Computational methods for the enhancement of energy efficiency rely on a measurement process with sufficient accuracy and number of measurements. Networked energy meters, energy monitors, serve as vital link between energy consumption of households and key insights that reveal strategies to achieve significant energy savings. During the design of such an energy monitor, several aspects such as data update rate or variety of measured physical quantities have to be considered. This paper introduces YoMoPie, a user-oriented energy monitor based on the Raspberry Pi platform that aims to enable intelligent energy services in households. YoMoPie measures active as well as apparent power, stores data locally, and integrates an easy to use Python library. Furthermore, the presented energy monitor comes with a Python API enabling the execution of user-designed services to enhance energy efficiency in buildings and households. Along with the presented design, possible applications that could run on top of this system such as residential demand response, immediate user feedback, smart meter data analytics, or energy disaggregation are discussed. Finally, a case study is presented, which compares the measurement accuracy of YoMoPie to a certified energy analyser for a selection of common household appliances.