Python tin consciousness intimidating if you’re not a developer. You spot scripts flying astir Twitter, perceive radical talking astir automation and APIs, and wonderment if it’s worthy learning—or adjacent possible—without a machine subject degree.

But here’s the truth: SEO is filled with repetitive, time-consuming tasks that Python tin automate successful minutes. Things similar checking for breached links, scraping metadata, analyzing rankings, and auditing on-page SEO are each doable with a fewer lines of code. And acknowledgment to tools similar ChatGPT and Google Colab, it’s ne'er been easier to get started.

In this guide, I’ll amusement you however to commencement learning.

SEO is afloat of repetitive, manual work. Python helps you automate repetitive tasks, extract insights from monolithic datasets (like tens of thousands of keywords oregon URLs), and physique method skills that assistance you tackle beauteous overmuch immoderate SEO problem: debugging JavaScript issues, parsing analyzable sitemaps, oregon using APIs.

Beyond that, learning Python helps you:

• Understand however websites and web information enactment (believe it oregon not, the net is not tubes).
• Collaborate with developers much efficaciously (how other are you readying to make thousands of location-specific pages for that programmatic SEO campaign?)
• Learn programming logic that translates to different languages and tools, similar gathering Google Apps Scripts to automate reporting successful Google Sheets, oregon penning Liquid templates for dynamic leafage instauration successful headless CMSs.

And successful 2025, you’re not learning Python alone. LLMs tin explicate mistake messages. Google Colab lets you tally notebooks without setup. It’s ne'er been easier.

You don’t request to beryllium an adept oregon instal a analyzable section setup. You conscionable request a browser, immoderate curiosity, and a willingness to interruption things.

I urge starting with a hands-on, beginner-friendly course. I used Replit’s 100 Days of Python and highly urge it.

Here’s what you’ll request to understand:

1. Tools to constitute and tally Python

Before you tin constitute immoderate Python code, you request a spot to bash it — that’s what we telephone an “environment.” Think of it similar a workspace wherever you tin type, test, and tally your scripts.

Choosing the close situation is important due to the fact that it affects however easy you tin get started and whether you tally into method issues that dilatory down your learning.

Here are 3 large options depending connected your preferences and acquisition level:

• Replit: A browser-based IDE (Integrated Development Environment), which means it gives you a spot to write, run, and debug your Python codification — each from your web browser. You don’t request to instal thing — conscionable motion up, unfastened a caller project, and commencement coding. It adjacent includes AI features to assistance you constitute and debug Python scripts successful existent time. Visit Replit.
• Google Colab: A escaped instrumentality from Google that lets you tally Python notebooks successful the cloud. It’s large for SEO tasks involving information analysis, scraping, oregon instrumentality learning. You tin besides stock notebooks similar Google Docs, which is cleanable for collaboration. Visit Google Colab.
• VS Code + Python interpreter: If you similar to enactment locally oregon privation much power implicit your setup, instal Visual Studio Code and the Python extension. This gives you afloat flexibility, entree to your record system, and enactment for precocious workflows similar Git versioning oregon utilizing virtual environments. Visit the VS Code website.

You don’t request to commencement here—but long-term, getting comfy with section improvement volition springiness you much powerfulness and flexibility arsenic your projects turn much complex.

If you’re unsure wherever to start, spell with Replit oregon Colab. They destruct setup friction truthful you tin absorption connected learning and experimenting with SEO scripts right away.

2. Key concepts to learn early

You don’t request to maestro Python to commencement utilizing it for SEO, but you should recognize a fewer foundational concepts. These are the gathering blocks of astir each Python publication you’ll write.

• Variables, loops, and functions: Variables store information similar a database of URLs. Loops fto you repetition an enactment (like checking HTTP presumption codes for each page). Functions fto you bundle actions into reusable blocks. These 3 ideas volition powerfulness 90% of your automation. You tin larn much astir these concepts done beginner tutorials like Python for Beginners – Learn Python Programming or W3Schools Python Tutorial.
• Lists, dictionaries, and conditionals: Lists assistance you enactment with collections (like each your site’s pages). Dictionaries store information successful pairs (like URL + title). Conditionals (like if, else) assistance you determine what to bash depending connected what the publication finds. These are particularly utile for branching logic oregon filtering results. You tin research these topics further with the W3Schools Python Data Structures guide and LearnPython.org’s power travel tutorial.
• Importing and utilizing libraries: Python has thousands of libraries: pre-written packages that bash dense lifting for you. For example, requests lets you nonstop HTTP requests, beautifulsoup4 parses HTML, and pandas handles spreadsheets and information analysis. You’ll usage these successful astir each SEO task. Check out The Python Requests Module by Real Python, Beautiful Soup: Web Scraping with Python for parsing HTML, and Python Pandas Tutorial from DataCamp for moving with information successful SEO audits.

These concepts whitethorn dependable abstract now, but they travel to beingness erstwhile you commencement utilizing them. And the bully news? Most SEO scripts reuse the aforesaid patterns again and again. Learn these fundamentals erstwhile and you tin use them everywhere.

3. Core SEO-related Python skills

These are the bread-and-butter skills you’ll usage successful astir each SEO script. They’re not analyzable individually, but erstwhile combined, they fto you audit sites, scrape data, physique reports, and automate repetitive work.

• Making HTTP requests: This is however Python loads a webpage down the scenes. Using the requests library, you tin cheque a page’s presumption codification (like 200 oregon 404), fetch HTML content, oregon simulate a crawl. Learn much from Real Python’s usher to the Requests module.
• Parsing HTML: After fetching a page, you’ll often privation to extract circumstantial elements, similar the rubric tag, meta description, oregon each representation alt attributes. That’s wherever beautifulsoup4 comes in. It helps you navigate and hunt HTML similar a pro. This Real Python tutorial explains precisely however it works.
• Reading and penning CSVs: SEO information lives successful spreadsheets: rankings, URLs, metadata, etc. Python tin work and constitute CSVs utilizing the built-in csv module oregon the much almighty pandas library. Learn however with this pandas tutorial from DataCamp.
• Using APIs: Many SEO tools (like Ahrefs, Google Search Console, oregon Screaming Frog) connection APIs — interfaces that fto you fetch information successful structured formats similar JSON. With Python’s requests and json libraries, you tin propulsion that information into your ain reports oregon dashboards. Here’s a basal overview of APIs with Python.

Once you cognize these 4 skills, you tin physique tools that crawl, extract, clean, and analyse SEO data. Pretty cool.

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

1. Check if pages are using HTTPS

One of the simplest yet astir utile checks you tin automate with Python is verifying whether a acceptable of URLs is utilizing HTTPS. If you’re auditing a client’s tract oregon reviewing rival URLs, it helps to cognize which pages are inactive utilizing insecure HTTP.

This publication reads a database of URLs from a CSV file, makes an HTTP petition to each one, and prints the presumption code. A presumption codification of 200 means the leafage is accessible. If the petition fails (e.g., the tract is down oregon the protocol is wrong), it volition archer you that too.

import csv import requests with open('urls.csv', 'r') arsenic file: scholar = csv.reader(file) for enactment successful reader: url = row[0] try: r = requests.get(url) print(f"{url}: {r.status_code}") except: print(f"{url}: Failed to connect")

2. Check for missing representation alt attributes

Missing alt substance is simply a communal on-page issue, particularly connected older pages oregon ample sites. Rather than checking each leafage manually, you tin usage Python to scan immoderate leafage and emblem images missing an alt attribute. This publication fetches the leafage HTML, identifies each <img> tags, and prints retired the src of immoderate representation 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 successful images: if not img.get('alt'): print(img.get('src'))

3. Scrape rubric and meta statement tags

With this script, you tin input a database of URLs, extract each page’s <title> and <meta name=“description”> content, and prevention the results to a CSV file. This makes it casual to spot missing, duplicated, oregon poorly written metadata astatine standard — and instrumentality enactment fast.

import requests from bs4 import BeautifulSoup import csv urls = ['https://example.com', 'https://example.com/about'] with open('meta_data.csv', 'w', newline='') arsenic f: writer = csv.writer(f) writer.writerow(['URL', 'Title', 'Meta Description']) for url successful urls: r = requests.get(url) crockery = BeautifulSoup(r.text, 'html.parser') rubric = soup.title.string if soup.title other 'No title' desc_tag = soup.find('meta', attrs={'name': 'description'}) desc = desc_tag['content'] if desc_tag other 'No description' writer.writerow([url, title, desc])

4. Using Python with the Ahrefs API

If you’re an Ahrefs lawsuit with API access, you tin usage Python to pat straight into our data, fetching backlinks, keywords, rankings, and more. This opens the doorway to large-scale SEO workflows: auditing thousands of pages, analyzing rival nexus profiles, oregon automating contented reporting.

For example, you could:

• Monitor caller backlinks to your tract regular and log them to a Google Sheet
• Automatically propulsion your apical integrated pages each period for contented reporting
• Track keyword rankings crossed aggregate sites and spot trends faster than utilizing the UI alone

Here’s a elemental illustration to fetch backlink data:

import requests url = "https://apiv2.ahrefs.com?from=backlinks&amp;target=ahrefs.com&amp;mode=domain&amp;output=json&amp;token=YOUR_API_TOKEN" r = requests.get(url) data = r.json() print(data)

You’ll request an Ahrefs API subscription and entree token to tally these scripts. Full documentation and endpoint details are disposable successful the Ahrefs API docs.

Patrick Stox, aka Mr Technical SEO, is ever tinkering with Python, and he’s made tons of escaped tools and scripts freely disposable successful Google Colab. Here are a fewer of my idiosyncratic favorites:

• Redirect matching script: This publication automates 1:1 redirect mapping by matching aged and caller URLs via full-text similarity. Upload your before-and-after URLs, tally the notebook, and fto it suggest redirects for you. It’s incredibly adjuvant during migrations. Run the publication here.
  
• Page rubric similarity report: Google often rewrites leafage titles successful hunt results. This instrumentality compares your submitted titles (via Ahrefs data) with what Google really displays, utilizing a BERT exemplary to measurement semantic similarity. Ideal for large-scale rubric audits. Run the publication here.
  
• Traffic forecasting script: Featured successful our SEO Forecasting guide, this publication uses humanities postulation information to foretell aboriginal performance. Great for mounting expectations with clients oregon making the lawsuit for continued investment. Run the publication here.

Learn much astir this forecasting publication successful Patrick’s usher to SEO forecasting.

Final thoughts

Python is 1 of the astir impactful skills you tin larn arsenic an SEO. Even a fewer basal scripts tin prevention hours of enactment and uncover insights you’d miss otherwise.

Start small. Run your archetypal script. Fork 1 of Patrick’s tools. Or walk 30 minutes with Replit’s Python course. It won’t instrumentality agelong earlier you’re thinking: wherefore didn’t I bash this sooner?

Got questions? Ping maine connected Twitter.