python-pypi-package-builder

name	python-pypi-package-builder
description	End-to-end skill for building, testing, linting, versioning, and publishing a production-grade Python library to PyPI. Covers all four build backends (setuptools+setuptools_scm, hatchling, flit, poetry), PEP 440 versioning, semantic versioning, dynamic git-tag versioning, OOP/SOLID design, type hints (PEP 484/526/544/561), Trusted Publishing (OIDC), and the full PyPA packaging flow. Use for: creating Python packages, pip-installable SDKs, CLI tools, framework plugins, pyproject.toml setup, py.typed, setuptools_scm, semver, mypy, pre-commit, GitHub Actions CI/CD, or PyPI publishing.
metadata	{"skill-author":"Marie-Lynne Block"}

Python 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:

1. Set up pyproject.toml → references/pyproject-toml.md All four backend templates (setuptools+scm, hatchling, flit, poetry), full tool configs, py.typed setup, versioning config.

2. Write your library code → references/library-patterns.md OOP/SOLID principles, type hints (PEP 484/526/544/561), core class design, factory functions, __init__.py, plugin/backend pattern, CLI entry point.

3. Add tests and code quality → references/testing-quality.md conftest.py, unit/backend/async tests, parametrize, ruff/mypy/pre-commit setup.

4. Set up CI/CD and publish → references/ci-publishing.md ci.yml, publish.yml with Trusted Publishing (OIDC, no API tokens), CHANGELOG format, release checklist.

5. Polish for community/OSS → references/community-docs.md README sections, docstring format, CONTRIBUTING, SECURITY, issue templates, anti-patterns table, and master release checklist.

6. Design backends, config, transport, CLI → references/architecture-patterns.md Backend system (plugin/strategy pattern), Settings dataclass, HTTP transport layer, CLI with click/typer, backend injection rules.

7. Choose and implement a versioning strategy → references/versioning-strategy.md PEP 440 canonical forms, SemVer rules, pre-release identifiers, setuptools_scm deep-dive, flit static versioning, decision engine (DEFAULT/BEGINNER/MINIMAL).

8. Govern releases and secure the publish pipeline → references/release-governance.md Branch strategy, branch protection rules, OIDC Trusted Publishing setup, tag author validation in CI, tag format enforcement, full governed publish.yml.

9. Simplify tooling with Ruff → references/tooling-ruff.md Ruff-only setup replacing black/isort/flake8, mypy config, pre-commit hooks, asyncio_mode=auto (remove @pytest.mark.asyncio), migration guide.