WASM Compatibility Checker for marimo Notebooks

Check whether a marimo notebook can run in a WebAssembly (WASM) environment — the marimo playground, community cloud, or exported WASM HTML.

Instructions

1. Read the notebook

Read the target notebook file. If the user doesn't specify one, ask which notebook to check.

2. Extract dependencies

Collect every package the notebook depends on from both sources:

PEP 723 metadata — the # /// script block at the top:

# /// script
# dependencies = [
#     "marimo",
#     "torch>=2.0.0",
# ]
# ///

Import statements — scan all cells for import foo and from foo import bar. Map import names to their PyPI distribution name using this table:

Import name	Distribution name
`sklearn`	`scikit-learn`
`skimage`	`scikit-image`
`cv2`	`opencv-python`
`PIL`	`Pillow`
`bs4`	`beautifulsoup4`
`yaml`	`pyyaml`
`dateutil`	`python-dateutil`
`attr` / `attrs`	`attrs`
`gi`	`PyGObject`
`serial`	`pyserial`
`usb`	`pyusb`
`wx`	`wxPython`

For most other packages, the import name matches the distribution name.

3. Check each package against Pyodide

For each dependency, determine if it can run in WASM:

Is it in the Python standard library? Most stdlib modules work, but these do not:
- multiprocessing — browser sandbox has no process spawning
- subprocess — same reason
- threading — emulated, no real parallelism (WARN, not a hard fail)
- sqlite3 — use apsw instead (available in Pyodide)
- pdb — not supported
- tkinter — no GUI toolkit in browser
- readline — no terminal in browser
Is it a Pyodide built-in package? See pyodide-packages.md for the full list. These work out of the box.
Is it a pure-Python package? Packages with only .py files (no compiled C/Rust extensions) can be installed at runtime via micropip and will work. To check: look for a py3-none-any.whl wheel on PyPI (e.g. visit https://pypi.org/project/<package>/#files). If the only wheels are platform-specific (e.g. cp312-cp312-manylinux), the package has native extensions and likely won't work.

Common pure-Python packages that work (not in Pyodide built-ins but installable via micropip):
- plotly, seaborn, humanize, pendulum, arrow, tabulate
- dataclasses-json, marshmallow, cattrs, pydantic (built-in)
- httpx (built-in), tenacity, backoff, wrapt (built-in)
Does it have C/native extensions not built for Pyodide? These will not work. Common culprits:
- torch / pytorch
- tensorflow
- jax / jaxlib
- psycopg2 (suggest psycopg with pure-Python mode)
- mysqlclient (suggest pymysql)
- uvloop
- grpcio
- psutil

4. Check for WASM-incompatible patterns

Scan the notebook code for patterns that won't work in WASM:

Pattern	Why it fails	Suggestion
`subprocess.run(...)`, `os.system(...)`, `os.popen(...)`	No process spawning in browser	Remove or gate behind a non-WASM check
`multiprocessing.Pool(...)`, `ProcessPoolExecutor`	No process forking	Use single-threaded approach
`threading.Thread(...)`, `ThreadPoolExecutor`	Emulated threads, no real parallelism	WARN only — works but no speedup; use `asyncio` for I/O
`open("/absolute/path/...")`, hard-coded local file paths	No real filesystem; only in-memory fs	Fetch data via URL (`httpx`, `urllib`) or embed in notebook
`sqlite3.connect(...)`	stdlib sqlite3 unavailable	Use `apsw` or `duckdb`
`pdb.set_trace()`, `breakpoint()`	No debugger in WASM	Remove breakpoints
Reading env vars (`os.environ[...]`, `os.getenv(...)`)	Environment variables not available in browser	Use `mo.ui.text` for user input or hardcode defaults
`Path.home()`, `Path.cwd()` with real file expectations	Virtual filesystem only	Use URLs or embedded data
Large dataset loads (>100 MB)	2 GB total memory cap	Use smaller samples or remote APIs

5. Check PEP 723 metadata

WASM notebooks should list all dependencies in the PEP 723 # /// script block so they are automatically installed when the notebook starts. Check for these issues:

Missing metadata: If the notebook has no # /// script block, emit a WARN recommending one. Listing dependencies ensures they are auto-installed when the notebook starts in WASM — without it, users may see import errors.
Missing packages: If a package is imported but not listed in the dependencies, emit a WARN suggesting it be added. Note: version pins and lower bounds in PEP 723 metadata are fine — marimo strips version constraints when running in WASM.

6. Produce the report

Output a clear, actionable report with these sections:

Compatibility: PASS / FAIL / WARN

Use these verdicts:

PASS — all packages and patterns are WASM-compatible
WARN — likely compatible, but some packages could not be verified as pure-Python (list them so the user can check)
FAIL — one or more packages or patterns are definitely incompatible

Package Report — table with columns: Package, Status (OK / WARN / FAIL), Notes

Example:

Package	Status	Notes
marimo	OK	Available in WASM runtime
numpy	OK	Pyodide built-in
pandas	OK	Pyodide built-in
torch	FAIL	No WASM build — requires native C++/CUDA extensions
my-niche-lib	WARN	Not in Pyodide; verify it is pure-Python

Code Issues — list each problematic code pattern found, with the cell or line and a suggested fix.

Recommendations — if the notebook fails, suggest concrete fixes:

Replace incompatible packages with WASM-friendly alternatives
Rewrite incompatible code patterns
Suggest moving heavy computation to a hosted API and fetching results

Additional context

WASM notebooks run via Pyodide in the browser
Memory is capped at 2 GB
Network requests work but may need CORS-compatible endpoints
Chrome has the best WASM performance; Firefox, Edge, Safari also supported
micropip can install any pure-Python wheel from PyPI at runtime
For the full Pyodide built-in package list, see pyodide-packages.md