python 正则表达式：从.txt 文件中逐行捕获不同的字符串

Question

I need to extract names/strings from a.txt file line by line. I am trying to use regex to do this.

Eg. In this below line I want to extract the name "Victor Lau", "Siti Zuan" and the string "TELEGRAPHIC TRANSFER" in three different lists then output them into an excel file. You may see the txt file also

TELEGRAPHIC TRANSFER 0008563668 040122 BRH BDVI0093 VICTOR LAU 10,126.75-.00 10,126.75- SITI ZUZAN 16:15:09

I have tried this code

for file in os.listdir(directory):
     filename = os.fsdecode(file)
     if (filename.endswith(".txt") or filename.endswith(".TXT")) and (filename.find('AllBanks')!=-1):
        with open(file) as AllBanks:
            for line in AllBanks:
                try:
                    match4 = re.search(r'( [a-zA-Z]+ [a-zA-Z]+ [a-zA-Z]+ )|( [a-zA-Z]+ [a-zA-Z]+)', line)                    
                    List4.append(match4.group(0).strip())                     
                except:
                    List4.append('NA')
df = pd.DataFrame(np.column_stack([List4,List5,List6]),columns=['a', 'b', 'c'])
df.to_excel('AllBanks.xlsx', index=False)

Answer 1

Your text file looks to be fixed width columns - no delimiters. You can use re capture groups like '^(.{20})(.{15})(.{30})'

or you can specify the columns start position and width and use that to splice out the data from each row.

This method will parse 2 columns from each line of your file and return an array of rows, each with an array of columns.

def parse(filename):
    fixed_columns = [[0, 28], [71, 50]] # start pos and width pairs of columns you want
    rows = []
    with open(filename) as file:
        for line in file:
            cols = []
            for start,wid in fixed_columns:
                cols.append(line[start: start+wid].strip())
            rows.append(cols)
    return rows

for row in parse(filename):
    print(", ".join(row))

Output:

TELEGRAPHIC TRANSFER, LIEW WAI KEEN
TELEGRAPHIC TRANSFER, KWAN SANG@KWAN CHEE SANG
TELEGRAPHIC TRANSFER, VICTOR LAU
TELEGRAPHIC TRANSFER, VICTOR LAU

From here you can save the data any way you like.