Migrate Python Connector Examples

Adding the examples using the Aurora DSQL Python Connector (with the
smoke tests), since using the connector is the preferred method and
offers a more seamless user experience. This is the promoted default
path on the documentation, and the samples should be consistent with
this. Moved the boto3 examples to an `alternatives`, for use as
needed.

This also offers agentic benefits, as most agents are now able to
leverage a single search space and cross-example contex can stay
intact. It creates stronger retrieval since all the variants sit in the
same space, and agents will quickly be able to locate the best example
since by default, the documentation normally points to the samples
repository.

Author: anwesham-lab

README.md

@@ -22,6 +22,7 @@ The subdirectories contain code examples for connecting and using Aurora DSQL in
 | JavaScript  | [node-postgres (standalone)](javascript/node-postgres/) |
 | JavaScript  |         [Postgres.js](javascript/postgres-js/)          |
 |   Python    |                [Jupyter](python/jupyter)                |
+|   Python    |               [asyncpg](python/asyncpg/)                |
 |   Python    |               [psycopg](python/psycopg/)                |
 |   Python    |              [psycopg2](python/psycopg2/)               |
 |   Python    |             [SQLAlchemy](python/sqlalchemy)             |

python/asyncpg/README.md

@@ -0,0 +1,151 @@
+# Aurora DSQL with asyncpg
+
+This example demonstrates how to use the Aurora DSQL Python Connector with asyncpg to connect to Amazon Aurora DSQL clusters and perform basic database operations.
+
+Aurora DSQL is a distributed SQL database service that provides high availability and scalability for
+your PostgreSQL-compatible applications.
+Asyncpg is a popular PostgreSQL database library for Python that allows
+you to interact with PostgreSQL databases using Python code.
+
+## About the code example
+
+The example demonstrates a flexible connection approach that works for both admin and non-admin users:
+
+* When connecting as an **admin user**, the example uses the `public` schema and generates an admin authentication
+  token.
+* When connecting as a **non-admin user**, the example uses a custom `myschema` schema and generates a standard
+  authentication token.
+
+The code automatically detects the user type and adjusts its behavior accordingly.
+
+## ⚠️ Important
+
+* Running this code might result in charges to your AWS account.
+* We recommend that you grant your code least privilege. At most, grant only the
+  minimum permissions required to perform the task. For more information, see
+  [Grant least privilege](https://docs.aws.amazon.com/IAM/latest/UserGuide/best-practices.html#grant-least-privilege).
+* This code is not tested in every AWS Region. For more information, see
+  [AWS Regional Services](https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services).
+
+
+## TLS connection configuration
+
+This example uses direct TLS connections where supported, and verifies the server certificate is trusted. Verified SSL
+connections should be used where possible to ensure data security during transmission.
+
+* Driver versions following the release of PostgreSQL 17 support direct TLS connections, bypassing the traditional
+  PostgreSQL connection preamble
+* Direct TLS connections provide improved connection performance and enhanced security
+* Not all PostgreSQL drivers support direct TLS connections yet, or only in recent versions following PostgreSQL 17
+* Ensure your installed driver version supports direct TLS negotiation, or use a version that is at least as recent as
+  the one used in this sample
+* If your driver doesn't support direct TLS connections, you may need to use the traditional preamble connection instead
+
+
+### Prerequisites
+
+* You must have an AWS account, and have your default credentials and AWS Region
+  configured as described in the
+  [Globally configuring AWS SDKs and tools](https://docs.aws.amazon.com/credref/latest/refdocs/creds-config-files.html)
+  guide.
+* [Python 3.10.0](https://www.python.org/) or later.
+* You must have an Aurora DSQL cluster. For information about creating an Aurora DSQL cluster, see the
+  [Getting started with Aurora DSQL](https://docs.aws.amazon.com/aurora-dsql/latest/userguide/getting-started.html)
+  guide.
+* If connecting as a non-admin user, ensure the user is linked to an IAM role and is granted access to the `myschema`
+  schema. See the
+  [Using database roles with IAM roles](https://docs.aws.amazon.com/aurora-dsql/latest/userguide/using-database-and-iam-roles.html)
+  guide.
+
+### Download the Amazon root certificate from the official trust store
+
+Download the Amazon root certificate from the official trust store:
+
+```
+wget https://www.amazontrust.com/repository/AmazonRootCA1.pem -O root.pem
+```
+
+### Set up environment for examples
+
+1. Create and activate a Python virtual environment:
+
+```bash
+python3 -m venv .venv
+source .venv/bin/activate  # Linux, macOS
+# or
+.venv\Scripts\activate     # Windows
+```
+
+2. Install the required packages for running the examples:
+
+```bash
+pip install -r requirements.txt
+```
+
+### Run the code
+
+#### What the Examples Do
+
+The example demonstrates the following operations:
+
+- Opening a connection to an Aurora DSQL cluster
+- Creating a table
+- Inserting and querying data
+
+The example is designed to work with both admin and non-admin users:
+
+- When run as an admin user, it uses the `public` schema
+- When run as a non-admin user, it uses the `myschema` schema
+
+**Note:** running the example will use actual resources in your AWS account and may incur charges.
+
+The connection pool examples demonstrate:
+- Creating a connection pool for Aurora DSQL
+- Using async context managers for connection management
+- Performing database operations through the pool
+- Running multiple concurrent database operations
+- Using asyncio.gather() for parallel execution
+- Proper resource management with connection pools
+
+#### Environment Cluster Details
+
+Set environment variables for your cluster details:
+
+```bash
+# e.g. "admin"
+export CLUSTER_USER="<your user>"
+
+# e.g. "foo0bar1baz2quux3quuux4.dsql.us-east-1.on.aws"
+export CLUSTER_ENDPOINT="<your endpoint>"
+
+# e.g. "us-east-1"
+export REGION="<your region>"
+```
+
+#### Run the example:
+
+```bash
+# Run example directly
+python src/example.py
+
+# Run example using pytest
+pytest ./test/test_example.py
+
+# Run all using pytest
+pytest ./test
+```
+
+The examples contain comments explaining the code and the operations being performed.
+
+## Additional resources
+
+* [Amazon Aurora DSQL Documentation](https://docs.aws.amazon.com/aurora-dsql/latest/userguide/what-is-aurora-dsql.html)
+* [Amazon Aurora DSQL Python Connector Documentation](https://docs.aws.amazon.com/aurora-dsql/latest/userguide/SECTION_program-with-dsql-connector-for-python.html)
+* [Asyncpg Documentation](https://magicstack.github.io/asyncpg/current/)
+* [AWS SDK for Python (Boto3) Documentation](https://boto3.amazonaws.com/v1/documentation/api/latest/index.html)
+
+---
+
+Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
+
+SPDX-License-Identifier: MIT-0

python/asyncpg/pyproject.toml

@@ -0,0 +1,4 @@
+[tool.pytest.ini_options]
+pythonpath = [
+  "src"
+]

python/asyncpg/requirements.txt

@@ -0,0 +1,5 @@
+aurora-dsql-python-connector>=0.2.0
+boto3>=1.35.74
+asyncpg>=0.30.0
+pytest>=8.0
+pytest-asyncio>=1.2.0

python/asyncpg/src/example.py

@@ -0,0 +1,101 @@
+"""
+Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
+SPDX-License-Identifier: MIT-0
+"""
+
+import asyncio
+import os
+
+import aurora_dsql_asyncpg as dsql
+
+
+async def create_connection(cluster_user, cluster_endpoint, region):
+    ssl_cert_path = "./root.pem"
+    if not os.path.isfile(ssl_cert_path):
+        raise FileNotFoundError(f"SSL certificate file not found: {ssl_cert_path}")
+
+    conn_params = {
+        "database": "postgres",
+        "user": cluster_user,
+        "host": cluster_endpoint,
+        "port": 5432,
+        "region": region,
+        "ssl": "verify-full",
+        "sslrootcert": ssl_cert_path,
+    }
+
+    # Make a connection to the cluster
+    conn = await dsql.connect(**conn_params)
+
+    if cluster_user == "admin":
+        schema = "public"
+    else:
+        schema = "myschema"
+
+    try:
+        await conn.execute(f"SET search_path = {schema};")
+    except Exception as e:
+        await conn.close()
+        raise e
+
+    return conn
+
+
+async def exercise_connection(conn):
+    await conn.execute(
+        """
+        CREATE TABLE IF NOT EXISTS owner(
+            id uuid NOT NULL DEFAULT gen_random_uuid(),
+            name varchar(30) NOT NULL,
+            city varchar(80) NOT NULL,
+            telephone varchar(20) DEFAULT NULL,
+            PRIMARY KEY (id))
+            """
+    )
+
+    # Insert some rows
+    await conn.execute(
+        "INSERT INTO owner(name, city, telephone) VALUES($1, $2, $3)",
+        "John Doe",
+        "Anytown",
+        "555-555-1999",
+    )
+
+    row = await conn.fetchrow("SELECT * FROM owner WHERE name=$1", "John Doe")
+
+    # Verify the result we got is what we inserted before
+    assert row[0] is not None
+    assert row[1] == "John Doe"
+    assert row[2] == "Anytown"
+    assert row[3] == "555-555-1999"
+
+    # Clean up the table after the example. If we run the example again
+    # we do not have to worry about data inserted by previous runs
+    await conn.execute("DELETE FROM owner WHERE name = $1", "John Doe")
+
+
+async def main():
+    conn = None
+    try:
+        cluster_user = os.environ.get("CLUSTER_USER", None)
+        assert cluster_user is not None, "CLUSTER_USER environment variable is not set"
+
+        cluster_endpoint = os.environ.get("CLUSTER_ENDPOINT", None)
+        assert (
+            cluster_endpoint is not None
+        ), "CLUSTER_ENDPOINT environment variable is not set"
+
+        region = os.environ.get("REGION", None)
+        assert region is not None, "REGION environment variable is not set"
+
+        conn = await create_connection(cluster_user, cluster_endpoint, region)
+        await exercise_connection(conn)
+    finally:
+        if conn is not None:
+            await conn.close()
+
+    print("Connection exercised successfully")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

python/asyncpg/src/example_with_connection_pool.py

@@ -0,0 +1,64 @@
+"""
+Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
+SPDX-License-Identifier: MIT-0
+"""
+
+import asyncio
+import os
+
+import aurora_dsql_asyncpg as dsql
+
+
+async def connect_with_pool(cluster_user, cluster_endpoint, region):
+    ssl_cert_path = "./root.pem"
+    if not os.path.isfile(ssl_cert_path):
+        raise FileNotFoundError(f"SSL certificate file not found: {ssl_cert_path}")
+
+    pool_params = {
+        "database": "postgres",
+        "user": cluster_user,
+        "host": cluster_endpoint,
+        "port": 5432,
+        "region": region,
+        "ssl": "verify-full",
+        "sslrootcert": ssl_cert_path,
+        "min_size": 2,
+        "max_size": 5,
+    }
+
+    pool = await dsql.create_pool(**pool_params)
+    try:
+        async with pool.acquire() as conn:
+            result = await conn.fetchval("SELECT 1")
+            assert result == 1
+    finally:
+        await pool.close()
+
+
+async def main():
+    try:
+        cluster_user = os.environ.get("CLUSTER_USER", None)
+        assert cluster_user is not None, "CLUSTER_USER environment variable is not set"
+
+        cluster_endpoint = os.environ.get("CLUSTER_ENDPOINT", None)
+        assert (
+            cluster_endpoint is not None
+        ), "CLUSTER_ENDPOINT environment variable is not set"
+
+        region = os.environ.get("REGION", None)
+        assert region is not None, "REGION environment variable is not set"
+
+        ssl_cert_path = "./root.pem"
+        if not os.path.isfile(ssl_cert_path):
+            raise FileNotFoundError(f"SSL certificate file not found: {ssl_cert_path}")
+
+        await connect_with_pool(cluster_user, cluster_endpoint, region)
+
+    finally:
+        pass
+
+    print("Pool exercised successfully")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())