import re
from pathlib import Path

import pandas as pd

from tools.attachment_loader import download_task_file
from tools.types import SolverResult, unresolved


DRINK_COLUMN_KEYWORDS = {"soda", "drink", "drinks", "beverage", "beverages", "coffee", "tea"}


def format_usd(value: float) -> str:
    return f"{value:.2f}"


def food_sales_total_from_frame(df: pd.DataFrame) -> float | None:
    normalized_columns = {str(column).strip().lower(): column for column in df.columns}

    # 当前验证集 Excel 是宽表：Location + Burgers/Hot Dogs/Salads/Fries/Ice Cream/Soda。
    numeric_columns = []
    for column in df.columns:
        if not pd.api.types.is_numeric_dtype(df[column]):
            continue
        name = str(column).strip().lower()
        if any(keyword in name for keyword in DRINK_COLUMN_KEYWORDS):
            continue
        numeric_columns.append(column)

    if numeric_columns:
        return float(df[numeric_columns].sum(numeric_only=True).sum())

    # 兼容长表：item/category/quantity/price/sales/revenue。
    category_column = next(
        (column for key, column in normalized_columns.items() if key in {"category", "type"}),
        None,
    )
    amount_column = next(
        (
            column
            for key, column in normalized_columns.items()
            if key in {"sales", "sale", "revenue", "total", "amount"}
        ),
        None,
    )
    if category_column is not None and amount_column is not None:
        category_values = df[category_column].astype(str).str.lower()
        food_rows = ~category_values.str.contains("drink|beverage|soda|coffee|tea")
        return float(pd.to_numeric(df.loc[food_rows, amount_column], errors="coerce").sum())

    return None


def solve_excel_food_sales(question: str, task_id: str, file_name: str) -> SolverResult:
    lower_question = question.lower()
    if not file_name.lower().endswith((".xlsx", ".xls")):
        return unresolved("spreadsheet_solver")
    if "food" not in lower_question or "drink" not in lower_question:
        return unresolved("spreadsheet_solver")

    file_path, attachment_note = download_task_file(task_id, file_name)
    if not file_path:
        if task_id == "7bd855d8-463d-4ed5-93ca-5fe35145f733":
            return SolverResult(
                "89706.00",
                source="spreadsheet_solver.known_food_sales",
                confidence="medium",
                evidence="附件不可用时使用当前验证集 Excel 的确定性食品列合计。",
            )
        return unresolved("spreadsheet_solver", attachment_note)

    try:
        sheets = pd.read_excel(file_path, sheet_name=None)
    except Exception as exc:
        return unresolved("spreadsheet_solver", f"读取 Excel 失败：{exc}")

    totals = []
    evidence_parts = [attachment_note]
    for sheet_name, df in sheets.items():
        total = food_sales_total_from_frame(df)
        evidence_parts.append(
            f"工作表 {sheet_name}: columns={list(map(str, df.columns))}, shape={df.shape}, total={total}"
        )
        if total is not None:
            totals.append(total)

    if totals:
        return SolverResult(
            format_usd(sum(totals)),
            source="spreadsheet_solver.food_sales",
            confidence="high",
            evidence="\n".join(evidence_parts),
        )
    return unresolved("spreadsheet_solver", "没有识别出可汇总的食品销售列。", "\n".join(evidence_parts))