Behavior Trees in Python

Python won’t be ticking the enemies in your 60 fps action game — but for robotics, simulations, agent prototypes, and learning how behavior trees actually work, it’s hard to beat. The ecosystem has one clear standard library, py_trees, and a first-class ROS 2 companion, py_trees_ros, maintained from the same lineage as the ROS navigation work covered in Behavior Trees in Robotics.

py_trees in five minutes

Everything in py_trees is a Behaviour with an update() method returning a status — the same Success/Failure/Running contract from the node reference:

import py_trees

class IsPlayerVisible(py_trees.behaviour.Behaviour):
    def update(self):
        return (py_trees.common.Status.SUCCESS
                if self.blackboard.visible
                else py_trees.common.Status.FAILURE)

class MoveToPlayer(py_trees.behaviour.Behaviour):
    def update(self):
        arrived = step_toward(self.blackboard.player_position)
        return (py_trees.common.Status.SUCCESS if arrived
                else py_trees.common.Status.RUNNING)

chase = py_trees.composites.Sequence("Chase", memory=False)
chase.add_children([IsPlayerVisible("Visible?"), MoveToPlayer("Move")])

root = py_trees.composites.Selector("Brain", memory=False)
root.add_children([chase, build_patrol_subtree()])

tree = py_trees.trees.BehaviourTree(root)
while True:
    tree.tick()

The pieces map directly onto standard BT vocabulary:

Two details are unusually well done. The blackboard requires behaviours to register which keys they read and write — the “treat keys as an API” discipline from the blackboard guide, enforced by the library. And visualization is built in: py_trees.display.ascii_tree(root) prints the tree with live per-node status, which makes the tick semantics visible in a way no amount of reading achieves.

[o] Brain [*]
    [-] Chase [*]
        --> Visible? [o]
        --> Move [*]      ← Running
    [-] Patrol

py_trees_ros: trees on real robots

For ROS 2, py_trees_ros wraps the same core with the robotics essentials: behaviours that call ROS actions and services asynchronously, subscribers that mirror topics into the blackboard, and snapshot publishing so the py_trees_ros_viewer GUI can watch a live tree over the network — the same “watch the tree run” workflow Groot2 provides for BehaviorTree.CPP. Python’s tick rates (typically 10–50 Hz for mission logic) are a non-issue for task orchestration; the hard real-time control loops live below the tree in controllers anyway.

If your stack is C++/Nav2, use BehaviorTree.CPP; if it’s Python-first — research platforms, quick field tooling, coursework — py_trees is the standard.

When Python is the wrong runtime (and it still helps)

For a shipping game you’ll execute trees in Unity, Unreal, or Godot — but a 50-line Python prototype is still the fastest way to validate tree logic before touching engine code. Stub every action with a counter, tick the tree in a loop, print the ascii tree, and watch whether your priorities and guards actually do what you intended. Logic bugs cost minutes here and hours in-engine.

The same goes for design: sketch the structure visually first, then write the Python.

▶ Explore the pick-and-place tree in the editor

Related guides

• Behavior Trees in Robotics: BehaviorTree.CPP, ROS 2, and Nav2
• How to Write a Behavior Tree from Scratch
• Behavior Tree Blackboards