Closed Matts52 closed 1 month ago
Looks good! Please note that in your readme when you say
To import this package into your dbt project, add the following to either the packages.yml or dbt_project.yml file:
It should actually be
packages.yml
ordependencies.yml
files - you can't specify packages in dbt_project.yml.
Great, thanks for catching that, updated!
Description
This package allows users to perform common machine learning preprocessing techniques inline with their SQL select statements, only requiring model references when absolutely required.
Techniques that can be performed inline include:
This allows for those doing their machine learning preprocessing in dbt to do so in a more semantically followable, interchangeable, and flexible fashion
Link to your package's repository: https://github.com/Matts52/dbt-ml-inline-preprocessing
Checklist
This checklist is a cut down version of the best practices that we have identified as the package hub has grown. Although meeting these checklist items is not a prerequisite to being added to the Hub, we have found that packages which don't conform provide a worse user experience.
First run experience
Customisability
Packages for data transformation (delete if not relevant):
Dependencies
Dependencies on dbt Core
require-dbt-version
range indbt_project.yml
. Example: A package which depends on functionality added in dbt Core 1.2 should set itsrequire-dbt-version
property to[">=1.2.0", "<2.0.0"]
.Dependencies on other packages defined in packages.yml:
Interoperability
{{ dbt.except() }}
and{{ dbt.type_string() }}
.users
.Versioning