Extract headers from online email and create a CSV file to import all found email addresses as contacts into GMail.

extract.py

import imaplib
import email
import csv
import sys
"""
Extract headers from online email and create a CSV file
 to import all found email addresses as contacts into GMail.

(c)2022 [email protected]
based on https://qr.ae/pvQWFi

Command-line args: {HOST} {USERNAME} {PASSWORD}

"""

skipped = 0


def split_addrs(s):
    """
    split an address list into list of tuples of (name,address)
    """
    if not(s):
        return []
    outQ = True
    cut = -1
    res = []
    for i in range(len(s)):
        if s[i] == '"':
            outQ = not(outQ)
        if outQ and s[i] == ',':
            res.append(email.utils.parseaddr(s[cut+1:i]))
            cut = i
    res.append(email.utils.parseaddr(s[cut+1:i+1]))
    return res


def accumulate_goodness(biggus_dictus, list_of_name_and_address):
    """
    Biggus dictus!
    """
    global skipped
    if len(list_of_name_and_address) == 0:
        return

    if len(list_of_name_and_address) > 1:
        print(f" To/From/CC: {list_of_name_and_address}")
        print(" ^^ Multiple-address message")
        # return

    for p in list_of_name_and_address:
        email_name = p[0]
        email_addr = p[1]
        # print(f" name: '{email_name}', addr: '{email_addr}'")

        if len(email_name) == 0:
            print("   skipping empty name")
            skipped += 1
            return

        if email_name in biggus_dictus:
            addresses = biggus_dictus[email_name]
        else:
            print(f"  new name '{email_name}'")
            addresses = set()
            biggus_dictus[email_name] = addresses
        # print(f"  Prev set of addresses is {addresses}")
        addresses.add(email_addr)
        if len(addresses) == 4:
            print("  **** MAX NAMES HIT FOR {email_name}")


# begin
if len(sys.argv) != 4:
    print(f"{sys.argv[0]} HOST USERNAME PASSWORD")
    exit(1)
pAddress = sys.argv[1]
pUser = sys.argv[2]
pPassword = sys.argv[3]

mail = imaplib.IMAP4_SSL(pAddress)
mail.login(pUser, pPassword)
mail.select("INBOX")
result, data = mail.search(None, "ALL")
ids = data[0].split()
# data_as_str = bytes(data).decode("utf-8")
# ids = data_as_str[0].split()

# FOR DEBUG
print("SHORTENING DATA....")
ids = ids[0:100]

# PROBLEM: ids is a tuple of bytes, but needs to be strings! (or does it?)
# super cheesy way to fix:
ids_str = []
for id in ids:
    ids_str.append(id.decode('UTF-8'))

print(f"fetching {len(ids)} ids....")
msgs = mail.fetch(','.join(ids_str), '(BODY.PEEK[HEADER])')[1][0::2]

print(f"fetched {len(msgs)} messages; iterating....")

# intermediate result: dictionary of
#  key: Person (or company) name
#  value: set of email addresses associated with that person
#
names_and_addresses = {}

for x, msg in msgs:
    msg_str = msg.decode('UTF-8')
    # print(f"Raw message is\n----------\n{msg_str}\n----------\n")

    # was msg; TODO: could use message_from_bytes and avoid above conversion??
    msgobj = email.message_from_string(msg_str)
    # msgobj = email.message_from_bytes(msg)

    accumulate_goodness(names_and_addresses, split_addrs(msgobj['to']))
    accumulate_goodness(names_and_addresses, split_addrs(msgobj['from']))
    accumulate_goodness(names_and_addresses, split_addrs(msgobj['cc']))

print("------------------------------------------------")
print(f"Found {len(names_and_addresses)} distinct names")
print(f" skipped: {skipped}")
# print(f"{names_and_addresses}")

# Now create a list of dictionaries for the CSV DictWriter.
# Each entry in the list is a dictionary like this:
#  {"Name": "Rob Cranfill",
#   "E-mail 1 - Value": "[email protected]",
#   "E-mail 2 - Value": "[email protected]"}
#
csv_data = []
for name_key in names_and_addresses.keys():
    d = dict()
    d["Name"] = name_key
    i = 1
    # todo: check for email addresses that only differ in upper/lower case?
    # todo: if there are more than 4 addresses, will create bad CSV?
    for a in names_and_addresses[name_key]:
        e_key_name = f"E-mail {i} - Value"
        d[e_key_name] = a
        # print(f" >>> {key_name} = {a}")
        i += 1
    csv_data.append(d)

# print(f"\n\nCSV dict: {csv_data}")

# Write the CSV file!
with open('output.csv', 'w', newline='') as csvfile:
    Gfieldnames = ["Name", "Given Name", "Additional Name", "Family Name",
                   "Yomi Name", "Given Name Yomi", "Additional Name Yomi",
                   "Family Name Yomi", "Name Prefix", "Name Suffix",
                   "Initials", "Nickname", "Short Name", "Maiden Name",
                   "Birthday", "Gender", "Location", "Billing Information",
                   "Directory Server", "Mileage", "Occupation", "Hobby",
                   "Sensitivity", "Priority", "Subject", "Notes",
                   "Language", "Photo", "Group Membership",
                   "E-mail 1 - Type", "E-mail 1 - Value",
                   "E-mail 2 - Type", "E-mail 2 - Value",
                   "E-mail 3 - Type", "E-mail 3 - Value",
                   "E-mail 4 - Type", "E-mail 4 - Value",
                   "Phone 1 - Type", "Phone 1 - Value",
                   "Phone 2 - Type", "Phone 2 - Value",
                   "Phone 3 - Type", "Phone 3 - Value",
                   "Phone 4 - Type", "Phone 4 - Value",
                   "Address 1 - Type", "Address 1 - Formatted",
                   "Address 1 - Street", "Address 1 - City",
                   "Address 1 - PO Box", "Address 1 - Region",
                   "Address 1 - Postal Code", "Address 1 - Country",
                   "Address 1 - Extended Address",
                   "Address 2 - Type", "Address 2 - Formatted",
                   "Address 2 - Street", "Address 2 - City",
                   "Address 2 - PO Box", "Address 2 - Region",
                   "Address 2 - Postal Code", "Address 2 - Country",
                   "Address 2 - Extended Address", "Organization 1 - Type",
                   "Organization 1 - Name", "Organization 1 - Yomi Name",
                   "Organization 1 - Title", "Organization 1 - Department",
                   "Organization 1 - Symbol", "Organization 1 - Location",
                   "Organization 1 - Job Description", "Website 1 - Type",
                   "Website 1 - Value"]

    writer = csv.DictWriter(csvfile, fieldnames=Gfieldnames)
    for d in csv_data:
        writer.writerow(d)