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Home Backend Development Python Tutorial Build an API to Keep Your Marketing Emails Out of Spam

Build an API to Keep Your Marketing Emails Out of Spam

Dec 23, 2024 pm 10:23 PM

When running email marketing campaigns, one of the biggest challenges is ensuring that your messages reach the inbox rather than the spam folder.

Apache SpamAssassin is a widely used tool for many email clients and email filtering tools to classify messages as spam. In this post, we’ll explore how to leverage SpamAssassin to validate if your email will be marked as spam and why it's marked so.
The logic will be packaged as an API and deployed online, so that it can be integrated into your workflow.

Why Apache SpamAssassin?

Apache SpamAssassin is an open-source spam detection platform maintained by the Apache Software Foundation. It uses a multitude of rules, Bayesian filtering, and network tests to assign a spam “score” to a given email. Generally, an email scoring 5 or above is at high risk of being flagged as spam.

Since that SpamAssassin’s scoring is transparent and well-documented, you can also use it to identify exactly which aspects of your email are causing high spam scores and improve your writing.

Getting Started with SpamAssassin

SpamAssassin is designed to run on Linux systems. You'll need a Linux OS or create a Docker VM to install and run it.

On Debian or Ubuntu systems, install SpamAssassin with:

apt-get update && apt-get install -y spamassassin
sa-update

The sa-update command ensures that SpamAssassin’s rules are up-to-date.

Once installed, you can pipe an email message into SpamAssassin’s command-line tool. The output includes an annotated version of the email with spam scores and explains which rules are triggered.

A typical usage might look like this:

spamassassin -t < input_email.txt > results.txt

results.txt will then contain the processed email with SpamAssassin’s headers and scores.

Use FastAPI to Wrap SpamAssassin as an API

Next, let’s create a simple API that accepts two email fields: subject and html_body. It will pass the fields to SpamAssassin and return the validation result.

Example FastAPI Code

from fastapi import FastAPI
from datetime import datetime, timezone
from email.utils import format_datetime
from pydantic import BaseModel
import subprocess
import re

def extract_analysis_details(text):
    rules_section = re.search(r"Content analysis details:.*?(pts rule name.*?description.*?)\n\n", text, re.DOTALL)
    if not rules_section:
        return []

    rules_text = rules_section.group(1)
    pattern = r"^\s*([-\d.]+)\s+(\S+)\s+(.+)$"
    rules = []
    for line in rules_text.splitlines()[1:]:
        match = re.match(pattern, line)
        if match:
            score, rule, description = match.groups()
            rules.append({
                "rule": rule,
                "score": float(score),
                "description": description.strip()
            })
    return rules

app = FastAPI()

class Email(BaseModel):
    subject: str
    html_body: str

@app.post("/spam_check")
def spam_check(email: Email):
    # assemble the full email
    message = f"""From: example@example.com
To: recipient@example.com
Subject: {email.subject}
Date: {format_datetime(datetime.now(timezone.utc))}
Content-Type: text/html; charset="UTF-8"

{email.html_body}"""

    # Run SpamAssassin and capture the output directly
    output = subprocess.run(["spamassassin", "-t"], 
                            input=message.encode('utf-8'), 
                            capture_output=True)

    output_str = output.stdout.decode('utf-8', errors='replace')
    details = extract_analysis_details(output_str)
    return {"result": details}

The response will contain the analysis details of SpamAssassin’s results.

Let's take this input as an example:

subject:
Test Email

html_body:
<html>
  <body>
    <p>This is an <b>HTML</b> test email.</p>
  </body>
</html>

The response would be like this:

[
  {
    "rule": "MISSING_MID",
    "score": 0.1,
    "description": "Missing Message-Id: header"
  },
  {
    "rule": "NO_RECEIVED",
    "score": -0.0,
    "description": "Informational: message has no Received headers"
  },
  {
    "rule": "NO_RELAYS",
    "score": -0.0,
    "description": "Informational: message was not relayed via SMTP"
  },
  {
    "rule": "HTML_MESSAGE",
    "score": 0.0,
    "description": "BODY: HTML included in message"
  },
  {
    "rule": "MIME_HTML_ONLY",
    "score": 0.1,
    "description": "BODY: Message only has text/html MIME parts"
  },
  {
    "rule": "MIME_HEADER_CTYPE_ONLY",
    "score": 0.1,
    "description": "'Content-Type' found without required MIME headers"
  }
]

Deploying the API Online

Running SpamAssassin requires a Linux environment with the software installed. Traditionally, you might need an EC2 instance or a DigitalOcean droplet to deploy, which can be costly and tedious, especially if your usage is low-volume.

As for serverless platforms, they often do not provide a straightforward way to run system packages like SpamAssassin.

Now with Leapcell, you can deploy any system packages like SpamAssassin, meanwhile keep the service serverless - you only pay for invocations, which is usually cheaper.

Deploying the API on Leapcell is very easy. You don't have to worry about how to set up a Linux environment or how to build a Dockerfile. Just select the Python image for deploying, and fill in the "Build Command" field properly.

Build an API to Keep Your Marketing Emails Out of Spam

Once deployed, you’ll have an endpoint you can call on-demand. Whenever your API is invoked, it will run SpamAssassin, score the email, and return the response.

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