Databricks SQL Connector for Python

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 that uses 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.

Requirements

Python 3.7 or above is required.

Documentation

For the latest documentation, see

• Databricks
• Azure Databricks

Quickstart

Install the library with pip install databricks-sql-connector

Example usage:

from databricks import sql

connection = sql.connect(
  server_hostname='********.databricks.com',
  http_path='/sql/1.0/endpoints/****************',
  access_token='dapi********************************')


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

Contributing

See CONTRIBUTING.md

License

Apache License 2.0