dbt_census_utils is a package with 6 macros that are handy for data activation, such as formatting names for Facebook or Google Ads, or telling whether a user's email is personal, internal, or from the same domain as other users.
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
[X] The package includes a README which explains how to get started with the package and customise its behaviour
[X] The README indicates which data warehouses/platforms are expected to work with this package
Customisability
[X] The package uses ref or source, instead of hard-coding table references.
Packages for data transformation (delete if not relevant):
The package only contains macros, so this isn't relevant.
Dependencies
Dependencies on dbt Core
[X] The package has set a supported require-dbt-version range in dbt_project.yml. Example: A package which depends on functionality added in dbt Core 1.2 should set its require-dbt-version property to [">=1.2.0", "<2.0.0"].
Dependencies on other packages defined in packages.yml:
[X] Dependencies are imported from the dbt Package Hub when available, as opposed to a git installation.
[X] Dependencies contain the widest possible range of supported versions, to minimise issues in dependency resolution.
[X] In particular, dependencies are not pinned to a patch version unless there is a known incompatibility.
Interoperability
[X] The package does not override dbt Core behaviour in such a way as to impact other dbt resources (models, tests, etc) not provided by the package.
[X] The package uses the cross-database macros built into dbt Core where available, such as {{ dbt.except() }} and {{ dbt.type_string() }}.
[X] The package disambiguates its resource names to avoid clashes with nodes that are likely to already exist in a project. For example, packages should not provide a model simply called users.
Our seeds are prefixed with census_utils.
Versioning
[X] (Required): The package's git tags validates against the regex defined in version.py
We use v0.1.0 for the tag, it looks like you just strip out the v.
[X] The package's version follows the guidance of Semantic Versioning 2.0.0. (Note in particular the recommendation for production-ready packages to be version 1.0.0 or above)
We use 0.1.0 for the version.
Added dbt_census_utils
Description
dbt_census_utils is a package with 6 macros that are handy for data activation, such as formatting names for Facebook or Google Ads, or telling whether a user's email is personal, internal, or from the same domain as other users.
Link to your package's repository: https://github.com/sutrolabs/dbt_census_utils
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):
The package only contains macros, so this isn't relevant.
Dependencies
Dependencies on dbt Core
require-dbt-versionrange indbt_project.yml. Example: A package which depends on functionality added in dbt Core 1.2 should set itsrequire-dbt-versionproperty to[">=1.2.0", "<2.0.0"].Dependencies on other packages defined in packages.yml:
Interoperability
{{ dbt.except() }}and{{ dbt.type_string() }}.users. Our seeds are prefixed with census_utils.Versioning