Scrape job information from Indeed (V8.4)

Indeed is one of the most popular job posting websites. With web scraping, you can uncover the value of tons of job information. In this tutorial, we will show you how to use Octoparse to scrape the job posts from Indeed.com.

Before we get started, we need to get the URL of the target result page by searching a keyword and a location.

Below is an example URL for demonstration:

https://www.indeed.com/jobs?q=devops&l=Dallas-Fort%20Worth%2C%20TX&radius=50

The easiest way to scrape the website is to go to "Task Templates" on the main screen of the Octoparse scraping tool and start with the ready-to-use Indeed Templates directly to save your time. Just input the URL into the template, and you can wait for the data to come out. For further details, you may check it out here: Task Templates

If you would like to know how to build the task from scratch, you may continue reading the following tutorial. 

Here are the main steps in this tutorial:  [Download the task file at the bottom of this page]

1. Go to Web Page - Open the targeted web page
2. Create Pagination - Scrape data from multiple pages
3. Create Loop Item - Scrape job information
4. Set up the wait time for "Extract Data" - control scraping speed
5. Start extraction - run the task and get data

1. Go to Web Page- open the targeted web page

• Enter the URL on the home page and click Start

2. Create Pagination - Scrape data from multiple pages

• Click on the Next page button (>) on the page
• Choose Loop click singe element on the Tips

A Pagination will be created in the workflow.

To make sure the pagination can work well, we need to modify the XPath of it.

• Click on Pagination 
• Enter XPath //a[@aria-label="Next"]
• Click Apply to save

3. Create Loop Item - Scrape job information

• Select the first two job info blocks (note to select the whole job block that includes all the information you want)
• Choose Extract text of the selected elements

A Loop Item will be created in the workflow.

But you may have noticed that all the information has been scraped into one cell. We need to separate the information into different columns.

• Select the first job title (within the highlighted area)
• Choose Extract the text of the element

• Do the same to scrape other information from the first job
• Double-click on the field name to rename it if needed

4. Set up the wait time for "Extract Data" - control scraping speed

• Click on Extract Data
• Click on Options
• Tick Wait before action
• Set up the wait time as 1-2s

5. Start extraction - run the task and get data

• Click Save
• Click Run on the upper left side
• Select Run on your device to run the task on your computer, or select Run task in the Cloud to run the task in the Cloud (for premium users only)

Here is the sample data for your reference -