python-packaging skill
Create distributable Python packages with proper project structure, setup.py/pyproject.toml, and publishing to PyPI. Use when packaging Python libraries, creating CLI tools, or distributing Python code.
Is the python-packaging skill safe?
Read the findings before you install it. We read 3 files in the folder on 2026-09-28.
- high
references/details.md:296Reads credential files (SSH keys, cloud or package-manager tokens) that a skill has no normal reason to touch.
# Create ~/.pypirc
Install the python-packaging skill
A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description.
git clone --depth 1 https://github.com/wshobson/agents.git /tmp/agents mkdir -p ~/.claude/skills cp -r /tmp/agents/plugins/python-development/skills/python-packaging ~/.claude/skills/python-packaging
In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub
The instructions your agent would load
SKILL.md as published, without the frontmatter. Read it on GitHub
Python Packaging
Comprehensive guide to creating, structuring, and distributing Python packages using modern packaging tools, pyproject.toml, and publishing to PyPI.
When to Use This Skill
- Creating Python libraries for distribution
- Building command-line tools with entry points
- Publishing packages to PyPI or private repositories
- Setting up Python project structure
- Creating installable packages with dependencies
- Building wheels and source distributions
- Versioning and releasing Python packages
- Creating namespace packages
- Implementing package metadata and classifiers
Core Concepts
1. Package Structure
- Source layout: src/package_name/ (recommended)
- Flat layout: package_name/ (simpler but less flexible)
- Package metadata: pyproject.toml, setup.py, or setup.cfg
- Distribution formats: wheel (.whl) and source distribution (.tar.gz)
2. Modern Packaging Standards
- PEP 517/518: Build system requirements
- PEP 621: Metadata in pyproject.toml
- PEP 660: Editable installs
- pyproject.toml: Single source of configuration
3. Build Backends
- setuptools: Traditional, widely used
- hatchling: Modern, opinionated
- flit: Lightweight, for pure Python
- poetry: Dependency management + packaging
4. Distribution
- PyPI: Python Package Index (public)
- TestPyPI: Testing before production
- Private repositories: JFrog, AWS CodeArtifact, etc.
Quick Start
Minimal Package Structure
my-package/
├── pyproject.toml
├── README.md
├── LICENSE
├── src/
│ └── my_package/
│ ├── __init__.py
│ └── module.py
└── tests/
└── test_module.pyMinimal pyproject.toml
[build-system]
requires = ["setuptools>=61.0"]
build-backend = "setuptools.build_meta"
[project]
name = "my-package"
version = "0.1.0"
description = "A short description"
authors = [{name = "Your Name", email = "you@example.com"}]
readme = "README.md"
requires-python = ">=3.8"
dependencies = [
"requests>=2.28.0",
]
[project.optional-dependencies]
dev = [
"pytest>=7.0",
"black>=22.0",
]Package Structure Patterns
Pattern 1: Source Layout (Recommended)
my-package/
├── pyproject.toml
├── README.md
├── LICENSE
├── .gitignore
├── src/
│ └── my_package/
│ ├── __init__.py
│ ├── core.py
│ ├── utils.py
│ └── py.typed # For type hints
├── tests/
│ ├── __init__.py
│ ├── test_core.py
│ └── test_utils.py
└── docs/
└── index.mdAdvantages:
- Prevents accidentally importing from source
- Cleaner test imports
- Better isolation
pyproject.toml for source layout:
[tool.setuptools.packages.find]
where = ["src"]Pattern 2: Flat Layout
my-package/
├── pyproject.toml
├── README.md
├── my_package/
│ ├── __init__.py
│ └── module.py
└── tests/
└── test_module.pySimpler but:
- Can import package without installing
- Less professional for libraries
Pattern 3: Multi-Package Project
project/
├── pyproject.toml
├── packages/
│ ├── package-a/
│ │ └── src/
│ │ └── package_a/
│ └── package-b/
│ └── src/
│ └── package_b/
└── tests/Detailed patterns and worked examples
Detailed pattern documentation lives in references/details.md. Read that file when the navigation tier above is insufficient.
More skills from wshobson/agents
- Aairflow-dag-patternsBuild production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.
- Aangular-migrationMigrate from AngularJS to Angular using hybrid mode, incremental component rewriting, and dependency injection updates. Use when upgrading AngularJS applications, planning framework migrations, or modernizing legacy Angular code.
- Aanti-reversing-techniquesUnderstand anti-reversing, obfuscation, and protection techniques encountered during software analysis. Use this skill when analyzing malware evasion techniques, when implementing anti-debugging protections for CTF challenges, when reverse engineering packed binaries, or when building security research tools that need to detect virtualized environments.
- Aapi-design-principlesMaster REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers. Use when designing new APIs, reviewing API specifications, or establishing API design standards.
- Aarchitecture-decision-recordsWrite and maintain Architecture Decision Records (ADRs) following best practices for technical decision documentation. Use when documenting significant technical decisions, reviewing past architectural choices, or establishing decision processes.
- Aarchitecture-patternsImplement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design. Use this skill when designing clean architecture for a new microservice, when refactoring a monolith to use bounded contexts, when implementing hexagonal or onion architecture patterns, or when debugging dependency cycles between application layers.
- Aasync-python-patternsMaster Python asyncio, concurrent programming, and async/await patterns for high-performance applications. Use when building async APIs, concurrent systems, or I/O-bound applications requiring non-blocking operations.
- Aauth-implementation-patternsMaster authentication and authorization patterns including JWT, OAuth2, session management, and RBAC to build secure, scalable access control systems. Use when implementing auth systems, securing APIs, or debugging security issues.
- Aavoid-ai-writingAudit and rewrite prose so it stops reading as machine-generated. Use this skill when asked to remove AI-isms, clean up AI writing, edit a draft for AI tells, audit a README, changelog, release note, PR description, or blog post for machine-sounding prose, or make text sound less like AI. Supports a detect-only mode, a rewrite mode, and an edit-in-place mode, with optional voice and context profiles.
- Abacktesting-frameworksBuild robust backtesting systems for trading strategies with proper handling of look-ahead bias, survivorship bias, and transaction costs. Use when developing trading algorithms, validating strategies, or building backtesting infrastructure.
- Abazel-build-optimizationOptimize Bazel builds for large-scale monorepos. Use when configuring Bazel, implementing remote execution, or optimizing build performance for enterprise codebases.
- Abefore-you-buildPre-build product and feature risk review for founders, product managers, and AI-assisted builders. Use this skill when the user is about to build a landing page, MVP, SaaS product, internal tool, agent workflow, or major feature and needs to check demand, positioning, monetization, retention, trust, distribution, and adoption risk before implementation starts.