Release Process¶

This document outlines the release process for SuperQuantX, including versioning, testing, and deployment procedures.

🏷️ Versioning Strategy¶

SuperQuantX follows Semantic Versioning (SemVer):

MAJOR version: Incompatible API changes
MINOR version: Backwards-compatible functionality additions
PATCH version: Backwards-compatible bug fixes

Version Format¶

MAJOR.MINOR.PATCH[-PRERELEASE][+BUILD]

Examples: - 1.0.0 - Major release - 1.1.0 - Minor release with new features - 1.1.1 - Patch release with bug fixes - 1.2.0-alpha.1 - Pre-release version - 1.2.0-rc.1 - Release candidate

🗓️ Release Schedule¶

Regular Releases¶

Major releases: Every 6-12 months
Minor releases: Every 2-3 months
Patch releases: As needed for critical bug fixes

Release Calendar¶

Version	Type	Planned Date	Features
1.1.0	Minor	Q2 2024	Enhanced noise modeling, new backends
1.2.0	Minor	Q3 2024	Distributed computing, performance improvements
1.3.0	Minor	Q4 2024	Advanced error correction, new algorithms
2.0.0	Major	Q1 2025	API redesign, breaking changes

🔄 Release Workflow¶

1. Pre-Release Phase (2 weeks before)¶

Feature Freeze¶

# Create release branch
git checkout -b release/v1.1.0
git push origin release/v1.1.0

Version Update¶

# Update version in src/superquantx/version.py
__version__ = "1.1.0"

Changelog Update¶

# CHANGELOG.md
## [1.1.0] - 2024-03-15

### Added
- Enhanced noise modeling with new channel types
- Support for Braket backend
- Quantum volume benchmarking tools

### Changed
- Improved circuit compilation performance
- Updated documentation structure

### Fixed
- Memory leak in long-running simulations
- Race condition in parallel execution

### Deprecated
- Old API methods (will be removed in v2.0.0)

2. Testing Phase (1 week)¶

Comprehensive Testing¶

# Run full test suite
pytest tests/ -v --cov=superquantx

# Performance benchmarks
pytest tests/performance/ --benchmark-only

# Integration tests with all backends
pytest tests/integration/ -m "all_backends"

# Documentation tests
pytest --doctest-modules src/superquantx/

Release Candidate¶

# Tag release candidate
git tag v1.1.0-rc.1
git push origin v1.1.0-rc.1

# Build and test distribution
python -m build
twine check dist/*

# Upload to TestPyPI
twine upload --repository testpypi dist/*

3. Release Day¶

Final Checks¶

# Ensure main branch is up to date
git checkout main
git pull origin main

# Merge release branch
git merge release/v1.1.0

# Final version tag
git tag v1.1.0
git push origin v1.1.0

Build and Deploy¶

# Clean previous builds
rm -rf dist/ build/

# Build distribution packages
python -m build

# Verify packages
twine check dist/*

# Upload to PyPI
twine upload dist/*

Documentation Update¶

# Update documentation
mkdocs build
mkdocs gh-deploy

# Update API documentation
sphinx-build -b html docs/ docs/_build/html

4. Post-Release¶

GitHub Release¶

Create GitHub release with: - Release notes from CHANGELOG - Binary assets - Migration guide (for breaking changes)

Announcements¶

Update README badges
Post on social media
Email to research community
Update paper repositories

🧪 Quality Assurance¶

Automated Checks¶

CI/CD Pipeline¶

# .github/workflows/release.yml
name: Release

on:
  push:
    tags:
      - 'v*'

jobs:
  test:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Run tests
        run: pytest tests/

  build:
    needs: test
    runs-on: ubuntu-latest
    steps:
      - name: Build package
        run: python -m build

  deploy:
    needs: build
    runs-on: ubuntu-latest
    steps:
      - name: Deploy to PyPI
        run: twine upload dist/*

Quality Gates¶

All tests pass (100%)
Code coverage > 85%
Documentation builds successfully
No security vulnerabilities
Performance benchmarks within 10% of baseline

Manual Testing¶

Backend Compatibility¶

# Test script for backend compatibility
import superquantx as sqx

backends = ['simulator', 'pennylane', 'qiskit', 'cirq']

for backend_name in backends:
    try:
        backend = sqx.get_backend(backend_name)

        # Test basic functionality
        circuit = sqx.QuantumCircuit(2)
        circuit.h(0)
        circuit.cx(0, 1)
        circuit.measure_all()

        result = backend.execute(circuit, shots=100)
        print(f"✅ {backend_name}: {result.counts}")

    except Exception as e:
        print(f"❌ {backend_name}: {e}")

Algorithm Validation¶

# Validate core algorithms
from sklearn.datasets import make_classification

X, y = make_classification(n_samples=20, n_features=2, random_state=42)

algorithms = [
    sqx.QuantumSVM(),
    sqx.VQE(),
    sqx.QAOA()
]

for algo in algorithms:
    try:
        if hasattr(algo, 'fit'):
            algo.fit(X, y)
            print(f"✅ {algo.__class__.__name__}: Training successful")
        else:
            print(f"✅ {algo.__class__.__name__}: Initialization successful")
    except Exception as e:
        print(f"❌ {algo.__class__.__name__}: {e}")

📦 Package Distribution¶

PyPI Configuration¶

Setup Configuration¶

# pyproject.toml
[build-system]
requires = ["setuptools>=45", "wheel", "setuptools_scm>=6.2"]
build-backend = "setuptools.build_meta"

[project]
name = "superquantx"
dynamic = ["version"]
description = "Experimental quantum AI research platform"
authors = [{name = "SuperXLab Research Team"}]
license = {text = "Apache-2.0"}
requires-python = ">=3.9"
classifiers = [
    "Development Status :: 4 - Beta",
    "Intended Audience :: Science/Research",
    "License :: OSI Approved :: Apache Software License",
    "Programming Language :: Python :: 3.9",
    "Programming Language :: Python :: 3.10",
    "Programming Language :: Python :: 3.11",
    "Topic :: Scientific/Engineering :: Physics",
]

Distribution Structure¶

dist/
├── superquantx-1.1.0-py3-none-any.whl    # Wheel package
├── superquantx-1.1.0.tar.gz              # Source distribution
└── superquantx-1.1.0-py3-none-any.whl.asc # GPG signature

Conda Distribution¶

Conda Recipe¶

# conda-recipe/meta.yaml
package:
  name: superquantx
  version: {{ environ.get('GIT_DESCRIBE_TAG', '').replace('v', '') }}

source:
  git_url: https://github.com/SuperagenticAI/superquantx.git
  git_rev: {{ environ.get('GIT_DESCRIBE_TAG', 'HEAD') }}

build:
  number: 0
  script: python -m pip install . -vv
  noarch: python

requirements:
  host:
    - python >=3.9
    - pip
    - setuptools
  run:
    - python >=3.9
    - numpy >=1.21.0
    - scipy >=1.7.0
    - matplotlib >=3.5.0

test:
  imports:
    - superquantx
  commands:
    - python -c "import superquantx; print(superquantx.__version__)"

🐛 Hotfix Process¶

Critical Bug Fixes¶

For critical bugs that need immediate release:

# Create hotfix branch from main
git checkout main
git checkout -b hotfix/v1.1.1

# Fix the bug and test
# ... make changes ...
pytest tests/

# Update version
echo "1.1.1" > src/superquantx/version.py

# Commit and tag
git add .
git commit -m "Fix critical memory leak in simulation"
git tag v1.1.1

# Merge to main and push
git checkout main
git merge hotfix/v1.1.1
git push origin main
git push origin v1.1.1

# Build and deploy immediately
python -m build
twine upload dist/*

📋 Release Checklist¶

Pre-Release Checklist¶

All features for release are complete
Version number updated in all files
CHANGELOG.md updated with all changes
Documentation updated and builds correctly
All tests pass on CI
Performance benchmarks acceptable
Security scan passes
Dependencies updated and compatible
Migration guide written (if needed)

Release Day Checklist¶

Post-Release Checklist¶

🔧 Tools and Scripts¶

Release Automation Script¶

#!/bin/bash
# scripts/release.sh

set -e

VERSION=$1
if [ -z "$VERSION" ]; then
    echo "Usage: ./release.sh <version>"
    exit 1
fi

echo "🚀 Starting release process for version $VERSION"

# Update version
echo "📝 Updating version to $VERSION"
echo "__version__ = \"$VERSION\"" > src/superquantx/version.py

# Run tests
echo "🧪 Running tests"
pytest tests/

# Build package
echo "📦 Building package"
python -m build

# Check package
echo "✅ Checking package"
twine check dist/*

# Create tag
echo "🏷️  Creating git tag"
git add .
git commit -m "Release version $VERSION"
git tag "v$VERSION"

# Upload to PyPI
echo "📤 Uploading to PyPI"
twine upload dist/*

# Push to GitHub
echo "📤 Pushing to GitHub"
git push origin main
git push origin "v$VERSION"

echo "✅ Release $VERSION completed successfully!"

Version Management¶

# scripts/bump_version.py
import re
import sys
from pathlib import Path

def bump_version(current_version, bump_type):
    """Bump version based on type: major, minor, patch"""
    major, minor, patch = map(int, current_version.split('.'))

    if bump_type == 'major':
        major += 1
        minor = 0
        patch = 0
    elif bump_type == 'minor':
        minor += 1
        patch = 0
    elif bump_type == 'patch':
        patch += 1

    return f"{major}.{minor}.{patch}"

if __name__ == "__main__":
    bump_type = sys.argv[1] if len(sys.argv) > 1 else 'patch'

    # Read current version
    version_file = Path("src/superquantx/version.py")
    content = version_file.read_text()

    current_version = re.search(r'__version__ = "(.+)"', content).group(1)
    new_version = bump_version(current_version, bump_type)

    # Update version file
    new_content = content.replace(current_version, new_version)
    version_file.write_text(new_content)

    print(f"Version bumped from {current_version} to {new_version}")

📊 Release Metrics¶

Success Metrics¶

Download Statistics: Track PyPI downloads
GitHub Metrics: Stars, forks, issues
Community Engagement: Discussion activity
Performance: Installation time, import time
Quality: Bug reports, test coverage

Monitoring Dashboard¶

Track key metrics: - Daily downloads - Issue resolution time - Test pass rate - Documentation page views - Backend compatibility status

This release process ensures consistent, high-quality releases of SuperQuantX while maintaining community trust and project stability.