viperx 1.3.0

Professional Python Project Initializer with uv, ml/dl support, and embedded config.

🐍 ViperX

Professional Python Project Initializer The modern, snake-fast way to bootstrap Python projects.

ViperX is a CLI tool designed to generate production-ready Python projects instantly. It leverages uv for blazing fast dependency management and offers specialized templates for Machine Learning (ml) and Deep Learning (dl).

✨ Features

• Blazing Fast: Built on top of uv.
• Pre-configured: pyproject.toml, proper src layout, ruff ready.
• ML/DL First: Templates with torch, tensorflow, kagglehub and Smart Caching.
• Smart Caching: Auto-downloads and caches datasets to ~/.cache/viperx/data (or local data/).
• Strict Isolation: Environment variables (.env) isolated in src/<pkg>/ for better security.
• Config-in-Package: Solves the "Colab/Kaggle doesn't see my config" problem.
• Platform Agnostic: Works on Local, VSCode, Colab, and Kaggle.
• Safe Mode: Never overwrites or deletes files automatically—reports changes for manual action.

📦 Installation

Recommended (Global Tool)

pipx install viperx

Alternative (uv)

uv tool install viperx

🚀 Quick Start

# Classic Package
viperx config -n my-lib

# Machine Learning Project
viperx config -n churn-prediction -t ml --env

# Deep Learning Project (PyTorch)
viperx config -n deep-vision -t dl -f pytorch

# Declarative Config (Infrastructure as Code)
viperx config get                   # Generate template
viperx config -c viperx.yaml        # Apply config

🧱 Project Structure

Standard Layout

my-lib/
├── pyproject.toml      # Managed by uv
├── README.md
├── .gitignore
├── viperx.yaml         # Config file
└── src/
    └── my_lib/
        ├── __init__.py
        ├── main.py         # Entry point
        ├── config.yaml     # Data URLs & Params
        ├── config.py       # Loader
        ├── .env            # Secrets (ISOLATED)
        └── tests/
            └── test_core.py

ML/DL Layout

deep-vision/
├── pyproject.toml
├── notebooks/
│   ├── Base_Kaggle.ipynb
│   └── Base_General.ipynb
├── data/               # Cached datasets
└── src/
    └── deep_vision/
        ├── main.py
        ├── config.py       # <--- ISOLATED
        ├── .env            # <--- ISOLATED
        ├── data_loader.py  # Smart caching
        └── tests/

💻 CLI Reference

config - Main Command

viperx config [OPTIONS]

Options:

Flag	Description	Default
-n, --name	Project name (Required)	-
-t, --type	classic, ml, dl	classic
-d, --description	Project description	-
-a, --author	Author name	git user
-l, --license	MIT, Apache-2.0, GPLv3	MIT
-b, --builder	uv, hatch	uv
-f, --framework	pytorch, tensorflow (DL only)	pytorch
--env / --no-env	Generate .env file	--no-env
-c, --config	Path to viperx.yaml	-

config get - Generate Template

viperx config get

Creates a viperx.yaml template in current directory.

package - Workspace Management

# Add package
viperx package add -n worker-api -t classic

# Delete package
viperx package delete -n worker-api

# Update dependencies
viperx package update -n worker-api

📝 Declarative Config (viperx.yaml)

project:
  name: "my-project"
  description: "A cool project"
  author: "Your Name"
  license: "MIT"
  builder: "uv"

settings:
  type: "classic"          # classic | ml | dl
  use_env: false
  use_config: true
  use_tests: true

workspace:
  packages:
    - name: "api"
      type: "classic"
    - name: "ml-core"
      type: "ml"
      use_env: true

🔒 Safe Mode Philosophy

ViperX follows a non-destructive approach:

Action	Behavior
Add	✅ Creates new files/packages
Update	⚠️ Reports changes, user decides
Delete	❌ Never deletes—warns user
Overwrite	❌ Never overwrites existing files

🧪 Test Coverage

uv run pytest src/viperx/tests
# 34 tests | 77% coverage

Test Structure:

• unit/ - Validation (5 tests)
• functional/ - CLI, licenses, project types (16 tests)
• scenarios/ - Classic, workspace, updates (11 tests)
• integration/ - E2E lifecycle (2 tests)

🤝 Contributing

git clone https://github.com/KpihX/viperx.git
cd viperx
uv sync
uv run viperx --help

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Built with ❤️ by KpihX