The design of the Scotch library for static mapping, graph partitioning and sparse matrix ordering is highly modular, so as to allow users and potential contributors to tweak it and add easily new static mapping, graph bipartitioning, vertex separation or graph ordering methods to match their particular needs. The purpose of this tutorial is twofold. It will start with a description of the interface of Scotch, presenting its visible objects and data structures. Then, we will step into the API mirror and have a look at the inside: the internal representation of graphs, mappings and orderings, and the basic sequential and parallel building blocks: graph induction, graph coarsening which can be re-used by third-party software. As an example, we will show how to add a simple genetic algorithm routine to the graph bipartitioning methods.