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        "author": "Christian Kothe",
        "author_email": "christiankothe@gmail.com",
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            "Development Status :: 5 - Production/Stable",
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            "License :: OSI Approved :: MIT License",
            "Operating System :: MacOS",
            "Operating System :: Microsoft :: Windows",
            "Operating System :: POSIX :: Linux",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 3",
            "Topic :: Scientific/Engineering",
            "Topic :: System :: Networking"
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        "description": "# pylsl\r\n\r\n[![Build Status](https://travis-ci.com/labstreaminglayer/liblsl-Python.svg?branch=master)](https://travis-ci.com/labstreaminglayer/liblsl-Python)\r\n[![Build status](https://ci.appveyor.com/api/projects/status/ggouc09585l2518i/branch/master?svg=true)](https://ci.appveyor.com/project/cboulay/liblsl-python/branch/master)\r\n\r\nThis is the Python interface to the [Lab Streaming Layer (LSL)](https://github.com/sccn/labstreaminglayer).\r\nLSL is an overlay network for real-time exchange of time series between applications,\r\nmost often used in research environments. LSL has clients for many other languages\r\nand platforms that are compatible with each other.\r\n\r\nLet us know if you encounter any bugs (ideally using the issue tracker on\r\nthe GitHub project).\r\n\r\n# Installation\r\n\r\n## Prepared distributions\r\n\r\nThe following platforms are supported with direct installation from [pypi](https://pypi.org/project/pylsl/)\r\nusing [pip](https://pip.pypa.io/en/stable/installing/): `pip install pylsl`\r\n\r\n|   | macOS 10.6+ | manylinux i686 | manylinux x86_64 |  Windows 32bit | Windows 64bit |\r\n|---|---|---|---|---|---|\r\n| Python 2.7 | \u2705 |  |  | \u2705 | \u2705 |\r\n| Python 3.4 | \u2705 |  |  | \u2705 | \u2705 |\r\n| Python 3.5 | \u2705 |  | \u2705 | \u2705 | \u2705 |\r\n| Python 3.6 | \u2705 |  | \u2705 | \u2705 | \u2705 |\r\n| Python 3.7 | \u2705 |  | \u2705 | \u2705 | \u2705 |\r\n\r\nMore or less experimental releases are in [tstenner's anaconda repo](https://anaconda.org/tstenner/pylsl), install with `conda install -c tstenner pylsl`.\r\n\r\n## Self-built\r\n\r\nIf 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.\r\nYou 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](https://github.com/sccn/liblsl/releases).\r\n* Copy the shared object into `liblsl-Python/pylsl/lib` (use `cp -L` on platforms that use symlinks).\r\n* From the `liblsl-Python` working directory, run `pip install .`.\r\n    * Note: You can use `pip install -e .` to install while keeping the files in-place. This is convenient for developing pylsl.\r\n\r\n# Usage\r\n\r\nSee the examples in pylsl/examples. Note that these can be run directly from the commandline with (e.g.) `python -m pylsl.examples.SendStringMarkers`.\r\n\r\n# For maintainers\r\n\r\n## Continuous Integration\r\n\r\npylsl uses continuous integration. It uses AppVeyor for Windows and Linux, and Travis-CI for MacOS.\r\nWhenever a new commit is pushed, AppVeyor and Travis build liblsl, copy it into the correct directory, install pylsl, then test its basic functionality.\r\nIn addition, whenever a new `git tag` is used on a commit that is pushed to the master branch,\r\nthe CI systems will deploy new wheels to pypi.\r\n\r\n## Manual Distrubtion\r\n\r\n1. Manual way:\r\n    1. `rm -Rf build dist *.egg-info`\r\n    1. `python setup.py sdist bdist_wheel`\r\n    1. `twine upload dist/*`\r\n1. For conda\r\n    1. build liblsl: `conda build ../liblsl/`\r\n    1. `conda build .`\r\n\r\n# Known Issues\r\n\r\n* On Linux one currently cannot call ``pylsl`` functions from a thread that is not the main thread.\r\n\r\n# Acknowledgments\r\n\r\nPylsl was primarily written by Christian Kothe while at Swartz Center for\r\nComputational Neuroscience, UCSD. The LSL project was funded by the Army\r\nResearch Laboratory under Cooperative Agreement Number W911NF-10-2-0022 as\r\nwell as through NINDS grant 3R01NS047293-06S1. Thanks for contributions,\r\nbug reports, and suggestions go to Bastian Venthur, Chadwick Boulay,\r\nDavid Medine, Clemens Brunner, and Matthew Grivich.\r\n\r\n\r\n",
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        "keywords": "networking lsl lab streaming layer labstreaminglayer data acquisition",
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