quantum-circuit-drawer 0.2.1

Backend-agnostic quantum circuit drawing library with Matplotlib as the first renderer.

quantum-circuit-drawer

quantum-circuit-drawer is a small Python library for drawing quantum circuits from different ecosystems with one consistent Matplotlib-based visual style.

It gives you one public entry point, draw_quantum_circuit(...), for supported Qiskit, Cirq, PennyLane, MyQLM, CUDA-Q, and internal IR inputs. The goal is simple: keep your visualization code stable even when the circuit source changes.

Why this library

Quantum frameworks do not all expose the same drawing workflow. This project focuses on the visualization layer, so you can:

• keep the same look across different circuit frameworks
• save circuit diagrams for reports, notebooks, and documentation
• draw into your own Matplotlib figures when you need larger layouts
• use one typed API instead of several framework-specific drawing calls

Supported inputs

Input path	Install	Typical object	Notes
Internal IR	python -m pip install quantum-circuit-drawer	CircuitIR	Included in the base package
Qiskit	python -m pip install "quantum-circuit-drawer[qiskit]"	qiskit.QuantumCircuit	Good default if you mainly use Qiskit
Cirq	python -m pip install "quantum-circuit-drawer[cirq]"	cirq.Circuit	Works with explicit or automatic framework detection
PennyLane	python -m pip install "quantum-circuit-drawer[pennylane]"	tape-like objects	Supports QuantumTape, QuantumScript, and wrappers exposing .qtape or .tape
MyQLM	python -m pip install "quantum-circuit-drawer[myqlm]"	qat.core.Circuit	Convert from Program().to_circ() first
CUDA-Q	python -m pip install "quantum-circuit-drawer[cudaq]"	closed CUDA-Q kernels	Linux or WSL2 oriented

Install

Install the base package inside your virtual environment:

python -m pip install quantum-circuit-drawer

Install the framework extra you need, for example Qiskit:

python -m pip install "quantum-circuit-drawer[qiskit]"

For notebooks, install Jupyter tools in the same environment:

python -m pip install jupyter ipykernel

See the full installation guide for Windows PowerShell commands, Linux/WSL commands, optional extras, CUDA-Q notes, and local editable installs.

Basic usage

from qiskit import QuantumCircuit

from quantum_circuit_drawer import draw_quantum_circuit

circuit = QuantumCircuit(2, 1)
circuit.h(0)
circuit.cx(0, 1)
circuit.measure(1, 0)

figure, axes = draw_quantum_circuit(circuit)

By default, the library detects the circuit framework, creates a Matplotlib figure, uses the built-in dark theme, and shows the figure when the active Matplotlib backend is interactive.

For script-friendly output:

draw_quantum_circuit(circuit, output="bell.png", show=False)

Documentation

• Documentation index: the full map.
• Getting started: the shortest first successful example.
• Installation: virtual environments, extras, notebooks, and local installs.
• API reference: draw_quantum_circuit(...), style options, return values, and exceptions.
• User guide: workflows, examples, tips, 2D/3D views, sliders, and reports.
• Frameworks: Qiskit, Cirq, PennyLane, MyQLM, CUDA-Q, and internal IR notes.
• Recipes: copy-paste solutions for common tasks.
• Troubleshooting: common errors and fixes.
• Development: local checks, build commands, and benchmark notes.

Runnable example scripts live in examples/, with more detail in examples/README.md.

Project links

• Repository: github.com/DOKOS-TAYOS/quantum-circuit-drawer
• Issue tracker: github.com/DOKOS-TAYOS/quantum-circuit-drawer/issues
• Changelog: CHANGELOG.md

License

This project is distributed under the MIT License.