python-pypi-package-builder

python-pypi-package-builder

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 cha

...