Job Board Data Scraping
Abhiram Kannuri
Project Overview Created a Python script to automate the scraping of job listings from various job boards, collating information such as job titles, descriptions, company names, and application links.
Technical Challenges
• Diverse Data Formats: Navigating different layouts and data structures across various job boards.
• Robustness and Reliability: Ensuring the scraper is resilient against changes in website layouts and intermittent network issues.
Solutions Implemented
• Adaptive Scraping Logic: Utilized advanced parsing techniques with BeautifulSoup to handle varying HTML structures.
• Scheduled Scraping: Set up automated scraping sessions using cron jobs to regularly update the job listings database.
Project Outcome The script efficiently aggregates job opportunities into a single database, providing job seekers with streamlined access to new postings, significantly simplifying their search process.
Technologies Used
• Languages: Python
• Libraries: Requests, BeautifulSoup, APScheduler
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Posted Jul 14, 2024
A custom script that gathers and integrates job postings from diverse job boards, aiding job seekers in finding ideal employment opportunities more efficiently.
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