spectrapepper is a Python package that makes advanced analysis of spectroscopic data easy and accessible through straightforward, simple, and intuitive code. This library contains functions for every stage of spectroscopic methodologies, including data acquisition, pre-processing, processing, and analysis. In particular, advanced and high statistic methods are intended to facilitate, namely combinatorial analysis and machine learning, allowing also fast and automated traditional methods. The following is a short list of some main procedures that spectrapepper package enables: i) Baseline removal functions, ii) Normalization methods, iii) Noise filters, trimming tools, and despiking methods, iv) Chemometric algorithms to find peaks, fit curves, and deconvolution of spectra, v) Combinatorial analysis tools, such as Spearman, Pearson, and n-dimensional correlation coefficients, vi) Tools for Machine Learning applications, such as data merging, randomization, and decision boundaries, and vii) Sample data and examples