git clone https://github.com/OpenNingia/l5r-character-manager-3.git
cd ./l5r-character-manager-3/
git switch master
Install python3-venv and create a new virtual environment for python.
apt install python3-venv
python3 -m venv .venv
source .venv/bin/activate
Before running the program you need to install the dependencies: Some of them can be installed using pip:
pip install -r requirements.txt
pip install git+https://github.com/OpenNingia/l5rcm-data-access.git@master
You will need Visual Studio or Visual Studio Build tools in order to build some of the dependencies (mainly lxml).
You will also need to install Python from here (latest version should be fine):
https://www.python.org/downloads/
You will need to download one more dependency, the pdf toolkit, needed to export the character sheets.
Use your package manager to install the pdftk-java
package.
In case this is not packaged for your distribution I recommend this version: https://gitlab.com/pdftk-java/pdftk
python3 ./main.py
The software alone is not useful. You need game data in order to create and manage your characters.
Game data is provided through packages named "datapacks" that are downloadable from the project website:
https://github.com/OpenNingia/l5rcm-data-packs/releases/latest
however you might want to compile the datapack yourself; in order to do so follow these simple instructions.
The data pack sources are hosted in a different repo, to get them run:
git clone https://github.com/OpenNingia/l5rcm-data-packs.git
git switch master
In the repo there is a convenience script that builds all the datapacks
cd scripts
python make_all_packs.py
The preferred way to install datapacks is from the application menu.
Click on Gear menu -> Import datapack... and select the files to import.
Typically datapacks have the .l5rcmpack
extension.
This operation is only needed the first time and on each datapack update.
If the program was installed using the setup and/or debian file then you can also doubleclick the datapack files.
If you make a modification to the software or datapack that add value to the application don't hesitate to share it!
Please submit a pull request to the relative repository.