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fix: reorganize service layer and move data loading logic to separate module
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‎README.md‎

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# python-app-template
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python-app-template
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# Python App Template
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A modern, modular Python application template with robust CI/CD, best practices, and synthwave terminal UI. This project demonstrates clean architecture, packaging, and workflow automation for professional Python development.
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## Features
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- **Modular Structure**: src layout, clear separation of core, UI, models, and tests
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- **Synthwave Terminal UI**: Rich + pyfiglet for beautiful astronomical data display
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- **Robust CI/CD**: GitHub Actions for linting, testing, Docker multi-arch builds, Trivy scanning, and releases
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- **Best Practices**: Type hints, logging, config management, reusable workflows, DRY code
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- **Packaging**: pyproject.toml, src layout, testable modules, versioned releases
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## Architecture
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```
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python-app-template/
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├── src/sample_python_app/
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│ ├── core/ # Core logic: config, logging, display (thin wrappers)
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│ ├── models/ # Data models (Pydantic)
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│ ├── ui/ # Terminal UI (synthwave)
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│ ├── data_loader/ # Data loader module (API logic)
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│ ├── services/ # Service layer (business logic, imports data loader)
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│ └── main.py # Entry point
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├── tests/ # Unit tests
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├── data/ # Sample data
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├── Dockerfile # Containerization
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├── pyproject.toml # Packaging
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├── .github/workflows # CI/CD workflows
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```
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## Frameworks & Libraries
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- **rich**: Terminal formatting and color
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- **pyfiglet**: ASCII art for synthwave look
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- **pydantic**: Data validation and settings
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- **httpx**: HTTP requests
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- **pytest**: Testing
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- **ruff, black, isort**: Linting and formatting
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## CI/CD & Workflows
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- **cache-uv-build.yaml**: Caches Python dependencies for fast builds
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- **ruff.yaml**: Lints code for style and quality
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- **pytest.yaml**: Runs unit tests
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- **docker-build-and-scan.yaml**: Multi-arch Docker builds, Trivy vulnerability scan
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- **ci-cd.yaml**: Orchestrates all jobs, triggers on push, PR, release, manual
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- **release.yaml**: Publishes releases on main/tags
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### Docker Build Safety Features
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- **Multi-arch builds**: Uses Docker Buildx and QEMU for isolated, reproducible builds across amd64 and arm64
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- **Trivy vulnerability scan**: Automated scan for critical/high OS and library vulnerabilities before release
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- **Buildx isolation**: Ensures builds are run in a clean environment, reducing risk of contamination
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- **Secrets management**: DockerHub credentials and other secrets are handled securely via GitHub Actions
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- **Minimal base image**: Dockerfile uses slim Python base for reduced attack surface
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- **No root user**: (Recommended) Run containers as non-root for extra safety (customize Dockerfile as needed)
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## Python Best Practices
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- **src layout**: Prevents import shadowing, enables clean packaging
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- **pyproject.toml**: Modern build system, dependency management
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- **Type hints**: Static analysis, clarity
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- **Logging**: Traceability for inputs, API calls, UI rendering
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- **Modularization**: UI logic in dedicated module, core as thin wrappers, data loader and service layer separated for clarity and maintainability
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- **Testing**: pytest for unit and integration tests
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- **CI/CD**: Automated lint, test, build, scan, release
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- **Multi-arch Docker**: Builds for amd64 and arm64
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## Getting Started
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1. Clone the repo
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2. Install dependencies: `uv sync`
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3. Run tests: `uv run pytest`
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4. Run app: `uv run src/sample_python_app/main.py`
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- Data loading and business logic are now handled via the service layer and data_loader module
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5. Build Docker: `docker build -t python-app-template .`
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## Contributing
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- Follow PEP8 and use ruff, black, isort
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- Write tests for new features
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- Use modular, reusable workflows
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## License
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MIT
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---
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This template is ideal for modern Python apps with clean architecture, robust automation, and beautiful terminal UI.

‎src/sample_python_app/core/__init__.py‎

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"""Export core modules for use in other modules."""
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from sample_python_app.core.config import Settings, settings, weather_settings
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from sample_python_app.core.data_loader import fetch_astronomical_data_from_api
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from sample_python_app.core.display import display_astronomical_data
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from sample_python_app.core.logging import setup_logger
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__all__ = [
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"settings",
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"weather_settings",
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"setup_logger",
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"fetch_astronomical_data_from_api",
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"Settings",
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"display_astronomical_data",
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]

‎src/sample_python_app/main.py‎

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from sample_python_app.core import (
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display_astronomical_data,
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fetch_astronomical_data_from_api,
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setup_logger,
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weather_settings,
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)
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from sample_python_app.services import fetch_astronomical_data_from_api
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logger = setup_logger(mode="silent")
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‎src/sample_python_app/services/__init__.py‎

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"""Service layer for data loading and related business logic."""
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from sample_python_app.services.data_loader import fetch_astronomical_data_from_api
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__all__ = ["fetch_astronomical_data_from_api"]

src/sample_python_app/core/data_loader.py renamed to src/sample_python_app/services/data_loader.py

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"""Handles loading and validating weather.gov astronomical data from file."""
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"""Handles loading and validating weather.gov astronomical data from file and API."""
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import httpx
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from pydantic import ValidationError
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from sample_python_app.core.logging import setup_logger
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from sample_python_app.core import setup_logger
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from sample_python_app.models import AstronomicalData, WeatherGovFeature
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except ValidationError as e:
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logger.error(f"Data validation error: {e}")
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raise
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except httpx.HTTPError as e:
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logger.error(f"Failed to fetch or validate data from API: {e}")
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raise

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