And in 2025, you’re not learning Python alone. LLMs can explain error messages. Google Colab lets you run notebooks without setup. It’s never been easier.

LLMs can tackle most error messages with ease—no matter how dumb they may be.

You don’t need to be an expert or install a complex local setup. You just need a browser, some curiosity, and a willingness to break things.

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

Choosing the right environment is important because it affects how easily you can get started and whether you run into 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 a few foundational concepts. These are the building blocks of nearly every Python script you’ll write.

These are the bread-and-butter skills you’ll use in nearly every SEO script. They’re not complex individually, but when combined, they let you audit sites, scrape data, build reports, and automate repetitive work.

One of the simplest yet most useful checks you can automate with Python is verifying whether a set of URLs is using HTTPS. If you’re auditing a client’s site or reviewing competitor URLs, it helps to know which pages are still using insecure HTTP.

This script reads a list of URLs from a CSV file, makes an HTTP request to each one, and prints the status code. A status code of 200 means the page is accessible. If the request fails (e.g., the site is down or the protocol is wrong), it will tell you that too.

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")

Missing alt text is a common on-page issue, especially on older pages or large sites. Rather than checking every page manually, you can use Python to scan any page and flag images missing an alt attribute. This script fetches the page HTML, identifies all tags, and prints out the src of any image 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'))

With this script, you can input a list of URLs, extract each page’s