Future utilization of nuclear power may involve fuel cycles that incorporate new reactors and new fuel utilization schemes. In comparing fuel cycles in terms of their waste characteristics, many previous studies have focused on properties intrinsic to the wastes themselves: mass, radioactivity, and/or radiotoxicity. These properties do not directly inform analyses that evaluate waste management strategies, impacts, or risks. For these, information about waste packages and waste loading is critical. This paper reports on research performed to bridge the divide between nuclear fuel cycle and waste management analyses while accommodating the diversity of reactors, processes, and waste forms that could be utilized by advanced fuel cycles. An object-oriented Python code, Nuclear Waste Analysis in Python, was written to connect fuel cycle data with backend process information, thereby generating waste form characteristics and package inventories. The backend process models are informed by literature review and engineering judgment. The package is applied to the fuel cycles considered in the Fuel Cycle Evaluation and Screening (FCES) study and is benchmarked against the FCES study waste management evaluation metric data for mass and radioactivity. Hypothetical waste package inventories are reported for each fuel cycle as functions of spent fuel and high-level waste loading.