blaecksprutte is a tagging script, that works on notmuch databases. you have to train blaecksprutte on your notmuch database, with already tagged emails. from this corpus blaecksprutte learns for which emails you use which tags and tags your mails for you. for now, blaecksprutte can only operate on the default notmuch database on your system. configuration is not possible.
blaecksprutte uses scikit-learn and the notmuch python api. make sure, you have installed both of them. also the progressbar package of python is used.
to train your personal email tagger use:
python blaecksprutte.py trainthe trained model is stored in your maildir in 'blaecksprutte.db'
you can check, how well the classifier can perform on your mails. when you use:
python blaecksprutte.py validatethe classifier is trained on 0.6 of your mails and tested on the other 0.4. a classification report with precision, recall and f1-score for every tag is printed to stdout.
blaecksprutte searches 90 combinations of 3 hyperparameters for the best fitting parameters on your dataset. this is done automatically before your first training run. you can choose the best parameters manually with:
python blaecksprutte.py optimizeblaecksprutte searches for all emails containing the 'new' tag and calculates probable tags for these emails. the new tag is removed. for tagging your emails use:
python blaecksprutte.py tagyou should be able to add to your notmuch command line as in for example:
watch -n 180 "mbsync -a && notmuch new && python blaecksprutte.py tag"please contact me or write me issuse and send patches. input of any kind is welcome :)