Developed and integrated a configurable spectral analysis windowing feature for the analogdevicesinc/pyadi-iio repository, focusing on enhancing frequency-domain measurement accuracy. Leveraged Python and signal processing expertise to implement an optional Kaiser window in the DDS loopback path, enabling users to apply windowing prior to FFT within the spectral estimation workflow. Expanded the unit testing suite to validate windowed spectral analysis and ensure correct scaling behavior across multiple test modules. The work addressed a key capability gap by allowing controlled window application, while improved test coverage contributed to greater measurement fidelity and ongoing stabilization of the spectral analysis pipeline without major bug fixes.