Circuitgraph
Tools for working with circuits as graphs in python
Install / Use
/learn @circuitgraph/CircuitgraphREADME
CircuitGraph
CircuitGraph is a library for working with hardware designs as graphs. CircuitGraph provides an interface to do this built on NetworkX, along with integrations with other useful tools such as sat solvers and the Yosys synthesis tool, and input/output to verilog.
Overview
The Circuit class is at the core of the library and it is essentially a wrapper around a NetworkX graph object. This graph is accessable through the graph member variable of Circuit and can be used as an entrypoint to the robust NetworkX API.
Here's a simple example of reading in a verilog file, adding a node to the graph, and writing back to a new file.
import circuitgraph as cg
c = cg.from_file('/path/to/circuit.v')
# Add an AND gate to the circuit that takes as input nets o0, o1, o2, o3
c.add('g', 'and', fanin=[f'o{i}' for i in range(4)])
cg.to_file(c, '/path/to/output/circuit.v')
The documentation can be found here.
Installation
CircuitGraph requires Python3.7 or greater The easiest way to install is via PyPi:
pip install circuitgraph
To install from the release, download and:
pip install circuitgraph-<release>.tar.gz
Finally, to install in-place with the source, use:
cd <install location>
git clone https://github.com/circuitgraph/circuitgraph.git
cd circuitgraph
pip install -r requirements.txt
pip install -e .
Optional Packages
In addition to the packages enumerated in requirements.txt, there are a few tools you can install to enable additional functionality.
If you would like to use the satisfiability functionality, install PySAT.
Open source synthesis can be perofmred by installing Yosys and adding it to your path.
Alternatively, Genus or DesignCompiler can be used by providing the path to a generic library to use by setting the CIRCUITGRAPH_GENUS_LIBRARY_PATH and CIRCUITGRAPH_DC_LIBRARY_PATH environment variables.
Contributing
If you have ideas on how to improve this library we'd love to hear your suggestions. Please open an issue. If you want to develop the improvement yourself, please consider the information below.
Coverage is computed using Codecov. If you would like to generate coverage information locally, install coverage and codecov.
pip install coverage codecov
make coverage
Documentation is built using pdoc3.
pip install pdoc3
make doc
Tests are run using the builtin unittest framework. Some basic linting is performed using flake8.
pip instsall flake8
make test
Code should be formatted using black. Pre-commit is used to automatically run black on commit.
pip install black pre-commit
pre-commit install
Pre-commit also runs a few other hooks, including a docstring formatter and linter. Docs follow the numpy documentation convention.
Citation
If you use this software for your research, we ask you cite this publication: https://joss.theoj.org/papers/10.21105/joss.02646
@article{sweeney2020circuitgraph,
title={CircuitGraph: A Python package for Boolean circuits},
author={Sweeney, Joseph and Purdy, Ruben and Blanton, Ronald D and Pileggi, Lawrence},
journal={Journal of Open Source Software},
volume={5},
number={56},
pages={2646},
year={2020}
}
Acknowledgements
Circuitgraph icon designed by ncasti.
Related Skills
node-connect
339.3kDiagnose OpenClaw node connection and pairing failures for Android, iOS, and macOS companion apps
claude-opus-4-5-migration
83.9kMigrate prompts and code from Claude Sonnet 4.0, Sonnet 4.5, or Opus 4.1 to Opus 4.5
frontend-design
83.9kCreate distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.
model-usage
339.3kUse CodexBar CLI local cost usage to summarize per-model usage for Codex or Claude, including the current (most recent) model or a full model breakdown. Trigger when asked for model-level usage/cost data from codexbar, or when you need a scriptable per-model summary from codexbar cost JSON.
