Directory Structure Template
Standardized Project Organization Framework
Template Overview
This template provides a comprehensive framework for creating consistent, scalable directory structures across different project types. It serves as the foundation for automated project scaffolding and ensures organizational consistency.
Template Categories
1. Python ML Project Template
python_ml_project:
metadata:
name: "python-ml-project"
version: "2.1.0"
description: "Machine Learning project with modern Python tooling"
last_updated: "2025-07-24"
compatibility: ["Python 3.9+", "Poetry", "Docker", "Jupyter"]
target_audience: "Data Scientists, ML Engineers, Research Teams"
directory_structure:
root: "/"
core_directories:
- path: ".github/workflows/"
purpose: "CI/CD pipeline configurations"
permissions: "644"
auto_create: true
- path: "src/"
purpose: "Main source code directory"
permissions: "755"
subdirectories:
- "data/" # Raw and processed datasets
- "models/" # Trained models and artifacts
- "notebooks/" # Jupyter notebooks for exploration
- "scripts/" # Standalone processing scripts
- "utils/" # Helper functions and shared utilities
- "tests/" # Unit and integration tests
- path: "docs/"
purpose: "Project documentation"
permissions: "755"
subdirectories:
- "api/" # API documentation
- "guides/" # User guides and tutorials
- "architecture/" # System architecture docs
- path: "config/"
purpose: "Configuration files"
permissions: "644"
subdirectories:
- "environments/" # Environment-specific configs
- "models/" # Model configuration files
- path: "staging/"
purpose: "File classification inbox for Classifico agent"
permissions: "777"
monitoring: "real_time_file_events"
- path: "logs/"
purpose: "Application and system logs"
permissions: "755"
retention_policy: "30_days"
- path: "results/"
purpose: "Experiment outputs and analysis results"
permissions: "755"
subdirectories:
- "experiments/" # Experiment results
- "reports/" # Generated reports
- "visualizations/" # Charts and graphs
configuration_files:
- name: ".gitignore"
template: "python_ml_gitignore"
purpose: "Version control exclusions"
- name: "README.md"
template: "python_ml_readme"
purpose: "Project overview and setup instructions"
- name: "pyproject.toml"
template: "python_ml_pyproject"
purpose: "Python project configuration and dependencies"
- name: "environment.yml"
template: "conda_environment"
purpose: "Conda environment specification"
- name: "Dockerfile"
template: "python_ml_dockerfile"
purpose: "Container configuration"
- name: "docker-compose.yml"
template: "ml_docker_compose"
purpose: "Multi-container orchestration"
- name: "Makefile"
template: "python_ml_makefile"
purpose: "Build and automation commands"2. Web Application Template
3. Research Project Template
Template Customization Framework
Dynamic Template Generation
Template Validation Rules
Template Integration Points
Classifico Integration
Locomoto Integration
Purgo Integration
Success Metrics
Template Quality Standards
โ Completeness: All necessary directories and files included
โ Scalability: Structure supports project growth without reorganization
โ Consistency: Standardized patterns across similar project types
โ Maintainability: Clear organization facilitates long-term maintenance
Usage Metrics
โ Adoption Rate: 90%+ of new projects use template-based initialization
โ Customization Success: 95%+ of templates successfully customized for specific needs
โ Developer Satisfaction: 85%+ approval rating for generated structures
โ Maintenance Efficiency: 50%+ reduction in manual directory organization time
This template framework ensures consistent, well-organized project structures that support efficient development workflows and automated file organization processes.
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