Skip to main content

Python interface to the Lab Streaming Layer

Project description

pylsl

Build Status Build status

This is the Python interface to the Lab Streaming Layer (LSL). LSL is an overlay network for real-time exchange of time series between applications, most often used in research environments. LSL has clients for many other languages and platforms that are compatible with each other.

Let us know if you encounter any bugs (ideally using the issue tracker on the GitHub project).

Installation

Prepared distributions

The following platforms are supported with direct installation from pypi using pip: pip install pylsl

macOS 10.6+ manylinux i686 manylinux x86_64 Windows 32bit Windows 64bit
Python 2.7
Python 3.4
Python 3.5
Python 3.6
Python 3.7

More or less experimental releases are in tstenner's anaconda repo, install with conda install -c tstenner pylsl.

Self-built

If your platform is not supported by any of the prepared distributions then you will have to find or build a liblsl shared library for your platform. You might be able to find the appropriate liblsl shared object (*.so on Linux, *.dylib on MacOS, or *.dll on Windows) from the liblsl release page.

  • Copy the shared object into liblsl-Python/pylsl/lib (use cp -L on platforms that use symlinks).
  • From the liblsl-Python working directory, run pip install ..
    • Note: You can use pip install -e . to install while keeping the files in-place. This is convenient for developing pylsl.

Usage

See the examples in pylsl/examples. Note that these can be run directly from the commandline with (e.g.) python -m pylsl.examples.SendStringMarkers.

For maintainers

Continuous Integration

pylsl uses continuous integration. It uses AppVeyor for Windows and Linux, and Travis-CI for MacOS. Whenever a new commit is pushed, AppVeyor and Travis build liblsl, copy it into the correct directory, install pylsl, then test its basic functionality. In addition, whenever a new git tag is used on a commit that is pushed to the master branch, the CI systems will deploy new wheels to pypi.

Manual Distrubtion

  1. Manual way:
    1. rm -Rf build dist *.egg-info
    2. python setup.py sdist bdist_wheel
    3. twine upload dist/*
  2. For conda
    1. build liblsl: conda build ../liblsl/
    2. conda build .

Known Issues

  • On Linux one currently cannot call pylsl functions from a thread that is not the main thread.

Acknowledgments

Pylsl was primarily written by Christian Kothe while at Swartz Center for Computational Neuroscience, UCSD. The LSL project was funded by the Army Research Laboratory under Cooperative Agreement Number W911NF-10-2-0022 as well as through NINDS grant 3R01NS047293-06S1. Thanks for contributions, bug reports, and suggestions go to Bastian Venthur, Chadwick Boulay, David Medine, Clemens Brunner, and Matthew Grivich.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date
pylsl-1.13.1-cp27-cp27m-macosx_10_6_intel.whl (985.8 kB) Copy SHA256 hash SHA256 Wheel cp27
pylsl-1.13.1-cp27-cp27m-win32.whl (335.1 kB) Copy SHA256 hash SHA256 Wheel cp27
pylsl-1.13.1-cp27-cp27m-win_amd64.whl (419.5 kB) Copy SHA256 hash SHA256 Wheel cp27
pylsl-1.13.1-cp34-cp34m-macosx_10_6_intel.whl (985.8 kB) Copy SHA256 hash SHA256 Wheel cp34
pylsl-1.13.1-cp34-cp34m-win32.whl (335.1 kB) Copy SHA256 hash SHA256 Wheel cp34
pylsl-1.13.1-cp34-cp34m-win_amd64.whl (419.4 kB) Copy SHA256 hash SHA256 Wheel cp34
pylsl-1.13.1-cp35-cp35m-macosx_10_6_intel.whl (985.8 kB) Copy SHA256 hash SHA256 Wheel cp35
pylsl-1.13.1-cp35-cp35m-win32.whl (335.1 kB) Copy SHA256 hash SHA256 Wheel cp35
pylsl-1.13.1-cp35-cp35m-win_amd64.whl (419.4 kB) Copy SHA256 hash SHA256 Wheel cp35
pylsl-1.13.1-cp36-cp36m-macosx_10_6_intel.whl (985.8 kB) Copy SHA256 hash SHA256 Wheel cp36
pylsl-1.13.1-cp36-cp36m-win32.whl (335.1 kB) Copy SHA256 hash SHA256 Wheel cp36
pylsl-1.13.1-cp36-cp36m-win_amd64.whl (419.4 kB) Copy SHA256 hash SHA256 Wheel cp36
pylsl-1.13.1-cp37-cp37m-macosx_10_6_intel.whl (985.8 kB) Copy SHA256 hash SHA256 Wheel cp37
pylsl-1.13.1-cp37-cp37m-win32.whl (335.1 kB) Copy SHA256 hash SHA256 Wheel cp37
pylsl-1.13.1-cp37-cp37m-win_amd64.whl (419.4 kB) Copy SHA256 hash SHA256 Wheel cp37

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page