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modinit

modinit is a Python package that helps you quickly scaffold AI model training repositories with a standardized, best-practice structure. It saves you time and ensures consistency across your machine learning projects.

Why use modinit?

  • Instant project setup: Get started with a ready-to-use directory structure in seconds.
  • Best practices built-in: Follows common conventions for organizing data, code, configs, and tests.
  • Docstring templates: All generated Python files include helpful docstrings.
  • Easy to use: Simple command-line interface.

Demo

modinit demo

Installation

pip install modinit

Usage

To create a new project, run:

modinit my-project

This will generate a new directory called my-project with a recommended structure for AI/ML projects.

Example

Below is a real example of using modinit to create a project called voice-rumba:

$ pip install modinit
$ modinit voice-rumba
Successfully created project: voice-rumba
To get started, navigate to the project directory:
  cd voice-rumba

The generated structure looks like this:

voice-rumba/
├── README.md
├── .gitignore
├── configs/
│   └── config.yaml
├── data/
│   ├── raw/
│   ├── processed/
│   └── interim/
├── main.py
├── notebooks/
│   └── prototype.ipynb
├── requirements.txt
├── src/
│   ├── __init__.py
│   ├── data.py
│   ├── evaluate.py
│   ├── model.py
│   ├── train.py
│   └── utils.py
└── tests/
    ├── __init__.py
    ├── test_data.py
    ├── test_model.py
    └── test_train.py

Features

  • Creates a well-structured project directory for AI model training
  • Follows best practices for machine learning project organization
  • Includes helpful docstrings in all generated files
  • Simple command-line interface

Development

To contribute to this project:

  1. Clone the repository
  2. Create a virtual environment
  3. Install development dependencies: pip install -e ".[dev]"
  4. Make your changes
  5. Run tests: pytest

License

MIT

Metadata

Release files for modinit 0.1.1

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