MicroECS
Minimal (~850 LoC) Entity Component System in python and numpy. Examples also use raylib for rendering.
Usage:
- Via pip:
pip install microecs - From source code:
git clone https://gitlab.com/meehai/microecs # clone the source code
cd microecs # go in the cloned directory
python -m venv .venv && source .venv/bin/activate # make a virtual env, optional but useful
python -m pip install -e . # install micro ecs in this virtual env
python -m pytest test/ # run the unit & integration tests to verify installation
python examples/01-hello-world.py # run the basic hello world example (others in that dir)
Docs: meehai.gitlab.io/microecs
Simple example
from dataclasses import field
import numpy as np
from microecs import World, Component
class HasPosition(Component):
position: np.ndarray = field(metadata={"shape": (2, ), "dtype": "float32", "default": np.float32([0, 0])})
class HasVelocity(Component):
velocity: np.ndarray = field(metadata={"shape": (2, ), "dtype": "float32", "default": np.float32([0, 0])})
world = World(components=[HasPosition, HasVelocity])
# both velocity and position (data) are optional since they have a default
eid1 = world.add_entity(components=[HasPosition, HasVelocity])
# data is passed as kwargs to add_entity
eid2 = world.add_entity(components=[HasPosition, HasVelocity],
velocity=np.float32([1, 1]))
world.update() # add_entity uses a command buffer internally until this is called
print(f"Added 2 entities. Id1={eid1}, Id2={eid2}")
# Querying: batch operate on all entities at once.
qr = world.query(HasVelocity) # qr is a QueryResult object, a numpy-based Structure of Arrays (SoA).
qr.velocity += np.float32([0.1, 0.5])
Documentation
- Primitives — the five building blocks (
Component,Entity,Pool,QueryResult,World), mutation timing, and how numpy-like the query views really are. - Systems & Per-Entity Iteration — writing systems, the three ways to touch data (vectorized,
zip-rows, theEntityAPI), and when each is right. - Hello World (raylib) — a complete runnable program, walked through part by part.
- Benchmarks — microecs vs OOP, and microecs vs six other Python ECS libraries (including the C++ EnTT and C flecs bindings) across seven workloads and an N-sweep to 1M.
1 maintainer
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