Closer to production quality Python notebooks with `marimo check` (marimo.io)

Marimo announced marimo check, a command‑line linter tailored to marimo’s Python-based notebooks that brings traditional software engineering guardrails—linting, CI integration, and automatic fixes—to notebook workflows. Unlike generic linters, marimo check enforces marimo‑specific rules that preserve reproducibility and executable dataflow semantics: it detects issues like multiple variable definitions across cells, circular dependencies, formatting problems, and unused definitions, and suggests actionable fixes (e.g., underscore‑prefixing private variables). It’s designed to complement tools such as ruff, pylint and mypy rather than replace them, borrows clear, prescriptive diagnostics inspired by Ruff and Rust, and provides flags like --fix, --unsafe-fixes, --strict and --format=json for automated pipelines and CI. For the AI/ML community this is significant because marimo notebooks are pure Python programs meant for production apps and pipelines, not ad‑hoc scratchpads. marimo check enables both humans and coding agents (Claude Code, Gemini, etc.) to iterate and self‑correct: JSON output and sub‑agent patterns let LLMs receive diagnostics, repair notebooks, and re‑lint in a closed loop. The project also includes tooling for automatic pruning and improved serialization, documentation for contributing new rules, and an explicit developer API—making it easier to enforce notebook quality at scale and integrate linting into ML development lifecycles.