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* 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
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!
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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