Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/alexis-moins/tsukuba-gdmc-2022
2022 participation in the Generative Design in Minecraft Challenge (GDMC) 👺
https://github.com/alexis-moins/tsukuba-gdmc-2022
gdmc-competition minecraft python
Last synced: 2 months ago
JSON representation
2022 participation in the Generative Design in Minecraft Challenge (GDMC) 👺
- Host: GitHub
- URL: https://github.com/alexis-moins/tsukuba-gdmc-2022
- Owner: alexis-moins
- Created: 2022-04-19T09:14:19.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2022-06-23T07:51:45.000Z (over 2 years ago)
- Last Synced: 2024-04-22T15:21:11.798Z (9 months ago)
- Topics: gdmc-competition, minecraft, python
- Language: Python
- Homepage:
- Size: 18.4 MB
- Stars: 11
- Watchers: 1
- Forks: 1
- Open Issues: 5
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Tsukuba GDMC 2022
This repository is an entry for the annual GDMC competition of 2022.
## How to use
### Clone the repository
Start by cloning the repository to get the files on your machine. Alternatively, you can change `~/GDMC` to any location you want.
```bash
git clone [email protected]:AlexisMoins/tsukuba-gdmc-2022.git ~/GDMC && cd ~/GDMC
```
### Setup the environment
**Note:** This repository relies on multiple python packages. You can find out which ones are used in the `pyprojet.toml` file. To manage our packages, We used [poetry](https://python-poetry.org). If you are not using this tool, you should try to install the packages directly via `pip`.
As a final note, please notice that the syntax used across the projet is python version **3.10** so you might want to install version 3.10 via python's [official website](https://www.python.org) or via tools like [pyenv](https://github.com/pyenv/pyenv).
This command will install the dependencies and start a new virtual environment
```bash
poetry install && poetry shell
```
Using `pip`, the main packages that you should install are `gdpc`, `pytest` if you want to run tests, `pre-commit` to keep the requirements.txt file **synchronized**. Exact versions of the aforementioned packages can again be found in the `pyproject.toml` file. Alternatively, you can directly install the dependencies by typing :
```bash
pip install -r requirements.txt
```
### Add pre-commit hooks (optional)
To keep the `requirements.txt` file in sync with the `pyproject.toml` file (given that the `pre-commit` package is installed), you need to run one of the following commands.
If you have launched a poetry virtual env:
```bash
pre-commit install
```
Otherwise, use one of the following (depending on your case)
- if you use poetry :
```bash
poetry run pre-commit install
```
- or, if you use pip:
```bash
python -m pre-commit install
```
### Install the GDPC Java mod
Instructions on how to get the mod running on your machine can be found in the official [GDPC Interface](https://github.com/nilsgawlik/gdmc_http_interface/wiki/Installation) github repository. Once you have succesfully followed the given instrtuction you can go to the final step below!
### Launch the simulation
Once the environment is ready, simply starta single-player minecraft game and launch the `main.py` script and you're good to go !
```bash
python main.py
```
## Simulation rules
- We have 3 main variables
1. The population, driven by the bed amount
2. The food, driven by the food production
3. The work productivity, driven by the population and the building work capacity
- Each turn:
- The city is updated:
- Food is produced then consumed
- Each inhabitant consume 1 food
- If there is not enough food, all unfed inhabitants die
- Productivity is computed as the minimum of the population and the buildings work capacity
- The player plays:
- Depending on its city's productivity, he can place some building that will increase : the bed amount, the food production or the work capacity
In the futur, environment will have effect on productivity : farm will be less effective in cold biomes, wood cutting will depend on the tree frequency, etc.
We could also add an 'oldness' variable for our buildings, the oldest, the more deteriorated