Skip to main content

PyGLM

OpenGL Mathematics (GLM) library for Python

GLSL + Optional features + Python = PyGLM
A mathematics library for graphics programming.

PyGLM is a Python extension written in C++.
By using GLM by G-Truc under the hood, it manages to bring glm's features to Python.
Some features are unsupported (such as unstable extensions) - Please see [Unsupported Functions] below.
If you encounter any issues or want to request a feature, please create an issue on the issue tracker.

Tiny Documentation

Why PyGLM?

Besides the obvious - being mostly compatible with GLM - PyGLM offers a variety of features for vector and matrix manipulation.
It has a lot of possible use cases, including 3D-Graphics (OpenGL, DirectX, ...), Physics and more.

At the same time, it has great performance, being between 2x and 15x as fast as numpy! (see end of page)
(depending on the individual function)

Installation

PyGLM supports Windows, Linux, MacOS and other operating systems with either x86 (32-bit) or x64 (64-bit) architecture,
running Python 3.5 or higher. (Prior versions of Python - such as Python 2 - were supported up to PyGLM version 0.4.8b1)

It can be installed from the PyPI using pip:
pip install pyglm
And finally imported and used:
import glm

Using PyGLM

PyGLM's syntax is very similar to the original GLM's syntax.
There is no need to import anything but glm, as it already contains the entire package.
License requirements
Please make sure to include the license for GLM in your project when you use PyGLM!
(this also includes binary distributions, e.g. *.exe)

You can do so by copying either the COPYING or GLM_LICENSE file (or their contents) to your project.
Differences to glm
Instead of using double colons (::) for namespaces, periods (.) are used, so
glm::vec2 becomes glm.vec2.

PyGLM supports the buffer protocol, meaning its compitible to other objects that support the buffer protocol,
such as bytes or numpy.array
(for example you can convert a glm matrix to a numpy array and vice versa).
PyGLM is also capable of interpreting iterables (such as tuples) as vectors, so e.g. the following equasion is possible:
result = glm.vec2(1) * (2, 3)

PyGLM doesn't support precision qualifiers. All types use the default precision (packed_highp).

If a glm function normally accepts float and double arguments, the higher precision (double) is used.

There is no way to set preprocessor definitions (macros).
If - for example - you need to use the left handed coordinate system, you have to use *LH, so
glm.perspective becomes glm.perspectiveLH.

All types are initialized by default to avoid memory access violations.
(i.e. the macro GLM_FORCE_CTOR_INIT is defined)

In case you need the size of a PyGLM datatype, you can use
glm.sizeof(<type>)

The function glm.identity requires a matrix type as it's argument.

The function glm.frexp(x, exp) returns a tuple (m, e), if the input arguments are numerical.
This function may issue a UserWarning. You can silence this warning using glm.silence(1).

The function glm.value_ptr(x) returns a ctypes pointer of the respective type.
I.e. if the datatype of x is float, then a c_float pointer will be returned.
Likewise the reverse-functions (such as make_vec2(ptr)) will take a ctypes pointer as their argument
and return (in this case) a 2 component vector of the pointers underlying type.

glm.silence(ID) can be used to silence specific warnings.
Supplying an id of 0 will silence all warnings.

There is currently no documentation for PyGLM.
Please refer to the source (in Python: *.__doc__) and GLM manuals, references and tutorials.

Unsupported functions
Aside from the unstable extensions,
PyGLM doesn't support the following extensions and methods, due to compatibility issues:
The GLM_GTC_bitfield extension,
glm::log2 from GLM_GTC_integer.
glm::packUnorm and glm::packSnorm from GLM_GTC_packing.

Build options
PyGLM can be built from source in a couple of different ways.
In PyGLM.cpp there is a preprocessor option PyGLM_BUILD which is set to PyGLM_DEFAULT by default.
PyGLM_DEFAULT will build all of PyGLM's functions and features.

A few other flags exist:
PyGLM_FAST removes PyGLM's iterable and GetBuffer checking, thus making it incompatible with tuples, numpy arrays and bytes objects while increasing overall performance.

PyGLM_NO_FUNCTIONS removes all of the functions of glm and only builds the bare types.

PyGLM_MINIMAL combines PyGLM_FAST and PyGLM_NO_FUNCTIONS.

Example

>>> import glm
>>> v = glm.vec3()
>>> v.x = 7
>>> print(v.xxy)
vec3(            7,            7,            0 )

>>> m = glm.mat4()
>>> print(m)
[            1 |            0 |            0 |            0 ]
[            0 |            1 |            0 |            0 ]
[            0 |            0 |            1 |            0 ]
[            0 |            0 |            0 |            1 ]

>>> v = glm.vec4(1, 2, 3, 4)
>>> print(v + (8, 7, 6, 5))
vec4(            9,            9,            9,            9 )

Speed comparison to numpy

How PyGLM's performance roughly compares to NumPy's performance:
instruction     | np speed (%)  | glm speed (%)
import          |   4.76        |  100.00
mat4()          |   9.76        |  100.00
dot(vec3, vec3) |  28.92        |  100.00
transpose(mat4) |  25.64        |  100.00
vec4 * vec4     |  27.89        |  100.00
mat4 * vec4     |  17.68        |  100.00
mat4[0]         |  49.99        |  100.00

Metadata

Release files for pyglm 1.1.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for pyglm 1.1.1
File Size Uploaded
PyGLM-1.1.1.tar.gz 281.9 kB Details

Built distributions (wheels)

Table of built distributions (wheels) for pyglm 1.1.1
File
PyGLM-1.1.1-cp38-cp38-win_amd64.whl CPython 3.8 CPython 3.8 Windows x86-64 Details
PyGLM-1.1.1-cp38-cp38-win32.whl CPython 3.8 CPython 3.8 Windows x86-32 Details
PyGLM-1.1.1-cp37-cp37m-win_amd64.whl CPython 3.7 CPython 3.7 pymalloc Windows x86-64 Details
PyGLM-1.1.1-cp37-cp37m-win32.whl CPython 3.7 CPython 3.7 pymalloc Windows x86-32 Details
PyGLM-1.1.1-cp36-cp36m-win_amd64.whl CPython 3.6 CPython 3.6 pymalloc Windows x86-64 Details
PyGLM-1.1.1-cp36-cp36m-win32.whl CPython 3.6 CPython 3.6 pymalloc Windows x86-32 Details
PyGLM-1.1.1-cp35-cp35m-win_amd64.whl CPython 3.5 CPython 3.5 pymalloc Windows x86-64 Details
PyGLM-1.1.1-cp35-cp35m-win32.whl CPython 3.5 CPython 3.5 pymalloc Windows x86-32 Details

Total release size: 6.6 MB

Release files / PyGLM-1.1.1.tar.gz

Download URL PyGLM-1.1.1.tar.gz
Size 281.9 kB
Tags Source
SHA-256 checksum
How to use checksums
b609cdaffc3a02aad12e937dc8f457b85cc1ba9d6bad2dd9a89f269b0b8d045a
BLAKE2b-256 checksum
How to use checksums
3c15c31f219428ddb6dc67f3b7c2925ed6a5afc587758dde45507231894cf520
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.8.0

Release files / PyGLM-1.1.1-cp38-cp38-win_amd64.whl

Download URL PyGLM-1.1.1-cp38-cp38-win_amd64.whl
Size 861.7 kB
Tags CPython 3.8 Windows x86-64
SHA-256 checksum
How to use checksums
aba8244871bad9e117c2a9bee15198ca521cada08969efd6c41f4d9b18fecdd0
BLAKE2b-256 checksum
How to use checksums
d2bc5387e52ade6317dd0876e4d9a8e57cba43e49e6c515c4b005dcca9d2a076
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.8.0

Release files / PyGLM-1.1.1-cp38-cp38-win32.whl

Download URL PyGLM-1.1.1-cp38-cp38-win32.whl
Size 730.5 kB
Tags CPython 3.8 Windows x86-32
SHA-256 checksum
How to use checksums
7a0035c2a7dfaaa57d166b1cc964f6f4941f9a667ea519a818dd99b082300f43
BLAKE2b-256 checksum
How to use checksums
4ecceb7b2df90b441b2831110dbee6275e1edc720c3a3c41b8633c46aeb7e975
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.8.0

Release files / PyGLM-1.1.1-cp37-cp37m-win_amd64.whl

Download URL PyGLM-1.1.1-cp37-cp37m-win_amd64.whl
Size 856.2 kB
Tags CPython 3.7 CPython 3.7 pymalloc Windows x86-64
SHA-256 checksum
How to use checksums
0661c93fc623211aacb16225f414e11f150da546cfeb73d68c49b15f0bd48c36
BLAKE2b-256 checksum
How to use checksums
0a0cf6d705a49a760cf817638e17fac1889bb08ef60ae0a40089d016a2d4e7d0
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.8.0

Release files / PyGLM-1.1.1-cp37-cp37m-win32.whl

Download URL PyGLM-1.1.1-cp37-cp37m-win32.whl
Size 728.2 kB
Tags CPython 3.7 CPython 3.7 pymalloc Windows x86-32
SHA-256 checksum
How to use checksums
5d977c7173d80028b85480c70174b18748ef1beb7e371a012f758cf877b613c8
BLAKE2b-256 checksum
How to use checksums
ceda8115b46c49741d7b9c723171619d1ac503b1c780de3b30cac7d8b3d12ca4
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.8.0

Release files / PyGLM-1.1.1-cp36-cp36m-win_amd64.whl

Download URL PyGLM-1.1.1-cp36-cp36m-win_amd64.whl
Size 856.2 kB
Tags CPython 3.6 CPython 3.6 pymalloc Windows x86-64
SHA-256 checksum
How to use checksums
2e95b50de09171a8f3ac0ae1773000a3d8e2db98d063276aa89175158f53c0e5
BLAKE2b-256 checksum
How to use checksums
3d3fa77a2436b1eae01b09cfee2e9d2091ba63e705d5014eba873cf1a8ac9bf2
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.8.0

Release files / PyGLM-1.1.1-cp36-cp36m-win32.whl

Download URL PyGLM-1.1.1-cp36-cp36m-win32.whl
Size 728.2 kB
Tags CPython 3.6 CPython 3.6 pymalloc Windows x86-32
SHA-256 checksum
How to use checksums
3dcc550aeecbb0f6350d18efafb86c5fadb3bea3e36136ffdc26289d21fe32db
BLAKE2b-256 checksum
How to use checksums
58525c3079a3fe2aa694ae87ed54da2fd812a9b2be7306bf559ec44514b57593
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.8.0

Release files / PyGLM-1.1.1-cp35-cp35m-win_amd64.whl

Download URL PyGLM-1.1.1-cp35-cp35m-win_amd64.whl
Size 869.6 kB
Tags CPython 3.5 CPython 3.5 pymalloc Windows x86-64
SHA-256 checksum
How to use checksums
75f1c9a2716b64b55c0998c94ded9b3391c2ac26c2a2d8c8ad4177ca711fc147
BLAKE2b-256 checksum
How to use checksums
0e7f38bfc2da00a5994c744d8869b13354bb89ae7398bc6159c4c4d614ad6f15
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.8.0

Release files / PyGLM-1.1.1-cp35-cp35m-win32.whl

Download URL PyGLM-1.1.1-cp35-cp35m-win32.whl
Size 716.8 kB
Tags CPython 3.5 CPython 3.5 pymalloc Windows x86-32
SHA-256 checksum
How to use checksums
3b751aae3e8c2d047c19dad1fcc5223abd6b0865f5c2cfee9d30f021e65a8e43
BLAKE2b-256 checksum
How to use checksums
73d5dc9a11c8298214684cdd67c9de954dd7d6ac1d12f1e49126d4a06762717b
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.8.0

Release history Release notifications | RSS feed

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page