cap-databricks-sql-connector 4.0.5a1
Databricks SQL Connector for Python
License: Apache-2.0
Requires Python: <4.0.0,>=3.8.0

# Databricks SQL Connector for Python

[![PyPI](https://img.shields.io/pypi/v/databricks-sql-connector?style=flat-square)](https://pypi.org/project/databricks-sql-connector/)
[![Downloads](https://pepy.tech/badge/databricks-sql-connector)](https://pepy.tech/project/databricks-sql-connector)

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](https://www.python.org/dev/peps/pep-0249/).

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](https://arrow.apache.org/docs/python/index.html) is required to enable this and use these APIs, you can install it via  `pip install pyarrow` or `pip install databricks-sql-connector[pyarrow]`.

You are welcome to file an issue here for general use cases. You can also contact Databricks Support [here](help.databricks.com).

## Requirements

Python 3.8 or above is required.

## Documentation

For the latest documentation, see

- [Databricks](https://docs.databricks.com/dev-tools/python-sql-connector.html)
- [Azure Databricks](https://docs.microsoft.com/en-us/azure/databricks/dev-tools/python-sql-connector)

## 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]`


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

Example usage:
```python
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](https://docs.databricks.com/en/dev-tools/auth/oauth-u2m.html) 
> 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.

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

- Github repository [databricks-sqlalchemy github](https://github.com/databricks/databricks-sqlalchemy)
- PyPI [databricks-sqlalchemy pypi](https://pypi.org/project/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](CONTRIBUTING.md)

## License

[Apache License 2.0](LICENSE)