energy-data-trans/tmp_file/光伏箱体.py

# -*- coding: utf-8 -*-
"""
Created on Tue Jul  9 16:28:48 2024

@author: Administrator
"""

import os
from datetime import datetime, timedelta
import pandas as pd
import chardet
from multiprocessing import Pool


# 获取文件编码
def detect_file_encoding(filename):
    # 读取文件的前1000个字节（足够用于大多数编码检测）
    with open(filename, 'rb') as f:
        rawdata = f.read(1000)
    result = chardet.detect(rawdata)
    encoding = result['encoding']

    if encoding is None:
        encoding = 'gb18030'

    if encoding and encoding.lower() == 'gb2312' or encoding.lower().startswith("windows"):
        encoding = 'gb18030'
    return encoding


# 读取数据到df
def read_file_to_df(file_path, read_cols=list(), header=0):
    df = pd.DataFrame()
    if str(file_path).lower().endswith("csv") or str(file_path).lower().endswith("gz"):
        encoding = detect_file_encoding(file_path)
        end_with_gz = str(file_path).lower().endswith("gz")
        if read_cols:
            if end_with_gz:
                df = pd.read_csv(file_path, encoding=encoding, usecols=read_cols, compression='gzip', header=header)
            else:
                df = pd.read_csv(file_path, encoding=encoding, usecols=read_cols, header=header, on_bad_lines='warn')
        else:

            if end_with_gz:
                df = pd.read_csv(file_path, encoding=encoding, compression='gzip', header=header)
            else:
                df = pd.read_csv(file_path, encoding=encoding, header=header, on_bad_lines='warn')

    else:
        xls = pd.ExcelFile(file_path)
        # 获取所有的sheet名称
        sheet_names = xls.sheet_names
        for sheet in sheet_names:
            if read_cols:
                df = pd.concat([df, pd.read_excel(xls, sheet_name=sheet, header=header, usecols=read_cols)])
            else:
                df = pd.concat([df, pd.read_excel(xls, sheet_name=sheet, header=header)])

    return df


def __build_directory_dict(directory_dict, path, filter_types=None):
    # 遍历目录下的所有项
    for item in os.listdir(path):
        item_path = os.path.join(path, item)
        if os.path.isdir(item_path):
            __build_directory_dict(directory_dict, item_path, filter_types=filter_types)
        elif os.path.isfile(item_path):
            if path not in directory_dict:
                directory_dict[path] = []

            if filter_types is None or len(filter_types) == 0:
                directory_dict[path].append(item_path)
            elif str(item_path).split(".")[-1] in filter_types:
                if str(item_path).count("~$") == 0:
                    directory_dict[path].append(item_path)

    # 读取所有文件


# 读取路径下所有的excel文件
def read_excel_files(read_path):
    directory_dict = {}
    __build_directory_dict(directory_dict, read_path, filter_types=['xls', 'xlsx', 'csv', 'gz'])

    return [path for paths in directory_dict.values() for path in paths if path]


# 创建路径
def create_file_path(path, is_file_path=False):
    if is_file_path:
        path = os.path.dirname(path)

    if not os.path.exists(path):
        os.makedirs(path, exist_ok=True)


def read_and_save_csv(file_path):
    begin = datetime.now()
    base_name = os.path.basename(file_path)
    print('开始', base_name)

    df1 = read_file_to_df(file_path + "箱变（1-8号逆变器）数据1.xls")
    del df1['Unnamed: 0']
    df1['时间'] = pd.to_datetime(df1['时间'])
    df1.set_index(keys='时间', inplace=True)

    df2 = read_file_to_df(file_path + "箱变（9-16号逆变器）数据1.xls")
    del df2['Unnamed: 0']
    df2['时间'] = pd.to_datetime(df2['时间'])
    df2.set_index(keys='时间', inplace=True)

    df3 = read_file_to_df(file_path + "箱变（1-8号逆变器）数据2.xls")
    del df3['Unnamed: 0']
    df3['时间'] = pd.to_datetime(df3['时间'])
    df3.set_index(keys='时间', inplace=True)

    df4 = read_file_to_df(file_path + "箱变（9-16号逆变器）数据2.xls")
    del df4['Unnamed: 0']
    df4['时间'] = pd.to_datetime(df4['时间'])
    df4.set_index(keys='时间', inplace=True)

    df = pd.concat([df1, df2, df3, df4], axis=1)
    df.reset_index(inplace=True)
    columns = list(df.columns)
    columns.sort()

    print(df.columns)

    df = df[columns]
    df.sort_values(by='时间', inplace=True)

    df.to_csv(os.path.join(r'D:\trans_data\大唐玉湖性能分析离线分析', '05整理数据', base_name + '_箱变.csv'), encoding='utf-8',
              index=False)
    print('结束', base_name, '耗时:' + str(datetime.now() - begin))


if __name__ == '__main__':

    path = r'D:\trans_data\大唐玉湖性能分析离线分析\test'
    all_files = read_excel_files(path)

    all_paths = set()
    for file in all_files:
        base_name = os.path.basename(file).split("箱变")[0]
        base_path = os.path.dirname(file)
        if base_name not in all_paths:
            all_paths.add(os.path.join(base_path, base_name))

    all_datas = list(all_paths)
    all_datas.sort()

    print(all_datas)
    # with Pool(1) as pool:
    #     pool.starmap(read_and_save_csv, [(i,) for i in all_datas])