Skip to content

Installation

NeuroQP Python requires Python 3.12 through 3.14. Install it in a dedicated environment for each analysis project so its packages do not conflict with other work.

Install NeuroQP Python

Choose the environment tool you already use. pip is available with Python; uv additionally records the analysis dependencies and their resolved versions.

Create and activate a virtual environment, then install NeuroQP Python.

macOS and Linux

python3.14 -m venv .venv
source .venv/bin/activate
python -m pip install neuroqp

Windows PowerShell

py -3.14 -m venv .venv
.venv\Scripts\Activate.ps1
python -m pip install neuroqp

Run the activation command again whenever you return to the analysis in a new terminal. If you already have an active environment, only run python -m pip install neuroqp.

Confirm the installation:

python -c "import neuroqp; print(neuroqp.__version__)"
neuroqp --help

Initialize the analysis directory with Python 3.14 and add NeuroQP Python. uv creates and maintains the project’s .venv and uv.lock.

uv init --python 3.14
uv add neuroqp

Run commands in that environment without activating it:

uv run python -c "import neuroqp; print(neuroqp.__version__)"
uv run neuroqp --help

Use Jupyter

Install JupyterLab in the same environment if you want to run the example notebooks or build your analysis interactively.

python -m pip install jupyterlab
jupyter lab

uv add jupyterlab
uv run jupyter lab

Open the downloaded notebook from JupyterLab. Its first code cell downloads the small synthetic example export if the file is not already in the notebook directory.

Update NeuroQP Python

python -m pip install --upgrade neuroqp

uv lock --upgrade-package neuroqp
uv sync

TIFF reading, LZW decompression, disk-backed arrays, and region selection are installed with NeuroQP Python. You do not need to install a separate TIFF plugin.