"""
读取104规约返回的数据,并标准化到临时表中
"""
import multiprocessing
import os.path
import time
import traceback
import warnings
from datetime import datetime

import pandas as pd

from service import plt_service, trans_service
from utils.conf.read_conf import yaml_conf, read_conf
from utils.log.trans_log import logger

warnings.filterwarnings('ignore')


def generate_mesurepoint_maps(file_path):
    df = pd.read_excel(file_path)

    wind_maps = dict()
    for _, data in df.iterrows():
        shunxuhao = int(data['顺序号']) + 1
        changzhan = data['场站标准化编号']
        wind_no = data['风机号']
        en_name = data['标准化英文']
        if changzhan in wind_maps.keys():
            if wind_no in wind_maps[changzhan].keys():
                wind_maps[changzhan][wind_no][shunxuhao] = en_name
            else:
                wind_maps[changzhan][wind_no] = {shunxuhao: en_name}
        else:
            wind_maps[changzhan] = {wind_no: {shunxuhao: en_name}}

    return wind_maps


def generate_scada_data(df, mesurepoint_maps, changzhan, wind_code_name_map):
    second_dfs = list()
    minute_dfs = list()
    wind_maps, _ = plt_service.get_wind_info(changzhan, False)

    for wind_no in mesurepoint_maps[changzhan].keys():
        shunxuhao_map = mesurepoint_maps[changzhan][wind_no]
        second_df = df[list(shunxuhao_map.keys())]
        second_df['wind_turbine_name'] = wind_no
        second_df['time_stamp'] = df[0]
        second_df['time_stamp'] = pd.to_datetime(second_df['time_stamp'])
        second_df.rename(columns=shunxuhao_map, inplace=True)
        second_dfs.append(second_df)
        minute_df = second_df.copy(deep=True)
        minute_df['time_stamp'] = minute_df['time_stamp'].min().strftime('%Y-%m-%d %H:%M:00')
        minute_df = minute_df.groupby(['wind_turbine_name', 'time_stamp']).mean(numeric_only=True).reset_index()
        minute_dfs.append(minute_df)

    changzhan_second_df = pd.concat(second_dfs, ignore_index=True)
    changzhan_minute_df = pd.concat(minute_dfs, ignore_index=True)

    changzhan_second_df['wind_turbine_name'] = changzhan_second_df['wind_turbine_name'].astype(str)
    changzhan_second_df['wind_turbine_number'] = changzhan_second_df['wind_turbine_name'].map(wind_maps)

    changzhan_minute_df['wind_turbine_name'] = changzhan_minute_df['wind_turbine_name'].astype(str)
    changzhan_minute_df['wind_turbine_number'] = changzhan_minute_df['wind_turbine_name'].map(wind_maps)

    # changzhan_second_df.to_csv(f'tmp/104/scada/{changzhan}-{int(time.time())}_second.csv', index=False)
    # changzhan_minute_df.to_csv(f'tmp/104/scada/{changzhan}-{int(time.time())}_minute.csv', index=False)

    date_str = datetime.now().strftime('%Y_%m_%d')
    second_table_name = f'{changzhan}_second_{date_str}_tmp'
    trans_service.save_df_to_db(second_table_name, changzhan_second_df)

    minute_table_name = f'{changzhan}_minute_{date_str}_tmp'
    trans_service.save_df_to_db(minute_table_name, changzhan_minute_df)
    changzhan_minute_df['time_stamp'] = pd.to_datetime(changzhan_minute_df['time_stamp'], errors='coerce')
    minute_max_date = changzhan_minute_df['time_stamp'].max()
    second_max_date = changzhan_second_df['time_stamp'].max()
    add_date_str = minute_max_date.strftime('%Y-%m-%d')

    minunte_last_date_str = minute_max_date
    second_last_date_str = second_max_date.strftime('%Y-%m-%d %H:%M:%S')

    # wind_farm_code, wind_farm_name, add_date, trans_type, count, latest_data_time
    trans_service.update_wind_farm_day_count(changzhan, wind_code_name_map.get(changzhan, ''), add_date_str,
                                             'minute', changzhan_minute_df.shape[0], minunte_last_date_str)

    trans_service.update_wind_farm_day_count(changzhan, wind_code_name_map.get(changzhan, ''), add_date_str,
                                             'second', changzhan_second_df.shape[0], second_last_date_str)


def add_table(changzhan_names):
    types = ['minute', 'second']

    for changzhan_name in changzhan_names:
        for type in types:
            table_name = f'{changzhan_name}_{type}_{date_str}_tmp'

            if not trans_service.boolean_table_exists(table_name):
                trans_service.create_tmp_table(table_name)


if __name__ == '__main__':
    time.sleep(60)
    total_begin = time.time()
    begin = time.time()

    date_str = datetime.now().strftime('%Y_%m_%d')

    wind_code_name_map = plt_service.get_all_wind_by_company_code('COM00002')

    conf_path = os.path.abspath(f"./conf/config.yaml")
    yaml_config = yaml_conf(conf_path)
    data_base_dir = read_conf(yaml_config, 'data_base_dir')
    read_dirs = [os.path.join(data_base_dir, '2404'), os.path.join(data_base_dir, '2405')]

    for read_dir in read_dirs:
        dir_time = time.time()
        for root, dirs, files in os.walk(read_dir):
            for file in files:
                try:
                    file_dir = os.path.basename(root)

                    read_csv = root + os.sep + file
                    df = pd.read_csv(read_csv, header=None)
                    mesurepoint_maps = generate_mesurepoint_maps(f'conf/测点表-{file_dir}.xlsx')
                    add_table(mesurepoint_maps.keys())

                    with multiprocessing.Pool(5) as pool:
                        pool.starmap(generate_scada_data,
                                     [(df, mesurepoint_maps, changzhan, wind_code_name_map) for changzhan in
                                      mesurepoint_maps.keys()])

                    os.remove(read_csv)
                except:
                    logger.error(traceback.format_exc())
                logger.info(f'SCADA执行完:{file_dir}/{file}耗时:{time.time() - dir_time}')
        logger.info(f'{read_dir}执行总耗时:{time.time() - dir_time}')
    logger.info(f'SCADA执行总耗时:{time.time() - total_begin}')