"""
Supabase persistence for Signal upload batches, scored records, and report runs.

All writes are best-effort: failures are logged but never surface to the API caller.
The core scoring pipeline works without Supabase (dev mode / env vars not set).
"""

import hashlib
import logging
from datetime import date

from core.supabase_client import get_client

logger = logging.getLogger(__name__)

DEMO_ORG_SLUG = "gaboro-pilot"
_demo_org_id: str | None = None


def _sha256(value: str) -> str:
    return hashlib.sha256(value.encode()).hexdigest()


def _get_or_create_org() -> str | None:
    global _demo_org_id
    if _demo_org_id:
        return _demo_org_id

    client = get_client()
    if not client:
        return None

    try:
        result = client.table("organizations").select("id").eq("slug", DEMO_ORG_SLUG).execute()
        if result.data:
            _demo_org_id = result.data[0]["id"]
            return _demo_org_id

        result = client.table("organizations").insert({
            "name": "Gaboro DME — Pilot",
            "slug": DEMO_ORG_SLUG,
        }).execute()
        _demo_org_id = result.data[0]["id"]
        logger.info(f"Created pilot org: {_demo_org_id}")
        return _demo_org_id

    except Exception as e:
        logger.error(f"Failed to get/create org: {e}")
        return None


def persist_upload(
    filename: str,
    content_bytes: bytes,
    shipment_records: list,
    coverage_results: list,
    skipped_count: int,
    mapping_summary: dict,
) -> str | None:
    """
    Persist one upload batch and all related records to Supabase.
    Returns the batch_id UUID string, or None if persistence is unavailable.
    """
    client = get_client()
    if not client:
        return None

    org_id = _get_or_create_org()
    if not org_id:
        return None

    try:
        # 1. Upload batch
        batch_res = client.table("upload_batches").insert({
            "org_id": org_id,
            "filename": filename,
            "row_count": len(coverage_results),
            "skipped_count": skipped_count,
            "status": "complete",
        }).execute()
        batch_id = batch_res.data[0]["id"]

        # 2. Source file metadata
        content_hash = _sha256(content_bytes.decode("utf-8", errors="replace"))
        client.table("source_files").insert({
            "batch_id": batch_id,
            "filename": filename,
            "content_hash": content_hash,
            "byte_size": len(content_bytes),
        }).execute()

        # 3. Normalized records — one row per scored patient
        # shipment_records and coverage_results are same-indexed
        qty_map = {sr.patient_id: sr.quantity for sr in shipment_records}
        norm_rows = []
        for r in coverage_results:
            flag_val = r.flag.value if hasattr(r.flag, "value") else str(r.flag)
            norm_rows.append({
                "batch_id": batch_id,
                "patient_id_hash": _sha256(r.patient_id),
                "device_type": r.device_type,
                "shipment_date": r.last_shipment_date.isoformat(),
                "quantity": qty_map.get(r.patient_id, 1),
                "payer": r.payer,
                "component": r.component,
                "coverage_status": flag_val,
                "days_remaining": r.days_until_coverage_end,
                "rule_version": r.rule_version,
            })
        if norm_rows:
            client.table("normalized_records").insert(norm_rows).execute()

        # 4. Mapping decisions — how each CSV header was resolved
        mapping_rows = []
        for canonical, detail in mapping_summary.get("mapped", {}).items():
            mapping_rows.append({
                "batch_id": batch_id,
                "raw_header": detail["raw_header"],
                "canonical_field": canonical,
                "confidence": detail["confidence"],
            })
        for raw_h in mapping_summary.get("unmapped_columns", []):
            mapping_rows.append({
                "batch_id": batch_id,
                "raw_header": raw_h,
                "canonical_field": None,
                "confidence": "unmapped",
            })
        if mapping_rows:
            client.table("mapping_decisions").insert(mapping_rows).execute()

        # 5. Report run summary
        flagged = sum(
            1 for r in coverage_results
            if (r.flag.value if hasattr(r.flag, "value") else str(r.flag)) != "OK"
        )
        client.table("report_runs").insert({
            "batch_id": batch_id,
            "org_id": org_id,
            "status": "complete",
            "total_records": len(coverage_results),
            "flagged_count": flagged,
        }).execute()

        logger.info(f"Persisted batch {batch_id}: {len(coverage_results)} records, {flagged} flagged")
        return batch_id

    except Exception as e:
        logger.error(f"Persistence error on upload '{filename}': {e}")
        return None


def persist_export(batch_id: str | None, filename: str, row_count: int) -> None:
    """Record that a work queue CSV was exported. Best-effort."""
    if not batch_id:
        return

    client = get_client()
    if not client:
        return

    try:
        # Find the report_run for this batch
        run_res = client.table("report_runs").select("id").eq("batch_id", batch_id).execute()
        if not run_res.data:
            return
        run_id = run_res.data[0]["id"]

        client.table("export_files").insert({
            "report_run_id": run_id,
            "filename": filename,
            "row_count": row_count,
        }).execute()
    except Exception as e:
        logger.error(f"Persistence error on export: {e}")