"""Yandex Realty parsing helpers — JSON-LD + regex + DOM utilities for SERP, detail, newbuilding,
and valuation parsers."""

from __future__ import annotations

import json
import re
from datetime import date, timedelta
from typing import Any

from selectolax.parser import HTMLParser

__all__ = [
    "RE_AGENCY_FOUNDED",
    "RE_AGENCY_OBJECTS",
    "RE_FLOOR",
    "RE_JK_ID",
    "RE_METRO_WALK",
    "RE_OFFER_ID",
    "RE_PPM2",
    "RE_PRICE",
    "RE_STREET_ID",
    "RE_TITLE_AREA",
    "RE_TITLE_ROOMS",
    "RE_VIEWS",
    "RE_YEAR",
    "RU_MONTHS",
    "RU_MONTH_NOMINATIVE",
    "extract_json_ld",
    "find_ld_by_type",
    "parse_dmy",
    "parse_house_class",
    "parse_house_type",
    "parse_listing_date",
    "parse_ru_date",
    "parse_rub",
]

# ---------------------------------------------------------------------------
# Section 1 — JSON-LD extraction
# ---------------------------------------------------------------------------


def extract_json_ld(html: str) -> list[dict[str, Any]]:
    """Extract all <script type='application/ld+json'> blocks from HTML.

    Returns a list of parsed JSON-LD dicts. Skips blocks that fail to parse.
    """
    tree = HTMLParser(html)
    results: list[dict[str, Any]] = []
    for script in tree.css('script[type="application/ld+json"]'):
        text = script.text() or ""
        if not text.strip():
            continue
        try:
            parsed = json.loads(text)
        except json.JSONDecodeError:
            continue
        if isinstance(parsed, dict):
            results.append(parsed)
        elif isinstance(parsed, list):
            # Some pages wrap multiple LDs in a JSON array
            results.extend(item for item in parsed if isinstance(item, dict))
    return results


def find_ld_by_type(html: str, type_name: str) -> dict[str, Any] | None:
    """Return the first JSON-LD dict whose @type equals type_name.

    If @type is a list, returns the dict if type_name is contained in it.
    """
    for ld in extract_json_ld(html):
        t = ld.get("@type")
        if t == type_name:
            return ld
        if isinstance(t, list) and type_name in t:
            return ld
    return None


# ---------------------------------------------------------------------------
# Section 2 — Regex extractors (module-level compiled)
# ---------------------------------------------------------------------------

# URL pattern extractors
RE_OFFER_ID = re.compile(r"/offer/(\d+)/?")
RE_JK_ID = re.compile(r"/novostrojka/([\w-]+?)-(\d+)/?")          # group(1)=slug, group(2)=id
RE_STREET_ID = re.compile(r"/kupit/kvartira/st-([\w-]+?)-(\d+)/?")

# Card / title text extractors
RE_TITLE_AREA = re.compile(r"(\d+[.,]?\d*)\s*м²")
RE_TITLE_ROOMS = re.compile(r"(\d+)\s*-?\s*комнатн|(студи[яюй])", re.IGNORECASE)
RE_FLOOR = re.compile(r"(\d+)\s+этаж\s+из\s+(\d+)", re.IGNORECASE)
RE_PRICE = re.compile(r"(\d[\d\s]+\d)\s*₽")
RE_PPM2 = re.compile(r"(\d[\d\s]+)\s*₽\s*за\s*м²", re.IGNORECASE)
RE_VIEWS = re.compile(r"(\d+)\s+просмотр", re.IGNORECASE)

# Detail / NLP extractors
RE_METRO_WALK = re.compile(
    r"(\d+)\s+минут\s+(?:неспешной\s+прогулки|ходьбы|пешком)", re.IGNORECASE
)
RE_YEAR = re.compile(r"\b(19\d{2}|20[0-2]\d)\b")

# Agency block ("Год основания 1995", "150 объектов")
RE_AGENCY_FOUNDED = re.compile(r"Год\s+основания\s+(\d{4})", re.IGNORECASE)
RE_AGENCY_OBJECTS = re.compile(r"(\d+)\s+объект", re.IGNORECASE)

# ---------------------------------------------------------------------------
# Section 3 — Russian date parsing
# ---------------------------------------------------------------------------

RU_MONTHS: dict[str, int] = {
    "января": 1, "февраля": 2, "марта": 3, "апреля": 4, "мая": 5, "июня": 6,
    "июля": 7, "августа": 8, "сентября": 9, "октября": 10, "ноября": 11, "декабря": 12,
}
RU_MONTH_NOMINATIVE: dict[str, int] = {
    "январь": 1, "февраль": 2, "март": 3, "апрель": 4, "май": 5, "июнь": 6,
    "июль": 7, "август": 8, "сентябрь": 9, "октябрь": 10, "ноябрь": 11, "декабрь": 12,
}
RE_RU_DATE = re.compile(r"(\d{1,2})\s+(\w+)\s+(\d{4})")
RE_DMY = re.compile(r"(\d{2})\.(\d{2})\.(\d{4})")


def parse_ru_date(text: str | None) -> date | None:
    """Parse Russian date string like '9 мая 2026' → date(2026, 5, 9). Genitive month form only."""
    if not text:
        return None
    m = RE_RU_DATE.search(text)
    if not m:
        return None
    day_s, month_ru, year_s = m.groups()
    month = RU_MONTHS.get(month_ru.lower())
    if not month:
        return None
    try:
        return date(int(year_s), month, int(day_s))
    except (ValueError, TypeError):
        return None


def parse_dmy(text: str | None) -> date | None:
    """Parse DD.MM.YYYY format (used by Yandex Valuation tool history) → date."""
    if not text:
        return None
    m = RE_DMY.search(text)
    if not m:
        return None
    try:
        return date(int(m.group(3)), int(m.group(2)), int(m.group(1)))
    except (ValueError, TypeError):
        return None


# Relative date parsing (Yandex SERP shows "N дней назад" / "N часов назад")
_RE_REL_DATE = re.compile(
    r"(?P<n>\d+)\s+(?P<unit>"
    r"секунд[ауы]?|"
    r"минут[ауы]?|"
    r"час(?:а|ов)?|"
    r"день|дн(?:я|ей?)|"
    r"недел[июяь]+|"
    r"месяц(?:а|ев)?|"
    r"год(?:а|ов)?"
    r")\s+назад",
    flags=re.I,
)
_REL_UNIT_DAYS: dict[str, int] = {
    "секунд": 0, "минут": 0, "час": 0,
    "день": 1, "дн": 1,
    "недел": 7,
    "месяц": 30,
    "год": 365,
}


def _parse_relative_date_yandex(s: str | None) -> date | None:
    """Parse 'N дней/недель/месяцев назад' → date. Returns None if not matched."""
    if not s:
        return None
    m = _RE_REL_DATE.search(s)
    if not m:
        return None
    n = int(m["n"])
    unit_raw = m["unit"].lower()
    for prefix, days in _REL_UNIT_DAYS.items():
        if unit_raw.startswith(prefix):
            return date.today() - timedelta(days=n * days)
    return None


RE_RU_DATE_NO_YEAR = re.compile(
    r"(\d{1,2})\s+(январ\w*|феврал\w*|март\w*|апрел\w*|ма[яй]|"
    r"июн\w*|июл\w*|август\w*|сентябр\w*|октябр\w*|ноябр\w*|декабр\w*)"
    r"(?!\s+\d{4})",
    flags=re.I,
)
_RU_MONTH_PREFIXES: dict[str, int] = {
    "январ": 1, "феврал": 2, "март": 3, "апрел": 4,
    "ма": 5, "июн": 6, "июл": 7, "август": 8,
    "сентябр": 9, "октябр": 10, "ноябр": 11, "декабр": 12,
}


def parse_listing_date(text: str | None) -> date | None:
    """Parse listing date from Yandex card text.

    Tries in order:
    1. Keyword shortcut: 'сегодня' / 'вчера' / 'позавчера'  → relative day
    2. Absolute Russian date with year: '9 мая 2026' → date(2026, 5, 9)
    3. Absolute without year: '18 мая' → current year (rollback to prev
       year if month >30 дней в будущем)
    4. Relative date: 'N дней назад' → date.today() - N days

    Returns None if none match.
    """
    if not text:
        return None
    text_lower = text.lower()

    # 1. Keyword shortcuts (common on Yandex SERP for recent cards).
    if "позавчера" in text_lower:
        return date.today() - timedelta(days=2)
    if "вчера" in text_lower:
        return date.today() - timedelta(days=1)
    if "сегодня" in text_lower or "только что" in text_lower:
        return date.today()

    # 2. Absolute with year (existing).
    result = parse_ru_date(text)
    if result is not None:
        return result

    # 3. Absolute without year — infer current, rollback to prev if future.
    m = RE_RU_DATE_NO_YEAR.search(text)
    if m:
        day = int(m.group(1))
        month_raw = m.group(2).lower()
        month: int | None = None
        for prefix, num in _RU_MONTH_PREFIXES.items():
            if month_raw.startswith(prefix):
                month = num
                break
        if month is not None and 1 <= day <= 31:
            today = date.today()
            try:
                parsed = date(today.year, month, day)
            except ValueError:
                parsed = None
            if parsed and (parsed - today).days > 30:
                try:
                    parsed = date(today.year - 1, month, day)
                except ValueError:
                    parsed = None
            if parsed:
                return parsed

    # 4. Relative numeric.
    return _parse_relative_date_yandex(text)


# ---------------------------------------------------------------------------
# Section 4 — House type / class NLP from description text
# ---------------------------------------------------------------------------


def parse_house_type(text: str | None) -> str | None:
    """Extract house material type from free-form description.

    Returns: 'panel' | 'monolith_brick' | 'monolith' | 'brick' | 'block' | 'wood' | None.
    Order matters: 'monolith_brick' is checked before 'monolith' and 'brick' alone.
    """
    if not text:
        return None
    t = text.lower()
    if "панельн" in t:
        return "panel"
    if "монолит" in t and "кирпич" in t:
        return "monolith_brick"
    if "монолит" in t:
        return "monolith"
    if "кирпичн" in t:
        return "brick"
    if "блочн" in t:
        return "block"
    if "деревянн" in t:
        return "wood"
    return None


def parse_house_class(text: str | None) -> str | None:
    """Extract ЖК class from description.

    Returns: 'elite' | 'premium' | 'business' | 'comfort_plus' | 'comfort' | 'economy' | None.
    """
    if not text:
        return None
    t = text.lower()
    if re.search(r"класса?\s+элит|элитный\s+класс", t):
        return "elite"
    if re.search(r"класса?\s+премиум|премиум.{0,5}класс", t):
        return "premium"
    if re.search(r"класса?\s+бизнес", t):
        return "business"
    if re.search(r"класса?\s+комфорт\s*\+", t):
        return "comfort_plus"
    if re.search(r"класса?\s+комфорт(?!\s*\+)", t):
        return "comfort"
    if re.search(r"класса?\s+эконом", t):
        return "economy"
    return None


# ---------------------------------------------------------------------------
# Section 5 — Money parsing
# ---------------------------------------------------------------------------

RE_RUB_MLN = re.compile(r"([\d,.]+)\s*млн\s*₽", re.IGNORECASE)
RE_RUB_RAW = re.compile(r"(\d[\d\s]*\d|\d)")


def parse_rub(text: str | None) -> int | None:
    """Parse Russian price string → integer rubles.

    Supports:
      '4 399 000 ₽'   → 4_399_000
      '4,4 млн ₽'     → 4_400_000
      '4.4 млн ₽'     → 4_400_000
      '117 500'       → 117_500   (raw digits without currency, e.g. ppm2)
      None / 'без цены' / ''      → None
    """
    if not text:
        return None
    text = text.strip()
    if not text:
        return None

    m = RE_RUB_MLN.search(text)
    if m:
        try:
            # `\s` strips also NBSP (\xa0), thin space, и т.д. — Yandex SERP
            # форматирует «9\xa0800\xa0000» через NBSP, не regular space.
            cleaned = re.sub(r"\s", "", m.group(1)).replace(",", ".")
            return int(float(cleaned) * 1_000_000)
        except (ValueError, TypeError):
            pass

    m = RE_RUB_RAW.search(text)
    if m:
        # Same NBSP issue: `.replace(" ", "")` оставляет \xa0 → int() raises.
        cleaned = re.sub(r"\s", "", m.group(1))
        try:
            return int(cleaned)
        except ValueError:
            return None
    return None