import os
from datetime import datetime
from pathlib import Path
from pprint import pprint

import pandas as pd

from .config_reader import ConfigReader
from ..DHU.config_reader import ConfigReader as ConfigReader_DHU
from ..._data.main import get_data

NOW             = datetime.now().replace(second=0,microsecond=0)
PATH            = os.path.dirname(os.path.realpath(__file__)).replace('\\','/')
MODEL_FUNC_PATH = f'{PATH}/model_func.py'
MODEL_FILE_PATH = f'./model.pkl'

def train(*inputs,config=None):
    config = {} if config is None else config
    
    if '__LOCAL' in config.keys():
        config_reader_path = config['__LOCAL']
        data_URL           = config['__URL']
        plot_metric        = True
    else:
        config_reader_path = '/mnt/workflow_data'
        data_URL           = 'http://basedataportal-svc:8080/data/getpointsdata'
        plot_metric        = False
    
    config_reader = ConfigReader(
        path          = f'{config_reader_path}/Room.xlsx',
        DHU_AB_config = ConfigReader_DHU(path=f'{config_reader_path}/DHU_AB.xlsx')
    )
    
    # 历史数据
    data_raw_folder = os.path.join(config_reader_path,f'data/train/data_his_raw/')
    if not os.path.exists(data_raw_folder): 
        os.makedirs(data_raw_folder)
    for each_room_dew in config_reader.all_room_dew:
        all_data = []
        data_his_folder = os.path.join(config_reader_path,f'data/train/data_his/{each_room_dew}')
        if not os.path.exists(data_his_folder): 
            os.makedirs(data_his_folder)
        
        points = config_reader.get_point(each_room_dew)
        for each_point_name,each_point_id in points.items():
            file_path = os.path.join(data_his_folder,f'{each_point_name}.pkl')
            get_data(
                points_id  = [each_point_id],
                time_start = config_reader.get_app_info(each_room_dew,'模型训练','开始时间','datetime'),
                time_end   = config_reader.get_app_info(each_room_dew,'模型训练','结束时间','datetime'),
                int_time   = 'M',
                url        = data_URL,
                from_cache = True,
                PATH       = Path(file_path),
            )
            all_data.append(pd.read_pickle(file_path).set_axis([each_point_name],axis=1))
        
        all_data = pd.concat(all_data,axis=1).to_pickle(f'{data_raw_folder}/{each_room_dew}.pkl')