The Chemoinformatics handbook is implemented within the GitBook platform, and it is organized into nine chapters that seek to promote the acquisition of basic concepts of Chemoinformatics and to develop competences for the search, acquisition, and analysis of chemical information employing programming and open access computational tools. The handbook covers a broad and diverse range of topics, including a general introduction to Python concepts and packages and basic commands on Linux. It also covers the search and analysis of chemical information using different databases and software for bibliometric visualization. It guides users on the applications of different molecular representations of low molecular weight organic compounds and further provides proficiency in utilizing databases pertinent to drug research through the use of Application Programming Interfaces (APIs), and instructs on building compound databases annotated with biological activity. Additionally, it introduces Exploratory Data Analysis (EDA) for examining physicochemical properties, exploring correlations within datasets, and visualizing the chemical space. The concept of a chemical multiverse is introduced and exemplified through a chemical art gallery. Applications of the similarity concept to conduct structure-activity relationships, such as quantitative structure-activity relationships (QSAR) and activity landscape modeling, are also covered. The GitBook also exemplifies published examples of chemical library enumeration in more detail. This can prove highly beneficial for investigating proposed methodologies • Introduce basic Python definitions and functions.