Skip to main content
This is a pre-production deployment of Warehouse. Changes made here affect the production instance of PyPI (
Help us improve Python packaging - Donate today!

Python/pyglet library for importing Wavefront .obj files

Project Description


This python module allows you to read Wavefront 3D object files
(`something.obj` and `something.mtl`) and use them as Python objects.
Currently Pyglet is required to render and display these objects.

Currently, only a subset of [the defined
specification]( has
been implemented.


* [Pyglet](


### From Python

import pywavefront
meshes = pywavefront.Wavefront('something.obj')

### Example Script

There are two pyglet example scripts with included `.obj` and `.mtl` files in the `example` directory. To run them, change to the `example`
directory and run either `./` or ``.

### Generating a Wavefront file with Blender

The following presumes you are using [Blender]( to generate your mesh:

* Using Blender, create a mesh with a UV-mapped texture. The UV-mapping is important! If it is working properly, you will see the texture applied within Blender's 3d view.
* Export the mesh from Blender using the Wavefront format, including normals.
* Reference your `*.obj` file as in the pywavefront example above.


### Source distribution

Assuming you are in the top-level PyWavefront directory:

python install

### Pip

pip install PyWavefront


All tests can be found in the `test` directory. To run the tests:

* Install nose: `pip install nose`
* Change to the top-level directory, e.g. `PyWavefront`, the directory that contains this `README` file.
* Run `nosetests`


* Jerek Shoemaker
* Kurt Yoder
* Zohar Jackson


PyWavefront is BSD-licensed; see file `LICENSE`.

Release History

History Node


History Node


This version
History Node


History Node


History Node


History Node


History Node


Download Files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, Size & Hash SHA256 Hash Help File Type Python Version Upload Date
(8.1 kB) Copy SHA256 Hash SHA256
Source None Jan 28, 2017

Supported By

Elastic Elastic Search Pingdom Pingdom Monitoring Dyn Dyn DNS Sentry Sentry Error Logging CloudAMQP CloudAMQP RabbitMQ Heroku Heroku PaaS Kabu Creative Kabu Creative UX & Design Fastly Fastly CDN DigiCert DigiCert EV Certificate Google Google Cloud Servers DreamHost DreamHost Log Hosting