Tell us about your new package!
We are pleased to share the first dbt package from Tasman Analytics 🚀 This is our reconfigurable multi-touch attribution engine that we have deployed and refined as a private package over the past 2-3 years.
Generally speaking (and in the dbt guidance 😛) attribution doesn't make a good package due to the amount of business logic, however what makes our package a little different is that it can be reconfigured to support a multitude of different models, and run them concurrently using rulesets defined in seed files.
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.
[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):
[x] provide a mechanism (such as variables) to customise the location of source tables.
[x] do not assume database/schema names in sources.
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.
Versioning
[x] (Required): The package's git tags validates against the regex defined in version.py
[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)
sakce
commented
8 months ago
Description
Tell us about your new package! We are pleased to share the first dbt package from Tasman Analytics 🚀 This is our reconfigurable multi-touch attribution engine that we have deployed and refined as a private package over the past 2-3 years.
Generally speaking (and in the dbt guidance 😛) attribution doesn't make a good package due to the amount of business logic, however what makes our package a little different is that it can be reconfigured to support a multitude of different models, and run them concurrently using rulesets defined in seed files.
Link to your package's repository: https://github.com/TasmanAnalytics/tasman-dbt-mta
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-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.Versioning