from datetime import datetime, timedelta
import logging
from typing import Any, Generator
from data_access import Listing
from models.listing import (
    BuyListing,
    FurnishType,
    Listing as modelListing,
    ListingType,
    QueryParameters,
    RentListing,
)
from sqlalchemy import Engine, func, select as sa_select
from sqlmodel import Session, select
from tqdm import tqdm

logger = logging.getLogger("uvicorn.error")

# Columns needed for GeoJSON streaming (excludes routing_info_json, additional_info)
STREAMING_COLUMNS = [
    'id', 'price', 'number_of_bedrooms', 'square_meters',
    'longitude', 'latitude', 'photo_thumbnail', 'last_seen',
    'agency', 'price_history_json', 'available_from',
    'service_charge', 'lease_left',
]


class ListingRepository:
    engine: Engine

    # Monthly rent prices in the UK are always below 20,000 GBP.
    # Any listing priced at or above this threshold is treated as a purchase (buy) listing.
    BUY_LISTING_PRICE_THRESHOLD: int = 20_000

    def __init__(self, engine: Engine):
        self.engine = engine

    async def get_listings(
        self,
        query_parameters: QueryParameters | None = None,
        only_ids: list[int] | None = None,
        limit: int | None = None,
    ) -> list[modelListing]:
        """
        Get all listings from the database.
        """
        only_ids = only_ids or []

        model = self._get_model_for_query(query_parameters)

        query = select(model)
        if only_ids:
            query = query.where(model.id.in_(only_ids))  # type: ignore
        query = self._apply_query_filters(query, model, query_parameters)
        if limit:
            query = query.limit(limit)

        with Session(self.engine) as session:
            rows = list(session.exec(query).all())
        logging.debug(f"Found {len(rows)} listings")
        return rows

    def stream_listings(
        self,
        query_parameters: QueryParameters | None = None,
        limit: int | None = None,
        chunk_size: int = 100,
    ) -> Generator[modelListing, None, None]:
        """Yield listings one at a time for streaming.

        Uses yield_per for memory-efficient iteration over large result sets.

        Args:
            query_parameters: Filtering parameters
            limit: Maximum number of listings to yield
            chunk_size: Number of rows to fetch at a time from the database
        """
        model = self._get_model_for_query(query_parameters)

        query = select(model)
        query = self._apply_query_filters(query, model, query_parameters)
        if limit:
            query = query.limit(limit)

        with Session(self.engine) as session:
            for listing in session.exec(query).yield_per(chunk_size):
                yield listing

    def _get_model_for_query(
        self, query_parameters: QueryParameters | None
    ) -> type[RentListing] | type[BuyListing]:
        """Get the appropriate model class based on query parameters."""
        if query_parameters and query_parameters.listing_type == ListingType.BUY:
            return BuyListing
        return RentListing

    def count_listings(self, query_parameters: QueryParameters | None = None) -> int:
        """Fast count for progress estimation."""
        model = self._get_model_for_query(query_parameters)

        query = sa_select(func.count(model.id))
        query = self._apply_query_filters(query, model, query_parameters)

        with Session(self.engine) as session:
            return session.execute(query).scalar() or 0

    def stream_listings_optimized(
        self,
        query_parameters: QueryParameters | None = None,
        limit: int | None = None,
        page_size: int = 100,
    ) -> Generator[dict, None, None]:
        """Stream listings with keyset pagination and column projection.

        Uses keyset pagination for O(1) performance at any offset, and only
        fetches columns needed for GeoJSON (excludes large JSON blobs).

        Args:
            query_parameters: Filtering parameters
            limit: Maximum number of listings to yield
            page_size: Number of rows to fetch per database round-trip
        """
        model = self._get_model_for_query(query_parameters)

        # Select only needed columns (excludes routing_info_json, additional_info)
        columns = [
            getattr(model, col) for col in STREAMING_COLUMNS if hasattr(model, col)
        ]

        last_id: int | None = None
        total_yielded = 0

        while True:
            if limit and total_yielded >= limit:
                break

            query = sa_select(*columns)
            query = self._apply_query_filters(
                query, model, query_parameters
            )

            # Keyset pagination: WHERE id > last_id (O(1) performance)
            if last_id is not None:
                query = query.where(model.id > last_id)

            batch_limit = page_size
            if limit:
                batch_limit = min(page_size, limit - total_yielded)
            query = query.order_by(model.id).limit(batch_limit)

            with Session(self.engine) as session:
                results = session.execute(query).fetchall()

            if not results:
                break

            for row in results:
                yield row._asdict()
                last_id = row.id
                total_yielded += 1

            if len(results) < page_size:
                break

    def _apply_query_filters(
        self,
        query: Any,
        model: type[RentListing] | type[BuyListing],
        query_parameters: QueryParameters | None = None,
    ) -> Any:
        """Apply WHERE clauses from query parameters to a query.

        Works with both SQLModel select() and raw SQLAlchemy sa_select() queries,
        since both support the .where() interface.

        Args:
            query: A SQLModel or SQLAlchemy select query
            model: The listing model class (RentListing or BuyListing)
            query_parameters: Optional filtering parameters

        Returns:
            The query with WHERE clauses applied
        """
        if query_parameters is None:
            return query
        query = query.where(
            model.number_of_bedrooms.between(
                query_parameters.min_bedrooms, query_parameters.max_bedrooms
            ),
            model.price.between(query_parameters.min_price, query_parameters.max_price),
        )
        if query_parameters.min_sqm is not None:
            query = query.where(model.square_meters >= query_parameters.min_sqm)
        if query_parameters.max_sqm is not None:
            query = query.where(model.square_meters <= query_parameters.max_sqm)
        if query_parameters.min_price_per_sqm is not None:
            query = query.where(
                model.square_meters.is_not(None),
                model.square_meters > 0,
                (model.price / model.square_meters) >= query_parameters.min_price_per_sqm,
            )
        if query_parameters.max_price_per_sqm is not None:
            query = query.where(
                model.square_meters.is_not(None),
                model.square_meters > 0,
                (model.price / model.square_meters) <= query_parameters.max_price_per_sqm,
            )
        if query_parameters.furnish_types and model == RentListing:
            query = query.where(model.furnish_type.in_(query_parameters.furnish_types))
        if (
            model == RentListing
            and query_parameters.let_date_available_from is not None
        ):
            query = query.where(
                model.available_from >= query_parameters.let_date_available_from
            )
        if query_parameters.last_seen_days is not None:
            last_seen_threshold = datetime.now() - timedelta(
                days=query_parameters.last_seen_days
            )
            query = query.where(model.last_seen >= last_seen_threshold)
        return query

    async def upsert_listings(
        self,
        listings: list[modelListing],
    ) -> list[modelListing]:
        """
        Upsert listings into the database.
        """
        models = []
        with Session(self.engine) as session:
            for listing in listings:
                session.merge(listing)
                models.append(listing)
            session.commit()
        return models

    async def upsert_listings_legacy(
        self,
        listings: list[Listing],
    ) -> list[modelListing]:
        """Upsert legacy Listing objects into the database.

        .. deprecated::
            This method converts legacy data_access.Listing objects to SQLModel
            entities. Use upsert_listings() with RentListing/BuyListing directly.

        Legacy Listing objects from filesystem-based data may contain malformed
        or incomplete data, so conversion errors are logged and skipped rather
        than aborting the entire batch.
        """
        models = []
        failed_to_upsert = []
        with Session(self.engine) as session:
            for listing in tqdm(listings, desc="Upserting listings"):
                # Convert legacy Listing to the appropriate SQLModel entity
                try:
                    model_listing = await self._get_concrete_listing(listing)
                except Exception as e:
                    # Legacy Listing -> model conversion may fail for malformed data
                    # (e.g. missing required fields, invalid types). Log and skip.
                    logger.error(f"Error converting listing {listing.identifier}: {e}")
                    failed_to_upsert.append(listing)
                    continue
                session.merge(model_listing)
                models.append(model_listing)
            session.commit()
        if failed_to_upsert:
            logger.warning(f"Failed to upsert {len(failed_to_upsert)} listings.")
        return models

    @staticmethod
    def _parse_furnish_type(listing: Listing) -> FurnishType:
        """Extract and normalize the furnish type from a legacy Listing's detail object.

        Handles missing/null detailobject, missing property key, missing or null
        letFurnishType value, and normalizes "landlord" variants to ASK_LANDLORD.

        Args:
            listing: A legacy data_access.Listing object

        Returns:
            The parsed FurnishType enum value
        """
        if (
            listing.detailobject is None
            or listing.detailobject.get("property") is None
            or listing.detailobject["property"].get("letFurnishType") is None
        ):
            return FurnishType.UNKNOWN

        furnish_type_str = listing.detailobject["property"]["letFurnishType"]
        if furnish_type_str is None:
            return FurnishType.UNKNOWN
        elif "landlord" in furnish_type_str.lower():
            furnish_type_str = "ask landlord"
        else:
            furnish_type_str = furnish_type_str.lower()

        return FurnishType(furnish_type_str)

    async def _get_concrete_listing(
        self,
        listing: Listing,
    ) -> modelListing:
        now = datetime.now()
        furnish_type = self._parse_furnish_type(listing)

        if listing.price < self.BUY_LISTING_PRICE_THRESHOLD:
            model_listing = RentListing(
                id=listing.identifier,
                price=listing.price,
                number_of_bedrooms=listing.bedrooms,
                square_meters=await listing.sqm_ocr(),
                agency=listing.agency,
                council_tax_band=listing.councilTaxBand,
                longitude=listing.longitude,
                latitude=listing.latitude,
                price_history_json=modelListing.serialize_price_history(
                    listing.priceHistory
                ),
                listing_site=listing.listing_site,
                last_seen=now,
                photo_thumbnail=listing.photoThumbnail,
                furnish_type=furnish_type,
                available_from=listing.letDateAvailable,
                additional_info=listing.detailobject,
            )
        else:
            model_listing = BuyListing(
                id=listing.identifier,
                price=listing.price,
                number_of_bedrooms=listing.bedrooms,
                square_meters=await listing.sqm_ocr(),
                agency=listing.agency,
                council_tax_band=listing.councilTaxBand,
                longitude=listing.longitude,
                latitude=listing.latitude,
                price_history_json=modelListing.serialize_price_history(
                    listing.priceHistory
                ),
                listing_site=listing.listing_site,
                last_seen=now,
                photo_thumbnail=listing.photoThumbnail,
                service_charge=listing.serviceCharge,
                additional_info=listing.detailobject,
            )

        return model_listing

    def get_listing_ids(
        self,
        listing_type: ListingType = ListingType.RENT,
    ) -> set[int]:
        """Get all listing IDs from the database (ID-only projection).

        Much faster than get_listings() when only IDs are needed for
        filtering against API results.
        """
        model = RentListing if listing_type == ListingType.RENT else BuyListing
        with Session(self.engine) as session:
            result = session.execute(sa_select(model.id))
            return {row[0] for row in result.fetchall()}

    async def mark_seen(self, listing_id: int, listing_type: ListingType = ListingType.RENT) -> None:
        query_params = QueryParameters(listing_type=listing_type)
        listings = await self.get_listings(only_ids=[listing_id], query_parameters=query_params)
        if len(listings) == 0:
            return
        listing = listings[0]
        now = datetime.now()
        listing.last_seen = now
        await self.upsert_listings([listing])