Scripting
Run Jupyter-based custom workflows on your team clusters.
The Scripting module runs Jupyter sessions on team clusters for custom analysis, plotting, and data preparation. It supports general notebooks and notebooks linked to a specific trajectory, and ships with the scientific Python stack preinstalled.
Notebook scopes
| Scope | What It Is For |
|---|---|
| General | Shared scratchpads, utilities, and workflows not anchored to a single trajectory |
| Trajectory | Notebook work tied to one specific simulation dataset |
How sessions are created
Opening a notebook coordinates a Jupyter runtime on the cluster. The backend resolves a suitable team cluster, deduplicates concurrent startups for the same session, provisions or reuses the notebook runtime container, and proxies the Jupyter interface back into the app. Notebook startup runs through this lifecycle before the workspace is ready.
What comes preinstalled
The notebook image includes voltsdk, numpy, scipy, pandas, matplotlib, ovito, ase, pymatgen, MDAnalysis, matminer, vtk, minio, and msgpack.
Trajectory-linked workspaces
When opened from a trajectory context, Scripting creates or reuses notebooks scoped to that trajectory and can seed an example notebook.
Notebook management
The listing supports search, rename, and delete operations. Deleting a notebook also tears down its associated runtime state.
Scripting vs. plugins
Scripting suits exploratory, temporary, or custom-Python work. Plugins suit stable, repeatable workflows shared across the team.