Getting Started#
The default install path is one command from PyPI.
1. Create a Python environment#
python3 -m venv .venv
source .venv/bin/activate
2. Install PalaceToolkit#
pip install palace-toolkit
On Linux x86_64, this also fetches the matching prebuilt Palace CPU runtime on first use. You can also install it explicitly:
palace-toolkit-install-binary
3. Verify Palace runtime#
palace-toolkit-check
Expected output includes Palace runtime check: OK, the selected runtime path,
and a Palace version line.
3b. WSL users (optional GUI + runtime libraries)#
Some WSL environments need additional runtime libraries:
sudo apt update
sudo apt install -y libglu1-mesa-dev libgomp1 libxft2
For interactive matplotlib windows in WSL:
sudo apt install -y python3-tk
Then set the backend in ~/.config/matplotlib/matplotlibrc:
backend: TkAgg
4. Optional power-user source builds (latest/custom Palace)#
Use this only when you explicitly want a source-built Palace (nightly/custom flags such as CUDA/HIP/MAGMA):
git clone https://github.com/EpsilonForge/PalaceToolkit.git
cd PalaceToolkit
python3 -m venv .venv
source .venv/bin/activate
PALACETOOLKIT_BUILD_PALACE=1 PALACETOOLKIT_CLONE_NIGHTLY=1 pip install -e .
You can then point PalaceToolkit at your custom runtime via Python:
python -c "from palacetoolkit.simulation import set_palace_path; set_palace_path('/path/to/palace-or-Palace.sif')"
See the dedicated Ubuntu build guide and compatibility policy for details.