marimo-batch

Convert marimo notebooks into CLI-executable batch jobs with Pydantic parameter configuration.

3|Updated Apr 2, 2026

Search Tags:#automation #pydantic #cli #machine learning #batch #marimo

Ready to run

npx skills add https://github.com/legout/pi-config --skill marimo-batch-legout

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: marimo-batch
Source: https://github.com/legout/pi-config/tree/main/installed-skills/marimo-batch
Command: npx skills add https://github.com/legout/pi-config --skill marimo-batch-legout

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires marimo, pydantic, python-dotenv, rich, wigglystuff, torch, wandb, huggingface-hub, numpy, and includes references (resource) components.

What problem does it solve?

This skill bridges the gap between interactive data exploration and production-grade batch processing by enabling CLI-based execution of marimo notebooks.

Core Features & Use Cases

Dual-Mode Execution: Seamlessly switch between a UI-driven interactive environment and a CLI-driven batch execution mode.
Hyperparameter Sweeps: Automate grid searches and job submissions using integrated reference scripts.
Use Case: Develop a machine learning training pipeline in a marimo notebook, then use the CLI to launch multiple training runs with varying hyperparameters on a compute cluster.

Quick Start

Ask the assistant to configure the current notebook for batch processing by defining ModelParams and adding the necessary CLI argument parsing logic.

Frequently Asked Questions about marimo-batch

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I convert a marimo notebook into a CLI batch job?▼

You convert a marimo notebook into a CLI batch job by defining ModelParams using Pydantic and adding argument parsing logic. This enables automated command-line execution for machine learning and data processing tasks.

What is the best way to run hyperparameter grid searches using marimo notebooks?▼

Running hyperparameter grid searches from marimo notebooks is achieved by transforming them into CLI batch jobs. This allows automated execution of multiple training runs with varying hyperparameters on a compute cluster.

Can I use Pydantic models to configure parameters for marimo batch execution?▼

Yes, you can use Pydantic models to configure parameters for marimo batch execution. Defining ModelParams with Pydantic allows seamless switching between UI-driven interactive environments and CLI-driven batch execution modes.

Does marimo batch execution support machine learning training pipelines?▼

Yes, marimo batch execution supports machine learning training pipelines. You can develop a training pipeline interactively, then use the CLI to launch multiple runs with varying hyperparameters on a compute cluster.

Do I need environment variable management to run marimo notebooks as batch jobs?▼

Yes, you need environment variable management to run marimo notebooks as batch jobs. Integration with environment variable management and compute provider APIs is required for scalable job submission and execution.