# Uv Package Manager

> Domina el gestor de paquetes uv para gestión rápida de dependencias Python, entornos virtuales y flujos de trabajo modernos de proyectos Python.

Fuente: https://skillsagentes.com/skills/wshobson/agents/uv-package-manager
Markdown: https://skillsagentes.com/skills/wshobson/agents/uv-package-manager.md

Repositorio: https://github.com/wshobson/agents
Autor: wshobson
Licencia: MIT
Actualizado: hace 5 meses
Coste de contexto: 60 tok instalada, 1.8k tok al activarse, 3.9k tok con todos los archivos del bundle
Bundle: 2 archivos, 15 KB
Permisos que pide: ninguno declarado

## Instalación

Un skill son archivos markdown: los mismos archivos valen para cualquier agente y lo único que cambia es el directorio de destino, es decir la bandera `--agent`. Añade `-g` para instalarlo en todos los proyectos de la máquina.

```bash
# Claude Code
npx -y skills add wshobson/agents --skill uv-package-manager --agent claude-code
# Cursor
npx -y skills add wshobson/agents --skill uv-package-manager --agent cursor
# Codex
npx -y skills add wshobson/agents --skill uv-package-manager --agent codex
# Gemini CLI
npx -y skills add wshobson/agents --skill uv-package-manager --agent gemini
# Windsurf
npx -y skills add wshobson/agents --skill uv-package-manager --agent windsurf
# Cline
npx -y skills add wshobson/agents --skill uv-package-manager --agent cline
```

## Qué hace

- Guía comandos de uv para crear proyectos, gestionar dependencias, entornos virtuales y versiones de Python
- Cubre patrones para instalar, actualizar, eliminar y bloquear dependencias con uv.lock
- Explica migración desde pip, pip-tools y poetry hacia uv
- Describe integración de pyproject.toml y ejecución con uv run

## Cuándo usarla

- Configurar nuevos proyectos Python rápidamente
- Gestionar dependencias Python más rápido que pip
- Crear y gestionar entornos virtuales
- Migrar desde pip/pip-tools/poetry

## Qué la activa

- "Configura un nuevo proyecto Python con uv"
- "Migra mi proyecto de poetry a uv"
- "Añade pytest como dependencia de desarrollo con uv"
- "Genera el archivo uv.lock para mi proyecto"

## Antes de instalar

- Requiere instalar uv (via curl, PowerShell, pip, Homebrew o cargo).
- Necesita en el PATH: curl, pip
- makes network requests

## Archivos

- SKILL.md — 7 KB
- references/advanced-patterns.md — 8 KB

## SKILL.md

Reproducido tal cual desde wshobson/agents bajo MIT. Esta sección es el documento original y está en inglés.

# UV Package Manager

Comprehensive guide to using uv, an extremely fast Python package installer and resolver written in Rust, for modern Python project management and dependency workflows.

## When to Use This Skill

- Setting up new Python projects quickly
- Managing Python dependencies faster than pip
- Creating and managing virtual environments
- Installing Python interpreters
- Resolving dependency conflicts efficiently
- Migrating from pip/pip-tools/poetry
- Speeding up CI/CD pipelines
- Managing monorepo Python projects
- Working with lockfiles for reproducible builds
- Optimizing Docker builds with Python dependencies

## Core Concepts

### 1. What is uv?

- **Ultra-fast package installer**: 10-100x faster than pip
- **Written in Rust**: Leverages Rust's performance
- **Drop-in pip replacement**: Compatible with pip workflows
- **Virtual environment manager**: Create and manage venvs
- **Python installer**: Download and manage Python versions
- **Resolver**: Advanced dependency resolution
- **Lockfile support**: Reproducible installations

### 2. Key Features

- Blazing fast installation speeds
- Disk space efficient with global cache
- Compatible with pip, pip-tools, poetry
- Comprehensive dependency resolution
- Cross-platform support (Linux, macOS, Windows)
- No Python required for installation
- Built-in virtual environment support

### 3. UV vs Traditional Tools

- **vs pip**: 10-100x faster, better resolver
- **vs pip-tools**: Faster, simpler, better UX
- **vs poetry**: Faster, less opinionated, lighter
- **vs conda**: Faster, Python-focused

## Installation

### Quick Install

```bash
# macOS/Linux
curl -LsSf https://astral.sh/uv/install.sh | sh

# Windows (PowerShell)
powershell -c "irm https://astral.sh/uv/install.ps1 | iex"

# Using pip (if you already have Python)
pip install uv

# Using Homebrew (macOS)
brew install uv

# Using cargo (if you have Rust)
cargo install --git https://github.com/astral-sh/uv uv
```

### Verify Installation

```bash
uv --version
# uv 0.x.x
```

## Quick Start

### Create a New Project

```bash
# Create new project with virtual environment
uv init my-project
cd my-project

# Or create in current directory
uv init .

# Initialize creates:
# - .python-version (Python version)
# - pyproject.toml (project config)
# - README.md
# - .gitignore
```

### Install Dependencies

```bash
# Install packages (creates venv if needed)
uv add requests pandas

# Install dev dependencies
uv add --dev pytest black ruff

# Install from requirements.txt
uv pip install -r requirements.txt

# Install from pyproject.toml
uv sync
```

## Virtual Environment Management

### Pattern 1: Creating Virtual Environments

```bash
# Create virtual environment with uv
uv venv

# Create with specific Python version
uv venv --python 3.12

# Create with custom name
uv venv my-env

# Create with system site packages
uv venv --system-site-packages

# Specify location
uv venv /path/to/venv
```

### Pattern 2: Activating Virtual Environments

```bash
# Linux/macOS
source .venv/bin/activate

# Windows (Command Prompt)
.venv\Scripts\activate.bat

# Windows (PowerShell)
.venv\Scripts\Activate.ps1

# Or use uv run (no activation needed)
uv run python script.py
uv run pytest
```

### Pattern 3: Using uv run

```bash
# Run Python script (auto-activates venv)
uv run python app.py

# Run installed CLI tool
uv run black .
uv run pytest

# Run with specific Python version
uv run --python 3.11 python script.py

# Pass arguments
uv run python script.py --arg value
```

## Package Management

### Pattern 4: Adding Dependencies

```bash
# Add package (adds to pyproject.toml)
uv add requests

# Add with version constraint
uv add "django>=4.0,<5.0"

# Add multiple packages
uv add numpy pandas matplotlib

# Add dev dependency
uv add --dev pytest pytest-cov

# Add optional dependency group
uv add --optional docs sphinx

# Add from git
uv add git+https://github.com/user/repo.git

# Add from git with specific ref
uv add git+https://github.com/user/repo.git@v1.0.0

# Add from local path
uv add ./local-package

# Add editable local package
uv add -e ./local-package
```

### Pattern 5: Removing Dependencies

```bash
# Remove package
uv remove requests

# Remove dev dependency
uv remove --dev pytest

# Remove multiple packages
uv remove numpy pandas matplotlib
```

### Pattern 6: Upgrading Dependencies

```bash
# Upgrade specific package
uv add --upgrade requests

# Upgrade all packages
uv sync --upgrade

# Upgrade package to latest
uv add --upgrade requests

# Show what would be upgraded
uv tree --outdated
```

### Pattern 7: Locking Dependencies

```bash
# Generate uv.lock file
uv lock

# Update lock file
uv lock --upgrade

# Lock without installing
uv lock --no-install

# Lock specific package
uv lock --upgrade-package requests
```

## Python Version Management

### Pattern 8: Installing Python Versions

```bash
# Install Python version
uv python install 3.12

# Install multiple versions
uv python install 3.11 3.12 3.13

# Install latest version
uv python install

# List installed versions
uv python list

# Find available versions
uv python list --all-versions
```

### Pattern 9: Setting Python Version

```bash
# Set Python version for project
uv python pin 3.12

# This creates/updates .python-version file

# Use specific Python version for command
uv --python 3.11 run python script.py

# Create venv with specific version
uv venv --python 3.12
```

## Project Configuration

### Pattern 10: pyproject.toml with uv

```toml
[project]
name = "my-project"
version = "0.1.0"
description = "My awesome project"
readme = "README.md"
requires-python = ">=3.8"
dependencies = [
    "requests>=2.31.0",
    "pydantic>=2.0.0",
    "click>=8.1.0",
]

[project.optional-dependencies]
dev = [
    "pytest>=7.4.0",
    "pytest-cov>=4.1.0",
    "black>=23.0.0",
    "ruff>=0.1.0",
    "mypy>=1.5.0",
]
docs = [
    "sphinx>=7.0.0",
    "sphinx-rtd-theme>=1.3.0",
]

[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"

[tool.uv]
dev-dependencies = [
    # Additional dev dependencies managed by uv
]

[tool.uv.sources]
# Custom package sources
my-package = { git = "https://github.com/user/repo.git" }
```

### Pattern 11: Using uv with Existing Projects

```bash
# Migrate from requirements.txt
uv add -r requirements.txt

# Migrate from poetry
# Already have pyproject.toml, just use:
uv sync

# Export to requirements.txt
uv pip freeze > requirements.txt

# Export with hashes
uv pip freeze --require-hashes > requirements.txt
```

For advanced workflows including Docker integration, lockfile management, performance optimization, tool comparison, common workflows, tool integration, troubleshooting, best practices, migration guides, and command reference, see [references/advanced-patterns.md](references/advanced-patterns.md)

## Dónde encaja

- Categoría: [Herramientas para desarrolladores](https://skillsagentes.com/categorias/herramientas-desarrollo.md) — Skills que cambian cómo tu agente escribe, revisa y despliega código.
- Creador: [wshobson](https://skillsagentes.com/creators/wshobson.md) — 183 skills en el directorio
- [Todas las skills](https://skillsagentes.com/skills.md)
- [Ranking de instalaciones](https://skillsagentes.com/ranking.md)

## Otras skills del mismo repositorio

- [Hermes Tweet](https://skillsagentes.com/skills/wshobson/agents/hermes-tweet.md): Instala y opera Hermes Tweet, un plugin de Hermes Agent para investigar X/Twitter, leer timelines, analizar tweets y ejecutar operaciones privadas o de cambio de estado con aprobación previa.
- [Superself](https://skillsagentes.com/skills/wshobson/agents/superself.md): Úsalo cuando un proyecto guarda su estado en Superself: lee `self context` al iniciar sesión, vincula el trabajo a una work unit, reporta con evidencia y registra decisiones confirmadas.
- [Grounded Vault](https://skillsagentes.com/skills/wshobson/agents/grounded-vault.md): Úsalo para mantener un almacén Markdown de conocimiento donde cada afirmación compilada se rastrea hasta una fuente inmutable y el drift se detecta con git diff sin gastar tokens.
- [Postgresql Table Design](https://skillsagentes.com/skills/wshobson/agents/postgresql-table-design.md): Úsalo al diseñar o revisar un esquema específico de PostgreSQL: buenas prácticas, tipos de datos, indexación, restricciones, patrones de rendimiento y funciones avanzadas.
- [Prompt Engineering Patterns](https://skillsagentes.com/skills/wshobson/agents/prompt-engineering-patterns.md): Úsalo cuando pidan optimizar un prompt, mejorar su rendimiento, diseñar una plantilla, aplicar chain-of-thought, few-shot prompting o técnicas avanzadas de prompt engineering para producción.

---

Skills Agentes · [Índice de páginas en markdown](https://skillsagentes.com/sitemap.md) · [Inicio](https://skillsagentes.com/index.md)