import hashlib
from google.ads.googleads.client import GoogleAdsClient
from google.ads.googleads.errors import GoogleAdsException

def create_customer_match_user_list(client, customer_id):
    """Creates a Customer Match user list.

    Args:
        client: The Google Ads client.
        customer_id: The ID for the customer that owns the user list.

    Returns:
        The string resource name of the newly created user list.
    """
    # Creates the UserListService client.
    user_list_service_client = client.get_service("UserListService")

    # Creates the user list operation.
    user_list_operation = client.get_type("UserListOperation")

    # Creates the new user list.
    user_list = user_list_operation.create
    user_list.name = f"Customer Match list #{uuid.uuid4()}"
    user_list.description = (
        "A list of customers that originated from email and physical addresses"
    )
    # Sets the upload key type to indicate the type of identifier that is used
    # to add users to the list. This field is immutable and required for a
    # CREATE operation.
    user_list.crm_based_user_list.upload_key_type = (
        client.enums.CustomerMatchUploadKeyTypeEnum.CONTACT_INFO
    )
    # Customer Match user lists can set an unlimited membership life span;
    # to do so, use the special life span value 10000. Otherwise, membership
    # life span must be between 0 and 540 days inclusive. See:
    # https://developers.devsite.corp.google.com/google-ads/api/reference/rpc/latest/UserList#membership_life_span
    # Sets the membership life span to 30 days.
    user_list.membership_life_span = 30

    response = user_list_service_client.mutate_user_lists(
        customer_id=customer_id, operations=[user_list_operation]
    )
    user_list_resource_name = response.results[0].resource_name
    print(
        f"User list with resource name '{user_list_resource_name}' was created."
    )

    return user_list_resource_name

def normalize_and_hash(s, remove_all_whitespace):
    """Normalizes and hashes a string with SHA-256.

    Args:
        s: The string to perform this operation on.
        remove_all_whitespace: If true, removes leading, trailing, and
            intermediate spaces from the string before hashing. If false, only
            removes leading and trailing spaces from the string before hashing.

    Returns:
        A normalized (lowercase, remove whitespace) and SHA-256 hashed string.
    """
    # Normalizes by first converting all characters to lowercase, then trimming
    # spaces.
    if remove_all_whitespace:
        # Removes leading, trailing, and intermediate whitespace.
        s = "".join(s.split())
    else:
        # Removes only leading and trailing spaces.
        s = s.strip().lower()

    # Hashes the normalized string using the hashing algorithm.
    return hashlib.sha256(s.encode()).hexdigest()

def build_offline_user_data_job_operations(client, emailList):
  operations = []
  for email in emailList:
        # Creates a UserData object that represents a member of the user list.
        user_data = client.get_type("UserData")
        user_identifier = client.get_type("UserIdentifier")
        user_identifier.hashed_email = normalize_and_hash(
            record["email"], True
        )
        # Adds the hashed email identifier to the UserData object's list.
        user_data.user_identifiers.append(user_identifier)

   # If the user_identifiers repeated field is not empty, create a new
   # OfflineUserDataJobOperation and add the UserData to it.
        if user_data.user_identifiers:
            operation = client.get_type("OfflineUserDataJobOperation")
            operation.create = user_data
            operations.append(operation)

return operations;

def add_users_to_customer_match_user_list(
    client,
    customer_id,
    user_list_resource_name,
    run_job,
    offline_user_data_job_id,
    ad_user_data_consent,
    ad_personalization_consent,
    emailList
):
    """Uses Customer Match to create and add users to a new user list.

    Args:
        client: The Google Ads client.
        customer_id: The ID for the customer that owns the user list.
        user_list_resource_name: The resource name of the user list to which to
            add users.
        run_job: If true, runs the OfflineUserDataJob after adding operations.
            Otherwise, only adds operations to the job.
        offline_user_data_job_id: ID of an existing OfflineUserDataJob in the
            PENDING state. If None, a new job is created.
        ad_user_data_consent: The consent status for ad user data for all
            members in the job.
        ad_personalization_consent: The personalization consent status for ad
            user data for all members in the job.
    """
    # Creates the OfflineUserDataJobService client.
    offline_user_data_job_service_client = client.get_service(
        "OfflineUserDataJobService"
    )

    if offline_user_data_job_id:
        # Reuses the specified offline user data job.
        offline_user_data_job_resource_name = (
            offline_user_data_job_service_client.offline_user_data_job_path(
                customer_id, offline_user_data_job_id
            )
        )
    else:
        # Creates a new offline user data job.
        offline_user_data_job = client.get_type("OfflineUserDataJob")
        offline_user_data_job.type_ = (
            client.enums.OfflineUserDataJobTypeEnum.CUSTOMER_MATCH_USER_LIST
        )
        offline_user_data_job.customer_match_user_list_metadata.user_list = (
            user_list_resource_name
        )

        # Specifies whether user consent was obtained for the data you are
        # uploading. For more details, see:
        # https://www.google.com/about/company/user-consent-policy
        if ad_user_data_consent:
            offline_user_data_job.customer_match_user_list_metadata.consent.ad_user_data = client.enums.ConsentStatusEnum[
                ad_user_data_consent
            ]
        if ad_personalization_consent:
            offline_user_data_job.customer_match_user_list_metadata.consent.ad_personalization = client.enums.ConsentStatusEnum[
                ad_personalization_consent
            ]

        # Issues a request to create an offline user data job.
        create_offline_user_data_job_response = (
            offline_user_data_job_service_client.create_offline_user_data_job(
                customer_id=customer_id, job=offline_user_data_job
            )
        )
        offline_user_data_job_resource_name = (
            create_offline_user_data_job_response.resource_name
        )
        print(
            "Created an offline user data job with resource name: "
            f"'{offline_user_data_job_resource_name}'."
        )

    # Issues a request to add the operations to the offline user data job.

    # Best Practice: This example only adds a few operations, so it only sends
    # one AddOfflineUserDataJobOperations request. If your application is adding
    # a large number of operations, split the operations into batches and send
    # multiple AddOfflineUserDataJobOperations requests for the SAME job. See
    # https://developers.google.com/google-ads/api/docs/remarketing/audience-types/customer-match#customer_match_considerations
    # and https://developers.google.com/google-ads/api/docs/best-practices/quotas#user_data
    # for more information on the per-request limits.
    request = client.get_type("AddOfflineUserDataJobOperationsRequest")
    request.resource_name = offline_user_data_job_resource_name
    request.operations = build_offline_user_data_job_operations(client, emailList)
    request.enable_partial_failure = True

    # Issues a request to add the operations to the offline user data job.
    response = offline_user_data_job_service_client.add_offline_user_data_job_operations(
        request=request
    )

    # Prints the status message if any partial failure error is returned.
    # Note: the details of each partial failure error are not printed here.
    # Refer to the error_handling/handle_partial_failure.py example to learn
    # more.
    # Extracts the partial failure from the response status.
    partial_failure = getattr(response, "partial_failure_error", None)
    if getattr(partial_failure, "code", None) != 0:
        error_details = getattr(partial_failure, "details", [])
        for error_detail in error_details:
            failure_message = client.get_type("GoogleAdsFailure")
            # Retrieve the class definition of the GoogleAdsFailure instance
            # in order to use the "deserialize" class method to parse the
            # error_detail string into a protobuf message object.
            failure_object = type(failure_message).deserialize(
                error_detail.value
            )

            for error in failure_object.errors:
                print(
                    "A partial failure at index "
                    f"{error.location.field_path_elements[0].index} occurred.\n"
                    f"Error message: {error.message}\n"
                    f"Error code: {error.error_code}"
                )

    print("The operations are added to the offline user data job.")

    if not run_job:
        print(
            "Not running offline user data job "
            f"'{offline_user_data_job_resource_name}', as requested."
        )
        return

    # Issues a request to run the offline user data job for executing all
    # added operations.
    offline_user_data_job_service_client.run_offline_user_data_job(
        resource_name=offline_user_data_job_resource_name
    )

# GoogleAdsClient will read the google-ads.yaml configuration file in the
# home directory if none is specified.
googleads_client = GoogleAdsClient.load_from_storage(version="v16")

if __name__ == "__main__":
  try:
        main(
            googleads_client,
            customer_id,
            run_job,
            user_list_id,
            offline_user_data_job_id,
            ad_user_data_consent,
            ad_personalization_consent,
            emailList
        )
    except GoogleAdsException as ex:
        print(
            f"Request with ID '{ex.request_id}' failed with status "
            f"'{ex.error.code().name}' and includes the following errors:"
        )
        for error in ex.failure.errors:
            print(f"\tError with message '{error.message}'.")
            if error.location:
                for field_path_element in error.location.field_path_elements:
                    print(f"\t\tOn field: {field_path_element.field_name}")
        sys.exit(1)

def main(
    client,
    customer_id,
    run_job,
    user_list_id,
    offline_user_data_job_id,
    ad_user_data_consent,
    ad_personalization_consent,
    emailList
):
    """Uses Customer Match to create and add users to a new user list.

    Args:
        client: The Google Ads client.
        customer_id: The ID for the customer that owns the user list.
        run_job: if True, runs the OfflineUserDataJob after adding operations.
            Otherwise, only adds operations to the job.
        user_list_id: ID of an existing user list. If None, a new user list is
            created.
        offline_user_data_job_id: ID of an existing OfflineUserDataJob in the
            PENDING state. If None, a new job is created.
        ad_user_data_consent: The consent status for ad user data for all
            members in the job.
        ad_personalization_consent: The personalization consent status for ad
            user data for all members in the job.
    """
    googleads_service = client.get_service("GoogleAdsService")

    if not offline_user_data_job_id:
        if user_list_id:
            # Uses the specified Customer Match user list.
            user_list_resource_name = googleads_service.user_list_path(
                customer_id, user_list_id
            )
        else:
            # Creates a Customer Match user list.
            user_list_resource_name = create_customer_match_user_list(
                client, customer_id
            )

    add_users_to_customer_match_user_list(
        client,
        customer_id,
        user_list_resource_name,
        run_job,
        offline_user_data_job_id,
        ad_user_data_consent,
        ad_personalization_consent,
        emailList
    )