energy-data-trans/etl/base/WindFarms.py

# -*- coding: utf-8 -*-
# @Time    : 2024/5/15
# @Author  : 魏志亮
import datetime
import multiprocessing

from etl.base.PathsAndTable import PathsAndTable
from etl.base.TransParam import TransParam
from etl.step.ClearData import ClearData
from etl.step.ReadAndSaveTmp import ReadAndSaveTmp
from etl.step.SaveToDb import SaveToDb
from etl.step.StatisticsAndSaveFile import StatisticsAndSaveFile
from etl.step.UnzipAndRemove import UnzipAndRemove
from service.plt_service import get_all_wind, update_trans_status_running, \
    update_trans_status_success, update_trans_transfer_progress
from service.trans_service import batch_statistics
from utils.df_utils.util import get_time_space
from utils.file.trans_methods import *


class WindFarms(object):

    def __init__(self, batch_no=None, batch_name=None, field_code=None, field_name=None, params: TransParam = None,
                 save_db=True, header=0, trans_param: TransParam = None):
        self.batch_no = batch_no
        self.batch_name = batch_name
        self.field_code = field_code
        self.field_name = field_name
        self.save_zip = False
        self.trans_param = params
        self.wind_col_trans, self.rated_power_and_cutout_speed_map = get_all_wind(self.field_code)
        self.batch_count = 50000
        self.save_path = None
        self.save_db = save_db
        self.statistics_map = multiprocessing.Manager().dict()
        self.header = header
        self.trans_param = trans_param
        self.trans_param.wind_col_trans = self.wind_col_trans
        self.pathsAndTable = PathsAndTable(batch_no, batch_name, self.trans_param.read_path, self.field_name,
                                           self.trans_param.read_type, save_db, save_zip=self.save_zip)

    def run(self, step=0, end=4):
        begin = datetime.datetime.now()
        trans_print("开始执行")
        update_trans_status_running(self.batch_no, self.trans_param.read_type, self.save_db)
        if step <= 0 and end >= 0:
            clean_data = ClearData(self.pathsAndTable)
            clean_data.run()

        if step <= 1 and end >= 1:
            # 更新运行状态到运行中
            unzip_and_remove = UnzipAndRemove(self.pathsAndTable)
            unzip_and_remove.run()

        if step <= 2 and end >= 2:
            read_and_save_tmp = ReadAndSaveTmp(self.pathsAndTable, self.trans_param)
            read_and_save_tmp.run()

        if step <= 3 and end >= 3:
            # 保存到正式文件
            statistics_and_save_file = StatisticsAndSaveFile(self.pathsAndTable, self.trans_param, self.statistics_map,
                                                             self.rated_power_and_cutout_speed_map)
            statistics_and_save_file.run()

        if step <= 4 and end >= 4:
            if self.save_db:
                save_to_db = SaveToDb(self.pathsAndTable)
                save_to_db.run()

        update_trans_transfer_progress(self.batch_no, self.trans_param.read_type, 99, self.save_db)
        # 如果end==0 则说明只是进行了验证
        if end >= 4:
            all_files = read_excel_files(self.pathsAndTable.get_save_path())
            if step <= 3:
                update_trans_status_success(self.batch_no, self.trans_param.read_type,
                                            len(all_files),
                                            self.statistics_map['time_granularity'],
                                            self.statistics_map['min_date'], self.statistics_map['max_date'],
                                            self.statistics_map['total_count'], self.save_db)
            else:
                df = read_file_to_df(all_files[0], read_cols=['time_stamp'])
                df['time_stamp'] = pd.to_datetime(df['time_stamp'])
                time_granularity = get_time_space(df, 'time_stamp')
                batch_data = batch_statistics("_".join([self.batch_no, self.trans_param.read_type]))
                if batch_data is not None:
                    update_trans_status_success(self.batch_no, self.trans_param.read_type,
                                                len(read_excel_files(self.pathsAndTable.get_save_path())),
                                                time_granularity,
                                                batch_data['min_date'], batch_data['max_date'],
                                                batch_data['total_count'], self.save_db)
                else:
                    update_trans_status_success(self.batch_no, self.trans_param.read_type,
                                                len(read_excel_files(self.pathsAndTable.get_save_path())),
                                                time_granularity,
                                                None, None,
                                                None, self.save_db)
        trans_print("结束执行", self.trans_param.read_type, ",总耗时:",
                    str(datetime.datetime.now() - begin))