在 .xslm 文件中从 Python 写入 Excel 数据验证

Question

我有一个 Excel 文件，该文件必须位于启用宏的工作簿 (.xlsm) 中，该工作簿具有名为

names_to_match

的命名范围。不同函数的输出将获取这些公司名称，将它们与数据库进行匹配，并返回前 5 个匹配项以及每个匹配项的匹配分数、匹配名称和匹配索引。

目标将是按 .xlsm 文件中的名称进行搜索，如果最高匹配分数为 100（假设名称为 A 列）。 B 列将是最高的匹配名称，C 列将是匹配分数 100。

棘手的部分是，如果匹配分数小于 100，则 b 列应该是所有匹配名称的数据验证列表，加上一个名为“创建新条目”的条目。

我遇到的问题是，在努力使用

openpyxl

让它工作几天后，我终于能够使用

xlsxwriter

让它在我的示例文件中工作。但是，当我尝试在实际文件上使用它时，它不起作用，因为 xlsxwriter 不支持 .xlsm 扩展名。

这是我在

openpyxl

中尝试过的代码。可以在

openpyxl

中做到这一点吗？如果没有，.xlsm 文件扩展名是否还有其他解决方法？

from sqlupdate import data_frame_from_xlsx_range
import pandas as pd
from openpyxl import Workbook

def read_data():
    # Read in the data from the two Excel files
    df_names = data_frame_from_xlsx_range('excel_write_test.xlsm', 'names_to_match')
    df_db_pull = pd.read_excel('test_with_db_pull.xlsx')
    return df_names, df_db_pull


def process_row(row, df_db_pull):
    # Find the corresponding name in the test_with_db_pull dataframe
    match_row = df_db_pull.loc[df_db_pull['original_name'] == row['Tracker_Name'], :]

    # Check if the score is 100
    if match_row['score_0'].values[0] == 100:
        # Set the value in column B to the match index
        row['Possible Matches'] = [match_row['match_name_0'].values[0]]
        # Set the value in column C to the score
        row['Match Score'] = match_row['score_0'].values[0]

    else:
        # Get the unique values in the match name columns
        match_names = set(
            match_row[['match_name_0', 'match_name_1', 'match_name_2',
 'match_name_3', 'match_name_4']].values.ravel())
            # Remove any NaN values
            match_names.discard(float('nan'))
            match_names = {x for x in match_names if pd.notnull(x)}
            match_names = list(match_names) + ['Create New Database Entry']
    
            # Set the value in column B to a list of the match names
            row['Possible Matches'] = match_names
            # Set the value in column C to the highest score
            row['Match Score'] = match_row[['score_0', 'score_1', 'score_2', 'score_3', 'score_4']].max().values[0]
    
        return row
    
    
    def create_dropdowns(df):
        # Get the workbook and the worksheet
        workbook = Workbook()
        worksheet = workbook.active
    
        # Write the dataframe to the worksheet
        df.to_excel(worksheet, index=False)
    
        # Loop over the dataframe's 'Possible Matches' column and create a data validation for each row
        for idx, item in enumerate(df['Possible Matches'], start=2):
            # Prepare a list of options
            options = item
    
            # Create a data validation object with the list of options
            dv = {'validate': 'list',
                  'source': options}
    
            # Add data validation to the corresponding cell in the worksheet
            worksheet.cell(row=idx, column=1).data_validation = dv
    
        # Save the workbook
        workbook.save_as('excel_write_test.xlsm')
    
    
    def main():
        df_names, df_db_pull = read_data()
    
        # Process each row
        df_names['Possible Matches'] = None
        df_names['Match Score'] = None
        df_names = df_names.apply(process_row, df_db_pull=df_db_pull, axis=1)

    # Create the dropdowns in the Excel file
    create_dropdowns(df_names)


if __name__ == '__main__':
    main()