def callable_method(key, data, errors, context):
if isinstance(data[key], basestring):
tags = [tag.strip() for tag in data[key].split(',') if tag.strip()]
else:
tags = data[key]
current_index = max(
[int(k[1])
for k in data.keys() if len(k) == 3 and k[0] == 'tags'] + [-1])
model = context['model']
v = model.Vocabulary.get(vocab)
if not v:
_create_vocabulary(vocab)
v = model.Vocabulary.get(vocab)
context['vocabulary'] = v
for num, tag in zip(count(current_index + 1), tags):
data[('tags', num, 'name')] = tag
data[('tags', num, 'vocabulary_id')] = v.id
for tag in tags:
tag_length_validator(tag, context)
tag_name_validator(tag, context)
_create_tag(tag, context)
def callable_method(key, data, errors, context):
if isinstance(data[key], basestring):
tags = [tag.strip() for tag in data[key].split(',') if tag.strip()]
else:
tags = data[key]
current_index = max([int(k[1]) for k in data.keys() if len(k) == 3 and k[0] == 'tags'] + [-1])
model = context['model']
v = model.Vocabulary.get(vocab)
if not v:
_create_vocabulary(vocab)
v = model.Vocabulary.get(vocab)
context['vocabulary'] = v
for num, tag in zip(count(current_index + 1), tags):
data[('tags', num, 'name')] = tag
data[('tags', num, 'vocabulary_id')] = v.id
for tag in tags:
tag_length_validator(tag, context)
tag_name_validator(tag, context)
_create_tag(tag, context)
def callable(key, data, errors, context):
new_tags = data.get(key)
if not new_tags:
return
if isinstance(new_tags, basestring):
new_tags = [new_tags]
# get current number of tags
n = 0
for k in data.keys():
if k[0] == 'tags':
n = max(n, k[1] + 1)
v = model.Vocabulary.get(vocab)
if not v:
raise Invalid(_('Tag vocabulary "%s" does not exist') % vocab)
context['vocabulary'] = v
for tag in new_tags:
tag_length_validator(tag, context)
tag_name_validator(tag, context)
tag_in_vocabulary_validator(tag, context)
for num, tag in enumerate(new_tags):
data[('tags', num+n, 'name')] = tag
data[('tags', num+n, 'vocabulary_id')] = v.id
def add_to_vocab(context, tags, vocab):
try:
v = get_action('vocabulary_show')(context, {'id': vocab})
except ObjectNotFound:
v = plugin.create_vocabulary(vocab)
context['vocabulary'] = model.Vocabulary.get(v.get('id'))
for tag in tags:
validators.tag_length_validator(tag, context)
validators.tag_name_validator(tag, context)
try:
validators.tag_in_vocabulary_validator(tag, context)
except Invalid:
plugin.create_tag_to_vocabulary(tag, vocab)
def add_to_vocab(context, tags, vocab):
try:
v = get_action('vocabulary_show')(context, {'id': vocab})
except ObjectNotFound:
v = plugin.create_vocabulary(vocab)
if isinstance(tags, basestring):
tags = [tags]
for tag in tags:
validators.tag_length_validator(tag, context)
validators.tag_name_validator(tag, context)
try:
validators.tag_in_vocabulary_validator(tag, context)
except Invalid:
plugin.create_tag_to_vocabulary(tag, vocab)
def keyword_string_convert(key, data, errors, context):
'''
Takes a list of tags that is a comma-separated string (in data[key])
and parses tag names. These are added to the data dict, enumerated. They
are also validated.
'''
if isinstance(data[key], basestring):
tags = [tag.strip() for tag in data[key].split(',') if tag.strip()]
else:
tags = data[key]
current_index = max(
[int(k[1])
for k in data.keys() if len(k) == 3 and k[0] == 'keywords'] + [-1])
for num, tag in zip(itertools.count(current_index + 1), tags):
data[('keywords', num, 'name')] = tag
for tag in tags:
val.tag_length_validator(tag, context)
val.tag_name_validator(tag, context)
def add_to_vocab(context, tags, vocab):
defer = context.get('defer', False)
try:
v = get_action('vocabulary_show')(context, {'id': vocab})
except ObjectNotFound:
log.info("creating vocab")
v = plugin.create_vocabulary(vocab, defer)
context['vocabulary'] = model.Vocabulary.get(v.get('id'))
if isinstance(tags, basestring):
tags = [tags]
for tag in tags:
validators.tag_length_validator(tag, context)
validators.tag_name_validator(tag, context)
try:
validators.tag_in_vocabulary_validator(tag, context)
except Invalid:
plugin.create_tag_to_vocabulary(tag, vocab, defer)
def keyword_string_convert(key, data, errors, context):
'''
Takes a list of tags that is a comma-separated string (in data[key])
and parses tag names. These are added to the data dict, enumerated. They
are also validated.
'''
if isinstance(data[key], basestring):
tags = [tag.strip() \
for tag in data[key].split(',') \
if tag.strip()]
else:
tags = data[key]
current_index = max([int(k[1]) for k in data.keys() if len(k) == 3 and k[0] == 'keywords'] + [-1])
for num, tag in zip(itertools.count(current_index + 1), tags):
data[('keywords', num, 'name')] = tag
for tag in tags:
val.tag_length_validator(tag, context)
val.tag_name_validator(tag, context)
def add_to_vocab(context, tags, vocab):
defer = context.get('defer', False)
try:
v = get_action('vocabulary_show')(context, {'id': vocab})
except ObjectNotFound:
log.info("creating vocab")
v = plugin.create_vocabulary(vocab, defer)
context['vocabulary'] = model.Vocabulary.get(v.get('id'))
if isinstance(tags, basestring):
tags = [tags]
for tag in tags:
validators.tag_length_validator(tag, context)
validators.tag_name_validator(tag, context)
try:
validators.tag_in_vocabulary_validator(tag, context)
except Invalid:
plugin.create_tag_to_vocabulary(tag, vocab, defer)
.format(previous_object.guid))
previous_object.current = False
previous_object.add()
# Flag this object as the current one
harvest_object.current = True
harvest_object.add()
if status == 'new':
try:
package_dict = self._get_package_dict(harvest_object)
# validate tags
for tag in package_dict['tags']:
try:
validator_response = v.tag_name_validator(
tag['name'], context)
except Exception, e:
log.exception('Error processing tags: %r', e)
self._save_object_error('%r' % e.error, harvest_object,
'Import')
return None
# Save reference to the package on the object
harvest_object.package_id = package_dict['id']
# Defer constraints and flush so the dataset can be indexed with
# the harvest object id (on the after_show hook from the harvester
# plugin)
model.Session.execute(
'SET CONSTRAINTS harvest_object_package_id_fkey DEFERRED')
model.Session.flush()