CI/CD Pipelines for Qiskit/Cirq Projects

As quantum software development evolves, applying modern CI/CD (Continuous Integration and Continuous Deployment) practices ensures efficient collaboration, reliable code, and faster innovation. Qiskit (IBM) and Cirq (Google) are two leading quantum frameworks, both built in Python and widely used for simulating and running quantum circuits.

Setting up a CI/CD pipeline for these frameworks enables automatic testing, environment setup, code validation, and deployment to cloud environments or research platforms.

1. Why Use CI/CD in Quantum Projects?

Quantum computing projects benefit from CI/CD for several reasons:

Rapid prototyping and validation of quantum circuits.
Collaboration among teams with reliable version control.
Error prevention through automated testing before merging.
Consistency across different environments (local, test, production).
Documentation validation for research reproducibility.

2. Basic Project Structure

Organize your Qiskit/Cirq project with a clean structure:

/quantum-project
├── main.py
├── circuits/
│   └── bell_circuit.py
├── tests/
│   └── test_circuits.py
├── requirements.txt
├── README.md
└── .github/
    └── workflows/
        └── ci.yml

3. Workflow with GitHub Actions (CI Pipeline)

A GitHub Actions pipeline file .github/workflows/ci.yml automates the process.

name: Quantum CI

on: [push, pull_request]

jobs:
  test:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout code
        uses: actions/checkout@v3

      - name: Set up Python
        uses: actions/setup-python@v4
        with:
          python-version: '3.10'

      - name: Install dependencies
        run: |
          pip install --upgrade pip
          pip install -r requirements.txt

      - name: Run unit tests
        run: |
          pytest tests/

4. Sample `requirements.txt`

For Qiskit projects:

qiskit==1.0.0
pytest

For Cirq projects:

cirq
pytest

Optionally include tools for code quality:

black
flake8
mypy

5. Writing Tests

Example test for Qiskit (tests/test_circuits.py):

from qiskit import QuantumCircuit

def test_bell_state():
    qc = QuantumCircuit(2)
    qc.h(0)
    qc.cx(0, 1)
    assert qc.depth() == 2

For Cirq:

import cirq

def test_cirq_circuit():
    qubit = cirq.LineQubit(0)
    circuit = cirq.Circuit(cirq.X(qubit))
    assert len(circuit) == 1

6. Optional Additions to Pipeline

a. Linting and Formatting

     - name: Lint with flake8
        run: flake8 .

b. Type Checking with mypy

     - name: Static Type Checking
        run: mypy .

c. Notebook Testing (if using Jupyter)

      - name: Test Jupyter Notebooks
        run: |
          pip install nbval
          pytest --nbval notebooks/

7. Deployment Options

Quantum projects can also deploy:

Simulation Results Dashboards (e.g., via Streamlit or Flask).
Cloud Submissions to IBM Q Experience or Google Quantum Cloud using API tokens (stored in GitHub Secrets).
Publishing Libraries to PyPI or GitHub Packages via release pipelines.

8. GitHub Secrets for API Access

If using cloud quantum backends, store your credentials securely:

IBMQ_API_TOKEN for Qiskit
GOOGLE_CLOUD_KEY or service account token for Cirq/GCP

Use secrets in workflow:

env:
  IBMQ_API_TOKEN: ${{ secrets.IBMQ_API_TOKEN }}

9. Multi-Framework Testing

If your project supports both Qiskit and Cirq, you can define a matrix strategy in your pipeline:

strategy:
  matrix:
    sdk: [qiskit, cirq]

Then conditionally install dependencies and run appropriate tests based on the selected SDK.

10. Benefits of CI/CD in Quantum Software

Scalability: Support large, modular quantum projects with confidence.
Traceability: Track failures and bug fixes through automated logs.
Team Agility: Encourage faster iteration in multi-developer environments.
Community Readiness: Open-source contributions are easier to validate.