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README updates (#9)
* Add license and contributing sections to README. * Add environment setup docs to CONTRIBUTING * Clarify example of connection details in example * Add badges from pypi * Explicitly call out Python 3.7 or above is needed
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‎CONTRIBUTING.md‎

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# Contributing
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To contribute to this repository, fork it and send pull requests.
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## Set up your environment
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This project uses [Poetry](https://python-poetry.org/) for dependency management, tests, and linting.
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1. Clone this respository
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2. Run `poetry install`
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### Unit Tests
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We use [Pytest](https://docs.pytest.org/en/7.1.x/) as our test runner. Invoke it with `poetry run pytest`, all other arguments are passed directly to `pytest`.
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#### All tests
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```bash
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poetry run pytest tests
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```
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#### Only a specific test file
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```bash
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poetry run pytest tests/tests.py
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```
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#### Only a specific method
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```bash
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poetry run pytest tests/tests.py::ClientTestSuite::test_closing_connection_closes_commands
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```
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### Code formatting
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This project uses [Black](https://pypi.org/project/black/).
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```
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poetry run black src
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```
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## Pull Request Process
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1. Update the [CHANGELOG.md](README.md) or similar documentation with details of changes you wish to make, if applicable.
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2. Add any appropriate tests.
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3. Make your code or other changes.
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4. Review guidelines such as
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[How to write the perfect pull request][github-perfect-pr], thanks!
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[github-perfect-pr]: https://blog.github.com/2015-01-21-how-to-write-the-perfect-pull-request/

‎README.md‎

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# Databricks SQL Connector for Python
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[![PyPI](https://img.shields.io/pypi/v/databricks-sql-connector?style=flat-square)](https://pypi.org/project/databricks-sql-connector/)
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[![Downloads](https://pepy.tech/badge/databricks-sql-connector)](https://pepy.tech/project/databricks-sql-connector)
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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/).
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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.
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You are welcome to file an issue here for general use cases. You can also contact Databricks Support [here](help.databricks.com).
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# Documentation
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## Requirements
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Python 3.7 or above is required.
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## Documentation
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For the latest documentation, see
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from databricks import sql
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connection = sql.connect(
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server_hostname='<server-hostname>',
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http_path='<http-path>',
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access_token='<personal-access-token>')
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server_hostname='********.databricks.com',
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http_path='/sql/1.0/endpoints/****************',
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access_token='dapi********************************')
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cursor = connection.cursor()
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connection.close()
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```
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Where:
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- `<server-hostname>` is the Databricks instance host name.
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- `<http-path>` is the HTTP Path either to a Databricks SQL endpoint (e.g. /sql/1.0/endpoints/1234567890abcdef),
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or to a Databricks Runtime interactive cluster (e.g. /sql/protocolv1/o/1234567890123456/1234-123456-slid123)
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- `<personal-access-token>` is a HTTP Bearer access token, e.g. a Databricks Personal Access Token.
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In the above example:
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- `server-hostname` is the Databricks instance host name.
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- `http-path` is the HTTP Path either to a Databricks SQL endpoint (e.g. /sql/1.0/endpoints/1234567890abcdef),
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or to a Databricks Runtime interactive cluster (e.g. /sql/protocolv1/o/1234567890123456/1234-123456-slid123)
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- `personal-access-token` is the Databricks Personal Access Token for the account that will execute commands and queries
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## Contributing
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See [CONTRIBUTING.md](CONTRIBUTING.md)
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## License
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[Apache License 2.0](LICENSE)

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