mirror of
https://github.com/agresdominik/predictify.git
synced 2026-04-21 09:51:56 +00:00
Chris Kiriakou
58 lines
2.1 KiB
Markdown
58 lines
2.1 KiB
Markdown
# Predictify
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## Overview
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A Data analysis tool to scrape your Spotify History usage and let a ML-Model predict your next songs
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## Authentication API
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[Official Documentation](https://developer.spotify.com/documentation/web-api/tutorials/getting-started)
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[Authorization Code Flow](https://developer.spotify.com/documentation/web-api/tutorials/code-flow)
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## Usable possible APIs
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Recently Played Tracks: `/me/player/recently-played` [Official Spotify Documentation](https://developer.spotify.com/documentation/web-api/reference/get-recently-played)
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Get Track: `/tracks/{id}` [Official Spotify Documentation](https://developer.spotify.com/documentation/web-api/reference/get-track)
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Get Track's Audio Features _(Deprecated)_: `/audio-features/{id}` [Official Spotify Documentation](https://developer.spotify.com/documentation/web-api/reference/get-audio-features)
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Get Track's Audio Analysis _(Deprecated)_: `/audio-analysis/{id}` [Official Spotify Documentation](https://developer.spotify.com/documentation/web-api/reference/get-audio-analysis)
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Get Artist: `/artists/{id}` [Official Spotify Documentation](https://developer.spotify.com/documentation/web-api/reference/get-an-artist)
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## Docker usage
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`cd` inside the projects directory:
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```sh
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cd predictify
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```
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To run predictify inside a container, first make sure to build the image:
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```sh
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make dockerfile
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```
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Create a seperate data directory (e.g. `data-docker`):
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```sh
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mkdir data-docker
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```
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> [!NOTE]
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> To detatch the container to run it in the background add the `--detach` directly after the `run` command.
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Then run the following docker command, to run the container in the foreground:
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```sh
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docker run \
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--name predictify \
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--network=host \
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--volume $(pwd)/data-docker:/app/predictify/data \
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--volume $(pwd)/config:/app/predictify/config \
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predictify:unstable
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```
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## GDPR Data
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If you have gdpr data, create a folder: ```data/gdpr_data``` and add all .json files containing your play history into it. In order to extract it, run the script: ```python3 src/runtime.py --export```
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## Authors
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[Chris Kiriakou](https://github.com/ckiri)
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[Dominik Agres](https://github.com/agresdominik)
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