You can use the csv module to read a .dat file and write it as a .csv file using these steps:

Here is an example, I hope you can modify the code as you see it fit:

import csv

with open('my_file.dat', 'r') as dat_file:

with open('my_file.csv', 'w', newline='') as csv_file:

csv_writer = csv.writer(csv_file)

for row in dat_file:

row = [value.strip() for value in row.split('|')]

csv_writer.writerow(row)

From here on you will definitely not done yet, I advise you to run EDAs on the dataset first to familiarized yourself with it before undergoing data cleaning/wrangling.

Hope this link will be helpful: https://wfdb.readthedocs.io/en/latest/

You can check with https://stats4edu.com/services/writing-new-and-efficient-r-code-pyhton-code-sas-code-and-stata-code/