{"id":37324655,"url":"https://github.com/ai-enhanced-engineer/aut-python-template","last_synced_at":"2026-01-16T03:27:17.111Z","repository":{"id":308602553,"uuid":"1029890708","full_name":"ai-enhanced-engineer/aut-python-template","owner":"ai-enhanced-engineer","description":"AI/ML project template with best practices baked in","archived":false,"fork":false,"pushed_at":"2026-01-14T20:39:57.000Z","size":156,"stargazers_count":0,"open_issues_count":0,"forks_count":1,"subscribers_count":0,"default_branch":"main","last_synced_at":"2026-01-15T00:49:49.118Z","etag":null,"topics":["ai-engineering","artificial-intelligence","machine-learning","machine-learning-projects","ml-engineering"],"latest_commit_sha":null,"homepage":"https://aienhancedengineer.substack.com/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ai-enhanced-engineer.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.md","contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2025-07-31T18:32:43.000Z","updated_at":"2026-01-14T20:40:00.000Z","dependencies_parsed_at":"2025-09-01T00:15:45.026Z","dependency_job_id":"184d6865-84da-40fa-a178-4be30b46bb97","html_url":"https://github.com/ai-enhanced-engineer/aut-python-template","commit_stats":null,"previous_names":["ai-enhanced-engineer/ai-base-template","ai-enhanced-engineer/aut-python-template"],"tags_count":9,"template":true,"template_full_name":null,"purl":"pkg:github/ai-enhanced-engineer/aut-python-template","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ai-enhanced-engineer%2Faut-python-template","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ai-enhanced-engineer%2Faut-python-template/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ai-enhanced-engineer%2Faut-python-template/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ai-enhanced-engineer%2Faut-python-template/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ai-enhanced-engineer","download_url":"https://codeload.github.com/ai-enhanced-engineer/aut-python-template/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ai-enhanced-engineer%2Faut-python-template/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28477203,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-16T03:13:13.607Z","status":"ssl_error","status_checked_at":"2026-01-16T03:11:47.863Z","response_time":107,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["ai-engineering","artificial-intelligence","machine-learning","machine-learning-projects","ml-engineering"],"created_at":"2026-01-16T03:27:16.501Z","updated_at":"2026-01-16T03:27:17.100Z","avatar_url":"https://github.com/ai-enhanced-engineer.png","language":"Python","readme":"# Autonomous Python Template\n\n\u003e Describe what you want to build. Let agents build it.\n\nA self-building Python ML/Data Science template powered by Claude Code. Clone, describe your project, and watch it come to life.\n\n## Quick Start\n\n### 1. Clone this template\n\n```bash\ngit clone https://github.com/ai-enhanced-engineer/aut-python-template.git my-project\ncd my-project\n```\n\n### 2. Set up environment\n\n```bash\njust init\n```\n\n### 3. Start Claude Code\n\n```bash\nclaude\n```\n\n### 4. Describe your project\n\n```\n\u003e I want to build a RAG system for legal documents\n```\n\nThat's it. Describe what you want; agents help you build it.\n\n## Example Session\n\n```\nYou: I want to build a fraud detection API\n\nClaude: I'll help you build a fraud detection API. Let me understand your requirements:\n        - What data sources will you use? (transactions, user behavior, etc.)\n        - Any specific ML approach preference? (rule-based, XGBoost, neural network)\n        - What's your target latency for predictions?\n\nYou: Transaction data from a PostgreSQL database. XGBoost for now, we can upgrade later.\n     Need sub-100ms latency.\n\nClaude: Great, let me set up the project structure:\n        1. Creating data pipeline for PostgreSQL ingestion\n        2. Setting up XGBoost model with feature engineering\n        3. Building FastAPI endpoint with async handlers\n        4. Adding monitoring and logging\n\n        [Creates files, writes tests, validates...]\n\nYou: Add a batch prediction endpoint too\n\nClaude: Adding batch prediction endpoint with:\n        - CSV upload support\n        - Background processing with status tracking\n        - Results stored in PostgreSQL\n\n        [Implements, tests, validates...]\n```\n\n## What's Included\n\nThis template comes with production-ready infrastructure:\n\n### Production Logging\n\n- Structured JSON logging with [structlog](https://www.structlog.org/)\n- Correlation ID tracking across requests\n- Dual-mode: human-readable (dev) / JSON (prod)\n\n### Testing Infrastructure\n\n- pytest with markers (unit, functional, integration)\n- 80% coverage requirement\n- Pre-commit hooks for quality gates\n\n### CI/CD Pipeline\n\n- GitHub Actions workflows\n- Semantic versioning with auto-release\n- Format → Lint → Type-check → Test pipeline\n\n### Modern Python Tooling\n\n- Python 3.12+\n- Type hints throughout\n- Pydantic for data validation\n- uv for fast dependency management\n- Ruff + Black for formatting/linting\n- mypy (strict mode) for type checking\n\n## Project Structure\n\n```\nmy-project/\n├── src/                       # Python source code\n│   ├── __init__.py\n│   └── logging.py             # Production logging system\n├── tests/                     # Test suite\n│   └── test_logging.py        # 21+ logging tests as examples\n├── .claude/                   # Claude Code settings\n├── .github/workflows/         # CI/CD pipelines\n│   └── ci.yml\n├── CLAUDE.md                  # Development standards\n├── pyproject.toml             # Project configuration\n├── justfile                   # Automation commands\n├── ADR.md                     # Architecture decisions\n└── .pre-commit-config.yaml    # Git hooks\n```\n\n## Development Commands\n\n```bash\njust                   # Show all available commands\n\n# Environment\njust init              # Complete development setup\njust sync              # Update dependencies\njust clean-env         # Reset environment\n\n# Code Quality\njust format            # Auto-format code\njust lint              # Fix linting issues\njust type-check        # Validate type hints\njust validate-branch   # Run all checks (required before commits)\n\n# Testing\njust test              # Standard test suite\njust test-unit         # Fast unit tests\njust test-functional   # Feature tests\njust test-integration  # Integration tests\njust test-all          # Complete test suite\n```\n\n## The Production-First Philosophy\n\nThis template embodies the principle that **production AI requires engineering discipline**:\n\n- **90% infrastructure, 10% model code**: Most production AI is validation, monitoring, error handling, and cost controls—not algorithms\n- **Reliability over novelty**: Production systems must work consistently, not just impressively\n- **Plan for failure**: Every external call needs error handling; every assumption needs validation\n\n## Who Should Use This\n\n### Teams Starting ML/Data Projects\n\nStop reinventing infrastructure. Describe your project and get a production-ready foundation.\n\n### Senior Engineers New to ML\n\nGet the safety rails you're accustomed to in production systems while learning ML concepts.\n\n### Technical Leaders\n\nGive your team a consistent, production-ready starting point that embodies engineering best practices.\n\n## Learn More\n\n### Production AI Engineering\n\n- [A Production-First Approach to AI Engineering](https://aienhancedengineer.substack.com/p/a-production-first-approach-to-ai)\n- [Google's Rules for ML](https://developers.google.com/machine-learning/guides/rules-of-ml)\n- [Hidden Technical Debt in ML Systems](https://papers.nips.cc/paper/5656-hidden-technical-debt-in-machine-learning-systems.pdf)\n\n### Technologies\n\n- [FastAPI](https://fastapi.tiangolo.com/) - Modern Python web framework\n- [Pydantic](https://docs.pydantic.dev/) - Data validation\n- [structlog](https://www.structlog.org/) - Structured logging\n- [uv](https://docs.astral.sh/uv/) - Fast Python package management\n\n## Contributing\n\nWhen contributing, prioritize:\n\n1. **Reliability over features**\n2. **Simplicity over cleverness**\n3. **Documentation over assumptions**\n4. **Tests over trust**\n\n## License\n\nApache License 2.0 - See [LICENSE](LICENSE) file.\n\n---\n\n*\"Describe what you want. Let agents build it.\"*\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fai-enhanced-engineer%2Faut-python-template","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fai-enhanced-engineer%2Faut-python-template","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fai-enhanced-engineer%2Faut-python-template/lists"}