pyOCCT — Python bindings for OpenCASCADE

The pyOCCT project provides Python bindings to the OpenCASCADE geometry kernel via pybind11. Together, this technology stack enables rapid CAD/CAE/CAM application development in the popular Python programming language.

If you are looking for Python bindings for CAE capabilities, check out pySMESH.

Enabling technology

The pyOCCT core technology stack includes:

• OpenCASCADE: Open CASCADE Technology (OCCT) is an object-oriented C++ class library designed for rapid production of sophisticated domain-specific CAD/CAM/CAE applications.

• pybind11: A lightweight header-only library that exposes C++ types in Python and vice versa, mainly to create Python bindings of existing C++ code.

Getting started using conda

Conda packages are available for a number of platforms and Python versions. Get started with:

conda create -n pyocct python=3.8
activate pyocct
conda install -c conda-forge -c trelau pyocct

This will create an environment named "pyocct" and install pyOCCT and all necessary dependencies. You can replace the "pyocct" environment name with anything you'd like.

To support minimal visualization the wxPython package is required and can be installed via conda by:

conda activate pyocct
conda install -c conda-forge wxpython

Navigate to the examples/ folder and run from the active environment:

python import_step.py

and you should see the following image in the viewing tool if all the requirements are correctly installed.

Installation files can be cleaned up by:

conda clean -a

Building from sources

To build from sources, you must generate the binding source code locally. This can be done using the pyOCCT_binder project which is available as a git submodule in this repository within the binder/ folder.

Clone this repository and use the --recurse-submodules command to initialize and download the external pyOCCT_binder project:

git clone --recurse-submodules https://github.com/trelau/pyOCCT.git

The binder uses clang to parse the C++ header files of the libraries and generate the source code. If you are familiar with conda, an environment can be created for this task by:

conda env create -f binder/environment.yml

If all the necessary dependencies are available, the binder can be run to generate the binding sources:

python binder/run.py -c binder/config.txt -o src

Be sure and check the output from the binding generation process in the command prompt in case there are missing header files or other errors.

After the binding sources are generated:

mkdir build
cd build
cmake ..

Note that PTHREAD_INCLUDE_DIR will likely need defined manually since it cannot typically not be automatically found by CMake.