Copilot commented on code in PR #69190:
URL: https://github.com/apache/airflow/pull/69190#discussion_r3560569795


##########
providers/amazon/tests/system/amazon/aws/example_s3_compatible_object_storage.py:
##########
@@ -0,0 +1,103 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+"""
+Example Dag: input -> transform -> output on an S3-compatible object store via 
``ObjectStoragePath``.
+
+The Amazon provider talks to any S3-compatible object store, so 
``ObjectStoragePath("s3://...")``
+reaches the store through the Amazon provider once the ``aws`` connection 
points at its S3
+endpoint. Amazon S3 is the baseline; the same code works against other 
S3-compatible services
+(for example Amazon S3, Backblaze B2, Cloudflare R2, and MinIO). See the 
recipe "Use an
+S3-compatible object store for Airflow remote task logs" for connection and 
``[logging]`` setup.

Review Comment:
   The module docstring says “Amazon S3 is the baseline” and then lists “Amazon 
S3” again as an example of *other* S3-compatible services. This reads 
contradictory/redundant; suggest listing only non-AWS examples (or rephrasing 
to “including Amazon S3 …”).



##########
providers/amazon/tests/system/amazon/aws/example_s3_compatible_object_storage.py:
##########
@@ -0,0 +1,103 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+"""
+Example Dag: input -> transform -> output on an S3-compatible object store via 
``ObjectStoragePath``.
+
+The Amazon provider talks to any S3-compatible object store, so 
``ObjectStoragePath("s3://...")``
+reaches the store through the Amazon provider once the ``aws`` connection 
points at its S3
+endpoint. Amazon S3 is the baseline; the same code works against other 
S3-compatible services
+(for example Amazon S3, Backblaze B2, Cloudflare R2, and MinIO). See the 
recipe "Use an
+S3-compatible object store for Airflow remote task logs" for connection and 
``[logging]`` setup.
+
+Set up an ``aws`` connection (default id ``aws_s3``) whose ``extra`` includes 
the S3
+``endpoint_url`` and ``region_name``. The bucket name comes from 
``S3_BUCKET_NAME``.
+
+Requires the s3fs extra: ``pip install 
'apache-airflow-providers-amazon[s3fs]'``.
+"""
+
+from __future__ import annotations
+
+import os
+from datetime import datetime
+
+import pytest
+
+from airflow.sdk import ObjectStoragePath, dag, task
+
+DAG_ID = "example_s3_compatible_object_storage"
+
+# Connection id and bucket are read from the environment so the example 
carries no secrets.
+S3_CONN_ID = os.environ.get("S3_CONN_ID", "aws_s3")
+S3_BUCKET_NAME_PLACEHOLDER = "replace-with-your-s3-bucket"
+S3_BUCKET_NAME = os.environ.get("S3_BUCKET_NAME", S3_BUCKET_NAME_PLACEHOLDER)
+BASE_URI = f"s3://{S3_CONN_ID}@{S3_BUCKET_NAME}/airflow-demo/"
+
+
+def _base_path() -> ObjectStoragePath:
+    if S3_BUCKET_NAME == S3_BUCKET_NAME_PLACEHOLDER:
+        raise ValueError("Set S3_BUCKET_NAME to a real bucket name before 
running this Dag.")
+    return ObjectStoragePath(BASE_URI)
+
+
+@dag(
+    schedule=None,
+    start_date=datetime(2021, 1, 1),
+    catchup=False,
+    tags=["example", "s3-compatible", "object-storage"],
+)

Review Comment:
   `DAG_ID` is defined but not wired into the `@dag` decorator. Setting 
`dag_id=DAG_ID` makes the dag id explicit (and keeps it stable if the function 
name changes), or alternatively the constant can be removed.



##########
providers/amazon/docs/logging/s3-compatible-remote-logging.rst:
##########
@@ -0,0 +1,211 @@
+ .. Licensed to the Apache Software Foundation (ASF) under one
+    or more contributor license agreements.  See the NOTICE file
+    distributed with this work for additional information
+    regarding copyright ownership.  The ASF licenses this file
+    to you under the Apache License, Version 2.0 (the
+    "License"); you may not use this file except in compliance
+    with the License.  You may obtain a copy of the License at
+
+ ..   http://www.apache.org/licenses/LICENSE-2.0
+
+ .. Unless required by applicable law or agreed to in writing,
+    software distributed under the License is distributed on an
+    "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+    KIND, either express or implied.  See the License for the
+    specific language governing permissions and limitations
+    under the License.
+
+.. _write-logs-s3-compatible:
+
+Use an S3-compatible object store for Airflow remote task logs
+==============================================================
+
+The Amazon provider talks to any S3-compatible object store, not just Amazon 
S3. Because the
+:ref:`S3 remote task handler <write-logs-amazon-s3>` issues standard S3 API 
calls, pointing the
+``aws`` connection at a custom ``endpoint_url`` makes it write Airflow task 
logs to that
+endpoint with no new provider and no core change. You use the ``s3://`` scheme 
in
+``[logging]`` exactly as you would for Amazon S3, and the same connection also 
backs
+``ObjectStoragePath("s3://...")`` for Dag data.
+
+Amazon S3 is the baseline. The same steps work against other services that 
expose an
+S3-compatible API, for example Amazon S3, Backblaze B2, Cloudflare R2, and 
MinIO. The only
+per-provider differences are the endpoint URL, the region, and whether 
path-style addressing
+is required.

Review Comment:
   This section says “Amazon S3 is the baseline” and then lists “Amazon S3” as 
an example of *other* S3-compatible services. That’s redundant/contradictory; 
suggest listing only non-AWS examples (or rephrasing the sentence).



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