AgentSkillsCN

manage-python-env

uv(快速Python包管理器)操作的快速参考,用于节省令牌。适用于创建虚拟环境、安装包、管理依赖或用户询问uv命令时。提供Python项目设置和包管理的简洁模式。

SKILL.md
--- frontmatter
name: manage-python-env
description: Quick reference for uv (fast Python package manager) operations to save tokens. Use when creating virtual environments, installing packages, managing dependencies, or when user asks about uv commands. Provides concise patterns for Python project setup and package management.

UV Management

Quick reference for uv - the fast Python package installer and environment manager.

Installation

Install UV

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

# Or with pip
pip install uv

# Verify installation
uv --version

Project Initialization

Create New Project

bash
# Initialize new project
uv init project-name

# Initialize in current directory
uv init

# With specific Python version
uv init --python 3.11

Project Structure Created

code
project-name/
├── pyproject.toml    # Project configuration
├── .python-version   # Python version specification
└── src/
    └── project_name/
        └── __init__.py

Virtual Environment

Create Virtual Environment

bash
# Create venv (automatic with uv)
uv venv

# With specific Python version
uv venv --python 3.11

# With custom name
uv venv .venv-custom

# Activate (same as regular venv)
source .venv/bin/activate  # macOS/Linux
.venv\Scripts\activate     # Windows

Python Version Management

bash
# List available Python versions
uv python list

# Install specific Python version
uv python install 3.11

# Pin Python version for project
uv python pin 3.11

Package Management

Install Packages

bash
# Install single package
uv pip install package-name

# Install specific version
uv pip install package-name==1.2.3

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

# Install from pyproject.toml
uv pip install -e .

# Install development dependencies
uv pip install -e ".[dev]"

Add Dependencies (Modern Way)

bash
# Add package to project
uv add numpy

# Add with version constraint
uv add "numpy>=1.24,<2.0"

# Add multiple packages
uv add numpy pandas matplotlib

# Add as dev dependency
uv add --dev pytest black ruff

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

Remove Packages

bash
# Remove package
uv remove package-name

# Remove dev dependency
uv remove --dev pytest

Update Packages

bash
# Update single package
uv pip install --upgrade package-name

# Update all packages
uv pip install --upgrade -r requirements.txt

# Sync dependencies (recommended)
uv sync

Dependency Management

Lock Dependencies

bash
# Generate lock file
uv lock

# Lock and sync
uv lock --sync

Export Requirements

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

# Export from pyproject.toml
uv export --format requirements-txt > requirements.txt

Running Commands

Run Python

bash
# Run Python script
uv run python script.py

# Run module
uv run -m module_name

# Run with arguments
uv run python script.py --arg value

Run Tools

bash
# Run pytest
uv run pytest

# Run black
uv run black .

# Run ruff
uv run ruff check .

# Run any tool
uv run tool-name [args]

VRP Project Setup

Initial Project Setup

bash
# 1. Create project directory
mkdir vrp-toolkit
cd vrp-toolkit

# 2. Initialize with uv
uv init

# 3. Create virtual environment
uv venv

# 4. Activate environment
source .venv/bin/activate

# 5. Install core dependencies
uv add numpy pandas matplotlib networkx

# 6. Install dev dependencies
uv add --dev pytest black ruff ipython jupyter

# 7. Install OSMnx (for real map support)
uv add osmnx geopandas

# 8. Install package in editable mode
uv pip install -e .

pyproject.toml for VRP Toolkit

toml
[project]
name = "vrp-toolkit"
version = "0.1.0"
description = "Reusable VRP/PDPTW solving framework"
requires-python = ">=3.8"
dependencies = [
    "numpy>=1.24.0",
    "pandas>=2.0.0",
    "matplotlib>=3.7.0",
    "networkx>=3.0",
]

[project.optional-dependencies]
dev = [
    "pytest>=7.0.0",
    "black>=23.0.0",
    "ruff>=0.1.0",
    "ipython>=8.0.0",
    "jupyter>=1.0.0",
]
osmnx = [
    "osmnx>=1.6.0",
    "geopandas>=0.14.0",
    "folium>=0.15.0",
]

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

[tool.ruff]
line-length = 100
target-version = "py38"

[tool.black]
line-length = 100
target-version = ["py38"]

Install All Dependencies

bash
# Install main dependencies
uv add numpy pandas matplotlib networkx

# Install dev tools
uv add --dev pytest black ruff ipython jupyter

# Install OSMnx group
uv add osmnx geopandas folium

# Or install from pyproject.toml
uv sync

Common Workflows

Daily Development

bash
# Activate environment
source .venv/bin/activate

# Run tests
uv run pytest

# Format code
uv run black .

# Lint code
uv run ruff check .

# Run Jupyter
uv run jupyter lab

Add New Dependency

bash
# Add package
uv add package-name

# Test it works
uv run python -c "import package_name; print('OK')"

# Commit updated pyproject.toml
git add pyproject.toml uv.lock
git commit -m "chore: add package-name dependency"

Clean Install

bash
# Remove existing environment
rm -rf .venv

# Recreate
uv venv

# Reinstall all dependencies
uv sync

# Verify
uv run python -c "import numpy; print(numpy.__version__)"

Comparison with pip/venv

TaskTraditionalUV
Create venvpython -m venv .venvuv venv
Activatesource .venv/bin/activateSame
Install packagepip install packageuv add package
Install requirementspip install -r requirements.txtuv pip install -r requirements.txt
Freeze depspip freeze > requirements.txtuv pip freeze > requirements.txt
Run toolpython -m pytestuv run pytest

Key Advantages of UV:

  • ⚡ 10-100x faster than pip
  • 🔒 Built-in dependency locking
  • 🐍 Python version management
  • 📦 Cleaner dependency specification in pyproject.toml

Additional Resources

Troubleshooting

Common issues and solutions: See troubleshooting.md

  • UV not found after install
  • Wrong Python version
  • Dependency conflicts
  • Package not found

Advanced Usage

Power user features: See advanced.md

  • Multiple environments
  • Dependency groups
  • Build and publish
  • Integration with other skills

Migration from pip

Convert existing projects: See migration.md

  • Convert requirements.txt to pyproject.toml
  • Migrate existing project step-by-step
  • pip vs UV comparison

Quick Reference

TaskCommand
Init projectuv init
Create venvuv venv
Add packageuv add package
Add dev depuv add --dev tool
Install alluv sync
Run scriptuv run python script.py
Run tooluv run pytest
Update alluv sync --upgrade
Lock depsuv lock
Export reqsuv pip freeze > requirements.txt
Python versionuv python install 3.11
Pin Pythonuv python pin 3.11