"""Конвейер обработки архива: извлечение → нормализация → валидация → SQLite.

Для MVP данные складываются в SQLite (разворачивается без Docker), а боевая схема
PostgreSQL + pgvector лежит в db/migrations. Здесь же — дедупликация партнёров,
версионирование цен (последний прайс активен, старые архивируются) и сбор отчёта о
качестве для дашборда и сдачи.
"""
from __future__ import annotations

import json
import sqlite3
import sys
import uuid
from collections import Counter
from datetime import date
from pathlib import Path

sys.path.insert(0, str(Path(__file__).resolve().parents[1]))

from etl.dictionary import load_dictionary, normalize_name
from etl.extractors import extract
from etl.normalize import Matcher
from etl.validate import validate_item

SCHEMA = """
CREATE TABLE IF NOT EXISTS service (
    service_id TEXT PRIMARY KEY, specialty TEXT, name_ru TEXT, name_norm TEXT, tarificator_code TEXT
);
CREATE TABLE IF NOT EXISTS partner (
    partner_id TEXT PRIMARY KEY, name TEXT, name_norm TEXT UNIQUE, city TEXT
);
CREATE TABLE IF NOT EXISTS price_document (
    doc_id TEXT PRIMARY KEY, partner_id TEXT, file_name TEXT, file_format TEXT,
    effective_date TEXT, parse_status TEXT, rows_count INTEGER
);
CREATE TABLE IF NOT EXISTS price_item (
    item_id INTEGER PRIMARY KEY AUTOINCREMENT, doc_id TEXT, partner_id TEXT,
    service_name_raw TEXT, service_code_source TEXT, service_id TEXT,
    prices TEXT, price_resident REAL, price_nonresident REAL, unit TEXT,
    effective_date TEXT, map_method TEXT, map_confidence REAL, status TEXT, is_active INTEGER,
    suggested_service_id TEXT, suggested_score REAL
);
-- Синонимы, выученные при ручной верификации (для дообучения нормализации).
CREATE TABLE IF NOT EXISTS learned_synonym (name_norm TEXT PRIMARY KEY, service_id TEXT);
CREATE INDEX IF NOT EXISTS price_item_service ON price_item(service_id);
CREATE INDEX IF NOT EXISTS price_item_partner ON price_item(partner_id);
"""


def _open(db_path: str) -> sqlite3.Connection:
    # Полная пересборка: удаляем файл, чтобы схема всегда создавалась свежей.
    Path(db_path).unlink(missing_ok=True)
    conn = sqlite3.connect(db_path)
    conn.executescript(SCHEMA)
    return conn


def run(data_dir: str, db_path: str, dict_path: str, embedder=None, use_vision: bool = False,
        today: date | None = None) -> dict:
    """Прогнать весь архив в SQLite и вернуть отчёт о качестве."""
    today = today or date.today()
    services = load_dictionary(dict_path)
    matcher = Matcher(services, embedder=embedder)

    conn = _open(db_path)
    conn.executemany(
        "INSERT INTO service VALUES (?,?,?,?,?)",
        [(s.service_id, s.specialty, s.name_ru, s.name_norm, s.tarificator_code) for s in services],
    )

    partners: dict[str, str] = {}
    staged: list[tuple] = []  # (doc_id, partner_id, raw, code, prices, unit, eff_iso)
    report: Counter = Counter()

    for path in sorted(Path(data_dir).glob("*")):
        doc = extract(str(path), use_vision=use_vision)
        partner_name = doc.partner_name or path.stem
        partner_norm = normalize_name(partner_name)
        partner_id = partners.get(partner_norm)
        if partner_id is None:
            partner_id = str(uuid.uuid4())
            partners[partner_norm] = partner_id
            conn.execute("INSERT INTO partner VALUES (?,?,?,?)", (partner_id, partner_name, partner_norm, None))

        doc_id = str(uuid.uuid4())
        eff_iso = doc.effective_date.isoformat() if doc.effective_date else None
        conn.execute(
            "INSERT INTO price_document VALUES (?,?,?,?,?,?,?)",
            (doc_id, partner_id, doc.file_name, doc.file_format, eff_iso, "done", len(doc.rows)),
        )
        report["documents"] += 1
        for row in doc.rows:
            staged.append((doc_id, partner_id, row.service_name_raw, row.service_code_source,
                           row.prices, row.unit, eff_iso))

    # Нормализация одной пачкой (эмбеддинги считаются разом — быстрее и дешевле).
    matches = matcher.match_batch([s[2] for s in staged], [s[3] for s in staged])

    for (doc_id, partner_id, raw, code, prices, unit, eff_iso), match in zip(staged, matches, strict=True):
        status, _flags = validate_item(raw, prices, effective_date=None, today=today)
        if match.service_id:
            report["matched"] += 1
        report[f"method_{match.method}"] += 1
        conn.execute(
            """INSERT INTO price_item
               (doc_id, partner_id, service_name_raw, service_code_source, service_id, prices,
                price_resident, price_nonresident, unit, effective_date, map_method, map_confidence,
                status, is_active, suggested_service_id, suggested_score)
               VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?,1,?,?)""",
            (doc_id, partner_id, raw, code, match.service_id, json.dumps(prices, ensure_ascii=False),
             prices.get("resident"), prices.get("nonresident"), unit, eff_iso, match.method,
             round(match.confidence, 3), status, match.suggested_service_id,
             round(match.suggested_score, 3) if match.suggested_score else None),
        )
        report["items"] += 1

    # Версионирование: если у партнёра по той же услуге есть более свежий прайс — старые архивируем.
    conn.execute(
        """UPDATE price_item SET is_active = 0
           WHERE effective_date IS NOT NULL AND EXISTS (
               SELECT 1 FROM price_item b
               WHERE b.partner_id = price_item.partner_id
                 AND b.service_name_raw = price_item.service_name_raw
                 AND b.effective_date > price_item.effective_date)"""
    )
    conn.commit()

    total = report["items"]
    summary = {
        "documents": report["documents"],
        "partners": len(partners),
        "items": total,
        "auto_matched": report["matched"],
        "auto_matched_pct": round(100 * report["matched"] / total, 1) if total else 0.0,
        "unmatched": total - report["matched"],
        "by_method": {
            method: report[f"method_{method}"] for method in ("code", "exact", "embedding", "fuzzy", None)
        },
    }
    conn.close()
    return summary