python-oephys 0.1.2

Python interface and utilities for working with Open Ephys devices and electrophysiology data

python-open-ephys

python-open-ephys is a Python toolkit for loading, streaming, processing, and visualizing Open Ephys electrophysiology data. The project combines file I/O, real-time interfaces, signal-processing utilities, and higher-level application examples in one package.

Highlights

• Load Open Ephys Binary recordings and normalized NPZ exports.
• Stream live data from the Open Ephys GUI over ZMQ and LSL.
• Process EMG and electrophysiology signals with filtering, synchronization, and QC utilities.
• Run GUI tools for viewing recordings and inspecting real-time streams.
• Prototype machine-learning workflows on top of the same session format.

Installation

Install the latest published release from PyPI:

pip install python-oephys

Install optional feature sets as needed:

pip install "python-oephys[gui]"
pip install "python-oephys[ml]"
pip install "python-oephys[docs]"

Install from source for development:

git clone https://github.com/Neuro-Mechatronics-Interfaces/python-open-ephys.git
cd python-open-ephys
pip install -e .

Install a pre-release build from TestPyPI when you want to validate an upcoming release candidate:

pip install --index-url https://test.pypi.org/simple/ --no-deps python-oephys

Quick Start

from pyoephys.io import load_open_ephys_session
from pyoephys.processing import filter_emg

session = load_open_ephys_session("path/to/recording.oebin")
amplifier_data = session["amplifier_data"]
sample_rate = session["sample_rate"]

filtered = filter_emg(
    amplifier_data,
    filter_type="bandpass",
    lowcut=10,
    highcut=500,
    fs=sample_rate,
)

Launch the real-time viewer against an Open Ephys ZMQ stream:

python -m pyoephys.applications._realtime_viewer --host 127.0.0.1 --channels 0:8

Examples

The repository includes runnable examples for common workflows:

• examples/read_files/ for loading .oebin recordings and exporting session data.
• examples/interface/ for ZMQ, LSL, IMU, and hardware integration workflows.
• examples/applications/ for standalone viewers and analysis tools.
• examples/analysis/, examples/benchmarks/, and examples/visualization/ for downstream analysis and diagnostics.

Documentation

Hosted documentation: https://neuro-mechatronics-interfaces.github.io/python-open-ephys/

Build the docs locally with:

python -m sphinx -b html docs/source docs/build/html

Development

Run the test suite:

pytest tests/

Build source and wheel distributions:

python -m build

Release Workflow

• Pushes to main publish the Sphinx site to GitHub Pages.
• The Test Publish to TestPyPI workflow is available for manual pre-release validation.
• Publishing a GitHub Release triggers the PyPI publish workflow.

Contributing

Issues and pull requests are welcome. If you are proposing a new feature, include the target workflow, example data format, and any GUI or hardware assumptions so the change can be tested cleanly.

License

This project is licensed under the MIT License. See LICENSE for details.