Poetry Packaging

Poetry Packaging

Overview

Master modern Python dependency management and packaging with Poetry. Learn to create, manage, and publish professional Python packages with reproducible builds and clean dependency resolution.

Learning Objectives

• Manage project dependencies with Poetry
• Create and publish Python packages
• Handle version constraints and dependency resolution
• Structure projects following best practices
• Implement semantic versioning
• Automate packaging workflows

Core Topics

1. Poetry Basics

• Installing Poetry
• Creating new projects
• Managing dependencies
• Virtual environment management
• Lock files and reproducibility
• Poetry commands and workflow

Code Example:

# Install Poetry
curl -sSL https://install.python-poetry.org | python3 -

# Create new project
poetry new my-awesome-package
cd my-awesome-package

# Project structure created:
# my-awesome-package/
# ├── my_awesome_package/
# │   └── __init__.py
# ├── tests/
# │   └── __init__.py
# ├── pyproject.toml
# └── README.md

# Add dependencies
poetry add requests
poetry add pandas numpy
poetry add --group dev pytest black mypy

# Install dependencies
poetry install

# Run commands in virtual environment
poetry run python main.py
poetry run pytest

# Update dependencies
poetry update

# Show dependency tree
poetry show --tree

# Export to requirements.txt
poetry export -f requirements.txt --output requirements.txt

2. pyproject.toml Configuration

• Project metadata
• Dependency specification
• Version constraints
• Development dependencies
• Build system configuration
• Scripts and entry points

Code Example:

# pyproject.toml
[tool.poetry]
name = "my-awesome-package"
version = "0.1.0"
description = "An awesome Python package"
authors = ["Your Name <you@example.com>"]
license = "MIT"
readme = "README.md"
homepage = "https://github.com/username/my-awesome-package"
repository = "https://github.com/username/my-awesome-package"
documentation = "https://my-awesome-package.readthedocs.io"
keywords = ["awesome", "package", "python"]
classifiers = [
    "Development Status :: 3 - Alpha",
    "Intended Audience :: Developers",
    "License :: OSI Approved :: MIT License",
    "Programming Language :: Python :: 3",
    "Programming Language :: Python :: 3.9",
    "Programming Language :: Python :: 3.10",
    "Programming Language :: Python :: 3.11",
]

[tool.poetry.dependencies]
python = "^3.9"
requests = "^2.28.0"
pandas = "^2.0.0"
click = "^8.1.0"

[tool.poetry.group.dev.dependencies]
pytest = "^7.0.0"
pytest-cov = "^4.0.0"
black = "^23.0.0"
mypy = "^1.0.0"
ruff = "^0.1.0"

[tool.poetry.scripts]
my-cli = "my_awesome_package.cli:main"

[build-system]
requires = ["poetry-core>=1.0.0"]
build-backend = "poetry.core.masonry.api"

# Version constraints examples:
# ^2.0.0  = >=2.0.0 <3.0.0  (caret)
# ~2.0.0  = >=2.0.0 <2.1.0  (tilde)
# 2.0.*   = >=2.0.0 <2.1.0  (wildcard)
# >=2.0.0 = 2.0.0 or higher (range)

3. Package Structure & Publishing

• Package layout best practices
• Versioning with semantic versioning
• Building distributions (sdist, wheel)
• Publishing to PyPI/TestPyPI
• Package metadata
• Documentation generation

Code Example:

# Recommended package structure
my-awesome-package/
├── my_awesome_package/
│   ├── __init__.py           # Package initialization
│   ├── core.py               # Core functionality
│   ├── utils.py              # Utility functions
│   ├── cli.py                # Command-line interface
│   └── py.typed              # Type hints marker
├── tests/
│   ├── __init__.py
│   ├── test_core.py
│   └── test_utils.py
├── docs/
│   ├── index.md
│   └── api.md
├── examples/
│   └── basic_usage.py
├── pyproject.toml
├── README.md
├── LICENSE
├── CHANGELOG.md
└── .gitignore

# my_awesome_package/__init__.py
"""
My Awesome Package

A comprehensive package for doing awesome things.
"""

__version__ = "0.1.0"
__author__ = "Your Name"
__email__ = "you@example.com"

from .core import main_function
from .utils import helper_function

__all__ = ["main_function", "helper_function"]

# Publishing workflow
# 1. Update version in pyproject.toml
poetry version patch  # 0.1.0 -> 0.1.1
poetry version minor  # 0.1.1 -> 0.2.0
poetry version major  # 0.2.0 -> 1.0.0

# 2. Build package
poetry build
# Creates dist/my_awesome_package-0.1.0.tar.gz
# Creates dist/my_awesome_package-0.1.0-py3-none-any.whl

# 3. Publish to TestPyPI first
poetry config repositories.testpypi https://test.pypi.org/legacy/
poetry publish -r testpypi

# 4. Test installation
pip install --index-url https://test.pypi.org/simple/ my-awesome-package

# 5. Publish to PyPI
poetry publish

# 6. Create git tag
git tag v0.1.0
git push origin v0.1.0

4. Advanced Features

• Monorepo management
• Plugin systems
• Custom build scripts
• Private package repositories
• CI/CD integration
• Dependency groups

Code Example:

# Advanced pyproject.toml configuration

[tool.poetry]
name = "advanced-package"
version = "1.0.0"
description = "Advanced packaging example"

# Include/exclude files
include = ["my_package/data/*.json"]
exclude = ["my_package/tests/*"]

[tool.poetry.dependencies]
python = "^3.9"

# Optional dependencies (extras)
psycopg2 = { version = "^2.9", optional = true }
mysqlclient = { version = "^2.1", optional = true }

[tool.poetry.extras]
postgresql = ["psycopg2"]
mysql = ["mysqlclient"]
all = ["psycopg2", "mysqlclient"]

# Multiple dependency groups
[tool.poetry.group.test.dependencies]
pytest = "^7.0.0"
pytest-cov = "^4.0.0"

[tool.poetry.group.docs.dependencies]
sphinx = "^5.0.0"
sphinx-rtd-theme = "^1.0.0"

[tool.poetry.group.lint.dependencies]
black = "^23.0.0"
ruff = "^0.1.0"
mypy = "^1.0.0"

# Platform-specific dependencies
[tool.poetry.dependencies.pywin32]
version = "^305"
platform = "win32"

# Plugins
[tool.poetry.plugins."my_package.plugins"]
plugin1 = "my_package.plugins:plugin1"

# CI/CD with GitHub Actions
# .github/workflows/publish.yml
name: Publish to PyPI

on:
  release:
    types: [published]

jobs:
  publish:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Set up Python
        uses: actions/setup-python@v4
        with:
          python-version: '3.11'
      - name: Install Poetry
        run: curl -sSL https://install.python-poetry.org | python3 -
      - name: Build and publish
        env:
          POETRY_PYPI_TOKEN_PYPI: ${{ secrets.PYPI_TOKEN }}
        run: |
          poetry build
          poetry publish

Hands-On Practice

Project 1: CLI Tool Package

Create a command-line tool and publish to PyPI.

Requirements:

• Build CLI with Click/Typer
• Add multiple subcommands
• Include configuration file support
• Write comprehensive tests
• Generate documentation
• Publish to PyPI

Key Skills: Poetry, CLI development, packaging

Project 2: Library Package

Develop a reusable library with clean API.

Requirements:

• Design public API
• Type hints throughout
• Comprehensive docstrings
• Unit and integration tests
• API documentation
• Versioning strategy

Key Skills: API design, documentation, testing

Project 3: Plugin System

Create package with plugin architecture.

Requirements:

• Plugin discovery mechanism
• Entry points configuration
• Plugin API specification
• Example plugins
• Plugin documentation
• Distribution strategy

Key Skills: Advanced packaging, architecture

Assessment Criteria

• Create projects with Poetry
• Manage dependencies effectively
• Understand version constraints
• Build and publish packages
• Structure projects professionally
• Write clear package metadata
• Implement semantic versioning

Resources

Official Documentation

• Poetry Docs - Official documentation
• PyPI - Python Package Index
• Packaging Guide - Python packaging authority

Learning Platforms

• Python Packaging - Real Python guide
• Modern Python Packaging - Video tutorial
• Poetry Tutorial - Comprehensive guide

Tools

• Poetry - Dependency management
• Twine - PyPI upload tool
• bump2version - Version bumping
• setuptools - Alternative packaging

Next Steps

After mastering Poetry, explore:

• Docker - Containerized packaging
• GitHub Actions - Automated publishing
• Read the Docs - Documentation hosting
• Pre-commit - Code quality automation