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
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github-hosted -
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