"""计算引擎：规则、读取、分组、结转/补发/累计逻辑"""
import openpyxl
from collections import defaultdict

# RULES: 18T用(1000/0/1000/1000), 非18T保持原逻辑(未达标不发, 结转补发=原奖励额)
RULES = {
    '交投40辆4.5T普货':    {'km': 3000, 'good': 150, 'bad': 0,   'carry': 150, 'other': 150},
    '交投190辆4.5T冷链车': {'km': 3000, 'good': 150, 'bad': 0,   'carry': 150, 'other': 150},
    '羚牛136辆4.5T冷链车': {'km': 5000, 'good': 260, 'bad': 0,   'carry': 260, 'other': 260},
    '恒运50辆4.5T普货':    {'km': 5000, 'good': 260, 'bad': 0,   'carry': 260, 'other': 260},
    '恒运50辆4.5T 普货':   {'km': 5000, 'good': 260, 'bad': 0,   'carry': 260, 'other': 260},
    '羚牛100辆18T':        {'km': 6000, 'good': 1000, 'bad': 0, 'carry': 1000, 'other': 1000},
}

# 2026年7月经业务确认的4辆18T执行下半年新政策：
# 月目标5000公里，达标150元，未达标不发，结转/补发按150元基准。
# 其余18T继续使用上面的原口径。
JULY_SCHEME3_PLATES = {'粤AGR0772', '粤AGQ0178', '粤AGP6675', '粤AGP9757'}
JULY_SCHEME3_RULE = {'km': 5000, 'good': 150, 'bad': 0, 'carry': 150, 'other': 150}
DAYS = {1: 31, 2: 28, 3: 31, 4: 30, 5: 31, 6: 30, 7: 31, 8: 31, 9: 30, 10: 31, 11: 30, 12: 31}

def read_file(fp, month):
    wb = openpyxl.load_workbook(fp, data_only=True)
    ws = wb['业务考核视图']
    h = [c.value for c in next(ws.iter_rows(min_row=1, max_row=1))]
    recs = []
    for row in ws.iter_rows(min_row=2, values_only=True):
        r = dict(zip(h, row))
        r['考核天数'] = float(r.get('考核天数') or 0)
        r['应考核里程(km)'] = float(r.get('应考核里程(km)') or 0)
        r['实际行驶里程(km)'] = float(r.get('实际行驶里程(km)') or 0)
        r['月份'] = month
        if month == 7 and str(r.get('车牌号') or '').strip().upper() in JULY_SCHEME3_PLATES:
            rule = JULY_SCHEME3_RULE
        else:
            rule = RULES.get(r.get('考核目标', ''), {'km': 0, 'good': 0, 'bad': 0, 'carry': 0, 'other': 0})
        r['月度目标里程'] = rule.get('km', 0)
        r['奖励基准_达标'] = rule.get('good', 0)
        r['奖励基准_未达标'] = rule.get('bad', 0)
        r['奖励基准_结转'] = rule.get('carry', 0)
        r['奖励基准_补发'] = rule.get('other', 0)
        t, a = r['应考核里程(km)'], r['实际行驶里程(km)']
        q = a >= t and t > 0
        r['是否达标'] = '达标' if q else '未达标'
        if q:
            r['奖金'] = r['奖励基准_达标'] * (r['考核天数'] / DAYS[month])
        else:
            r['奖金'] = r['奖励基准_未达标'] * (r['考核天数'] / DAYS[month])
        r['多跑'] = max(0, a - t) if q else 0
        r['可结转'] = int(r['多跑'] // r['月度目标里程']) if r['月度目标里程'] > 0 and q else 0
        recs.append(r)
    wb.close()
    return recs

def grp(recs, month):
    gs = defaultdict(lambda: {'recs':[], '应考核':0, '实际':0, '奖金':0, '天数':0,
                               '有达标':False, '目标km':0, '奖励达标':0, '奖励未达标':0,
                               '奖励结转':0, '奖励补发':0})
    for r in recs:
        k = (r['车牌号'], r['销售经理'])
        g = gs[k]
        g['recs'].append(r)
        g['应考核'] += r['应考核里程(km)']
        g['实际'] += r['实际行驶里程(km)']
        g['奖金'] += r['奖金']
        g['天数'] += r['考核天数']
        if r['是否达标'] == '达标': g['有达标'] = True
        g['目标km'] = max(g['目标km'], r['月度目标里程'])
        g['奖励达标'] = max(g['奖励达标'], r['奖励基准_达标'])
        g['奖励未达标'] = max(g['奖励未达标'], r['奖励基准_未达标'])
        g['奖励结转'] = max(g['奖励结转'], r['奖励基准_结转'])
        g['奖励补发'] = max(g['奖励补发'], r['奖励基准_补发'])
        g['部门'] = r['部门名称']
        g['销售'] = r['销售经理']
        g['车牌'] = r['车牌号']
    return dict(gs)

def calc_jan_carryover(G1):
    for k, g in G1.items():
        tc = 0
        for r in g['recs']:
            if r['是否达标'] == '达标': tc += r['可结转']
        g['可结转'] = tc
        g['累计已发结转'] = 0
        g['1月已发'] = g['有达标']  # 当月有达标 → 已发
        g['cum_t'] = g['应考核']
        g['cum_a'] = g['实际']
        g['cum_q'] = g['实际'] >= g['应考核'] and g['应考核'] > 0

def calc_month(month, G_all, all_data, G_prev, G_cur):
    """通用月计算: 结转/补发/累计补发/当月"""
    prev_m = month - 1
    days_m = DAYS[month]
    data_m = {'结转': [], '当月': []}
    # 向后兼容的key: 当月达标/当月未达标 用于18T区分
    data_18t = {'当月达标': [], '当月未达标': []}
    use_18t = True  # 统一使用拆分标签

    for k, gm in G_cur.items():
        gp = G_prev.get(k)

        # 累计
        cum_t = (gp['cum_t'] if gp else 0) + gm['应考核']
        cum_a = (gp['cum_a'] if gp else 0) + gm['实际']
        cum_q = cum_a >= cum_t and cum_t > 0

        # 结转: carry × 1 (整月, 不折算)
        carry = 0
        p_carry = gp['可结转'] if gp else 0
        if gp and p_carry >= 1:
            carry = gm['奖励结转']
            data_m['结转'].append({'车牌': k[0], '销售': gp['销售'], '部门': gm['部门'], '额': carry})

        # 当月奖金
        is_18t = gm['奖励达标'] == 1000  # 18T特征
        bonus = 0
        if carry == 0 and gm['奖金'] > 0:
            bonus = gm['奖金']
            data_m['当月'].append({'车牌': k[0], '销售': gm['销售'], '部门': gm['部门'], '额': bonus})

        # 补发历史月: other × 折算
        for back_m in range(1, month):
            label = f'补发{back_m}月'
            if label not in data_m:
                data_m[label] = []
            g_bm = G_all[back_m].get(k)
            if not g_bm:
                continue
            bm_paid = g_bm.get(f'{back_m}月已发', g_bm['有达标'])
            if bm_paid:
                continue
            bm_paid_later = False
            for later_m in range(back_m + 1, month):
                gl = G_all[later_m].get(k)
                if gl and gl.get(f'补发{back_m}月', 0) > 0:
                    bm_paid_later = True
                    break
            if bm_paid_later:
                continue
            if cum_q:
                bj = g_bm['奖励补发'] * (g_bm['天数'] / DAYS[back_m])
                data_m[label].append({'车牌': k[0], '销售': g_bm['销售'], '部门': gm['部门'], '额': bj})
                gm[f'补发{back_m}月'] = bj

        # 累计补发当月: other × 折算
        label_cbp = f'累计补发{month}月'
        if label_cbp not in data_m:
            data_m[label_cbp] = []
        cbp = 0
        if not gm['有达标'] and carry == 0 and cum_q:
            cbp = gm['奖励补发'] * (gm['天数'] / days_m)
            data_m[label_cbp].append({'车牌': k[0], '销售': gm['销售'], '部门': gm['部门'], '额': cbp})

        gm['cum_t'] = cum_t
        gm['cum_a'] = cum_a
        gm['cum_q'] = cum_q
        gm['结转'] = carry
        gm['当月奖金'] = bonus
        gm['累计补发当月'] = cbp
        gm[f'{month}月已发'] = carry > 0 or gm['奖金'] > 0 or cbp > 0

        # 更新可结转
        cum_over = max(0, cum_a - cum_t) if cum_q else 0
        earned = int(cum_over // gm['目标km']) if gm['目标km'] > 0 else 0
        prev_used = gp['累计已发结转'] if gp else 0
        cur_used = prev_used + (1 if carry > 0 else 0)
        gm['累计已发结转'] = cur_used
        gm['可结转'] = max(0, earned - cur_used)

    # 补充: 上月有结转但本月无考核记录的车
    for k, gp in G_prev.items():
        if k not in G_cur and gp.get('可结转', 0) >= 1:
            carry = gp['奖励结转']
            data_m['结转'].append({'车牌': k[0], '销售': gp['销售'], '部门': gp['部门'], '额': carry})
            G_cur[k] = {
                'recs': [], '应考核': gp['目标km'], '实际': 0, '奖金': 0, '天数': days_m,
                '有达标': False, '目标km': gp['目标km'],
                '奖励达标': gp['奖励达标'], '奖励未达标': gp['奖励未达标'],
                '奖励结转': gp['奖励结转'], '奖励补发': gp['奖励补发'],
                '部门': gp['部门'], '销售': gp['销售'], '车牌': k[0],
                'cum_t': gp.get('cum_t', 0) + gp['目标km'], 'cum_a': gp.get('cum_a', 0),
                'cum_q': False,
                '结转': carry, '当月奖金': 0,
                f'{month}月已发': True,
                '可结转': max(0, gp['可结转'] - 1),
                '累计已发结转': gp.get('累计已发结转', 0) + 1,
                '虚拟': True,
            }

    all_data[month] = data_m
    return data_m, G_cur


def collect_vehicle_payments(G, all_data):
    """收集所有月的付款记录"""
    payments = defaultdict(list)
    info = {}

    # 1月
    for k, g in G[1].items():
        plate = k[0]
        if not info.get(plate):
            first = g['recs'][0]
            info[plate] = {'考核目标': first.get('考核目标', ''), '月度奖励': g['奖励达标'], '目标km': g['目标km']}
        if g['奖金'] > 0:
            payments[plate].append({'结算月': 1, '对应考核月': 1, '业务员': g['销售'],
                                     '金额': g['奖金'], '类型': '当月达标', '部门': g['部门']})

    # 2月-7月
    cat_map = {}
    for month in range(2, 8):
        cat_map[('结转', month)] = month
        for bm in range(1, month):
            cat_map[(f'补发{bm}月', month)] = bm
        cat_map[('当月', month)] = month
        cat_map[(f'累计补发{month}月', month)] = month

    for month in range(2, 8):
        mdata = all_data.get(month, {})
        for cat, dl in mdata.items():
            assess_month = cat_map.get((cat, month), month)
            for d in dl:
                payments[d['车牌']].append({'结算月': month, '对应考核月': assess_month,
                    '业务员': d['销售'], '金额': d['额'], '类型': cat, '部门': d['部门']})

    for m in G:
        for k, g in G[m].items():
            if not info.get(k[0]):
                first = g['recs'][0] if g['recs'] else None
                if first:
                    info[k[0]] = {'考核目标': first.get('考核目标', ''), '月度奖励': g['奖励达标'], '目标km': g['目标km']}

    for plate in payments:
        records = sorted(payments[plate], key=lambda x: (x['对应考核月'], x['结算月']))
        for i, r in enumerate(records): r['期数'] = i + 1
    return payments, info


# (归属公司+车型) → 考核目标 映射，用于补全无考核记录的车辆
VEHICLE_TARGET_MAP = {
    ('广州开发区交投氢能运营管理有限公司', '4.5吨冷链车'): ('交投190辆4.5T冷链车', 3000, 150),
    ('广州开发区交投氢能运营管理有限公司', '4.5吨货车'): ('交投40辆4.5T普货', 3000, 150),
    ('羚牛氢能科技(广东)有限公司', '4.5吨冷链车'): ('羚牛136辆4.5T冷链车', 5000, 260),
    ('羚牛氢能科技(广东)有限公司', '18吨双飞翼货车'): ('羚牛100辆18T', 6000, 1000),
    ('现代氢能科技(广州)有限公司', '4.5吨货车'): ('恒运50辆4.5T普货', 5000, 260),
    ('现代氢能科技（广州）有限公司', '4.5吨货车'): ('恒运50辆4.5T普货', 5000, 260),
}


def read_loss_data(month):
    """读取亏损表，返回 {客户名称: '是'/'否'} 字典。无亏损表返回None"""
    import os
    fp = f'{month}月.xlsx'
    if not os.path.exists(fp):
        return None

    wb = openpyxl.load_workbook(fp, data_only=True)
    ws = wb[wb.sheetnames[0]]
    h = [c.value for c in next(ws.iter_rows(min_row=1, max_row=1))]

    client_col = None; loss_col = None
    for i, col_name in enumerate(h):
        if col_name and ('项目' in str(col_name) or '客户' in str(col_name)):
            client_col = i
        if col_name and '亏损' in str(col_name):
            loss_col = i

    if client_col is None or loss_col is None:
        wb.close()
        return None

    result = {}
    for row in ws.iter_rows(min_row=2, values_only=True):
        client = row[client_col]
        loss = row[loss_col]
        if client:
            result[str(client).strip()] = str(loss).strip() if loss else ''
    wb.close()
    return result


def get_vehicle_client_map(D):
    """从考核源数据构建 {车牌号: 客户名称} 映射（取最新月的客户名）"""
    plate_client = {}
    for m in sorted(D.keys()):
        for r in D[m]:
            plate_client[r['车牌号']] = r.get('客户名称', '')
    return plate_client


def read_master_vehicles(fp='里程任务考核_Q1汇总.xlsx'):
    """从现有Q1汇总文件读取全量车辆台账"""
    wb = openpyxl.load_workbook(fp, data_only=True)
    ws = wb['车辆奖金池总览']
    h = [c.value for c in next(ws.iter_rows(min_row=1, max_row=1))]
    vehicles = []
    for row in ws.iter_rows(min_row=2, values_only=True):
        r = dict(zip(h, row))
        if r.get('车牌号'):
            vehicles.append({'车牌号': r['车牌号'], '车架号': r.get('车架号', ''),
                             '归属公司': r.get('归属公司', ''), '车型确定': r.get('车型', '')})
    wb.close()
    return vehicles