Validate Configuration
Data sources support validating an entire practitioner configuration in either declarative or imperative logic. Feedback, such as required syntax or acceptable combinations of values, is returned via diagnostics.
This page describes implementation details for validating entire data source configurations, typically referencing multiple attributes. Further documentation is available for other configuration validation concepts:
- Single attribute validation is a schema-based mechanism for implementing attribute-specific validation logic.
- Type validation is a schema-based mechanism for implementing reusable validation logic for any attribute using the type.
Configuration validation in Terraform occurs without provider configuration ("offline"), so therefore the data source Configure
method will not have been called. To implement validation with a configured API client, use logic within the Read
method, which occurs during Terraform's planning phase when possible.
ConfigValidators Method
The datasource.DataSourceWithConfigValidators
interface follows a similar pattern to attribute validation and allows for a more declarative approach. This enables consistent validation logic across multiple data sources. Each validator intended for this interface must implement the datasource.ConfigValidator
interface.
During execution of the terraform validate
, terraform plan
and terraform apply
commands, Terraform calls the provider ValidateDataResourceConfig
RPC, in which the framework calls the ConfigValidators
method on data sources that implement the datasource.DataSourceWithConfigValidators
interface.
The terraform-plugin-framework-validators
Go module has a collection of common use case data source configuration validators in the datasourcevalidator
package. These use path expressions for matching attributes.
This example will raise an error if a practitioner attempts to configure both attribute_one
and attribute_two
:
// Other methods to implement the datasource.DataSource interface are omitted for brevitytype ThingDataSource struct {} func (d ThingDataSource) ConfigValidators(ctx context.Context) []datasource.ConfigValidator { return []datasource.ConfigValidator{ datasourcevalidator.Conflicting( path.MatchRoot("attribute_one"), path.MatchRoot("attribute_two"), ), }}
ValidateConfig Method
The datasource.DataSourceWithValidateConfig
interface is more imperative in design and is useful for validating unique functionality across multiple attributes that typically applies to a single data source.
During execution of the terraform validate
, terraform plan
and terraform apply
commands, Terraform calls the provider ValidateDataResourceConfig
RPC, in which the framework calls the ValidateConfig
method on providers that implement the datasource.DatasourceWithValidateConfig
interface.
This example will raise a warning if a practitioner attempts to configure attribute_one
, but not attribute_two
:
// Other methods to implement the datasource.DataSource interface are omitted for brevitytype ThingDataSource struct {} type ThingDataSourceModel struct { AttributeOne types.String `tfsdk:"attribute_one"` AttributeTwo types.String `tfsdk:"attribute_two"`} func (d ThingDataSource) ValidateConfig(ctx context.Context, req datasource.ValidateConfigRequest, resp *datasource.ValidateConfigResponse) { var data ThingDataSourceModel resp.Diagnostics.Append(req.Config.Get(ctx, &data)...) if resp.Diagnostics.HasError() { return } // If attribute_one is not configured, return without warning. if data.AttributeOne.IsNull() || data.AttributeOne.IsUnknown() { return } // If attribute_two is not null, return without warning. if !data.AttributeTwo.IsNull() { return } resp.Diagnostics.AddAttributeWarning( path.Root("attribute_two"), "Missing Attribute Configuration", "Expected attribute_two to be configured with attribute_one. "+ "The data source may return unexpected results.", )}