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create_resource_policy 

create_resource_policy(
    resource_arn: AmazonResourceName,
    policy: Policy,
    *,
    config_overrides: Optional[LexModelsV2ClientConfig] = None,
) -> CreateResourcePolicyResponse

Creates a new resource policy with the specified policy statements.

Parameters:

  • resource_arn (AmazonResourceName) –

    The Amazon Resource Name (ARN) of the bot or bot alias that the resource policy is attached to.

  • policy (Policy) –

    A resource policy to add to the resource. The policy is a JSON structure that contains one or more statements that define the policy. The policy must follow the IAM syntax. For more information about the contents of a JSON policy document, see IAM JSON policy reference .

    If the policy isn't valid, Amazon Lex returns a validation exception.

Raises:

Source code in docs_src/capo_lex_models_v2/_services/lex_models_v2.py 
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def create_resource_policy(
    self,
    resource_arn: "capo_lex_models_v2.types.amazon_resource_name.AmazonResourceName",
    policy: "capo_lex_models_v2.types.policy.Policy",
    *,
    config_overrides: Optional[LexModelsV2ClientConfig] = None,
) -> "capo_lex_models_v2.types.create_resource_policy_response.CreateResourcePolicyResponse":
    """<p>Creates a new resource policy with the specified policy statements.</p>

    Args:
        resource_arn: <p>The Amazon Resource Name (ARN) of the bot or bot alias that the resource policy is attached to.</p>
        policy: <p>A resource policy to add to the resource. The policy is a JSON structure that contains one or more statements that define the policy. The policy must follow the IAM syntax. For more information about the contents of a JSON policy document, see <a href="https://docs.aws.amazon.com/IAM/latest/UserGuide/reference_policies.html"> IAM JSON policy reference </a>. </p> <p>If the policy isn't valid, Amazon Lex returns a validation exception.</p>

    Raises:
        capo_lex_models_v2.errors.internal_server_exception.InternalServerException: <p>The service encountered an unexpected condition. Try your request again.</p>
        capo_lex_models_v2.errors.precondition_failed_exception.PreconditionFailedException: <p>Your request couldn't be completed because one or more request fields aren't valid. Check the fields in your request and try again.</p>
        capo_lex_models_v2.errors.resource_not_found_exception.ResourceNotFoundException: <p>You asked to describe a resource that doesn't exist. Check the resource that you are requesting and try again.</p>
        capo_lex_models_v2.errors.service_quota_exceeded_exception.ServiceQuotaExceededException: <p>You have reached a quota for your bot. </p>
        capo_lex_models_v2.errors.throttling_exception.ThrottlingException: <p>Your request rate is too high. Reduce the frequency of requests.</p>
        capo_lex_models_v2.errors.validation_exception.ValidationException: <p>One of the input parameters in your request isn't valid. Check the parameters and try your request again.</p>
        capo_lex_models_v2.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_lex_models_v2.types.create_resource_policy_request.CreateResourcePolicyRequest]",
    ) -> OperationResponse[
        "capo_lex_models_v2.types.create_resource_policy_response.CreateResourcePolicyResponse"
    ]:
        import capo_lex_models_v2._operations.lex_model_building_service_v2.create_resource_policy

        output, http_response = (
            capo_lex_models_v2._operations.lex_model_building_service_v2.create_resource_policy.create_resource_policy(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("CreateResourcePolicy")
    )
    input_: capo_lex_models_v2.types.create_resource_policy_request.CreateResourcePolicyRequest = {
        "resource_arn": resource_arn,
        "policy": policy,
    }

    response = execute_pipeline(
        OperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    response.response.close()
    return response.output