v0.4.0 — R kernels, no nbformat, reopenable CPU hint

dsh-notebook v0.4.0

R kernels, a notebook format that no longer needs nbformat, and a hybrid-CPU
hint you can actually find again.

R kernels

IRkernel is now a first-class kernel, discovered the way Jupyter discovers it:

• kernelspecs in the user data dir (%APPDATA%\jupyter\kernels,
  ~/.local/share/jupyter/kernels),
• kernelspecs shipped inside a conda env (<env>/share/jupyter/kernels),
• conda environments that merely have IRkernel in their R library — a
  kernelspec is synthesised for them.

Two details that make it work in practice:

• A conda R needs its env's DLL directories. Launching the bare
  <env>/lib/R/bin/x64/R.exe exits instantly with 0xC0000135 (DLL not found).
  The kernel is started with the env's bin/Library/bin directories prepended
  to PATH and R_HOME set — the equivalent of conda activate, without a
  shell.
• argv[0] is not trusted. The kernelspec a conda env ships usually says
  "R", which only resolves while that env is activated (and often lacks the
  .exe). The absolute binary is substituted, and the spec is regenerated in a
  temp dir exposed through JUPYTER_PATH, so your Jupyter config is untouched
  and nothing has to be installed.

nb_list_vars / nb_inspect_object have R implementations (ls/class/
deparse; data.frame additionally reports rows, columns and column types).
Saving writes the real kernelspec.language (r or python).

Every entry in the kernel dropdown is labelled with its language — py · scRNAv2, R · ggtree — with the full launch line as its tooltip.
nb_kernel_list reports the same language field, and the catalog is projected
before it leaves the host, so an R entry's argv and activation PATH/R_HOME
stay on the host instead of reaching the browser or the agent's context.

R kernels are opt-in: a fresh notebook still defaults to Python. Pick one in
the kernel dropdown (R · ggtree, R · hdWGCNA, …). An env that has Python and
R together is reported to the agent by dsh-envsel 0.3.1, which now states the
Rscript of the selected python environment.

nbformat is no longer a dependency

Opening a notebook used to import nbformat inside the sidecar, and the sidecar
runs on the interpreter you selected. Any conda env with ipykernel +
jupyter_client but without nbformat therefore failed on open with:

Operation failed: No module named 'nbformat'

That is a common shape — nbformat is not an ipykernel dependency — and a lean
or R-only environment can never have it. Reading and writing .ipynb now uses
the standard library and is byte-identical to nbformat.write(): same
indent=1 / sort_keys / ensure_ascii=False, same line-list form for
multi-line strings, same rule that only text/* mime payloads are split,
image/png base64 kept as one string, same CRLF and trailing newline. Files do
not churn in git.

jupyter_client and ipykernel remain genuine requirements; a missing one is
now reported as such (and the kernel dropdown marks the env unavailable) instead
of surfacing a raw ModuleNotFoundError.

Lossless notebook round-trip

Anything the plugin does not model survives a load → save cycle: markdown
attachments (pasted images), per-output metadata (widget view sizes),
metadata.widgets state, vendor keys. Outputs the file format does not allow
(update_display_data) collapse to display_data; duplicate or missing cell ids
are regenerated so the result always passes nbformat.validate.

nbformat 3 notebooks — worksheets / input / prompt_number and the
png/html/json mime aliases — are upgraded on read (mirroring
nbformat.v4.convert) instead of being read as an empty notebook and wiped on
the next save. 4.0–4.4 files gain stable cell ids exactly as
nbformat.read(as_version=4) does, with orig_nbformat_minor recorded.
A document that is neither v4 nor v3-shaped is rejected instead of being treated
as empty.

The hybrid-CPU hint can be reopened

Dismissing it used to be permanent for the browser session, with no entry point
anywhere. The CPU probe result now stays in the session and a
⚡ 大小核 / ⚡ Hybrid CPU toolbar button reopens the same panel — only the
automatic popup remains dismissed.

Verification

• tmp/verify-ipynb-io.py — 52 checks: byte-identity with nbformat.write,
  nbformat.validate acceptance, attachments/widgets/application/json/
  update_display_data round-trip, v3 upgrade, 4.4 → 4.5, malformed input.
• tmp/verify-sidecar-no-nbformat.py — drives the real sidecar with an
  interpreter that genuinely lacks nbformat and loads/saves a notebook.
• tmp/verify-r-kernel.py — 19 checks through the real sidecar: start, execute,
  error path, list_vars, inspect_object on a data.frame, restart.
• tmp/verify-0.4.0.mjs — extracts the shipped discovery functions and runs them
  against the real machine (R kernels resolve to real binaries with a valid
  R_HOME; envs without IRkernel are not offered; one R binary is not listed
  twice).

Compatibility

Unchanged: @deepseek-ai/dsh-tools: ^0.1.0-rc.6 || ^0.2.0-rc.1, verified against
DSH 0.2.0-rc.2. Existing notebooks, tools and UI are unaffected.