Hi Google Ads Team,
Thanks for posting this tutorial
<https://developers.google.com/google-ads/api/docs/remarketing/audience-types/customer-match>
and I tried to follow every step to add users to customer match user List.
My problem came with the huge volume of customers. I have around 1M+ users
want to upload to that user List and here's my code to build the operation
list.
10k users adding to the operation list takes around 7mins and it seems too
slow. Any code improvement and opinion will be appreciated!
def _build_offline_user_data_job_operations(df):
size = df.shape[0]
operations_list = []
for i in range(0, size-1, 50000):
operations = []
df_copy = df.iloc[i:min(size, i+50000)]
for row in df_copy.itertuples():
operations.append(_build_single_offline_user_data_job_operation(row[1],
row[2], row[3], row[4], row[5], row[6]))
operations_list.append(operations)
return operations_list
def _build_single_offline_user_data_job_operation( email, first_name,
last_name, postal_code, country_code, phone_number):
user_data_operation = client.get_type("OfflineUserDataJobOperation")
user_data = user_data_operation.create
user_identifier = client.get_type('UserIdentifier')
user_identifier.hashed_email = _normalize_and_hash(email)
user_identifier.hashed_phone_number = _normalize_and_hash(phone_number)
address_info = client.get_type('OfflineUserAddressInfo')
address_info.hashed_first_name = _normalize_and_hash(first_name)
address_info.hashed_last_name = _normalize_and_hash(last_name)
address_info.country_code = country_code
address_info.postal_code = postal_code
user_identifier.address_info = address_info
user_data.user_identifiers.append(user_identifier)
return user_data
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