#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""sync_missing_contacts_to_brand.py

Sincroniza al CRM de Marca los contactos que existen en sucursal y NO tienen
contraparte en Marca (bucket "contacts_in_branch_not_in_brand" del audit
audit_brand_vs_branches_totals).

Flujo por cada contacto de sucursal sin contraparte en Marca:

  1. Doble verificacion en Marca antes de crear, buscando por:
        a) telefono normalizado (ultimos 10 digitos)
        b) email (lowercase)
        c) nombre completo (normalizado: sin acentos, lowercase, espacios colapsados)
  2. Si match en cualquiera de los 3 criterios: skip (ya existe, falso positivo
     del audit que solo busca por phone/email).
  3. Si no existe: crea el contacto en Marca con todos los datos basicos y los
     custom fields mapeados por nombre del schema de la sucursal al de Marca.

NO crea oportunidades. Si el contacto tenia opps en sucursal, esas se sincronizan
con `sync_missing_opps_to_brand.py` (que ya gestiona contactos faltantes ad-hoc).

Modos:
  - dry-run (default): no escribe nada en GHL, solo planea.
  - --apply: ejecuta las escrituras y registra cada cambio en script_audit
    (rollback disponible desde el dashboard).

Uso CLI:
    python scripts/sync_missing_contacts_to_brand.py
    python scripts/sync_missing_contacts_to_brand.py --apply --yes
    python scripts/sync_missing_contacts_to_brand.py --apply --run-id <ID>
    python scripts/sync_missing_contacts_to_brand.py --only-contact <id>
    python scripts/sync_missing_contacts_to_brand.py --json

Para uso programatico (desde el endpoint /api/comparativa/sync-missing-contacts):
    from scripts.sync_missing_contacts_to_brand import run_sync
    result = run_sync(dry_run=True)
"""

import argparse
import json
import os
import sqlite3
import sys
from datetime import datetime

ROOT_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
if ROOT_DIR not in sys.path:
    sys.path.insert(0, ROOT_DIR)
SCRIPTS_DIR = os.path.dirname(os.path.abspath(__file__))
if SCRIPTS_DIR not in sys.path:
    sys.path.insert(0, SCRIPTS_DIR)

import script_audit  # noqa: E402
import sync_engine  # noqa: E402
from audit_brand_vs_branches_totals import (  # noqa: E402
    run_audit,
    normalize_phone,
    normalize_email,
    resolve_contact_link_field_id,
    extract_contact_link_value,
)
from sync_missing_opps_to_brand import (  # noqa: E402
    BRAND_LOCATION_ID,
    DB_PATH,
    build_brand_contact_payload,
    find_brand_contact,
    index_brand_contacts,
    load_branch_contact,
    load_brand_contacts,
    load_schemas_id_to_name,
    load_schemas_name_to_id,
    normalize_name,
    safe_print,
    upsert_brand_contact_in_db,
)

SCRIPT_NAME = os.path.basename(__file__)


def run_sync(contact_ids=None, dry_run=True, log=None, run_id=None):
    """Ejecuta la creacion masiva de contactos en Marca. Devuelve dict serializable.

    Args:
        contact_ids: lista opcional de contact_ids de sucursal a procesar.
            None = todos los del bucket contacts_in_branch_not_in_brand.
        dry_run: True (default) = no escribe en GHL.
        log: funcion opcional log(line) para streaming.
        run_id: id de script_audit para registrar cambios cuando apply.
    """
    if log is None:
        log = safe_print

    if not os.path.exists(DB_PATH):
        raise FileNotFoundError(f"No existe {DB_PATH}. Corre una sincronizacion global primero.")

    log(f"[{datetime.now().strftime('%H:%M:%S')}] === sync_missing_contacts_to_brand ===")
    log(f"Modo: {'DRY-RUN (no escribe)' if dry_run else 'APPLY (escribe en GHL)'}")

    log("Calculando bucket contacts_in_branch_not_in_brand desde audit...")
    audit_data = run_audit(limit_missing=None)
    missing = audit_data["missing"]["contacts_in_branch_not_in_brand"]
    targets = missing["items"]
    if contact_ids:
        wanted = set(contact_ids)
        targets = [t for t in targets if t["id"] in wanted]
    log(f"Contactos candidatos: {len(targets)} (total en bucket: {missing['total']})")

    if not targets:
        return {
            "dry_run": dry_run,
            "summary": {
                "candidates": 0,
                "contacts_created": 0,
                "skipped_already_in_brand": 0,
                "errors": 0,
            },
            "items": [],
        }

    tokens = sync_engine.get_tokens_map()
    brand_token = tokens.get(BRAND_LOCATION_ID)
    if not brand_token:
        raise RuntimeError("No se encontro token para la cuenta de Marca en el CSV de tokens.")

    conn = sqlite3.connect(DB_PATH)
    conn.row_factory = sqlite3.Row

    try:
        brand_contact_schema_name_to_id = load_schemas_name_to_id(conn, BRAND_LOCATION_ID, "contact")
        if not brand_contact_schema_name_to_id:
            log("ADVERTENCIA: schema de contactos de Marca vacio. Corre sync de metadata para que los custom fields se mapeen.")

        brand_contacts = load_brand_contacts(conn)
        idx_phone, idx_email, idx_name = index_brand_contacts(brand_contacts)
        log(f"Indice Marca: {len(brand_contacts)} contactos.")

        # Índice DETERMINÍSTICO por "ID Contacto Sucursal" (paralelo al match por id
        # de opps). Match principal antes de la cascada phone/email/name.
        brand_contact_link_field_id = resolve_contact_link_field_id(conn, BRAND_LOCATION_ID)
        brand_contacts_by_link = {}
        if brand_contact_link_field_id:
            for bc in brand_contacts:
                v = extract_contact_link_value(bc.get("custom_fields_json"), brand_contact_link_field_id)
                if v:
                    brand_contacts_by_link.setdefault(v, bc)
            log(f"Índice por 'ID Contacto Sucursal': {len(brand_contacts_by_link)} contactos Marca con link poblado.")

        results = []
        summary = {
            "candidates": len(targets),
            "contacts_created": 0,
            "skipped_already_in_brand": 0,
            "errors": 0,
        }

        for idx, target in enumerate(targets, 1):
            branch_loc_id = target["branch_location_id"]
            branch_name = target.get("branch_name", "")
            branch_contact_id = target["id"]
            display_name = target.get("name") or "(sin nombre)"
            log(f"\n[{idx}/{len(targets)}] Contacto {branch_contact_id} | {display_name} | sucursal: {branch_name}")

            item = {
                "branch_contact_id": branch_contact_id,
                "branch_location_id": branch_loc_id,
                "branch_name": branch_name,
                "name": display_name,
                "phone": target.get("phone"),
                "email": target.get("email"),
                "opps_in_branch": target.get("opps_in_branch", 0),
                "actions": [],
                "status": "pending",
                "error": None,
            }

            try:
                branch_contact = load_branch_contact(conn, branch_loc_id, branch_contact_id)
                if not branch_contact:
                    raise RuntimeError(f"No se encontro el contacto {branch_contact_id} en SQLite")

                # Match PRINCIPAL determinístico por "ID Contacto Sucursal".
                # Si una opp de Marca tiene como link el id de este contacto de
                # sucursal -> ya existe en Marca, skip (el audit pudo dejarlo en
                # missing por sync de SQLite viejo).
                linked = brand_contacts_by_link.get(branch_contact_id)
                if linked:
                    log(f"  Match por 'ID Contacto Sucursal' -> contacto Marca {linked.get('id')}. Skip (ya existe).")
                    item["status"] = "skipped_already_in_brand"
                    item["actions"].append({
                        "action": "skip_already_in_brand",
                        "strategy": "id_contacto_sucursal",
                        "brand_contact_id": linked.get("id"),
                    })
                    summary["skipped_already_in_brand"] += 1
                    results.append(item)
                    continue

                # Double-check: el audit busca por phone/email; aqui agregamos nombre.
                match, strategy, collision = find_brand_contact(branch_contact, idx_phone, idx_email, idx_name)
                if collision and not match:
                    # Phone idéntico a un contacto en Marca pero el nombre
                    # diverge — caso pareja con mismo número. Crear este
                    # contacto en Marca de forma normal NO es seguro porque
                    # algunas integraciones lo detectarán como duplicado y
                    # mergearán/eliminarán. Reportamos y dejamos para
                    # revisión manual.
                    log(
                        f"  COLISION TELEFONO con contacto Marca {collision.get('id')} "
                        f"({(collision.get('first_name') or '') + ' ' + (collision.get('last_name') or '')!r}). "
                        "Skip para revision manual."
                    )
                    item["status"] = "skipped_phone_collision"
                    item["actions"].append({
                        "action": "skip_phone_collision",
                        "colliding_brand_contact_id": collision.get("id"),
                        "colliding_brand_name": f"{collision.get('first_name') or ''} {collision.get('last_name') or ''}".strip(),
                    })
                    summary.setdefault("phone_collisions_unresolved", 0)
                    summary["phone_collisions_unresolved"] += 1
                    if run_id:
                        try:
                            script_audit.record_change(
                                run_id, BRAND_LOCATION_ID, "contact", branch_contact_id,
                                "", "skipped_phone_collision", None,
                                {
                                    "branch_contact_id": branch_contact_id,
                                    "branch_location_id": branch_loc_id,
                                    "colliding_brand_contact_id": collision.get("id"),
                                    "phone": branch_contact.get("phone"),
                                },
                            )
                        except Exception as audit_exc:
                            log(f"  WARN: no se pudo registrar la colision en script_audit: {audit_exc}")
                    results.append(item)
                    continue
                if match:
                    log(f"  YA EXISTE en Marca por {strategy}: {match['id']}. Skip.")
                    item["status"] = "skipped"
                    item["actions"].append({
                        "action": "skip_already_in_brand",
                        "strategy": strategy,
                        "brand_contact_id": match["id"],
                    })
                    summary["skipped_already_in_brand"] += 1
                    results.append(item)
                    continue

                # Construir payload y crear.
                branch_contact_schema_id_to_name = load_schemas_id_to_name(conn, branch_loc_id, "contact")
                payload = build_brand_contact_payload(
                    branch_contact,
                    branch_contact_schema_id_to_name,
                    brand_contact_schema_name_to_id,
                )
                log(f"  Plan: CREAR en Marca (cf_count={len(payload.get('customFields', []))})")
                item["actions"].append({
                    "action": "create_contact",
                    "payload_preview": _preview_payload(payload),
                })

                if not dry_run:
                    res = sync_engine.ghl_client.create_contact(brand_token, payload)
                    brand_contact_id = (res.get("contact") or {}).get("id") or res.get("id")
                    if not brand_contact_id:
                        raise RuntimeError(f"GHL no devolvio id de contacto creado. Respuesta: {res}")
                    summary["contacts_created"] += 1
                    log(f"  Contacto creado en Marca: {brand_contact_id}")
                    item["actions"][-1]["result"] = {"brand_contact_id": brand_contact_id}

                    # Replicar en SQLite local para mantener snapshot sincronizado.
                    try:
                        upsert_brand_contact_in_db(conn, brand_contact_id, payload)
                    except Exception as db_exc:
                        log(f"  WARN: no se pudo upsert contacto en SQLite: {db_exc}")
                    # Refresh autoritativo desde Bucéfalo para garantizar 1:1
                    # (CFs auto-poblados por GHL, tags, dateAdded reales).
                    try:
                        ref = sync_engine.refresh_contact_in_db(brand_token, brand_contact_id, BRAND_LOCATION_ID)
                        if not ref.get("ok"):
                            log(f"  WARN: refresh_contact_in_db fallo: {ref.get('error')}")
                            summary.setdefault("local_refresh_errors", 0)
                            summary["local_refresh_errors"] += 1
                    except Exception as ref_exc:
                        log(f"  WARN: refresh_contact_in_db excepcion: {ref_exc}")

                    # Indexar el nuevo en memoria para detectar duplicados intra-batch.
                    new_c = {
                        "id": brand_contact_id,
                        "first_name": branch_contact.get("first_name"),
                        "last_name": branch_contact.get("last_name"),
                        "phone": branch_contact.get("phone"),
                        "email": branch_contact.get("email"),
                    }
                    p = normalize_phone(new_c.get("phone"))
                    e = normalize_email(new_c.get("email"))
                    n = normalize_name(new_c.get("first_name"), new_c.get("last_name"))
                    if p: idx_phone.setdefault(p, new_c)
                    if e: idx_email.setdefault(e, new_c)
                    if n: idx_name.setdefault(n, new_c)

                    if run_id:
                        cid = script_audit.record_change(
                            run_id, BRAND_LOCATION_ID, "contact", brand_contact_id,
                            "", "created", None,
                            {"phone": new_c["phone"], "email": new_c["email"],
                             "name": f"{new_c['first_name']} {new_c['last_name']}".strip(),
                             "source_branch": branch_loc_id},
                        )
                        if cid:
                            script_audit.mark_change(cid, "applied")
                else:
                    summary["contacts_created"] += 1

                item["status"] = "created"
                results.append(item)

            except Exception as e:
                summary["errors"] += 1
                item["status"] = "error"
                item["error"] = str(e)
                log(f"  ERROR: {e}")
                results.append(item)

        log(f"\n=== RESUMEN ===")
        log(f"  Candidatos    : {summary['candidates']}")
        log(f"  Contactos {'a crear' if dry_run else 'creados'}: {summary['contacts_created']}")
        log(f"  Ya existian en Marca: {summary['skipped_already_in_brand']}")
        if summary.get("phone_collisions_unresolved"):
            log(f"  Colisiones telefono sin match (revision manual): {summary['phone_collisions_unresolved']}")
        log(f"  Errores       : {summary['errors']}")

        return {
            "dry_run": dry_run,
            "summary": summary,
            "items": results,
        }
    finally:
        conn.close()


def _preview_payload(payload):
    cf_count = len(payload.get("customFields", []))
    p = {k: v for k, v in payload.items() if k != "customFields"}
    if cf_count:
        p["customFields_count"] = cf_count
    return p


def main():
    parser = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter)
    parser.add_argument("--apply", action="store_true", help="Ejecuta las escrituras en GHL. Por default es dry-run.")
    parser.add_argument("--yes", action="store_true", help="Skip confirmacion interactiva.")
    parser.add_argument("--only-contact", action="append", default=[], help="Procesa solo el contact_id dado (puede repetirse).")
    parser.add_argument("--run-id", type=str, default=None, help="Id de script_audit. Solo aplica con --apply.")
    parser.add_argument("--json", action="store_true", help="Imprime el resultado como JSON al final.")
    args = parser.parse_args()

    dry_run = not args.apply
    if not dry_run and not args.yes:
        confirm = input("Esto escribira en GHL. Continuar? (y/N): ").strip().lower()
        if confirm not in ("y", "yes", "s", "si", "sí"):
            print("Cancelado.")
            sys.exit(0)

    try:
        result = run_sync(
            contact_ids=args.only_contact or None,
            dry_run=dry_run,
            log=safe_print,
            run_id=args.run_id,
        )
    except FileNotFoundError as e:
        safe_print(f"ERROR: {e}")
        sys.exit(2)
    except RuntimeError as e:
        safe_print(f"ERROR: {e}")
        sys.exit(3)

    if args.json:
        safe_print(json.dumps(result, ensure_ascii=False, indent=2, default=str))


if __name__ == "__main__":
    main()