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Remove duplicated iTunes song files from your computer

Project description

unduplicate-itunes

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Moves duplicate song files from your iTunes music directory to the trash.

iTunes doesn't automatically remove missing songs, so after you use this package to delete them, follow these instructions.

Depending on the structure of your iTunes music directory, it's possible that some duplicate files will be untouched while their original counterparts will be deleted instead (e.g. song.mp4 is removed, song 1.mp4 survives). Although, duplicates and originals look identical in iTunes regardless so this problem only matters if you care about the file names.

Behavior

  • You are prompted to make a backup of your iTunes music directory before executing. Even if you don't, you can still restore your files from the trash after the script is finished.
  • You are prompted with the number of duplicates to be removed before executing.
  • Directories (usually albums folders) that only contain duplicate files will be moved to the trash.
  • A log file of all actions is output once the script finishes. It is created in whatever cd you have your terminal set to.

Install (PyPi)

pip install unduplicate-itunes

Usage

Using remove_by_artist_and_title.py

cd into any directory (the log file will be dumped here)

python
from unduplicate_itunes import remove_by_artist_and_title as undup
undup.main()

When you are prompted to enter the iTunes music directory, you can find the path by right clicking on any song in iTunes and select Show in Windows Explorer or Show in Finder (macOS). Grab the root folder that contains all the artist folders.

There are other scripts included that try to find duplicates by other methods but they are unfinished and aren't as effective at finding all duplicates.

Cleanup iTunes songs

Once the files are trashed, you can remove the dead songs from iTunes using these instructions here.

Project details


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Source Distribution

unduplicate_itunes-1.0.2.tar.gz (5.8 kB view hashes)

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unduplicate_itunes-1.0.2-py3-none-any.whl (8.1 kB view hashes)

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