Spotify Mood analyzer using a ml algorithm to study my music playback and create a personalized listening experience
My name is Pranav, and I am a Computer Science student working on a personal project that utilizes the Spotify API to build a mood analyzer for my music preferences. I am reaching out for some assistance regarding an issue with the rate limits on my app, as well as guidance on how to proceed with building the algorithm.
Project Overview:
The goal of my project is to develop a system that can analyze and track my music preferences over time, adjusting my playlist suggestions and moods based on my listening behavior. The system stores data from my Spotify account and uses machine learning (ML) to understand how my music choices correlate with different times of day, my mood, and specific song characteristics (such as skips, completions, and likes).
Here is the approach I am currently using:
- Data Collection: I am collecting real-time data on my Spotify listening activity (track name, artist, play status) every 10 seconds.
- Database: This data is stored in a local database, which is used by a machine learning model to analyze my listening patterns.
- Mood-based Algorithm: Based on the data, the algorithm adjusts the mood of the music played, ensuring that different types of songs are recommended based on the time of day or my emotional state. For example:
- In the morning, I might want soothing or calming music.
- By the afternoon, I might need something more upbeat to keep me productive.
- In the evening, I want music that is relaxing or sets a vibe.
- Late at night, I might prefer softer music to help me wind down.
However, I am encountering an issue with Spotify's rate limits when my app continuously updates the track information every 10 seconds. It appears that these frequent requests are triggering the rate limits, and I'm unable to get the data I need consistently.
Request for Assistance:
I would greatly appreciate your help in resolving the rate limit issue. Specifically, I am hoping to understand:
- If there is a recommended way to optimize the frequency of data requests to avoid hitting the rate limits (e.g., updating less frequently, caching results, etc.).
- Any best practices for managing rate limits with the Spotify API when building apps that require frequent updates.
- Any potential changes I can make to my approach to avoid running into these rate limit issues, while still being able to track my listening patterns effectively.
Next Steps in the Project:
Additionally, I would love to get some guidance on how to proceed with the machine learning part of the project. The goal is to create an algorithm that:
- Builds a personalized mood profile based on my listening history.
- Analyzes my preferences based on when I skip or like songs and when I listen to them.
- Recommends music in real-time based on my current mood, or the mood I want to set for a particular part of the day.
I would be grateful for any advice or resources that can help me improve the implementation of the algorithm and optimize the data flow.
Thank you so much for your time and assistance. I look forward to your guidance and suggestions to help me move forward with this project.
Best regards,
Pranav