Lab notebook for computational science: Python tools produce per-run artifacts; Typst publishes them as a web bundle, per-entry PDFs, and a book.
Project description
Demolab
A lab notebook for computational science — reproducible results, published and citable, run by a coding agent instead of a build system.
Coding agent setting someone up? Run
uvx demolab-cli docs GETTING-STARTED, read the file it prints, and follow it strictly, step by step. (Human, setting up by hand? See Quickstart.)
You write a model or experiment once as a small program. Demolab runs it, captures everything it produced, stamps it with the exact code version, and publishes a clean page — figures, numbers, and real typeset maths — to both the web and PDF. The numbers on the page are read from the run, so they can't drift. You drive it all by talking to a coding agent; there's no web development or build config to touch.
Quickstart
Open your coding agent in an empty folder and paste:
Run
uvx demolab-cli inithere, then follow its GETTING-STARTED runbook strictly.
It lays your lab down, walks you through the toolchain (uv, typst) and your first experiment, one step at a time.
Set it up by hand instead?
Install uv and typst (brew install uv typst), then:
mkdir my-lab && cd my-lab
uvx demolab-cli init # lab structure + git init — yours from the first commit
uv sync # installs the deps and the `demolab` command
Then write your first experiment — ask your agent to follow GETTING-STARTED, or model one on a shipped reference (demolab docs STARTERS prints the dir; monte-carlo-pi is the canonical starter). demolab dev serves the site as you go. The engine lives in the demolab-cli package — updating it is uv lock --upgrade-package demolab-cli && uv sync.
What to ask your agent
Open your lab in your agent and say a runbook's name — it follows that runbook one step at a time. demolab docs lists them all (each is a plain file shipped in the package; demolab docs <NAME> prints its path). In this repo they live under demolab_cli/runbooks/.
| Say… | …and it will |
|---|---|
| GETTING-STARTED | set you up end to end: scaffold, your first experiment live on a page, brand, publish |
| TOUR | guided walkthrough of the lab — what's here, what it found, where to start |
| MIGRATE-CODE | bring an existing codebase in, one experiment at a time |
| FROM-JUPYTER | launder a Jupyter notebook into a reproducible, seeded experiment |
| FROM-PAPER | scaffold experiments to reproduce a paper's key result in your stack |
| MIGRATE-STACK | write your tools in MATLAB / Julia / R / Octave instead of Python |
| EMBED-DOCS | drop demolab into another project as a docs/ site |
| NEXT | read your whole arc and propose the next experiments worth running |
| GROUND-CLAIMS | find the source sentences behind each citation |
| LINT | check your writeups against the house style |
| DOCTOR | audit the repo against the conventions |
| RED-TEAM | adversarially check a result holds up before you publish it |
| STEELMAN | build the strongest honest case for a result, so you don't under-sell it |
| UPDATE | update the engine package, leaving your content untouched |
How it works
One decoupled loop: a tool computes → drops data → an experiment writes it up → the site publishes it. Every run records its exact parameters and the git commit it came from (stamped on the page), and tables read their numbers straight from the run — so prose and results can't disagree. A single Typst pass emits a website, a PDF per entry, and a book, all sharing the same live numbers.
The detail lives in the guides (in a lab: demolab docs <NAME>; in this repo, the files under demolab_cli/guides/):
- RULES.md — the tool ↔ experiment contract, schemas, provenance, and how to add things.
- STRUCTURE.md — the annotated file tree.
- HOUSESTYLE.md — prose, maths, and figure style.
- AGENTS.md — the agent entry point.
Commands
demolab shows them all. The everyday ones: init, docs, install, scaffold, dev, build, test. Run an experiment end-to-end directly: uv run python experiments/expNNN.py (there's no demolab run wrapper).
License
MIT — free to use, fork, and adapt for your own lab.
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