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One command ML project scaffolding CLI — works on Windows, Mac, and Linux.

Project description

Vantix

Professional ML project scaffolding CLI — one command, zero config.

Version

Quick Start

pip install vantix
vantix init my_project

That's it. Your entire ML workspace is ready.

Run pip install -U vantix to always get the latest version.

What It Does

A single vantix init command will:

Step Action
1 Create a professional folder structure (data, src, notebooks, configs, logs, tests)
2 Generate essential files (.gitignore, .env, config.yaml, train.py, eda.ipynb)
3 Include a full SETUP_GUIDE.md manual inside every project
4 Set up a virtual environment (.venv) with pip, setuptools, wheel
5 Install 10 core ML/DS packages (NumPy, Pandas, Scikit-learn, etc.)
6 Pin exact versions in requirements.txt
7 Generate a project-specific README.md
8 Initialize Git with an initial commit

Default Packages

All packages install the latest compatible version automatically.

Package Description
numpy Numerical computing
pandas Data manipulation
scikit-learn Machine learning algorithms
matplotlib Visualization
seaborn Statistical visualization
jupyter Interactive notebooks
mlflow Experiment tracking
fastapi REST API framework
uvicorn ASGI server
python-dotenv Environment variable management
vantix packages     # View all defaults anytime

Note: These 10 core packages include their own transitive dependencies (~150+ total), all of which are auto-detected and pinned in requirements.txt.

Customize Packages

Override any default or add new packages with --pkg:

# Pin specific versions
vantix init my_project --pkg numpy==1.24.0 --pkg pandas==2.0.0

# Install latest (no pin)
vantix init my_project --pkg numpy==latest

# Add packages not in defaults
vantix init my_project --pkg torch --pkg transformers

# Mix and match
vantix init my_project --pkg numpy==1.24.0 --pkg torch --pkg transformers==4.40.0

Project Structure

my_project/
├── .venv/                 Virtual environment (auto-created)
├── data/
│   ├── raw/               Original, untouched data
│   └── processed/         Cleaned and transformed data
├── notebooks/
│   └── eda.ipynb          Exploration and visualization
├── src/
│   ├── features/          Feature engineering
│   ├── models/            Model definitions
│   ├── training/
│   │   └── train.py       Training entry point
│   └── inference/         Prediction and serving
├── configs/
│   └── config.yaml        Settings and hyperparameters
├── logs/                  Training logs
├── tests/                 Unit and integration tests
├── .env                   Secrets (never committed)
├── .gitignore
├── requirements.txt       Pinned dependencies
├── SETUP_GUIDE.md         Full manual reference
└── README.md

After Setup

cd my_project

# Activate virtual environment
source .venv/bin/activate          # Mac / Linux
.venv\Scripts\Activate.ps1         # Windows (PowerShell)

# Start training
python src/training/train.py

All Commands

Command Description
vantix init <name> Create project with default packages
vantix init <name> --pkg <spec> Override specific packages
vantix packages List default packages and versions
vantix --version Show version
vantix --help Show help

Requirements

  • Python 3.8+
  • Git (optional, for auto git init)

Troubleshooting

Command not found: vantix (Windows)

If you see vantix: The term 'vantix' is not recognized..., your Python Scripts folder is not in PATH.

Fix PATH (Recommended):

  1. Search Windows for "Edit the system environment variables"
  2. Click "Environment Variables"
  3. Under "User variables", find Path and click "Edit"
  4. Add your Python Scripts folder (e.g., C:\Users\YourName\AppData\Roaming\Python\Python313\Scripts)
  5. Restart your terminal

Or use Python module directly:

python -m vantix init my_project

License

MIT

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