hypernote 0.4.1

Thin control plane for Jupyter notebook execution with jobs, attribution, and runtime lifecycle

Hypernote

• JupyterLab-first - Hypernote is a thin execution control plane for a Hypernote-enabled JupyterLab server.
• One notebook truth - notebook edits, execution, and late-open JupyterLab views all operate on the same logical document.
• Agent-first surface - the Python SDK is primary, and the CLI is a thin shell over it.
• Ephemeral control plane - Jupyter owns durable .ipynb contents and outputs; Hypernote owns in-memory runtimes, jobs, and attribution.
• Temporary collaboration journal - setup serve keeps Jupyter RTC updates in server-local temp storage, not repo-root databases.

What it ships

• notebook-first SDK in src/hypernote/sdk.py
• agent-first CLI in src/hypernote/cli/main.py
• Jupyter server extension for execution and runtime control
• subshell-routed execute, interrupt, and restart so JupyterLab stays usable while Hypernote is running cells
• notebook-scoped runtime lifecycle with attach, detach, recovery, and stop
• job polling and input() round-trips for agent automation without requiring an open Lab tab
• live-server and browser regression coverage for shared-document behavior

Quick start

uv sync
uv run hypernote setup doctor
# If no Hypernote API is reachable, start the server from this repo.
# Omit --no-browser when you want setup to open JupyterLab immediately.
uv run hypernote setup serve --no-browser > tmp/hypernote-serve.log 2>&1 &
for _ in 1 2 3 4 5 6 7 8 9 10; do
  uv run hypernote setup doctor | grep -q '"hypernote_api"[[:space:]]*:[[:space:]]*"ok"' && break
  sleep 0.5
done
uv run hypernote setup doctor
notebook_path="tmp/demo-$(date +%Y%m%d-%H%M%S).ipynb"
uv run hypernote create "$notebook_path" --empty --brief
uv run hypernote ix "$notebook_path" -s 'value = 20 + 22; print(value)' --brief
uv run hypernote status "$notebook_path" --brief

Use the notebook path you actually want. The tmp/demo-... path above is only a disposable example that avoids overwriting an existing notebook. --brief keeps the cell's output_preview while omitting hints, snapshot tokens, and bulky raw output payloads.

For another repo's environment, install Hypernote there (uv add hypernote --dev) and run setup doctor / setup serve from that repo so kernels and notebook paths line up.

Install

The default install includes the JupyterLab integration stack Hypernote needs: JupyterLab, shared-document support, server-side notebook execution, and the Hypernote server extension.

Use hypernote[dev] only for local development and CI tooling.

Examples:

uv sync
uv sync --extra dev

Mental model

Jupyter owns:

• notebook persistence
• shared YDoc document state
• temporary collaboration journal state for live RTC updates
• kernel and session primitives
• notebook rendering in JupyterLab

Hypernote owns:

• runtime lifecycle around a notebook
• job coordination and stdin round-trips
• actor attribution
• SDK, CLI, and thin REST handlers

Contributor discipline

• shared behavior should have one owner, usually the SDK for agent-facing observation rules
• command and payload variants should preserve one contract unless a difference is explicit and documented
• adapters should normalize valid upstream shape differences at the boundary
• tests should cover invariants across variants, not only the main workflow

Documentation

Operator docs:

• Getting Started
• CLI Reference
• SDK Reference

Contributor and advanced behavior docs:

• Agent Contributor Guide
• Runtime Model
• Browser Regression Spec

Agents that only need to create, run, recover, or open notebooks can stop after the operator docs.

Verification

For local development and CI, install the dev tier first:

uv sync --extra dev

uv run ruff check src/hypernote tests
uv run python -m pytest -q