def test_annotations(self):
tm = TemplateMaker(self.PAGE)
tm.annotate("field1", best_match("text to annotate"), best_match=False)
annotations = [x[0] for x in tm.annotations()]
self.assertEqual(
annotations, [{u"annotations": {u"content": u"field1"}}, {u"annotations": {u"content": u"field1"}}]
)
def test_annotations(self):
tm = TemplateMaker(self.PAGE)
tm.annotate('field1', best_match('text to annotate'), best_match=False)
annotations = [x[0] for x in tm.annotations()]
self.assertEqual(annotations,
[{u'annotations': {u'content': u'field1'}},
{u'annotations': {u'content': u'field1'}}])
def test_annotate_multiple(self):
tm = TemplateMaker(self.PAGE)
tm.annotate('field1', best_match('text to annotate'), best_match=False)
tpl = tm.get_template()
ex = InstanceBasedLearningExtractor([(tpl, None)])
self.assertEqual(ex.extract(self.PAGE)[0],
[{u'field1': [u'Some text to annotate here', u'Another text to annotate there']}])
def test_annotate_ignore_unpaired(self):
tm = TemplateMaker(self.PAGE)
tm.annotate('field1', best_match("and that's"), best_match=False)
tpl = tm.get_template()
ex = InstanceBasedLearningExtractor([(tpl, None)])
self.assertEqual(ex.extract(self.PAGE)[0],
[{u'field1': [u"More text with unpaired tag <img />and that's it"]}])
def test_annotations(self):
tm = TemplateMaker(self.PAGE)
tm.annotate('field1', best_match('text to annotate'), best_match=False)
annotations = [x[0] for x in tm.annotations()]
self.assertEqual(annotations,
[{u'annotations': {u'content': u'field1'}},
{u'annotations': {u'content': u'field1'}}])
def test_annotate_ignore_unpaired(self):
tm = TemplateMaker(self.PAGE)
tm.annotate('field1', best_match("and that's"), best_match=False)
tpl = tm.get_template()
ex = InstanceBasedLearningExtractor([(tpl, None)])
self.assertEqual(ex.extract(self.PAGE)[0],
[{u'field1': [u"More text with unpaired tag <img />and that's it"]}])
def test_annotate_multiple(self):
tm = TemplateMaker(self.PAGE)
tm.annotate('field1', best_match('text to annotate'), best_match=False)
tpl = tm.get_template()
ex = InstanceBasedLearningExtractor([(tpl, None)])
self.assertEqual(ex.extract(self.PAGE)[0],
[{u'field1': [u'Some text to annotate here', u'Another text to annotate there']}])
def test_annotate_multiple(self):
tm = TemplateMaker(self.PAGE)
tm.annotate("field1", best_match("text to annotate"), best_match=False)
tpl = tm.get_template()
ex = InstanceBasedLearningExtractor([tpl])
self.assertEqual(
ex.extract(self.PAGE)[0], [{u"field1": [u"Some text to annotate here", u"Another text to annotate there"]}]
)
def train_from_htmlpage(self, htmlpage, data):
assert data, "Cannot train with empty data"
tm = TemplateMaker(htmlpage)
for field, values in data.items():
if (isinstance(values, (bytes, str)) or
not hasattr(values, '__iter__')):
values = [values]
for value in values:
value = str_to_unicode(value, htmlpage.encoding)
tm.annotate(field, best_match(value))
self.add_template(tm.get_template())
def train_from_htmlpage(self, htmlpage, data):
assert data, "Cannot train with empty data"
tm = TemplateMaker(htmlpage)
for field, values in data.items():
if not hasattr(values, '__iter__'):
values = [values]
for value in values:
if isinstance(value, str):
value = value.decode(htmlpage.encoding or 'utf-8')
tm.annotate(field, best_match(value))
self.add_template(tm.get_template())
def train_from_htmlpage(self, htmlpage, data):
assert data, "Cannot train with empty data"
tm = TemplateMaker(htmlpage)
for field, values in data.items():
if (isinstance(values, (bytes, str))
or not hasattr(values, '__iter__')):
values = [values]
for value in values:
value = str_to_unicode(value, htmlpage.encoding)
tm.annotate(field, best_match(value))
self.add_template(tm.get_template())
def train(self, url=None, data=None, html=None, encoding='utf-8'):
assert data, "Cannot train with empty data"
page = self._get_page(url, encoding, html)
tm = TemplateMaker(page)
for field, values in data.items():
if not hasattr(values, '__iter__'):
values = [values]
for value in values:
if isinstance(value, str):
value = value.decode(encoding)
tm.annotate(field, best_match(value))
self.templates.append(tm.get_template())
def train(self, url=None, data=None, html=None, encoding='utf-8'):
assert data, "Cannot train with empty data"
page = self._get_page(url, encoding, html)
tm = TemplateMaker(page)
for field, values in data.items():
if not hasattr(values, '__iter__'):
values = [values]
for value in values:
if isinstance(value, str):
value = value.decode(encoding)
tm.annotate(field, best_match(value))
self.templates.append(tm.get_template())
def test_annotate_fragment_already_annotated(self):
tm = TemplateMaker(self.PAGE)
tm.annotate("field1", best_match("text to annotate"))
self.assertRaises(FragmentAlreadyAnnotated, tm.annotate, "field1", best_match("text to annotate"))
def test_annotate_fragment_already_annotated(self):
tm = TemplateMaker(self.PAGE)
tm.annotate('field1', best_match('text to annotate'))
self.assertRaises(FragmentAlreadyAnnotated, tm.annotate, 'field1', best_match("text to annotate"))
