我正在使用CSV文件来读取我在文本文件中查找的术语。
我想使用通配符或“类似”作为术语。我不是在文本文档名称中查找通配符，而是在CSV文件中查找要搜索的术语。
例如：要在文本文件中搜索的CSV文件中的术语，每个术语都在其自己的行中。
test* #搜索测试、测试、测试等项目
列表
工作台
一种椅子
CSV文件中是否可以使用通配符，以便返回该单词的所有变体？我想将通配符放在CSV文件中。
下面是我的代码，它读取我搜索的术语的文件是contract_search_terms.csv

def main():
    txt_filepaths = glob.glob("**/*.txt", recursive=True)
    start = time.time()
    results = {}
    new_results = [] #place dictionary values organized per key = value instead of key = tuple of values 
    term_filename = open('contract_search_terms.csv', 'r') #file where terms to be searched is found
    term_file = csv.DictReader(term_filename)
    search_terms =[] #append terms into a list, this means that we can use several columns and append them all to one list.
    
    #############search for the terms imported into the list############################################################
    for col in term_file:
                
        search_terms.append(col['Contract Terms']) #indicate what columns you want read in

    print(search_terms) #this is just a check to show what terms are in the list
    
    for filepath in txt_filepaths:
        print(f"Searching document {filepath}")   #print what file the code is reading
        
        search_terms = search_terms #place terms list into search_terms so that the code below can read it when looping through the contracts.
                    
        filename = os.path.basename(filepath)
        found_terms = {} #dictionary of the terms found
        
        line_number={}
        
        
        for term in search_terms:
            if term in found_terms.keys():
                continue
                
            with open(filepath, "r", encoding="utf-8") as fp:
                lines = str(fp.readlines()).split('.') #turns contract file lines as a list
                
                for line in lines:
                    if line.find(term) != -1: #line by line is '-1', paragraph '\n'
                        line_number = lines.index(line)
                        new_results.append(f"'{term}' New_Column '{filename}' New_Column '{line}' New_Column '{line_number}'") #placing the results from the print statement below into a list
                        print(f"Found '{term}' in document '{filename}' in line '{line_number}'") 

                    if term in results.keys():
                        pages = results[''.join(term)].append([filename,line,line_number])

                    else:
                        results[term] = [filename]

                #Place results into dataframe and create a csv file to use as a check if results_reports is not correct
                d2=pd.DataFrame(new_results, columns=['Results']) #passing the list to a dataframe and giving it a column title
                d2.to_csv('results.csv', index=True)