Psynteract Python bindings
Real-time interactive experiments for the behavioral sciences, using Python.
This package allows researchers to build real-time interactive experiments in pure Python. If you are using PsychoPy, expyriment or a similar package to build your studies and are studying strategic interactions or another paradigm that requires that participants interact in real time, this is for you.
Please note that a graphical interface for OpenSesame is also available.
psynteract-py is developed jointly by Felix Henninger and Pascal
Kieslich. It is published under the Apache License, Version 2.0.
This software is stable and has been successfully used in several studies across multiple labs. Additional features will be added, radical changes are not currently planned.
Comments, suggestions, and pull requests are always very welcome -- please do not hesitate to let the authors know if we can help in any way!
The package can be installed locally via the
pip command, specifying the
latest release URL, such as:
pip install https://github.com/psynteract/psynteract-py/releases/download/v0.8.0/psynteract-0.8.0.tar.gz
The psynteract library should then be available within the local python installation.
To install the latest development version, please run:
pip install git+https://github.com/psynteract/psynteract-py.git
Please note that the psynteract backend, which is bundled with the releases, needs to be downloaded and installed separately if you would like to use the backend installation function from the library.
Please drop us a line if you've used the library: We sincerely love to hear from our users!
If you use
psynteract in your published research, we kindly ask that you
cite the associated article as follows:
Henninger, F., Kieslich, P. J., & Hilbig, B. E. (2017). Psynteract: A flexible, cross-platform, open framework for interactive experiments. Behavior Research Methods, 49(5), 1605-1614. doi:10.3758/s13428-016-0801-6
We would like to thank Hosam Alqaderi and Susann Fiedler at the Max Planck Institute for Research on Collective Goods, Bonn, and the members of the University of Mannheim Chair of Experimental Psychology and the University of Landau Cognition Lab for their feedback and testing during the development of this library.
Development was supported by the University of Mannheim’s Graduate School of Economic and Social Sciences, which is funded by the German Research Foundation.
Shoulders of giants
The python-based implementation of psynteract depends on the following excellent libraries: