Roberthalf Scrap

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Roberthalf Scrap






4 Days

Project overview :

This project aims to scrape job listing information from a specific website,, using web automation with Selenium in Python. The project involves navigating through multiple pages of job listings, extracting relevant details from each job listing, and saving this data to a CSV file for further analysis.

What we did for this project :

1. Imports: The project starts with importing necessary libraries, including Selenium for web automation, ChromeDriverManager for managing the Chrome WebDriver, time for controlling timing, and CSV for handling data storage.

2. get_driver() Function: A function named get_driver() is defined to set up a Selenium WebDriver. This function configures the WebDriver with specific options and opens a given URL.

3. scrap() Function: The scrap() function is created to extract job details from the current web page. It uses XPath expressions to locate and retrieve the following information:
• Position
• Job Type
• Location
• Salary
• Job Description
• Job Requirements
• Qualifications

4. save_csv() Function: Another function, save_csv(), is defined to save the scraped data to a CSV file. It appends data to the CSV file, adding a header row if the file is empty or creating a new file if it doesn’t exist.
5. Main Script: The main part of the script utilizes the WebDriver to navigate through multiple pages of job listings and scrape data from each listing. The script uses a loop to iterate through the job listing pages. It collects job details using the scrap() function, then saves this data to a CSV file using the save_csv() function. The total count of scraped job listings is maintained for further analytics.

Project results :

The project successfully scrapes job listings from the specified website and saves the job details into a CSV file. It navigates through multiple pages of job listings, extracts various attributes, and ensures data is correctly appended to the CSV file.

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