def rename_field(key: FlattenKey, data: FlattenDataDict,
errors: FlattenErrorDict, context: Context):
index = max([int(k[1]) for k in data.keys()
if len(k) == 3 and k[0] == new] + [-1])
for field_name in list(data.keys()):
if field_name[0] == old and data.get(field_name):
new_field_name = list(field_name)
new_field_name[0] = new
if len(new_field_name) > 1:
new_field_name[1] = int(new_field_name[1]) + index + 1
data[tuple(new_field_name)] = data[field_name]
data.pop(field_name)
def func(key: FlattenKey, data: FlattenDataDict, errors: FlattenErrorDict,
context: Context):
new_tags = data.get(key)
if not new_tags:
return
if isinstance(new_tags, str):
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 df.Invalid(_('Tag vocabulary "%s" does not exist') % vocab)
context['vocabulary'] = v
for tag in new_tags:
validators.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 free_tags_only(key: FlattenKey, data: FlattenDataDict,
errors: FlattenErrorDict, context: Context) -> Any:
tag_number = key[1]
if not data.get(('tags', tag_number, 'vocabulary_id')):
return
for k in list(data.keys()):
if k[0] == 'tags' and k[1] == tag_number:
del data[k]
def unflatten(data: FlattenDataDict) -> dict[str, Any]:
'''Unflatten a simple dict whose keys are tuples.
e.g.
>>> unflatten(
{('name',): u'testgrp4',
('title',): u'',
('description',): u'',
('packages', 0, 'name'): u'testpkg',
('packages', 1, 'name'): u'testpkg',
('extras', 0, 'key'): u'packages',
('extras', 0, 'value'): u'["testpkg"]',
('extras', 1, 'key'): u'',
('extras', 1, 'value'): u'',
('state',): u'active'
('save',): u'Save Changes',
('cancel',): u'Cancel'})
{'name': u'testgrp4',
'title': u'',
'description': u'',
'packages': [{'name': u'testpkg'}, {'name': u'testpkg'}],
'extras': [{'key': u'packages', 'value': u'["testpkg"]'},
{'key': u'', 'value': u''}],
'state': u'active',
'save': u'Save Changes',
'cancel': u'Cancel'}
'''
unflattened: dict[str, Any] = {}
clean_lists: dict[int, Any] = {}
for flattend_key in sorted(data.keys(), key=flattened_order_key):
current_pos: Union[list[Any], dict[str, Any]] = unflattened
for key in flattend_key[:-1]:
try:
current_pos = current_pos[key]
except IndexError:
while True:
new_pos: Any = {}
assert isinstance(current_pos, list)
current_pos.append(new_pos)
if key < len(current_pos):
break
# skipped list indexes need to be removed before returning
clean_lists[id(current_pos)] = current_pos
current_pos = new_pos
except KeyError:
new_pos = []
current_pos[key] = new_pos
current_pos = new_pos
current_pos[flattend_key[-1]] = data[flattend_key]
for cl in clean_lists.values():
cl[:] = [i for i in cl if i]
return unflattened
def convert_to_extras(key: FlattenKey, data: FlattenDataDict,
errors: FlattenErrorDict, context: Context) -> Any:
# Get the current extras index
current_indexes = [
k[1] for k in data.keys() if len(k) > 1 and k[0] == 'extras'
]
new_index = max(current_indexes) + 1 if current_indexes else 0
data[('extras', new_index, 'key')] = key[-1]
data[('extras', new_index, 'value')] = data[key]
def func(key: FlattenKey, data: FlattenDataDict, errors: FlattenErrorDict,
context: Context):
v = model.Vocabulary.get(vocab)
if not v:
raise df.Invalid(_('Tag vocabulary "%s" does not exist') % vocab)
tags = []
for k in data.keys():
if k[0] == 'tags':
if data[k].get('vocabulary_id') == v.id:
name = data[k].get('display_name', data[k]['name'])
tags.append(name)
data[key] = tags
def tag_string_convert(key: FlattenKey, data: FlattenDataDict,
errors: FlattenErrorDict, context: Context) -> Any:
'''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], str):
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] )
for num, tag in zip(count(current_index+1), tags):
data[('tags', num, 'name')] = tag
for tag in tags:
tag_length_validator(tag, context)
tag_name_validator(tag, context)
