I designed a scraping 🕸️ tool to extract job posting data from Glassdoor. This scraping tool will return job title, company name, job id, location, salary, language and skills and many more.
It was easier to extract Glassdoor data compared to Indeed because job postings in Glassdoor are organized, properly labelled and glassdoor also provides estimated salary (if not present).
Thank you Glassdoor
Install required dependencies in your project folder.
pip install -r requirements.txt
Make sure you have Chrome ⬇️ latest version installed in your system. This step creates scraped_glassdoor_job_file.csv with all columns. You can check the sample output in this repository itself, I extracted for Data Analyst Position in Canada.
Currently, only one web address can be processed during each run. Create a list of different addresses, and pass the index value; the tool should fetch each url one by one, and scrap accordingly, and create a final output or multiple outputs.