Skip to main content

Set of tools for handling LookML files: a linter, updater, and grapher

Project description

LookML Tools

This repository contains some tools to handle best practices of a set of developers working on LookML files.

There are three tools:

  • LookML updater
  • LookML linter
  • LookML grapher


LookML updater

The first tool helps solve a problem of official definitions of dimensions and measures—such as in a business glossary—getting out of sync from some other system. The solution implemented here is to have a remote master list whose definitions are propagated to LookML. Thus, given some remote definition for a given LookML dimension, dimension_group, or measure, inject it in the LookML.

Full documentation is here.

LookML linter

The second tool helps us check that our LookML conforms to some given coding standards and LookML developer best practices. It runs a series of checks over our LookML files and reports which files, or which dimensions, dimension_groups, or measures, fail those checks.

Full documentation is here.

LookML grapher

The third tool creates a "network diagram" of the model - explore - view relationships and writes to an PNG image file. The code will also identify any orphans i.e. views not referenced by any models or explores.

Full documentation is here.


For the grapher, you will need to install grapviz:

brew install graphviz

For all tools, you will need to install dependencies:

  pip install -r requirements.txt

You can install the Python codebase of lookml-tools via pip:

  pip install lookml-tools

One user reported having to install a specific version of pandas (pandas==0.24.0) to make this all work. YMMV.

Alternatively, you can install with

  python install

Unit tests

There is a test suite with close to 100% code coverage

Run with

pip install pytest-cov

python -m pytest --cov=lkmltools/ test/*.py ; coverage html

Developer Notes

There are some developer notes for the linter here.


We would love to have your feedback, suggestions, and especially contributions to the project. Create a pull request!

You can reach me directly at as well as @leapingllamas on Twitter.

Release notes

2019-07-17: 2.0.1

Adding missing lkml to requirements.txt

2019-07-17: 2.0.0

Given the impact of the following two changes, this is a major release:

  • swapped out the node-based LookML parser with Josh Temple's new Python lkml parser ( This simplifies install, dependency management, and underlying parsed JSON format.
  • added layer of abstraction via LookML and LookMLField classes so that rules and other code can query LookML attributes via methods instead of inspecting raw JSON.

Other changes:

  • lkmltools.RuleFactory is now a singleton so it is easier for users to register their own rules.
  • Can now parameterize any rule in the configuration by adding additional keys to the dictionary for that rule. For instance, if the config defines {"name": "MyAwesomeRule", "run": true, "debug": true, "strict_mode":true, length: 6} then this whole dictionary is passed into the constructor during rule instantiation.

2019-06-10: 1.0.0

  • initial release


Copyright 2019 WW International, Inc.

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

Project details

Download files

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

Files for lookml-tools, version 2.0.1
Filename, size & hash File type Python version Upload date
lookml_tools-2.0.1-py3-none-any.whl (12.6 kB) View hashes Wheel py3
lookml-tools-2.0.1.tar.gz (17.1 kB) View hashes Source None

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page