python-tooling

Automate Python project setup, dependency management, and profiling with UV.

Updated Aug 29, 2025
One-click install
npx skills add https://github.com/DDTully/dotfiles --skill python-tooling-ddtully
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: python-tooling
Source: https://github.com/DDTully/dotfiles/tree/main/skills/.agent_skills/python-tooling
Command: npx skills add https://github.com/DDTully/dotfiles --skill python-tooling-ddtully

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Python project ecosystems often suffer from inconsistent dependencies, fragile environments, and manual, error-prone profiling and CI/CD setups. This skill provides a cohesive toolkit to manage packages, virtual environments, performance profiling, and automated pipelines for Python projects.

Core Features & Use Cases

  • Dependency management and virtual environment setup with UV for reproducible builds across machines.
  • Performance profiling and optimization techniques to improve runtime efficiency in development and production.
  • Docker integration and CI/CD configurations to automate testing, packaging, and deployment pipelines.

Quick Start

Start a new Python project with UV and auto-configured tooling by running uv init in your project directory.

Frequently Asked Questions about python-tooling

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I set up a Python project with UV for reproducible builds?

To set up a Python project with UV, run the 'uv init' command in your project directory to automatically configure virtual environments and dependency management for consistent builds across machines.

What is the best way to integrate Python applications with Docker and CI/CD pipelines?

The best way to integrate Python applications with Docker and CI/CD pipelines is by applying automated configurations for testing, packaging, and deployment. This ensures consistent environments and streamlined release workflows across development stages.

Can I use UV for performance profiling and build optimization in Python?

Yes, you can use UV alongside provided performance profiling techniques to optimize Python build processes. This combination improves runtime efficiency and addresses build-optimization requirements during development and production.

Does this Python tooling approach work for both development and release workflows?

Yes, this Python tooling approach works across development, testing, and release workflows. It provides a cohesive toolkit to manage dependencies, virtual environments, and automated pipelines throughout the entire project lifecycle.

Why does my Python project suffer from inconsistent dependencies and fragile environments?

Python projects suffer from inconsistent dependencies and fragile environments due to manual setup processes. Using UV for dependency management and virtual environment setup provides reproducible builds that resolve these error-prone inconsistencies.