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- import multiprocessing
- from utils.file.trans_methods import *
- def boolean_is_check_data(df_vas):
- # fault_list = ['Checked', 'Indeterminate', 'Unchecked']
- # for fault in fault_list:
- # if fault in df_vas:
- # return True
- return False
- def compareTwoFolders(df1s, df2s):
- for is_falut in [False]:
- list1 = list()
- for df in df1s:
- tmp_list = [str(i).split('_')[-1] for i in list(df.columns) if i != 'sheet_name']
- if is_falut:
- if boolean_is_check_data(df.values):
- list1.extend(tmp_list)
- else:
- if not boolean_is_check_data(df.values):
- list1.extend(tmp_list)
- list2 = list()
- for df in df2s:
- tmp_list = [str(i).split('_')[-1] for i in list(df.columns) if i != 'sheet_name']
- if is_falut:
- if boolean_is_check_data(df.values):
- list2.extend(tmp_list)
- else:
- if not boolean_is_check_data(df.values):
- list2.extend(tmp_list)
- set1 = set(list1)
- set2 = set(list2)
- list1 = list(set1)
- list2 = list(set2)
- list1.sort()
- list2.sort()
- print(list1)
- print(list2)
- list3 = list(set1 - set2)
- list3.sort()
- list4 = list(set2 - set1)
- list4.sort()
- print(list3)
- print(list4)
- list5 = list(set1)
- list5.extend(list(set2))
- list5 = list(set(list5))
- list5.sort()
- max_count = len(list5)
- list1.extend([''] * (max_count - len(list1)))
- list2.extend([''] * (max_count - len(list2)))
- list3.extend([''] * (max_count - len(list3)))
- list4.extend([''] * (max_count - len(list4)))
- file_name = 'col_compare.csv' if not is_falut else 'col_compare_falut.csv'
- with open(file_name, 'w', encoding='utf8') as f:
- f.write(",".join(["全部字段", "对方提供(3-25风机)", "自己获取(1-2风机)", "对方提供多的字段", "自己提供多的字段"]))
- f.write('\n')
- for e, a, b, c, d in zip(list5, list1, list2, list3, list4):
- f.write(",".join([e, a, b, c, d]))
- f.write('\n')
- f.flush()
- if __name__ == '__main__':
- begin = datetime.datetime.now()
- dir1 = r'D:\data\新华水电\风机SCADA数据\9月风机数据_对方复制'
- dir2 = r'D:\data\新华水电\风机SCADA数据\自己复制'
- files1 = read_excel_files(dir1)
- files2 = read_excel_files(dir2)
- with multiprocessing.Pool(10) as pool:
- df1s = pool.starmap(read_file_to_df, [(file, list(), None, 1) for file in files1])
- with multiprocessing.Pool(10) as pool:
- df2s = pool.starmap(read_file_to_df, [(file, list(), None, 1) for file in files2])
- compareTwoFolders(df1s, df2s)
- print(datetime.datetime.now() - begin)
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