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WEB SCRAPPING

Empowering Data-Driven Decisions with Seamless Web Insights

🌐 Overview

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.


📚 Table of Contents


✨ Features

  • 🔥 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

⚙️ Installation

  1. Clone the repository

    git clone https://github.com/AryanGupta5084/Python.git
    cd Python
  2. Create a virtual environment (optional but recommended)

    python3 -m venv venv
    source venv/bin/activate  # On Windows: venv\Scripts\activate
  3. Install dependencies

    pip install -r requirements.txt

🚀 Usage

Run the application locally:

python application.py

By default, the app runs on http://localhost:5000. You can access the homepage and begin interacting with the web interface.


⚙️ Configuration

  • Elastic Beanstalk: Configured via .elasticbeanstalk/config.yml and .ebextensions/python.config for deployment.
  • CORS: Enabled via Flask-Cors.
  • Gunicorn: Used for production WSGI server.

📦 Dependencies

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

🛠 Troubleshooting

  • Ensure all dependencies are installed correctly.
  • When deploying on Elastic Beanstalk, double-check .ebextensions and Python version compatibility.
  • For CORS issues, review Flask-Cors middleware configuration in application.py.

👥 Contributors

  • Aryan Gupta – Author & Maintainer

About

This project showcases web scraping using Python, including scripts and resources for automating data extraction from websites. It also features a web interface for ease of use.

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