def print_message_score(msg_name, msg_fp):
msg = email.message_from_file(msg_fp)
bayes = CdbClassifier(open(DB_FILE, 'rb'))
prob, evidence = bayes.spamprob(tokenize(msg), evidence=True)
print msg_name, prob
for word, prob in evidence:
print ' ', repr(word), prob
def filter_message(hamdir, spamdir):
signal.signal(signal.SIGALRM, lambda s, f: sys.exit(1))
signal.alarm(24 * 60 * 60)
tmpfile, pathname, filename = maketmp(hamdir)
try:
tmpfile.write(os.environ.get("DTLINE", "")) # delivered-to line
bytes = 0
blocks = []
while 1:
block = sys.stdin.read(BLOCK_SIZE)
if not block:
break
bytes += len(block)
if bytes < SIZE_LIMIT:
blocks.append(block)
tmpfile.write(block)
tmpfile.close()
if bytes < SIZE_LIMIT:
msgdata = ''.join(blocks)
del blocks
msg = email.message_from_string(msgdata)
del msgdata
bayes = CdbClassifier(open(DB_FILE, 'rb'))
prob = bayes.spamprob(tokenize(msg))
else:
prob = 0.0
if prob > SPAM_CUTOFF:
os.rename(pathname, "%s/new/%s" % (spamdir, filename))
else:
os.rename(pathname, "%s/new/%s" % (hamdir, filename))
except:
os.unlink(pathname)
raise
def filter_message(hamdir, spamdir):
signal.signal(signal.SIGALRM, lambda s, f: sys.exit(1))
signal.alarm(24 * 60 * 60)
# write message to temporary file (must be on same partition)
tmpfile, pathname, filename = maketmp(hamdir)
try:
tmpfile.write(os.environ.get("DTLINE", "")) # delivered-to line
bytes = 0
blocks = []
while 1:
block = sys.stdin.read(BLOCK_SIZE)
if not block:
break
bytes += len(block)
if bytes < SIZE_LIMIT:
blocks.append(block)
tmpfile.write(block)
tmpfile.close()
if bytes < SIZE_LIMIT:
msgdata = ''.join(blocks)
del blocks
msg = email.message_from_string(msgdata)
del msgdata
bayes = CdbClassifier(open(DB_FILE, 'rb'))
prob = bayes.spamprob(tokenize(msg))
else:
prob = 0.0
if prob > SPAM_CUTOFF:
os.rename(pathname, "%s/new/%s" % (spamdir, filename))
else:
os.rename(pathname, "%s/new/%s" % (hamdir, filename))
except:
os.unlink(pathname)
raise
