sentiment-analyzer Tailwind Templates

Sentiment Analyzer

Simple sentiment analysis using Flask, TextBlob, and jQuery (for fun). Deployed to AWS Lambda using Zappa, with some Google fonts and Tailwind styling for good measure.

Sentiment Analyzer

Hey there, friend! This is the Sentiment Analyzer. I designed it with a touch of warmth to make it more human-friendly. It's an application that allows users to analyze the sentiment of any text input — showing you whether the text is generally positive, negative, or neutral. This application runs as a web app, and it's powered by Python's Flask framework on the backend and Tailwind CSS for the frontend. Let's get started on how to set this up.

Features

  • Easy Input: Just type in or paste any text you want to analyze.
  • Instant Analysis: Click the "Analyze" button, and get your results right away!
  • Reset Function: Want to try with different text? No problem, just hit the "Reset" button.

Getting Started

To get a local copy up and running, follow these simple steps:

  1. Clone the repository:
git clone https://github.com/johncarmack/sentiment-analyzer.git
cd sentiment-analyzer
  1. Install Python. If you're not sure how, you can check this guide for instructions.

  2. Install the project dependencies and start your virtual environment:

pip install -r requirements.txt
python -m venv venv
source venv/bin/activate
  1. Run the app:
flask run

Then, open up your web browser and navigate to http://localhost:5000/.

Deployment

This app is ready to be deployed using Zappa, a serverless framework for Python. The app is configured to be deployed on AWS via the zappa_settings.json file. Remember to replace the placeholders with your AWS details.

To deploy the app, you just need to run:

zappa deploy dev

or:

zappa deploy production

depending on the environment you wish to deploy.

For more information about Zappa, check their documentation.

GitHub Actions

The .github/workflows/zappa.yml file sets up a GitHub Actions workflow for continuous integration and deployment. Whenever you push to the main branch, your application will be deployed to AWS automatically.

Future Improvements

Like all projects, this is a work in progress. Here are some enhancements that could be made:

  • Allow the analysis of more complex forms of text, like documents or URLs.
  • Improve the interface for a more immersive user experience.

Contributing

Contributions, issues, and feature requests are welcome! Feel free to check issues page.

Show Your Support

Give a ⭐️ if you like this project!

Thank you so much for taking the time to read this. I hope you find it useful and I'm looking forward to hearing your feedback!

Warm regards,
John

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