nuraz12/ShakeIt-Music-Recommendation

View on GitHub by @nuraz12

🎶 Discover personalized music suggestions with ShakeIt, a terminal-based engine that analyzes your listening habits from over 114,000 tracks.

What's novel

🎶 Discover personalized music suggestions with ShakeIt, a terminal-based engine that analyzes your listening habits from over 114,000 tracks.

Code Analysis

3 files read · 2 rounds

A terminal-based content-based music recommendation system that uses audio features from a static CSV dataset to suggest similar songs and visualize them via radar charts.

Strengths

The code is well-structured with clear separation of concerns between the CLI loop, recommendation logic, and visualization. It effectively implements standard machine learning techniques (Cosine Similarity, PCA) for a simple use case and includes helpful visualizations.

Weaknesses

Lacks error handling for file I/O and edge cases like missing datasets or ambiguous song names. The README significantly overstates the project's capabilities by claiming Spotify integration and executable installation which do not exist in the codebase.

Score Breakdown

Innovation

3 (25%)

Craft

54 (35%)

Traction

8 (15%)

Scope

42 (25%)

Signal breakdown

Innovation

Not Fork+1

Code Novelty+1

Concept Novelty+0

Craft

Ci+0

Tests-1

Polish+0

Releases+0

Has License+5

Code Quality+16

Readme Quality+15

Recent Activity+7

Structure Quality+5

Commit Consistency+2

Has Dependency Mgmt+5

Traction

Forks+0

Stars+6

Hn Points+0

Watchers+0

Early Traction+0

Devto Reactions+0

Community Contribs+2

Scope

Commits+5

Languages+3

Subsystems+5

Bloat Penalty+0

Completeness+7

Contributors+6

Authored Files+8

Readme Code Match+3

Architecture Depth+3

Implementation Depth+8

Evidence

Commits

Contributors

Files

Active weeks

TestsCI/CDREADMELicenseContributing

Repository

Language

Python

Stars

Forks

License

MIT