GitHub - el10savio/artistInsights: A full-stack Last.fm 1k dataset listening insights page for artists using Go/ClickHouse/React · GitHub
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Artist Insights
This is a full-stack project to visualize and provide reports and insights on the Last.fm song listening history dataset and to provide insights for artists so that they can infer and improve on their fan base.
Overview
The repository is built mainly by importing the Last.fm dataset and then adding it to ClickHouse, which stores the listening data points for each user (which song they listen to and when). ClickHouse is connected to it as a core server, which exposes its reports as an API and a React frontend using Recharts to present this to the user.
Prerequisites
Get the dataset from http://ocelma.net/MusicRecommendationDataset/lastfm-1K.html and add to the root as dataset folder and unzip.
Getting Started
Provision ClickHouse and the Go Server using the makefile commands.
make provision
and to load the data into Clickhouse
make load-full
Finally, start the frontend server using.
npm run dev
And head to http://localhost:5173/ to view the Insights page where you can search for each artist and view their reports.
Future Scope
Extend to simulate real-time insights like current plays and users.
More artist-specific reports.
Observability via oTel for both app and ClickHouse metrics.
References
http://ocelma.net/MusicRecommendationDataset/lastfm-1K.html
https://clickhouse.com/docs/install/docker
https://clickhouse.com/docs/engines/table-engines/mergetree-family
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A full-stack Last.fm 1k dataset listening insights page for artists using Go/ClickHouse/React
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Languages
Go<br>55.7%
TypeScript<br>34.0%
CSS<br>4.9%
Makefile<br>4.3%
JavaScript<br>0.6%
HTML<br>0.3%
Dockerfile<br>0.2%
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