Dominique Paul developed boolean serialization support for the Lightning-AI/litData repository, focusing on enhancing data fidelity in streaming pipelines. Dominique designed and implemented a dedicated BooleanSerializer in Python, integrating it into the existing serializer registry to standardize boolean handling across both streaming and optimisation workflows. The approach emphasized test-driven development, with expanded test coverage to ensure correctness and regression safety for boolean serialization and deserialization. By addressing the need for reliable boolean data flow, Dominique’s work reduced downstream parsing errors and enabled predictable behavior in litdata.optimise(). This contribution demonstrated depth in data serialization, registry-based architectures, and robust Python testing practices.