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Added support for asyncio (#6).
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Diff for: ‎doc/src/release_notes.rst

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@@ -13,6 +13,8 @@ oracledb 2.0.0 (TBD)
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Thin Mode Changes
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+++++++++++++++++
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#) Added support for asyncio
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(`issue 6 <https://github.com/oracle/python-oracledb/issues/6>`__).
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#) Added support for an Oracle Database 23c JSON feature allowing for field
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names with more than 255 UTF-8 encoded bytes.
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#) Added support for an Oracle Database 23c JSON feature improving JSON

Diff for: ‎samples/array_dml_rowcounts_async.py

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# -----------------------------------------------------------------------------
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# Copyright (c) 2023, Oracle and/or its affiliates.
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#
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# This software is dual-licensed to you under the Universal Permissive License
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# (UPL) 1.0 as shown at https://oss.oracle.com/licenses/upl and Apache License
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# 2.0 as shown at http://www.apache.org/licenses/LICENSE-2.0. You may choose
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# either license.
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#
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# If you elect to accept the software under the Apache License, Version 2.0,
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# the following applies:
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# https://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# -----------------------------------------------------------------------------
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# -----------------------------------------------------------------------------
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# array_dml_rowcounts_async.py
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#
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# An asynchronous version of array_dml_rowcounts.py
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#
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# Demonstrates the use of the 12.1 feature that allows cursor.executemany()
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# to return the number of rows affected by each individual execution as a list.
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# The parameter "arraydmlrowcounts" must be set to True in the call to
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# cursor.executemany() after which cursor.getarraydmlrowcounts() can be called.
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# -----------------------------------------------------------------------------
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import asyncio
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import oracledb
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import sample_env
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async def main():
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connection = await oracledb.connect_async(
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user=sample_env.get_main_user(),
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password=sample_env.get_main_password(),
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dsn=sample_env.get_connect_string(),
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)
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with connection.cursor() as cursor:
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# show the number of rows for each parent ID as a means of verifying
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# the output from the delete statement
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await cursor.execute(
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"""
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select ParentId, count(*)
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from ChildTable
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group by ParentId
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order by ParentId
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"""
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)
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async for parent_id, count in cursor:
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print("Parent ID:", parent_id, "has", int(count), "rows.")
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print()
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# delete the following parent IDs only
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parent_ids_to_delete = [20, 30, 50]
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print("Deleting Parent IDs:", parent_ids_to_delete)
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print()
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# enable array DML row counts for each iteration executed in
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# executemany()
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await cursor.executemany(
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"delete from ChildTable where ParentId = :1",
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[(i,) for i in parent_ids_to_delete],
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arraydmlrowcounts=True,
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)
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# display the number of rows deleted for each parent ID
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row_counts = cursor.getarraydmlrowcounts()
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for parent_id, count in zip(parent_ids_to_delete, row_counts):
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print("Parent ID:", parent_id, "deleted", count, "rows.")
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asyncio.run(main())

Diff for: ‎samples/async_gather.py

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# -----------------------------------------------------------------------------
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# Copyright (c) 2023, Oracle and/or its affiliates.
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#
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# This software is dual-licensed to you under the Universal Permissive License
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# (UPL) 1.0 as shown at https://oss.oracle.com/licenses/upl and Apache License
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# 2.0 as shown at http://www.apache.org/licenses/LICENSE-2.0. You may choose
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# either license.
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#
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# If you elect to accept the software under the Apache License, Version 2.0,
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# the following applies:
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# https://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# -----------------------------------------------------------------------------
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# -----------------------------------------------------------------------------
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# async_gather.py
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#
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# Demonstrates using a connection pool with asyncio and gather().
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#
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# Multiple database sessions will be opened and used by each coroutine. The
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# number of connections opened can depend on the speed of your environment.
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# -----------------------------------------------------------------------------
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import asyncio
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import oracledb
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import sample_env
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# Number of coroutines to run
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CONCURRENCY = 5
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# Query the unique session identifier/serial number combination of a connection
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SQL = """SELECT UNIQUE CURRENT_TIMESTAMP AS CT, sid||'-'||serial# AS SIDSER
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FROM v$session_connect_info
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WHERE sid = SYS_CONTEXT('USERENV', 'SID')"""
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# Show the unique session identifier/serial number of each connection that the
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# pool opens
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async def init_session(connection, requested_tag):
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res = await connection.fetchone(SQL)
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print(res[0].strftime("%H:%M:%S.%f"), "- init_session SID-SERIAL#", res[1])
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# The coroutine simply shows the session identifier/serial number of the
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# conneciton returned by the pool.acquire() call
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async def query(pool):
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async with pool.acquire() as connection:
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await connection.callproc("dbms_session.sleep", [1])
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res = await connection.fetchone(SQL)
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print(res[0].strftime("%H:%M:%S.%f"), "- query SID-SERIAL#", res[1])
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async def main():
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pool = oracledb.create_pool_async(
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user=sample_env.get_main_user(),
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password=sample_env.get_main_password(),
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dsn=sample_env.get_connect_string(),
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min=1,
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max=CONCURRENCY,
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session_callback=init_session,
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)
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coroutines = [query(pool) for i in range(CONCURRENCY)]
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await asyncio.gather(*coroutines)
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await pool.close()
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asyncio.run(main())

Diff for: ‎samples/batch_errors_async.py

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# -----------------------------------------------------------------------------
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# Copyright (c) 2023, Oracle and/or its affiliates.
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#
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# This software is dual-licensed to you under the Universal Permissive License
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# (UPL) 1.0 as shown at https://oss.oracle.com/licenses/upl and Apache License
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# 2.0 as shown at http://www.apache.org/licenses/LICENSE-2.0. You may choose
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# either license.
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#
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# If you elect to accept the software under the Apache License, Version 2.0,
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# the following applies:
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# https://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# -----------------------------------------------------------------------------
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# -----------------------------------------------------------------------------
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# batch_errors_async.py
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#
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# An asynchronous version of batch_errors.py
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#
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# Demonstrates the use of the Oracle Database 12.1 feature that allows
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# cursor.executemany() to complete successfully, even if errors take
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# place during the execution of one or more of the individual
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# executions. The parameter "batcherrors" must be set to True in the
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# call to cursor.executemany() after which cursor.getbatcherrors() can
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# be called, which will return a list of error objects.
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# -----------------------------------------------------------------------------
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import asyncio
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import oracledb
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import sample_env
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async def main():
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connection = await oracledb.connect_async(
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user=sample_env.get_main_user(),
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password=sample_env.get_main_password(),
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dsn=sample_env.get_connect_string(),
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)
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with connection.cursor() as cursor:
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# retrieve the number of rows in the table
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await cursor.execute("select count(*) from ChildTable")
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(count,) = await cursor.fetchone()
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print("Number of rows in child table:", int(count))
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# define data to insert
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data_to_insert = [
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(1016, 10, "Child B of Parent 10"),
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(1017, 10, "Child C of Parent 10"),
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(1018, 20, "Child D of Parent 20"),
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(1018, 20, "Child D of Parent 20"), # duplicate key
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(1019, 30, "Child C of Parent 30"),
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(1020, 30, "Child D of Parent 40"),
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(1021, 60, "Child A of Parent 60"), # parent does not exist
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(1022, 40, "Child F of Parent 40"),
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]
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print("Number of rows to insert:", len(data_to_insert))
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# old method: executemany() with data errors results in stoppage after
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# the first error takes place; the row count is updated to show how
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# many rows actually succeeded
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try:
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await cursor.executemany(
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"insert into ChildTable values (:1, :2, :3)", data_to_insert
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)
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except oracledb.DatabaseError as e:
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(error,) = e.args
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print("Failure with error:", error.message)
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print("Number of rows successfully inserted:", cursor.rowcount)
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# demonstrate that the row count is accurate
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await cursor.execute("select count(*) from ChildTable")
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(count,) = await cursor.fetchone()
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print("Number of rows in child table after failed insert:", int(count))
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# roll back so we can perform the same work using the new method
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await connection.rollback()
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# new method: executemany() with batch errors enabled (and array DML
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# row counts also enabled) results in no immediate error being raised
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await cursor.executemany(
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"insert into ChildTable values (:1, :2, :3)",
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data_to_insert,
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batcherrors=True,
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arraydmlrowcounts=True,
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)
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# display the errors that have taken place
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errors = cursor.getbatcherrors()
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print("Number of rows with bad values:", len(errors))
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for error in errors:
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print(
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"Error", error.message.rstrip(), "at row offset", error.offset
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)
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# arraydmlrowcounts also shows rows with invalid data: they have a row
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# count of 0; otherwise 1 is shown
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row_counts = cursor.getarraydmlrowcounts()
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print("Array DML row counts:", row_counts)
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# demonstrate that all of the rows without errors have been
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# successfully inserted
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await cursor.execute("select count(*) from ChildTable")
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(count,) = await cursor.fetchone()
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print(
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"Number of rows in child table after insert with batcherrors "
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"enabled:",
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int(count),
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)
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asyncio.run(main())

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