One of the key skills developed in foundational thermodynamics courses is obtaining property and state data for various substances of interest. Typically, students are instructed to perform this task through the use of tables or computer software. In this paper, we present and evaluate modules for teaching the foundations of thermodynamics using free open-source software intended to port to students' professional lives. The approach introduces the PYro thermodynamic property calculator. PYro is implemented in Python, which is free and available on most widely used platforms. PYro is clearly documented, and all data are readily traceable to reputable sources. Most of the data describe ideal gases from the NIST JANAF database, but there is also support for mixtures (such as air) and multiphase substances (such as steam). The interface design makes the software appropriate to most tasks in introductory and intermediate thermodynamics courses without requiring proficiency in the Python language. While the idea of using software to teach thermodynamics is far from new, commercial software usually comes at a substantial price and places the implementation burden on the instructor. On the other hand, educational software rarely transitions into students' professional lives. This paper proposes a model for productively separating the development of skills (like table look-ups) from knowledge and concepts. In addition to an introduction of the tool, this paper provides results of preliminary evaluation conducted within a thermodynamics classroom. The authors developed a learning module demonstrating the use of PYro to compute states for an ideal Brayton cycle. Students were tasked with performing parametric analysis on the cycle, by varying various limiting factors (e.g. combustor pressure, turbine inlet temperature). Students were asked to compare power produced and cycle efficiency computed under these conditions. At the end of the module, students were surveyed about the experience of working with the software. Evaluation is provided in the form of instructor and student feedback from a classroom implementation. We propose that this utilization of the tool demonstrates its ability to promote higher-level cognitive thinking in problem solving, removing the time intensive task of performing table look-ups and allowing them to focus on more holistic questions of cycle performance.