Connect using Cloud SQL Language Connectors

import com.zaxxer.hikari.HikariConfig;
import com.zaxxer.hikari.HikariDataSource;
import javax.sql.DataSource;

public class ConnectorConnectionPoolFactory extends ConnectionPoolFactory {

  // Note: Saving credentials in environment variables is convenient, but not
  // secure - consider a more secure solution such as
  // Cloud Secret Manager (https://cloud.google.com/secret-manager) to help
  // keep secrets safe.
  private static final String INSTANCE_CONNECTION_NAME =
      System.getenv("INSTANCE_CONNECTION_NAME");
  private static final String DB_USER = System.getenv("DB_USER");
  private static final String DB_PASS = System.getenv("DB_PASS");
  private static final String DB_NAME = System.getenv("DB_NAME");

  public static DataSource createConnectionPool() {
    // The configuration object specifies behaviors for the connection pool.
    HikariConfig config = new HikariConfig();

    // The following is equivalent to setting the config options below:
    // jdbc:sqlserver://;user=<DB_USER>;password=<DB_PASS>;databaseName=<DB_NAME>;
    // socketFactoryClass=com.google.cloud.sql.sqlserver.SocketFactory;
    // socketFactoryConstructorArg=<INSTANCE_CONNECTION_NAME>

    // See the link below for more info on building a JDBC URL for the Cloud SQL JDBC Socket Factory
    // https://github.com/GoogleCloudPlatform/cloud-sql-jdbc-socket-factory#creating-the-jdbc-url

    // Configure which instance and what database user to connect with.
    config
        .setDataSourceClassName("com.microsoft.sqlserver.jdbc.SQLServerDataSource");
    config.setUsername(DB_USER); // e.g. "root", "sqlserver"
    config.setPassword(DB_PASS); // e.g. "my-password"
    config.addDataSourceProperty("databaseName", DB_NAME);

    config.addDataSourceProperty("socketFactoryClass",
        "com.google.cloud.sql.sqlserver.SocketFactory");
    config.addDataSourceProperty("socketFactoryConstructorArg", INSTANCE_CONNECTION_NAME);

    // The Java Connector provides SSL encryption, so it should be disabled
    // at the driver level.
    config.addDataSourceProperty("encrypt", "false");

    // cloudSqlRefreshStrategy set to "lazy" is used to perform a
    // refresh when needed, rather than on a scheduled interval.
    // This is recommended for serverless environments to
    // avoid background refreshes from throttling CPU.
    config.addDataSourceProperty("cloudSqlRefreshStrategy", "lazy");

    // ... Specify additional connection properties here.
    // ...

    // Initialize the connection pool using the configuration object.
    return new HikariDataSource(config);
  }
}

import os

from google.cloud.sql.connector import Connector, IPTypes
import pytds

import sqlalchemy


def connect_with_connector() -> sqlalchemy.engine.base.Engine:
    """
    Initializes a connection pool for a Cloud SQL instance of SQL Server.

    Uses the Cloud SQL Python Connector package.
    """
    # Note: Saving credentials in environment variables is convenient, but not
    # secure - consider a more secure solution such as
    # Cloud Secret Manager (https://cloud.google.com/secret-manager) to help
    # keep secrets safe.

    instance_connection_name = os.environ[
        "INSTANCE_CONNECTION_NAME"
    ]  # e.g. 'project:region:instance'
    db_user = os.environ.get("DB_USER", "")  # e.g. 'my-db-user'
    db_pass = os.environ["DB_PASS"]  # e.g. 'my-db-password'
    db_name = os.environ["DB_NAME"]  # e.g. 'my-database'

    ip_type = IPTypes.PRIVATE if os.environ.get("PRIVATE_IP") else IPTypes.PUBLIC

    # initialize Cloud SQL Python Connector object
    connector = Connector(ip_type=ip_type, refresh_strategy="LAZY")

    connect_args = {}
    # If your SQL Server instance requires SSL, you need to download the CA
    # certificate for your instance and include cafile={path to downloaded
    # certificate} and validate_host=False. This is a workaround for a known issue.
    if os.environ.get("DB_ROOT_CERT"):  # e.g. '/path/to/my/server-ca.pem'
        connect_args = {
            "cafile": os.environ["DB_ROOT_CERT"],
            "validate_host": False,
        }

    def getconn() -> pytds.Connection:
        conn = connector.connect(
            instance_connection_name,
            "pytds",
            user=db_user,
            password=db_pass,
            db=db_name,
            **connect_args
        )
        return conn

    pool = sqlalchemy.create_engine(
        "mssql+pytds://",
        creator=getconn,
        # ...
    )
    return pool