dataos-cookiecutter 0.0.3

Dataos Cookiecutter

dataos-cookiecutter

dataos-cookiecutter package provides commands to facilitate various tasks of Lens2, enabling users to efficiently generate templates, perform schema checks, generate data quality checks yaml, and create Rill YAML configurations.

Installation

You can install dataos-cookiecutter via pip:

pip install dataos-cookiecutter

Usage

dataos-cookiecutter offers several commands to simplify Lens2-related tasks:

1. lens2 lens: This command allows users to get started by creating a sample template along with folder structure, which they can modify based on their needs. It includes two flags:

   • -n lens_name: Specifies the name of the Lens.
   • -s source_type: Specifies the type of data source.

   lens2 lens create -n <lens_name> -s <source_type>
   

2. lens2 checks: This command provides two subcommands:

   • schema-check: Validates that all dimensions used in Lens2 tables are fulfilled by the SQL provided for them.
   • create: Creates checks YAML files and stores them in the checks folder.

   # Validate dimensions in Lens2 tables
   lens2 checks schema-check
   
   # Create checks YAML files
   lens2 checks create
   

3. lens2 rill: This command provides two subcommands for Rill-related tasks:

   • create: Creates Rill dashboard YAML for views made public in Lens2 and stores files in the Rill folder.
   • start: Uses the generated Rill content and starts Rill to initiate the dashboard.

   # Create Rill dashboard YAML for Lens2 views
   lens2 rill create
   
   # Start Rill with generated content
   lens2 rill start