Databricks SQL Connector for Python
Project description
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 which 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
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-hostnameis the Databricks instance host name.http-pathis 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-tokenis the Databricks Personal Access Token for the account that will execute commands and queries
Contributing
See CONTRIBUTING.md
License
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