
Python PyPI Package Builder
OfficialFreeStreamline the process of creating and publishing Python packages.
Free · Opens the source repo
What Python PyPI Package Builder does
The Python PyPI Package Builder skill is designed for developers looking to create, test, and publish Python libraries to the Python Package Index (PyPI) efficiently. This skill provides a comprehensive guide that covers everything from the initial project setup to the final release, ensuring that your package adheres to modern Python packaging standards. It supports various build backends, including setuptools, hatchling, flit, and poetry, allowing you to choose the best fit for your project requirements.
This skill emphasizes the importance of following a structured approach to package development. It includes decision trees for package type, folder structure, and build backend selection, which help you make informed choices based on your project's complexity and goals. The skill also covers essential topics such as versioning strategies (PEP 440 and semantic versioning), type hints, and OOP/SOLID design principles, ensuring that your library is not only functional but also maintainable and scalable.
Additionally, the skill provides scripts for scaffolding your project, generating a complete directory layout and necessary files with a single command. It includes references to best practices for testing, CI/CD with GitHub Actions, and community documentation, making it a valuable resource for both new and experienced developers. By following the guidelines provided, you can confidently create a production-grade Python package that meets the expectations of the Python community.
Whether you're building a simple utility library or a complex SDK, this skill equips you with the knowledge and tools needed to navigate the Python packaging landscape effectively.
When to use it
Use this skill when you need to create or publish a Python package, set up CI/CD pipelines, or understand modern Python packaging practices.
When not to use it
This skill may not be suitable for projects that do not require packaging for distribution or for developers who prefer a more manual approach to package management.
What you can build with it
Creating a New Python Library
Use this skill to guide you through the entire process of setting up and publishing a new Python library to PyPI.
Setting Up CI/CD for Python Packages
Integrate CI/CD pipelines into your Python project using the provided GitHub Actions templates for automated testing and publishing.
Migrating an Existing Package to Modern Standards
Refactor your existing Python package to comply with modern packaging standards and best practices outlined in this skill.
How to install Python PyPI Package Builder
View source1. Install with the skills CLI
npx skills add github/awesome-copilot/python-pypi-package-builder --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by githubPython PyPI Package Builder Skill
A complete, battle-tested guide for building, testing, linting, versioning, typing, and publishing a production-grade Python library to PyPI — from first commit to community-ready release.
AI Agent Instruction: Read this entire file before writing a single line of code or creating any file. Every decision — layout, backend, versioning strategy, patterns, CI — has a decision rule here. Follow the decision trees in order. This skill applies to any Python package type (utility, SDK, CLI, plugin, data library). Do not skip sections.
Quick Navigation
| Section in this file | What it covers |
|---|---|
| 1. Skill Trigger | When to load this skill |
| 2. Package Type Decision | Identify what you are building |
| 3. Folder Structure Decision | src/ vs flat vs monorepo |
| 4. Build Backend Decision | setuptools / hatchling / flit / poetry |
| 5. PyPA Packaging Flow | The canonical publish pipeline |
| 6. Project Structure Templates | Full layouts for every option |
| 7. Versioning Strategy | PEP 440, semver, dynamic vs static |
| Reference file | What it covers |
|---|---|
references/pyproject-toml.md | All four backend templates, setuptools_scm, py.typed, tool configs |
references/library-patterns.md | OOP/SOLID, type hints, core class design, factory, protocols, CLI |
references/testing-quality.md | conftest.py, unit/backend/async tests, ruff/mypy/pre-commit |
references/ci-publishing.md | ci.yml, publish.yml, Trusted Publishing, TestPyPI, CHANGELOG, release checklist |
references/community-docs.md | README, docstrings, CONTRIBUTING, SECURITY, anti-patterns, master checklist |
references/architecture-patterns.md | Backend system (plugin/strategy), config layer, transport layer, CLI, backend injection |
references/versioning-strategy.md | PEP 440, SemVer, pre-release, setuptools_scm deep-dive, flit static, decision engine |
references/release-governance.md | Branch strategy, branch protection, OIDC, tag author validation, prevent invalid tags |
references/tooling-ruff.md | Ruff-only setup (replaces black/isort), mypy config, pre-commit, asyncio_mode=auto |
Scaffold script: run python skills/python-pypi-package-builder/scripts/scaffold.py --name your-package-name
to generate the entire directory layout, stub files, and pyproject.toml in one command.
1. Skill Trigger
Load this skill whenever the user wants to:
- Create, scaffold, or publish a Python package or library to PyPI
- Build a pip-installable SDK, utility, CLI tool, or framework extension
- Set up
pyproject.toml, linting, mypy, pre-commit, or GitHub Actions for a Python project - Understand versioning (
setuptools_scm, PEP 440, semver, static versioning) - Understand PyPA specs:
py.typed,MANIFEST.in,RECORD, classifiers - Publish to PyPI using Trusted Publishing (OIDC) or API tokens
- Refactor an existing package to follow modern Python packaging standards
- Add type hints, protocols, ABCs, or dataclasses to a Python library
- Apply OOP/SOLID design patterns to a Python package
- Choose between build backends (setuptools, hatchling, flit, poetry)
Also trigger for phrases like: "build a Python SDK", "publish my library", "set up PyPI CI", "create a pip package", "how do I publish to PyPI", "pyproject.toml help", "PEP 561 typed", "setuptools_scm version", "semver Python", "PEP 440", "git tag release", "Trusted Publishing".
2. Package Type Decision
Identify what the user is building before writing any code. Each type has distinct patterns.
Decision Table
| Type | Core Pattern | Entry Point | Key Deps | Example Packages |
|---|---|---|---|---|
| Utility library | Module of pure functions + helpers | Import API only | Minimal | arrow, humanize, boltons, more-itertools |
| API client / SDK | Class with methods, auth, retry logic | Import API only | httpx or requests | boto3, stripe-python, openai |
| CLI tool | Command functions + argument parser | [project.scripts] or [project.entry-points] | click or typer | black, ruff, httpie, rich |
| Framework plugin | Plugin class, hook registration | [project.entry-points."framework.plugin"] | Framework dep | pytest-*, django-*, flask-* |
| Data processing library | Classes + functional pipeline | Import API only | Optional: numpy, pandas | pydantic, marshmallow, cerberus |
| Mixed / generic | Combination of above | Varies | Varies | Many real-world packages |
Decision Rule: Ask the user if unclear. A package can combine types (e.g., SDK with a CLI entry point) — use the primary type for structural decisions and add secondary type patterns on top.
For implementation patterns of each type, see references/library-patterns.md.
Package Naming Rules
- PyPI name: all lowercase, hyphens —
my-python-library - Python import name: underscores —
my_python_library - Check availability: https://pypi.org/search/ before starting
- Avoid shadowing popular packages (verify
pip install <name>fails first)
3. Folder Structure Decision
Decision Tree
Does the package have 5+ internal modules OR multiple contributors OR complex sub-packages?
├── YES → Use src/ layout
│ Reason: prevents accidental import of uninstalled code during development;
│ separates source from project root files; PyPA-recommended for large projects.
│
├── NO → Is it a single-module, focused package (e.g., one file + helpers)?
│ ├── YES → Use flat layout
│ └── NO (medium complexity) → Use flat layout, migrate to src/ if it grows
│
└── Is it multiple related packages under one namespace (e.g., myorg.http, myorg.db)?
└── YES → Use namespace/monorepo layout
Quick Rule Summary
| Situation | Use |
|---|---|
| New project, unknown future size | src/ layout (safest default) |
| Single-purpose, 1–4 modules | Flat layout |
| Large library, many contributors | src/ layout |
| Multiple packages in one repo | Namespace / monorepo |
| Migrating old flat project | Keep flat; migrate to src/ at next major version |
4. Build Backend Decision
Decision Tree
Does the user need version derived automatically from git tags?
├── YES → Use setuptools + setuptools_scm
│ (git tag v1.0.0 → that IS your release workflow)
│
└── NO → Does the user want an all-in-one tool (deps + build + publish)?
├── YES → Use poetry (v2+ supports standard [project] table)
│
└── NO → Is the package pure Python with no C extensions?
├── YES, minimal config preferred → Use flit
│ (zero config, auto-discovers version from __version__)
│
└── YES, modern & fast preferred → Use hatchling
(zero-config, plugin system, no setup.py needed)
Does the package have C/Cython/Fortran extensions?
└── YES → MUST use setuptools (only backend with full native extension support)
Backend Comparison
| Backend | Version source | Config | C extensions | Best for |
|---|---|---|---|---|
setuptools + setuptools_scm | git tags (automatic) | pyproject.toml + optional setup.py shim | Yes | Projects with git-tag releases; any complexity |
hatchling | manual or plugin | pyproject.toml only | No | New pure-Python projects; fast, modern |
flit | __version__ in __init__.py | pyproject.toml only | No | Very simple, single-module packages |
poetry | pyproject.toml field | pyproject.toml only | No | Teams wanting integrated dep management |
For all four complete pyproject.toml templates, see references/pyproject-toml.md.
5. PyPA Packaging Flow
This is the canonical end-to-end flow from source code to user install. Every step must be understood before publishing.
1. SOURCE TREE
Your code in version control (git)
└── pyproject.toml describes metadata + build system
2. BUILD
python -m build
└── Produces two artifacts in dist/:
├── *.tar.gz → source distribution (sdist)
└── *.whl → built distribution (wheel) — preferred by pip
3. VALIDATE
twine check dist/*
└── Checks metadata, README rendering, and PyPI compatibility
4. TEST PUBLISH (first release only)
twine upload --repository testpypi dist/*
└── Verify: pip install --index-url https://test.pypi.org/simple/ your-package
5. PUBLISH
twine upload dist/* ← manual fallback
OR GitHub Actions publish.yml ← recommended (Trusted Publishing / OIDC)
6. USER INSTALL
pip install your-package
pip install "your-package[extra]"
Key PyPA Concepts
| Concept | What it means |
|---|---|
| sdist | Source distribution — your source + metadata; used when no wheel is available |
| wheel (.whl) | Pre-built binary — pip extracts directly into site-packages; no build step |
| PEP 517/518 | Standard build system interface via pyproject.toml [build-system] table |
| PEP 621 | Standard [project] table in pyproject.toml; all modern backends support it |
| PEP 639 | license key as SPDX string (e.g., "MIT", "Apache-2.0") — not {text = "MIT"} |
| PEP 561 | py.typed empty marker file — tells mypy/IDEs this package ships type information |
For complete CI workflow and publishing setup, see references/ci-publishing.md.
6. Project Structure Templates
A. src/ Layout (Recommended default for new projects)
your-package/
├── src/
│ └── your_package/
│ ├── __init__.py # Public API: __all__, __version__
│ ├── py.typed # PEP 561 marker — EMPTY FILE
│ ├── core.py # Primary implementation
│ ├── client.py # (API client type) or remove
│ ├── cli.py # (CLI type) click/typer commands, or remove
│ ├── config.py # Settings / configuration dataclass
│ ├── exceptions.py # Custom exception hierarchy
│ ├── models.py # Data classes, Pydantic models, TypedDicts
│ ├── utils.py # Internal helpers (prefix _utils if private)
│ ├── types.py # Shared type aliases and TypeVars
│ └── backends/ # (Plugin pattern) — remove if not needed
│ ├── __init__.py # Protocol / ABC interface definition
│ ├── memory.py # Default zero-dep implementation
│ └── redis.py # Optional heavy implementation
├── tests/
│ ├── __init__.py
│ ├── conftest.py # Shared fixtures
│ ├── unit/
│ │ ├── __init__.py
│ │ ├── test_core.py
│ │ ├── test_config.py
│ │ └── test_models.py
│ ├── integration/
│ │ ├── __init__.py
│ │ └── test_backends.py
│ └── e2e/ # Optional: end-to-end tests
│ └── __init__.py
├── docs/ # Optional: mkdocs or sphinx
├── scripts/
│ └── scaffold.py
├── .github/
│ ├── workflows/
│ │ ├── ci.yml
│ │ └── publish.yml
│ └── ISSUE_TEMPLATE/
│ ├── bug_report.md
│ └── feature_request.md
├── .pre-commit-config.yaml
├── pyproject.toml
├── CHANGELOG.md
├── CONTRIBUTING.md
├── SECURITY.md
├── LICENSE
├── README.md
└── .gitignore
B. Flat Layout (Small / focused packages)
your-package/
├── your_package/ # ← at root, not inside src/
│ ├── __init__.py
│ ├── py.typed
│ └── ... (same internal structure)
├── tests/
└── ... (same top-level files)
C. Namespace / Monorepo Layout (Multiple related packages)
your-org/
├── packages/
│ ├── your-org-core/
│ │ ├── src/your_org/core/
│ │ └── pyproject.toml
│ ├── your-org-http/
│ │ ├── src/your_org/http/
│ │ └── pyproject.toml
│ └── your-org-cli/
│ ├── src/your_org/cli/
│ └── pyproject.toml
├── .github/workflows/
└── README.md
Each sub-package has its own pyproject.toml. They share the your_org namespace via PEP 420
implicit namespace packages (no __init__.py in the namespace root).
Internal Module Guidelines
| File | Purpose | When to include |
|---|---|---|
__init__.py | Public API surface; re-exports; __version__ | Always |
py.typed | PEP 561 typed-package marker (empty) | Always |
core.py | Primary class / main logic | Always |
config.py | Settings dataclass or Pydantic model | When configurable |
exceptions.py | Exception hierarchy (YourBaseError → specifics) | Always |
models.py | Data models / DTOs / TypedDicts | When data-heavy |
utils.py | Internal helpers (not part of public API) | As needed |
types.py | Shared TypeVar, TypeAlias, Protocol definitions | When complex typing |
cli.py | CLI entry points (click/typer) | CLI type only |
backends/ | Plugin/strategy pattern | When swappable implementations |
_compat.py | Python version compatibility shims | When 3.9–3.13 compat needed |
7. Versioning Strategy
PEP 440 — The Standard
Canonical form: N[.N]+[{a|b|rc}N][.postN][.devN]
Examples:
1.0.0 Stable release
1.0.0a1 Alpha (pre-release)
1.0.0b2 Beta
1.0.0rc1 Release candidate
1.0.0.post1 Post-release (e.g., packaging fix only)
1.0.0.dev1 Development snapshot (not for PyPI)
Semantic Versioning (recommended)
MAJOR.MINOR.PATCH
MAJOR: Breaking API change (remove/rename public function/class/arg)
MINOR: New feature, fully backward-compatible
PATCH: Bug fix, no API change
Dynamic versioning with setuptools_scm (recommended for git-tag workflows)
# How it works:
git tag v1.0.0 → installed version = 1.0.0
git tag v1.1.0 → installed version = 1.1.0
(commits after tag) → version = 1.1.0.post1 (suffix stripped for PyPI)
# In code — NEVER hardcode when using setuptools_scm:
from importlib.metadata import version, PackageNotFoundError
try:
__version__ = version("your-package")
except PackageNotFoundError:
__version__ = "0.0.0-dev" # Fallback for uninstalled dev checkouts
Required pyproject.toml config:
[tool.setuptools_scm]
version_scheme = "post-release"
local_scheme = "no-local-version" # Prevents +g<hash> from breaking PyPI uploads
Critical: always set fetch-depth: 0 in every CI checkout step. Without full git history,
setuptools_scm cannot find tags and the build version silently falls back to 0.0.0+dev.
Static versioning (flit, hatchling manual, poetry)
# your_package/__init__.py
__version__ = "1.0.0" # Update this before every release
Version specifier best practices for dependencies
# In [project] dependencies:
"httpx>=0.24" # Minimum version — PREFERRED for libraries
"httpx>=0.24,<1.0" # Upper bound only when a known breaking change exists
"httpx==0.27.0" # Pin exactly ONLY in applications, NOT libraries
# NEVER do this in a library — it breaks dependency resolution for users:
# "httpx~=0.24.0" # Too tight
# "httpx==0.27.*" # Fragile
Version bump → release flow
# 1. Update CHANGELOG.md — move [Unreleased] entries to [x.y.z] - YYYY-MM-DD
# 2. Commit the changelog
git add CHANGELOG.md
git commit -m "chore: prepare release vX.Y.Z"
# 3. Tag and push — this triggers publish.yml automatically
git tag vX.Y.Z
git push origin main --tags
# 4. Monitor GitHub Actions → verify on https://pypi.org/project/your-package/
For complete pyproject.toml templates for all four backends, see references/pyproject-toml.md.
Where to Go Next
After understanding decisions and structure:
-
Set up
pyproject.toml→references/pyproject-toml.mdAll four backend templates (setuptools+scm, hatchling, flit, poetry), full tool configs,py.typedsetup, versioning config. -
Write your library code →
references/library-patterns.mdOOP/SOLID principles, type hints (PEP 484/526/544/561), core class design, factory functions,__init__.py, plugin/backend pattern, CLI entry point. -
Add tests and code quality →
references/testing-quality.mdconftest.py, unit/backend/async tests, parametrize, ruff/mypy/pre-commit setup. -
Set up CI/CD and publish →
references/ci-publishing.mdci.yml,publish.ymlwith Trusted Publishing (OIDC, no API tokens), CHANGELOG format, release checklist. -
Polish for community/OSS →
references/community-docs.mdREADME sections, docstring format, CONTRIBUTING, SECURITY, issue templates, anti-patterns table, and master release checklist. -
Design backends, config, transport, CLI →
references/architecture-patterns.mdBackend system (plugin/strategy pattern), Settings dataclass, HTTP transport layer, CLI with click/typer, backend injection rules. -
Choose and implement a versioning strategy →
references/versioning-strategy.mdPEP 440 canonical forms, SemVer rules, pre-release identifiers, setuptools_scm deep-dive, flit static versioning, decision engine (DEFAULT/BEGINNER/MINIMAL). -
Govern releases and secure the publish pipeline →
references/release-governance.mdBranch strategy, branch protection rules, OIDC Trusted Publishing setup, tag author validation in CI, tag format enforcement, full governedpublish.yml. -
Simplify tooling with Ruff →
references/tooling-ruff.mdRuff-only setup replacing black/isort/flake8, mypy config, pre-commit hooks, asyncio_mode=auto (remove @pytest.mark.asyncio), migration guide.
Frequently asked questions about Python PyPI Package Builder
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