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This tutorial describes TuLiP, the Temporal Logic Planning toolbox, a collection of tools for designing controllers for hybrid systems from specifications in temporal logic. The tools support a workflow that starts from a description of desired behavior, and of the system to be controlled. The system can have discrete state, or be a hybrid dynamical system with a mixed discrete and continuous state space. The desired behavior can be represented with temporal logic and discrete transition systems. The system description can include uncontrollable variables that take discrete or continuous values, and represent disturbances and other environmental factors that affect the dynamics, as well as communication signals that affect controller decisions. A control design problem is solved in phases that involve abstraction, discrete synthesis, and continuous feedback control. Abstraction yields a discrete description of system dynamics in logic. For piecewise affine dynamical systems, this abstraction is constructed automatically, guided by the geometry of the dynamics and under logical constraints from the specification. The resulting logic formulae describe admissible discrete behaviors that capture both controlled and environment variables. The discrete description resulting from abstraction is then conjoined with the desired logic specification. To find a controller, the toolbox solves a game of infinite duration. Existence of a discrete (winning) strategy for the controlled variables in this game is a proof certificate for the existence of a controller for the original problem, which guarantees satisfaction of the specification. This discrete strategy, concretized by using continuous controllers, yields a feedback controller for the original hybrid system. The toolbox frontend is written in Python, with backends in C, Python, and Cython. The tutorial starts with an overview of the theory behind TuLiP, and of its software architecture, organized into specifi- cation frontends and backends that implement algorithms for abstraction, solving games, and interfaces to other tools. Then, the main elements for writing a specification for input to TuLiP are introduced. These include logic formulae, discrete transition systems annotated with predicates, and hybrid dynamical systems, with linear or piecewise affine continuous dynamics. The working principles of the algorithms for predicate abstraction and discrete game solving using nested fixpoints are explained, by following the input specification through the various transformations that compile it to a symbolic representation that scales well to solving large games. The tutorial concludes with several design examples that demonstrate the toolbox’s capabilities.