def parse_data(cls, title, body, itemtype=u'Article'):
body = body.replace('\r\n', '\n')
default_data = {
'name': title,
'schema': schema.get_itemtype_path(itemtype)
}
# collect
yaml_data = cls.parse_schema_yaml(body)
body_data = pairs_to_dict((m.group('name'), m.group('value'))
for m in re.finditer(cls.re_data, body))
if itemtype == u'Article' or u'Article' in schema.get_schema(
itemtype)[u'ancestors']:
default_section = u'articleBody'
else:
default_section = u'longDescription'
section_data = cls.parse_sections(body, default_section)
# merge
data = merge_dicts([default_data, yaml_data, body_data, section_data])
# validation and type conversion
typed = schema.SchemaConverter.convert(itemtype, data)
return typed
def parse_data(cls, title, body, itemtype=u'Article'):
# collect data
default_data = {'name': title, 'schema': schema.get_itemtype_path(itemtype)}
yaml_data = cls.parse_schema_yaml(body)
body_data = pairs_to_dict((m.group('name'), m.group('value')) for m in re.finditer(cls.re_data, body))
data = merge_dicts([default_data, yaml_data, body_data])
# validation and type conversion
typed = schema.SchemaConverter.convert(itemtype, data)
return typed
def parse_data(cls, title, body, itemtype=u"Article"):
body = body.replace("\r\n", "\n")
default_data = {"name": title, "schema": schema.get_itemtype_path(itemtype)}
# collect
yaml_data = cls.parse_schema_yaml(body)
body_data = pairs_to_dict((m.group("name"), m.group("value")) for m in re.finditer(cls.re_data, body))
if itemtype == u"Article" or u"Article" in schema.get_schema(itemtype)[u"ancestors"]:
default_section = u"articleBody"
else:
default_section = u"longDescription"
section_data = cls.parse_sections(body, default_section)
# merge
data = merge_dicts([default_data, yaml_data, body_data, section_data])
# validation and type conversion
typed = schema.SchemaConverter.convert(itemtype, data)
return typed
def parse_data(cls, title, body, itemtype=u'Article'):
body = body.replace('\r\n', '\n')
default_data = {'name': title, 'schema': schema.get_itemtype_path(itemtype)}
# collect
yaml_data = cls.parse_schema_yaml(body)
body_data = pairs_to_dict((m.group('name'), m.group('value')) for m in re.finditer(cls.re_data, body))
if itemtype == u'Article' or u'Article' in schema.get_schema(itemtype)[u'ancestors']:
default_section = u'articleBody'
else:
default_section = u'longDescription'
section_data = cls.parse_sections(body, default_section)
# merge
data = merge_dicts([default_data, yaml_data, body_data, section_data])
# validation and type conversion
typed = schema.SchemaConverter.convert(itemtype, data)
return typed
def test_normal_pairs(self):
self.assertEqual({'a': 1, 'b': 2}, pairs_to_dict([('a', 1), ('b', 2)]))
def test_duplicated_key_and_value(self):
self.assertEqual({'a': 1}, pairs_to_dict([('a', 1), ('a', 1)]))
def test_empty(self):
self.assertEqual({}, pairs_to_dict([]))
def test_duplicated_key(self):
self.assertEqual({'a': [1, 2]}, pairs_to_dict([('a', 1), ('a', 2)]))
def test_normal_pairs(self):
self.assertEqual({'a': 1, 'b': 2}, pairs_to_dict([('a', 1), ('b', 2)]))
def test_empty(self):
self.assertEqual({}, pairs_to_dict([]))
def test_duplicated_key_and_value(self):
self.assertEqual({'a': 1}, pairs_to_dict([('a', 1), ('a', 1)]))
def test_duplicated_key(self):
self.assertEqual({'a': [1, 2]}, pairs_to_dict([('a', 1), ('a', 2)]))
