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

Inizia con la configurazione fornita in pyproject.toml e il punto di ingresso main.py, quindi esegui il comando uv in un ambiente Databricks che richiede un certificato SSL nelle versioni di Python elencate. Usa results.log e l’SSLVerificationError riportato per confrontare il comportamento; il lavoro è completato quando la query di esempio restituisce il numero di righe della relativa tabella nelle versioni interessate.

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