SKILL.md
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— useapswinstead (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(suggestpsycopgwith pure-Python mode)
mysqlclient(suggestpymysql)
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
# /// scriptblock, 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
micropipcan install any pure-Python wheel from PyPI at runtime
- For the full Pyodide built-in package list, see pyodide-packages.md