https://github.com/pavelkomarov/exportify

Export Spotify playlists using the Web API. Analyze them in the Jupyter notebook.
https://github.com/pavelkomarov/exportify

data-analysis github-pages-website javascript javascript-promise jupyter-notebook spotify spotify-api spotify-web-api

Last synced: about 1 month ago
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Export Spotify playlists using the Web API. Analyze them in the Jupyter notebook.

• Host: GitHub
• URL: https://github.com/pavelkomarov/exportify
• Owner: pavelkomarov
• License: mit
• Created: 2019-06-21T13:58:48.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2025-04-08T21:34:02.000Z (about 2 months ago)
• Last Synced: 2025-04-12T11:12:33.480Z (about 1 month ago)
• Topics: data-analysis, github-pages-website, javascript, javascript-promise, jupyter-notebook, spotify, spotify-api, spotify-web-api
• Language: Jupyter Notebook
• Homepage: https://exportify.net
• Size: 8.44 MB
• Stars: 278
• Watchers: 4
• Forks: 29
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • Funding: .github/FUNDING.yml
  • License: LICENSE

Awesome Lists containing this project

README

        

[![Build Status](https://github.com/pavelkomarov/exportify/actions/workflows/deploy.yml/badge.svg)](https://github.com/pavelkomarov/exportify/actions)

[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/pavelkomarov/exportify/master)

Export your Spotify playlist metadata for analysis or just safekeeping: [exportify.net](https://exportify.net)



### Export Format

Playlist data is exported in [CSV](http://en.wikipedia.org/wiki/Comma-separated_values) format with the following fields:

- [Track URI](https://developer.spotify.com/documentation/web-api/concepts/spotify-uris-ids)

- Track Name

- Album Name

- Artist Name(s)

- Release Date

- Duration (ms)

- Popularity

- Added By

- Added At

- Genres

- Record Label

- Danceability

- Energy

- Key

- Loudness

- Mode (Major or Minor)

- Speechiness

- Acousticness

- Instrumentalness

- Liveness

- Valence

- Tempo

- Time Signature

### Analysis

Run the [Jupyter Notebook](https://github.com/pavelkomarov/exportify/blob/master/taste_analysis.ipynb) or [launch it in Binder](https://mybinder.org/v2/gh/pavelkomarov/exportify/master) to get a variety of plots about the music in a playlist including:

- Most common artists

- Most common genres

- Release date distribution

- Popularity distribution

- Your songs' distributions of Acousticness, Valence, etc.

- Time signatures and keys

- All songs plotted in 2D to indicate relative similarities

### Development

Most of the interesting logic that communicates with the Spotify Web API happens in Javascript in `exportify.js`. I've left many detailed code comments and tried to structure it as rationally as I can, so take a look. The webpage skin and a few action bindings are defined in `index.html`.

To experiment with changes, run a local web server. For example, using Python (in the Exportify repo dir):

```bash

python3 -m http.server

```

Then open [http://localhost:8000](http://localhost:8000). The Javascript can be invoked by interacting with this locally-served webpage.

Data science stuff is written with Python in `taste_analysis.ipynb`, which you can run with `python3 -m notebook`, then navigating to [http://localhost:8888](http://localhost:8888).

### Contributing

1. Fork it

2. Create your feature branch (`git checkout -b my-new-feature`)

3. Commit your changes (`git commit -m "message"`)

4. Push to the branch (`git push origin my-new-feature`)

5. Create a new Pull Request