"""基金深度分析的数据整理层。"""
from __future__ import annotations

from decimal import Decimal
from typing import Iterable


def _number(value):
    if isinstance(value, Decimal):
        return float(value)
    return value


def _display_value(value):
    if value is None:
        return "暂无"
    if isinstance(value, float):
        return f"{value:g}"
    return str(value)


def _build_analysis_text(fund: dict, metrics: list[dict]) -> str:
    fund_name = fund.get("fund_name") or fund.get("fund_code") or "该基金"
    if not metrics:
        return f"{fund_name}暂无足够业绩数据，暂无法形成完整解读。"

    latest = metrics[-1]
    period = _display_value(latest.get("period"))
    return_rate = _display_value(latest.get("return_rate"))
    max_drawdown = _display_value(latest.get("max_drawdown"))
    sharpe = _display_value(latest.get("sharpe"))
    return (
        f"{fund_name}在{period}的历史收益率为{return_rate}%，"
        f"最大回撤为{max_drawdown}%，夏普比率为{sharpe}。"
        "以上仅基于历史业绩数据，不代表未来收益。"
    )


def build_fund_analysis(fund: dict, performance_rows: Iterable[dict]) -> dict:
    metrics = []
    for row in performance_rows:
        metrics.append(
            {
                key: _number(value)
                for key, value in row.items()
            }
        )
    return {
        "fund_code": fund.get("fund_code"),
        "fund_name": fund.get("fund_name"),
        "risk_level": fund.get("risk_level"),
        "metrics": metrics,
        "analysis_text": _build_analysis_text(fund, metrics),
        "chart_data": {
            "periods": [row.get("period") for row in metrics],
            "return_rate": [row.get("return_rate") for row in metrics],
            "annual_volatility": [row.get("annual_volatility") for row in metrics],
            "max_drawdown": [row.get("max_drawdown") for row in metrics],
            "sharpe": [row.get("sharpe") for row in metrics],
        },
    }