def _update_skill(
skill_model: skill_models.SkillModel,
migrated_skill: skill_domain.Skill,
skill_changes: Sequence[skill_domain.SkillChange]
) -> Sequence[base_models.BaseModel]:
"""Generates newly updated skill models.
Args:
skill_model: SkillModel. The skill which should be updated.
migrated_skill: Skill. The migrated skill domain object.
skill_changes: sequence(SkillChange). The skill changes to apply.
Returns:
sequence(BaseModel). Sequence of models which should be put into
the datastore.
"""
updated_skill_model = (skill_services.populate_skill_model_fields(
skill_model, migrated_skill))
commit_message = ('Update skill content schema version to %d and '
'skill misconceptions schema version to %d and '
'skill rubrics schema version to %d.') % (
feconf.CURRENT_SKILL_CONTENTS_SCHEMA_VERSION,
feconf.CURRENT_MISCONCEPTIONS_SCHEMA_VERSION,
feconf.CURRENT_RUBRIC_SCHEMA_VERSION)
change_dicts = [change.to_dict() for change in skill_changes]
with datastore_services.get_ndb_context():
models_to_put = updated_skill_model.compute_models_to_commit(
feconf.MIGRATION_BOT_USERNAME,
feconf.COMMIT_TYPE_EDIT,
commit_message,
change_dicts,
additional_models={}).values()
datastore_services.update_timestamps_multi(list(models_to_put))
return models_to_put
def _update_story(
story_model: story_models.StoryModel,
migrated_story: story_domain.Story,
story_change: story_domain.StoryChange
) -> Sequence[base_models.BaseModel]:
"""Generates newly updated story models.
Args:
story_model: StoryModel. The story which should be updated.
migrated_story: Story. The migrated story domain object.
story_change: StoryChange. The story change to apply.
Returns:
sequence(BaseModel). Sequence of models which should be put into
the datastore.
"""
updated_story_model = story_services.populate_story_model_fields(
story_model, migrated_story)
change_dicts = [story_change.to_dict()]
with datastore_services.get_ndb_context():
models_to_put = updated_story_model.compute_models_to_commit(
feconf.MIGRATION_BOT_USERNAME,
feconf.COMMIT_TYPE_EDIT,
'Update story contents schema version to %d.' % (
feconf.CURRENT_STORY_CONTENTS_SCHEMA_VERSION),
change_dicts,
additional_models={}
)
models_to_put_values = []
for _, value in models_to_put.items():
# Here, we are narrowing down the type from object to BaseModel.
assert isinstance(value, base_models.BaseModel)
models_to_put_values.append(value)
datastore_services.update_timestamps_multi(models_to_put_values)
return models_to_put_values
def setUp(self):
super().setUp()
story_summary_model = self.create_model(
story_models.StorySummaryModel,
id=self.STORY_1_ID,
title='title',
url_fragment='urlfragment',
language_code='cs',
description='description',
node_titles=['title1', 'title2'],
story_model_last_updated=datetime.datetime.utcnow(),
story_model_created_on=datetime.datetime.utcnow(),
version=1)
topic_model = self.create_model(
topic_models.TopicModel,
id=self.TOPIC_1_ID,
name='topic title',
canonical_name='topic title',
story_reference_schema_version=1,
subtopic_schema_version=1,
next_subtopic_id=1,
language_code='cs',
url_fragment='topic',
canonical_story_references=[{
'story_id': self.STORY_1_ID,
'story_is_published': False
}],
page_title_fragment_for_web='fragm',
)
datastore_services.update_timestamps_multi(
[topic_model, story_summary_model])
datastore_services.put_multi([topic_model, story_summary_model])
self.latest_contents = {
'nodes': [{
'id': 'node_1111',
'title': 'title',
'description': 'description',
'thumbnail_filename': 'thumbnail_filename.svg',
'thumbnail_bg_color': '#F8BF74',
'thumbnail_size_in_bytes': None,
'destination_node_ids': [],
'acquired_skill_ids': [],
'prerequisite_skill_ids': [],
'outline': 'outline',
'outline_is_finalized': True,
'exploration_id': 'exp_id'
}],
'initial_node_id':
'node_1111',
'next_node_id':
'node_2222'
}
self.broken_contents = copy.deepcopy(self.latest_contents)
self.broken_contents['nodes'][0]['description'] = 123
self.unmigrated_contents = copy.deepcopy(self.latest_contents)
self.unmigrated_contents['nodes'][0]['thumbnail_size_in_bytes'] = 123
def put_multi(self, model_list: Sequence[base_models.BaseModel]) -> None:
"""Puts the input models into the datastore.
Args:
model_list: list(Model). The NDB models to put into the datastore.
"""
datastore_services.update_timestamps_multi(
model_list, update_last_updated_time=False)
datastore_services.put_multi(model_list)
def mark_outdated_models_as_deleted() -> None:
"""Mark models in MODEL_CLASSES_TO_MARK_AS_DELETED, as deleted if they were
last updated more than four weeks ago.
"""
date_before_which_to_mark_as_deleted = (
datetime.datetime.utcnow() - feconf.PERIOD_TO_MARK_MODELS_AS_DELETED)
models_to_mark_as_deleted: List[base_models.BaseModel] = []
for model_class in MODEL_CLASSES_TO_MARK_AS_DELETED:
models_to_mark_as_deleted.extend(
model_class.query(
model_class.last_updated < date_before_which_to_mark_as_deleted
).fetch())
for model_to_mark_as_deleted in models_to_mark_as_deleted:
model_to_mark_as_deleted.deleted = True
datastore_services.update_timestamps_multi(models_to_mark_as_deleted)
datastore_services.put_multi(models_to_mark_as_deleted)
