🧠 Sentiment Analysis Web Tool 🛠️ Technologies Used TextBlob — Sentiment analysis
Flask-SQLAlchemy — Database ORM
SQLite — Lightweight database for storing entries
HTML/CSS — Frontend templates
Render — Cloud deployment
🚀 How to Run Locally
- Clone the repository git clone https://github.com/ldodson10/sentiment-app.git cd sentiment-app
- Create and activate a virtual environment (recommended): python -m venv venv venv\Scripts\activate # On Windows
- Install the required packages: pip install -r requirements.txt
- Run the application: python app.py Visit http://localhost:5000 in your browser.
☁️ Deployment with Render This project is deployed using Render, a cloud hosting platform that enables developers to launch web applications with ease.
⚡ Why Render? Render simplifies the process of hosting and running backend applications like this Flask-based sentiment analysis tool. It automatically pulls the latest code from GitHub and deploys it, eliminating the need to manually manage infrastructure.
🔧 Workflow Overview GitHub is used to store, version, and manage the project code. Render connects to the GitHub repository, builds the application, and hosts it live.
🔗 Live Demo: https://sentiment-app-6y17.onrender.com
🗂️ Project Structure
📁 sentiment-app/
├── app.py # Main application logic
├── requirements.txt # Python dependencies
├── render.yaml # Render deployment configuration
├── templates/
│ ├── index.html # Input form page
│ └── result.html # Output results page
├── static/ # Static assets (if any)
└── README.md # Project documentation