Navidrome_love_to_ListenBrainz

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Navidrome_love_to_ListenBrainz

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A Python script to synchronize your loved songs from navidrome to listenbrainz.org

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# Navidrome_love_to_ListenBrainz
A Python script to synchronize your loved songs from your Navidrome database to your ListenBrainz.org profile.
A maintenance script to run at your discretion, updating loved songs in Navidrome. This is necessary because loved songs do not sync automatically, even when Navidrome and ListenBrainz are configured to sync scrobbles.

## Important Note

Syncing loved tracks to ListenBrainz requires that each song in your Navidrome database has a valid `mbz_recording_id` from MusicBrainz.

To ensure this:

1. Import song metadata from MusicBrainz, for example using [MusicBrainz Picard](https://picard.musicbrainz.org/).
2. Perform a full scan of your Navidrome database so that the `mbz_recording_id` values are written and updated in the database.

Without the  `mbz_recording_id` attribute loved data will not sync correctly with ListenBrainz.

## Description

The script connects to your Navidrome database and retrieves all tracks you’ve marked as “loved” within the specified date range (`START_DATE` to `END_DATE`). It loops through each track, extracting essential metadata such as the recording MBID, artist name, track title, and album. Tracks without a valid MusicBrainz Recording MBID are skipped to ensure that only recognized recordings are submitted to ListenBrainz.

For each valid track, the script sends a POST request to the ListenBrainz API with your user token, marking the track as “loved” on your ListenBrainz profile. To handle network issues or temporary API failures, the script includes a retry mechanism, attempting each request up to three times with a short delay between attempts. Progress and errors are logged to the console, and a summary is maintained for skipped or failed tracks, allowing users to review and troubleshoot any issues.

## How It Works

1. **Retrieve Loved Tracks**  
   The script queries your Navidrome database for tracks marked as “loved” within the specified `START_DATE` and `END_DATE`. Each track’s metadata—recording MBID, artist, title, and album—is extracted for submission.

2. **Validate Tracks**  
   Tracks without a valid MusicBrainz Recording MBID are skipped, ensuring that only recognized recordings are sent to ListenBrainz.

3. **Submit to ListenBrainz**  
   Each valid track is sent to the ListenBrainz API via a POST request with your user token. A retry mechanism attempts each request up to three times in case of temporary network or API failures, with a short delay between attempts.

4. **Logging and Summary**  
   Successful submissions are logged as “Loved,” while skipped or failed tracks are tracked in a summary for review. This provides transparency and allows troubleshooting of any issues.

## Configure the following variables

| Name                 | Description                                                                                                     | Suggested Value                     |
|----------------------|-----------------------------------------------------------------------------------------------------------------|------------------------------------|
| `DB_PATH`            | Path to your Navidrome database file                                                                            | `/path/to/navidrome.db`            |
| `LISTENBRAINZ_TOKEN` | Your ListenBrainz API token (see [ListenBrainz API docs](https://listenbrainz.readthedocs.io/en/latest/users/api/index.html)) | `YOUR_TOKEN_HERE`                  |
| `START_DATE`         | Starting date limit to avoid uploading all likes every time. Can be the date of the latest execution           | `"2025-01-01"`                     |
| `END_DATE`           | Ending date limit. Can be the date of the current execution                                                    | `"2026-01-15"`                     |

## Execute the script

```bash
python3 love_tracks_listenbrainz.py

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