![]() If you would like to extract details in bulk, a JSON file is more preferable. In this article, we are only scraping the job name, company, location and estimated salary from the first page of results, so a CSV file should be enough to fit in all the data. ![]() We have predefined the XPaths for the details we need in the code. Parse the page using LXML – LXML lets you navigate the HTML Tree Structure using Xpaths.Download HTML of the search result page using Python Requests.Since we will be extracting listings by their job name and location, here are the listings to find Android developer in Boston, Massachusetts. First, construct the URL for the search results from Glassdoor.Here is a screenshot of the data we will be extracting Here is the list of fields that we will be extracting: The scraper will extract the data fields for a particular job name in a location given. In this tutorial, we will scrape, one of the fastest growing job recruiting sites. Learn to scrape Glassdoor Jobs without having to code using ScrapeHero Cloud
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