magsim 1.1.2

A simulator for Magical Athlete

magsim - A Magical Athlete Simulator

A fan-made Python simulation engine and analysis toolkit for the board game Magical Athlete.

BoardGameGeek · CMYK Games · Designer Diary · Art Blog

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What is this?

Magical Athlete is a draft-based racing board game where you roll a die to move, but every racer has a game-breaking, unique ability.

magsim translates the physical game into a high-performance Python engine. Capable of running 60+ full races per second with complete state logging, it allows you to:

• Simulate Races: Run single game simulations in the command line or UI
• Data Generation: Run high-volume batch simulations to generate datasets for analysis
• Visual Analytics: Visualize races and analyze aggregated data in a reactive marimo dashboard
• A/B Experiments: Pit Smart AI against Random AI, compare the impact of racers and measure modifying rules changes the balance via the CLI tool

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Quickstart

The fastest way to use magsim is via the web-based frontend. The dashboard runs in WASM-mode, expect long loading times.

To run magsim locally, I recommend using uv (Install uv here).

1. Run a single test race:

uvx magsim game

2. Run a game with specific configuration:

uvx magsim game -n 6 -b standard -r Egg Magician

3. Launch the interactive dashboard locally:

uvx magsim gui

CLI

This project ships a magsim command with multiple subcommands for running simulations and doing analysis.

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game — Run one simulation

Run a single game simulation. If you don’t specify racers/board/seed, it will pick defaults (and a random seed).

magsim game [OPTIONS]

Arguments/options:

• -r, --racers <RACER...>: Space-separated list of racer names
• -n, --number <INT>: Target number of racers. If fewer racers were provided than this number, the roster is filled with unique random racers
• -b, --board <BOARD>: Board name
• -s, --seed <INT>: RNG seed
• -c, --config <PATH>: Path to a TOML config file
• -e, --encoding <STR>: Base64 encoded configuration
• -H, --houserule <KEY=VALUE...>: House rules (repeatable / multiple values)
• --max-turns <INT>: Max turns before stopping (default: 200)

Config precedence (highest wins):

1. CLI args
2. --encoding
3. --config TOML file
4. Defaults

Examples:

magsim game
magsim game -n 6 -b WildWilds
magsim game -r Mouth BabaYaga -n 5 -s 123
magsim game -H start_pos=5 -H timing_mode=BFS
magsim game -c configs/quick.toml
magsim game -e "<base64>"

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gui — Launch dashboard

Launch the interactive simulation analysis dashboard using uvx.

magsim gui

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batch — Run many simulations from a config

Run batch simulations driven by a TOML simulation config. Saves results to parquets which can be loaded in frontend.

magsim batch <config.toml> [OPTIONS]

Arguments/options:

• <config.toml>: Path to TOML simulation config file
• --runs <INT>: Override runs per combination
• --max <INT>: Override maximum total runs
• --turns <INT>: Override max turns per race
• --seed-offset <INT>: Offset for RNG seeds (default: 0)
• -f, --force: Delete existing .parquet / .duckdb files in results/ without prompting

Behavior:

• Writes to results/
• If results/ already contains .parquet files, it prompts before deleting unless --force is set
• Skips configs already present in the database by hash
• Periodically flushes data to disk in batches

Example:

magsim batch configs/sim.toml --runs 50 --max 100000 --turns 300
magsim batch configs/sim.toml --force

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compare — Comparative experiments

Appends run histories to Parquet files in results/ (AI history, rule history, racer-impact history).

compare ai — Smart vs Baseline AI

magsim compare ai <RACER> [-n INT] [-o PATH]

• <RACER>: Racer to test
• -n <INT>: Number of games (default: 500)
• -o <PATH>: Save a Markdown report to a file

Example:

magsim compare ai Mouth -n 1000 -o results/ai_mouth.md

compare rule — Default vs modified rule

magsim compare rule <key=value> [-n INT] [-o PATH]

• <key=value>: Rule setting to test (e.g. start_pos=5, some_flag=true)
• -n <INT>: Total games (default: 1000)
• -o <PATH>: Save a report to a file

Example:

magsim compare rule hr_mastermind_steal_1st=True -n 2000

compare racer — Impact of one racer on the field

magsim compare racer <RACER> [-n INT] [-o PATH]

• <RACER>: Target racer
• -n <INT>: Total games (default: 1000)
• -o <PATH>: Save a report to a file

Example:

magsim compare racer BabaYaga -n 3000

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recompute — Data analysis tools

recompute aggregate — Recompute internal aggregates

magsim recompute aggregate [-f PATH]

• -f, --folder <PATH>: Data directory containing parquet files (default: results/)

recompute stats — Generate racer_stats.json

magsim recompute stats [-f PATH]

• -f, --folder <PATH>: Data directory containing parquet files (default: results/)

Examples:

magsim recompute aggregate
magsim recompute stats -f results

Run GUI locally

To make changes and look at custom data, you may clone this repository. You can get your own data via a config file and the magsim batch command. You may then start the dashboard and load that data by running uv run marimo run frontend/magical_athlete_analysis.py.

Changelog

See the CHANGELOG.md for version history.