"""Deterministic noon-report checks. No LLM — fast, certain, never hallucinates.

Findings use the FuelSense-style taxonomy:
  severity: CRITICAL | ERROR | WARNING
  category: MISSING_DATA | OUT_OF_RANGE | INCONSISTENT_DATA
"""

from dataclasses import dataclass, asdict

import schema
from schema import FIELDS, REQUIRED, BY_KEY


@dataclass
class Finding:
    severity: str      # CRITICAL | ERROR | WARNING
    category: str      # MISSING_DATA | OUT_OF_RANGE | INCONSISTENT_DATA
    field: str
    message: str

    def as_row(self):
        return [self.severity, self.category, self.field, self.message]


def _num(v):
    """Coerce to float, return None if not numeric."""
    try:
        return float(v)
    except (TypeError, ValueError):
        return None


def check_missing(report: dict) -> list[Finding]:
    out = []
    for key in REQUIRED:
        val = report.get(key)
        if val is None or str(val).strip() == "":
            out.append(Finding(
                "CRITICAL", "MISSING_DATA",
                BY_KEY[key].label,
                f"Required field '{BY_KEY[key].label}' is missing.",
            ))
    return out


def check_ranges(report: dict) -> list[Finding]:
    out = []
    for f in FIELDS:
        if f.lo is None and f.hi is None:
            continue
        v = _num(report.get(f.key))
        if v is None:
            continue
        if (f.lo is not None and v < f.lo) or (f.hi is not None and v > f.hi):
            out.append(Finding(
                "ERROR", "OUT_OF_RANGE", f.label,
                f"{f.label} = {v}{f.unit} is outside expected range "
                f"[{f.lo}, {f.hi}]{f.unit}.",
            ))
    return out


def check_consistency(report: dict) -> list[Finding]:
    """Cross-field arithmetic. The high-value checks officers miss."""
    out = []
    hours = _num(report.get("steaming_hours"))
    dist = _num(report.get("distance_run"))
    speed = _num(report.get("avg_speed"))

    # 1. distance / hours should match reported avg speed (within 5%)
    if hours and dist is not None and speed is not None and hours > 0:
        implied = dist / hours
        if speed > 0 and abs(implied - speed) / speed > 0.05:
            out.append(Finding(
                "ERROR", "INCONSISTENT_DATA", "Avg speed",
                f"Reported avg speed {speed}kn disagrees with "
                f"distance/hours = {implied:.2f}kn (>5% off).",
            ))

    # 2. FO ROB carry-over: prev_rob - total_cons should ≈ reported ROB
    prev_rob = _num(report.get("fo_rob_prev"))
    me = _num(report.get("me_fo_cons")) or 0
    ae = _num(report.get("ae_fo_cons")) or 0
    rob = _num(report.get("fo_rob"))
    bunkered = _num(report.get("fo_bunkered")) or 0
    if prev_rob is not None and rob is not None:
        expected = prev_rob - (me + ae) + bunkered
        if abs(expected - rob) > 1.0:  # >1 mt drift
            out.append(Finding(
                "CRITICAL", "INCONSISTENT_DATA", "FO ROB",
                f"FO ROB {rob}mt doesn't reconcile: "
                f"prev {prev_rob} - cons {me+ae} + bunkered {bunkered} "
                f"= {expected:.1f}mt (drift {expected-rob:+.1f}mt).",
            ))

    # 3. draft sanity: aft usually >= fwd when laden/trimmed by stern
    fwd = _num(report.get("draft_fwd"))
    aft = _num(report.get("draft_aft"))
    if fwd is not None and aft is not None and fwd - aft > 0.5:
        out.append(Finding(
            "WARNING", "INCONSISTENT_DATA", "Draft",
            f"Trimmed by head: fwd {fwd}m > aft {aft}m by "
            f"{fwd-aft:.1f}m. Confirm intentional.",
        ))

    return out


def check_advanced(report: dict) -> list[Finding]:
    """Higher-order reconciliations. Still pure arithmetic + explicit rules —
    no LLM. Thresholds live in schema.py and are read at call time so they can
    be tuned (or patched in tests) without touching this file."""
    out = []
    hours = _num(report.get("steaming_hours"))
    dist = _num(report.get("distance_run"))
    speed = _num(report.get("avg_speed"))
    rpm = _num(report.get("rpm_avg"))
    slip = _num(report.get("slip_pct"))
    me = _num(report.get("me_fo_cons"))
    wind = _num(report.get("wind_force"))

    # 1. Slip reconciliation. Engine distance = RPM * pitch * minutes, in nm.
    #    Computed slip = (engine_dist - observed_dist) / engine_dist.
    #    DISABLED unless a real propeller pitch is configured — we never invent
    #    the constant we'd be checking against.
    pitch = schema.PROP_PITCH_M
    if (pitch and rpm and hours and hours > 0
            and dist is not None and slip is not None):
        engine_dist = rpm * pitch * (hours * 60.0) / 1852.0  # revs*m -> nm
        if engine_dist > 0:
            computed_slip = (engine_dist - dist) / engine_dist * 100.0
            if abs(computed_slip - slip) > schema.SLIP_TOLERANCE_PCT:
                out.append(Finding(
                    "ERROR", "INCONSISTENT_DATA", "Slip",
                    f"Reported slip {slip}% disagrees with slip computed from "
                    f"RPM x pitch = {computed_slip:.1f}% "
                    f"(>{schema.SLIP_TOLERANCE_PCT:g} pts off).",
                ))

    # 2. ME fuel-oil burn rate outside the plausible band (mt per steaming hour).
    if me is not None and hours and hours > 0:
        rate = me / hours
        if (rate < schema.ME_FO_RATE_LO_MT_PER_H
                or rate > schema.ME_FO_RATE_HI_MT_PER_H):
            out.append(Finding(
                "WARNING", "INCONSISTENT_DATA", "ME FO consumption",
                f"ME burn rate {rate:.2f} mt/h is outside the typical band "
                f"[{schema.ME_FO_RATE_LO_MT_PER_H}, "
                f"{schema.ME_FO_RATE_HI_MT_PER_H}] mt/h. Confirm cons vs. hours.",
            ))

    # 3. High slip in calm water — usually hull fouling or a data error,
    #    not weather.
    if (slip is not None and wind is not None
            and slip > schema.HIGH_SLIP_PCT and wind <= schema.CALM_WIND_BF):
        out.append(Finding(
            "WARNING", "INCONSISTENT_DATA", "Slip",
            f"High slip {slip}% in calm conditions (BF{wind:g}). "
            f"Check hull fouling or a distance/RPM entry error.",
        ))

    # 4. High speed sustained in heavy weather — verify speed/distance entry.
    if (speed is not None and wind is not None
            and wind >= schema.ROUGH_WIND_BF and speed >= schema.HIGH_SPEED_KN):
        out.append(Finding(
            "WARNING", "INCONSISTENT_DATA", "Average speed",
            f"Avg speed {speed}kn sustained in heavy weather (BF{wind:g}) "
            f"looks high. Verify distance and steaming hours.",
        ))

    return out


def run_all(report: dict) -> list[Finding]:
    findings = []
    findings += check_missing(report)
    findings += check_ranges(report)
    findings += check_consistency(report)
    findings += check_advanced(report)
    # severity sort: CRITICAL first
    order = {"CRITICAL": 0, "ERROR": 1, "WARNING": 2}
    findings.sort(key=lambda f: order.get(f.severity, 9))
    return findings