https://github.com/hazarddede/risk-sim
Risk Combat Simulator
https://github.com/hazarddede/risk-sim
risk-game simulator
Last synced: 12 months ago
JSON representation
Risk Combat Simulator
- Host: GitHub
- URL: https://github.com/hazarddede/risk-sim
- Owner: HazardDede
- License: gpl-3.0
- Created: 2018-01-08T15:22:19.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2018-01-15T08:21:20.000Z (over 8 years ago)
- Last Synced: 2025-03-06T11:19:06.605Z (over 1 year ago)
- Topics: risk-game, simulator
- Language: Python
- Size: 25.4 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# risk-sim - Risk Combat Simulator
This python program is a combat simulator for the famous `Risk` strategy board game.
The idea was born during an exciting game of `Risk: Halo Legendary Edition` with my family and friends.
Back then I was curious about the odds when attacking an enemy army, which inspired my to write this little program to perform some hacker statistics in the `Risk` campaign setting.
I will not take a deeper look at the rules - so if you are interested do it yourself:
[https://www.wikihow.com/Play-Risk](https://www.wikihow.com/Play-Risk)
The `Risk: Halo Legendary Edition` introduced so called leaders (generals), which grants units in the same territory a +1 to the value of their rolled dices.
Besides implementing some hacker statistics about `Risk` I also pursued the following goals:
* Use `attrs` to model my container classes
* Use `docopt` for parsing console arguments
* Use `schema` for adapting additional validation
## Installation
Cause I will not publish this repo via pypi you have to install it manually without pip support
# Clone this repo
https://github.com/HazardDede/risk-sim.git && cd risk-sim
# Make a python3 virtualenv
python3 -m venv venv && source venv/bin/activate
# Install the dependencies
pip install -r requirements.txt && pip install -r requirements-dev.txt
# Run the test to see if everything worked fine
pytest
## Running the simulator
$ python risk_sim.py -h
Risk Simulator.
Usage:
risksim [-i ] [--attacking-general] [--defending-general]
risksim (-h | --help)
risksim --version
Arguments:
attacker Number of attacking units (> 1)
defender Number of defending units (> 0)
Options:
-h --help Show this screen.
--version Show version.
-i --iterations= Number of iterations to simulate [default: 1000].
--attacking-general Enables the general when attacking (+1 to all pips) [default: False]
--defending-general Enables the general when defending (+1 to all pips) [default: False]
Following these help page you have to
python -m risksim 100 50 --defending-general --iterations=1000
to simulate a battle between 100 attacking and 50 defending units, while the defending army is lead by a general (+1 to all rolled dice values).
The same battle between those units will be repeated and recorded for a 1.000 times, leading to a summary statistic like below:
╔Success Rate: 63.8 %════╦═════════╦════════╦═════════╗
║ Metric ║ avg ║ median ║ min ║ max ║
╠══════════════╬═════════╬═════════╬════════╬═════════╣
║ Attacks ║ 68.174 ║ 69.0 ║ 49 ║ 77 ║
║ Attacker ║ -- ║ -- ║ -- ║ -- ║
║ Casualties ║ 87.872 ║ 92.0 ║ 45 ║ 99 ║
║ Casualties % ║ 87.87 % ║ 92.0 % ║ 45.0 % ║ 99.0 % ║
║ Survivor ║ 12.128 ║ 8.0 ║ 1 ║ 55 ║
║ Defender ║ -- ║ -- ║ -- ║ -- ║
║ Casualties ║ 47.308 ║ 50.0 ║ 25 ║ 50 ║
║ Casualties % ║ 94.62 % ║ 100.0 % ║ 50.0 % ║ 100.0 % ║
║ Survivor ║ 2.692 ║ 0.0 ║ 0 ║ 25 ║
╚══════════════╩═════════╩═════════╩════════╩═════════╝
Cause the odds are highest when rolling three (attacker) or two (defender) dices the algorithm will always (if possible) maximize the number of rolled dices.