change gather orm example

changed gather orm example to avoid passing the same session to the
function called in the gather. While this is not an issue since no
sql is executed on it, it's still confusing for some users

References: #9312
Change-Id: I7f86e9c1640649ac13fd459b761d67718d4c3dc0

diff --git a/examples/asyncio/gather_orm_statements.py b/examples/asyncio/gather_orm_statements.py
index 334521f0e426b133c4939eabff1f5156c93b89e6..b11ee558cd1391d6d4d8469a041279a785f6c8d5 100644 (file)
--- a/examples/asyncio/gather_orm_statements.py
+++ b/examples/asyncio/gather_orm_statements.py
@@ -19,31 +19,33 @@ traditional approach.
 import asyncio
 import random
 
-from sqlalchemy import Column
-from sqlalchemy import Integer
-from sqlalchemy import String
 from sqlalchemy.ext.asyncio import async_sessionmaker
 from sqlalchemy.ext.asyncio import create_async_engine
-from sqlalchemy.ext.declarative import declarative_base
 from sqlalchemy.future import select
+from sqlalchemy.orm import DeclarativeBase
+from sqlalchemy.orm import Mapped
+from sqlalchemy.orm import mapped_column
 from sqlalchemy.orm import merge_frozen_result
 
-Base = declarative_base()
+
+class Base(DeclarativeBase):
+    pass
 
 
 class A(Base):
     __tablename__ = "a"
 
-    id = Column(Integer, primary_key=True)
-    data = Column(String)
+    id: Mapped[int] = mapped_column(primary_key=True)
+    data: Mapped[str]
 
+    def __repr__(self):
+        id_, data = self.id, self.data
+        return f"A({id_=}, {data=})"
 
-async def run_out_of_band(
-    async_sessionmaker, session, statement, merge_results=True
-):
-    """run an ORM statement in a distinct session, merging the result
-    back into the given session.
 
+async def run_out_of_band(async_sessionmaker, statement, merge_results=True):
+    """run an ORM statement in a distinct session,
+    returning the frozen results
     """
 
     async with async_sessionmaker() as oob_session:
@@ -53,30 +55,10 @@ async def run_out_of_band(
             execution_options={"isolation_level": "AUTOCOMMIT"}
         )
 
-        # pre 1.4.24
-        # await oob_session.run_sync(
-        #     lambda sync_session: sync_session.connection(
-        #         execution_options={"isolation_level": "AUTOCOMMIT"}
-        #     )
-        # )
-
         result = await oob_session.execute(statement)
 
         if merge_results:
-            # merge_results means the ORM objects from the result
-            # will be merged back into the original session.
-            # load=False means we can use the objects directly without
-            # re-selecting them.  however this merge operation is still
-            # more expensive CPU-wise than a regular ORM load because the
-            # objects are copied into new instances
-            return (
-                await session.run_sync(
-                    merge_frozen_result,
-                    statement,
-                    result.freeze(),
-                    load=False,
-                )
-            )()
+            return result.freeze()
         else:
             await result.close()
 
@@ -101,12 +83,27 @@ async def async_main():
         for i in range(30)
     ]
 
-    results = await asyncio.gather(
+    frozen_results = await asyncio.gather(
         *(
-            run_out_of_band(async_session, session, statement)
+            run_out_of_band(async_session, statement)
             for statement in statements
         )
     )
+    results = [
+        # merge_results means the ORM objects from the result
+        # will be merged back into the original session.
+        # load=False means we can use the objects directly without
+        # re-selecting them.  however this merge operation is still
+        # more expensive CPU-wise than a regular ORM load because the
+        # objects are copied into new instances
+        (
+            await session.run_sync(
+                merge_frozen_result, statement, result, load=False
+            )
+        )()
+        for statement, result in zip(statements, frozen_results)
+    ]
+
     print(f"results: {[r.all() for r in results]}")