psyflow is a small framework that helps build modular cognitive and behavioural experiments on top of PsychoPy. It bundles a collection of helper classes and utilities so you can focus on experimental logic rather than boilerplate.
- BlockUnit – manage blocks of trials and collect results
- StimUnit – present a single trial and log responses
- StimBank – register and build stimuli from Python functions or YAML definitions
- SubInfo – gather participant information via a simple GUI
- TaskSettings – central configuration object for an experiment
- TriggerSender – send triggers to external devices (e.g. EEG/MEG)
The package also provides a command line tool psyflow-init which
scaffolds a new project using the bundled cookiecutter template.
Comprehensive documentation and tutorials are available on the GitHub Pages site.
To generate the HTML docs locally:
pip install -r docs/requirements.txt
sphinx-build -b html docs docs/_build/htmlOpen docs/_build/html/index.html in a browser to view them.
Releases are automated with GitHub Actions. Any push to the main branch
that contains [publish] in the commit message will trigger the
publish workflow. The workflow builds
sdist and wheel via python -m build and uploads them to PyPI using the
pypa/gh-action-pypi-publish action. The upload requires a
PYPI_API_TOKEN secret configured in the repository.