Exemplo n.º 1
0
 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)
Exemplo n.º 2
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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)
Exemplo n.º 3
0
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)
Exemplo n.º 4
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 def soft_delete(self, session):
     """Mark this object as deleted."""
     self.deleted = self.id
     self.deleted_at = timeutils.utcnow()
     self.save(session=session)
Exemplo n.º 5
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class TimestampMixin(object):
    created_at = Column(DateTime, default=lambda: timeutils.utcnow())
    updated_at = Column(DateTime, onupdate=lambda: timeutils.utcnow())
Exemplo n.º 6
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 def soft_delete(self, session):
     """Mark this object as deleted."""
     self.deleted = self.id
     self.deleted_at = timeutils.utcnow()
     self.save(session=session)
Exemplo n.º 7
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 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)