Chan/ChanMacro/web/app.py

"""
web/app.py — ChanMacro dashboard (Flask, port 8124).
"""

import sys
import os
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))

from datetime import date as Date, timedelta
from flask import Flask, render_template, jsonify, request

from database import get_connection
from config import config
from scoring.price_structure import PriceStructureScorer
from scoring.breadth_scorer import BreadthScorer
from scoring.oi_matrix import OIMatrixScorer
from scoring.volatility_regime import VolatilityRegimeScorer
from regime_detector import RegimeDetector
from models import MarketStateVector
from expectancy.engine import BayesianExpectancyEngine

app = Flask(__name__)


def _build_state(target: Date):
    """Shared: build MarketStateVector for a date."""
    ps = PriceStructureScorer().compute(target)
    br = BreadthScorer().compute(target)
    oi = OIMatrixScorer().compute(target)
    vol = VolatilityRegimeScorer().compute(target)

    detector = RegimeDetector()
    detector.load_state(config.db_path)
    r = detector.detect(ps.score, br.breadth_top50, vol.vol_regime.value, target)

    state = MarketStateVector(
        date=target, regime=r.regime, regime_confidence=r.confidence,
        regime_version=r.regime_version, regime_maturity_score=r.maturity_score,
        breadth_top20=br.breadth_top20, breadth_top30=br.breadth_top30,
        breadth_top50=br.breadth_top50, breadth_bucket=br.breadth_bucket,
        breadth_divergence=br.breadth_divergence,
        oi_state=oi.oi_state, volatility_regime=vol.vol_regime,
        price_structure_score=ps, breadth_score=br,
        oi_matrix_score=oi, volatility_regime_score=vol,
    )
    state.market_state_hash = state.compute_hash()
    return state


@app.route("/")
def dashboard():
    return render_template("index.html")


@app.route("/api/state")
def api_state():
    """Current market state with all factor scores."""
    try:
        target = Date.today()
        state = _build_state(target)
        return jsonify({
            "date": str(state.date),
            "regime": state.regime.value,
            "regime_confidence": state.regime_confidence,
            "regime_maturity": state.regime_maturity_score,
            "breadth": {
                "score": state.breadth_score.score,
                "bucket": state.breadth_bucket.value,
                "top20": state.breadth_top20,
                "top30": state.breadth_top30,
                "top50": state.breadth_top50,
                "divergence": state.breadth_divergence,
                "narrative": state.breadth_score.narrative,
            },
            "oi_state": state.oi_state.value,
            "oi_score": state.oi_matrix_score.score,
            "oi_narrative": state.oi_matrix_score.narrative,
            "volatility": state.volatility_regime.value,
            "price_structure": {
                "score": state.price_structure_score.score,
                "trend": state.price_structure_score.trend_strength,
                "vol_comp": state.price_structure_score.volatility_compression,
                "momentum": state.price_structure_score.momentum,
                "label": state.price_structure_score.label,
                "narrative": state.price_structure_score.narrative,
            },
        })
    except Exception as e:
        return jsonify({"error": str(e)}), 500


@app.route("/api/history")
def api_history():
    """Regime and factor score history."""
    days = request.args.get("days", 60, type=int)
    conn = get_connection()

    # Regime history
    regimes = conn.execute(
        "SELECT date, regime, confidence, maturity_score FROM regime_history ORDER BY date DESC LIMIT ?",
        (days,)
    ).fetchall()

    # Breadth history
    breadth = conn.execute(
        "SELECT date, advance_top50, decline_top50, above_ema20_top50 FROM breadth_daily ORDER BY date DESC LIMIT ?",
        (days,)
    ).fetchall()

    conn.close()

    return jsonify({
        "regimes": [{"date": r["date"], "regime": r["regime"],
                      "confidence": r["confidence"], "maturity": r["maturity_score"]}
                    for r in reversed(regimes)],
        "breadth": [{"date": b["date"], "advance": b["advance_top50"],
                      "decline": b["decline_top50"], "above_ema20": b["above_ema20_top50"]}
                    for b in reversed(breadth)],
    })


@app.route("/api/expectancy")
def api_expectancy():
    """Query signal expectancy."""
    signal = request.args.get("signal", "B3")
    try:
        target = Date.today()
        state = _build_state(target)
        engine = BayesianExpectancyEngine(level_min_samples=5)
        report = engine.estimate(state, signal_type=signal, target_date=target)

        layers = []
        for l in report.layers:
            layers.append({
                "name": l.name,
                "samples": l.samples,
                "effective_samples": l.effective_samples,
                "raw_winrate": l.raw_winrate,
                "posterior_winrate": l.posterior_winrate,
                "avg_return": l.avg_return,
            })

        return jsonify({
            "signal": signal,
            "final_estimate": report.final_estimate,
            "sufficiency": report.sufficiency.value,
            "source": report.source,
            "avg_return_7d": report.avg_return_7d,
            "profit_factor": report.profit_factor,
            "max_adverse": report.max_adverse_excursion,
            "layers": layers,
        })
    except Exception as e:
        return jsonify({"error": str(e)}), 500


if __name__ == "__main__":
    app.run(host="0.0.0.0", port=8124, debug=True)