These are my scripts for optimizing work process with music distribution companies, which provide big monthly/quarterly reports for your account. In case you are a label, like me, chances are that you have multiple artists distributed via your account, and you need to send them separate reports and figure out how much to pay them. These scripts are quite simple, but useful tools for exactly that.
NEW: Now there is an example below for usage with Bandcamp sales reports
You need pandas in order to use these scripts. You can install it via pip
$ pip install pandas
or use a distribution like anaconda and use the provided Jupyter notebook
$ python3 report_split.py -h
usage: report_split.py [-h] -p PREFIX -f FILE
optional arguments:
-h, --help show this help message and exit
-p PREFIX, --prefix PREFIX
prefix for generated reports (folder name and prefix in filename)
-f FILE, --file FILE csv file path
-ac ARTIST, --artist-column ARTIST
artist column name (default "Artist")
-e ENCODING, --encoding ENCODING
csv file encoding (default "utf8, but bandcamp needs "utf-16")
$ python3 report_sum.py -h
usage: report_sum.py [-h] -f FILE
optional arguments:
-h, --help show this help message and exit
-f FILE, --file FILE csv file path
-ac ARTIST, --artist-column ARTIST
artist column name (default "Artist")
-rc REVENUE, --revenue-column REVENUE
revenue column name (default "Net Revenue in USD")
-e ENCODING, --encoding ENCODING
csv file encoding (default "utf8, but bandcamp needs "utf-16")
If you are not using the same distributor and/or report schema and your columns have different names - each script has those column names available as optional arguments, so you can easily customize it as it suits you
For Bandcamp the arguments would be:
$ python3 report_sum.py -ac artist -rc "net amount" -e utf-16 -f data.csv