Announcing iProtal, automatically retrieves and manages genre for iTunes song

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I was tired of maintaining my huge collection of iTunes mp3 of Metal and Progressive Rock/Metal songs. In particular I was tired of typing the genre of all the artists in my Libary. Therefore, I decided to write a Python program for Mac OS X that for the currently selected songs in iTunes (or the whole Library), is able to connect to some websites, retrieve the correct genre and store it.
Moreover, I wanted my program to be completely automatic (no user interaction) and able to handle cases in which more than one genre is found.

iProtal update iTunes genre

iProtal is able to handle all of this. When multiple genres are found for some tracks, it delays their processing and continues with the other tracks. When it finished processing the tracks, it asks the user which genre is the right one for those with more than one genre found.

iProtal Multiple Genres found

The program currently works for songs for the genres of Metal and Progressive (Rock, Metal), because it is able to look at Enciclopaedia Metallum and Progarchives.
Did I mention that it comes for free? It is also opensource and I would be very happy to see people join me to improve it.

The program is in a very initial stage but correctly works on my Macbook Pro. I would be very happy if you help me to find errors and bugs.

More information (and download) available on the project page.

About the author

dgraziotin

Dr. Daniel Graziotin is a senior researcher (Akademischer Rat) at the University of Stuttgart, Germany. His research interests include human, behavioral, and psychological aspects of empirical software engineering, studies of science, and open science. He is associate editor at the Journal of Open Research Software and academic editor at the Research Ideas and Outcomes (RIO) journal. Daniel was awarded an Alexander von Humboldt Fellowship for postdoctoral researchers in 2017, the European Design Award (bronze) in 2016, and the Data Journalism Award in 2015. He received his Ph.D. in computer science at the Free University of Bozen-Bolzano, Italy.

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About Author

dgraziotin

Dr. Daniel Graziotin is a senior researcher (Akademischer Rat) at the University of Stuttgart, Germany. His research interests include human, behavioral, and psychological aspects of empirical software engineering, studies of science, and open science. He is associate editor at the Journal of Open Research Software and academic editor at the Research Ideas and Outcomes (RIO) journal. Daniel was awarded an Alexander von Humboldt Fellowship for postdoctoral researchers in 2017, the European Design Award (bronze) in 2016, and the Data Journalism Award in 2015. He received his Ph.D. in computer science at the Free University of Bozen-Bolzano, Italy.