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.
The dbt-database-adapter-scaffold
package is a user-friendly interactive way to build out a new adapter.
dbt-core
use semver to denote compatibility and intends to maintain compatibility for database adapters of the same major and minor version. (i.e. any patch version for a given major and minor version) This is a convention used by existing plugins that database adapter plugin developers can opt into during project setup. When generating a scaffold, the project version will include the same major and minor version of the latest stable version ofdbt-core
.
cd
to where you'd like your adapter to live. the scaffold will create a new folder for your adapter, e.g.dbt-{myadapter}
. This will be the folder to make into a Git repository- setup a virtual env
python3 -m venv env
- choose how you would like to run the
dbt-database-adapter-scaffold
- Running from Github (recommended) - Running Locally - Once you have generated your adapter please continue by using the
README
located within the repo.
- Install cookiecutter with
pip install cookiecutter
(guide for alt install methods) - run
cookiecutter gh:dbt-labs/dbt-database-adapter-scaffold
in console
- Install cookiecutter
- Fork and clone this repo
- Once cloned run cookiecutter
path_to_this_repo/.
- Be part of the conversation in the dbt Community Slack
- 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.