Python for SEO
Python was first utilised in the SEO area a few years ago. Since then, it has grown in popularity, and many individuals have begun to use and recognise the benefits of utilising it in their daily responsibilities.
What Is Python?
Python is a programming language that has been in the industry for a few years. It is different because it is an open-source, line-by-line interpreted object-oriented interactive programming language. Python as a language has been becoming popular in recent years for the enhanced productivity it gives, thanks to its simple and easy-to-learn syntax, advanced readability, and support for a variety of modules and libraries. Because of the advantages provided by python, it is used by some of the world’s largest corporations to power their platforms, execute data analysis, and run machine learning models, as evidence of this.
Some big companies like Google, YouTube, Netflix, NASA, Spotify, and IBM have used python as a major element of their success because of its simplicity, speed, and scalability. In fact, Python was the language used to create Google’s initial web crawler, and it is still one of their official server-side languages.
How To Run Python
Python codes can be used in a variety of ways, based on what works best for you. Most systems come pre-installed with Python, which will most likely be Python 3. If you still have Python 2 installed on your system, you can upgrade to Python 3 by downloading it from the Python website. Python 2 was stopped being used in 2020 since there are significant syntax differences between the two, so it is recommended to use Python 3.
Python can be run in several ways such as a terminal, a command-line IDE (Integrated Development Environment), or desktop apps like Pycharm or VSCode. Alternatives include Google Colab and Jupyter Notebooks, both of which are cloud-based. These make learning and testing code elements line by line, as well as sharing and collaborating with your team, easier for newcomers.
Why Python Is Popular With SEOs
Python is a blessing for SEO workers in a variety of ways, including automating tedious operations and extracting and analysing massive data sets.
Because the number of data marketers who use Python is only growing, being able to efficiently use it will help in solving many complex problems in less time. This will help users save time and be more efficient in performing SEO tasks. Because of these factors combined, Python has gained huge popularity among SEO specialists in this sector.
A better understanding of data will help users do their jobs better, as well as make data-driven decisions. Having a thorough knowledge will allow them to deliver more concrete insights to their clients and stakeholders, as well as gain trust and reputation.
The Benefits Of Automating With Python
Python surely does not have a human mind which can imitate emotion-led strategies, but Python scripts can be used to automate a large number of time-consuming tasks.
This list of tasks Python can help you do is growing tremendously, it includes:
- Identifying user intent.
- Mapping URLs ahead of migration.
- Internal link analysis.
- Performing keyword research.
- Optimizing images.
- Scraping websites.
How to learn python for SEO
Python can be added to your workflow if you start thinking about what tasks can be automated which are particularly tedious and time-consuming. You can think of what problems you have and ways you can more efficiently deal them with and make conclusions from the data you have available to you.
You can start playing around with the data from your website that you already have, for example from a site crawl or your analytics tool.
You can also learn new things from the opposition, try new things and even break something when learning, as this is often the best way to learn. To find the problem of an issue and try to fix it is something SEOs specialists do, and it’s really the same when learning and using Python.
You can learn a great deal from many useful resources out there from other SEOs who have shared practical examples of how they are using Python for SEO-related tasks.
Applications of Python
To get started with Python, here are a few useful ways that can be useful for numerous tasks, along with a brief description of how each one works and the challenges they solve.
Among the various applications of Python, the first is to create a redirect relevancy script to determine whether the redirect mapping that has been created for migration is accurate. It includes crawling your site before the migration and after the migration and segmentation of various categories based on their URL structure.
After this step, you can use comparison operators which are included in python itself to see if the folder and depth of each page have remained the same or have changed as a result of the migration.
The Python script will check your URLs before and after migration and compare them to see if they are the same, and the results will be displayed in a new table. It will return True if they are the same and False if they have changed.
Python package Pandas is a tool that can help you generate a pivot table that shows the number of URLs that match and how many have changed for each category.
You can now go ahead and check for any missing categories or URLs, as well as evaluate the redirect rules that have been set up.
Internal Link Analysis
Internal link analysis in Python is another handy piece of information that makes use of crawl data. This will enable you to determine which portions of your site have the most internal links, as well as possibilities to increase internal linking for certain sections.
You will get data in segments that will help to establish the different categories of URLs, and pivot tables will be used to export a count of the number of internal links to each site category.
Image Captioning With Pythia
Pythia is a modular deep learning platform created by Facebook, which generates a caption for an image URL by using this python coding. This can be a great option for photos that don’t have alt tags, by adding this description URL you can enhance image search and accessibility.
All the aspects from top to bottom and even the small details are considered in the script to calculate outcomes by focusing attention on distinct elements within an image. For each word produced, individual pixels within the image are extensively examined, indicating the region getting the greatest attention. For this, the codes are easily available because it does not require any direct coding and they can be executed directly from Google Colab.
After saving a copy of the required code to your Google Colab storage, you can run all of the cells, which will complete each step for you. By doing this all the data sources required to perform the procedure will be downloaded automatically, as well as all of the steps that would normally be completed manually will be done automatically.
For example, all libraries will be installed, classes will be created, and functions will be allocated. This will provide you with a space to enter your image URL as well as a button to caption the image. After that, for each image, a caption will be provided, which can be used as an alt tag or can be used to inspire the creation of one.
These are only a few examples of the various automation and optimization possibilities available with Python scripts, which include:
- Optimizing images.
- • Combining datasets to reach even more conclusive results.
- Hreflang validation.
- Keyword growth calculation.
- Collecting GSC data.
- Performing competitor analysis.
I hope this has sparked your interest in learning Python and exploring how it may assist you in automating tasks and analysing complex data to boost your efficiency.
Finally, keep in mind that you don’t have to learn Python to be a successful SEO, but if you’re curious or interested, I hope you have fun learning and implementing some Python scripts into your workflow.
Credits – https://www.searchenginejournal.com/python-machine-learning-technical-seo/430000/#close