Gdstk (GDSII Tool Kit) is a C++ library for creation and manipulation of GDSII and OASIS files. It is also available as a Python module meant to be a successor to Gdspy.

Key features for the creation of complex CAD layouts are included:

• Boolean operations on polygons (AND, OR, NOT, XOR) based on clipping algorithm
• Polygon offset (inward and outward rescaling of polygons)
• Efficient point-in-polygon solutions for large array sets

Typical applications of Gdstk are in the fields of electronic chip design, planar lightwave circuit design, and mechanical engineering.

The complete documentation is available here.

The source files can be found in the docs directory.

The C++ library is meant to be used by including it in your own source code.

If you prefer to install a static library, the included CMakeLists.txt should be a good starting option (use -DCMAKE_INSTALL_PREFIX=path to control the installation path):

cmake -S . -B build
cmake --build build --target install

The library depends on zlib.

The Python module can be installed via pip, Conda or compiled directly from source. It depends on:

• zlib
• qhull
• CMake
• Python
• Numpy
• Sphinx, Read the Docs Theme, and Sphinx Inline Tabs (to build the documentation)

Simply run the following to install the package for the current user:

pip install --user gdstk

Or download and install the available wheels manually.

Windows users are suggested to install via Conda using the available conda-forge recipe. The recipe works on MacOS and Linux as well.

To install in a new Conda environment:

# Create a new conda environment named gdstk
conda create -n gdstk -c conda-forge --strict-channel-priority
# Activate the new environment
conda activate gdstk
# Install gdstk
conda install gdstk

To use an existing environment, make sure it is configured to prioritize the conda-forge channel:

# Configure the conda-forge channel
conda config --env --add channels conda-forge
conda config --env --set channel_priority strict
# Install gdstk
conda install gdstk

The module must be linked against zlib. The included CMakeLists.txt file can be used as a guide.

Installation from source should follow the usual method (there is no need to compile the static library beforehand):

python setup.py install

Help support Gdstk development by donating via PayPal or sponsoring me on GitHub.

The benchmarks directory contains a few tests to compare the performance gain of the Python interface versus Gdspy. They are only for reference; the real improvement is heavily dependent on the type of layout and features used. If maximal performance is important, the library should be used directly from C++, without the Python interface.

Timing results were obtained with Python 3.11 on an Intel Core i7-9750H @ 2.60 GHz They represent the best average time to run each function out of 16 sets of 8 runs each.

Memory usage per object for 100000 objects: