Using Python for Technical SEO
Using Python for Technical SEO: What You Need to Know
Python has been receiving a lot of attention within the SEO community recently.
So, being the curious technical SEO that I am, I started looking into why and before I knew it, I was deep into learning and applying it.
It’s fair to say that I have fallen in love with the language over the past few months that I have been learning it and want to share it with everyone, to show how it can help automate SEO tasks.
I’m not a data scientist and I don’t have a computer science background, but the beauty of Python is you don’t need to have experience in either of these things in order to understand and start using it.
What Is Python?
In short, Python is an open-source, object-oriented interactive programming language that is interpreted line by line.
With simple and easy to learn syntax, as well as advanced readability and support for a number of modules and libraries, Python is well-loved due to the increased productivity it provides.
As a testament to this, Python is used by some of the biggest organizations in the world to power their platforms, perform data analysis, and run their machine learning models.
Companies including Google, YouTube, Netflix, NASA, Spotify, and IBM have publicly stated Python has been an important part of their growth, due to its simplicity, speed, and scalability.
In fact, Google’s first web-crawler was actually written in Python and it remains one of their official server-side languages.
How to Run Python
You can run Python scripts in a number of ways, depending on what works best for you.
Most systems come with Python already installed, although it’s worth noting that this will more than likely be Python 2, which will be officially deprecated in 2020 now that Python 3 is deemed stable.
You can run Python from your terminal or command line IDE (Integrated Development Environment) or use cloud-based alternatives including:
These provide an easier experience for beginners to learn and test elements of code line by line.
Python Libraries
The main power of Python is in its libraries, which enable a number of add-ons including:
- Data extraction.
- Analysis and preparation.
- Scientific computing.
- Natural language processing.
- Machine learning.
Some useful libraries for tasks involving data analysis and automation include:
- TensorFlow: An open-source machine learning library.
- NumPy: Useful for scientific computing.
- SciPy: Used for scientific and technical computing.
- SciKit Lear: Machine learning for data mining and analysis.
- Pandas: Used for data manipulation and analysis.
- SpaCy: A great natural language processing library.
- Requests: A library for making HTTP requests.
How Python Can Help with Technical SEO
While having an understanding of the languages which power the websites we work on (such as HTML, CSS, and JavaScript) is important, Python provides many automation opportunities for low-level tasks which we would usually spend several hours undertaking.
Python empowers SEO professionals in a number of ways as it not only enables us to automate repetitive tasks, but also to extract and analyze large data sets.
The amount of data marketers work with is only increasing, so being able to efficiently analyze this will help to solve many complex problems in a shorter amount of time.
This in turn saves valuable time and allows us to be more efficient in undertaking other important SEO tasks.
These factors combined have led to a growth in the popularity of Python amongst SEO professionals.
The ability to better understand data will not only help us do our jobs better, but will also allow us to make data-driven decisions.
These decisions will then enable us to provide concrete insights for our clients and stakeholders and have more confidence in the recommendations we implement.
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