RELEASE-CHECKLIST.md

Release Checklist for v1.0.1

This document guides you through creating your first release of Jenkins AI Optimizer on PyPI.

✅ Pre-Release Checklist (Completed)

• Updated author email in pyproject.toml to karadhub@gmail.com
• Fixed Issues URL typo (JkaradHub → karadHub)
• Updated license format to SPDX identifier (GPL-3.0-or-later)
• Created comprehensive CHANGELOG.md with all v1.0.1 features
• Built package locally and verified with twine check
• Created GitHub workflow .github/workflows/publish.yml

🔧 Setup Steps Required (Do These Now)

Step 1: Create PyPI and Test PyPI Accounts

1. Create PyPI account: https://pypi.org/account/register/

   • Use email: karadhub@gmail.com
   • Enable 2FA (required for publishing)

2. Create Test PyPI account: https://test.pypi.org/account/register/

   • Same email for consistency
   • Enable 2FA

Step 2: Configure Trusted Publishing on PyPI

For Test PyPI (do this first):

1. Go to: https://test.pypi.org/manage/account/publishing/
2. Click "Add a new pending publisher"
3. Fill in:
   • PyPI Project Name: jenkins-ai-optimizer
   • Owner: karadHub
   • Repository name: jenkins-ai-optimizer
   • Workflow filename: publish.yml
   • Environment name: test-pypi
4. Click "Add"

For Production PyPI (do after testing):

1. Go to: https://pypi.org/manage/account/publishing/
2. Click "Add a new pending publisher"
3. Fill in:
   • PyPI Project Name: jenkins-ai-optimizer
   • Owner: karadHub
   • Repository name: jenkins-ai-optimizer
   • Workflow filename: publish.yml
   • Environment name: pypi
4. Click "Add"

Step 3: Create GitHub Environments

1. Go to your repository: https://github.com/karadHub/jenkins-ai-optimizer
2. Click Settings → Environments
3. Click "New environment"
4. Create environment named: test-pypi
5. (Optional) Add protection rules:
   • ✓ Required reviewers (yourself)
   • ✓ Wait timer (0 minutes)
6. Click "Configure environment"
7. Repeat for environment named: pypi

Step 4: Commit and Push Current Changes

# Stage all changes
git add .

# Commit the release preparation
git commit -m "chore: prepare for v1.0.1 release

- Updated author email and fixed URLs in pyproject.toml
- Created CHANGELOG.md with comprehensive feature list
- Added GitHub workflow for PyPI publishing
- Fixed license format to SPDX identifier
- Verified package builds successfully"

# Push to GitHub
git push origin main

🧪 Testing the Release (Test PyPI First)

Option A: Test with Manual Workflow Trigger

1. Go to: https://github.com/karadHub/jenkins-ai-optimizer/actions
2. Click "Publish to PyPI" workflow
3. Click "Run workflow"
4. ✓ Check "Publish to Test PyPI instead of PyPI"
5. Click "Run workflow" button

Option B: Test Locally (If workflow fails)

# Build the package (already done)
python -m build

# Upload to Test PyPI manually
python -m twine upload --repository testpypi dist/*

# You'll need to create an API token at:
# https://test.pypi.org/manage/account/token/

Verify Test PyPI Installation

# Install from Test PyPI
pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple jenkins-ai-optimizer

# Test the installation
jenkins_mcp_enterprise --help

# Uninstall after testing
pip uninstall jenkins-ai-optimizer -y

🚀 Production Release

Create GitHub Release (Triggers Production PyPI)

1. Go to: https://github.com/karadHub/jenkins-ai-optimizer/releases
2. Click "Draft a new release"
3. Fill in:
   • Choose a tag: v1.0.1 (create new tag on publish)
   • Target: main
   • Release title: v1.0.1 - Initial Public Release
   • Description: Copy from CHANGELOG.md (the v1.0.1 section)
4. ✓ Check "Set as the latest release"
5. Click "Publish release"

This will automatically:

• Trigger the GitHub workflow
• Build the package
• Publish to PyPI
• Make it available via pip install jenkins-ai-optimizer

📋 Post-Release Verification

1. Check PyPI page: https://pypi.org/project/jenkins-ai-optimizer/

   • Verify version shows as 1.0.1
   • Check that README displays correctly
   • Verify all metadata (author, license, links)

2. Test installation from PyPI:

   # In a fresh environment
   pip install jenkins-ai-optimizer
   
   # Verify installation
   jenkins_mcp_enterprise --version
   jenkins_mcp_enterprise --help

3. Monitor downloads: PyPI provides statistics at:

   • https://pypistats.org/packages/jenkins-ai-optimizer

4. Update README badge (optional): Add to README.md after release:

   [![PyPI version](https://badge.fury.io/py/jenkins-ai-optimizer.svg)](https://badge.fury.io/py/jenkins-ai-optimizer)
   [![Downloads](https://pepy.tech/badge/jenkins-ai-optimizer)](https://pepy.tech/project/jenkins-ai-optimizer)

🎉 Announcement

After successful release, consider:

1. GitHub Discussions: Announce in your repo discussions
2. Social Media: Share on Twitter/LinkedIn with #DevOps #Jenkins #AI #MCP tags
3. Reddit: r/devops, r/Python, r/opensource
4. Discord/Slack: Share in relevant DevOps communities

📊 Release Summary

Package Details:

• Name: jenkins-ai-optimizer
• Version: 1.0.1
• License: GPL-3.0-or-later
• Author: Vaibhav Karad (karadhub@gmail.com)
• Repository: https://github.com/karadHub/jenkins-ai-optimizer
• PyPI: https://pypi.org/project/jenkins-ai-optimizer/

Installation Command:

pip install jenkins-ai-optimizer

Command Line Usage:

jenkins_mcp_enterprise --config config/mcp-config.yml --transport stdio

🔄 Next Steps After v1.0.1

1. Start working on v1.1.0 features
2. Set up GitHub issue templates
3. Create contributing guidelines
4. Add more comprehensive examples
5. Consider creating a documentation site (GitHub Pages, Read the Docs)

⚠️ Important Notes

• Version Immutability: Once published to PyPI, you cannot republish the same version
• Delete Limitation: You can only delete releases within 24 hours
• Test First: Always test on Test PyPI before production
• Semantic Versioning: Follow semver for version numbers (MAJOR.MINOR.PATCH)

🆘 Troubleshooting

"Package already exists" error

• You can't republish the same version
• Increment version in pyproject.toml and rebuild

Trusted Publishing not working

• Verify environment names match exactly (case-sensitive)
• Ensure workflow is pushed to default branch (main)
• Check that you're creating release, not just tags

Build fails in workflow

• Check Python version compatibility
• Verify all files are committed to git
• Review workflow logs in GitHub Actions

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Good luck with your first release! 🚀

If you encounter any issues, check the GitHub Actions logs or PyPI project dashboard for details.