Installation Guide (original) (raw)

Dependencies

Colour requires various dependencies in order to run and follows theminimum supported versionsas given by Scientific Python. Depending on your intended use case, i.e., using or developing, you may not need to install all of them.

Please refer to the Installation Methods for Using Colourand Installation Methods for Developing Colour sections below.

Primary Dependencies

• python >= 3.11, < 3.15
• numpy >= 2.0.0, < 3

Optional, Meshing and Plotting Dependencies

• imageio >= 2, < 3
• matplotlib >= 3.9
• networkx >= 3.3, < 4
• opencolorio >= 2, < 3
• openimageio >= 3, < 4
• pandas >= 2.2, < 3
• pydot >= 3, < 4
• scipy >= 1.13.0, < 2
• tqdm >= 4, < 5
• trimesh >= 4, < 5
• xxhash >= 3, < 4

Development Dependencies

• biblib-simple
• coverage
• coveralls
• hatch
• invoke
• jupyter
• pre-commit
• pyright
• pydata-sphinx-theme
• pytest
• pytest-cov
• pytest-xdist
• restructuredtext-lint
• sphinx
• sphinxcontrib-bibtex
• toml
• twine

Installation Methods for Using Colour

Pypi

Colour can be easily installed from thePython Package Index by issuing this command in a shell:

pip install --user colour-science

This asciicast demonstrates how to generate a pristine Python _VirtualEnv_environment for Colour:

The optional features dependencies are installed as follows:

pip install --user 'colour-science[optional]'

The development dependencies are installed as follows:

pip install --user 'colour-science[development]'

The graphviz figure plotting dependencies are installed as follows:

pip install --user 'colour-science[graphviz]'

The meshing dependencies for gamut computations are installed as follows:

pip install --user 'colour-science[meshing]'

If you wish to read OpenEXR files, you will need to install the _FreeImage_plugin for Imageio as follows:

python -c "import imageio;imageio.plugins.freeimage.download()"

Continuum Analytics Anaconda

Colour is also available for Anacondafrom Continuum Analytics via conda-forge:

conda install -c conda-forge colour-science

This asciicast demonstrates how to generate a pristine Python _conda_environment for Colour:

Github

Alternatively, you can also install directly fromGithub source repository:

git clone git://github.com/colour-science/colour.git cd colour pip install --user .

Installation Methods for Developing Colour

uv

Colour adopts uv to help managing its dependencies, this is the recommended way to get started with Colourdevelopment.

Assuming python >= 3.11, < 3.15 is available on your system, the development dependencies are installed withuv as follows:

git clone git://github.com/colour-science/colour.git cd colour uv sync --all-extras

Those commands will create a Virtual Environment in which all the required python packages will be installed.

Tools can then be run as follows:

or alternatively:

source .venv/bin/activate invoke -l

Vagrant

An easy way to get all the pre-requisites at once is to use ourcolour-vagrantenvironment for Vagrant.

Please refer to the dedicated blog post for more details about its deployment:PyCharm, Vagrant, Ansible & Poetry