whoot

Tools for capturing, analyzing, and parsing audio data

Installation Instructions

Default Python Instructions

1. Install Python>=3.10
2. Create a virtual enviroment via python -m venv
3. Activate the enviroment using an activate script:

• Windows: .venv\Scripts\activate
• macOS/Linux: source .venv/bin/activate

If this works, you should see in your command line (whoot). If not check https://docs.python.org/3/library/venv.html#how-venvs-work

4. Run in project root pip install -e .

To install optional dependencies run pip install -e .[extra1,extra2,...]

Current support optional dependency collections include

• cpu: Installs torch and torchvision for CPU use only
• cu128: Installs torch and torchvision with Cuda 12.8 Binaries
• model-training: Required for running scripts in whoot/model_training, make sure to add either cpu or cu128
• dev: Installs linters pylint and flake8. MUST be used by developers of whoot

Usage

Once the enviroment is activated, you should be able to do python path/to/script.py to run any of the whoot scripts. If a script states a package is missing, you might not be using the virtual enviroment.

Developer Notes

Creating a new Project

When adding a new package, like assess_birdnet to the whoot toolkit, add your package name to the [tool.setuptools] section of pyproject.toml

Linting

Style guidelines are listed in .flake8 and pylintrc. To use these tools do the following

1. Follow the Installation Instructions, on pip install do pip install -e .[dev,extra1,extra2,...].
2. Activate the environment

To run the linters run python -m flake8 and python -m pylint --recursive y PATH/TO/FILES.py In order to contribute to whoot, both of these must be cleared.