def patch()

in src/lambdas/r8s_api_handler/processors/recommendation_history_processor.py [0:0]
50 lines of code
4 McCabe index (conditional complexity)

    def patch(self, event):
        _LOG.debug(f'Update recommendation event: {event}')
        validate_params(event, (INSTANCE_ID_ATTR, RECOMMENDATION_TYPE_ATTR,
                                FEEDBACK_STATUS_ATTR))

        customer = event.get(PARAM_USER_CUSTOMER)
        if customer == 'admin':
            customer = event.get(CUSTOMER_ATTR)

        if not customer:
            _LOG.warning(f'\'{CUSTOMER_ATTR}\' must be '
                         f'specified for admin users.')
            return build_response(
                code=RESPONSE_BAD_REQUEST_CODE,
                content=f'\'{CUSTOMER_ATTR}\' must be specified '
                        f'for admin users.'
            )

        instance_id = event.get(INSTANCE_ID_ATTR)
        recommendation_type = event.get(RECOMMENDATION_TYPE_ATTR)
        feedback_status = event.get(FEEDBACK_STATUS_ATTR)

        self._validate_recommendation_type(
            recommendation_type=recommendation_type)
        self._validate_feedback_status(feedback_status=feedback_status,
                                       recommendation_type=recommendation_type)

        _LOG.debug(f'Searching for instance \'{instance_id}\' '
                   f'recommendation of type \'{recommendation_type}\'')
        recommendation = list(
            self.recommendation_history_service.get_recent_recommendation(
                instance_id=instance_id,
                recommendation_type=recommendation_type,
                customer=customer,
                limit=1
            ))
        if not recommendation:
            _LOG.error(f'No recommendations found matching given query.')
            return build_response(
                code=RESPONSE_RESOURCE_NOT_FOUND_CODE,
                content=f'No recommendations found matching given query.'
            )
        recommendation = recommendation[0]
        _LOG.debug(f'Updating recommendation')
        recommendation = self.recommendation_history_service.save_feedback(
            recommendation=recommendation,
            feedback_status=feedback_status
        )
        _LOG.debug(f'Describing recommendation dto')
        response = recommendation.get_dto()

        _LOG.debug(f'Response: {response}')
        return build_response(
            code=RESPONSE_OK_CODE,
            content=response
        )