Empowering Data-Driven Decisions with Seamless Web Insights
This project is a lightweight Python web application built with Flask, designed to extract and serve structured insights from web sources. Featuring a modular setup and deployment-ready configurations for AWS Elastic Beanstalk, it's ideal for rapid development and deployment of web scraping or data extraction tools.
- 🔥 Flask-based web interface for processing and displaying results
- 📄 HTML scraping using BeautifulSoup
- 🌐 Cross-Origin Resource Sharing (CORS) support
- 🚀 Production-ready with Gunicorn and Elastic Beanstalk support
- 📁 Templated frontend using Jinja2 and custom CSS
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Clone the repository
git clone https://github.com/AryanGupta5084/Python.git cd Python -
Create a virtual environment (optional but recommended)
python3 -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate
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Install dependencies
pip install -r requirements.txt
Run the application locally:
python application.pyBy default, the app runs on http://localhost:5000. You can access the homepage and begin interacting with the web interface.
- Elastic Beanstalk: Configured via
.elasticbeanstalk/config.ymland.ebextensions/python.configfor deployment. - CORS: Enabled via
Flask-Cors. - Gunicorn: Used for production WSGI server.
From requirements.txt:
Flask==1.1.2
Flask-Cors==3.0.9
gunicorn==20.0.4
requests==2.24.0
beautifulsoup4==4.9.1
bs4==0.0.1
pymongo
Jinja2, click, certifi, idna, urllib3, six, chardet, MarkupSafe, itsdangerous, Werkzeug
- Ensure all dependencies are installed correctly.
- When deploying on Elastic Beanstalk, double-check
.ebextensionsand Python version compatibility. - For CORS issues, review
Flask-Corsmiddleware configuration inapplication.py.
- Aryan Gupta – Author & Maintainer