Installation

Installation#

pip install harpy-analysis

With extras

pip install "harpy-analysis[extra]"

[extra] installs optional dependencies for:

  • Segmentation: cellpose

  • OpenCV support: opencv-python-headless

  • FlowSOM Clustering: flowsom, scikit-learn

  • Notebook workflows: ipywidgets, tqdm, bokeh, textalloc, joypy, supervenn, nbconvert, ipython

  • CLI workflows: hydra-core, hydra-colorlog, submitit, hydra-submitit-launcher

With extras and napari

pip install "harpy-analysis[extra,napari]"

[napari] adds:

  • napari[all]

  • napari-spatialdata

Only for developers. Clone this repository locally, install the .[dev] instead of the .[extra] dependencies and read the contribution guide.

# Clone repository from GitHub
uv venv --python=3.12  # create venv using uv, set python version (>=3.11)
source .venv/bin/activate  # activate the virtual environment
uv pip install -e '.[dev]'  # editable install with dev tooling
python -c 'import harpy; print(harpy.__version__)'  # check if the package is installed
# make changes
python -m pytest  # run the tests

Installation using conda#

It is possible to install Harpy using Anaconda although we recommend uv, and we provide an environment.yml.

1. Create the conda environment:#

# Use standard Conda environment creation
conda env create -f environment.yml
# Or use Mamba as alternative
mamba env update -f environment.yml --prune

conda activate harpy

If you plan to use the Harpy function harpy.im.tiling_correction, please install jax and basicpy. On Mac and Linux, this can be done via pip install ..., on Windows you will have to run the following commands:

pip install "jax[cpu]" -f https://whls.blob.core.windows.net/unstable/index.html --use-deprecated legacy-resolver
pip install basicpy

On Mac, please comment out the line mkl=2024.0.0 in environment.yml.

For a mimimal list of requirements for Harpy, we refer to the pyproject.toml.

2. Install Harpy:#

pip install "harpy-analysis[extra]"

3. Additional dependencies#

To be able to run the unit tests:

pip install "git+https://github.com/saeyslab/harpy.git#egg=harpy-analysis[dev]"

NVIDIA GPU support#

We recommend using uv, however, it is possible to use Anaconda, and we provide environment_vib_compute.yml that will install torch with NVIDIA GPU support on Linux (tested on CentOS). After creation of the environment via conda env create -f environment_vib_compute.yml, activate the environment, and install Harpy via pip install git+https://github.com/saeyslab/harpy.git.

For VIB members we also refer to this document, for an example on how to use the VIB compute cluster with GPU support.