Top 10 Web Scraping Projects for Final Year Students with Source Code 2026

Web Scraping is the process of automatically extracting data from websites using code. It is one of the most practical and impressive skills a programmer can have – used by data scientists, market analysts, journalists, and software engineers worldwide.

If you are looking for unique, practical, and highly impressive final year project ideas, Web Scraping projects stand out from the crowd. All projects below are available for free on FinalYearProjectsHub.

Why Web Scraping Projects Are Perfect for Final Year Students

Web scraping projects are excellent because they:

Demonstrate real automation skills that companies actively use
Combine multiple skills: Python, HTML parsing, databases, and data analysis
Can be applied to any industry – news, finance, jobs, real estate, and more
Produce real, live data that makes your project demo impressive
Are unique – most students don’t choose scraping projects, making you stand out

Top 10 Web Scraping Final Year Projects

1. Job Listings Scraper and Aggregator

Technologies: Python, BeautifulSoup, Requests, Flask, SQLite

Scrapes job listings from multiple job portals and displays them in a unified dashboard. Users can search, filter, and bookmark jobs without visiting multiple sites.

What You Will Learn:

Multi-site web scraping with BeautifulSoup
Data deduplication and cleaning
Building a job search interface with Flask
Database storage with SQLite

2. Real-Time Product Price Tracker

Technologies: Python, BeautifulSoup, Selenium, Flask, Email Alerts

Tracks product prices on e-commerce sites and sends email alerts when the price drops below a set threshold. Similar to tools used by millions of online shoppers.

What You Will Learn:

Dynamic page scraping with Selenium
Price history tracking and database storage
Email alert system with Python smtplib
Building a price history chart

3. News Aggregator and Sentiment Analyzer

Technologies: Python, BeautifulSoup, NLTK, Flask, Pandas

Scrapes news headlines from multiple news sites and performs sentiment analysis to classify each article as positive, negative, or neutral. Displays results in a dashboard.

What You Will Learn:

Multi-source news scraping
Natural Language Processing for sentiment analysis
Combining web scraping with machine learning
Real-time dashboard with auto-refresh

4. Stock Market Data Scraper and Visualizer

Technologies: Python, BeautifulSoup, Pandas, Matplotlib, Flask

Scrapes real-time stock prices, historical data, and company information from financial websites. Displays interactive stock charts and trend analysis.

What You Will Learn:

Financial data scraping and parsing
Data visualization with Matplotlib and Plotly
Time series analysis
Building a stock dashboard

5. Real Estate Listing Scraper

Technologies: Python, Selenium, Pandas, Flask, SQLite

Scrapes property listings from real estate websites and organises them by location, price, and type. Users can compare properties and track new listings.

What You Will Learn:

Handling pagination and dynamic content with Selenium
Location-based data filtering
Property comparison dashboard
Automated daily scraping with scheduling

6. Social Media Trend Tracker

Technologies: Python, Tweepy API, NLTK, Flask, Pandas

Collects trending topics and hashtags from Twitter/X using the API and analyses their sentiment and frequency. Displays trending topics with charts and word clouds.

What You Will Learn:

Twitter API integration with Tweepy
Text preprocessing and word cloud generation
Trend analysis and visualisation
Real-time data collection

7. E-Commerce Review Scraper and Analyser

Technologies: Python, BeautifulSoup, NLTK, Flask, Pandas

Scrapes customer reviews from e-commerce sites and analyses them using NLP to extract common themes, ratings distribution, and overall sentiment.

What You Will Learn:

Review scraping from complex page structures
NLP-based review summarisation
Rating analysis and visualisation
Extracting insights from unstructured text

8. Wikipedia Data Extractor

Technologies: Python, BeautifulSoup, Requests, Pandas, Flask

Extracts structured data from Wikipedia articles — tables, infoboxes, and sections – and converts them into clean, downloadable datasets. Useful for research and data analysis.

What You Will Learn:

Wikipedia HTML structure parsing
Table extraction and data cleaning
Converting scraped data to CSV and JSON
Building a search interface for extracted data

9. Government Data Scraper and Dashboard

Technologies: Python, Requests, Pandas, Plotly, Flask

Scrapes publicly available government data (population, employment, crime statistics) and presents it in an interactive analytics dashboard. A high-impact social good project.

What You Will Learn:

Scraping structured government and open data portals
Data cleaning and normalisation
Interactive Plotly dashboard development
Geographical data visualisation

10. Automated Research Paper Scraper

Technologies: Python, BeautifulSoup, Requests, Pandas, Flask

Scrapes research papers from Google Scholar, arXiv, or PubMed based on a keyword search and organises them by citation count, year, and relevance.

What You Will Learn:

Academic data scraping and parsing
Citation analysis and ranking
Building a research paper search engine
PDF download automation

Tools You Need for Web Scraping Projects

Python 3.8+: Primary language for web scraping
BeautifulSoup4: For parsing static HTML pages
Selenium: For scraping JavaScript-heavy dynamic pages
Requests: For making HTTP requests
Pandas: For cleaning and organising scraped data
Flask: For building a web interface for your project

Install all at once:
pip install requests beautifulsoup4 selenium pandas flask plotly nltk

Frequently Asked Questions

1. Is web scraping legal for final year projects?

Web scraping publicly available data for educational and non-commercial purposes is generally accepted. Always check a website’s robots.txt file and terms of service. For final year projects, scraping public data for research is widely considered acceptable.

2. Which is better for web scraping – BeautifulSoup or Selenium?

BeautifulSoup is better for static pages that load all content in the initial HTML response. Selenium is necessary for dynamic pages that load content via JavaScript. Most projects use both together.

3. Can a beginner do a web scraping final year project?

Yes! Projects like the Wikipedia Data Extractor and Job Listings Scraper are beginner-friendly with clear HTML structures. Start with BeautifulSoup on a simple site before moving to Selenium.