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Output Files

Artist Scraper generates two output files after each scrape.

artists.csv

The main output file containing all artists with MusicBrainz IDs.

Format

CSV file with four columns:

Column Description Example
Artist Name The artist's name Taylor Swift
MusicBrainz ID Unique ID (prefixed with lidarr:) lidarr:20244d07-534f-4eff-b4d4-930878889970
Source Where the artist was found Spotify, YouTube Music, or both
Play Count Number of tracks by this artist 45

Example

Artist Name,MusicBrainz ID,Source,Play Count
Taylor Swift,lidarr:20244d07-534f-4eff-b4d4-930878889970,Spotify,45
The Beatles,lidarr:b10bbbfc-cf9e-42e0-be17-e2c3e1d2600d,"Spotify, YouTube Music",23
Radiohead,lidarr:a74b1b7f-71a5-4011-9441-d0b5e4122711,YouTube Music,12
Ed Sheeran,lidarr:b8a7c51f-362c-4dcb-a259-bc6e0095f0a6,Spotify,8

Field Details

Artist Name

  • The artist's name as it appears in Spotify/YouTube Music
  • May include variations (e.g., "The Beatles" vs "Beatles")
  • Unicode characters are preserved

MusicBrainz ID

  • Format: lidarr: + MusicBrainz UUID
  • The lidarr: prefix is required by Lidarr's import format
  • Can be used to look up the artist on musicbrainz.org
  • Example URL: https://musicbrainz.org/artist/20244d07-534f-4eff-b4d4-930878889970

Source

  • Spotify - Found only in Spotify
  • YouTube Music - Found only in YouTube Music
  • Spotify, YouTube Music - Found in both sources

Helps identify: - Which platform you use most for an artist - Artists unique to one platform - Cross-platform favorites

Play Count

  • Total number of tracks by this artist in your library
  • Includes:
    • Liked tracks
    • Tracks in playlists
    • Albums by followed artists (Spotify)
  • Useful for:
    • Filtering with --min-plays
    • Identifying your most-listened artists
    • Prioritizing imports to Lidarr

skipped_artists.log

A log file containing artists that couldn't be matched to MusicBrainz IDs.

Format

Plain text file with one artist name per line:

Unknown Artist Name
Artist With Typo
很新艺人 (New Artist in Chinese)

Why Artists are Skipped

Artists may be skipped for several reasons:

  1. Not in MusicBrainz Database

    • Very new/emerging artists
    • Local/regional artists
    • Artists with limited online presence

  2. Name Variations

    • Different spellings
    • Special characters
    • Language differences

  3. Fuzzy Match Threshold

    • Match quality below 90% threshold
    • Multiple possible matches with low confidence

  4. Parsing Errors (YouTube Music)

    • Couldn't extract artist from video title
    • Non-music content (podcasts, audiobooks)
    • Unusual title format

Using the Skip Log

  1. Review the log: 

    cat skipped_artists.log

  2. Manually search for important artists:

  3. Add to CSV manually: 

    Skipped Artist,lidarr:MBID-HERE,Spotify,10

  4. Re-import: 

    artistscraper import artists.csv

Customizing Output Paths

Via Configuration File

Edit config.json:

{
  "output": {
    "csv_file": "my_artists.csv",
    "skipped_log": "my_skipped.log"
  }
}

Via Command Line

Override the CSV path for a single run:

artistscraper scrape --output custom_output.csv

The skip log will be named based on your config file setting.

File Locations

By default, files are created in the current directory:

./artists.csv
./skipped_artists.log

You can use absolute or relative paths:

{
  "output": {
    "csv_file": "/path/to/output/artists.csv",
    "skipped_log": "/path/to/output/skipped.log"
  }
}

Handling Existing Files

Artist Scraper overwrites existing files without warning.

To preserve previous scrapes:

Option 1: Custom Output Path

artistscraper scrape --output artists_$(date +%Y%m%d).csv

Option 2: Move Before Scraping

mv artists.csv artists_backup.csv
artistscraper scrape

Option 3: Version in Config

Update your config before each scrape:

{
  "output": {
    "csv_file": "artists_v2.csv",
    "skipped_log": "skipped_v2.log"
  }
}

Importing to Other Tools

Excel/Google Sheets

Both Excel and Google Sheets can open CSV files directly:

  • Excel: File → Open → Select CSV
  • Google Sheets: File → Import → Upload CSV

Python/Pandas

import pandas as pd

df = pd.read_csv('artists.csv')
print(df.head())

SQL Database

LOAD DATA INFILE '/path/to/artists.csv'
INTO TABLE artists
FIELDS TERMINATED BY ','
ENCLOSED BY '"'
LINES TERMINATED BY '\n'
IGNORE 1 ROWS;

Custom Scripts

The CSV format is standard and can be parsed by any programming language.

Next Steps