Files
service_mail/run.py
2017-08-07 16:21:30 +02:00

215 lines
6.9 KiB
Python

from __future__ import unicode_literals
#import imapclient
from config import Config
import sys
#from email.header import decode_header
#import email
import codecs
#import sys
#import bs4
import yaml
#sys.stdout = codecs.getwriter('utf8')(sys.stdout)
from storage.fetch_mail import fetch_mail
from storage.fetch_mail import fetch_threads, flatten_threads
from storage import Mail, MailThread, db_session
#import yaml
#import email
from classifier import get_training_threads, print_answers, in_training, store_training_data, get_pipe, test_pipe, train_single_thread # , pipe2, pipe2b
from flaskapp import app
def predict_thread(p,l,t):
pre=p.predict([t])
print "Status is answered is estimated to be: " + str(l.inverse_transform(pre)[0])
return pre
#print "arg1:"+sys.argv[1]
if len(sys.argv)>1:
if sys.argv[1] == "fetch_threads":
print flatten_threads(fetch_threads())
if sys.argv[1] == "run_server":
app.run(port=3000,debug=True)
if sys.argv[1] == "print_threads":
mth=db_session.query(MailThread).all()
for t in mth:
print t.firstmail
print t.mail_flat_dict()
if sys.argv[1] == "print_thrd":
if len(sys.argv)<3:
mth=db_session.query(MailThread).all()
for t in mth:
print t.firstmail
else:
t=db_session.query(MailThread).filter(MailThread.firstmail==sys.argv[2]).first()
print t.firstmail
print t.subject()
print t.text()
if sys.argv[1] == "compile_threads":
mth=db_session.query(MailThread).all()
for t in mth:
t.compile()
if sys.argv[1] == "print_threads2":
mth=db_session.query(MailThread).all()
for t in mth:
print t.to_text()
print "---------------\n"
if sys.argv[1] == "train_thrd2":
p, le=get_pipe("pipe2", "maintopic")
pb, lb =get_pipe("pipe2b", "maintopic")
train_single_thread(int(sys.argv[2]),p,le,b"maintopic")
if sys.argv[1] == "train_thrd3":
# p, le=get_pipe("pipe2", "maintopic")
pb, lb =get_pipe("pipe2b", "lang")
train_single_thread(int(sys.argv[2]),pb,lb,b"lang")
if sys.argv[1] == "train_all2":
p, labelencoder=train_fit_pipe2()
pb, lb=train_fit_pipe2b()
mth=db_session.query(MailThread).all()
print mth
for t in mth:
if not in_training(t.firstmail,"maintopic"):
print "---------------------------------------------------"
print "---------------------------------------------------"
print t.firstmail
print t.text()
predict_thread(pb,lb,t)
train_single_thread(t.firstmail, p, labelencoder, b"maintopic")
if sys.argv[1] == "benchpipe2":
test_pipe(["pipe2","pipe2b","pipe2c"],"maintopic")
if sys.argv[1] == "testpipe2":
from classifier import ThreadSubjectExtractor, ThreadTextExtractor
pipe2,le=train_fit_pipe2()
if len(sys.argv)>2:
t=db_session.query(MailThread).filter(MailThread.firstmail==sys.argv[2]).first()
print t.to_text()
print le.inverse_transform(pipe2.predict([t]))
if sys.argv[1] == "train_thrd":
pipe1, labelencoder=train_fit_pipe()
train_single_thread(int(sys.argv[2]),pipe1,labelencoder)
if sys.argv[1] == "train_all":
pipe1, labelencoder=train_fit_pipe()
mth=db_session.query(MailThread).all()
print mth
for t in mth:
if not in_training(t.firstmail):
print "---------------------------------------------------"
print "---------------------------------------------------"
print t.firstmail
train_single_thread(t.firstmail,pipe1,labelencoder)
if sys.argv[1] == "print_thread":
mth=db_session.query(MailThread).filter(MailThread.firstmail==int(sys.argv[2])).first()
print mth.mail_dicts()
print mth.mail_flat_dict()
if sys.argv[1] == "store_threads":
thrds=flatten_threads(fetch_threads())
for t in thrds:
if type(t[0]) is int:
th=db_session.query(MailThread).filter(MailThread.firstmail==t[0]).first()
if th == None:
th=MailThread()
th.firstmail=t[0]
if not th.body == yaml.dump(t):
th.body=yaml.dump(t)
th.islabeled=False
th.opened=True
else:
th.body=yaml.dump(t)
db_session.add(th)
db_session.commit()
print thrds
if sys.argv[1] == "print_raw_mail":
mm=db_session.query(Mail).filter(Mail.id==int(sys.argv[2])).first()
print yaml.load(mm.envelope)
if sys.argv[1] == "print_mail":
mm=db_session.query(Mail).filter(Mail.id==int(sys.argv[2])).first()
mm.compile_text()
mm.compile_envelope()
print mm.subject
print "----------"
print mm.text
if sys.argv[1] == "mail_dict_test":
mm=db_session.query(Mail).filter(Mail.id==int(sys.argv[2])).first()
mm.compile_envelope()
print mm.dict_envelope()
if sys.argv[1] == "load_mail":
mm=db_session.query(Mail).filter(Mail.id==int(sys.argv[2])).first()
mm.compile_text()
print mm.text
env=yaml.load(mm.envelope)
print env.subject
print env
if sys.argv[1] == "store_mail":
m=fetch_mail(int(sys.argv[2]))
mm=Mail()
mm.envelope=yaml.dump(m['ENVELOPE'])
mm.body=yaml.dump(m['RFC822'])
mm.id=m['id']
db_session.add(mm)
db_session.commit()
if sys.argv[1] == "fetch_mail":
print "fetching mail %d " % int(sys.argv[2])
m=fetch_mail(int(sys.argv[2]))
hd=decode_header(m['ENVELOPE'].subject)
hd2=[]
# print hd
for h in hd:
if not h[1] is None:
hd2.append(h[0].decode(h[1]))
# print h[0].decode(h[1])
else:
hd2.append(h[0])
print "\nBetreff:"
for h in hd2:
print h
print "FROM:"
for t in m['ENVELOPE'].from_:
print t
print "TO:"
for t in m['ENVELOPE'].to:
print t
em=email.message_from_string(m['RFC822'])
for p in em.walk():
if p.get_content_maintype()=="text":
print p.get_payload()
elif p.get_content_maintype()=="multipart":
print p.get_payload()
else:
print p.get_content_maintype()
if sys.argv[1] == "initdb":
from storage import init_db
init_db()