Bloodstock Reviser

Every year, knowing which bands to watch at Bloodstock requires studious, meticulous revision, taking hours of time and planning.

In order to speed this process up, to create a shortlist for deeper revision, this project provides a pipeline of tools that:

• Mine the Bloodstock website for all bands performing in the current line up
• Decorate that data with Spotify-based preview audio clips and genres
• Present the final data as a web UI allowing browsing of the artists and listening to the previews

Pipeline

Artists performing

Scrapy has been used to create a custom spider to crawl the https://www.bloodstock.uk.com/events/boa-2022/stages. This can be run as follows:

scrapy crawl bands -O bands.json

This will output bands.json

Spotify previews

The Spotify genres/previews is run as follows and assumes bands.json as input:

python spotify.py

This will output bands_final.json. A client ID and secret is required at Spotify to run this, using the Client Credentials auth flow.

Web page

The HTML file is created as follows and assumes bands_final.json as input:

python html.py

This will output boa-revision.html which can be opened in a local web browser. Strap in for a truly 1999 UI experience, this was not the point at this stage.

Improvements

• Structure the data into stages and order by date
• Enhance the UI (React + Bootstrap or Material or Tailwind) to provide a better experience e.g. filtering, type-down search, inline audio preview and a nicer look
• Create a script that runs the entire pipeline end to end for a given year, possibly deploying out to public web for others to use