CommKit

High-performance digital communications research kit for Python.

CommKit is a Python library for digital communications research that treats hardware as a first-class concern. A single Signal object carries IQ samples, physical metadata, and modulation context - with DSP operations dispatching automatically to NumPy, CuPy, or JAX based on data location.

Why CommKit?

• One object, complete context: Sampling rate, symbol rate, modulation format, and pulse shape travel with the signal through the processing pipeline.
• Backend-transparent DSP: dispatch() resolves NumPy, CuPy, or SciPy modules at runtime. The same code executes seamlessly on CPU or GPU.
• Functional pipelines: DSP functions accept and return a Signal directly (sig = fir_filter(sig, taps); sig = resample(sig, sps_out=2)), so pipelines compose without a monolithic Signal wrapper API - sig.to("gpu") moves data across backends, the rest is plain function composition.
• JAX escape hatch: Zero-copy DLPack export on GPU allows direct application of JAX transforms (gradients, vmap, scan) without leaving the research loop.

Modules & Features

Installation & Usage

Requires Python 3.12+ and uv.

Core Installation (CPU)

# Using uv (Recommended)
uv pip install commkit

# Or with standard pip
pip install commkit

GPU Support

To install with CUDA acceleration (includes JAX CUDA 13 and CuPy stacks):

# Using uv
uv pip install "commkit[gpu]"

# Or with standard pip
pip install "commkit[gpu]"

Notebook Support

To run the example notebooks and enable the rich HTML Signal.print_info() table (falls back to plain text without it):

# Using uv
uv pip install "commkit[notebook]"

# Or with standard pip
pip install "commkit[notebook]"

Extras can be combined, e.g. commkit[gpu,notebook], or install everything at once with commkit[full].

Development Installation

git clone https://github.com/lokgar/commkit.git
cd commkit

# Sync core environment
uv sync

# Sync environment with all extras (including GPU and notebook packages)
uv sync --all-extras

Examples & Notebooks

For complete usage scripts and DSP examples, explore the examples/ directory.

Running Tests

# CPU test suite
uv run pytest --device=cpu

# GPU test suite (requires CuPy + CUDA)
uv run pytest --device=gpu

# Run all test suites
uv run pytest --device=all

License

This project is licensed under the MIT License.