The Databricks SQL Connector for Python allows you to develop Python applications that connect to Databricks clusters and SQL warehouses. It is a Thrift-based client with no dependencies on ODBC or JDBC. It conforms to the Python DB API 2.0 specification and exposes a SQLAlchemy dialect for use with tools like pandas and alembic which use SQLAlchemy to execute DDL.

This connector uses Arrow as the data-exchange format, and supports APIs to directly fetch Arrow tables. Arrow tables are wrapped in the ArrowQueue class to provide a natural API to get several rows at a time.

You are welcome to file an issue here for general use cases. You can also contact Databricks Support here.

Python 3.7 or above is required.

For the latest documentation, see

• Databricks
• Azure Databricks

Install the library with pip install databricks-sql-connector

Note: Don't hard-code authentication secrets into your Python. Use environment variables

export DATABRICKS_HOST=********.databricks.com
export DATABRICKS_HTTP_PATH=/sql/1.0/endpoints/****************
export DATABRICKS_TOKEN=dapi********************************

Example usage:

import os
from databricks import sql

host = os.getenv("DATABRICKS_HOST")
http_path = os.getenv("DATABRICKS_HTTP_PATH")
access_token = os.getenv("DATABRICKS_ACCESS_TOKEN")

connection = sql.connect(
  server_hostname=host,
  http_path=http_path,
  access_token=access_token)

cursor = connection.cursor()

cursor.execute('SELECT * FROM RANGE(10)')
result = cursor.fetchall()
for row in result:
  print(row)

cursor.close()
connection.close()

In the above example:

• server-hostname is the Databricks instance host name.
• http-path is the HTTP Path either to a Databricks SQL endpoint (e.g. /sql/1.0/endpoints/1234567890abcdef), or to a Databricks Runtime interactive cluster (e.g. /sql/protocolv1/o/1234567890123456/1234-123456-slid123)
• personal-access-token is the Databricks Personal Access Token for the account that will execute commands and queries

See CONTRIBUTING.md

Apache License 2.0