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Data Engineering · APIs · Python
Python, Spotify API, OAuth 2.0, REST APIs LinksCode All projects
Overview
A Python project demonstrating best practices for batch data extraction from the Spotify Web API. This serves as a foundation for music analytics, trend analysis, and recommendation systems.
Features
- OAuth 2.0 Authentication: Token-based auth with automatic refresh
- Paginated Data Retrieval: Two pagination strategies implemented
- Rate Limit Handling: Built-in rate limiting awareness
API Endpoints Used
- Browse New Releases
- Get Album Tracks
Pagination Strategies
1. Offset-Based Pagination
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# Manual calculation of next page
offset = offset + limit
- More control over pagination logic
- Useful for custom requirements
2. URL-Based Pagination
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# Uses 'next' URL from API response
next_url = response['next']
- Simpler implementation
- Recommended approach
Rate Limiting
Spotify API uses dynamic rate limiting (30-second rolling window):
- Configurable request intervals
- Exponential backoff strategies
- Request timing analysis
Future Enhancements
Data & Analytics
- Audio features integration (tempo, energy, danceability)
- Artist analytics and visualization dashboards
Technical
- Database integration (PostgreSQL/MongoDB)
- Docker containerization
- Async processing
Machine Learning
- Music recommendation algorithms
- Genre classification models
- Trend analysis and clustering