"""VIOLET V3e: shadow-decision journal — V-TYPES row guard + CH sink.

Sinks each ACTUATED ``ShadowDecision`` to ``dolphin_violet.violet_decisions`` as a
validated row. PARSE, DON'T VALIDATE: a malformed decision dies HERE (rejected to a
counter), never at the head of the CH spool — the bars_held=-106 lesson. NEVER an
order: this journals what BLUE *would* do; execution stays off (ObserveOnlyVenue).
"""

from __future__ import annotations

import logging
import time
from typing import Any, Callable, Optional

from pydantic import Field, ValidationError

from .decision_engine import ShadowDecision
from .domain import EpochMs, MonoNs, SessionId, StrictModel, Symbol, Seq

LOGGER = logging.getLogger("violet.shadow_journal")

TABLE = "violet_decisions"


class DecisionRow(StrictModel):
    """One ``dolphin_violet.violet_decisions`` row. Field set MUST equal the DDL
    column set in prod/clickhouse/violet/22_violet_decisions.sql (asserted by test)."""

    ts: EpochMs                      # DateTime64(3) — epoch milliseconds
    session_id: SessionId
    scan_number: Seq
    mono_ns: MonoNs
    asset: Symbol
    side: str = Field(min_length=1, max_length=8)
    vel_div: float = Field(allow_inf_nan=False)
    fraction: float = Field(ge=0.0, allow_inf_nan=False)
    conviction_leverage: float = Field(ge=0.0, allow_inf_nan=False)
    notional_fraction: float = Field(ge=0.0, allow_inf_nan=False)
    target_exposure: float = Field(ge=0.0, allow_inf_nan=False)
    ars_score: float = Field(allow_inf_nan=False)
    bucket_idx: int = Field(ge=0, le=255)        # UInt8
    actuated: int = Field(ge=0, le=1)
    # V3.4 full-sizing breakdown (Nullable(Float64) in DDL): NULL on the base-only
    # path, populated when live SizingFactors drive the decision. ge=0.0 — leverage
    # and all four multipliers are non-negative by BLUE's construction.
    base_leverage: Optional[float] = Field(default=None, ge=0.0, allow_inf_nan=False)
    dc_lev_mult: Optional[float] = Field(default=None, ge=0.0, allow_inf_nan=False)
    regime_size_mult: Optional[float] = Field(default=None, ge=0.0, allow_inf_nan=False)
    market_ob_mult: Optional[float] = Field(default=None, ge=0.0, allow_inf_nan=False)
    esof_size_mult: Optional[float] = Field(default=None, ge=0.0, allow_inf_nan=False)


class VioletDecisionJournal:
    """Validate-then-sink shadow decisions. ``sink(table, row_dict)`` mirrors
    ch_put_violet / the divergence sink signature."""

    def __init__(self, *, sink: Callable[[str, dict], Any], session_id: str):
        self.sink = sink
        self.session_id = session_id
        self.rows_emitted = 0
        self.rows_rejected = 0

    def journal(self, decision: ShadowDecision, *, mono_ns: int) -> bool:
        """Build a validated row and sink it. Returns True if emitted."""
        try:
            row = DecisionRow(
                ts=int(time.time() * 1000),
                session_id=self.session_id,
                scan_number=int(decision.scan_number),
                mono_ns=int(mono_ns),
                asset=decision.asset,
                side=decision.side,
                vel_div=float(decision.vel_div),
                fraction=float(decision.fraction),
                conviction_leverage=float(decision.conviction_leverage),
                notional_fraction=float(decision.notional_fraction),
                target_exposure=float(decision.target_exposure),
                ars_score=float(decision.ars_score),
                bucket_idx=int(decision.bucket_idx),
                actuated=1 if decision.actuated else 0,
                # getattr-with-None: duck-typed decisions (and the base-only path)
                # may omit the breakdown; it stays NULL rather than raising here.
                base_leverage=getattr(decision, "base_leverage", None),
                dc_lev_mult=getattr(decision, "dc_lev_mult", None),
                regime_size_mult=getattr(decision, "regime_size_mult", None),
                market_ob_mult=getattr(decision, "market_ob_mult", None),
                esof_size_mult=getattr(decision, "esof_size_mult", None),
            )
        except ValidationError as exc:
            self.rows_rejected += 1
            if self.rows_rejected == 1 or self.rows_rejected % 1000 == 0:
                LOGGER.warning(
                    "shadow decision REJECTED at source (#%d) asset=%s: %s",
                    self.rows_rejected, getattr(decision, "asset", "?"), exc,
                )
            return False
        self.sink(TABLE, row.model_dump())
        self.rows_emitted += 1
        return True