dataos-cookiecutter 0.0.5

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 Board 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 create -n <lens2_name> -d <lens2_dir_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 of table.
   • create: Creates checks YAML files and stores them in the checks folder.

   # Validate dimensions in Lens2 tables
   lens2 checks schema-check -n tables/views '(comma separated)'
   
   # Create checks YAML files
   lens2 checks create -n tables/views '(comma separated)'
   

3. lens2 board: This command provides two subcommands for Board related tasks:

   • create: Creates View Board YAML made public in Lens2 and stores files in the boards/view_name folder.
   • start: Uses the generated Board content and starts Board to explore. This command only requires a view name (not comma separated values).

   # Create Board dashboard YAML for Lens2 views
   lens2 board create -n views '(comma separated)'
   
   # Start Board with generated content of View
   lens2 board start -n view_name