In this paper, we have introduced RamanSPy -a computational framework for integrative Raman spectroscopic data analysis. RamanSPy offers a comprehensive collection of tools for spectroscopic analysis designed to systematise the RS data analysis life cycle, reducing typical overheads of analysis workflows and improving methodological standardisation. The package also lays the foundations of a common repository of standardised methods, protocols and datasets, which users can readily access and exploit within the RamanSPy framework to conduct different benchmarking studies. Furthermore, RamanSPy is fully compatible with frameworks for data science and machine learning in Python, thereby facilitating the adoption and validation of advanced AI technologies for next-generation RS analysis. Lastly, we remark that, while our focus here has been on Raman spectroscopy, many of the tools in RamanSPy are of broad applicability to other vibrational spectroscopy techniques, including infrared (IR) spectroscopy.