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# This module is part of the Divmod project and is Copyright 2003 Amir Bakhtiar:
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# amir@divmod.org. This is free software; you can redistribute it and/or
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# modify it under the terms of version 2.1 of the GNU Lesser General Public
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# License as published by the Free Software Foundation.
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from rfc822 import AddressList
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from reverend.thomas import Bayes
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from reverend.splitter import Splitter
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class EmailClassifier(Bayes):
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def getTokens(self, msg):
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# This should return a list of strings
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# which will be used as the key into
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# the table of token counts
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tokens = self.getHeaderTokens(msg)
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tokens += self.getBodyTokens(msg)
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# Get some tokens that are generated from the
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# header and the structure
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tokens += self.getMetaTokens(msg)
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def getBodyTokens(self, msg):
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text = self.getTextPlain(msg)
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tl = self.splitter.split(text)
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def getHeaderTokens(self, msg):
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subj = msg.get('subject','nosubject')
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text += msg.get('from','fromnoone') + ' '
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text += msg.get('to','tonoone') + ' '
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text += msg.get('cc','ccnoone') + ' '
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tl = self.splitter.split(text)
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def getTextPlain(self, msg):
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for part in msg.walk():
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if typ and typ.lower() == "text/plain":
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text = part.get_payload(decode=True)
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def getTextHtml(self, msg):
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for part in msg.walk():
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if typ and typ.lower() == "text/html":
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text = part.get_payload(decode=False)
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def getMetaTokens(self, msg):
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for f in ['Content-type', 'X-Priority', 'X-Mailer',
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'content-transfer-encoding', 'X-MSMail-Priority']:
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r.append(f +':' + msg.get(f, 'None'))
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text = self.getTextPlain(msg)
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html = self.getTextHtml(msg)
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for stem, part in zip(['text','html'],[text,html]):
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r.append(stem + '_None')
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r.append(stem + '_True')
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at = AddressList(t).addresslist
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ac = AddressList(c).addresslist
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r.append('to_more_than_5')
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r.append('to_more_than_10')
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r.append('cc_more_than_5')
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r.append('cc_more_than_10')
added
removed
Reverend/reverend/guessers/email.py
