Spinal Tap is a Dash application that provides simple visualization tools for the Scalable Particle Imaging With Neural Embeddings (SPINE) package.
Installation
You can install Spinal Tap and all dependencies (including Dash, Flask, Plotly, and spine) using pip:
pip install .
Or, for editable development mode:
pip install -e .
Usage
Launch the application and open http://localhost:8888 in a browser:
spinal-tap
Check the installed version with:
spinal-tap --version
Spinal Tap provides fast WebGL and Plotly renderers, reconstruction/truth comparison, object filtering and inspection, configurable appearance, and portable exports. The complete user guide covers:
- opening files, manifests, uploads, URLs, and shared views,
- display controls and object inspection,
- appearance and camera controls, and
- sharing and export formats.
See the Spinal Tap documentation for the full installation, usage, deployment, and development guides.
Deployment
Kubernetes
Spinal Tap is deployed on SLAC's S3DF Kubernetes infrastructure and is accessible at:
https://spinal-tap.slac.stanford.edu
S3DF input paths may use either the host form /sdf/data/neutrino/... or the
container form /data/...; Spinal Tap resolves both forms automatically.
Readers and built events are cached per application process. The bounds can be
configured with SPINAL_TAP_READER_CACHE_SIZE (default 8) and
SPINAL_TAP_EVENT_CACHE_SIZE (default 2); set either to 0 to disable that
cache. Compact binary scenes are held in an eight-entry process-local LRU while
the browser fetches them; configure this bound with
SPINAL_TAP_SCENE_CACHE_SIZE (minimum 1).
The Kubernetes configuration files are located in the k8s/ directory. For deployment instructions and SLAC-specific configuration details, see:
k8s/README.md- Deployment guidek8s/SLAC_CONFIG.md- Detailed SLAC S3DF configuration
Docker
Docker images are automatically built and published to GitHub Container Registry when version tags are pushed:
docker pull ghcr.io/deeplearnphysics/spinal-tap:latest
To run locally with Docker:
docker run -p 8888:8888 ghcr.io/deeplearnphysics/spinal-tap:latest
Development & CI/CD
- Code style is enforced with black, isort, and flake8 (pre-commit and CI).
- The GitHub Actions workflow builds and tests on every commit, PR, tag, and release.
- The complete test suite enforces 100% statement coverage and publishes its report to Codecov.
- Docker images are built automatically on version tag pushes (e.g.,
v0.1.2). - Publishing:
- On tag push: publishes to Test PyPI (requires
TEST_PYPI_API_TOKENsecret). - On GitHub Release: publishes to PyPI (requires
PYPI_API_TOKENsecret).
- On tag push: publishes to Test PyPI (requires
1 maintainer
Metadata
1 maintainer
Release files for spinal-tap 1.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| spinal_tap-1.1.0.tar.gz | 821.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| spinal_tap-1.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 1.6 MB
Release files / spinal_tap-1.1.0.tar.gz
| Download URL | spinal_tap-1.1.0.tar.gz |
|---|---|
| Size | 821.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
|
BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.11.16
|
Release files / spinal_tap-1.1.0-py3-none-any.whl
| Download URL | spinal_tap-1.1.0-py3-none-any.whl |
|---|---|
| Size | 788.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
114475a9d6581f5ed91f9b491bac33be1e25862b3cf9013b3d6b6310b08214bc
|
|
BLAKE2b-256 checksum How to use checksums |
82e4997ff5ff150652847da080556e5f130367a1f728500b0136f67419d7a21e
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.11.16
|
