(WebApp Demo - Please wait for a couple Seconds for app to load for the first time) - (https://musicstreamhub.azurewebsites.net/)
Welcome to the GitHub repository for our Music MusicStreamHub Web Application! This project is a web application that aims to provide users with an all in one Music Streaming experience. By combining various third-party APIs and micro services, we have created a platform that allows users to explore, discover, and analyze music and Artists in a unique and interactive way.
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Frontend Technologies: Our frontend is built using a combination of HTML, CSS, JavaScript, Thymeleaf, and Bootstrap. This ensures a visually appealing Design.
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Third-Party APIs Integration: We leverage several third-party APIs, including Spotify API, Genius API, MusixMatch API, and YouTube API. These APIs enable us to fetch a wealth of music-related data, including artist information, song details, lyrics, and embedded YouTube videos.
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Backend Development: The backend of our application is powered by Java and Spring Boot, creating a robust foundation for handling server-side logic and RESTful APIs. This ensures seamless communication between the frontend and the various APIs.
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Interactive User Experience: Our web app features user-friendly interactive elements implemented with JavaScript libraries. These interactive features enhance the overall user experience, providing a smoother and more engaging interface.
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Song and Artist Recommendations: Users can receive personalized song and artist recommendations based on their preferences, enhancing their music discovery journey.
Our Music Discovery and Analysis Web Application offers a seamless and engaging process for users to dive into the world of music:
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Artist Selection: Users begin by typing in the name of their favorite artist. A dynamic carousel of different artists emerges, allowing users to explore various options. Users can either select the correct artist from the carousel or browse for similar artists that pique their interest.
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Track Exploration: Once an artist is elected, the application navigates to the tracks page. This page presents a curated list of top tracks from the selected artist, along with tracks that are stylistically similar. Users can effortlessly explore these tracks, gaining insight into the artist's diverse musical offerings.
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Comprehensive Music Experience: Upon selecting a track, the application seamlessly transitions to the final page. Here, users are treated to a comprehensive music streaming experience. The page automatically loads the selected track's corresponding lyrics and a seamlessly embedded YouTube video. This integration of lyrics and video ensures users can immerse themselves in the music, enhancing their connection to the song.
Through this intuitive process, our application provides a holistic and immersive journey into the world of music, allowing users to explore artists, discover tracks, and engage with their favorite tunes in an interactive and enjoyable manner.
We have deployed our web application on the Microsoft Azure cloud platform using a continuous integration and continuous deployment (CI/CD) pipeline integrated with GitHub workflow. This deployment strategy ensures that updates are efficiently automated and made available to the public, maintaining a seamless user experience.
We are committed to continuous improvement and innovation. In the future, we plan to implement AI models for Music Mood Analysis. This feature will allow users to explore music based on emotions, providing a unique and personalized way to engage with their favorite tunes.
We welcome contributions, feedback, and suggestions from the community. If you're interested in collaborating or have ideas for enhancing our Music Discovery and Analysis Web Application, please don't hesitate to get in touch.
Thank you for visiting our repository and for your interest in our project!
Authors: Eniola O.
Website: https://musicstreamhub.azurewebsites.net/
Email: Olumeyae@tcd.ie
LinkedIn: https://www.linkedin.com/in/eniolabo/