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DataLab Web

Full-Web reimplementation of the DataLab scientific data-processing platform — the entire computation engine and processing catalog run inside the browser.

DataLab Web overview, with Eze-sur-mer in the background

DataLab Web embeds the Sigima computation engine in Pyodide (CPython compiled to WebAssembly, JupyterLite-style) and pairs it with a dedicated React / TypeScript user interface modelled on the desktop Qt DataLab application. Plotting is delegated to Plotly.js since Qt-based PlotPy is not available in the browser.

🚀 Try it now — no install required

👉 https://datalab-platform.com/web/

The latest release is deployed automatically to GitHub Pages. Open the link in any modern browser (Chrome, Edge, Firefox, Safari) and the full DataLab application — Sigima, NumPy, SciPy, scikit-image, h5py — runs locally inside the browser tab. No server, no account, no upload: your data never leaves your machine.

First load downloads Pyodide and installs Sigima via micropip (~30–60 s). Subsequent loads are cached by the browser. On Microsoft Edge the first load may be much slower — see doc/troubleshooting.md for the one-line fix.

DataLab Web demo — creating a 2D sinc image, extracting a cross-section profile, measuring its full width at half-maximum, and running Canny edge detection from the command palette

Features

DataLab Web mirrors a large portion of the desktop application surface:

  • Signal & image panels — 1D curves and 2D arrays with a rich set of synthetic generators, full Plotly visualisation, cross-hair markers, contrast adjustment, cross profiles and stats area tools.
  • Processing & analysis — operations, transforms, filters, fitting, FFT/PSD, stability analyses, measurements and profile extraction, exposed automatically through the menu bar by introspecting Sigima's catalog.
  • ROI & object tree — segment / rectangular / circular / polygonal regions of interest, plus a multi-group workspace with drag & drop, metadata editor, statistics card and computation history.
  • Macros & notebooks — embedded Python editor and multi-tab notebook panel, each running in dedicated Web Workers, with .ipynb import/export and bidirectional macro ⇄ notebook conversion. See doc/notebooks.md.
  • Plugins — Qt-compatible PluginBase API: the same plugin source runs in DataLab desktop and DataLab Web. See doc/plugins.md.
  • I/O — HDF5 browser (via h5py in Pyodide), text import wizard and per-directory save dialog.
  • UI niceties — light / dark theme, persisted layout, pop-out result panel, contextual help, full internationalisation.

Architecture overview

flowchart LR
    UI["<b>React / TypeScript UI</b><div style='text-align:left;min-width:260px'>• Signal &amp; image panels<br/>• Plotly.js plots<br/>• Menus / dialogs<br/>• Macro editor<br/>• Plugin manager</div>"]
    Py["<b>Pyodide (CPython + WASM)</b><div style='text-align:left;min-width:420px;white-space:nowrap'>• numpy / scipy / scikit-image<br/>• h5py<br/>• sigima (computation engine)<br/>• bootstrap.py (object store + JS-friendly helpers)</div>"]
    UI -->|"runtime.ts bridge"| Py
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For the full picture — layer view, component view, worker protocols, the source-tree breakdown and end-to-end flows with diagrams — see doc/architecture.md. The persistence model explains why the HDF5 workspace file is the single durable source of truth.

Comparison with related projects

Project Purpose Runs where
DataLab Reference desktop app (Qt + PlotPy) Native
DataLab-Kernel Jupyter kernel exposing DataLab to notebooks Local Python
DataLab-Web Full browser app, Sigima in WASM (this project) Browser
Sigima Headless computation engine (signals/images) Anywhere Python

Development

Prerequisites: Node.js ≥ 18.

npm install
npm run dev      # Vite dev server on http://localhost:5173
npm run build    # static bundle in dist/ (deployable to any static host)
npm run lint     # ESLint
npm run format   # Prettier

The first dev load downloads Pyodide (~10 MB) and installs Sigima via micropip (30–60 s); subsequent loads are cached. Vite is configured with base: "./" so the build works under sub-paths.

Documentation

Topic Guide
Documentation index doc/README.md
Architecture (layers, workers, flows, source tree) doc/architecture.md
Persistence model doc/persistence.md
Notebooks doc/notebooks.md
Plugins doc/plugins.md
Internationalisation doc/i18n.md
Testing strategy & running the suites doc/testing-strategy.md
Releasing & distribution (app + SDK tarballs) doc/releasing.md
Troubleshooting doc/troubleshooting.md
Roadmap doc/roadmap.md

Use of Generative AI

DataLab-Web is funded under an NLnet grant and complies with the NLnet policy on the use of Generative AI. GenAI is used as a development aid only; high-level review, architectural decisions and scientific validation remain under exclusive human responsibility, and AI-assisted commits carry an Assisted-by: <Model> <Version> trailer. The full rules live in CONTRIBUTING.md.

License

BSD 3-Clause, same as DataLab and Sigima.