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SeriesFeedback


📗 Table of Contents

📖 SeriesFeedback (JavaScrip-Capstone)

SeriesFeedback is an interactive website that provides a platform for users to engage in discussions and share their feedback on a wide range of TV shows. Whether you're a fan of captivating classics or enjoy exploring innovative creations, SeriesFeedback offers a diverse collection of films and shows for you to explore.

With the integration of two powerful external APIs, MazeTv and the Microverse Involvement API, SeriesFeedback ensures a seamless experience when it comes to fetching, displaying, and interacting with TV series. You can easily discover new genres, embark on visual adventures, and express your thoughts and opinions.

Join our community of film enthusiasts, and immerse yourself in conversations about your favorite shows. Share your feedback, leave comments, and connect with fellow users who share your passion for the silver screen. At SeriesFeedback, every movie and series becomes an opportunity for engaging discussions and exciting conversations.

Experience the joy of voicing your impressions and being part of a vibrant community of TV show enthusiasts on SeriesFeedback. Start exploring now and let your opinions be heard!


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🛠 Built With

Tech Stack

The following stacks were used

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Key Features

  • TV Show Listings: The home page of SeriesFeedback presents users with an extensive catalog of TV shows. Users can effortlessly browse through the available shows and discover new content to explore.

  • Likes and Interactions: To express their appreciation for a TV show, users can simply click on the heart icon button associated with each show. This functionality is seamlessly integrated, allowing users to easily indicate their preference.

  • Commenting System: SeriesFeedback provides a convenient pop-up window or modal where users can leave comments about their favorite TV shows. This interactive feature allows for lively discussions and encourages users to share their thoughts.

  • Counters: To enhance the user experience, SeriesFeedback incorporates counters that dynamically track important metrics. These counters keep a real-time tally of the number of shows displayed on the home page and the total number of comments in the pop-up window.

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🚀 Live Demo

Live Demo

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🔭 Walk through video

Here

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💻 Getting Started

Prerequisites

In order to run this project you need to have a browser and of course a code editor

Setup

Clone this repository to your desired folder, you can also set up HTML, CSS and JavaScript linters, for this you will need node installed. you can follow the steps here and here to setup the linters

Install

Once you cloned this project you are done !

Usage

To run the project, you can simply open the index.html file with your favorite browser.

Run tests

If you follow the tutorial above to setup linters then you can run these tests

  npx hint .
  npx stylelint "**/*.scss"

or if you use css then run this instead of the latter command above

  npx stylelint "**/*.{css,scss}"

Deployment

You can deploy this project using: GitHub Pages

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👥 Authors

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🔭 Future Features

  • Pagination
  • Integration with popular streaming services
  • Customizable notifications and alerts
  • Multilingual support

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🤝 Contributing

Contributions, issues, and feature requests are welcome!

Feel free to check the issues page.

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⭐️ Show your support

If you like this project you can follow me on github for more.

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🙏 Acknowledgments

  • We would like to express our gratitude to the creators and maintainers of the MazeTv and Microverse Involvement APIs for their invaluable contributions.
  • We would like to express our heartfelt gratitude to Microvere for the invaluable learning experience they have provided. The supportive community, dedicated mentors, and remote collaboration opportunities have enhanced my technical skills and prepared me for real-world projects.

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❓ FAQ (OPTIONAL)

  • Are the linters necessary?

    • It is a good practice to install and use them as they guide you towards best practice, but yes you can do without.

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📝 License

This project is MIT licensed.

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