On Windows 11 connect to local PostgreSQL using Python and GoogleCloudPlatform (Google Cloud Run & Google Cloud Postgresql) sqlalchemy

• My applications are running on Google Cloud Run.
• They are all written in Python.
• My databases are located in Google Cloud SQL for PostgreSQL.

When I run the application on my local Windows 11 machine I want to use my local PostgreSQL instance, not the one in Google Cloud PostgreSQL.

I have downloaded the following example provided by Google that I am trying to run:

https://github.com/GoogleCloudPlatform/python-docs-samples/tree/6982717f255e87f3e2f1797ac3469f088b9b8693/cloud-sql/postgres/sqlalchemy

The example works on Google Cloud Run, but on my local Windows 11 machine I get the following error:

sqlalchemy.exc.OperationalError: (pytds.tds_base.LoginError) ("Cannot connect to server '127.1.1.0': [WinError 10061] No connection could be made because the target machine actively refused it", ConnectionRefusedError(10061, 'No connection could be made because the target machine actively refused it', None, 10061, None))

The enviroment variables are set correctly in PyCharm:

The database exists in PostgreSQL:

Why am I getting the error and how can it be fixed?

connect_tcp.py

# Copyright 2022 Google LLC
#
# Licensed 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.

# TODO (https://github.com/GoogleCloudPlatform/python-docs-samples/issues/8253): remove old region tags
# [START cloud_sql_postgres_sqlalchemy_connect_tcp]
# [START cloud_sql_postgres_sqlalchemy_sslcerts]
# [START cloud_sql_postgres_sqlalchemy_connect_tcp_sslcerts]
import os
import ssl

import sqlalchemy


# connect_tcp_socket initializes a TCP connection pool
# for a Cloud SQL instance of Postgres.
def connect_tcp_socket() -> sqlalchemy.engine.base.Engine:
    # 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.
    db_host = os.environ["INSTANCE_HOST"]  # e.g. '127.0.0.1' ('172.17.0.1' if deployed to GAE Flex)
    db_user = os.environ["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'
    db_port = os.environ["DB_PORT"]  # e.g. 5432

    # [END cloud_sql_postgres_sqlalchemy_connect_tcp]
    connect_args = {}
    # For deployments that connect directly to a Cloud SQL instance without
    # using the Cloud SQL Proxy, configuring SSL certificates will ensure the
    # connection is encrypted.
    if os.environ.get("DB_ROOT_CERT"):
        db_root_cert = os.environ["DB_ROOT_CERT"]  # e.g. '/path/to/my/server-ca.pem'
        db_cert = os.environ["DB_CERT"]  # e.g. '/path/to/my/client-cert.pem'
        db_key = os.environ["DB_KEY"]  # e.g. '/path/to/my/client-key.pem'

        ssl_context = ssl.SSLContext()
        ssl_context.verify_mode = ssl.CERT_REQUIRED
        ssl_context.load_verify_locations(db_root_cert)
        ssl_context.load_cert_chain(db_cert, db_key)
        connect_args["ssl_context"] = ssl_context

    # [START cloud_sql_postgres_sqlalchemy_connect_tcp]
    pool = sqlalchemy.create_engine(
        # Equivalent URL:
        # postgresql+pg8000://<db_user>:<db_pass>@<db_host>:<db_port>/<db_name>
        sqlalchemy.engine.url.URL.create(
            drivername="postgresql+pg8000",
            username=db_user,
            password=db_pass,
            host=db_host,
            port=db_port,
            database=db_name,
        ),
        # [END cloud_sql_postgres_sqlalchemy_connect_tcp]
        connect_args=connect_args,
        # [START cloud_sql_postgres_sqlalchemy_connect_tcp]
        # [START_EXCLUDE]
        # [START cloud_sql_postgres_sqlalchemy_limit]
        # Pool size is the maximum number of permanent connections to keep.
        pool_size=5,
        # Temporarily exceeds the set pool_size if no connections are available.
        max_overflow=2,
        # The total number of concurrent connections for your application will be
        # a total of pool_size and max_overflow.
        # [END cloud_sql_postgres_sqlalchemy_limit]

        # [START cloud_sql_postgres_sqlalchemy_backoff]
        # SQLAlchemy automatically uses delays between failed connection attempts,
        # but provides no arguments for configuration.
        # [END cloud_sql_postgres_sqlalchemy_backoff]

        # [START cloud_sql_postgres_sqlalchemy_timeout]
        # 'pool_timeout' is the maximum number of seconds to wait when retrieving a
        # new connection from the pool. After the specified amount of time, an
        # exception will be thrown.
        pool_timeout=30,  # 30 seconds
        # [END cloud_sql_postgres_sqlalchemy_timeout]

        # [START cloud_sql_postgres_sqlalchemy_lifetime]
        # 'pool_recycle' is the maximum number of seconds a connection can persist.
        # Connections that live longer than the specified amount of time will be
        # re-established
        pool_recycle=1800,  # 30 minutes
        # [END cloud_sql_postgres_sqlalchemy_lifetime]
        # [END_EXCLUDE]
    )
    return pool

# [END cloud_sql_postgres_sqlalchemy_connect_tcp_sslcerts]
# [END cloud_sql_postgres_sqlalchemy_sslcerts]
# [END cloud_sql_postgres_sqlalchemy_connect_tcp]