https://github.com/yu-iskw/dbt-airflow-macros
Dbt package for Apache Airflow inspired macros
https://github.com/yu-iskw/dbt-airflow-macros
airflow dbt dbt-packages
Last synced: 6 months ago
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Dbt package for Apache Airflow inspired macros
- Host: GitHub
- URL: https://github.com/yu-iskw/dbt-airflow-macros
- Owner: yu-iskw
- License: apache-2.0
- Created: 2020-11-12T07:52:40.000Z (almost 5 years ago)
- Default Branch: main
- Last Pushed: 2025-03-10T06:37:22.000Z (7 months ago)
- Last Synced: 2025-03-29T02:12:17.581Z (7 months ago)
- Topics: airflow, dbt, dbt-packages
- Language: Shell
- Homepage: https://hub.getdbt.com/yu-iskw/dbt_airflow_macros/latest/
- Size: 55.7 KB
- Stars: 15
- Watchers: 2
- Forks: 3
- Open Issues: 14
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# dbt-airflow-macros
[](https://app.circleci.com/pipelines/github/yu-iskw/dbt-airflow-macros)
This is a dbt package to use macros inspired by Apache Airflow.
The macros are not warehouse-specific.
Those work with any warehouse.
- [Recommended environments](#recommended-environments)
- [Installation](#installation)
- [Environment variable](#environment-variable)
- [Macros](#macros)
- [Examples](#examples)
- [Tested environments](#tested-environments)
- [Links](#links)
## Recommended environments
- Python: 3.6, 3.7 and 3.8
- dbt: >=0.17.0
## Installation
Include in `packages.yaml`
```yaml
packages:
- git: "https://github.com/yu-iskw/dbt-airflow-macros.git"
revision: 0.2.2
```
## Environment variable
The shell environment variable `EXECUTION_DATE` enables us to pass the date and time for the dbt macros.
The ISO 8601 format is available, because the package uses `datetime.datetime.fromisoformat` internally.
If we don't set `EXECUTION_DATE`, then it is set to the current UTC date and time.
```bash
EXECUTION_DATE="2020-01-01T01:23:45" dbt run
EXECUTION_DATE="2020-01-01" dbt run
```
## Macros
The package includes the following macros.
`timezone` is an optional argument.
When it is set to `none`, the timezone is UTC by default.
|Macro |Description |
|--------------------------------------------------|---------------------------------------------|
|`dbt_airflow_macros.execution_date(timezone=none)`|`datetime.datetime` object |
|`dbt_airflow_macros.ds(timezone=none)` |`"%Y-%m-%d"` of execution time |
|`dbt_airflow_macros.ds_nodash(timezone=none)` |`"%Y%m%d"` of execution time |
|`dbt_airflow_macros.ts(timezone=none)` |`"%Y-%m-%dT%H:%M:%S+00:00"` of execution time|
|`dbt_airflow_macros.ts_nodash(timezone=none)` |`"%Y%m%dT%H%M%S"`of execution_time |
## Examples
[`test_macros.sql`](./integration_tests/postgres/models/test_macros.sql) is a file to test the macros on PostgreSQL.
Those would be helpful to understand how to use the macros.
## Tested environments
The continuous integration tested the dbt package with the environments below.
- dbt-airflow-macros==0.2.x
- Python: 3.6, 3.7 and 3.8
- dbt: 0.17.2, 0.18.1, 0.19.0, 0.20.0 and 0.21.0
## Links
* [dbt_airflow_macros on dbt hub](https://hub.getdbt.com/yu-iskw/dbt_airflow_macros/latest/)
* [Use Airflow\-like macros in dbt | Medium](https://yu-ishikawa.medium.com/use-airflow-like-macros-in-dbt-4bc9fba8e21a)