CS50P - A Mini Search Engine using Python
This video demonstrates my CS50 Python Final Project: Mini Search Engine in Python.
The project analyzes text files and ranks them based on relevance to user-provided keywords using the TF-IDF algorithm. It calculates relevance percentages, highlights keywords in the preview, and displays all files—including those with zero relevance.
Key features:
TF-IDF–based relevance ranking
Case-insensitive keyword matching
Keyword highlighting in file previews
Compact preview output
Automated testing using pytest
Fully compliant with CS50 Python project requirements
In this video, I demonstrate:
How the project runs from the command line
How files are ranked based on keyword relevance
How keyword highlighting works
How automated tests validate the implementation
This project showcases Python file handling, text processing, and basic information retrieval concepts.
Project by: Rajesh Kumar
Course: CS50’s Introduction to Programming with Python
Date Recorded: January 6, 2026
(Note: Exact relevance percentages may vary depending on keyword frequency and document length.)
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