NeuroQP Python

NeuroQP Python lets neuroscientists open a NeuroQP project export, navigate its animals, slices, stainings, images, and registrations, and analyze classification or cell-match results with Python and NumPy.

Installation

Create and activate a virtual environment for your analysis:

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

See the installation guide for uv, Windows, JupyterLab, and update instructions.

Getting started

Validate or inspect an exported NeuroQP project:

neuroqp validate path/to/neuroqp_export.zip
neuroqp inspect path/to/neuroqp_export.zip

Open an export from Python:

from neuroqp import open_export

with open_export("neuroqp_export.zip") as export:
    print(export)

    animal = export.animal_by_name("Mouse 1")
    for slice_ in animal.slices:
        print(slice_.name, slice_.slice_coordinate_mm)

    if export.classification is not None:
        classification = export.classification.for_staining("NeuN")
        results = classification.load_results()
        print(results.positive_centroids)

ZIP archives and extracted export directories are both supported. Continue with the quickstart, analysis guide, or example notebooks.

Project links

• Documentation
• Using NeuroQP with AI coding agents
• AI-readable documentation
• Export v2 specification
• Versions
• Releases
• Changelog
• Questions and support
• Issue tracker

Supported versions

• Python 3.12 through 3.14
• NeuroQP project export format v2

Contributing

See CONTRIBUTING.md if you want to work on the package itself.

License

MIT