SSL Certificate Error Issue before and after Python 3.11.13 with Databricks Instance

Commencez par la configuration fournie dans pyproject.toml et le point d’entrée main.py, puis exécutez la commande uv dans un environnement Databricks qui nécessite un certificat SSL avec les versions de Python indiquées. Utilisez results.log et le SSLVerificationError signalé pour comparer le comportement ; le travail est terminé lorsque la requête d’exemple renvoie le nombre de lignes de sa table sur les versions concernées.

Overview

When I try to use different versions of python to connect to a databricks environment, I get an SSL certificate issue. It appears to be resolved in 3.11.13 but is broken in versions below (e.g. 3.11.11) and above (3.12, 3.13). Please note that you will need to test with an environment that require an ssl certificate.

Recreation Steps

1. Setup environment as below
2. Run script

uv run main.py --python 3.11.11

Expected - The script will output a row count for the specific table
Actual - An SSLVerificationError will happen

Hardware Info

• macOS - 15.5
• chip - Apple M4 Pro

Affected Python Version

• 3.11.11, <3.11.13
• > 3.11.13

Setup

setup uv project

uv init dbks_testing --python

sample uv project template

[project]
name = "dbks-testing"
version = "0.1.0"
description = "Add your description here"
readme = "README.md"
requires-python = ">=3.11"
dependencies = [
    "databricks-sqlalchemy>=2.0.6",
]

script to verify issue

you will need to change the table variable to a valid table for your schema

def main():

    access_token = os.getenv("DATABRICKS_TOKEN")
    server_hostname = os.getenv("DATABRICKS_SERVER_HOSTNAME")
    http_path = os.getenv("DATABRICKS_HTTP_PATH")
    catalog = os.getenv("DATABRICKS_CATALOG")
    schema = os.getenv("DATABRICKS_SCHEMA")

    engine = create_engine(
        url=f"databricks://token:{access_token}@{server_hostname}?" +
            f"http_path={http_path}&catalog={catalog}&schema={schema}"
    )

    session = Session(engine)

    account = Table(table, MetaData(schema=schema), autoload_with=engine)

    print(f"Table count for {account.name} is {session.query(account).count()}")


if __name__ == "__main__":

    # add logging
    logging.getLogger("databricks.sql").setLevel(logging.DEBUG)
    logging.basicConfig(filename="results.log",
                        level=logging.DEBUG,
                        format="%(asctime)s - %(name)s - %(levelname)s - %(message)s")

    # set variables need for main
    table = "account"

    main()

Run command in project

uv run main.py --python 3.11.11