# arguments (for macros)

macros/\<filename>.yml

```yml


macros:
  - name: <macro name>
    arguments:
      - name: <arg name>
        type: <string>
        description: <markdown_string>
```

## Definition

The `arguments` property is used to define the parameters that a resource can accept. Each argument can have a `name`, a `type` field, and an optional `description`.

For **macros**, you can add `arguments` to a [macro property](../macro-properties.md), which helps in documenting the macro and understanding what inputs it requires.

## type

(Applies to dbt v1.10 and later)

The data type of your argument. Setting [`validate_macro_args`](../global-configs/behavior-flags/validate_macro_args.md) to `true` ensures that documented macro argument names match those in the macro definition and validates their types against the [supported types](#supported-types). When set to `false`, `type` is only used for documentation purposes and there are no restrictions on the values you can specify.

tip

From dbt Core v1.10, you can opt into validating the arguments you define in macro documentation using the `validate_macro_args` behavior change flag. When enabled, dbt will:

* Infer arguments from the macro and includes them in the [manifest.json](../artifacts/manifest-json.md) file if no arguments are documented.
* Raise a warning if documented argument names don't match the macro definition.
* Raise a warning if `type` fields don't follow [supported formats](./arguments.md#supported-types).

Learn more about [macro argument validation](../global-configs/behavior-flags/validate_macro_args.md).

macros/\<filename>.yml

```yml

macros:
  - name: <macro name>
    arguments:
      - name: <arg name>
        type: <string>
```

### Supported types

From dbt Core v1.10, when you use the [`validate_macro_args`](../global-configs/behavior-flags/validate_macro_args.md) flag, dbt supports the following types for macro arguments:

* `string` or `str`
* `boolean` or `bool`
* `integer` or `int`
* `float`
* `any`
* `list[<Type>]`, for example, `list[string]`
* `dict[<Type>, <Type>]`, for example, `dict[str, list[int]]`
* `optional[<Type>]`, for example, `optional[integer]`
* [`relation`](../dbt-classes.md#relation)
* [`column`](../dbt-classes.md#column)

Note that the types follow a Python-like style but are used for documentation and validation only. They are not Python types.

## Examples

macros/cents\_to\_dollars.sql

```sql
{% macro cents_to_dollars(column_name, scale=2) %}
    ({{ column_name }} / 100)::numeric(16, {{ scale }})
{% endmacro %}
```

macros/cents\_to\_dollars.yml

```yml

macros:
  - name: cents_to_dollars
    arguments:
      - name: column_name
        type: column
        description: "The name of a column"
      - name: scale
        type: integer
        description: "The number of decimal places to round to. Default is 2."
```

## Related documentation

* [Macro properties](../macro-properties.md)
* [Arguments (for functions)](./function-arguments.md)

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