Benchmarks

To get a grip of the actual performance of Pymunk this page contains a number of benchmarks.

The full code of all benchmarks are available under the benchmarks folder.

Micro benchmarks

In order to measure the overhead created by Pymunk in the most common cases I have created two micro benchmarks. They should show the speed of the actual wrapping code, which can tell how big overhead Pymunk creates, and how big difference different wrapping methods does.

The most common thing a typical program using Pymunk does is to read out the position and angle from a Pymunk object. Usually this is done each frame for every object in the simulation, so this is a important factor in how fast something will be.

Given this our first test is:

t += b.position.x + b.position.y + b.angle

(see pymunk-get.py)

Running it is simple, for example like this for pymunk 4.0:

> python -m pip install pymunk==4.0
> python pymunk-get.py

The second test we do is based on the second heavy thing we can do, and that is using a callback, for example as a collision handler or a position function:

def f(b,dt):
    b.position += (1,0)

s.step(0.01)

(see pymunk-callback.py)

Results:

Tests run on a HP G1 1040 laptop with a Intel i7-4600U. Laptop runs Windows, and the tests were run inside a VirtualBox VM running 64bit Debian. The CPython tests uses CPython from Conda, while the Pypy tests used a manually downloaded Pypy. CPython 2.7 is using Cffi 1.7, the other tests Cffi 1.8.

Remember that these results doesn’t tell you how you game/application will perform, they can more be seen as a help to identify performance issues and know differences between Pythons.

Pymunk-Get:

CPython 2.7.12 CPython 3.5.2 Pypy 5.4.1
Pymunk 5.1 2.1s 2.2s 0.36s
Pymunk 5.0 4.3s 4.5s 0.37s
Pymunk 4.0 1.0s 0.9s 0.52s

Pymunk-Callback:

CPython 2.7.12 CPython 3.5.2 Pypy 5.4.1
Pymunk 5.1 5.7s 6.8s 1.1s
Pymunk 5.0 6.5s 7.3s 1.0s
Pymunk 4.0 5.1s 6.5s 4.5s

What we can see from these results is that you should use Pypy if you have the possibility since that is much faster than regular CPython. We can also see that moving from Ctypes to Cffi between Pymunk 4 and 5 had a negative impact in CPython, but positive impact on Pypy, and Pymunk 5 together with Pypy is with a big margin the fastest option.

The speed increase between 5.0 and 5.1 happened because the Vec2d class and how its handled internally in Pymunk was changed to improve performance.

Compared to Other Physics Libraries

Cymunk

Cymunk is an alternative wrapper around Chipmunk. In contrast to Pymunk it uses Cython for wrapping (Pymunk uses CFFI) which gives it a different performance profile. However, since both are built around Chipmunk the overall speed will be very similar, only when information passes from/to Chipmunk will there be a difference. This is exactly the kind of overhead that the micro benchmarks are made to measure.

Cymunk is not as feature complete as Pymunk, so in order to compare with Pymunk we have to make some adjustments. A major difference is that it does not implement the position_func function, so instead we do an alternative callback test using the collision handler:

h = s.add_default_collision_handler()
def f(arb):
    return false
h.pre_solve = f

s.step(0.01)

(see pymunk-collision-callback.py and `cymunk-collision-callback.py)

Results

Tests run on a HP G1 1040 laptop with a Intel i7-4600U. Laptop runs Windows, and the tests were run inside a VirtualBox VM running 64bit Debian. The CPython tests uses CPython from Conda, while the Pypy tests used a manually downloaded Pypy. Cffi version 1.10.0 and Cython 0.25.2.

Since Cymunk doesnt have a proper release I used the latest master from its Github repository, hash 24845cc retrieved on 2017-09-16.

Get:
CPython 3.5.3 Pypy 5.8
Pymunk 5.3 2.14s 0.33s
Cymunk 20170916 0.41s (10.0s)
Collision-Callback:
CPython 3.5.3 Pypy 5.8
Pymunk 5.3 3.71s 0.58s
Pymunk 20170916 0.95s (7.01s)

(Cymunk results on Pypy within parentheses since Cython is well known to be slow on Pypy)

What we can see from these results is that Cymunk on CPython is much faster than Pymunk on CPython, but Pymunk takes the overall victory when we include Pypy.

Something we did not take into account is that you can trade convenience for performance and use Cython in the application code as well to speed things up. I think this is the approach used in KivEnt which is the primary user of Cymunk. However, that requires a much more complicated setup when you develop your application because of the compiler requirements and code changes.