ts}] {msg}")
            if len(self.state["logs"]) > 150: 
                self.state["logs"] = self.state["logs"][-50:]

    def get_state(self):
        with self._lock:
            return json.loads(json.dumps(self.state))

engine = SimEngine()

# ==========================================
# GRADIO DASHBOARD (FIXED)
# ==========================================
def ui_update():
    s = engine.get_state()
    logs = "\n".join(s["logs"][-20:])
    pos = [[p["symbol"], f"${p['entry']:.2f}", f"{p['qty']:.4f}", f"${p['sl']:.2f}", 
            "WAIT" if not p["tp1"] else "TP1" if not p["tp2"] else "TP2"] for p in s["positions"]]
    return (f"Balance: ${s['balance']:.2f}", 
            f"Trades: {s['trades']}/{CONFIG['MAX_DAILY_TRADES']}",
            f"Daily PnL: {s['daily_pnl']:.2%}", 
            pos, logs)

def refresh_logs():
    """Fungsi khusus untuk timer refresh log saja"""
    s = engine.get_state()
    return "\n".join(s["logs"][-20:])

with gr.Blocks(title="Binance Spot Simulator", css=".footer {text-align: center; margin-top: 20px;}") as demo:
    gr.Markdown("# 📊 System Trading + Profit Management (SIMULATOR)")
    gr.Markdown("*✅ Tanpa API Key | ✅ Data Publik Binance | ✅ Semua Rule Aktif | ✅ Telegram Ready*")
    
    with gr.Row():
        btn_start = gr.Button("▶ START SIMULATOR", variant="primary", scale=1)
        btn_stop = gr.Button("⏹ STOP", variant="stop", scale=1)
        btn_reset = gr.Button("🔄 RESET STATE", variant="secondary", scale=1)
    
    with gr.Row():
        bal = gr.Textbox(label="💰 Balance", value="Balance: $1000.00", interactive=False)
        trades = gr.Textbox(label="📈 Trades Hari Ini", value="Trades: 0/2", interactive=False)
        pnl = gr.Textbox(label="📊 Daily PnL", value="Daily PnL: 0.00%", interactive=False)
    
    pos_table = gr.Dataframe(
        headers=["Pair", "Entry", "Qty", "SL", "Status"], 
        value=[], 
        interactive=False, 
        label="📍 Open Positions",
        wrap=True
    )
    
    log_box = gr.Textbox(label="📝 System Log", value="", lines=10, interactive=False, max_lines=20)
    
    gr.Markdown('<div class="footer">🔐 Mode: SIMULATOR (Virtual Trading) | Data: Binance Public API</div>', elem_classes="footer")

    # Event handlers
    btn_start.click(lambda: engine.start(), inputs=None, outputs=None)
    btn_stop.click(lambda: engine.stop(), inputs=None, outputs=None)
    
    def do_reset():
        engine.state = {
            "date": datetime.now(timezone.utc).strftime("%Y-%m-%d"),
            "balance": 1000.0, "trades": 0, "daily_pnl": 0.0,
            "positions": [], "logs": ["🔄 State di-reset"]
        }
        save_state(engine.state)
        return "Balance: $1000.00", "Trades: 0/2", "Daily PnL: 0.00%", [], "🔄 State di-reset"
    
    btn_reset.click(do_reset, inputs=None, outputs=[bal, trades, pnl, pos_table, log_box])
    
    # ✅ FIXED: Gunakan gr.Timer untuk auto-refresh (Gradio 4.x compatible)
    timer = gr.Timer(value=5)  # Refresh setiap 5 detik
    timer.tick(ui_update, inputs=None, outputs=[bal, trades, pnl, pos_table, log_box])
    
    # Refresh log lebih sering agar real-time
    log_timer = gr.Timer(value=2)
    log_timer.tick(refresh_logs, inputs=None, outputs=log_box)

if __name__ == "__main__":
    demo.launch(server_name="0.0.0.0", server_port=int(os.getenv("PORT", "7860")))