class Item(object):
    """單筆交易對(duì)象呆细，存儲(chǔ)購(gòu)買日期和數(shù)量 可能是買入也可能是賣出"""
    def __init__(self, time, num):

        if type(time) is int or type(time) is str:
            self.time = datetime.datetime.strptime(str(time),'%Y%m%d')
        else:
            self.time = time

        if type(num) is str:
            self.num = int(num)
        else:
            self.num = num


class Position(object):
    """頭寸對(duì)象雇逞，存儲(chǔ)某人員對(duì)于某股票的全部頭寸 以隊(duì)列模式先進(jìn)先出"""
    def __init__(self, stock_name, person_name):
        self.items = []
        self.stock_name = stock_name
        self.person_name = person_name

    def is_empty(self):
        return self.items == []

    def buy(self, item):
        """有買入則在items列表里追加此次交易記錄"""
        self.items.append(item)

    def sell(self, item, limit):
        """根據(jù)賣出的交易記錄更新本頭寸 返回可能存在的相關(guān)交易信息（以元組的列表返回）"""
        related = []
        # 首次記錄先是賣的，則pass
        if len(self.items) == 0 :
            return related
        else:
            # 不斷根據(jù)賣出數(shù)量抵消買入記錄诈唬，時(shí)間最久遠(yuǎn)的先被抵消，完全抵消后離開(kāi)隊(duì)列怎诫，賣出數(shù)量抵完為止
            while item.num > 0:
                # 判斷此次抵消的買入記錄是否和賣出記錄的日期差≤limit天
                if (item.time.date() - self.items[0].time.date()).days <= limit:
                    # 發(fā)現(xiàn)相關(guān)交易虐唠，將相關(guān)信息打包為元組，放入列表related
                    info = (self.person_name, self.stock_name, self.items[0].time,
                            self.items[0].num,
                            item.time,
                            min(item.num,self.items[0].num),
                            (item.time.date() - self.items[0].time.date()).days)
                    related.append(info)
                # 判斷最遠(yuǎn)的一次買入是否能完全抵消剩余賣出數(shù)量（臨界值稍微注意少态，和不能一樣也需要?jiǎng)h除隊(duì)列頭）
                if item.num >= self.items[0].num:
                    # 不能城侧，則先用最遠(yuǎn)的買入抵消部分賣出，剩余的賣出數(shù)量繼續(xù)被后面的買入抵消
                    item.num -= self.items[0].num
                    # 最遠(yuǎn)的買入記錄離開(kāi)隊(duì)列彼妻，循環(huán)繼續(xù)
                    del (self.items[0])
                    if len(self.items) == 0:  # 如果賣的比買的多嫌佑，直接跳出循環(huán)
                        return related
                else:
                    # 能，則最遠(yuǎn)的買入記錄完全消化剩余賣出數(shù)量侨歉，并留有余量屋摇，下一次循環(huán)會(huì)停止
                    self.items[0].num -= item.num
                    item.num = 0
            return related



def FIFO(df,col_people,col_stock,col_time,col_num,col_type,limit=1e4):
    df = df.sort_values(by=col_time)

    # dic 以人員，股票為索引存儲(chǔ)所有頭寸的字典
    dic = {}
    relate = []
    for row in df.iterrows():
        name = row[1][col_people]
        date = row[1][col_time]
        stock = row[1][col_stock]
        num = row[1][col_num]
        type = row[1][col_type]

        index = name + ','+stock
        if index not in dic:
            dic[index] = Position(person_name=name, stock_name=stock)

        if type == '買入':
            dic[index].buy(Item(date, num))

        else:
            #賣出交易返回信息
            relate += (dic[index].sell(Item(date,num),limit))
        print(name,date,stock,type)
    result = pd.DataFrame(relate)
    result.columns = ['PERSON','INSTRUMENT_CODE','BUY_TIME','BUY_VOLUME_CUMSUM','SELL_TIME','SELL_VOLUME','INTERVAL_DAYS']
    return result