Routine Workflow

Production-grade automation for repository hygiene: code reformatting, cache cleaning, backups, dumps orchestration, and security auditing.

routine_workflow is a robust, "batteries-included" Python tool designed to automate the mundane but critical maintenance tasks of your repository. Whether running in a CI pipeline or on a local developer machine, it ensures your project stays clean, secure, and well-formatted with a single command.

⚡ Quick Start (The "5-Minute Rule")

Prerequisites

• Python: 3.9+
• Pip: Latest version recommended

Installation

Install via pip:

pip install routine-workflow

Run

Run the default workflow in Dry-Run Mode (Safe by default):

routine-workflow

To execute the Full Workflow (Real changes):

routine-workflow -nd -y

Demo

Copy-paste this snippet to see it in action (Dry Run):

# 1. Install
pip install routine-workflow

# 2. Run with rich interface (safe mode)
routine-workflow

# 3. View help for more options
routine-workflow --help

✨ Features

🛠️ Core Essentials

• Code Reformatting: Automatically formats code using ruff and isort.
• Cache Cleaning: Wipes __pycache__, .pytest_cache, and other temporary files.
• Backups & Dumps: Orchestrates safe backups and code dumps before changes.
• Git Integration: Auto-commits and pushes a "hygiene snapshot" after success.

🛡️ Security & Quality

• Security Audits: Runs bandit and safety to catch vulnerabilities.
• Dependency Auditing: Checks for outdated or insecure dependencies.
• Test Integration: Runs pytest suite with coverage enforcement.

🚀 Performance & UX

• Parallel Execution: Uses multi-processing for CPU-bound tasks.
• Interactive Mode: Guided wizard (-i) for easy configuration.
• Profiling: Built-in performance profiling (--profile).
• Rich Logging: JSON output, log rotation, and beautiful terminal UI.

🛠️ Configuration

Configure routine-workflow via Environment Variables (for CI/CD) or CLI Arguments (for local use).

Environment Variables

CLI Arguments

🏗️ Architecture

The project follows a modular, step-based architecture designed for extensibility and reliability.

Directory Tree

src/routine_workflow
├── __init__.py
├── banner.py           # CLI Art
├── cli.py              # Entry Point
├── config.py           # Configuration Model
├── runner.py           # Workflow Orchestrator
├── lock.py             # File-based Locking
├── steps/              # Modular Workflow Steps
│   ├── step1.py        # Delete Dumps
│   ├── step2.py        # Reformat
│   ├── step3.py        # Clean Caches
│   ├── step3_5.py      # Security Scan
│   ├── step4.py        # Backup
│   ├── step6.py        # Git Operations
│   └── ...
└── utils.py            # Helpers

Data Flow

1. Init: CLI parses args & env vars -> WorkflowConfig.
2. Lock: Acquires file lock to prevent concurrent runs.
3. Plan: WorkflowRunner resolves requested steps/aliases.
4. Execute: Steps run sequentially (some parallelized internally).
5. Report: Results logged to console and JSON log files.

🐞 Troubleshooting

Common Issues

Debug Mode

To see verbose output for debugging:

routine-workflow --log-level DEBUG

🤝 Contributing

We welcome contributions!

1. Fork the repository.
2. Install dev dependencies:

   pip install -e ".[dev]"
   

3. Run Tests:

   pytest
   

4. Submit a Pull Request.

See CONTRIBUTING.md (if available) for detailed guidelines.

🗺️ Roadmap

• Core: CLI, Step Runner, Reformat, Clean, Backup.
• Security: Bandit, Safety, Dependency Audit.
• Advanced: Interactive Mode, Profiling, JSON Logging.
• Upcoming: 3rd Party Plugins, Webhooks (Slack/Discord), AI Refactoring.

See ROADMAP.md for the full vision.