def _inner():
if initial_delay:
greenthread.sleep(initial_delay)
try:
while self._running:
start = timeutils.utcnow()
self.f(*self.args, **self.kw)
end = timeutils.utcnow()
if not self._running:
break
delay = interval - timeutils.delta_seconds(start, end)
if delay <= 0:
LOG.warning(_('task run outlasted interval by %s '
'sec'), -delay)
greenthread.sleep(delay if delay > 0 else 0)
except LoopingCallDone as e:
self.stop()
done.send(e.retvalue)
except Exception:
LOG.exception(_('in fixed duration looping call'))
done.send_exception(*sys.exc_info())
return
else:
done.send(True)
def soft_delete(self, synchronize_session='evaluate'):
return self.update(
{
'deleted': literal_column('id'),
'updated_at': literal_column('updated_at'),
'deleted_at': timeutils.utcnow()
},
synchronize_session=synchronize_session)
def soft_delete(self, synchronize_session="evaluate"):
return self.update(
{
"deleted": literal_column("id"),
"updated_at": literal_column("updated_at"),
"deleted_at": timeutils.utcnow(),
},
synchronize_session=synchronize_session,
)
def drop_old_duplicate_entries_from_table(migrate_engine, table_name,
use_soft_delete, *uc_column_names):
"""Drop all old rows having the same values for columns in uc_columns.
This method drop (or mark ad `deleted` if use_soft_delete is True) old
duplicate rows form table with name `table_name`.
:param migrate_engine: Sqlalchemy engine
:param table_name: Table with duplicates
:param use_soft_delete: If True - values will be marked as `deleted`,
if False - values will be removed from table
:param uc_column_names: Unique constraint columns
"""
meta = MetaData()
meta.bind = migrate_engine
table = Table(table_name, meta, autoload=True)
columns_for_group_by = [table.c[name] for name in uc_column_names]
columns_for_select = [func.max(table.c.id)]
columns_for_select.extend(columns_for_group_by)
duplicated_rows_select = sqlalchemy.sql.select(
columns_for_select, group_by=columns_for_group_by,
having=func.count(table.c.id) > 1)
for row in migrate_engine.execute(duplicated_rows_select):
# NOTE(boris-42): Do not remove row that has the biggest ID.
delete_condition = table.c.id != row[0]
is_none = None # workaround for pyflakes
delete_condition &= table.c.deleted_at == is_none
for name in uc_column_names:
delete_condition &= table.c[name] == row[name]
rows_to_delete_select = sqlalchemy.sql.select(
[table.c.id]).where(delete_condition)
for row in migrate_engine.execute(rows_to_delete_select).fetchall():
LOG.info(_LI("Deleting duplicated row with id: %(id)s from table: "
"%(table)s") % dict(id=row[0], table=table_name))
if use_soft_delete:
delete_statement = table.update().\
where(delete_condition).\
values({
'deleted': literal_column('id'),
'updated_at': literal_column('updated_at'),
'deleted_at': timeutils.utcnow()
})
else:
delete_statement = table.delete().where(delete_condition)
migrate_engine.execute(delete_statement)
def soft_delete(self, session):
"""Mark this object as deleted."""
self.deleted = self.id
self.deleted_at = timeutils.utcnow()
self.save(session=session)
class TimestampMixin(object):
created_at = Column(DateTime, default=lambda: timeutils.utcnow())
updated_at = Column(DateTime, onupdate=lambda: timeutils.utcnow())
def soft_delete(self, session):
"""Mark this object as deleted."""
self.deleted = self.id
self.deleted_at = timeutils.utcnow()
self.save(session=session)