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.
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.