Analyze text sentiments (positive, negative, or neutral) with this lightweight Flask application powered by TextBlob for Natural Language Processing (NLP).
- ✅ Real-Time Sentiment Analysis: Analyze text and classify sentiments instantly.
- 🌐 Responsive Web Interface: Clean, modern, and mobile-friendly design.
- 🎨 Dynamic Visual Feedback:
- Positive Sentiment: ✅ Displayed in green.
- Neutral Sentiment: 🔘 Displayed in gray.
- Negative Sentiment: ❌ Displayed in red.
- 🛠️ Built with Flask, TextBlob, and Bootstrap.
| Technology | Purpose |
|---|---|
| Python | Backend logic and Flask framework |
| TextBlob | Sentiment analysis and NLP functionality |
| HTML & CSS | Frontend structure and styling |
| Bootstrap | Responsive and modern web design |
| Render | Hosting platform for deployment |
🎉 Try the live application here: Live App on Render
- 🐍 Python 3.9+ installed on your system.
- 📦 Dependencies listed in
requirements.txt.
-
Clone the Repository:
git clone https://github.com/your-username/flask-sentiment-analysis.git cd flask-sentiment-analysis -
Create and Activate a Virtual Environment:
- On macOS/Linux:
python3 -m venv venv
source venv/bin/activate- On Windows:
python -m venv venv
venv\Scripts\activate- Install Dependencies:
- Run the following command to install required libraries:
pip install -r requirements.txt- Run the Application Locally:
python app.py- Run the Application Locally:
- Start the Flask application:
python app.py- Open the App in Your Browser:
- Navigate to: http://127.0.0.1:8000
Contributions are welcome! Here's how you can help:
- Fork the repository.
- Create a new branch (
git checkout -b feature-name). - Commit your changes (
git commit -m "Added feature"). - Push to the branch (
git push origin feature-name). - Submit a Pull Request.
Feel free to reach out if you have any questions or suggestions:
- 📩 Email: [email protected]
This project is licensed under the MIT License. See the LICENSE file for details.