Carnopy generates reproducible thermophysical datasets by interfacing with scientific backends such as CoolProp. It includes built-in visualization, full data provenance, and leakage-aware preparation specifically designed for physics-informed machine learning and engineering workflows. The package is distributed as a Python library under the MIT license.
In the Developer Tools space, carnopy takes a focused approach. It focuses on creating reproducible, leakage-free thermophysical datasets from scientific simulators for use in physics-informed machine learning models. It is built as an open-source project for developers. carnopy is open source under the MIT license. It ships for the command line.
It is developed by gcalpay, and it first shipped in 2026. The project is developed in the open on GitHub with 173 commits in the last 90 days. Key capabilities include Dataset Generation, Provenance Tracking, and visualization.
Summary written by a language model from the project’s public pages.
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