Mivek Python Metar Taf Parser Python Metar Taf Parser

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

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

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

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

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

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

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.

Source: mivek/python-metar-taf-parser — distributed by TomeVault.