Skip to main content

Databricks SQL Connector for Python

Project description

Databricks SQL Connector for Python

PyPI Downloads

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.

This connector uses Arrow as the data-exchange format, and supports APIs (e.g. fetchmany_arrow) 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. PyArrow is required to enable this and use these APIs, you can install it via pip install pyarrow or pip install databricks-sql-connector[pyarrow].

The connector includes built-in support for HTTP/HTTPS proxy servers with multiple authentication methods including basic authentication and Kerberos/Negotiate authentication. See docs/proxy.md and examples/proxy_authentication.py for details.

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

Requirements

Python 3.9 or above is required.

Documentation

For the latest documentation, see

Quickstart

Installing the core library

Install using pip install databricks-sql-connector

Installing the core library with PyArrow

Install using pip install databricks-sql-connector[pyarrow]

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

Example usage:

import os
from databricks import sql

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

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

cursor = connection.cursor()
cursor.execute('SELECT :param `p`, * FROM RANGE(10)', {"param": "foo"})
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)

Note: This example uses Databricks OAuth U2M to authenticate the target Databricks user account and needs to open the browser for authentication. So it can only run on the user's machine.

Transaction Support

The connector supports multi-statement transactions with manual commit/rollback control. Set connection.autocommit = False to disable autocommit mode, then use connection.commit() and connection.rollback() to control transactions.

For detailed documentation, examples, and best practices, see TRANSACTIONS.md.

SQLAlchemy

Starting from databricks-sql-connector version 4.0.0 SQLAlchemy support has been extracted to a new library databricks-sqlalchemy.

Quick SQLAlchemy guide

Users can now choose between using the SQLAlchemy v1 or SQLAlchemy v2 dialects with the connector core

  • Install the latest SQLAlchemy v1 using pip install databricks-sqlalchemy~=1.0
  • Install SQLAlchemy v2 using pip install databricks-sqlalchemy

Contributing

See CONTRIBUTING.md

License

Apache License 2.0

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

databricks_sql_connector-4.2.6.tar.gz (189.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

databricks_sql_connector-4.2.6-py3-none-any.whl (216.7 kB view details)

Uploaded Python 3

File details

Details for the file databricks_sql_connector-4.2.6.tar.gz.

File metadata

  • Download URL: databricks_sql_connector-4.2.6.tar.gz
  • Upload date:
  • Size: 189.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.2.0 CPython/3.12.3

File hashes

Hashes for databricks_sql_connector-4.2.6.tar.gz
Algorithm Hash digest
SHA256 65e59f08e55dcc563c05e02e2321d5171dd9482e5792328d99ac097377795d01
MD5 daf3e80c0884fd36d01ce527d7c03cd0
BLAKE2b-256 2b2f2c1a96b1d40d53dc9a0abf639c823895b6da76b1b5dc2f2230df2ae1aa6c

See more details on using hashes here.

File details

Details for the file databricks_sql_connector-4.2.6-py3-none-any.whl.

File metadata

File hashes

Hashes for databricks_sql_connector-4.2.6-py3-none-any.whl
Algorithm Hash digest
SHA256 61e0f425c990a0ec52c31165ea7dd0582cc0ad90c5fbd5fc9bea59bb38faeb00
MD5 7d2bf56b5d509b67bd89f48d3494e8ab
BLAKE2b-256 b74f4ea282af1e413d26e47b9e987c1cbef1d3fc599da81eb54ac2bf74b6b822

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page