Faculty Information Scraper

Introduction

This project is designed to automate the process of extracting faculty information from the college website. It scrapes names, designations, and images of all professors and saves the data in a CSV file. This information was used to create personalized posters for Teachers' Day, significantly improving efficiency and reducing manual effort.

Implementation Details

• The script uses BeautifulSoup to parse the HTML content and extract faculty names, designations, and image URLs.
• The extracted data is cleaned and written to a CSV file.
• The images are saved locally and the CSV file includes the paths to these images.
• An automation pipeline with Adobe Illustrator and Photoshop uses the CSV data to create personalized posters for each faculty member.
• The posters are automatically exported and uploaded to Google Drive, making them easily accessible to student volunteers which were then shared to respective teachers with personalised notes.

Results and Performance

The automated pipeline drastically reduced the time required to create and distribute posters for Teachers' Day. The efficiency improved tenfold, enabling the creation of posters for all faculty members in a very short time.