I'm trying to decrypt my encrypted data stored in a text file from my DropBox bucket. When I create a pandas dataframe of the txt data and match it up with my user input, I exclusively pick the row that matches. Using this data I run it through my decryption (AES_CBC).

When I run I get the error: "TypeError: can only concatenate str (not "bytes") to str"

The error appears from my padding function (p4 = padded_text(df1))

I'm not sure if this is an encoding issue, or if the fact I'm using .get() as my user input and because that's a string it isn't working. Any help would be greatly appreciated.

def login():
import sqlite3
import os.path

def decoder():
    from Crypto.Cipher import AES
    import hashlib
    from secrets import token_bytes

    cursor.execute(
        '''
        Select enc_key FROM Login where ID = (?);
        ''',
        (L_ID_entry.get(), ))

    row = cursor.fetchone()
    if row is not None:
        keys = row[0]

        import pyDes
        #design padding function for encryption
        def padded_text(data_in):
            while len(data_in)% 16 != 0:
                data_in = data_in + b"0"
            return data_in

        #calling stored key from main file and reverting back to bytes
        key_original = bytes.fromhex(keys)
        mode = AES.MODE_CBC

        #model
        cipher = AES.new(key_original, mode, IV3)

        #padding data
        p4 = padded_text(df1)
        p5 = padded_text(df2)
        p6 = padded_text(df3)

        #decrypting data
        d_fname = cipher.decrypt(p4)
        d_sname = cipher.decrypt(p5)
        d_email = cipher.decrypt(p6)

#connecting to db
try:
    conn = sqlite3.connect('login_details.db')
    cursor = conn.cursor()
    print("Connected to SQLite")

except sqlite3.Error as error:
    print("Failure, error: ", error)
finally:
    #downloading txt from dropbox and converting to dataframe to operate on
    import New_user
    _, res = client.files_download("/user_details/enc_logins.txt")
    with io.BytesIO(res.content) as csvfile:
            df = pd.read_csv(csvfile, sep=';',  names=['ID', 'Fname', 'Sname', 'Email'])
            newdf = df.loc[df['ID'] == L_ID_entry.get()]
            print(newdf)
            df1 = newdf['Fname']
            df2 = newdf['Sname']
            df3 = newdf['Email']
            csvfile.close()

    decoder()