Replace use of 'Engine.execute()'

Resolve the following RemovedIn20Warning warning:

  The Engine.execute() method is considered legacy as of the 1.x series
  of SQLAlchemy and will be removed in 2.0. All statement execution in
  SQLAlchemy 2.0 is performed by the Connection.execute() method of
  Connection, or in the ORM by the Session.execute() method of Session.

Change-Id: I4c47a690a94abcb3b4b6fb087a1bf86c5350b523
Signed-off-by: Stephen Finucane <stephenfin@redhat.com>

1 files changed, 31 insertions, 27 deletions

diff --git a/oslo_db/sqlalchemy/utils.py b/oslo_db/sqlalchemy/utils.py
index 90236d5..333fff0 100644
--- a/oslo_db/sqlalchemy/utils.py
+++ b/oslo_db/sqlalchemy/utils.py
@@ -490,32 +490,34 @@ def drop_old_duplicate_entries_from_table(engine, table_name,
         func.count(table.c.id) > 1
     )
 
-    for row in engine.execute(duplicated_rows_select).fetchall():
-        # 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._mapping[name]
-
-        rows_to_delete_select = sqlalchemy.sql.select(
-            table.c.id,
-        ).where(delete_condition)
-        for row in engine.execute(rows_to_delete_select).fetchall():
-            LOG.info("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)
-        engine.execute(delete_statement)
+    with engine.connect() as conn:
+        for row in conn.execute(duplicated_rows_select).fetchall():
+            # 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._mapping[name]
+
+            rows_to_delete_select = sqlalchemy.sql.select(
+                table.c.id,
+            ).where(delete_condition)
+            for row in conn.execute(rows_to_delete_select).fetchall():
+                LOG.info(
+                    "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)
+            conn.execute(delete_statement)
 
 
 def _get_default_deleted_value(table):
@@ -1118,7 +1120,9 @@ def get_non_innodb_tables(connectable, skip_tables=('migrate_version',
 
     params['database'] = connectable.engine.url.database
     query = text(query_str)
-    noninnodb = connectable.execute(query, params)
+    # TODO(stephenfin): What about if this is already a Connection?
+    with connectable.connect() as conn:
+        noninnodb = conn.execute(query, params)
     return [i[0] for i in noninnodb]