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🚀 PyPI Deployment Setup Guide for UnicoLab

This guide will help you set up automated PyPI deployment for the KMR package under the UnicoLab organization.

📋 Prerequisites

  1. UnicoLab PyPI Account: Create a PyPI account for UnicoLab organization
  2. GitHub Repository: Ensure the repository is under UnicoLab/keras-model-registry
  3. GitHub Actions: Enable GitHub Actions in repository settings

🔧 Step 1: Create UnicoLab PyPI Account

1.1 Register PyPI Account

  1. Go to PyPI Registration
  2. Use an official UnicoLab email address (e.g., contact@unicolab.ai)
  3. Choose a username like unicolab or unicolab-org
  4. Complete the registration process

1.2 Generate API Token

  1. Log into your PyPI account
  2. Go to Account Settings → API tokens
  3. Click Add API token
  4. Choose Scope: Entire account (all projects)
  5. Token name: KMR Package Deployment
  6. Copy the generated token (starts with pypi-)

🔐 Step 2: Configure GitHub Secrets

2.1 Add PyPI Token to GitHub

  1. Go to your GitHub repository: https://github.com/UnicoLab/keras-model-registry
  2. Navigate to Settings → Secrets and variables → Actions
  3. Click New repository secret
  4. Name: PYPI_API_TOKEN
  5. Value: Paste your PyPI API token
  6. Click Add secret

2.2 Verify Secrets

Your repository should now have: - PYPI_API_TOKEN: Your PyPI API token - GITHUB_TOKEN: Automatically provided by GitHub

🚀 Step 3: Test Deployment

  1. Go to Actions tab in your GitHub repository
  2. Select Publish to PyPI - UnicoLab workflow
  3. Click Run workflow
  4. Enter version: 0.1.0
  5. Click Run workflow

3.2 Automatic Deployment via Tags

# Create and push a tag to trigger automatic deployment
git tag v0.1.0
git push origin v0.1.0

📦 Step 4: Verify Package on PyPI

  1. Go to PyPI
  2. Verify the package appears with UnicoLab branding
  3. Test installation: 
    pip install kmr

🔄 Step 5: Update Package Information

5.1 Package Metadata

The pyproject.toml is already configured with: - Name: kmr - Author: UnicoLab <contact@unicolab.ai> - Homepage: https://unicolab.ai - Repository: https://github.com/UnicoLab/keras-model-registry - Documentation: https://unicolab.github.io/keras-model-registry/

5.2 Package Description

The package description includes UnicoLab branding: 

"Reusable Model Architecture Bricks in Keras - Enterprise AI by UnicoLab"

🎯 Step 6: Release Process

6.1 Version Bumping

Update version in pyproject.toml: 

[tool.poetry]
version = "0.1.1"  # Increment as needed

6.2 Create Release

# Update version
poetry version patch  # or minor, major

# Create tag
git add pyproject.toml
git commit -m "Bump version to $(poetry version -s)"
git tag v$(poetry version -s)
git push origin main --tags

6.3 GitHub Release

The workflow automatically creates a GitHub release with: - Release notes - Documentation deployment - PyPI package upload

🛠️ Workflow Features

The PUBLISH_PYPI.yml workflow includes:

✅ Automated Testing

  • Runs full test suite before deployment
  • Ensures code quality with linting
  • Validates package structure

✅ Build Process

  • Uses Poetry for dependency management
  • Builds wheel and source distributions
  • Validates package metadata

✅ Deployment

  • Uploads to PyPI with proper authentication
  • Creates GitHub release automatically
  • Deploys documentation to GitHub Pages

✅ Security

  • Uses GitHub secrets for API tokens
  • No hardcoded credentials
  • Secure token handling

🔍 Troubleshooting

Common Issues

1. Authentication Failed

Error: HTTP 403: The user 'unicolab' isn't allowed to upload to project 'kmr'
Solution: Ensure the PyPI token has the correct scope and the package name is available.

2. Package Already Exists

Error: File already exists
Solution: Increment the version number in pyproject.toml.

3. Build Failed

Error: Poetry build failed
Solution: Check pyproject.toml syntax and dependencies.

Debug Steps

  1. Check GitHub Actions logs
  2. Verify PyPI token permissions
  3. Test local build: poetry build
  4. Validate package: poetry check

📚 Additional Resources

🎉 Success Checklist

  • UnicoLab PyPI account created
  • API token generated and added to GitHub secrets
  • Package builds successfully locally
  • First deployment to PyPI successful
  • Package appears on PyPI with correct metadata
  • Documentation deployed to GitHub Pages
  • Installation test: pip install kmr

🚀 Next Steps

After successful deployment:

  1. Announce Release: Share on UnicoLab social media and blog
  2. Monitor Usage: Track PyPI download statistics
  3. Gather Feedback: Collect user feedback for improvements
  4. Plan Next Release: Prepare roadmap for future versions

Need Help? Contact the UnicoLab team at contact@unicolab.ai