from apps.enm.models import Mpoint, MpointStat, EnStat
import re
import traceback
from apps.mtm.services import get_mgroup_goals


def translate_eval_formula(exp_str: str, year: int, month: int, day: int, hour: int):
    """
    传入
    """
    pattern = r'\${(\d+)}'
    matches = re.findall(pattern, exp_str)

    for match in matches:
        mpst = MpointStat.objects.filter(type='hour', mpoint__id=match, year=year, month=month, day=day).first()
        if mpst:
            exp_str = exp_str.replace(f"${{{match}}}", mpst.val)
    
    rval = eval(exp_str)
    return rval


# cal_rule = {
#     "电石渣": {
#         "total_production": 0.4,
#         "elec_consume_unit": 0.4,
#         "production_cost_unit": 0.2
#     },
#     "原料磨":{
#         "production_hour": 0.3,
#         "elec_consume_unit": 0.3,
#         "production_cost_unit": 0.1,
#         "辅料_细度":0.05,
#         "辅料_水分":0.04,
#         "干混生料_CaO":0.04
#     }
# }
# def cal_team_score(data):
#     """
#     计算月度绩效
#     """
#     qua_rate = {}
#     month_s = data['month_s']
#     for item in data['qua_data']:
#         qua_rate[f'{item["material_name"]}_{item["testitem_name"]}'] = item["rate_pass"]
    
#     goal_dict = get_mgroup_goals(data['mgroup'], data['year_s'], False)
#     goal_data = {}
#     try:
#         rule = cal_rule[data['mgroup_name']]
#         score = 0
#         for key in rule:
#             new_key = f'{key}_{month_s}'
#             goal_data[new_key] = goal_dict[new_key]
#             if '-' in key:
#                 score = score + qua_rate.get(key, 0)/goal_data[new_key]*rule[key]
#             else:
#                 score = score + data.get(key)/goal_data[new_key]*rule[key]
#                 print(score)
#         # enstat.goal_data = goal_data
#         # enstat.score =score
#         # enstat.save(update_fields=['goal_data', 'score'])
#     except:
#         print(traceback.format_exc())
#     return goal_data, score