51 lines
1.7 KiB
Python
51 lines
1.7 KiB
Python
# -*- coding: utf-8 -*-
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from ... import *
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import os
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from PyML import SparseDataSet
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from talon.signature.learning import dataset as d
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from talon.signature.learning.featurespace import features
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def test_is_sender_filename():
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assert_false(d.is_sender_filename("foo/bar"))
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assert_false(d.is_sender_filename("foo/bar_body"))
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ok_(d.is_sender_filename("foo/bar_sender"))
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def test_build_sender_filename():
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eq_("foo/bar_sender", d.build_sender_filename("foo/bar_body"))
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def test_parse_msg_sender():
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sender, msg = d.parse_msg_sender(EML_MSG_FILENAME)
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# if the message in eml format
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with open(EML_MSG_FILENAME) as f:
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eq_(sender,
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" Alex Q <xxx@yahoo.com>")
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eq_(msg, f.read())
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# if the message sender is stored in a separate file
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sender, msg = d.parse_msg_sender(MSG_FILENAME_WITH_BODY_SUFFIX)
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with open(MSG_FILENAME_WITH_BODY_SUFFIX) as f:
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eq_(sender, u"john@example.com")
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eq_(msg, f.read())
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def test_build_extraction_dataset():
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if os.path.exists(os.path.join(TMP_DIR, 'extraction.data')):
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os.remove(os.path.join(TMP_DIR, 'extraction.data'))
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d.build_extraction_dataset(os.path.join(EMAILS_DIR, 'P'),
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os.path.join(TMP_DIR,
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'extraction.data'), 1)
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test_data = SparseDataSet(os.path.join(TMP_DIR, 'extraction.data'),
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labelsColumn=-1)
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# the result is a loadable signature extraction dataset
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# 32 comes from 3 emails in emails/P folder, 11 lines checked to be
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# a signature, one email has only 10 lines
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eq_(test_data.size(), 32)
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eq_(len(features('')), test_data.numFeatures)
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