"""Phase 2: engine LOO+1 (re-enable disabled engines on new snapshot) + risk_budget scaling.

The 5 disabled engines were LOO-rejected on the OLD ftb_fix_v2 snapshot.
On NEW pead_dualconv_ftb_fix_v2_probe snapshot they may behave differently.
"""
import json
import subprocess
import shutil
import copy
from pathlib import Path

BASE = "configs/experiments/return_max_long_v8.11_composed_gld_tqqq_bmc30_cl65_vol40_rmin1_cap96.json"
SWEEP_DIR = Path("configs/experiments/_tune_v811_p2")
SWEEP_DIR.mkdir(exist_ok=True)
SNAPSHOT = "pead_dualconv_ftb_fix_v2_probe"


def load_base():
    with open(BASE) as f:
        return json.load(f)


def save(name: str, cfg: dict) -> str:
    cfg["experiment_name"] = name
    path = SWEEP_DIR / f"{name}.json"
    path.write_text(json.dumps(cfg, indent=2))
    return str(path)


def make_loo_plus(eid_to_enable: str) -> dict:
    """Re-enable a specific disabled engine."""
    cfg = load_base()
    for e in cfg["strategy_engines"]:
        if e.get("engine_id") == eid_to_enable and "_disabled_reason" in e:
            del e["_disabled_reason"]
            return cfg
    raise ValueError(f"Engine {eid_to_enable} not found or not disabled")


def make_loo_minus(eid_to_disable: str) -> dict:
    """Disable an enabled engine."""
    cfg = load_base()
    for e in cfg["strategy_engines"]:
        if e.get("engine_id") == eid_to_disable and "_disabled_reason" not in e:
            e["_disabled_reason"] = "phase2_loo_minus_test"
            return cfg
    raise ValueError(f"Engine {eid_to_disable} not found or already disabled")


def make_rb_scale(scale_dict: dict) -> dict:
    """Scale engine_risk_budget_pct for specific engines."""
    cfg = load_base()
    for e in cfg["strategy_engines"]:
        eid = e.get("engine_id")
        if eid in scale_dict and "_disabled_reason" not in e:
            if "engine_risk_budget_pct" in e:
                e["engine_risk_budget_pct"] *= scale_dict[eid]
    return cfg


def run_backtest(config_path: str) -> dict:
    cmd = ["python3", "-m", "apps.backtester.run", "--manifest", config_path,
           "--start", "2022-01-01", "--split", "all", "--initial-equity", "10000",
           "--snapshot-id", SNAPSHOT]
    cache = Path(f"data/parquet/{SNAPSHOT}/.runtime_cache")
    if cache.exists():
        shutil.rmtree(cache)
    proc = subprocess.run(cmd, capture_output=True, text=True, timeout=200)
    tail = proc.stdout.split("\n")[-12:]
    run_id = return_pct = sqs_total = trades = None
    for line in tail:
        if "Run complete:" in line:
            run_id = line.split("Run complete:")[1].strip()
        elif "Total return:" in line:
            try: return_pct = float(line.split(":")[1].strip().rstrip("%"))
            except: pass
        elif "SQS:" in line:
            try: sqs_total = float(line.split("SQS:")[1].strip().split(" ")[0])
            except: pass
        elif "Trades:" in line:
            try: trades = int(line.split(":")[1].strip())
            except: pass
    mdd = sharpe = pf = None
    if run_id:
        m_path = Path(f"runs/{run_id}/metrics/metrics_summary.json")
        if m_path.exists():
            m = json.loads(m_path.read_text())
            mdd = m["max_drawdown_pct"]
            sharpe = m["sharpe_ratio"]
            pf = m["profit_factor"]
    return {"return": return_pct, "trades": trades, "mdd": mdd, "sharpe": sharpe, "pf": pf, "sqs": sqs_total, "run_id": run_id}


DISABLED_ENGINES = [
    "next_open_long_unknown_material_patient",
    "next_open_long_guidance_unknown_orderly",
    "next_open_long_unknown_material_orderly",
    "next_open_long_other_material_mixed_orderly",
    "next_open_long_unknown_ome_orderly",
]

ENABLED_ENGINES = [
    "reaction_close_long_core",
    "reaction_close_long_residual_lowclose_gap_d3",
    "reaction_close_long_residual_smallcap_gap",
    "reaction_close_long_extreme_orderly",
    "next_open_long_unknown_inline_hivol",
    "next_open_long_earnings_mixed_inline_orderly",
    "next_open_long_megacap_material_contract_orderly",
    "next_open_long_bullish_raised_recovery_broad_oneoff",
]


def main():
    baseline = {"return": 6839, "mdd": 9.78, "sharpe": 3.53, "pf": 8.26, "sqs": 84.8, "trades": 329}
    print(f"BASELINE v8.11: ret={baseline['return']}% MDD={baseline['mdd']}% Sharpe={baseline['sharpe']} PF={baseline['pf']} SQS={baseline['sqs']} trades={baseline['trades']}", flush=True)
    print("=" * 120, flush=True)
    results = []

    # Phase 2A: re-enable each disabled engine
    print("\n=== Phase 2A: Re-enable disabled engines (LOO+1) ===", flush=True)
    for i, eid in enumerate(DISABLED_ENGINES):
        name = f"L_plus_{i:02d}_{eid[:30]}"
        cfg = make_loo_plus(eid)
        path = save(name, cfg)
        print(f"\n>>> [{i+1}/{len(DISABLED_ENGINES)}] +{eid}", flush=True)
        try:
            r = run_backtest(path)
            r["op"] = f"+{eid}"
            if r["return"] is None:
                print(f"    FAILED", flush=True); continue
            d_ret = r["return"] - baseline["return"]
            d_sqs = (r["sqs"] or 0) - baseline["sqs"]
            d_mdd = (r["mdd"] or 0) - baseline["mdd"]
            print(f"    ret={r['return']:.0f}% (Δ{d_ret:+.0f}) MDD={r['mdd']:.2f}% (Δ{d_mdd:+.2f}) Sharpe={r['sharpe']:.2f} PF={r['pf']:.2f} SQS={r['sqs']:.1f} (Δ{d_sqs:+.1f}) trades={r['trades']}", flush=True)
            results.append(r)
        except Exception as e:
            print(f"    FAILED: {e}", flush=True)

    # Phase 2B: scale top engine risk budgets
    print("\n=== Phase 2B: Risk budget scaling ===", flush=True)
    rb_tests = [
        ("core_x12", {"reaction_close_long_core": 1.2}),
        ("core_x08", {"reaction_close_long_core": 0.8}),
        ("residuals_x2", {"reaction_close_long_residual_lowclose_gap_d3": 2.0, "reaction_close_long_residual_smallcap_gap": 2.0}),
        ("extreme_x15", {"reaction_close_long_extreme_orderly": 1.5}),
        ("next_open_x3", {"next_open_long_unknown_inline_hivol": 3.0, "next_open_long_earnings_mixed_inline_orderly": 3.0, "next_open_long_megacap_material_contract_orderly": 3.0, "next_open_long_bullish_raised_recovery_broad_oneoff": 3.0}),
        ("hivol_x4", {"next_open_long_unknown_inline_hivol": 4.0}),
    ]
    for i, (label, scale_dict) in enumerate(rb_tests):
        name = f"RB_{label}"
        cfg = make_rb_scale(scale_dict)
        path = save(name, cfg)
        print(f"\n>>> RB scale: {label} {scale_dict}", flush=True)
        try:
            r = run_backtest(path)
            r["op"] = f"RB:{label}"
            if r["return"] is None:
                print(f"    FAILED", flush=True); continue
            d_ret = r["return"] - baseline["return"]
            d_sqs = (r["sqs"] or 0) - baseline["sqs"]
            d_mdd = (r["mdd"] or 0) - baseline["mdd"]
            print(f"    ret={r['return']:.0f}% (Δ{d_ret:+.0f}) MDD={r['mdd']:.2f}% (Δ{d_mdd:+.2f}) Sharpe={r['sharpe']:.2f} PF={r['pf']:.2f} SQS={r['sqs']:.1f} (Δ{d_sqs:+.1f}) trades={r['trades']}", flush=True)
            results.append(r)
        except Exception as e:
            print(f"    FAILED: {e}", flush=True)

    print("\n" + "=" * 120, flush=True)
    print("SUMMARY (sorted by SQS, then return):", flush=True)
    results.sort(key=lambda x: (x.get("sqs") or 0, x.get("return") or 0), reverse=True)
    print(f"{'op':50s} {'return':>10s} {'MDD':>8s} {'Sharpe':>8s} {'PF':>6s} {'SQS':>7s} {'trades':>7s}", flush=True)
    print(f"{'BASELINE':50s} {baseline['return']:>9.0f}% {baseline['mdd']:>7.2f}% {baseline['sharpe']:>8.2f} {baseline['pf']:>6.2f} {baseline['sqs']:>7.1f} {baseline['trades']:>7d}", flush=True)
    for r in results:
        print(f"{r['op'][:48]:50s} {r['return']:>9.0f}% {r['mdd']:>7.2f}% {r['sharpe']:>8.2f} {r['pf']:>6.2f} {r['sqs']:>7.1f} {r['trades']:>7d}", flush=True)


if __name__ == "__main__":
    main()