Skills Showcased: Python, Web Scraping, HTML
As a job seeker, it is frustrating to apply for jobs on pages like LinkedIn, and not to have any JD as reference a few weeks / months after the application as the application page was taken down, or that you have forgotten where you've applied. What I would have done to circumvent this issue is to copy and paste the JD into a word document and save it into a folder named as with the company and the job title (e.g. Coca-cola - Business Analyst). This was a multi-step process and takes roughly a minute or two. The time adds up when application number increases.
This webscraping project is to automate these tasks to reduce time for each job application.
The project utilizes the BeautifulSoup library, which is a library that works by assessing the data within the HTML of a page. One can further specify the section by searching for the HTML elements' tag and class to get a specific data. This is reflected in the project as I extracted the job company, job title and job description from different elements.
As the JD for each company is built differently with different formattings, I chose to save the JD as a HTML file to maintain its format structure. Then, with the extracted Company Name and Job Title, a folder is created in the specified path given earlier in the code for the HTML file to be written. It is then a 3-step process.
- Copy the LinkedIn job posting link.
- Run the code.
- Paste the link into the input pop-up.
Simple and effective! Hope this will help other job seekers who looks to do the same too!