Skip to main content

droughty is an analytics engineering toolkit, helping keep your workflow dry.

Project description

#### droughty. ## adjective, drought·i·er, drought·i·est. ## dry.

Droughty helps keep your workflow ah hem dry


What is droughty?

droughty is an analytics engineering toolkit. It takes warehouse metadata and outputs semantic files.

Current tools and supported platforms are:

  • lookml - generates a lkml with views, explores and measures from a warehouse schema
  • dbt - generates a base schema from specified warehouse schemas. Includes standard testing routines
  • dbml - generates an ERD based on the warehouse layer of your warehouse. Includes pk, fk relationships
  • cube - generates a cube schema including dimensions, integrations and meassures

The purpose of this project is to automate the repetitive, dull elements of analytics engineering in the modern data stack. It turns out this also leads to cleaner projects, less human error and increases the likelihood of the basics getting done...

Documentation

Installation, configuration and usage documentation can be found on ReadTheDocs

Installation

droughty is available through pip:

pip install droughty

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

droughty-0.8.1.tar.gz (71.5 kB view hashes)

Uploaded Source

Built Distribution

droughty-0.8.1-py3-none-any.whl (60.6 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page