Python code to search emails in csv, xlsx and json files; split email into name and domain; and apply md5 hash to the name, name in uppercase and name in lowercase; returning them in csv format.

apply-md5.py

# Python code to search emails in csv, xlsx and json files;
# split email into name and domain;
# and apply md5 hash to the name, name in uppercase and name in lowercase; 
# returning them in csv format.

import hashlib
import re
import csv
import glob
import pandas as pd

def csv_from_excel(filename):
    # Read and store content
    # of an excel file 
    read_file = pd.read_excel(filename, engine='openpyxl')
    
    # Write the dataframe object
    # into csv file
    read_file.to_csv (filename+".csv",index = None, sep=";")
        

EMAIL = r'\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b'

def md5(text):
    return hashlib.md5(text.encode()).hexdigest()

def process(csv_lines, text):
    # All mail
    match = re.findall(EMAIL, text )
    if match:
        for m in match:
            m_split = m.split("@")
            if len(m_split)>=2:
                m_name = m_split[0]
                
                line = [m_name, md5(m_name), m]
                csv_lines.append(line)

                line = [m_name.lower(), md5(m_name.lower()), m]
                csv_lines.append(line)

                line = [m_name.upper(), md5(m_name.upper()), m]
                csv_lines.append(line)

csv_lines = []

for filename in glob.glob('./data/*.xlsx'):
    csv_from_excel(filename)

for filename in glob.glob('./data/*.json')+glob.glob('./data/*.csv'):
    print(filename)
    try:
        with open(filename, encoding = 'utf-8', mode='r') as file:
            text = file.read()
            process(csv_lines, text)
    except:
        with open(filename, mode='r') as file:
            text = file.read()
            process(csv_lines, text)

# Remove dupes
def removeDupes(csv_lines):
    csv_lines = sorted(csv_lines, key=lambda x: x[0])
    csv_dict = {}
    for line in csv_lines:
        csv_dict[line[0]] = line[1:]
    csv_lines_ = []
    for l0,l1 in csv_dict.items():
        csv_lines_.append([l0]+l1)
    csv_lines = csv_lines_
    return sorted(csv_lines, key=lambda x: x[0])

csv_lines = removeDupes(csv_lines)
print(csv_lines[:5])
print(len(csv_lines))

# open the file in the write mode
with open('output.csv', 'w', encoding='utf-8') as f:
    # create the csv writer
    writer = csv.writer(f, delimiter=';', lineterminator = '\n')
    for line in csv_lines:
        writer.writerow(line)