Open DevCEDTeam opened 1 month ago
To develop a robust email management system that integrates bulk email sending, AI-generated content, tracking, bounce handling, and unsubscribe management, I will break down the task using the Gilbert technique. Each stage will be actionable, and examples will guide you through setting up this system using open-source tools, Google Cloud, Python, Cloudflare, and Terraform.
Purpose: Ensure your environment has the necessary tools to handle Gmail authentication (OAuth 2.0), Vertex AI for content generation, and MongoDB for logging.
pip install google-auth google-auth-oauthlib google-auth-httplib2 google-cloud-aiplatform pymongo
Purpose: Securely send emails on behalf of your Gmail account using OAuth 2.0.
client_secret.json
file for OAuth 2.0 credentials.from google_auth_oauthlib.flow import InstalledAppFlow
import pickle
import os
SCOPES = ['https://www.googleapis.com/auth/gmail.send']
def generate_gmail_token():
creds = None
if os.path.exists('token.json'):
with open('token.json', 'rb') as token:
creds = pickle.load(token)
else:
flow = InstalledAppFlow.from_client_secrets_file('client_secret.json', SCOPES)
creds = flow.run_local_server(port=0)
with open('token.json', 'wb') as token:
pickle.dump(creds, token)
return creds
Purpose: Dynamically generate personalized email content using Google's Vertex AI.
your-service-account.json
).from google.cloud import aiplatform
from google.oauth2 import service_account
def generate_ai_content(prompt):
credentials = service_account.Credentials.from_service_account_file('your-service-account.json')
aiplatform.init(project="your-gcp-project-id", location="us-central1", credentials=credentials)
chat_model = aiplatform.models.ChatModel(model_name="gemini-chat-model")
response = chat_model.predict(prompt)
return response['text']
Purpose: Automate bulk email sending with AI-generated content, including tracking pixels and unsubscribe links.
from google.oauth2.credentials import Credentials
from googleapiclient.discovery import build
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
import base64
def send_email_with_oauth2(to_email, content):
creds = Credentials.from_authorized_user_file('token.json', SCOPES)
service = build('gmail', 'v1', credentials=creds)
msg = MIMEMultipart("alternative")
msg["From"] = "your-email@gmail.com"
msg["To"] = to_email
msg["Subject"] = "Your AI-Enhanced Email"
html_body = f"""
<html>
<body>
<p>{content}</p>
<p>If you no longer wish to receive emails, <a href="https://yourserver.com/unsubscribe?email={to_email}">unsubscribe here</a>.</p>
<img src="https://yourserver.com/tracking_pixel?email={to_email}" width="1" height="1"/>
</body>
</html>
"""
msg.attach(MIMEText(html_body, "html"))
encoded_message = base64.urlsafe_b64encode(msg.as_bytes()).decode()
message = {'raw': encoded_message}
service.users().messages().send(userId="me", body=message).execute()
Purpose: Track email opens by embedding a tracking pixel and log the open events in MongoDB.
from pymongo import MongoClient
from flask import Flask, request
app = Flask(__name__)
client = MongoClient("your_mongo_uri")
db = client['email_campaign']
collection_opens = db['email_opens']
@app.route("/tracking_pixel", methods=["GET"])
def track_open():
email = request.args.get("email")
user_agent = request.headers.get('User-Agent')
timestamp = datetime.datetime.utcnow()
collection_opens.insert_one({"email": email, "user_agent": user_agent, "timestamp": timestamp})
return "", 200, {'Content-Type': 'image/gif'}
Purpose: Allow recipients to unsubscribe from your emails and log this event in MongoDB.
@app.route("/unsubscribe", methods=["GET"])
def unsubscribe():
email = request.args.get("email")
timestamp = datetime.datetime.utcnow()
collection_unsubscribes.insert_one({"email": email, "timestamp": timestamp, "status": "unsubscribed"})
return "You have successfully unsubscribed."
Purpose: Track hard and soft bounces and remove invalid emails or retry soft bounces.
@app.route("/bounce", methods=["POST"])
def bounce_handler():
bounce_data = request.json
email = bounce_data.get('email')
bounce_type = bounce_data.get('type')
if bounce_type == "hard":
# Log hard bounce and remove email
elif bounce_type == "soft":
# Log soft bounce and schedule retry
Purpose: Retry sending emails for soft bounces up to a defined number of attempts.
import time
def send_email_with_retry(to_email, content, retries=3):
attempt = 0
while attempt < retries:
try:
send_email_with_oauth2(to_email, content)
break
except Exception:
attempt += 1
time.sleep(10) # Retry after 10 seconds
Purpose: Measure the performance of your email campaigns by tracking metrics such as open rate, bounce rate, and unsubscribe rate.
def log_campaign_performance(metrics):
db.collection('campaign_performance').insert_one(metrics)
Purpose: Set up Google Cloud infrastructure (e.g., VPC, Cloud Functions) using Terraform.
main.tf
):provider "google" {
credentials = file("path/to/your-service-account.json")
project = "your-gcp-project-id"
region = "us-central1"
}
# Create a VPC for email processing
resource "google_compute_network" "vpc_network" {
name = "vpc-email-processing"
}
# Cloud Function for email processing (Bounce, Open Tracking, Unsubscribe)
resource "google_cloudfunctions_function" "email_function" {
name = "emailFunction"
runtime = "python39"
entry_point = "process_email"
available_memory_mb = 256
trigger_http = true
}
terraform init
terraform apply
Purpose: Manage DNS records and set up Cloudflare Workers to route inbound emails.
Add MX Records in Cloudflare:
route1.mx.cloudflare.net
(Priority: 2)
route2.mx.cloudflare.net
(Priority: 81)route3.mx.cloudflare.net
(Priority: 91)Set Up Cloudflare Worker to handle inbound emails:
addEventListener('fetch', event => {
event.respondWith(handleRequest(event.request))
})
async function handleRequest(request) {
const fetchResponse = await fetch('https://your-cloud-function-url', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: await request.text()
})
return new Response(fetchResponse.body)
}
This guide walks you through creating a robust email management system using Google Cloud, Vertex AI, MongoDB, Cloudflare, and Terraform. The system can handle bulk email sending, AI-generated content, tracking pixels, bounce management, and unsubscribe handling. Each step is practical and actionable, ensuring a seamless deployment of your email infrastructure.
To optimize the Step-by-Step Gilbert Instructions for the Email Management System and incorporate the Outbound Email Routing via Mailhop server (a970359.mx.mailhop.org), let's revise the instructions, ensuring that we cover the outbound routing through Mailhop after email processing.
Example main.tf
configuration for setting up the environment:
provider "google" {
credentials = file("path/to/your-service-account.json")
project = "gmail-bulk-sending"
region = "us-central1"
}
# Create the network for email processing
resource "google_compute_network" "vpc_network" {
name = "vpc-email-processing"
}
# Create Google Cloud Function
resource "google_cloudfunctions_function" "email_function" {
name = "processEmailFunction"
runtime = "python39"
entry_point = "process_email"
trigger_http = true
source_archive_bucket = google_storage_bucket.email_function_bucket.name
source_archive_object = "email_function.zip"
}
# Storage bucket for Cloud Function
resource "google_storage_bucket" "email_function_bucket" {
name = "email-function-bucket-${var.project_id}"
location = var.region
force_destroy = true
}
a970359.mx.mailhop.org
Configure the following MX records to route inbound emails:
a970359.mx.mailhop.org
a84996.mx.mailhop.org
addEventListener('fetch', event => {
event.respondWith(handleRequest(event.request))
})
async function handleRequest(request) {
const emailRecipient = request.headers.get('To')
const response = await fetch('https://REGION-gmail-bulk-sending.cloudfunctions.net/processEmailFunction', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({ email_content: await request.text() })
})
return new Response(response.body, {
status: response.status,
headers: response.headers
})
}
Deploy the worker script via the Cloudflare dashboard or Terraform.
895054114655-75saopm0mheadp8hdm3nqnbsi4c7so7k.apps.googleusercontent.com
AIzaSyCx2S2YKYBiAKcUwEYJqeK9yfL7PPpxHq4
import imaplib
import email
from pymongo import MongoClient
client = MongoClient("mongodb://localhost:27017/")
db = client.email_db
imap_server = "imap.gmail.com"
user = "you@gmail.com"
password = "yourpassword"
mail = imaplib.IMAP4_SSL(imap_server)
mail.login(user, password)
mail.select("inbox")
status, messages = mail.search(None, '(FROM "mailer-daemon")')
mail_ids = messages[0].split()
for mail_id in mail_ids:
status, msg_data = mail.fetch(mail_id, "(RFC822)")
for response_part in msg_data:
if isinstance(response_part, tuple):
msg = email.message_from_bytes(response_part[1])
subject = msg["subject"]
body = msg.get_payload(decode=True)
db.bounced_emails.insert_one({"subject": subject, "body": body})
mail.logout()
This script checks for bounced emails and stores them in Firestore/MongoDB.
import smtplib
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
def send_email_with_tracking(to_email):
msg = MIMEMultipart("alternative")
msg["From"] = "you@gmail.com"
msg["To"] = to_email
msg["Subject"] = "Your Subject"
html = """<html><body>
<p>Hello,</p>
<p>We have a tracking pixel in this email.</p>
<img src="https://yourserver.com/pixel.png?email={}"/>
</body></html>""".format(to_email)
msg.attach(MIMEText(html, "html"))
server = smtplib.SMTP("smtp.gmail.com", 587)
server.starttls()
server.login("you@gmail.com", "yourpassword")
server.sendmail("you@gmail.com", to_email, msg.as_string())
server.quit()
send_email_with_tracking("recipient@example.com")
from flask import Flask, request
app = Flask(__name__)
@app.route("/pixel.png", methods=["GET"])
def track_open():
email = request.args.get("email")
print(f"Email opened by: {email}")
return "", 200
if __name__ == "__main__":
app.run(debug=True)
def send_email_with_unsubscribe(to_email):
msg = MIMEMultipart("alternative")
msg["From"] = "you@gmail.com"
msg["To"] = to_email
msg["Subject"] = "Unsubscribe from our mailing list"
html = """<html><body>
<p>If you wish to unsubscribe, click <a href="https://yourserver.com/unsubscribe?email={}">here</a>.</p>
</body></html>""".format(to_email)
msg.attach(MIMEText(html, "html"))
server = smtplib.SMTP("smtp.gmail.com", 587)
server.starttls()
server.login("you@gmail.com", "yourpassword")
server.sendmail("you@gmail.com", to_email, msg.as_string())
server.quit()
send_email_with_unsubscribe("recipient@example.com")
@app.route("/unsubscribe", methods=["GET"])
def unsubscribe():
email = request.args.get("email")
print(f"Unsubscribed: {email}")
return "You have been unsubscribed."
After processing the email (bounce tracking, open pixel, and unsubscribe handling), the final step is to route the processed email via the Mailhop server:
Outbound Mail Routing to a970359.mx.mailhop.org
:
a970359.mx.mailhop.org
).Send Emails via OAuth 2.0 and Route:
# Final step after processing (via OAuth)
server.sendmail("you@gmail.com", to_email, msg.as_string()) # Routes via Mailhop
Store email-related data (bounces, opens, unsubscribes) in Firestore or MongoDB for analytics and tracking.
Example for storing bounce data:
db.bounced_emails.insert_one({"subject": subject, "body": body})
With this optimized structure, the email management system covers inbound email routing, processing, and outbound delivery through the Mailhop server. Let me know if you need further refinement!