Lipidomic analyses address the problem of characterizing the lipid components of given cells, tissues and organisms by means of chromatographic separations coupled to high-resolution, tandem mass spectrometry analyses. A number of software tools have been developed to help in the daunting task of mass spectrometry signal processing and cleaning, peak analysis and compound identification, and a typical finished lipidomic dataset contains hundreds to thousands of individual molecular lipid species. To provide researchers without a specific technical expertise in mass spectrometry the possibility of broadening the exploration of lipidomic datasets, we have developed liputils, a Python module that specializes in the extraction of fatty acid moieties from individual molecular lipids. there is no prerequisite data format, as liputils extracts residues from RefMet-compliant textual identifiers and from annotations of other commercially available services. We provide three examples of realworld data processing with liputils, as well as a detailed protocol on how to readily process an existing dataset that can be followed with basic informatics skills. Lipidomics is the analysis of the large-scale identification and quantification of individual lipid species, which relies-at its finest-on the analytical technology of chromatographic separation coupled to mass spectrometry (MS) and dedicated software 1,2. Lipidomics is among the most juvenile-omic technologies, yet recent advances in MS, lipid biochemistry and software pipelines allow for high-throughput, unbiased analysis of diverse biomolecules. A typical workflow of a high-resolution, high-throughput lipidomics involves MS-based studies of the structure, composition, and quantity of lipids in biological systems-typically organs, cells, and bodily fluids. Analytes are then identified and quantified with software tools that can process MS data in an automated or semi-automated manner 3,4. Most of the tools that are available on dedicated portals, such as LIPID MAPS 5 , are designed to tackle the problems such as fragments recognition, lipids reconstruction from fragment analysis and artefactual signals removal 4. As of beginning of 2020, ~ 3,000 papers featuring "lipidomics" and "mass spectrometry" could be retrieved from Web of Science, showing an ever growing trend since 2003 6. A modern lipidomic analysis can contain hundreds of individual molecular lipid species, of the 43,645 annotated in databases such as LIPID MAPS, as of March 2020 5. Lipids-generically defined as water-insoluble molecules, or molecules soluble in organic solvents-have been grouped into eight categories: fatty acyls (9,374), glycerolipids (7,608), glycerophospholipids (9,918), sphingolipids (4,438), sterol lipids (2,828), prenol lipids (1,353), saccharolipids (1,316) and polyketides (6,810), further divided into sub-categories 7. In living organisms, they are used as energy reserve 8 , structural components of biological membranes, transporters, lipoprotein components 9,10 , signalling molecules 1...