import csv
import io
from datetime import datetime


def parse_chase_csv(content: str, account_type: str) -> tuple[list[dict], list[str]]:
    """Parse a Chase CSV file into transaction dicts.

    Returns (rows, errors) where rows is a list of dicts with keys:
    date, amount, category, description.
    """
    content = content.lstrip("\ufeff")
    reader = csv.DictReader(io.StringIO(content))

    if not reader.fieldnames:
        return [], ["Empty CSV file"]

    first_field = reader.fieldnames[0].strip()
    if first_field == "Details":
        return _parse_checking(reader)
    elif first_field == "Transaction Date":
        return _parse_credit_card(reader)
    else:
        return [], [f"Unrecognized CSV format (first column: '{first_field}')"]


def _parse_checking(reader: csv.DictReader) -> tuple[list[dict], list[str]]:
    """Chase checking/savings: Details,Posting Date,Description,Amount,Type,Balance,Check or Slip #"""
    rows = []
    errors = []
    for i, row in enumerate(reader, start=2):
        try:
            date_str = row.get("Posting Date", "").strip()
            description = row.get("Description", "").strip()
            amount_str = row.get("Amount", "").strip()
            if not date_str or not amount_str:
                continue
            rows.append({
                "date": datetime.strptime(date_str, "%m/%d/%Y").date(),
                "amount": float(amount_str),
                "category": "Uncategorized",
                "description": description,
            })
        except (ValueError, KeyError) as e:
            errors.append(f"Row {i}: {e}")
    return rows, errors


def _parse_credit_card(reader: csv.DictReader) -> tuple[list[dict], list[str]]:
    """Chase credit card: Transaction Date,Post Date,Description,Category,Type,Amount,Memo"""
    rows = []
    errors = []
    for i, row in enumerate(reader, start=2):
        try:
            date_str = row.get("Transaction Date", "").strip()
            description = row.get("Description", "").strip()
            amount_str = row.get("Amount", "").strip()
            category = row.get("Category", "").strip() or "Uncategorized"
            if not date_str or not amount_str:
                continue
            rows.append({
                "date": datetime.strptime(date_str, "%m/%d/%Y").date(),
                "amount": float(amount_str),
                "category": category,
                "description": description,
            })
        except (ValueError, KeyError) as e:
            errors.append(f"Row {i}: {e}")
    return rows, errors