siloqy/prod/clean_arch/persistence/pink_clickhouse.py

"""PINK ClickHouse persistence — DITAv2-backed, reads capital from kernel.

Row families preserved (same schema, no new columns):
- policy_events / v7_decision_events
- position_state
- account_events
- status_snapshots
- trade_events
- trade_reconstruction
- trade_exit_legs
- anomaly_events

Capital/peak_capital/trade_seq are read from the kernel's AccountProjection
(single authority).  No duplicate tracking in this module.
"""

from __future__ import annotations

import json
import math
from dataclasses import dataclass
from datetime import datetime, timezone
from enum import Enum
from typing import Any, Callable, Mapping, Optional

from prod.clean_arch.dita import AccountProjection, Decision, DecisionAction, Intent, TradeSide, TradeStage
from prod.clean_arch.dita_v2.contracts import KernelDiagnosticCode, KernelOutcome

Writer = Callable[[str, dict[str, Any]], None]


def _json_safe(value: Any) -> Any:
    if isinstance(value, Enum):
        return value.value
    if isinstance(value, dict):
        return {str(key): _json_safe(val) for key, val in value.items()}
    if isinstance(value, (list, tuple)):
        return [_json_safe(item) for item in value]
    if hasattr(value, "isoformat"):
        try:
            return value.isoformat()
        except Exception:
            pass
    if hasattr(value, "__dict__"):
        try:
            return _json_safe(dict(vars(value)))
        except Exception:
            pass
    return value


def _json_text(value: Any) -> str:
    return json.dumps(_json_safe(value), separators=(",", ":"), ensure_ascii=False, default=str)


def _direction(side: TradeSide) -> int:
    return -1 if side == TradeSide.SHORT else 1


def _direction_from_str(side: str) -> int:
    return -1 if side.upper() in ("SHORT", "SELL") else 1


def _notional(size: float, price: float) -> float:
    if not math.isfinite(size) or not math.isfinite(price):
        return 0.0
    return abs(size) * abs(price)


def _safe_float(value: Any, default: float = 0.0) -> float:
    try:
        out = float(value)
    except Exception:
        return default
    if not math.isfinite(out):
        return default
    return out


def _decision_summary(decision: Decision | None) -> dict[str, Any]:
    if decision is None:
        return {}
    return {
        "timestamp": decision.timestamp.isoformat() if hasattr(decision.timestamp, "isoformat") else str(decision.timestamp),
        "decision_id": decision.decision_id,
        "asset": decision.asset,
        "action": decision.action.value,
        "side": decision.side.value,
        "reason": decision.reason,
        "confidence": float(decision.confidence or 0.0),
        "velocity_divergence": float(decision.velocity_divergence or 0.0),
        "irp_alignment": float(decision.irp_alignment or 0.0),
        "reference_price": float(decision.reference_price or 0.0),
        "target_size": float(decision.target_size or 0.0),
        "leverage": float(decision.leverage or 0.0),
        "bars_held": int(decision.bars_held or 0),
        "stage": decision.stage.value,
        "metadata": _json_safe(decision.metadata),
    }


def _intent_summary(intent: Intent | None) -> dict[str, Any]:
    if intent is None:
        return {}
    return {
        "timestamp": intent.timestamp.isoformat() if hasattr(intent.timestamp, "isoformat") else str(intent.timestamp),
        "trade_id": intent.trade_id,
        "decision_id": intent.decision_id,
        "asset": intent.asset,
        "action": intent.action.value,
        "side": intent.side.value,
        "reason": intent.reason,
        "target_size": float(intent.target_size or 0.0),
        "leverage": float(intent.leverage or 0.0),
        "reference_price": float(intent.reference_price or 0.0),
        "confidence": float(intent.confidence or 0.0),
        "bars_held": int(intent.bars_held or 0),
        "stage": intent.stage.value,
        "exit_leg_ratios": [float(r) for r in intent.exit_leg_ratios],
        "metadata": _json_safe(intent.metadata),
    }


def _outcome_summary(outcome: KernelOutcome | None) -> dict[str, Any]:
    if outcome is None:
        return {}
    return {
        "accepted": bool(outcome.accepted),
        "slot_id": int(outcome.slot_id),
        "trade_id": outcome.trade_id,
        "state": outcome.state.value,
        "diagnostic_code": outcome.diagnostic_code.value,
        "severity": outcome.severity.value,
        "details": _json_safe(outcome.details),
    }


@dataclass(frozen=True)
class PinkClickHousePersistenceConfig:
    """Row-shape knobs for the PINK ClickHouse mirror."""

    strategy: str = "pink"
    runtime_namespace: str = "pink"
    strategy_namespace: str = "pink"
    event_namespace: str = "pink"
    actor_name: str = "PinkDirectRuntime"
    exec_venue: str = "bingx"
    data_venue: str = "binance"
    ledger_authority: str = "exchange"
    initial_capital: float = 25_000.0
    max_account_leverage: float = 3.0
    exchange_leverage_mode: str = ""
    leverage_mapping_rule: str = "round_half_even_linear_0.5_to_9.0_to_1_to_exchange_cap"


class PinkClickHousePersistence:
    """Durable PINK ClickHouse sink — capital reads from kernel AccountProjection."""

    def __init__(
        self,
        account: AccountProjection,
        *,
        config: PinkClickHousePersistenceConfig | None = None,
        sink: Writer | None = None,
        v7_sink: Writer | None = None,
    ) -> None:
        self.account = account
        self.config = config or PinkClickHousePersistenceConfig(
            runtime_namespace=account.runtime_namespace,
            strategy_namespace=account.strategy_namespace,
            event_namespace=account.event_namespace,
            actor_name=account.actor_name,
            exec_venue=account.exec_venue,
            data_venue=account.data_venue,
            ledger_authority=account.ledger_authority,
            initial_capital=float(account.snapshot.capital or 25_000.0),
        )
        self._sink = sink or self._resolve_sink("pink")
        self._v7_sink = v7_sink or self._resolve_v7_sink("pink")
        # Per-trade incremental leg state for trade_exit_legs row deltas.
        # Keyed by trade_id; reset on ENTER. Tracks the cumulative realized PnL
        # and remaining size observed at the previous leg so each leg row carries
        # an isolated (non-cumulative) pnl_leg / exit_qty.
        self._leg_state: dict[str, dict[str, Any]] = {}

    @staticmethod
    def _resolve_sink(strategy: str) -> Writer:
        from prod.ch_writer import ch_put_pink

        return ch_put_pink

    @staticmethod
    def _resolve_v7_sink(strategy: str) -> Writer:
        from prod.ch_writer import ch_put_pink_v7

        return ch_put_pink_v7

    def _capital(self) -> float:
        return float(self.account.snapshot.capital or 0.0)

    def _peak_capital(self) -> float:
        return float(getattr(self.account.snapshot, "peak_capital", self._capital()) or self._capital())

    def _trade_seq(self) -> int:
        return int(getattr(self.account.snapshot, "trade_seq", 0) or 0)

    def _equity(self) -> float:
        return float(self.account.snapshot.equity or self._capital())
    # ------------------------------------------------------------------
    # Public API
    # ------------------------------------------------------------------

    def persist_step(
        self,
        *,
        snapshot: Any,
        decision: Decision,
        intent: Intent,
        outcome: KernelOutcome | None = None,
        slot_dict: dict[str, Any] | None = None,
        acc_dict: dict[str, Any] | None = None,
        phase: str = "step",
        market_state: Mapping[str, Any] | None = None,
    ) -> None:
        slot = slot_dict or {}
        stage = (
            TradeStage(decision.stage.value)
            if hasattr(decision.stage, "value")
            else TradeStage(decision.stage) if isinstance(decision.stage, str)
            else TradeStage.ORDER_REQUESTED
        )
        status = self._state_label(slot, phase)

        self._write_policy_event(snapshot, decision, intent, phase=phase)
        self._write_account_event(snapshot, decision, intent, stage=stage, slot_dict=slot)
        self._write_position_state(snapshot, decision, intent, slot_dict=slot, stage=stage, status=status, market_state=market_state)
        self._write_status_snapshot(snapshot, decision, intent, slot_dict=slot, phase=phase)

        # Emit anomaly for diagnostic codes (except OK).
        if outcome is not None and outcome.diagnostic_code != KernelDiagnosticCode.OK:
            self._write_anomaly(
                snapshot, decision, intent,
                anomaly=outcome.diagnostic_code.value,
                origin="ditav2_kernel",
                detail=outcome.details,
            )

        if outcome is None:
            # Decision-only step (HOLD, no execution).
            return

        if decision.action == DecisionAction.ENTER:
            # Reset per-trade leg deltas: a fresh position starts with zero
            # realized PnL and the full initial size remaining.
            self._leg_state[intent.trade_id] = {
                "prev_realized": 0.0,
                "prev_size": _safe_float(
                    slot.get("initial_size", slot.get("size", 0.0)), 0.0
                ) or _safe_float(intent.target_size, 0.0),
                "prev_leg_id": "",
            }
            self._write_trade_reconstruction(
                snapshot, intent.trade_id,
                event_type="ENTRY_FILLED",
                event_id=f"{intent.trade_id}:entry",
                payload={
                    "decision": _decision_summary(decision),
                    "intent": _intent_summary(intent),
                    "outcome": _outcome_summary(outcome),
                    "slot": slot,
                    "market_state": _json_safe(market_state or {}),
                },
                market_state=market_state,
            )
            return

        if decision.action != DecisionAction.EXIT:
            return

        partial = slot.get("closed", False) is False and slot.get("size", 0) > 0
        # One trade_exit_legs row per exit leg (partial or final), BLUE-schema
        # compatible so PINK multi-exit trades reconcile against the same table.
        self._write_trade_exit_leg(snapshot, decision, intent, slot, outcome)
        self._write_trade_reconstruction(
            snapshot, intent.trade_id,
            event_type="PARTIAL_EXIT" if partial else "EXIT",
            event_id=f"{intent.trade_id}:{'partial' if partial else 'close'}",
            payload={
                "decision": _decision_summary(decision),
                "intent": _intent_summary(intent),
                "outcome": _outcome_summary(outcome),
                "slot": slot,
                "market_state": _json_safe(market_state or {}),
            },
            market_state=market_state,
        )
        # Terminal trade event.
        if slot.get("closed", False):
            self._write_trade_event(snapshot, decision, intent, slot, outcome, market_state=market_state)

    def persist_recovery_state(
        self,
        *,
        snapshot: Any,
        acc_dict: dict[str, Any] | None = None,
        phase: str = "recovery",
        event_type: str = "RECOVERY",
        market_state: Mapping[str, Any] | None = None,
    ) -> None:
        """Persist recovery-only state after kernel reconcile."""
        slot_dict = acc_dict or {}
        self._write_status_snapshot(
            snapshot, decision=None, intent=None, slot_dict={}, phase=phase,
        )
        self._write_account_event(
            snapshot, decision=None, intent=None,
            stage=TradeStage.TRADE_TERMINAL_WRITTEN,
            slot_dict={}, event_type=event_type,
        )
        self._write_position_state(
            snapshot, decision=None, intent=None,
            slot_dict={}, stage=TradeStage.TRADE_TERMINAL_WRITTEN,
            status=self._state_label({}, phase), market_state=market_state,
        )
        self._write_trade_reconstruction(
            snapshot,
            trade_id=acc_dict.get("trade_id", "") if acc_dict else "",
            event_type=event_type,
            event_id=f"recovery:{phase}",
            payload={"acc_dict": _json_safe(acc_dict or {}), "phase": phase, "market_state": _json_safe(market_state or {})},
            market_state=market_state,
        )

    def record_anomaly(
        self,
        *,
        snapshot: Any,
        decision: Any,
        intent: Any,
        anomaly: str,
        origin: str = "emergent",
        sensor: str = "",
        detail: Any = "",
        rm_meta: float = 0.0,
    ) -> None:
        """Persist a DITA anomaly row with legacy-compatible shape."""
        self._sink(
            "anomaly_events",
            {
                "ts": snapshot.timestamp.isoformat(),
                "decision_id": decision.decision_id,
                "trade_id": intent.trade_id,
                "symbol": intent.asset,
                "anomaly": anomaly,
                "origin": origin,
                "sensor": sensor,
                "detail": _json_text(detail) if not isinstance(detail, str) else detail,
                "rm_meta": float(rm_meta),
            },
        )

    # ------------------------------------------------------------------
    # Internal helpers
    # ------------------------------------------------------------------

    @staticmethod
    def _state_label(slot_dict: dict[str, Any], phase: str) -> str:
        if slot_dict.get("closed", False):
            return "CLOSED"
        if slot_dict.get("size", 0) > 0:
            if phase.lower().startswith("recovery"):
                return "RECOVERED_OPEN"
            return "OPEN"
        return "FLAT"

    def _posture(self, slot_dict: dict[str, Any]) -> str:
        if slot_dict.get("closed", False) or not slot_dict.get("size", 0):
            return "FLAT"
        return str(slot_dict.get("side", "FLAT"))

    def _slot_entry_price(self, slot_dict: dict[str, Any]) -> float:
        return _safe_float(slot_dict.get("entry_price", 0.0), 0.0)

    def _slot_size(self, slot_dict: dict[str, Any]) -> float:
        return _safe_float(slot_dict.get("size", 0.0), 0.0)

    def _slot_side(self, slot_dict: dict[str, Any]) -> TradeSide:
        raw = str(slot_dict.get("side", "FLAT")).upper()
        if raw == "SHORT":
            return TradeSide.SHORT
        if raw == "LONG":
            return TradeSide.LONG
        return TradeSide.FLAT

    def _slot_trade_id(self, slot_dict: dict[str, Any]) -> str:
        return str(slot_dict.get("trade_id", ""))

    def _slot_asset(self, slot_dict: dict[str, Any]) -> str:
        return str(slot_dict.get("asset", ""))

    # ------------------------------------------------------------------
    # Row writers
    # ------------------------------------------------------------------

    def _write_anomaly(
        self, snapshot: Any, decision: Decision, intent: Intent,
        *, anomaly: str, origin: str = "ditav2_kernel", detail: Any = "",
    ) -> None:
        self._sink("anomaly_events", {
            "ts": snapshot.timestamp.isoformat(),
            "decision_id": decision.decision_id,
            "trade_id": intent.trade_id,
            "symbol": intent.asset,
            "anomaly": anomaly,
            "origin": origin,
            "sensor": "",
            "detail": _json_text(detail) if not isinstance(detail, str) else detail,
            "rm_meta": 0.0,
        })

    def _write_policy_event(
        self, snapshot: Any, decision: Decision, intent: Intent, *, phase: str,
    ) -> None:
        price = _safe_float(decision.reference_price, 0.0)
        quantity = _safe_float(intent.target_size, 0.0)
        row = {
            "ts": snapshot.timestamp.isoformat(),
            "strategy": self.config.strategy,
            "runtime_namespace": self.config.runtime_namespace,
            "strategy_namespace": self.config.strategy_namespace,
            "event_namespace": self.config.event_namespace,
            "actor_name": self.config.actor_name,
            "exec_venue": self.config.exec_venue,
            "data_venue": self.config.data_venue,
            "source": "ditav2",
            "trade_id": intent.trade_id,
            "asset": decision.asset,
            "side": decision.side.value,
            "entry_price": price,
            "current_price": price,
            "quantity": quantity,
            "notional": _notional(quantity, price),
            "leverage": _safe_float(intent.leverage, 1.0),
            "bar_idx": 0,
            "decision_seq": self._trade_seq(),
            "bars_held": int(intent.bars_held or 0),
            "action": decision.action.value,
            "reason": decision.reason,
            "pnl_pct": 0.0,
            "mfe": 0.0,
            "mae": 0.0,
            "mfe_risk": 0.0,
            "mae_risk": 0.0,
            "exit_pressure": 0.0,
            "rv_comp": 0.0,
            "mae_thresh1": 0.0,
            "bounce_score": 0.0,
            "bounce_risk": 0.0,
            "ob_imbalance": 0.0,
            "vel_div_entry": float(decision.velocity_divergence or 0.0),
            "vel_div_now": float(decision.velocity_divergence or 0.0),
            "v50_vel": 0.0,
            "v750_vel": 0.0,
            "exf_funding": 0.0,
            "exf_dvol": 0.0,
            "exf_fear_greed": 0.0,
            "exf_taker": 0.0,
            "posture": decision.side.value,
        }
        self._sink("policy_events", row)
        self._v7_sink("v7_decision_events", row)

    def _write_account_event(
        self, snapshot: Any, decision: Decision | None, intent: Intent | None,
        *, stage: TradeStage, slot_dict: dict[str, Any], event_type: str | None = None,
    ) -> None:
        capital = self._capital()
        peak_cap = self._peak_capital()
        is_open = not slot_dict.get("closed", False) and slot_dict.get("size", 0) > 0
        open_notional = _notional(self._slot_size(slot_dict), self._slot_entry_price(slot_dict)) if is_open else 0.0
        drawdown_pct = 0.0 if peak_cap <= 0 else max(0.0, (peak_cap - capital) / peak_cap)
        row = {
            "ts": snapshot.timestamp.isoformat(),
            "event_type": event_type or stage.value,
            "strategy": self.config.strategy,
            "posture": self._posture(slot_dict),
            "capital": capital,
            "peak_capital": peak_cap,
            "drawdown_pct": drawdown_pct,
            "pnl_today": float(self.account.snapshot.realized_pnl or 0.0),
            "trades_today": self._trade_seq(),
            "open_positions": 1 if is_open else 0,
            "boost": 1.0,
            "beta": 0.0,
            "current_open_notional": open_notional,
            "current_account_leverage": 0.0 if capital <= 0 else open_notional / capital,
            "exchange_leverage": int(round(_safe_float(slot_dict.get("leverage", 0.0), 0.0))),
            "exchange_leverage_mode": self.config.exchange_leverage_mode,
            "leverage_mapping_rule": self.config.leverage_mapping_rule,
            "runtime_namespace": self.config.runtime_namespace,
            "strategy_namespace": self.config.strategy_namespace,
            "event_namespace": self.config.event_namespace,
            "actor_name": self.config.actor_name,
            "exec_venue": self.config.exec_venue,
            "data_venue": self.config.data_venue,
            "notes": _json_text({
                "decision_id": None if decision is None else decision.decision_id,
                "trade_id": None if intent is None else intent.trade_id,
                "reason": None if intent is None else intent.reason,
                "stage": stage.value,
            }),
        }
        self._sink("account_events", row)

    def _write_position_state(
        self, snapshot: Any, decision: Decision | None, intent: Intent | None,
        *, slot_dict: dict[str, Any], stage: TradeStage, status: str,
        market_state: Mapping[str, Any] | None = None,
    ) -> None:
        side = self._slot_side(slot_dict)
        trade_id = self._slot_trade_id(slot_dict)
        asset = self._slot_asset(slot_dict)
        if not trade_id and intent is not None:
            trade_id = intent.trade_id
            asset = intent.asset
            side = intent.side
        row = {
            "ts": snapshot.timestamp.isoformat(),
            "trade_id": trade_id,
            "asset": asset,
            "direction": _direction(side),
            "entry_price": self._slot_entry_price(slot_dict),
            "quantity": self._slot_size(slot_dict),
            "notional": _notional(self._slot_size(slot_dict), self._slot_entry_price(slot_dict)),
            "leverage": _safe_float(slot_dict.get("leverage", 0.0), 0.0),
            "bucket_id": -1,
            "entry_bar": int(slot_dict.get("active_leg_index", 0) or 0),
            "status": status,
            "exit_reason": slot_dict.get("close_reason", ""),
            "pnl": _safe_float(slot_dict.get("realized_pnl", 0.0), 0.0),
            "bars_held": 0,
            "market_state_bundle_json": _json_text(market_state or {}),
            "tp_base_pct": 0.0,
            "tp_effective_pct": 0.0,
            "our_leverage": _safe_float(slot_dict.get("leverage", 0.0), 0.0),
        }
        self._sink("position_state", row)

    def _write_status_snapshot(
        self, snapshot: Any, decision: Decision | None, intent: Intent | None,
        *, slot_dict: dict[str, Any], phase: str,
    ) -> None:
        capital = self._capital()
        peak_cap = self._peak_capital()
        is_open = not slot_dict.get("closed", False) and slot_dict.get("size", 0) > 0
        open_notional = _notional(self._slot_size(slot_dict), self._slot_entry_price(slot_dict)) if is_open else 0.0
        leverage = 0.0 if capital <= 0 else open_notional / capital
        drawdown = 0.0 if peak_cap <= 0 else max(0.0, (peak_cap - capital) / peak_cap)
        row = {
            "ts": snapshot.timestamp.isoformat(timespec="milliseconds"),
            "capital": capital,
            "roi_pct": 0.0 if self.config.initial_capital <= 0 else ((capital / self.config.initial_capital) - 1.0) * 100.0,
            "dd_pct": drawdown * 100.0,
            "trades_executed": self._trade_seq(),
            "posture": self._posture(slot_dict),
            "rm": 1.0 if decision is None else max(0.0, min(1.0, decision.confidence)),
            "vel_div": 0.0 if decision is None else float(decision.velocity_divergence),
            "vol_ok": 1,
            "phase": phase,
            "mhs_status": "GREEN",
            "boost": 1.0,
            "cat5": 0.0,
            "conviction_multiplier": 0.0 if intent is None else float(intent.confidence or 0.0),
            "exchange_leverage": int(round(_safe_float(slot_dict.get("leverage", 0.0), 0.0))),
            "exchange_leverage_mode": self.config.exchange_leverage_mode,
            "leverage_mapping_rule": self.config.leverage_mapping_rule,
            "account_capital": capital,
            "portfolio_capital": capital,
            "current_open_notional": open_notional,
            "current_account_leverage": leverage,
            "remaining_notional_capacity": max(0.0, self.config.max_account_leverage * capital - open_notional),
            "max_account_leverage": self.config.max_account_leverage,
            "ledger_authority": self.config.ledger_authority,
        }
        self._sink("status_snapshots", row)

    def _write_trade_exit_leg(
        self, snapshot: Any, decision: Decision, intent: Intent,
        slot_dict: dict[str, Any], outcome: KernelOutcome | None,
    ) -> None:
        """Emit one BLUE-schema-compatible ``trade_exit_legs`` row per exit leg.

        The DITAv2 kernel uses a single slot with sequential exit legs rather
        than BLUE's chained per-leg trade_ids, so the chain_* columns describe
        the leg sequence within this one trade (root = trade_id). Per-leg deltas
        (exit_qty, pnl_leg) are computed against the previous leg's snapshot held
        in ``self._leg_state`` so each row is isolated, not cumulative.
        """
        trade_id = intent.trade_id
        prev = self._leg_state.get(trade_id) or {
            "prev_realized": 0.0,
            "prev_size": _safe_float(slot_dict.get("initial_size", 0.0), 0.0),
            "prev_leg_id": "",
        }
        entry_price = self._slot_entry_price(slot_dict) or _safe_float(intent.reference_price, 0.0)
        exit_price = _safe_float(intent.reference_price, 0.0) or _safe_float(decision.reference_price, 0.0)
        side = self._slot_side(slot_dict)
        if side == TradeSide.FLAT:
            side = intent.side
        leverage_val = _safe_float(slot_dict.get("leverage", intent.leverage), 1.0)

        cur_size = self._slot_size(slot_dict)
        cur_realized = _safe_float(slot_dict.get("realized_pnl", 0.0), 0.0)
        prev_size = _safe_float(prev.get("prev_size", 0.0), 0.0)
        prev_realized = _safe_float(prev.get("prev_realized", 0.0), 0.0)

        # active_leg_index is post-fill (already advanced); the leg that just
        # filled is therefore one behind. Clamp to a valid ratio index.
        ratios = slot_dict.get("exit_leg_ratios", []) or []
        leg_index = max(0, int(slot_dict.get("active_leg_index", 0) or 0) - 1)
        fraction = _safe_float(ratios[leg_index], 0.0) if 0 <= leg_index < len(ratios) else 0.0

        exit_qty = max(0.0, prev_size - cur_size)
        pnl_leg = cur_realized - prev_realized
        capital_after = self._capital()
        capital_before = capital_after - pnl_leg
        exit_notional = _notional(exit_qty, exit_price or entry_price)
        remaining_notional = _notional(cur_size, entry_price)
        denom = abs(exit_qty * entry_price * max(leverage_val, 1e-9))
        pnl_pct_leg = pnl_leg / denom if denom > 0 else 0.0
        exit_leg_id = f"{trade_id}:leg{leg_index}"

        self._sink("trade_exit_legs", {
            "ts": snapshot.timestamp.isoformat(),
            "date": snapshot.timestamp.date().isoformat(),
            "strategy": self.config.strategy,
            "trade_id": trade_id,
            "chain_root_trade_id": trade_id,
            "chain_head_leg_id": f"{trade_id}:leg0",
            "chain_prev_leg_id": str(prev.get("prev_leg_id", "") or ""),
            "chain_seq": leg_index,
            "chain_token": trade_id,
            "chain_mode": "LIVE",
            "exit_leg_id": exit_leg_id,
            "exit_seq": leg_index,
            "command_id": decision.decision_id,
            "source": "ditav2",
            "reason": intent.reason,
            "asset": intent.asset,
            "side": side.value,
            "entry_price": entry_price,
            "exit_price": exit_price,
            "fraction": fraction,
            "capital_before": capital_before,
            "capital_after": capital_after,
            "exit_notional": exit_notional,
            "remaining_notional": remaining_notional,
            "remaining_qty": cur_size,
            "pnl_pct_leg": pnl_pct_leg,
            "pnl_leg": pnl_leg,
            "pnl_realized_total": cur_realized,
            "bars_held": int(intent.bars_held or 0),
        })

        # Advance the per-trade leg snapshot for the next leg's delta.
        self._leg_state[trade_id] = {
            "prev_realized": cur_realized,
            "prev_size": cur_size,
            "prev_leg_id": exit_leg_id,
        }

    def _write_trade_event(
        self, snapshot: Any, decision: Decision, intent: Intent,
        slot_dict: dict[str, Any], outcome: KernelOutcome | None,
        *, market_state: Mapping[str, Any] | None = None,
    ) -> None:
        entry_price = _safe_float(slot_dict.get("entry_price", 0.0), 0.0) or _safe_float(intent.reference_price, 0.0)
        quantity = _safe_float(slot_dict.get("initial_size", slot_dict.get("size", 0.0)), 0.0) or _safe_float(intent.target_size, 0.0)
        exit_price = _safe_float(slot_dict.get("entry_price", 0.0), 0.0)
        pnl = _safe_float(slot_dict.get("realized_pnl", 0.0), 0.0)
        pnl_pct = 0.0
        leverage_val = _safe_float(slot_dict.get("leverage", intent.leverage), 1.0)
        denom = abs(quantity * entry_price * max(leverage_val, 1e-9))
        if denom > 0:
            pnl_pct = pnl / denom
        capital_after = self._capital()
        capital_before = capital_after - pnl
        open_notional = _notional(quantity, exit_price or entry_price)
        conviction = float(intent.confidence or decision.confidence or 0.0)
        metadata = intent.metadata if intent is not None else (decision.metadata if decision is not None else {})
        row = {
            "ts": snapshot.timestamp.isoformat(),
            "date": snapshot.timestamp.date().isoformat(),
            "strategy": self.config.strategy,
            "trade_id": intent.trade_id,
            "asset": intent.asset,
            "side": intent.side.value,
            "entry_price": entry_price,
            "exit_price": exit_price,
            "quantity": quantity,
            "pnl": pnl,
            "pnl_pct": pnl_pct,
            "exit_reason": intent.reason,
            "vel_div_entry": float(decision.velocity_divergence or 0.0),
            "boost_at_entry": 1.0,
            "beta_at_entry": 0.0,
            "posture": intent.side.value,
            "leverage": leverage_val,
            "conviction_multiplier": conviction,
            "exchange_leverage": int(round(leverage_val)),
            "exchange_leverage_mode": self.config.exchange_leverage_mode,
            "leverage_mapping_rule": self.config.leverage_mapping_rule,
            "runtime_namespace": self.config.runtime_namespace,
            "strategy_namespace": self.config.strategy_namespace,
            "event_namespace": self.config.event_namespace,
            "actor_name": self.config.actor_name,
            "exec_venue": self.config.exec_venue,
            "data_venue": self.config.data_venue,
            "account_capital": capital_after,
            "portfolio_capital": capital_after,
            "current_open_notional": open_notional,
            "remaining_notional_capacity": max(0.0, self.config.max_account_leverage * capital_after - open_notional),
            "max_account_leverage": self.config.max_account_leverage,
            "margin_required": 0.0 if leverage_val <= 0 else open_notional / leverage_val,
            "ledger_authority": self.config.ledger_authority,
            "regime_signal": 0,
            "capital_before": capital_before,
            "capital_after": capital_after,
            "peak_capital": self._peak_capital(),
            "drawdown_at_entry": 0.0 if self._peak_capital() <= 0 else max(0.0, (self._peak_capital() - capital_before) / self._peak_capital()),
            "open_positions_count": 0,
            "scan_uuid": decision.decision_id,
            "bars_held": int(intent.bars_held or 0),
            "entry_payload_json": _json_text({"decision": _decision_summary(decision), "intent": _intent_summary(intent)}),
            "exit_payload_json": _json_text({"outcome": _outcome_summary(outcome), "slot": _json_safe(slot_dict)}),
            "execution_payload_json": _json_text({"outcome": _outcome_summary(outcome)}),
            "friction_payload_json": _json_text({"fees": 0.0}),
            "event_payload_json": _json_text({"phase": "terminal_close", "trade_id": intent.trade_id}),
            "market_state_bundle_json": _json_text(market_state or {}),
            "tp_base_pct": _safe_float(metadata.get("tp_base_pct", 0.0), 0.0),
            "tp_effective_pct": _safe_float(metadata.get("tp_effective_pct", 0.0), 0.0),
            "our_leverage": _safe_float(metadata.get("our_leverage", 0.0), 0.0),
        }
        self._sink("trade_events", row)

    def _write_trade_reconstruction(
        self, snapshot: Any, trade_id: str, *,
        event_type: str, event_id: str, payload: Any,
        market_state: Mapping[str, Any] | None = None,
    ) -> None:
        self._sink("trade_reconstruction", {
            "ts": snapshot.timestamp.isoformat(),
            "trade_id": trade_id,
            "event_type": event_type,
            "event_id": event_id,
            "payload_json": _json_text(payload),
            "market_state_bundle_json": _json_text(market_state or {}),
        })