This paper presents an approach for the efficient numerical implementation of transformation based state feedback laws for linear distributed parameter systems. The control laws considered may originate from backstepping or flatness-based design methods. They are, therefore, directly based on the underlying distributed parameter systems. In general, they are given as unbounded functionals on the infinite-dimensional state-space. By approximating a carefully chosen bounded part, the implementation of these feedback-operators can be considerably simplified. This is achieved by approximating the state in appropriate finite-dimensional sub-spaces of the state-space. The choice of these sub-spaces as well as the controller implementation are discussed for both, a particular motivating example specific and the general case. For the implementation and validation of the obtained approximated controllers the python-based software toolbox PyInduct is introduced.