This release is a pre-release and may not be stable for production use.
pyjoltphysics: Jolt Physics for Python
pyjoltphysics wraps Jolt Physics 5.6.0
for Python with nanobind. The design steps
a Jolt PhysicsSystem on a native thread the module owns, takes commands as
arrays and publishes each tick's poses as read-only NumPy views.
>>> import numpy as np
>>> import pyjoltphysics as pj
>>> with pj.World(pj.WorldSettings(threads=4)) as world:
... floor = world.add_bodies(pj.BodyBatch.plane())
... uids, seq = world.add_bodies(pj.BodyBatch.boxes(np.random.uniform(0, 4, (500, 3)) + (0, 2, 0),
... size=(0.25, 0.25, 0.25)))
... world.run_ticks(240) # or world.start() to free-run at tick_hz
... snapshot = world.latest() # read-only NumPy views, no copy
... resting = snapshot.position[snapshot.rows_of(uids), 1]
... events = world.drain_events() # contact, trigger, sleep and wake records
... hit = world.raycast((0, 10, 0), (0, -1, 0), 50.0) # on this thread, under a shared lock
... hero = world.add_character((0.0, 1.0, 0.0), pj.CharacterCapabilities(jumpHeight=1.5))
... hero.set_move((1.0, 0.0, 0.0), 'run')
... world.run_ticks(60)
... where = hero.position, hero.state
A World steps on its own thread at tick_hz (120 by default) or in lockstep
with run_ticks(n). Commands are batches of arrays applied at the start of
the next tick; each tick publishes a snapshot of every body's pose and
velocity into a pool of reference-counted buffers, and appends one 72-byte
record per contact begin, end and (on request) persist to an event ring.
Callbacks run on the world thread only when registered. Shapes are boxes,
spheres, capsules, cylinders, static planes, convex hulls, triangle meshes,
height fields (and landscapes of height field tiles) and compounds, each
built once and shared by every body naming its id, with scale, offset and
centre of mass as body parameters. Static meshes and height fields smooth
their inner edges (Jolt's enhanced internal edge removal) unless a body asks
otherwise.
Rays, ray batches, shape sweeps and overlaps run on the calling thread under
the world lock's shared side, with the GIL released: 100,000 scattered rays
take 55 ms. Characters are omi_physics' controller over Jolt's
CharacterVirtual (walk, run, sprint, crouch, an exact ballistic jump,
stairs, slopes, slides, knock-downs, landings, pushing, platforms, pass
groups), moved on the world thread every tick and read from the snapshot; 300
of them on a height field take 0.60 ms a 60 Hz frame on 8 job threads.
swap_bodies replaces tiles of a streamed landscape in one tick.
Joints (fixed, ball, hinge, slider, distance, six-axis with universal and
two-axis hinge builders, and X3D's motor joint) take limits, springs,
friction and motors, break past a force or torque, and report their angle,
position, force and torque in the snapshot. Materials combine by the OMI
modes, with an (M, M) pair table and static friction below a slip speed.
Collision filters are an (F, F) table changeable at run time. A Python
contact filter is asked on Jolt's job threads about pairs that opted in.
Gravity zones (box, sphere or shape regions; directional or point fields),
quadratic drag and kinematic tracks run natively each tick. Vehicles are
Jolt's vehicle constraint with a wheeled, motorcycle or tracked controller
(suspension, tyre curves, engine, gearbox, differentials, anti-roll bars),
driven by input batches and read from the snapshot with every wheel's pose,
load, slip and the surface under it; ten cars step in 0.05 ms a tick.
VehicleSettings.from_raycast maps omi_physics' raycast vehicle tuning.
Ragdolls are Jolt's ragdoll, a body a bone joined by swing-twist limits,
kinematic (following an animated pose exactly), powered (motors per bone
turning it towards the pose, the root held by a limited spring) or limp, with
blends between the modes; the pose target is a held pose or a clip the world
thread evaluates each tick, and every joint's pose is one slice of one
snapshot array. Soft bodies are Jolt's: cloth, ropes, pressure balls and any
triangle mesh, pinned to world points or to moving bodies, blown by wind,
colliding with rigid bodies, their vertices and normals float32 views in the
snapshot rewritten only when they moved. Twenty ragdolls and five cloths of
1,024 vertices take 0.46 ms a 60 Hz tick on 8 job threads (median of four).
docs/API.md describes every call.
The build information:
>>> import pyjoltphysics
>>> pyjoltphysics.jolt_version()
'5.6.0'
>>> pyjoltphysics.build_options()
BuildOptions(double_precision=True, cross_platform_deterministic=True,
simd_level='sse4.2', free_threaded=False, debug=False,
compiler='gcc 13.3.0')
>>> pyjoltphysics.selftest()
True
| Function | Returns |
|---|---|
jolt_version() |
the Jolt version compiled in, '5.6.0' |
build_options() |
a frozen BuildOptions, fields below |
selftest() |
True after one 1/60 s step of a world holding one falling box, on the calling thread with the GIL released |
Build options
Every wheel is built with the same Jolt options.
BuildOptions field |
Value in a wheel | Jolt setting |
|---|---|---|
double_precision |
True |
JPH_DOUBLE_PRECISION: positions are 64-bit floats, where 32-bit ones resolve 0.98 mm between 8 and 16 km from the origin |
cross_platform_deterministic |
True |
JPH_CROSS_PLATFORM_DETERMINISTIC: the same inputs step to the same bits on x86-64 and arm64 |
simd_level |
'sse4.2' on x86-64, 'neon' on arm64 |
x86-64 compiles for -march=x86-64-v2 (SSE3, SSSE3, SSE4.1, SSE4.2, POPCNT, CMPXCHG16B, LAHF/SAHF), with AVX, AVX2, F16C, FMA, LZCNT and TZCNT off. Intel Nehalem (2008) and later Core and Xeon, Intel Silvermont (2013) and later Atom, and AMD Bulldozer (2011), Jaguar (2013) and later have it. Intel Core 2, Bonnell and Saltwell Atom, and AMD K10 (Phenom II, Athlon II) and Bobcat lack it, and the module does not run on them |
free_threaded |
True in the cp313t and cp314t wheels |
nanobind's FREE_THREADED: importing the module leaves the GIL off |
debug |
False |
no JPH_ENABLE_ASSERTS, NDEBUG defined, no debug renderer or profiler |
compiler |
such as 'gcc 14.2.1' |
the compiler that built the module |
The module and Jolt are compiled with floating-point contraction off
(-ffp-contract=off, or /fp:precise on MSVC) and without fast-math, since a
fused multiply-add changes the result of a step between machines. Jolt is a
static library inside the module, its symbols hidden; the module needs no
system library beyond the C++ runtime.
Install
pip install pyjoltphysics
Wheels cover CPython 3.10 and 3.11, one abi3 wheel for CPython 3.12 and later, and free-threaded CPython 3.13t and 3.14t, on manylinux and musllinux x86_64 and aarch64, macOS arm64 and x86_64, and Windows AMD64 and ARM64. The package needs NumPy.
Build from source
The sdist carries Jolt's library sources. A checkout carries them as a git submodule:
git clone --recurse-submodules https://github.com/mcfletch/pyjoltphysics
pip install ./pyjoltphysics
A build needs a C++17 compiler; scikit-build-core fetches CMake and Ninja
where the machine has none. In an existing checkout,
git submodule update --init fetches Jolt.
The C++ is src/_native.cpp (the module and its build information) and
src/native/, a file per concern: world (the thread and the tick),
commands and apply (batches), snapshot, events, callbacks (Python on
the world thread), layers (collision groups), shapes, queries (rays,
sweeps, overlaps), characters (the controller over CharacterVirtual),
vehicles (the vehicle constraint and its inputs, forces and blows),
ragdolls (Jolt's ragdoll, its modes and pose targets), softbodies (soft
bodies, their pins, wind and vertex cache),
seams (edge removal across static bodies laid flush) and bind_world (the
nanobind classes).
An editable install keeps a build directory per wheel tag under build/, so
reinstalling after a change to a source file recompiles that file only:
pip install -e '.[dev]'
src/pyjoltphysics/_native.pyi is generated by nanobind from the built
module and committed. After a change to the module's signatures:
python -m nanobind.stubgen -p tools/stub-patterns.txt -m pyjoltphysics._native -o src/pyjoltphysics/_native.pyi
tests/test_stub.py and the CI stubs job fail when the committed stub and
the generated one differ. tools/stub-patterns.txt leaves out World.__del__,
which nanobind writes differently on Python 3.12 and earlier than on 3.13 and later.
Tests
pytest
tox # lint, typecheck, stubs and the suite per interpreter
tox -e asan # the suite against an ASan, UBSan and float-cast-overflow build (Linux, gcc)
python benchmarks/boxes5000.py --threads 1 8
python benchmarks/statics.py --threads 1 8
python benchmarks/characters.py --threads 1 8 # characters, tile streaming, rays, query waits
python benchmarks/vehicles.py --threads 1 8 # ten cars on a height field
python benchmarks/ragdolls_cloth.py --threads 1 8 # 20 ragdolls and 5 cloths of 1,024 vertices
tests/differential/ compares Jolt with omi_physics, the reference engine,
within the tolerance each test states: shapes resting on box, mesh and height
field grounds, slides by friction, bounces, stacks, a pyramid, stairs,
triggers, continuous detection, a bin of 1,000 boxes, a compound, characters (a
run across a height field, stairs, slopes, a jump at gravity 42, a fall)
against omi_physics' controller, and glisteel's car (settling, acceleration,
braking, cornering, a jump, a wall, a banked road, bumps) against omi_physics'
raycast vehicle. omi_physics' side is its recorded answer
(tests/differential/omi_golden.json), so the suite runs without it; where
omi_physics is installed each recorded answer is also checked against a live
run, within 0.1% or 0.1 mm. PYJOLTPHYSICS_RECORD_OMI=<path> writes the
answers a run computes to <path> instead. The tests are marked
differential. omi_physics has no ragdoll or soft body, so tests/test_ragdolls.py
and tests/test_softbodies.py hold those to analytic expectations: rest
within the joint limits, the animated pose to 1 mm, a hanging cloth's pins to
0.1 mm, no vertex inside a sphere by more than its radius, a rope's length.
Licence
pyjoltphysics is MIT licensed; see LICENSE. The compiled module carries Jolt
Physics (MIT, Jorrit Rouwe) and the nanobind runtime (BSD 3-Clause, Wenzel
Jakob); NOTICE names both, and the wheel carries their licence files.
1 maintainer
Metadata
1 maintainer
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