v
dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
dbt is the T in ELT. Organize, cleanse, denormalize, filter, rename, and pre-aggregate the raw data in your warehouse so that it's ready for analysis.
This repo contains the base code to help you start to build out your dbt-bqcost adapter plugin, for more information on how to build out the adapter please follow the docs
** Note ** this README is meant to be replaced with what information would be required to use your adpater once your at a point todo so.
** Note **
This adapter plugin follows semantic versioning. The first version of this plugin is v1.3.0, in order to be compatible with dbt Core v1.3.0.
It's also brand new! For dbt_bqcost-specific functionality, we will aim for backwards-compatibility wherever possible. We are likely to be iterating more quickly than most major-version-1 software projects. To that end, backwards-incompatible changes will be clearly communicated and limited to minor versions (once every three months).
- run
pip install -r dev-requirements.txt. - cd directory into the
dbt-coreyou'd like to be testing against and runmake dev.
- run
git init. - Connect your lcoal code to a Github repo.
- Be part of the conversation in the dbt Community Slack
- If one doesn't exist feel free to request a #db-dbt_bqcost channel be made in the #channel-requests on dbt community slack channel.
- Read more on the dbt Community Discourse
- Want to report a bug or request a feature? Let us know on Slack, or open an issue
- Want to help us build dbt? Check out the Contributing Guide
Everyone interacting in the dbt project's codebases, issue trackers, chat rooms, and mailing lists is expected to follow the dbt Code of Conduct.