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Copy file name to clipboardExpand all lines: docs/assets/definition-schema.md
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Hooks are currently supported for SQL assets. Each hook entry supports a single `query` field and is executed in order. Queries may have a trailing `;` or not.
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Hooks can also be set as pipeline defaults (see [pipeline defaults](/getting-started/pipeline#default-pipeline-level-defaults)). Assets inherit default `pre` and `post` hooks independently - defining only `pre` hooks on an asset will still inherit default `post` hooks.
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Hooks can also be set as pipeline defaults (see [pipeline defaults](/pipelines/definition#default-pipeline-level-defaults)). Assets inherit default `pre` and `post` hooks independently - defining only `pre` hooks on an asset will still inherit default `post` hooks.
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### Pipeline
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Bruin supports user-defined variables at a pipeline level. These become available as a JSON document in your python asset as `BRUIN_VARS`. When no variables exist, `BRUIN_VARS` is set to `{}`. See [pipeline variables](/getting-started/pipeline-variables) for more information on how to define and override them, including the [full list of JSON Schema `type` options and complementary keywords](/getting-started/pipeline-variables#supported-json-schema-keywords).
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Bruin supports user-defined variables at a pipeline level. These become available as a JSON document in your python asset as `BRUIN_VARS`. When no variables exist, `BRUIN_VARS` is set to `{}`. See [Variables](/core-concepts/variables) for more information on how to define and override them, including the [full list of JSON Schema `type` options and complementary keywords](/core-concepts/variables#custom-variables).
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### Pipeline
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Bruin supports user-defined variables at a pipeline level. These become available as a JSON document in your R asset as `BRUIN_VARS`. When no variables exist, `BRUIN_VARS` is set to `{}`. See [pipeline variables](/getting-started/pipeline-variables) for more information on how to define and override them.
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Bruin supports user-defined variables at a pipeline level. These become available as a JSON document in your R asset as `BRUIN_VARS`. When no variables exist, `BRUIN_VARS` is set to `{}`. See [Variables](/core-concepts/variables) for more information on how to define and override them.
Copy file name to clipboardExpand all lines: docs/assets/templating/macros.md
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@@ -465,7 +465,7 @@ AND region = '{{ region }}'
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:::
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> [!TIP]
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> The pipeline snippet above showcases array enums and numeric bounds. For additional JSON Schema keywords you can mix into macros-driven workflows—including nested objects and nullable values—refer to the [pipeline variables keyword reference](/getting-started/pipeline-variables#supported-json-schema-keywords).
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> The pipeline snippet above showcases array enums and numeric bounds. For additional JSON Schema keywords you can mix into macros-driven workflows—including nested objects and nullable values—refer to the [Variables keyword reference](/core-concepts/variables#custom-variables).
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### Dynamic Column Generation
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- [Templating](./templating.md) - Learn about Jinja templating basics
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- [Filters](./filters.md) - Use filters to transform variables
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:::
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> [!TIP]
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> Need enumerations, numeric bounds, or nested structures for your variables? Consult the [JSON Schema keyword reference](/getting-started/pipeline-variables#supported-json-schema-keywords) for the full list of `type` values and examples of arrays-of-objects and object-of-arrays patterns you can reuse in templated SQL.
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> Need enumerations, numeric bounds, or nested structures for your variables? Consult the [Variables documentation](/core-concepts/variables#custom-variables) for the full list of `type` values and examples of arrays-of-objects and object-of-arrays patterns you can reuse in templated SQL.
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This will render into the following SQL query:
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| `execution_datetime` | The execution date and time in YYYY-MM-DDThh:mm:ss format | "2023-12-01T15:30:00" |
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| `execution_timestamp` | The execution timestamp in [RFC3339](https://datatracker.ietf.org/doc/html/rfc3339) format | "2023-12-01T15:30:00.000000Z07:00" |
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| `pipeline` | The name of the currently executing pipeline | `my_pipeline` |
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| `run_id` | The unique identifier for the current [pipeline run](../../getting-started/concepts.md#pipeline-run) | `run_1234567890` |
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| `run_id` | The unique identifier for the current pipeline run | `run_1234567890` |
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| `full_refresh` | Boolean indicating whether the `--full-refresh` flag was used | `True` or `False` |
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You can use these variables in your SQL queries by referencing them with the `{{ }}` syntax:
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## Custom variables
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You can define your own variables and use them across your Assets. See [variables](/getting-started/pipeline-variables) for more information.
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You can define your own variables and use them across your Assets. See [Variables](/core-concepts/variables) for more information.
This will add the connection to the `.bruin.yml` file and the connection will be available in the given environment.
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The parameter after `--credentials` is the value of the connection in JSON format, as you would write it in the `.bruin.yml` file. For further reference, you can check the [Connections section](../getting-started/concepts.md#connection) of the documentation.
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The parameter after `--credentials` is the value of the connection in JSON format, as you would write it in the `.bruin.yml` file. For further reference, you can check the [Connections](/core-concepts/connections) documentation.
|`--query-annotations`| str | - | Add annotations to SQL queries as comments. Use `default` to add asset name, pipeline name, and execution step, or provide custom JSON for additional fields. **BigQuery only.**|
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