def main():
parser = argparse.ArgumentParser()
parser.add_argument("--verbose",
help="print logging messages to stdout",
action="store_true")
parser.add_argument("--progress",
help="print a progress bar",
action="store_true")
subparsers = parser.add_subparsers(dest="command")
subparsers.add_parser(
"train", help="train the tagger from standard notmuch database")
subparsers.add_parser("tag", help="tag the mails with a new-tag")
subparsers.add_parser(
"validate",
help=
"show a classification report on stdout when trained on 0.6 of the maildir and tested on the other 0.4."
)
args = parser.parse_args()
db = Database()
path = db.get_path()
db.close()
filename = os.path.join(path, "blaecksprutte.db")
warnings.simplefilter('ignore', UndefinedMetricWarning)
level = logging.ERROR
if args.verbose:
level = logging.INFO
log = logging.getLogger(__name__)
out_hdlr = logging.StreamHandler(sys.stdout)
out_hdlr.setFormatter(logging.Formatter('%(message)s'))
out_hdlr.setLevel(level)
log.addHandler(out_hdlr)
log.setLevel(level)
if args.command == 'train':
v, b, c = train_from_bottom(log, args.progress)
with open(filename, 'wb') as f:
pickle.dump([v, b, c], f, pickle.HIGHEST_PROTOCOL)
if args.command == 'tag':
tag_new_mails(filename, log)
if args.command == 'validate':
validate(log, args.progress)
def cmd_new(self):
"""Run 'notmuch new'"""
#get the database directory
db = Database(mode=Database.MODE.READ_WRITE)
path = db.get_path()
print self._add_new_files_recursively(path, db)
def cmd_new(self):
"""Run 'notmuch new'"""
#get the database directory
db = Database(mode=Database.MODE.READ_WRITE)
path = db.get_path()
print self._add_new_files_recursively(path, db)
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--verbose",
help="print logging messages to stdout",
action="store_true")
parser.add_argument("--progress",
help="print a progress bar",
action="store_true")
subparsers = parser.add_subparsers(dest="command")
subparsers.add_parser(
"train", help="train the tagger from standard notmuch database")
subparsers.add_parser("tag", help="tag the mails with a new-tag")
subparsers.add_parser(
"validate",
help=
"show a classification report on stdout when trained on 0.6 of the maildir and tested on the other 0.4."
)
subparsers.add_parser(
"optimize",
help=
"perform a grid search with 60 different possible hyperparameters to find the best ones"
)
args = parser.parse_args()
db = Database()
path = db.get_path()
db.close()
model_filename = os.path.join(path, "blaecksprutte.db")
pipeline_filename = os.path.join(path, "best_pipeline.db")
warnings.simplefilter('ignore', UndefinedMetricWarning)
warnings.simplefilter('ignore', FutureWarning)
warnings.simplefilter('ignore', UserWarning)
level = logging.ERROR
if args.verbose:
level = logging.INFO
log = logging.getLogger(__name__)
out_hdlr = logging.StreamHandler(sys.stdout)
out_hdlr.setFormatter(logging.Formatter('%(message)s'))
out_hdlr.setLevel(level)
log.addHandler(out_hdlr)
log.setLevel(level)
if args.command == 'train':
train(log, pipeline_filename, model_filename, args.progress)
if args.command == 'tag':
if not os.path.isfile(model_filename):
log.warn(
"no existing model file found: training model. This may take some time!"
)
train(log, pipeline_filename, model_filename, args.progress)
tag_new_mails(model_filename, log)
if args.command == 'validate':
validate(log, pipeline_filename, args.progress)
if args.command == 'optimize':
optimize(log, pipeline_filename, args.progress)
