pytrip98 3.11.0

PyTRiP: Python tools for TRiP98 treatment planning and data handling

PyTRiP98 is a python package for working with TRiP98 and VIRTUOS/VOXELPLAN files. It is mainly supposed for batch processing, but an experimental GUI is also included (see https://github.com/pytrip/pytripgui).

PyTRiP provides several command-line applications including trip2dicom, dicom2trip and cubeslice. They works under Linux, Windows and Mac OSX operating systems (interpreter of Python programming language has to be also installed). No programming knowledge is required from the user, but basic skills in working with the console are needed to use them.

Documentation

Full PyTRiP documentation can be found here: https://pytrip.readthedocs.io/

See Getting Started for installation and basic information, and the User’s Guide for an overview of how to use the PyTRiP library.

Installation

PyTRiP98 is distributed as pre-built wheels for CPython 3.9–3.14 on Linux, macOS and Windows. The wheels are produced by cibuildwheel via GitHub Actions. NumPy 2.x is required.

We strongly recommend using a Python virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

Basic installation (latest release from PyPI):

pip install pytrip98

Optional remote execution support (adds paramiko):

pip install "pytrip98[remote]"

To build from source (requires a C compiler and Python headers):

git clone --recurse-submodules https://github.com/pytrip/pytrip.git
cd pytrip
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -e .

The build is managed by pyproject.toml (PEP 621) and uses setuptools; NumPy (>=2.0) headers are installed during wheel builds to ensure a stable ABI.

Local Development

To set up a local development environment:

1. Clone the repository (with test-data submodules):

   git clone --recurse-submodules https://github.com/pytrip/pytrip.git
   cd pytrip
   # If you already cloned without submodules:
   #   git submodule update --init --recursive

2. Create and activate a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies and the package in editable mode:

   pip install -e .[test]
   # If your pip complains about NumPy headers, install NumPy first:
   #   pip install numpy

4. Run tests:

   python -m pytest tests/

5. Build the package locally:

   pip install build
   python -m build