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Generate LookML with Python code

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LookML Generator

https://travis-ci.org/symphonyrm/lookml-gen.svg?branch=master Documentation Status Updates

Programmatically generate LookML

Features

  • Generate LookML views programmatically
  • Include dimensions, dimension groups, filters, and measures in your views
  • Support Persistent Derived Tables (PDTs)
  • Write output to files or StringIO buffers

Quick Start

Install it:

pip install lookml-gen

Use it:

from lookmlgen.view import View
from lookmlgen.field import Dimension, DimensionGroup, Measure
from lookmlgen.base_generator import GeneratorFormatOptions

view_name = 'my_view'
v = View(view_name, sql_table_name='my_table')
v.add_field(Dimension('id', type='number', primary_key=True))
v.add_field(DimensionGroup('created'))
v.add_field(Dimension('name'))
v.add_field(Dimension('quantity', type='number'))
v.add_field(Measure('total_quantity', sql='${TABLE}.quantity', type='sum'))

with open('%s.view.lkml' % view_name, 'w') as f:
    v.generate_lookml(f, GeneratorFormatOptions(view_fields_alphabetical=False))

See it:

# STOP! This file was generated by an automated process.
# Any edits you make will be lost the next time it is
# re-generated.
view: my_view {
  sql_table_name: my_table ;;

  dimension: id {
    type: number
    primary_key: yes
    sql: ${TABLE}.id ;;
  }

  dimension_group: created {
    type: time
    timeframes: ["time", "date", "week", "month"]
    datatype: datetime
    sql: ${TABLE}.created ;;
  }

  dimension: name {
    sql: ${TABLE}.name ;;
  }

  dimension: quantity {
    type: number
    sql: ${TABLE}.quantity ;;
  }

  measure: total_quantity {
    type: sum
    sql: ${TABLE}.quantity ;;
  }
}

TODOs

Full LookML support is far from complete right now. At the moment only very basic aspects of Views and Fields are supported and there is no support for Explores yet. However, it does cover the most common functionality, including Persistent Derived Tables. The code can easily be extended and we'd love to get pull requests to fill out additional functionality.

Credits

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.

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