Float64 attributes store a 64-bit floating point number. Values are represented by a float64 type in the framework.
In this Terraform configuration example, a float64 attribute named example_attribute is set to the value 1.23:
resource "examplecloud_thing" "example" {
example_attribute = 1.23
}
Use one of the following attribute types to directly add a float64 value to a schema or nested attribute type:
In this example, a resource schema defines a top level required float64 attribute named example_attribute:
func (r ThingResource) Schema(ctx context.Context, req resource.SchemaRequest, resp *resource.SchemaResponse) {
resp.Schema = schema.Schema{
Attributes: map[string]schema.Attribute{
"example_attribute": schema.Float64Attribute{
Required: true,
// ... potentially other fields ...
},
// ... potentially other attributes ...
},
}
}
If the float64 value should be the element type of a collection attribute type, set the ElementType field according to the float64 type. Refer to the collection attribute type documentation for additional details.
If the float64 value should be a value type of an object attribute type, set the AttributeTypes map value according to the float64 type. Refer to the object attribute type documentation for additional details.
At least one of the Computed, Optional, or Required fields must be set to true. This defines how Terraform and the framework should expect data to set, whether the value is from the practitioner configuration or from the provider logic, such as API response value.
The acceptable behaviors of these configurability options are:
Required only: The value must be practitioner configured to an eventually known value (not null), otherwise the framework will automatically raise an error diagnostic for the missing value.Optional only: The value may be practitioner configured to a known value or null.Optional and Computed: The value may be practitioner configured or the value may be set in provider logic when the practitioner configuration is null.Computed only: The value will be set in provider logic and any practitioner configuration causes the framework to automatically raise an error diagnostic for the unexpected configuration value.If creating a resource identity schema, set either OptionalForImport or RequiredForImport to true to inform Terraform if practitioners must set the attribute when importing with that resource's identity.
The acceptable behaviors of these configurability options are:
RequiredForImport only: A practitioner must configure the attribute to a known value (not null), otherwise Terraform automatically raises an error diagnostic for the missing value.OptionalForImport only: A practitioner must configure the value to a known value or null.You may want to build your own attribute value and type implementations to allow your provider to combine validation, description, and plan customization behaviors into a reusable bundle. This helps avoid duplication or reimplementation and ensures consistency. These implementations use the CustomType field in the attribute type.
Refer to Custom Types for further details on creating provider-defined types and values.
DeprecationSet the DeprecationMessage field to a practitioner-focused message for how to handle the deprecation. The framework will automatically raise a warning diagnostic with this message if the practitioner configuration contains a known value for the attribute. Terraform version 1.2.7 and later will raise a warning diagnostic in certain scenarios if the deprecated attribute value is referenced elsewhere in a practitioner configuration. The framework deprecations documentation fully describes the recommended practices for deprecating an attribute or resource.
Some practitioner-focused examples of a deprecation message include:
other_attribute instead. This attribute will be removed in the next major version of the provider.The framework provides two description fields, Description and MarkdownDescription, which various tools use to show additional information about an attribute and its intended purpose. This includes, but is not limited to, terraform-plugin-docs for automated provider documentation generation and terraform-ls for Terraform configuration editor integrations.
Tip
Only managed resources implement this concept.
The framework provides two plan modification fields for managed resource attributes, Default and PlanModifiers, which define resource and attribute value planning behaviors. The resource default and plan modification documentation covers these features more in-depth.
The float64default package defines common use case Default implementations:
StaticFloat64(float64): Define a static float64 default value for the attribute.The float64planmodifier package defines common use case PlanModifiers implementations:
RequiresReplace(): Marks the resource for replacement if the resource is being updated and the plan value does not match the prior state value.RequiresReplaceIf(): Similar to RequiresReplace(), but also checks if a given function returns true.RequiresReplaceIfConfigured(): Similar to RequiresReplace(), but also checks if the configuration value is not null.UseStateForUnknown(): Copies a known prior state value into the planned value. Use this when it is known that an unconfigured value will remain the same after a resource update.Set the Sensitive field if the attribute value should always be considered sensitive data. In Terraform, this will generally mask the value in practitioner output. This setting cannot be conditionally set and does not impact how data is stored in the state.
Tip
Only managed resources implement this concept.
Set the WriteOnly field to define a write-only argument. Write-only arguments can accept ephemeral values and are not persisted in the Terraform plan or state artifacts. Write-only arguments are supported in Terraform 1.11 and later.
Set the Validators field to define validation. This validation logic is ran in addition to any validation contained within a custom type.
HashiCorp provides the additional terraform-plugin-framework-validators Go module which contains validation logic for common use cases. The float64validator package within that module has float64 attribute validators such as minimum, maximum, and defining conflicting attributes.
The accessing values documentation covers general methods for reading schema (configuration, plan, and state) data, which is necessary before accessing an attribute value directly. The float64 type documentation covers methods for interacting with the attribute value itself.
The float64 type documentation covers methods for creating or setting the appropriate value. The writing data documentation covers general methods for writing schema (plan and state) data, which is necessary afterwards.
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