conda create -n don_tomate python=3.11
conda activate don_tomate
pip install -r requirements.txt
pre-commit install
make run-macos
pyinstaller --name "Don Tomate" --windowed --onedir main.py
datas=[
('don_tomate/Resources/play.png', 'don_tomate/Resources'),
('don_tomate/Resources/pause.png', 'don_tomate/Resources'),
('don_tomate/Resources/reset.png', 'don_tomate/Resources'),
('don_tomate/Resources/sound.png', 'don_tomate/Resources'),
('don_tomate/Resources/stop_sound.png', 'don_tomate/Resources'),
('don_tomate/Resources/settings.png', 'don_tomate/Resources'),
('don_tomate/Resources/next.png', 'don_tomate/Resources'),
('don_tomate/Resources/prev.png', 'don_tomate/Resources'),
('don_tomate/Resources/notification.wav', 'don_tomate/Resources'),
('don_tomate/Resources/don_tomate.png', 'don_tomate/Resources'),
],
icon='don_tomate/Resources/don_tomate.png',
pyinstaller Don\ Tomate.spec
create-dmg 'dist/Don Tomate.app' --overwrite
When macOS detects that an app has been downloaded or transferred from another system, it may quarantine the app, causing a "damaged" error. You can remove this attribute using the following command:
xattr -cr /path/to/YourApp.app
├── LICENSE <- Open-source license if one is chosen
├── Makefile <- Makefile with convenience commands like `make data` or `make train`
├── README.md <- The top-level README for developers using this project.
├── docs <- A default mkdocs project; see mkdocs.org for details
│
├── pyproject.toml <- Project configuration file with package metadata for clustering_rpca
│ and configuration for tools like black
│
├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g.
│ generated with `pip freeze > requirements.txt`
│
├── setup.cfg <- Configuration file for flake8
├── tests
│ ├── contest.py <-
│ └── don_tomate_testing.py <-
│
└── don_tomate <- Source code for use in this project.
│
├── __init__.py <- Makes clustering_rpca a Python module
│
├── main.py <- Script with the app
│
└── visualization <- Scripts to create exploratory and results oriented visualizations
└── visualize.py