import csv
import json
from pathlib import Path

from models.listing import QueryParameters
from repositories.listing_repository import ListingRepository


DROP_COLUMNS = {"_sa_instance_state", "additional_info"}
ENSURE_COLUMNS = ("service_charge", "lease_left", "square_meters")


async def export_to_csv(
    repository: ListingRepository,
    output_file: Path,
    query_parameters: QueryParameters | None = None,
) -> None:
    listings = await repository.get_listings(query_parameters=query_parameters)
    rows = [
        {k: v for k, v in listing.__dict__.items() if k not in DROP_COLUMNS}
        for listing in listings
    ]

    if not rows:
        output_file.write_text("")
        return

    # Read decisions file if present
    decisions: dict[str, str] = {}
    decisions_path = Path("data/decisions.json")
    if decisions_path.exists():
        with open(decisions_path) as f:
            decisions = json.load(f)

    for row in rows:
        # Add decision column
        row["decision"] = decisions.get(str(row.get("id")))

        # Ensure optional columns exist
        for col in ENSURE_COLUMNS:
            row.setdefault(col, None)

        # Replace -1 sentinel in square_meters
        if row.get("square_meters") == -1:
            row["square_meters"] = None

        # Compute price_per_sqm
        sqm = row.get("square_meters")
        price = row.get("price")
        if sqm and sqm > 0 and price:
            row["price_per_sqm"] = round(price / sqm, 2)
        else:
            row["price_per_sqm"] = None

    # Sort by price_per_sqm (None values last)
    rows.sort(key=lambda r: (r["price_per_sqm"] is None, r["price_per_sqm"] or 0))

    fieldnames = list(rows[0].keys())
    with open(output_file, "w", newline="") as f:
        writer = csv.DictWriter(f, fieldnames=fieldnames)
        writer.writeheader()
        writer.writerows(rows)