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.github/ISSUE_TEMPLATE/bug_report.yml

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.github/ISSUE_TEMPLATE/config.yml

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url: mailto:[email protected]
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about: Are you using dbt Cloud? Contact our support team for help!
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- name: Participate in Discussions
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url: https://github.com/dbt-labs/dbt-snowflake/discussions
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about: Do you have a Big Idea for dbt-snowflake? Read open discussions, or start a new one
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url: https://github.com/dbt-labs/dbt-adapters/discussions
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about: Do you have a Big Idea for dbt-athena? Read open discussions, or start a new one
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- name: Create an issue for dbt-athena
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url: https://github.com/dbt-labs/dbt-adapters/issues/new/choose
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about: Report a bug or request a feature for dbt-athena
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- name: Create an issue for dbt-core
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url: https://github.com/dbt-labs/dbt-core/issues/new/choose
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about: Report a bug or request a feature for dbt-core

.github/ISSUE_TEMPLATE/feature-request.yml

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.github/ISSUE_TEMPLATE/regression-report.yml

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.github/PULL_REQUEST_TEMPLATE.md

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# Description
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<!--- Add a little description on what you plan to tackle with this PR -->
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<!--- Add resolve #issue-number in case you resolve an open issue -->
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## Models used to test - Optional
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<!--- Add here the models that you use to test the changes -->
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## Checklist
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- [ ] You followed [contributing section](https://github.com/dbt-athena/dbt-athena#contributing)
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- [ ] You kept your Pull Request small and focused on a single feature or bug fix.
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- [ ] You added unit testing when necessary
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- [ ] You added functional testing when necessary
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<!---
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This repository has moved into [dbt-labs/dbt-adapters](https://www.github.com/dbt-labs/dbt-adapters).
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-->

.github/dependabot.yml

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CONTRIBUTING.md

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# Contributing
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## Requirements
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* Python>=3.9 - [docs](https://www.python.org/)
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* Hatch - [docs](https://hatch.pypa.io/dev/)
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## Getting started
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### Hatch
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This repository uses `hatch` as its primary development tool.
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`hatch` will store its virtual environments in its own user space unless you configure it.
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We strongly recommend that you configure `hatch` to store its virtual environments in an explicit location.
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This has two benefits:
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* this path is predictable and easily discoverable, making it much easier to use with IDEs
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* the default environment uses a hash for the name whereas the explicit environment will use
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a predictable and human-readable name
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For example, we configure `hatch` to store its virtual environments in the project itself (first option below).
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This is akin to running `python -m venv venv` from the project root.
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Many folks prefer to store virtual environments in a central location separate from the project (second option below).
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```toml
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# MacOS : ~/Library/Application Support/hatch/config.toml
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# Windows : %USERPROFILE%\AppData\Local\hatch\config.toml
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# Unix : ~.config/hatch/config.toml
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# this will create the virtual environment at `dbt-athena/dbt-athena/.hatch/dbt-athena
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[dirs.env]
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virtual = ".hatch"
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# this will create the virtual environment at `~/.hatch/dbt-athena`
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[dirs.env]
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virtual = "~/.hatch"
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```
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You can find the full docs [here](https://hatch.pypa.io/dev/config/hatch/) if you'd like to learn more about `hatch`.
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### Initial setup
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You will need to perform these steps the first time you contribute.
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If you plan on contributing in the future (we would really appreciate that!),
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most of this should persist and be reusable at that point in time.
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<!-- markdownlint-disable MD013 -->
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* Fork the `dbt-athena` repo into your own user space on GitHub - [docs](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/fork-a-repo)
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* Install `hatch` on your local machine - [docs](https://hatch.pypa.io/dev/install/)
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* Clone the fork to your local machine - [docs](https://docs.github.com/en/repositories/creating-and-managing-repositories/cloning-a-repository)
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* Navigate to the `dbt-athena` package directory
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* There are two packages in this repository. Don't worry about `dbt-athena-community`,
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it will automatically remain in sync with `dbt-athena`
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* Setup your development environment with `hatch run setup`:
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1. Create a `hatch` virtual environment
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2. Install all dependencies
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3. Install pre-commit hooks
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4. Create a `test.env` stub file (formerly `.env`)
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* Adjust the `test.env` file by configuring the environment variables to match your Athena development environment
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<!-- markdownlint-restore -->
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```shell
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# install `hatch`
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pip install hatch
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# clone your fork
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git clone https://github.com/<user>/dbt-athena
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# navigate to the dbt-athena package
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cd dbt-athena
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# setup your development environment (formerly `make setup`)
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hatch run setup
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```
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## Running tests and checks
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There are many checks that are collectively referred to as Code Quality checks as well as 2 different types of testing:
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* **code quality checks**: these checks include static analysis, type checking, and other code quality assurances
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* **unit testing**: these tests are fast tests that don't require a platform connection
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* **integration testing**: these tests are more thorough and require an AWS account with an Athena instance configured
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* Details of the Athena instance also need to be configured in your `test.env` file
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These tests and checks can be run as follows:
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```shell
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# run all pre-commit checks
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hatch run code-quality
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# run unit tests (formerly `make unit_test`)
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hatch run unit-tests
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# run integration tests (formerly `make integration_test`)
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hatch run integration-tests
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# run unit tests and integration tests, formerly `make test`
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hatch run all-tests
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# run specific integration tests
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hatch run integration-tests tests/functional/my/test_file.py
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```
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## Submitting a pull request
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* Create a commit with your changes and push them back up to your fork (e.g. `https://github.com/<user>/dbt-athena`)
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* Create a [pull request](https://github.com/dbt-labs/dbt-athena/compare) on GitHub - [docs](https://docs.github.com/en/github/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/creating-a-pull-request-from-a-fork)
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* The pull request title and commit messages should adhere to [conventional commits](https://www.conventionalcommits.org)
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* The pull request body should describe _motivation_
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<!-- markdownlint-restore -->
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### General Guidelines
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* Keep your Pull Request small and focused on a single feature or bug fix
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* Make sure your change is well tested
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* Add new tests for completely new features or bug fixes
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* Add scenarios to existing tests if extending a feature
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* Make sure your change is well documented
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* Mention when something is not obvious, or is being used for a specific purpose
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* Provide a link to the GitHub bug in the docstring when writing a new test demonstrating the bug
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* Provide a clear description in your pull request to allow the reviewer to understand the context of your changes
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* Use a "self-review" to walk the reviewer through your thought process in a specific area
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* Use a "self-review" to ask a question about how to handle a specific problem
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* Use a draft pull request during development and mark it as Ready for Review when you're ready
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* Ideally CI is also passing at this point, but you may also be looking for feedback on how to resolve an issue
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This repository has moved into [dbt-labs/dbt-adapters](https://www.github.com/dbt-labs/dbt-adapters).
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Please refer to that repo for a guide on how to contribute to `dbt-athena`.

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