Name | in-metricflow JSON |
Version |
0.205.0
JSON |
| download |
home_page | None |
Summary | Translates a simple metric definition into reusable SQL and executes it against the SQL engine of your choice. |
upload_time | 2024-06-04 14:57:57 |
maintainer | None |
docs_url | None |
author | dbt Labs |
requires_python | <3.12,>=3.8 |
license | None |
keywords |
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VCS |
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bugtrack_url |
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requirements |
No requirements were recorded.
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Travis-CI |
No Travis.
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coveralls test coverage |
No coveralls.
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<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](https://github.com/dbt-labs/metricflow/blob/main/CHANGELOG.md)!
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](https://docs.getdbt.com/docs/build/build-metrics-intro).
## 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](https://github.com/dbt-labs/metricflow/blob/main/LICENSE).
## 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](https://www.postgresql.org/download/) or [Graphviz](https://www.graphviz.org/download/). 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
- [Website](https://transform.co/metricflow)
- [Documentation](https://docs.getdbt.com/docs/build/build-metrics-intro)
- [Slack Community](https://www.getdbt.com/community/)
- [MetricFlow Git Repository](https://github.com/dbt-labs/metricflow)
- [CHANGELOG.md](https://github.com/dbt-labs/metricflow/blob/main/CHANGELOG.md)
- [TENETS.md](https://github.com/dbt-labs/metricflow/blob/main/TENETS.md)
## 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](https://docs.getdbt.com/community/resources/code-of-conduct) before diving in.
To get started on direct contributions, head on over to our [contributor guide](https://github.com/dbt-labs/metricflow/blob/main/CONTRIBUTING.md).
## 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](https://www.getdbt.com/).
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"description": "<p align=\"center\">\n <a target=\"_blank\" href=\"https://transform.co/metricflow\">\n <picture>\n <img alt=\"metricflow logo\" src=\"https://github.com/dbt-labs/metricflow/raw/main/assets/MetricFlow_logo.png\" width=\"auto\" height=\"120\">\n </picture>\n </a>\n <br /><br />\n <b>Build and maintain all of your metric logic in code.</b>\n <br /><br />\n <a target=\"_blank\" href=\"https://twitter.com/dbt_labs\">\n <img src=\"https://img.shields.io/twitter/follow/dbt_labs?labelColor=image.png&color=163B36&logo=twitter&style=flat\">\n </a>\n <a target=\"_blank\" href=\"https://www.getdbt.com/community/\">\n <img src=\"https://img.shields.io/badge/Slack-join-163B36\">\n </a>\n <a target=\"_blank\" href=\"https://github.com/dbt-labs/metricflow\">\n <img src=\"https://img.shields.io/github/stars/dbt-labs/metricflow?labelColor=image.png&color=163B36&logo=github\">\n </a>\n <br />\n <a target=\"_blank\" href=\"https://github.com/dbt-labs/metricflow/blob/master/LICENSE\">\n <img src=\"https://img.shields.io/pypi/l/metricflow?color=163B36&logo=AGPL-3.0\">\n </a>\n <a target=\"_blank\" href=\"https://pypi.org/project/metricflow/\">\n <img src=\"https://img.shields.io/pypi/v/metricflow?labelColor=&color=163B36\">\n </a>\n <img src=\"https://img.shields.io/pypi/pyversions/metricflow?labelColor=&color=163B36\">\n</p>\n\n# Welcome to MetricFlow\n\nSee our latest updates in the [Metricflow Changelog](https://github.com/dbt-labs/metricflow/blob/main/CHANGELOG.md)!\n\nMetricFlow 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.\n\nThe 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.\n\n<p align=\"center\">\n<img src=\"https://github.com/dbt-labs/metricflow/raw/main/assets/example_plan.svg\" height=\"500\"/>\n<br /><br />\n</p>\n\nMetricFlow provides a set of abstractions that help you construct complicated logic and dynamically generate queries to handle:\n\n- Multi-hop joins between fact and dimension sources\n- Complex metric types such as ratio, expression, and cumulative\n- Metric aggregation to different time granularities\n- And so much more\n\nTo get up and running with your own metrics, you should rely on [MetricFlow\u2019s documentation](https://docs.getdbt.com/docs/build/build-metrics-intro).\n\n## Licensing\n\nMetricFlow 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](https://github.com/dbt-labs/metricflow/blob/main/LICENSE).\n\n## Getting Started\n\n### Install MetricFlow\n\nMetricFlow can be installed from PyPi for use as a Python library with the following command:\n\n```\npip install dbt-metricflow\n```\n\nMetricFlow 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.\n\nYou may need to install Postgres or Graphviz. You can do so by following the install instructions for [Postgres](https://www.postgresql.org/download/) or [Graphviz](https://www.graphviz.org/download/). Mac users may prefer to use brew: `brew install postgresql` or `brew install graphviz`.\n\n### Tutorial\n\nThe best way to get started is to follow the tutorial steps, which you can access by running:\n\n```\nmf tutorial\n```\n\nNote: this must be run from a dbt project root directory.\n\n## Resources\n\n- [Website](https://transform.co/metricflow)\n- [Documentation](https://docs.getdbt.com/docs/build/build-metrics-intro)\n- [Slack Community](https://www.getdbt.com/community/)\n- [MetricFlow Git Repository](https://github.com/dbt-labs/metricflow)\n- [CHANGELOG.md](https://github.com/dbt-labs/metricflow/blob/main/CHANGELOG.md)\n- [TENETS.md](https://github.com/dbt-labs/metricflow/blob/main/TENETS.md)\n\n## Contributing and Code of Conduct\n\nThis project will be a place where people can easily contribute high-quality updates in a supportive environment.\n\nPlease read our [code of conduct](https://docs.getdbt.com/community/resources/code-of-conduct) before diving in.\n\nTo get started on direct contributions, head on over to our [contributor guide](https://github.com/dbt-labs/metricflow/blob/main/CONTRIBUTING.md).\n\n## License\n\nMetricFlow is source-available software.\n\nVersion 0 to 0.140.0 was covered by the Affero GPL license.\nVersion 0.150.0 and greater is covered by the BSL license..\n\nMetricFlow is built by [dbt Labs](https://www.getdbt.com/).\n",
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