app.py

import asyncio
import json
import logging
import time
import bisect
import math
import statistics
import aiohttp
from datetime import datetime
from aiohttp import web
import websockets

SYMBOL_KRAKEN = "BTC/USD"
PORT = 7860
HISTORY_LENGTH = 300
BROADCAST_RATE = 0.1

DECAY_LAMBDA = 50.0
IMPACT_SENSITIVITY = 2.0
WALL_DAMPENING = 0.8
Z_SCORE_THRESHOLD = 3.0
WALL_LOOKBACK = 200

logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(message)s')

market_state = {
    "bids": {},
    "asks": {},
    "history": [],
    "pred_history": [],
    "trade_vol_history": [],
    "ohlc_history": [],
    "current_vol_window": {"buy": 0.0, "sell": 0.0, "start": time.time()},
    "current_mid": 0.0,
    "ready": False
}

connected_clients = set()

def detect_anomalies(orders, scan_depth):
    if len(orders) < 10: return []
    relevant_orders = orders[:scan_depth]
    volumes = [q for p, q in relevant_orders]
    if not volumes: return []

    try:
        avg_vol = statistics.mean(volumes)
        stdev_vol = statistics.stdev(volumes)
    except statistics.StatisticsError:
        return []

    if stdev_vol == 0: return []

    walls = []
    for price, qty in relevant_orders:
        z_score = (qty - avg_vol) / stdev_vol
        if z_score > Z_SCORE_THRESHOLD:
            walls.append({"price": price, "vol": qty, "z_score": z_score})

    walls.sort(key=lambda x: x['z_score'], reverse=True)
    return walls[:3]

def calculate_micro_price_structure(diff_x, diff_y_net, current_mid, best_bid, best_ask, walls):
    if not diff_x or len(diff_x) < 5: return None

    weighted_imbalance = 0.0
    total_weight = 0.0

    for i in range(len(diff_x)):
        dist = diff_x[i]
        net_vol = diff_y_net[i]
        weight = math.exp(-dist / DECAY_LAMBDA)
        weighted_imbalance += net_vol * weight
        total_weight += weight

    rho = weighted_imbalance / total_weight if total_weight > 0 else 0

    spread = best_ask - best_bid
    theoretical_delta = (spread / 2) * rho * IMPACT_SENSITIVITY
    projected_price = current_mid + theoretical_delta

    final_delta = theoretical_delta
    if final_delta > 0 and walls['asks']:
        nearest_wall = walls['asks'][0]
        if projected_price >= nearest_wall['price']:
            damp_factor = 1.0 / (1.0 + (nearest_wall['z_score'] * 0.2))
            final_delta *= damp_factor
    elif final_delta < 0 and walls['bids']:
        nearest_wall = walls['bids'][0]
        if projected_price <= nearest_wall['price']:
            damp_factor = 1.0 / (1.0 + (nearest_wall['z_score'] * 0.2))
            final_delta *= damp_factor

    return {
        "projected": current_mid + final_delta,
        "rho": rho
    }

def process_market_data():
    if not market_state['ready']: return {"error": "Initializing..."}

    mid = market_state['current_mid']
    
    now = time.time()
    if now - market_state['current_vol_window']['start'] >= 1.0:
        market_state['trade_vol_history'].append({
            't': now,
            'buy': market_state['current_vol_window']['buy'],
            'sell': market_state['current_vol_window']['sell']
        })
        if len(market_state['trade_vol_history']) > 60: 
            market_state['trade_vol_history'].pop(0)
        market_state['current_vol_window'] = {"buy": 0.0, "sell": 0.0, "start": now}

    sorted_bids = sorted(market_state['bids'].items(), key=lambda x: -x[0])
    sorted_asks = sorted(market_state['asks'].items(), key=lambda x: x[0])

    if not sorted_bids or not sorted_asks: return {"error": "Empty Book"}

    best_bid = sorted_bids[0][0]
    best_ask = sorted_asks[0][0]

    bid_walls = detect_anomalies(sorted_bids, WALL_LOOKBACK)
    ask_walls = detect_anomalies(sorted_asks, WALL_LOOKBACK)

    d_b_x, d_b_y, cum = [], [], 0
    for p, q in sorted_bids[:300]:
        d = mid - p
        if d >= 0:
            cum += q
            d_b_x.append(d); d_b_y.append(cum)

    d_a_x, d_a_y, cum = [], [], 0
    for p, q in sorted_asks[:300]:
        d = p - mid
        if d >= 0:
            cum += q
            d_a_x.append(d); d_a_y.append(cum)

    diff_x, diff_y_net = [], []
    chart_bids, chart_asks = [], []

    if d_b_x and d_a_x:
        max_dist = min(d_b_x[-1], d_a_x[-1])
        step_size = max_dist / 100
        steps = [i * step_size for i in range(1, 101)]
        
        for s in steps:
            idx_b = bisect.bisect_right(d_b_x, s)
            vol_b = d_b_y[idx_b-1] if idx_b > 0 else 0
            idx_a = bisect.bisect_right(d_a_x, s)
            vol_a = d_a_y[idx_a-1] if idx_a > 0 else 0
            
            diff_x.append(s)
            diff_y_net.append(vol_b - vol_a)
            chart_bids.append(vol_b)
            chart_asks.append(vol_a)

    analysis = calculate_micro_price_structure(
        diff_x, diff_y_net, mid, best_bid, best_ask, 
        {"bids": bid_walls, "asks": ask_walls}
    )

    if analysis:
        if not market_state['pred_history'] or (now - market_state['pred_history'][-1]['t'] > 0.5):
            market_state['pred_history'].append({'t': now, 'p': analysis['projected']})
            if len(market_state['pred_history']) > HISTORY_LENGTH:
                market_state['pred_history'].pop(0)

    return {
        "mid": mid,
        "history": market_state['history'],
        "pred_history": market_state['pred_history'],
        "trade_history": market_state['trade_vol_history'],
        "ohlc": market_state['ohlc_history'],
        "depth_x": diff_x,
        "depth_net": diff_y_net,
        "depth_bids": chart_bids,
        "depth_asks": chart_asks,
        "analysis": analysis,
        "walls": {"bids": bid_walls, "asks": ask_walls}
    }

HTML_PAGE = f"""
<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <title>{SYMBOL_KRAKEN}</title>
    <script src="https://unpkg.com/lightweight-charts@4.1.1/dist/lightweight-charts.standalone.production.js"></script>
    <link href="https://fonts.googleapis.com/css2?family=Inter:wght@500;600&family=JetBrains+Mono:wght@400;700&display=swap" rel="stylesheet">
    <style>
        :root {{
            --bg-base: #000000;
            --bg-panel: #0a0a0a;
            --border: #252525;
            --text-main: #FFFFFF;
            --text-dim: #999999;
            --green: #00ff9d;
            --red: #ff3b3b;
            --blue: #2979ff;
            --yellow: #ffeb3b; 
        }}
        body {{ 
            margin: 0; padding: 0; 
            background-color: var(--bg-base); 
            color: var(--text-main); 
            font-family: 'Inter', sans-serif; 
            overflow: hidden; 
            height: 100vh; width: 100vw;
        }}
        .layout {{ 
            display: grid; 
            grid-template-rows: 34px 1fr 1fr; 
            grid-template-columns: 3fr 1fr; 
            gap: 1px;
            background-color: var(--border); 
            height: 100vh; 
            box-sizing: border-box;
        }}
        .panel {{ background: var(--bg-panel); display: flex; flex-direction: column; overflow: hidden; }}
        
        .status-bar {{
            grid-column: 1 / 3;
            grid-row: 1 / 2;
            background: var(--bg-panel);
            display: flex;
            align-items: center;
            justify-content: space-between;
            padding: 0 12px;
            font-family: 'JetBrains Mono', monospace;
            font-size: 12px;
            text-transform: uppercase;
            border-bottom: 1px solid var(--border);
            z-index: 50;
        }}
        .status-left {{ display: flex; gap: 20px; align-items: center; }}
        .live-dot {{ width: 8px; height: 8px; background-color: var(--green); border-radius: 50%; display: inline-block; box-shadow: 0 0 8px var(--green); }}
        .ticker-val {{ font-weight: 700; color: #fff; font-size: 13px; }}

        #p-chart {{ grid-column: 1 / 2; grid-row: 2 / 3; }}
        
        #p-bottom {{ 
            grid-column: 1 / 2; grid-row: 3 / 4; 
            display: grid; 
            grid-template-columns: 1fr 1fr; 
            gap: 1px; 
            background: var(--border); 
        }}
        .bottom-sub {{ background: var(--bg-panel); display: flex; flex-direction: column; position: relative; }}

        #p-sidebar {{ 
            grid-column: 2 / 3; 
            grid-row: 2 / 4; 
            padding: 15px;
            display: flex;
            flex-direction: column;
            gap: 15px;
            border-left: 1px solid var(--border);
            overflow: hidden;
        }}

        .chart-header {{
            height: 24px;
            min-height: 24px;
            display: flex;
            align-items: center;
            padding-left: 12px;
            font-size: 10px;
            font-weight: 700;
            color: var(--text-dim);
            background: #050505; 
            border-bottom: 1px solid #151515;
            letter-spacing: 0.5px;
        }}

        .data-group {{ display: flex; flex-direction: column; gap: 4px; }}
        .label {{ font-size: 10px; color: var(--text-dim); font-weight: 600; text-transform: uppercase; letter-spacing: 0.5px; }}
        .value {{ font-family: 'JetBrains Mono', monospace; font-size: 20px; font-weight: 700; color: #fff; }}
        .value-lg {{ font-size: 26px; }}
        .value-sub {{ font-family: 'JetBrains Mono', monospace; font-size: 11px; margin-top: 2px; color: #666; }}

        .divider {{ height: 1px; background: var(--border); width: 100%; }}
        .c-green {{ color: var(--green); }}
        .c-red {{ color: var(--red); }}
        .c-dim {{ color: var(--text-dim); }}

        .list-container {{ display: flex; flex-direction: column; gap: 8px; overflow-y: auto; height: 100px; }}
        .list-item {{ 
            display: flex; justify-content: space-between; 
            font-family: 'JetBrains Mono', monospace; 
            font-size: 11px; 
            border-bottom: 1px solid #151515;
            padding-bottom: 4px;
        }}
        .list-item span:first-child {{ color: #e0e0e0; }}
        .list-item:last-child {{ border: none; }}
        
        .sidebar-chart-box {{
            flex: 1;
            display: flex;
            flex-direction: column;
            min-height: 0;
        }}
        .mini-chart {{
            flex: 1;
            background: rgba(255,255,255,0.02);
            border: 1px solid var(--border);
            border-radius: 4px;
        }}
    </style>
</head>
<body>
<div class="layout">
    <div class="status-bar">
        <div class="status-left">
            <span class="live-dot"></span>
            <span style="font-weight:700; color:#fff;">{SYMBOL_KRAKEN}</span>
            <span id="price-ticker" class="ticker-val">---</span>
        </div>
        <div class="status-right" id="clock">00:00:00 UTC</div>
    </div>

    <div id="p-chart" class="panel">
        <div class="chart-header">PRICE ACTION (BLUE) // PREDICTION (YELLOW)</div>
        <div id="tv-price" style="flex: 1; width: 100%;"></div>
    </div>

    <div id="p-bottom">
        <div class="bottom-sub">
            <div class="chart-header">1M KLINE (KRAKEN OHLC)</div>
            <div id="tv-candles" style="flex: 1; width: 100%;"></div>
        </div>
        <div class="bottom-sub">
            <div class="chart-header">ORDER FLOW IMBALANCE</div>
            <div id="tv-net" style="flex: 1; width: 100%;"></div>
        </div>
    </div>

    <div id="p-sidebar" class="panel">
        
        <div class="data-group">
            <span class="label">Micro-Price Delta</span>
            <div style="display:flex; align-items: baseline; gap: 10px;">
                <span id="proj-pct" class="value value-lg">--%</span>
                <span id="proj-val" class="value-sub">---</span>
            </div>
        </div>

        <div class="divider"></div>

        <div class="data-group">
            <span class="label">OFI Imbalance Ratio</span>
            <span id="score-val" class="value">0.00</span>
        </div>

        <div class="divider"></div>

        <div class="data-group">
            <span class="label">Detected Walls (Z > 3.0)</span>
            <div id="wall-list" class="list-container">
                <span class="c-dim" style="font-size: 11px;">Scanning...</span>
            </div>
        </div>

        <div class="sidebar-chart-box">
            <span class="label" style="margin-bottom:4px;">Real-time Volume Ticks</span>
            <div id="sidebar-vol" class="mini-chart"></div>
        </div>

        <div class="sidebar-chart-box">
            <span class="label" style="margin-bottom:4px;">Liquidity Density</span>
            <div id="sidebar-density" class="mini-chart"></div>
        </div>
    </div>
</div>

<script>
    setInterval(() => {{
        const now = new Date();
        document.getElementById('clock').innerText = now.toISOString().split('T')[1].split('.')[0] + ' UTC';
    }}, 1000);

    document.addEventListener('DOMContentLoaded', () => {{
        const dom = {{
            ticker: document.getElementById('price-ticker'),
            score: document.getElementById('score-val'),
            projVal: document.getElementById('proj-val'),
            projPct: document.getElementById('proj-pct'),
            wallList: document.getElementById('wall-list')
        }};

        const chartOpts = {{
            layout: {{ background: {{ type: 'solid', color: '#0a0a0a' }}, textColor: '#888', fontFamily: 'JetBrains Mono' }},
            grid: {{ vertLines: {{ color: '#151515' }}, horzLines: {{ color: '#151515' }} }},
            rightPriceScale: {{ borderColor: '#222', scaleMargins: {{ top: 0.1, bottom: 0.1 }} }},
            timeScale: {{ borderColor: '#222', timeVisible: true, secondsVisible: true }},
            crosshair: {{ mode: 1, vertLine: {{ color: '#444', labelBackgroundColor: '#444' }}, horzLine: {{ color: '#444', labelBackgroundColor: '#444' }} }}
        }};

        const priceChart = LightweightCharts.createChart(document.getElementById('tv-price'), chartOpts);
        const priceSeries = priceChart.addLineSeries({{ color: '#2979ff', lineWidth: 2, title: 'Price' }}); 
        const predSeries = priceChart.addLineSeries({{ color: '#ffeb3b', lineWidth: 2, lineStyle: 2, title: 'Forecast' }});

        const candleChart = LightweightCharts.createChart(document.getElementById('tv-candles'), {{
            ...chartOpts, 
            timeScale: {{ timeVisible: true, secondsVisible: false }}
        }});
        const candleSeries = candleChart.addCandlestickSeries({{ 
            upColor: '#00ff9d', downColor: '#ff3b3b', borderVisible: false, wickUpColor: '#00ff9d', wickDownColor: '#ff3b3b' 
        }});

        const netChart = LightweightCharts.createChart(document.getElementById('tv-net'), {{
            ...chartOpts, localization: {{ timeFormatter: t => '$' + t.toFixed(2) }}
        }});
        const netSeries = netChart.addHistogramSeries({{ color: '#2979ff' }});

        const volChart = LightweightCharts.createChart(document.getElementById('sidebar-vol'), {{
            ...chartOpts,
            grid: {{ vertLines: {{ visible: false }}, horzLines: {{ visible: false }} }},
            rightPriceScale: {{ visible: false }},
            timeScale: {{ visible: false }},
            handleScroll: false, handleScale: false
        }});
        const volBuySeries = volChart.addHistogramSeries({{ color: '#00ff9d' }});
        const volSellSeries = volChart.addHistogramSeries({{ color: '#ff3b3b' }});

        const denChart = LightweightCharts.createChart(document.getElementById('sidebar-density'), {{
            ...chartOpts,
            grid: {{ vertLines: {{ visible: false }}, horzLines: {{ visible: false }} }},
            rightPriceScale: {{ visible: false }},
            timeScale: {{ visible: false }},
            handleScroll: false, handleScale: false
        }});
        const bidSeries = denChart.addAreaSeries({{ lineColor: '#00ff9d', topColor: 'rgba(0, 255, 157, 0.15)', bottomColor: 'rgba(0,0,0,0)', lineWidth: 1 }});
        const askSeries = denChart.addAreaSeries({{ lineColor: '#ff3b3b', topColor: 'rgba(255, 59, 59, 0.15)', bottomColor: 'rgba(0,0,0,0)', lineWidth: 1 }});

        let activeLines = [];
        let activeCandleLines = [];

        new ResizeObserver(entries => {{
            for(let entry of entries) {{
                const {{width, height}} = entry.contentRect;
                if(entry.target.id === 'tv-price') priceChart.applyOptions({{width, height}});
                if(entry.target.id === 'tv-candles') candleChart.applyOptions({{width, height}});
                if(entry.target.id === 'tv-net') netChart.applyOptions({{width, height}});
                if(entry.target.id === 'sidebar-vol') volChart.applyOptions({{width, height}});
                if(entry.target.id === 'sidebar-density') denChart.applyOptions({{width, height}});
            }}
        }}).observe(document.body);

        ['tv-price', 'tv-candles', 'tv-net', 'sidebar-vol', 'sidebar-density'].forEach(id => {{
            new ResizeObserver(e => {{
                 const t = document.getElementById(id);
                 if (t.clientWidth && t.clientHeight) {{
                    if(id === 'tv-price') priceChart.applyOptions({{ width: t.clientWidth, height: t.clientHeight }});
                    if(id === 'tv-candles') candleChart.applyOptions({{ width: t.clientWidth, height: t.clientHeight }});
                    if(id === 'tv-net') netChart.applyOptions({{ width: t.clientWidth, height: t.clientHeight }});
                    if(id === 'sidebar-vol') volChart.applyOptions({{ width: t.clientWidth, height: t.clientHeight }});
                    if(id === 'sidebar-density') denChart.applyOptions({{ width: t.clientWidth, height: t.clientHeight }});
                 }}
            }}).observe(document.getElementById(id));
        }});

        function connect() {{
            const ws = new WebSocket((location.protocol === 'https:' ? 'wss' : 'ws') + '://' + location.host + '/ws');
            
            ws.onmessage = (e) => {{
                const data = JSON.parse(e.data);
                if (data.error) return;

                if (data.history.length) {{
                    const hist = data.history.map(d => ({{ time: Math.floor(d.t), value: d.p }}));
                    const cleanHist = [...new Map(hist.map(i => [i.time, i])).values()];
                    priceSeries.setData(cleanHist);

                    const lastP = cleanHist[cleanHist.length-1].value;
                    dom.ticker.innerText = lastP.toLocaleString('en-US', {{ minimumFractionDigits: 2 }});

                    if (data.analysis) {{
                        const proj = data.analysis.projected;
                        const rho = data.analysis.rho; 

                        predSeries.setData([
                            cleanHist[cleanHist.length-1],
                            {{ time: cleanHist[cleanHist.length-1].time + 60, value: proj }}
                        ]);

                        const pct = ((proj - lastP) / lastP) * 100;
                        const sign = pct >= 0 ? "+" : "";
                        
                        dom.projPct.innerText = `${{sign}}${{pct.toFixed(4)}}%`;
                        dom.projPct.style.color = pct >= 0 ? "var(--green)" : "var(--red)";
                        dom.projVal.innerText = proj.toLocaleString('en-US', {{ minimumFractionDigits: 2 }});
                        dom.score.innerText = rho.toFixed(3);
                        dom.score.style.color = rho > 0 ? "var(--green)" : (rho < 0 ? "var(--red)" : "var(--text-main)");
                    }}
                }}

                if (data.ohlc && data.ohlc.length) {{
                    const candles = data.ohlc.map(c => ({{
                        time: c.time,
                        open: c.open,
                        high: c.high,
                        low: c.low,
                        close: c.close
                    }}));
                    // Deduplicate candles
                    const uniqueCandles = [...new Map(candles.map(i => [i.time, i])).values()];
                    candleSeries.setData(uniqueCandles);
                }}

                if (data.walls) {{
                    activeLines.forEach(l => priceSeries.removePriceLine(l));
                    activeLines = [];
                    activeCandleLines.forEach(l => candleSeries.removePriceLine(l));
                    activeCandleLines = [];
                    
                    let html = "";
                    const addWall = (w, type) => {{
                        const color = type === 'BID' ? '#00ff9d' : '#ff3b3b';
                        const lineOpts = {{ price: w.price, color: color, lineWidth: 1, lineStyle: 2, axisLabelVisible: false }};
                        
                        activeLines.push(priceSeries.createPriceLine(lineOpts));
                        activeCandleLines.push(candleSeries.createPriceLine(lineOpts));
                        
                        html += `<div class="list-item"><span style="color:${{color}}">${{type}} ${{w.price}}</span><span class="c-dim">Z:${{w.z_score.toFixed(1)}}</span></div>`;
                    }};
                    data.walls.asks.forEach(w => addWall(w, 'ASK'));
                    data.walls.bids.forEach(w => addWall(w, 'BID'));
                    dom.wallList.innerHTML = html || '<span class="c-dim" style="font-size:11px">Scanning...</span>';
                }}

                if (data.trade_history && data.trade_history.length) {{
                    const buyData = [], sellData = [];
                    data.trade_history.forEach(t => {{
                        const time = Math.floor(t.t);
                        buyData.push({{ time: time, value: t.buy }});
                        sellData.push({{ time: time, value: t.sell }});
                    }});
                    volBuySeries.setData([...new Map(buyData.map(i => [i.time, i])).values()]);
                    volSellSeries.setData([...new Map(sellData.map(i => [i.time, i])).values()]);
                }}

                if (data.depth_x.length) {{
                    const bids = [], asks = [], nets = [];
                    for(let i=0; i<data.depth_x.length; i++) {{
                        const t = data.depth_x[i];
                        bids.push({{ time: t, value: data.depth_bids[i] }});
                        asks.push({{ time: t, value: data.depth_asks[i] }});
                        nets.push({{ time: t, value: data.depth_net[i], color: data.depth_net[i] > 0 ? '#00ff9d' : '#ff3b3b' }});
                    }}
                    bidSeries.setData(bids);
                    askSeries.setData(asks);
                    netSeries.setData(nets);
                }}
            }};
            ws.onclose = () => setTimeout(connect, 2000);
        }}
        connect();
    }});
</script>
</body>
</html>
"""

async def kraken_worker():
    global market_state
    try:
        # Fetch initial history (Kraken REST API uses start time for candles)
        async with aiohttp.ClientSession() as session:
            url = "https://api.kraken.com/0/public/OHLC?pair=XBTUSD&interval=1"
            async with session.get(url) as response:
                if response.status == 200:
                    data = await response.json()
                    if 'result' in data:
                        for key in data['result']:
                            if key != 'last':
                                raw_candles = data['result'][key]
                                market_state['ohlc_history'] = [
                                    {
                                        'time': int(c[0]),
                                        'open': float(c[1]),
                                        'high': float(c[2]),
                                        'low': float(c[3]),
                                        'close': float(c[4])
                                    }
                                    for c in raw_candles[-120:]
                                ]
                                break
    except Exception as e:
        logging.error(f"History fetch failed: {e}")

    while True:
        try:
            async with websockets.connect("wss://ws.kraken.com/v2") as ws:
                logging.info(f"🔌 Connected to Kraken ({SYMBOL_KRAKEN})")
                
                await ws.send(json.dumps({
                    "method": "subscribe",
                    "params": {"channel": "book", "symbol": [SYMBOL_KRAKEN], "depth": 500}
                }))
                await ws.send(json.dumps({
                    "method": "subscribe",
                    "params": {"channel": "trade", "symbol": [SYMBOL_KRAKEN]}
                }))
                await ws.send(json.dumps({
                    "method": "subscribe",
                    "params": {"channel": "ohlc", "symbol": [SYMBOL_KRAKEN], "interval": 1}
                }))

                async for message in ws:
                    payload = json.loads(message)
                    channel = payload.get("channel")
                    data = payload.get("data", [])

                    if channel == "book":
                        for item in data:
                            for bid in item.get('bids', []):
                                q, p = float(bid['qty']), float(bid['price'])
                                if q == 0: market_state['bids'].pop(p, None)
                                else: market_state['bids'][p] = q
                            for ask in item.get('asks', []):
                                q, p = float(ask['qty']), float(ask['price'])
                                if q == 0: market_state['asks'].pop(p, None)
                                else: market_state['asks'][p] = q
                        
                        if market_state['bids'] and market_state['asks']:
                            best_bid = max(market_state['bids'].keys())
                            best_ask = min(market_state['asks'].keys())
                            mid = (best_bid + best_ask) / 2
                            market_state['prev_mid'] = market_state['current_mid']
                            market_state['current_mid'] = mid
                            market_state['ready'] = True
                            
                            now = time.time()
                            if not market_state['history'] or (now - market_state['history'][-1]['t'] > 0.5):
                                market_state['history'].append({'t': now, 'p': mid})
                                if len(market_state['history']) > HISTORY_LENGTH:
                                    market_state['history'].pop(0)
                    
                    elif channel == "trade":
                        for trade in data:
                            try:
                                qty = float(trade['qty'])
                                price = float(trade['price'])
                                side = trade['side']
                                
                                # Update Vol stats
                                if side == 'buy': market_state['current_vol_window']['buy'] += qty
                                else: market_state['current_vol_window']['sell'] += qty

                                # LIVE CANDLE UPDATE (Crucial for "actual price")
                                current_minute_start = int(time.time()) // 60 * 60
                                
                                if market_state['ohlc_history']:
                                    last_candle = market_state['ohlc_history'][-1]
                                    
                                    # If still in the same minute, update the current candle
                                    if last_candle['time'] == current_minute_start:
                                        last_candle['close'] = price
                                        if price > last_candle['high']: last_candle['high'] = price
                                        if price < last_candle['low']: last_candle['low'] = price
                                    
                                    # If new minute started, create new candle
                                    elif current_minute_start > last_candle['time']:
                                        new_candle = {
                                            'time': current_minute_start,
                                            'open': price,
                                            'high': price,
                                            'low': price,
                                            'close': price
                                        }
                                        market_state['ohlc_history'].append(new_candle)
                                        if len(market_state['ohlc_history']) > 200:
                                            market_state['ohlc_history'].pop(0)

                            except: pass

                    elif channel == "ohlc":
                        for candle in data:
                            try:
                                # Kraken WS sends 'endtime'. We convert to 'starttime' to match REST data and charting lib.
                                start_time = int(float(candle['endtime'])) - 60
                                c_data = {
                                    'time': start_time, 
                                    'open': float(candle['open']),
                                    'high': float(candle['high']),
                                    'low': float(candle['low']),
                                    'close': float(candle['close'])
                                }
                                
                                # Sync with existing history if found
                                if market_state['ohlc_history']:
                                    if market_state['ohlc_history'][-1]['time'] == start_time:
                                        market_state['ohlc_history'][-1] = c_data
                                    elif market_state['ohlc_history'][-1]['time'] < start_time:
                                        market_state['ohlc_history'].append(c_data)
                                        if len(market_state['ohlc_history']) > 200:
                                            market_state['ohlc_history'].pop(0)
                            except Exception as e:
                                pass

        except Exception as e:
            logging.warning(f"⚠️ Reconnecting: {e}")
            await asyncio.sleep(3)

async def broadcast_worker():
    while True:
        if connected_clients and market_state['ready']:
            payload = process_market_data()
            msg = json.dumps(payload)
            for ws in list(connected_clients):
                try: await ws.send_str(msg)
                except: pass
        await asyncio.sleep(BROADCAST_RATE)

async def websocket_handler(request):
    ws = web.WebSocketResponse()
    await ws.prepare(request)
    connected_clients.add(ws)
    try:
        async for msg in ws:
            pass
    finally:
        connected_clients.remove(ws)
    return ws

async def handle_index(request):
    return web.Response(text=HTML_PAGE, content_type='text/html')

async def start_background(app):
    app['kraken_task'] = asyncio.create_task(kraken_worker())
    app['broadcast_task'] = asyncio.create_task(broadcast_worker())

async def cleanup_background(app):
    app['kraken_task'].cancel()
    app['broadcast_task'].cancel()
    try: await app['kraken_task']; await app['broadcast_task']
    except: pass

async def main():
    app = web.Application()
    app.router.add_get('/', handle_index)
    app.router.add_get('/ws', websocket_handler)
    app.on_startup.append(start_background)
    app.on_cleanup.append(cleanup_background)
    runner = web.AppRunner(app)
    await runner.setup()
    site = web.TCPSite(runner, '0.0.0.0', PORT)
    await site.start()
    print(f"🚀 Quant Dashboard: http://localhost:{PORT}")
    await asyncio.Event().wait()

if __name__ == "__main__":
    try: asyncio.run(main())
    except KeyboardInterrupt: pass