Awesome
<p align="center"> <a target="_blank" href="https://transform.co/metricflow"> <picture> <img alt="metricflow logo" src="https://github.com/dbt-labs/metricflow/raw/main/assets/MetricFlow_logo.png" width="auto" height="120"> </picture> </a> <br /><br /> <b>Build and maintain all of your metric logic in code.</b> <br /><br /> <a target="_blank" href="https://twitter.com/dbt_labs"> <img src="https://img.shields.io/twitter/follow/dbt_labs?labelColor=image.png&color=163B36&logo=twitter&style=flat"> </a> <a target="_blank" href="https://www.getdbt.com/community/"> <img src="https://img.shields.io/badge/Slack-join-163B36"> </a> <a target="_blank" href="https://github.com/dbt-labs/metricflow"> <img src="https://img.shields.io/github/stars/dbt-labs/metricflow?labelColor=image.png&color=163B36&logo=github"> </a> <br /> <a target="_blank" href="https://github.com/dbt-labs/metricflow/blob/master/LICENSE"> <img src="https://img.shields.io/pypi/l/metricflow?color=163B36&logo=AGPL-3.0"> </a> <a target="_blank" href="https://pypi.org/project/metricflow/"> <img src="https://img.shields.io/pypi/v/metricflow?labelColor=&color=163B36"> </a> <img src="https://img.shields.io/pypi/pyversions/metricflow?labelColor=&color=163B36"> </p>Welcome to MetricFlow
See our latest updates in the Metricflow Changelog!
MetricFlow is a semantic layer that makes it easy to organize metric definitions. It takes those definitions and generates legible and reusable SQL. This makes it easy to get consistent metrics output broken down by attributes (dimensions) of interest.
The name comes from the approach taken to generate metrics. A query is compiled into a query plan (represented below) called a dataflow that constructs metrics. The plan is then optimized and rendered to engine-specific SQL.
<p align="center"> <img src="https://github.com/dbt-labs/metricflow/raw/main/assets/example_plan.svg" height="500"/> <br /><br /> </p>MetricFlow provides a set of abstractions that help you construct complicated logic and dynamically generate queries to handle:
- Multi-hop joins between fact and dimension sources
- Complex metric types such as ratio, expression, and cumulative
- Metric aggregation to different time granularities
- And so much more
To get up and running with your own metrics, you should rely on MetricFlow’s documentation.
Licensing
MetricFlow is distributed under a Business Source License (BUSL-1.1). For details on our additional use grant, change license, and change date please refer to our licensing agreement.
Getting Started
Install MetricFlow
MetricFlow can be installed from PyPi for use as a Python library with the following command:
pip install dbt-metricflow
MetricFlow currently serves as a query compilation and SQL rendering library, built to work in conjunction with a dbt project. As such, using MetricFlow requires a working dbt project and a dbt adapter. We provide the dbt-metricflow bundle for this purpose. You may choose to install other adapters as optional extras from dbt-metricflow.
You may need to install Postgres or Graphviz. You can do so by following the install instructions for Postgres or Graphviz. Mac users may prefer to use brew: brew install postgresql or brew install graphviz.
Tutorial
The best way to get started is to follow the tutorial steps, which you can access by running:
mf tutorial
Note: this must be run from a dbt project root directory.
Resources
Contributing and Code of Conduct
This project will be a place where people can easily contribute high-quality updates in a supportive environment.
Please read our code of conduct before diving in.
To get started on direct contributions, head on over to our contributor guide.
License
MetricFlow is source-available software.
Version 0 to 0.140.0 was covered by the Affero GPL license. Version 0.150.0 and greater is covered by the BSL license..
MetricFlow is built by dbt Labs.