To send emails from an Azure Databricks notebook, there are a few different approaches you can take:
1. Using SMTP server:
This is one of the most straightforward methods. You can use Python’s built-in `smtplib` library along with an SMTP server to send emails directly from your Databricks notebook.
Here’s a basic example:
“`python
import smtplib
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
def send_email(sender, recipient, subject, message):
# Configure SMTP server details
smtp_server = “smtp.example.com”
smtp_port = 587
smtp_username = “your_username”
smtp_password = “your_password”
# Create message
msg = MIMEMultipart()
msg[‘From’] = sender
msg[‘To’] = recipient
msg[‘Subject’] = subject
msg.attach(MIMEText(message, ‘plain’))
# Send email
with smtplib.SMTP(smtp_server, smtp_port) as server:
server.starttls()
server.login(smtp_username, smtp_password)
server.send_message(msg)
# Usage
send_email(“sender@example.com”, “recipient@example.com”, “Test Subject”, “This is a test email.”)
“`
Make sure to replace the SMTP server details with your actual server information.
2. Using Azure Logic Apps:
You can use Azure Logic Apps as an intermediary to send emails. This method involves saving your data or attachment to Azure Blob Storage, then triggering a Logic App via an HTTP request to send the email.
3. Using third-party services:
Services like SendGrid can be used to send emails. You’ll need to set up an account and use their API or SMTP server.
4. Using Databricks Notifications:
For job-related emails, you can configure Databricks to send notifications about job events (start, success, failure) to email addresses or other destinations like Slack or Microsoft Teams.
5. Using AWS SES (Amazon Simple Email Service):
If you have access to AWS services, you can use Amazon SES to send emails. However, this requires proper AWS credentials configuration.
Important considerations:
– Ensure you have the necessary permissions and credentials set up correctly.
– Store sensitive information like passwords or API keys securely, preferably using Azure Key Vault or Databricks Secrets.
– Be aware of any email sending limits or restrictions imposed by your email service provider.
– For production use, consider using more robust solutions like Azure Logic Apps or dedicated email services that can handle large volumes of emails reliably.
Remember to test your email sending functionality thoroughly before implementing it in production workflows.