SEO Python, explained to beginners

SEO is full of repetitive manual work. Python can help you automate repetitive tasks, extract insights from large data sets such as thousands of keywords or URLs, and build technical skills to help you solve almost any SEO problem: debug JavaScript problems, parse complex sitemaps, or use APIs.

Besides that, learning Python can help you:

You don’t need to be an expert or install complex local settings. You only need a browser, some curiosity and willingness to ruin things.

Before writing any Python code, you need a place to do it – that’s what we call “environment”. Think of it as a workspace where you can type, test, and run scripts.

Choosing the right environment is important because it can affect your ease of getting started and whether you have technical issues that slow down your learning.

Here are three great options depending on your preferences and experience level:

You don’t need to master Python to start using it for SEO, but you should understand some basic concepts. These are the basis for almost every Python script you want to write.

These are the bread and fuel skills you use in almost every SEO script. They are not individually complex, but when combined, they allow you to review websites, scrape data, build reports, and automate repetitive work.

These projects are simple, practical, and can be built with less than 20 lines of code.

One of the easiest but most useful checks you can use Python automation is to verify that a set of URLs is using HTTPS. If you are reviewing a customer’s website or reviewing competitor URLs, you can help know which pages are still using unsafe HTTP.

This script reads a list of URLs from a CSV file, reads an HTTP request to each script, and prints a status code. A status code of 200 means that the page is accessible. It will also tell you if the request fails (for example, the site is closed or the protocol is incorrect).

import csv
import requests

with open('urls.csv', 'r') as file:
    reader = csv.reader(file)
    for row in reader:
        url = row(0)
        try:
            r = requests.get(url)
            print(f"{url}: {r.status_code}")
        except:
            print(f"{url}: Failed to connect")

Lack of ALT text is a common page problem, especially on older pages or larger sites. Instead of manually checking each page, you can use python to scan any page and tag images with ALT attributes. This script gets the page html and identifies allLabel and print out any image with SRC missing descriptive alt text.

import requests
from bs4 import BeautifulSoup

url="https://example.com"
r = requests.get(url)
soup = BeautifulSoup(r.text, 'html.parser')

images = soup.find_all('img')
for img in images:
    if not img.get('alt'):
        print(img.get('src'))

Using this script, you can enter a list of URLs to extract the page’s