import heurams.services.timer as timer
from heurams.context import config_var
from heurams.kernel.algorithms import algorithms


class Electron:
    """电子: 记忆分析元数据及算法"""

    def __init__(self, ident: str, algodata: dict = {}, algo_name: str = "supermemo2"):
        """初始化电子对象 (记忆数据)

        Args:
            ident: 算法的唯一标识符, 用于区分不同的算法实例, 使用 algodata[ident] 获取
            algodata: 算法数据字典, 包含算法的各项参数和设置
            algo: 使用的算法模块标识
        """
        self.algodata = algodata
        self.ident = ident
        self.algo = algorithms[algo_name]

        if self.algo not in self.algodata.keys():
            self.algodata[self.algo] = {}
        if not self.algodata[self.algo]:
            self._default_init(self.algo.defaults)

    def _default_init(self, defaults: dict):
        """默认初始化包装"""
        self.algodata[self.algo] = defaults.copy()

    def activate(self):
        """激活此电子"""
        self.algodata[self.algo]["is_activated"] = 1
        self.algodata[self.algo]["last_modify"] = timer.get_timestamp()

    def modify(self, var: str, value):
        """修改 algodata[algo] 中子字典数据"""
        if var in self.algodata[self.algo]:
            self.algodata[self.algo][var] = value
            self.algodata[self.algo]["last_modify"] = timer.get_timestamp()
        else:
            print(f"警告: '{var}' 非已知元数据字段")

    def is_due(self):
        """是否应该复习"""
        return self.algo.is_due(self.algodata)

    def is_activated(self):
        return self.algodata[self.algo]["is_activated"]

    def rate(self):
        "评价"
        return self.algo.rate(self.algodata)

    def nextdate(self) -> int:
        return self.algo.nextdate(self.algodata)

    def revisor(self, quality: int = 5, is_new_activation: bool = False):
        """算法迭代决策机制实现

        Args:
            quality (int): 记忆保留率量化参数 (0-5)
            is_new_activation (bool): 是否为初次激活
        """
        self.algo.revisor(self.algodata, quality, is_new_activation)

    def __str__(self):
        return (
            f"记忆单元预览 \n"
            f"标识符: '{self.ident}' \n"
            f"算法: {self.algo} \n"
            f"易度系数: {self.algodata[self.algo]['efactor']:.2f} \n"
            f"已经重复的次数: {self.algodata[self.algo]['rept']} \n"
            f"下次间隔: {self.algodata[self.algo]['interval']} 天 \n"
            f"下次复习日期时间戳: {self.algodata[self.algo]['next_date']}"
        )

    def __eq__(self, other):
        if self.ident == other.ident:
            return True
        return False

    def __hash__(self):
        return hash(self.ident)

    def __getitem__(self, key):
        if key == "ident":
            return self.ident
        if key in self.algodata[self.algo]:
            return self.algodata[self.algo][key]
        else:
            raise KeyError(f"键 '{key}' 未在 algodata[self.algo] 中")

    def __setitem__(self, key, value):
        if key == "ident":
            raise AttributeError("ident 应为只读")
        self.algodata[self.algo][key] = value
        self.algodata[self.algo]["last_modify"] = timer.get_timestamp()

    def __len__(self):
        """仅返回当前算法的配置数量"""
        return len(self.algodata[self.algo])

    @staticmethod
    def placeholder():
        """生成一个电子占位符"""
        return Electron("电子对象样例内容", {})