feat(codec): auto-register Arrow decoder

[bbopen]

Summary

• auto-register Arrow decoder in Node bridges for frictionless Arrow defaults
• expose helper for manual registration + tests for auto-register behavior
• update living app + docs to rely on auto-registration

Testing

• npm test -- test/runtime_codec.test.ts

Notes

• Stacked on feat(codec): envelope validation + size cap #35 (feat/codec-envelope-validation)

[coderabbitai]

Important

Review skipped

Auto reviews are disabled on base/target branches other than the default branch.

Please check the settings in the CodeRabbit UI or the .coderabbit.yaml file in this repository. To trigger a single review, invoke the @coderabbitai review command.

You can disable this status message by setting the reviews.review_status to false in the CodeRabbit configuration file.

---

_{Comment @coderabbitai help to get the list of available commands and usage tips.}

[chatgpt-codex-connector]

💡 Codex Review

Here are some automated review suggestions for this pull request.

Reviewed commit: ed1cf275e6

ℹ️ About Codex in GitHub

Your team has set up Codex to review pull requests in this repo. Reviews are triggered when you

• Open a pull request for review
• Mark a draft as ready
• Comment "@codex review".

If Codex has suggestions, it will comment; otherwise it will react with 👍.

Codex can also answer questions or update the PR. Try commenting "@codex address that feedback".

[chatgpt-codex-connector]

Avoid importing heavy SciPy/Sklearn during meta

module_available() uses importlib.util.find_spec, which imports the parent package for dotted names; calling it with 'scipy.sparse' and 'sklearn.base' therefore imports SciPy/Sklearn on every meta request (bridge startup). These imports are heavy and can take seconds or fail when native dependencies are missing, delaying or disrupting startup even when those codecs aren’t used. Consider checking only the top-level package (e.g., 'scipy', 'sklearn') or deferring submodule imports until actually needed.

Useful? React with 👍 / 👎.