Python is one of the most popular open-source programming languages today. In the SEO community, Python is considered the way to automate repetitive tasks, raise the level of technical SEO campaigns and save a lot of time without compromising quality.
In this post, we’ll explore how Python can help you in your technical SEO efforts.
- How to get started with Python
- Some insights on Python’s learning curve
- An overview of what Python libraries are
- Tips for automating tasks with Python
- Some basic SEO audit Python scripts
- How to optimize Images with Python
- How to use Machine Learning for SEO
- How to use the Python API for Natural Language Processing
Ready? Let’s get started.
First Things First: How Difficult Is Python?
If you are a newcomer to the world of SEO, let us tell you something: you’ll be surprised by how easy it is to learn Python. One of the things that makes it so accessible is its object-oriented approach:
The Python language is interpreted line by line. In order to understand the entire function or script you’re looking at, you must understand each line individually.
Since it is a language like any other, you will need to learn its grammar and vocabulary. Python syntax is relatively easy to understand. You can also rely on external libraries and modules so you don’t have to program your scripts’ capabilities from scratch.
Moreover, Python is scalable and can suit both an individual developer and a niche giant: Google’s first web crawler was written with Python.
How to Run Python
You can execute Python scripts from the terminal’s Integrated Development Environment (IDE) or from a cloud service such as Google Colab.
If you’re getting started, cloud services are a good option for you: you will be able to test the code online and you will not have to worry about version updates, as the platform will stay updated.
It’s worth noting that, if your computer runs Windows, you most likely don’t have Python installed. So, you’ll have to download the language from its official website.
Pro tip: If you’re unsure about whether your computer has Python installed, enter your terminal and type py or Python. If you’ve got Python installed, you’ll see your version’s details. Otherwise, an error message will appear.
If you’re a macOS user, you’ve got Python pre-installed in your system. So, if you type py or Python on your terminal, you’re likely to see a warning message letting you know that you’re running an old version of the language. To use the latest one, you should download it from Python’s website.
A Look at Python Libraries
Python libraries are basically add-ons for the programming language. They allow you to add additional functions without having to program them. What types of functions are we talking about?
- Data analysis
- Data extraction
- Machine learning
- Language processing
- Scientific computing
There are several popular libraries to choose from, such as:
- Pandas, a library for data analysis
- NumPy, a library for scientific computing
- Python Requests, which is useful for making HTTP requests
Using Python to Automate Tedious SEO Tasks
Python’s greatest power is the automation of repetitive and time-consuming tasks. You may not be able to build a beautiful landing page with Python, but it can save you hours of tedious optimization work.
At this point, you’re probably wondering what tasks you can automate with Python, right? Well, you could automate some SEO tasks such as:
- Image optimization
- Keyword research
- Link analysis
- Sitemap creation
- Content migration
- User intention analysis
For example, you could write scripts that employ deep learning to write an image’s caption or alt text when given its URL. Thus, filling any gaps in your metadata.
Another widely used function in Python is data analysis. Keep this in mind when working with:
- Website analysis data
- E-commerce transaction data
- Detailed keyword reports
Python’s open-source approach allows you to avoid spending time on low-level analysis and apply your expertise where it’s most needed.
SEO Audit & Optimization Scripts in Python
Some scripts can crawl your website and offer SEO recommendations based on a list of common problems.
You can start by crawling your website’s homepage. You can also provide the script with a sitemap in XML format. The script displays a set of data for each page, including:
- Meta tags
- Word count
This can help you to easily detect missing meta tags and thin content, at scale. Basics like these are an excellent first step to improving on-page SEO, but identifying missing elements and generating content to fill tags can also be done automatically with Python.
Here are two useful everyday scripts:
Make a Web Bot
With this script, you can automate websites. In fact, any website can be managed by a web bot.
Here’s a simple example from Python in Plain English:
- Installs Selenium
- Imports a system library allowing you to work with time
- Instructs the bot to open Google Chrome
- Instructs the bot to go on Google.com
- Searches for “@codedev101”
- Waits for 5 seconds
- Quits Google Chrome
Extract OCR Text from Photos
Optical character recognition (OCR) is a technique that recognizes text from digital and scanned documents. Though fallible, OCR is a good first step for transcribing long documents.
You can extract OCR text from pictures with the pytesseract library.
Simply open your terminal and run the following script:
- Installs pytesseract
- Imports pytesseract into your project
- Opens an image
- Detects the image’s text
- Prints the text into your terminal
Optimize your Images in Python
Reducing the size of image files increases your pages’ loading speed, which in turn is good news for your search rankings. Python can also help here!
Use a Python script to compress the images on your site individually or as a whole. Even if the compression percentage is slight, the impact can be significant when multiplied by the number of images.
These image compression Python libraries are worth checking out:
Pro tip: combine this strategy with other techniques such as “lazy” image loading to complete your pages’ first rendering even faster.
Python Machine Learning for SEO & UX
Machine learning is the process of improving AI systems through repeated tasks. Python works through an intuitive syntax that has made it very popular for programming machine-learning applications.
Today, many libraries offer machine-learning capabilities. Also, don’t forget that Python runs on open source, so there is a large community that accumulates expertise on your behalf.
Machine learning analyzes data and patterns and makes predictions based on them. And with the inspected data, the scripts kick off their “learning” process.
Using Machine Learning in Python
You can train a data set by running Python scripts using machine learning methods. The mechanism enables the kind of features you see on websites and social networks that use very complex algorithms.
Some places where you may have encountered this type of AI-driven website content are:
- Customized social media trends and curated timelines.
- Suggestions from video and music streaming services
- Personalized product recommendations on eCommerce sites
Machine learning is nothing more than algorithms “getting to know you” in order to personalize your experience.
Pro tip: Remember machine learning is great for recognizing patterns and curating experiences. But when it comes to creating content, human creativity and knowledge are unrivaled.
You can also use Python machine learning for:
- Content quality checks
- Keyword gap detection
- Metadata optimization processes
- Audio transcription
- Video captioning
- Engagement analysis
Natural Language Processing API for Python: A Great SEO Ally
If you’re handling large volumes of content, consider trying out Google’s Natural Language Processing API or NLP.
As a way to test the API, you could write a small script that uses the google-cloud-language library in Python.
This API has the function of examining:
- Word count
- The overall meaning of your text
Once you feed HTML into the API, it’ll return a list of sentiment, entities, and categories. Use this API to examine your content based on Google’s perception of it, and to train a machine-learning model on your own content to avoid using text from third-party sources.
Protect your Rankings with Automated Technical SEO Monitoring
In this post, we showed you some very useful ways to simplify your technical SEO efforts using Python.
You may be ignoring some of your most important technical SEO elements – not due to lack of knowledge, but because they’re impossible to keep track of. For instance, how can you make sure not a single one of your thousands of URLs has a missing alt text or a misplaced no-index tag?
That’s where SEORadar can help. SEORadar is a technical SEO auditing and monitoring tool that keeps an eye on your code to protect your positioning.
SEORadar will automatically notify you whenever potentially problematic code changes occur on your website. That way, you can take action before your ranking drops. The notifications will be sent based on your preferences, through the channels you choose.
Take control of your technical SEO today. Start a free trial or schedule a demo.