PySNT

Python wrapper for SNT, the framework for quantification of neuronal anatomy

Installation | Documentation | Support

Technical Features

• Complete Java Bridge: Full programmatic access to SNT's neuroanatomy toolkit from Python (via JPype and ScyJava), enabling integration of advanced tracing, analysis, and visualization capabilities into Python workflows

• Consistent API: 1:1 correspondence with SNT's Java API while maintaining Python conventions, allowing developers familiar with either language to work efficiently

• Full Type Annotation: Type hints for all methods and classes, enabling static type checking with mypy and improved code reliability

• IDE Integration: Autocomplete, inline documentation, and parameter hints in VS Code, PyCharm, Spyder, and Jupyter notebooks through type stubs and docstrings

• Performant: Lazy class loading minimizes initialization overhead, loading only required SNT components on demand

• Native Python Converters: Automatic conversion between SNT objects and Python-native types:

  SNT/ImgLib2 Java Object	PySNT Python Object
  SNTChart	matplotlib Figure
  SNTGraph	NetworkX graph
  SNTTable	xarray Dataset; pandas DataFrame
  ImgPlus/RAI	xarray; numpy
  ImagePlus	xarray; numpy (via ScyJava)
  Collections	lists/dicts, etc. (via ScyJava)

Limitations

• Bleeding Edge: Requires building SNT from the main branch (stable release integration planned for SNT v5.0)

• Early Stage Software: Limited test coverage and community validation: Expect potential bugs and breaking API changes

Getting Started for Users

See Install instructions.

Getting Started for Developers

Environment Setup

# 1. Clone the repository
git clone https://github.com/morphonets/pysnt.git
cd pysnt

# 2. Set up conda/mamba (if not already configured)
mamba config append channels conda-forge
mamba config set channel_priority strict

# 3. Create and activate the development environment
mamba env create -f environment-dev.yml
mamba activate pysnt-dev

# 4. Install PySNT in development mode
pip install -e .[dev]

# 5. Verify the setup
python -c "import pysnt; print('PySNT imported successfully!')"

# 6. Have a look at ./dev/README.md for common workflows

IDE Configuration

PyCharm

1. Open this folder as a project in PyCharm
2. Go to File → Settings → Project → Python Interpreter
3. Select the 'pysnt' environment

VS Code

1. Open this folder in VS Code
2. Install recommended extensions when prompted
3. Select the 'pysnt' Python interpreter when prompted

Spyder

1. Make sure Spyder is installed in the 'pysnt' environment:

    mamba activate pysnt
    mamba install spyder
    mamba install spyder-notebook -c conda-forge # Optional: support for tutorials notebooks

2. Launch Spyder from the activated environment
3. Open this folder as a project: Projects → New Project... → Existing Directory

Project Structure

pysnt/
├── src/pysnt/           # main package source
├── tests/               # test suite
├── dev/scripts/         # development scripts
├── docs/                # documentation source
├── dev/                 # development utilities and templates
├── pyproject.toml       # packaging metadata and dependency groups
├── requirements.txt     # pip core runtime dependencies
├── requirements-gui.txt # pip optional runtime extras (display/gui/java/zarr)
├── requirements-dev.txt # pip development stack (extends requirements-gui.txt)
├── environment-min.yml  # minimal conda-compatible runtime environment
├── environment.yml      # full-featured conda-compatible runtime environment
└── environment-dev.yml  # full-featured conda-compatible development environment

Dependency Files and Scope

• pyproject.toml: canonical dependency definitions for packaging and extras
• requirements.txt: core pip runtime set only
• requirements-gui.txt: optional runtime features layered on top of core (display, gui, java, zarr)
• requirements-dev.txt: development/test/docs tools layered on top of requirements-gui.txt
• environment-min.yml: smallest conda-compatible runtime setup
• environment.yml: full runtime conda-compatible setup with optional user-facing features
• environment-dev.yml: full runtime plus development/test/docs tools

Dependencies

Core Dependencies (Required)

• JPype1 - Python/JVM bridge used by runtime utilities
• matplotlib - Used extensively for plotting and figure creation
• numpy - Used throughout for array operations
• pyimagej - ImageJ integration
• scyjava - Core Java integration
• xarray - Dataset operations

Optional Dependencies (Display/Conversion Features)

• cairosvg - SNTChart SVG to matplotlib conversion
• install-jdk - Automatic OpenJDK installation helper
• ipykernel - Notebook kernel support
• pandas - DataFrame operations and SNTTable conversion
• pandasgui - Interactive DataFrame display
• networkx - SNTGraph to NetworkX graph conversion
• pyobjc-core (macOS only) - Required by PyImageJ GUI mode on macOS
• pyobjc-framework-cocoa (macOS only) - Required by PyImageJ GUI mode on macOS
• PyMuPDF - SNTChart PDF to matplotlib conversion

Optional Dependencies (OME-ZARR)

• fsspec - Remote filesystem access (HTTP/HTTPS/S3)
• zarr - OME-ZARR format support for local and remote data

Install examples:

• pip install -e . (core)
• pip install -e .[display]
• pip install -e .[gui]
• pip install -e .[all]
• pip install -e .[dev]

macOS users: PyImageJ GUI mode requires pyobjc-core and pyobjc-framework-cocoa (or pyobjc). These are included in the GUI-focused dependency files.

Need Help?

• 📖 Documentation: pysnt.readthedocs.io
• 💬 Forum: forum.image.sc/tag/snt
• 🐛 Issues: GitHub Issues