---
id: dwave-networkx
version: "0.8.19"
license: Apache 2.0
license_treatment: permissive
maintenance: active
---

# dwave-networkx — A NetworkX extension providing graphs and algorithms relevant to working with the D-Wave System

License: permissive · Maintenance: active · Downloads: 95.6K/mo

## What it is and what it does

dwave-networkx is a NetworkX extension designed for users working with D-Wave quantum computers. It provides specialized tools for working with quantum processor unit (QPU) topology graphs—such as the Pegasus topology used on Advantage quantum computers—and implements graph-theory algorithms that run on D-Wave quantum systems and other binary quadratic model samplers. The package builds on NetworkX's graph exploration and analysis capabilities, adding quantum-specific functionality.

The package is actively maintained but officially deprecated in favor of dwave-graphs, which provides the same core functionality under a new namespace (dwave.graphs). It has low installation friction as a pure-Python package and supports modern Python versions (3.10–3.14). Its three runtime dependencies—NetworkX, dimod, and NumPy—are widely used and stable.

Use it for:

- Generate and analyze Pegasus topology graphs for D-Wave Advantage quantum computers.
- Implement graph algorithms optimized for quantum processing on D-Wave systems.
- Convert classical graph problems into binary quadratic models for quantum sampling.
- Explore quantum processor connectivity and topology constraints in research.
- Prototype quantum-classical hybrid algorithms using graph-based problem formulations.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Extends NetworkX with tools for D-Wave quantum computer topology graphs and implements graph algorithms for quantum processing units and binary quadratic model samplers.

Yes, but with a caveat: the package is actively maintained and suitable for working with D-Wave quantum systems, but it is officially deprecated in favor of dwave-graphs. Install this only if you have an existing codebase using dwave-networkx or are specifically targeting its current API; for new projects, use dwave-graphs instead. No security vulnerabilities are known.

## Install

pip install dwave-networkx
uv add dwave-networkx
poetry add dwave-networkx

## Installing dwave-networkx

Before you install: Low install friction with a pure-Python wheel distribution. Actively maintained with a recent release (59 days old) and current Python version support (3.10–3.14). Repository shows steady activity and modest community engagement (95 stars).

License in practice: Released under Apache License 2.0, a permissive license that allows commercial and private use with minimal restrictions—suitable for most projects.

Quickstart:

pip install dwave-networkx

import dwave_networkx as dnx
graph = dnx.pegasus_graph(16)

Requires Python 3.10 or later; depends on NetworkX, dimod, and NumPy.

Verify before relying:

- Whether dwave-graphs (the recommended replacement) provides feature parity or if migration is necessary for new projects.
- Specific quantum algorithms implemented beyond graph topology support.
- Performance characteristics when working with large Pegasus topologies.

## Package facts

- License: Apache 2.0 (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 95.6K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

quantum computing graph algorithms, D-Wave QPU topology, Pegasus graph generation, quantum network analysis, binary quadratic model graphs, quantum processor topology, D-Wave quantum graphs, quantum-computing, graph-algorithms, deprecated

[View on SkillFed](https://skillfed.io/packages/dwave-networkx) · [View on PyPI](https://pypi.org/project/dwave-networkx/)