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python-build

README.md

Python Build Workflows

Sammlung von GitHub Actions Workflows für Python-Projekte aller Art.

🚀 Schnellstart

  1. Workflow kopieren - Wählen Sie den passenden Workflow für Ihr Projekt
  2. Konfiguration anpassen - Nutzen Sie die entsprechende Config-Datei aus .github/config/python-build/
  3. Secrets einrichten - Konfigurieren Sie die benötigten Repository-Secrets
  4. Workflow aktivieren - Committen Sie die Datei nach .github/workflows/

📁 Verfügbare Workflows

Basic Workflows

Workflow Beschreibung Verwendung
python-app.yml Einfache Python-Anwendung Web-Apps, Scripts, CLI-Tools
python-package.yml Python-Paket für PyPI Libraries, Frameworks
python-publish.yml PyPI Publishing Automatische Releases
python-docker.yml Docker Build & Deploy Containerisierte Apps

Beispiel-Workflows

Workflow Framework Features
python-fastapi-example.yml FastAPI PostgreSQL, Redis, API-Tests
python-django-example.yml Django Migrations, Static Files, Frontend
python-ml-example.yml Scikit-learn/ML Model Training, Validation, Deployment

⚙️ Konfigurationen

Alle Konfigurationsdateien befinden sich in .github/config/python-build/:

  • default.yml - Standard-Konfiguration für einfache Projekte
  • web-app.yml - Web-Anwendungen (Flask, Django, FastAPI)
  • package.yml - PyPI-Pakete mit Multi-Platform Testing
  • data-science.yml - Data Science und ML-Projekte
  • microservice.yml - Microservices mit Kubernetes

🛠️ Setup-Anleitung

1. Basic Python Application

# .github/workflows/ci.yml
name: CI

on:
  push:
    branches: [ main ]
  pull_request:

jobs:
  test:
    runs-on: ubuntu-latest
    steps:
    - uses: actions/checkout@v4
    - uses: actions/setup-python@v5
      with:
        python-version: "3.12"
        cache: 'pip'
    - name: Install dependencies
      run: |
        pip install -r requirements.txt
        pip install pytest pytest-cov
    - name: Run tests
      run: pytest --cov=. --cov-report=xml

2. FastAPI with Database

# Kopiere python-fastapi-example.yml
# Anpassungen:
services:
  postgres:
    image: postgres:15
    env:
      POSTGRES_DB: your_db_name
      POSTGRES_USER: your_user
      POSTGRES_PASSWORD: your_password

3. Package Publishing

# Kopiere python-publish.yml
# Erforderliche Secrets:
# - PYPI_API_TOKEN (für PyPI)
# - TEST_PYPI_API_TOKEN (für TestPyPI)

🔧 Erforderliche Dateien

Minimal Setup

your-project/
├── .github/
│   └── workflows/
│       └── ci.yml
├── src/
│   └── your_package/
├── tests/
├── requirements.txt
├── requirements-dev.txt
├── setup.py oder pyproject.toml
└── README.md

requirements.txt

# Produktions-Dependencies
requests>=2.28.0
click>=8.0.0

requirements-dev.txt

# Entwicklungs-Dependencies
pytest>=7.0.0
pytest-cov>=4.0.0
black>=22.0.0
flake8>=5.0.0
mypy>=0.991

pyproject.toml

[build-system]
requires = ["setuptools>=61.0", "wheel"]
build-backend = "setuptools.build_meta"

[project]
name = "your-package"
version = "0.1.0"
description = "Your package description"
authors = [{name = "Your Name", email = "your.email@example.com"}]
license = {text = "MIT"}

🔐 Repository Secrets

Je nach Workflow benötigen Sie verschiedene Secrets:

Basis Secrets

GITHUB_TOKEN          # Automatisch verfügbar

PyPI Publishing

PYPI_API_TOKEN        # PyPI API Token
TEST_PYPI_API_TOKEN   # TestPyPI API Token

Docker Registry

DOCKER_USERNAME       # Docker Hub Username
DOCKER_PASSWORD       # Docker Hub Token

Cloud Deployment

AWS_ACCESS_KEY_ID     # AWS Credentials
AWS_SECRET_ACCESS_KEY
AZURE_CLIENT_ID       # Azure Credentials
AZURE_CLIENT_SECRET

📊 Unterstützte Features

Testing & Quality

  • ✅ pytest mit Coverage
  • ✅ flake8 Linting
  • ✅ Black Code Formatting
  • ✅ isort Import Sorting
  • ✅ mypy Type Checking
  • ✅ bandit Security Scanning
  • ✅ safety Dependency Scanning

Builds & Deployment

  • ✅ Multi-Platform Testing (Linux, Windows, macOS)
  • ✅ Multiple Python Versions (3.9-3.12)
  • ✅ Docker Multi-Platform Builds
  • ✅ PyPI/TestPyPI Publishing
  • ✅ GitHub Container Registry
  • ✅ Kubernetes Deployment

Integrations

  • ✅ Codecov Coverage Reports
  • ✅ GitHub Security Advisories
  • ✅ Dependabot Integration
  • ✅ Artifact Uploads
  • ✅ Test Result Publishing

🚀 Erweiterte Beispiele

ML-Pipeline mit DVC

- name: Setup DVC
  run: |
    pip install dvc[s3]
    dvc pull

- name: Train Model
  run: |
    python train.py
    dvc add models/model.pkl

Multi-Environment Deployment

deploy-staging:
  if: github.ref == 'refs/heads/develop'
  environment:
    name: staging
    url: https://staging.example.com

deploy-production:
  if: github.ref == 'refs/heads/main'
  environment:
    name: production
    url: https://example.com

Matrix Testing mit Services

strategy:
  matrix:
    python-version: ["3.10", "3.11", "3.12"]
    database: ["postgresql", "mysql"]

services:
  db:
    image: ${{ matrix.database == 'postgresql' && 'postgres:15' || 'mysql:8' }}

🐛 Troubleshooting

Häufige Probleme

Import Error bei Tests

# Lösung: Package installieren
pip install -e .

Coverage zu niedrig

# Lösung: Coverage-Konfiguration anpassen
pytest --cov=src --cov-fail-under=80

Docker Build langsam

# Lösung: Multi-stage Build verwenden
FROM python:3.12-slim as builder
COPY requirements.txt .
RUN pip install --user -r requirements.txt

FROM python:3.12-slim
COPY --from=builder /root/.local /root/.local

Flake8 Fehler

# setup.cfg
[flake8]
max-line-length = 88
extend-ignore = E203, W503
exclude = venv/, build/, dist/

📚 Zusätzliche Ressourcen

🤝 Contributing

Beiträge sind willkommen! Bitte:

  1. Fork das Repository
  2. Erstelle einen Feature Branch
  3. Teste deine Änderungen
  4. Erstelle eine Pull Request

📄 Lizenz

MIT License - siehe LICENSE für Details.