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Agent Skill · 待分类

python-venv-manager(Python venv manager 测试)

用于辅助 Python 项目开发、测试、依赖管理和常见框架工作流。它适合让 Agent 阅读 Python 代码、定位测试问题、整理运行命令、生成脚本或分析数据处理逻辑。使用时需要确认项目虚拟环境、依赖版本和测试入口;涉及执行脚本、读写文件、访问数据库或调用外部 API 时,应先明确运行目录和输入输出范围,避免误改生产数据。

python-venv-manager 是待分类类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证为 MIT,第三方扫描有未通过项,按安装量在待分类类的 11,209 个 Skill 里排第 6,387。

总安装 461周安装 19GitHub Stars 26下载 150核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:python-venv-manager(Python venv manager 测试)
来源仓库:https://github.com/curiouslearner/devkit
仓库路径:skills/python-venv-manager
安装命令:
npx skills add https://github.com/curiouslearner/devkit --skill python-venv-manager
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/curiouslearner/devkit --skill python-venv-manager

这个 Skill 是做什么的

这个 Skill 的分类还没最终确定,用法以来源仓库的说明为准。

用于辅助 Python 项目开发、测试、依赖管理和常见框架工作流。适合让 Agent 管理虚拟环境、整理依赖版本或处理测试入口问题。使用时需确认项目虚拟环境、依赖版本和测试入口,避免误改生产数据。安装方式:通过 npx skills add 从指定 GitHub 仓库添加。

涉及执行脚本或访问数据库时,应先明确运行目录和输入输出范围。

来源仓库内路径:skills/python-venv-manager

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/curiouslearner/devkit --skill python-venv-mana…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

python-venv-manager 怎么安装?

在终端执行 npx skills add https://github.com/curiouslearner/devkit --skill python-venv-manager。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

python-venv-manager 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

python-venv-manager 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/curiouslearner/devkit --skill python-venv-manager;npx skills add curiouslearner/devkit --skill "python-venv-manager" 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

python-venv-manager 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

python-venv-manager 用的人多吗?

公开数据是累计安装 461 次,近一周安装 19 次,下载 150 次,GitHub 26 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

python-venv-manager 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理待分类类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

待分类类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
infsh-cli

infsh CLI · Codex、Claude

4,374,576382权限未标注未明确未收录
ai-video-generation

AI 视频生成 · Codex、Claude

4,313,376382调用外部服务未明确有提醒
lark-openapi-explorer

云雀 OpenAPI 浏览器 · Codex、Claude

2,064,1209,011需要联网未明确有提醒
lark-workflow-standup-report

Lark 工作流程站立报告 · Codex、Claude

2,041,6328,978需要联网未明确通过
use-my-browser

使用我的浏览器 · Codex、Claude

1,848,49140操作浏览器未明确未通过
python-venv-manager

Python venv manager 测试 · 本页

46126执行命令MIT未通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Python Virtual Environment Manager Skill

Python virtual environment management, dependency handling, and project setup automation.

Instructions

You are a Python environment and dependency expert. When invoked:

  1. Virtual Environment Management:

- Create and configure virtual environments - Manage Python versions with pyenv - Set up isolated development environments - Handle multiple Python versions per project - Configure environment activation scripts

  1. Dependency Management:

- Generate and manage requirements.txt - Use modern tools (pip-tools, poetry, pipenv) - Lock dependencies with hashes - Handle dev vs production dependencies - Resolve dependency conflicts

  1. Project Setup:

- Initialize new Python projects - Configure project structure - Set up testing frameworks - Configure linting and formatting - Create reproducible environments

  1. Troubleshooting:

- Fix import errors - Resolve version conflicts - Debug installation issues - Handle platform-specific dependencies - Clean corrupted environments

  1. Best Practices: Provide guidance on Python packaging, versioning, and environment isolation

Virtual Environment Tools Comparison

venv (Built-in)

# Pros: Built-in, no installation needed
# Cons: Basic features, manual workflow

# Create environment
python3 -m venv venv

# Activate (Linux/Mac)
source venv/bin/activate

# Activate (Windows)
venv\Scripts\activate

# Deactivate
deactivate

# Install dependencies
pip install -r requirements.txt

virtualenv (Enhanced)

# Pros: More features, faster than venv
# Cons: Requires installation

# Install
pip install virtualenv

# Create with specific Python version
virtualenv -p python3.11 venv

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

Poetry (Modern, Recommended)

# Pros: Dependency resolution, packaging, publishing
# Cons: Learning curve

# Install
curl -sSL https://install.python-poetry.org | python3 -

# Create new project
poetry new my-project

# Initialize existing project
poetry init

# Add dependencies
poetry add requests
poetry add --group dev pytest

# Install dependencies
poetry install

# Run commands in virtual environment
poetry run python script.py
poetry run pytest

# Activate shell
poetry shell

# Update dependencies
poetry update

# Show dependency tree
poetry show --tree

Pipenv

# Pros: Automatic venv, Pipfile format
# Cons: Slower than alternatives

# Install
pip install pipenv

# Install dependencies
pipenv install requests

# Install dev dependencies
pipenv install --dev pytest

# Activate environment
pipenv shell

# Run command
pipenv run python script.py

# Generate requirements.txt
pipenv requirements > requirements.txt

pyenv (Python Version Manager)

# Install multiple Python versions
# Manage Python versions per project

# Install
curl https://pyenv.run | bash

# Install Python version
pyenv install 3.11.5
pyenv install 3.12.0

# List available versions
pyenv install --list

# Set global version
pyenv global 3.11.5

# Set local version (per directory)
pyenv local 3.11.5

# List installed versions
pyenv versions

# Show current version
pyenv version

Usage Examples

@python-venv-manager
@python-venv-manager --setup-project
@python-venv-manager --create-venv
@python-venv-manager --poetry
@python-venv-manager --fix-dependencies
@python-venv-manager --migrate-to-poetry

Project Setup Workflows

Basic Project with venv

# Create project directory
mkdir my-project
cd my-project

# Create virtual environment
python3 -m venv venv

# Activate environment
source venv/bin/activate  # Linux/Mac
# or
venv\Scripts\activate  # Windows

# Upgrade pip
pip install --upgrade pip

# Install dependencies
pip install requests pytest black flake8

# Freeze dependencies
pip freeze > requirements.txt

# Create .gitignore
cat > .gitignore << EOF
venv/
__pycache__/
*.pyc
*.pyo
*.pyd
.Python
*.so
*.egg
*.egg-info/
dist/
build/
.pytest_cache/
.coverage
htmlcov/
.env
.venv
EOF

Modern Project with Poetry

# Create new project with structure
poetry new my-project
cd my-project

# Project structure created:
# my-project/
# ├── pyproject.toml
# ├── README.md
# ├── my_project/
# │   └── __init__.py
# └── tests/
#     └── __init__.py

# Add dependencies
poetry add requests httpx pydantic
poetry add --group dev pytest pytest-cov black flake8 mypy

# Install dependencies
poetry install

# Configure pyproject.toml
cat >> pyproject.toml << EOF

[tool.black]
line-length = 88
target-version = ['py311']

[tool.pytest.ini_options]
testpaths = ["tests"]
python_files = "test_*.py"

[tool.mypy]
python_version = "3.11"
warn_return_any = true
warn_unused_configs = true
EOF

Initialize Existing Project

# Navigate to project
cd existing-project

# Initialize poetry
poetry init

# Follow interactive prompts, then add dependencies
poetry add $(cat requirements.txt)

# Add dev dependencies
poetry add --group dev pytest black flake8

# Create virtual environment
poetry install

# Verify installation
poetry run python -c "import requests; print(requests.__version__)"

Dependency Management

requirements.txt Best Practices

# Basic requirements.txt
requests==2.31.0
django==4.2.7
celery==5.3.4

# With hashes for security (pip-tools)
pip-compile --generate-hashes requirements.in

# Separate files
requirements/
├── base.txt          # Common dependencies
├── development.txt   # Dev dependencies
├── production.txt    # Production dependencies
└── testing.txt       # Test dependencies

# development.txt
-r base.txt
pytest==7.4.3
black==23.11.0
flake8==6.1.0

# Install from specific file
pip install -r requirements/development.txt

Using pip-tools (Recommended)

# Install pip-tools
pip install pip-tools

# Create requirements.in
cat > requirements.in << EOF
django>=4.2,<5.0
requests
celery[redis]
EOF

# Compile to requirements.txt with pinned versions
pip-compile requirements.in

# Install from compiled requirements
pip-sync requirements.txt

# Update dependencies
pip-compile --upgrade requirements.in

# Compile with hashes for security
pip-compile --generate-hashes requirements.in

Poetry Dependency Management

# Add dependency with version constraint
poetry add "django>=4.2,<5.0"

# Add with specific version
poetry add django@4.2.7

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

# Add from local path
poetry add --editable ./local-package

# Add with extras
poetry add "celery[redis,auth]"

# Update specific package
poetry update django

# Update all packages
poetry update

# Show outdated packages
poetry show --outdated

# Remove package
poetry remove requests

# Export to requirements.txt
poetry export -f requirements.txt --output requirements.txt
poetry export --without-hashes -f requirements.txt --output requirements.txt

Development vs Production Dependencies

# Poetry approach
[tool.poetry.dependencies]
python = "^3.11"
django = "^4.2"
requests = "^2.31"

[tool.poetry.group.dev.dependencies]
pytest = "^7.4"
black = "^23.11"
flake8 = "^6.1"

# Install without dev dependencies
poetry install --without dev

# Install only specific groups
poetry install --only dev

# pip-tools approach
# requirements.in (production)
django>=4.2
requests

# requirements-dev.in (development)
-r requirements.in
pytest>=7.4
black>=23.11
flake8>=6.1

# Compile both
pip-compile requirements.in
pip-compile requirements-dev.in

Python Version Management

Using pyenv

# Install pyenv
curl https://pyenv.run | bash

# Add to shell configuration (.bashrc, .zshrc)
export PYENV_ROOT="$HOME/.pyenv"
export PATH="$PYENV_ROOT/bin:$PATH"
eval "$(pyenv init -)"
eval "$(pyenv virtualenv-init -)"

# Install Python versions
pyenv install 3.11.5
pyenv install 3.12.0

# Set global version
pyenv global 3.11.5

# Set local version (creates .python-version file)
pyenv local 3.11.5

# Create virtual environment with specific version
pyenv virtualenv 3.11.5 my-project-env

# Activate virtual environment
pyenv activate my-project-env

# Deactivate
pyenv deactivate

# List virtual environments
pyenv virtualenvs

# Delete virtual environment
pyenv uninstall my-project-env

Using pyenv with Poetry

# Set local Python version
pyenv local 3.11.5

# Initialize Poetry project
poetry init

# Poetry will use pyenv's Python version
poetry env use python

# Or specify version explicitly
poetry env use 3.11

# List Poetry environments
poetry env list

# Remove environment
poetry env remove python3.11

# Show environment info
poetry env info

Project Structure Best Practices

Small Project

my-project/
├── .gitignore
├── README.md
├── requirements.txt
├── setup.py  (optional)
├── my_module.py
└── tests/
    ├── __init__.py
    └── test_my_module.py

Medium Project

my-project/
├── .gitignore
├── README.md
├── pyproject.toml
├── setup.py
├── requirements/
│   ├── base.txt
│   ├── development.txt
│   └── production.txt
├── src/
│   └── my_package/
│       ├── __init__.py
│       ├── core.py
│       ├── utils.py
│       └── models.py
├── tests/
│   ├── __init__.py
│   ├── conftest.py
│   └── test_core.py
└── docs/
    └── index.md

Large Project with Poetry

my-project/
├── .gitignore
├── .python-version
├── README.md
├── pyproject.toml
├── poetry.lock
├── src/
│   └── my_package/
│       ├── __init__.py
│       ├── core/
│       │   ├── __init__.py
│       │   └── engine.py
│       ├── api/
│       │   ├── __init__.py
│       │   └── routes.py
│       └── utils/
│           ├── __init__.py
│           └── helpers.py
├── tests/
│   ├── __init__.py
│   ├── conftest.py
│   ├── unit/
│   │   └── test_core.py
│   └── integration/
│       └── test_api.py
├── docs/
│   ├── conf.py
│   └── index.rst
└── scripts/
    └── setup_dev.sh

Common Issues & Solutions

Issue: ModuleNotFoundError

# Check if virtual environment is activated
which python  # Should point to venv/bin/python

# Verify package is installed
pip list | grep package-name

# Reinstall package
pip install --force-reinstall package-name

# Check Python path
python -c "import sys; print('\n'.join(sys.path))"

# Fix: Activate virtual environment
source venv/bin/activate

# Fix: Install in editable mode for local development
pip install -e .

Issue: Dependency Conflicts

# Check for conflicts
pip check

# Show dependency tree
pip install pipdeptree
pipdeptree

# Using Poetry (better conflict resolution)
poetry add package-name
# Poetry will resolve conflicts automatically

# Force specific version
pip install "package==1.2.3"

# Use pip-tools to resolve
pip-compile --resolver=backtracking requirements.in

Issue: Multiple Python Versions Confusion

# Check current Python version
python --version
which python

# Use specific version explicitly
python3.11 -m venv venv

# With pyenv
pyenv versions  # List installed versions
pyenv which python  # Show current python path

# Set specific version for project
pyenv local 3.11.5

Issue: Corrupted Virtual Environment

# Delete and recreate
rm -rf venv/
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

# With Poetry
poetry env remove python3.11
poetry install

Issue: SSL Certificate Errors

# Temporary workaround (NOT for production)
pip install --trusted-host pypi.org --trusted-host pypi.python.org package-name

# Better solution: Update certificates
pip install --upgrade certifi

# macOS specific
/Applications/Python\ 3.11/Install\ Certificates.command

Issue: Permission Denied

# Don't use sudo with pip in virtual environment!
# Recreate venv with proper permissions

# Fix ownership
chown -R $USER:$USER venv/

# Use user install only if not in venv
pip install --user package-name

Environment Variables and Configuration

.env Files

# Install python-decouple or python-dotenv
poetry add python-dotenv

# Create .env file
cat > .env << EOF
DEBUG=True
SECRET_KEY=your-secret-key
DATABASE_URL=postgresql://user:pass@localhost/db
REDIS_URL=redis://localhost:6379
EOF

# Load in Python
from dotenv import load_dotenv
import os

load_dotenv()

DEBUG = os.getenv('DEBUG', 'False') == 'True'
SECRET_KEY = os.getenv('SECRET_KEY')
DATABASE_URL = os.getenv('DATABASE_URL')

Environment-Specific Settings

# config.py
import os
from pathlib import Path

class Config:
    BASE_DIR = Path(__file__).parent
    SECRET_KEY = os.getenv('SECRET_KEY')
    DEBUG = False
    TESTING = False

class DevelopmentConfig(Config):
    DEBUG = True
    DATABASE_URL = 'sqlite:///dev.db'

class ProductionConfig(Config):
    DATABASE_URL = os.getenv('DATABASE_URL')

class TestingConfig(Config):
    TESTING = True
    DATABASE_URL = 'sqlite:///test.db'

# Select config based on environment
config = {
    'development': DevelopmentConfig,
    'production': ProductionConfig,
    'testing': TestingConfig,
    'default': DevelopmentConfig
}

def get_config():
    env = os.getenv('FLASK_ENV', 'default')
    return config[env]()

Testing Setup

pytest Configuration

# Install pytest
poetry add --group dev pytest pytest-cov pytest-mock

# pyproject.toml
[tool.pytest.ini_options]
testpaths = ["tests"]
python_files = "test_*.py"
python_classes = "Test*"
python_functions = "test_*"
addopts = "-v --tb=short --strict-markers"

# Run tests
poetry run pytest

# With coverage
poetry run pytest --cov=src --cov-report=html

# Run specific test
poetry run pytest tests/test_core.py::test_function_name

Code Quality Tools

Formatting and Linting

# Install tools
poetry add --group dev black isort flake8 mypy pylint

# pyproject.toml configuration
[tool.black]
line-length = 88
target-version = ['py311']
include = '\.pyi?$'
extend-exclude = '''
/(
  # directories
  \.eggs
  | \.git
  | \.venv
  | build
  | dist
)/
'''

[tool.isort]
profile = "black"
line_length = 88

[tool.mypy]
python_version = "3.11"
warn_return_any = true
warn_unused_configs = true
disallow_untyped_defs = true

# Run formatting
poetry run black .
poetry run isort .

# Run linting
poetry run flake8 src/
poetry run mypy src/
poetry run pylint src/

Pre-commit Hooks

# Install pre-commit
poetry add --group dev pre-commit

# Create .pre-commit-config.yaml
cat > .pre-commit-config.yaml << EOF
repos:
  - repo: https://github.com/psf/black
    rev: 23.11.0
    hooks:
      - id: black
        language_version: python3.11

  - repo: https://github.com/pycqa/isort
    rev: 5.12.0
    hooks:
      - id: isort
        args: ["--profile", "black"]

  - repo: https://github.com/pycqa/flake8
    rev: 6.1.0
    hooks:
      - id: flake8

  - repo: https://github.com/pre-commit/mirrors-mypy
    rev: v1.7.0
    hooks:
      - id: mypy
        additional_dependencies: [types-requests]
EOF

# Install hooks
poetry run pre-commit install

# Run manually
poetry run pre-commit run --all-files

Migration Scripts

Migrate from requirements.txt to Poetry

# Script: migrate_to_poetry.sh
#!/bin/bash

echo "Migrating to Poetry..."

# Backup current setup
cp requirements.txt requirements.txt.backup

# Initialize Poetry
poetry init --no-interaction

# Add dependencies from requirements.txt
cat requirements.txt | grep -v "^#" | grep -v "^$" | while read package; do
    # Remove version specifiers for initial add
    pkg_name=$(echo $package | cut -d'=' -f1 | cut -d'>' -f1 | cut -d'<' -f1)
    poetry add "$pkg_name"
done

# Install dependencies
poetry install

echo "Migration complete. Check pyproject.toml"
echo "Original requirements.txt backed up to requirements.txt.backup"

Convert between formats

# Poetry to requirements.txt
poetry export -f requirements.txt --output requirements.txt --without-hashes

# requirements.txt to Poetry
cat requirements.txt | xargs poetry add

# Pipenv to requirements.txt
pipenv requirements > requirements.txt

# Pipenv to Poetry
poetry add $(pipenv requirements | sed 's/==/=/g')

Docker Integration

Dockerfile with Virtual Environment

FROM python:3.11-slim

WORKDIR /app

# Install system dependencies
RUN apt-get update && apt-get install -y \
    gcc \
    && rm -rf /var/lib/apt/lists/*

# Copy dependency files
COPY requirements.txt .

# Create virtual environment and install dependencies
RUN python -m venv /opt/venv
ENV PATH="/opt/venv/bin:$PATH"
RUN pip install --no-cache-dir -r requirements.txt

# Copy application
COPY . .

# Run as non-root
RUN useradd -m -u 1001 appuser && \
    chown -R appuser:appuser /app
USER appuser

CMD ["python", "app.py"]

Dockerfile with Poetry

FROM python:3.11-slim as builder

WORKDIR /app

# Install Poetry
RUN pip install poetry==1.7.0

# Configure Poetry
ENV POETRY_NO_INTERACTION=1 \
    POETRY_VIRTUALENVS_IN_PROJECT=1 \
    POETRY_VIRTUALENVS_CREATE=1 \
    POETRY_CACHE_DIR=/tmp/poetry_cache

# Copy dependency files
COPY pyproject.toml poetry.lock ./

# Install dependencies
RUN poetry install --without dev --no-root && rm -rf $POETRY_CACHE_DIR

# Runtime stage
FROM python:3.11-slim as runtime

WORKDIR /app

# Copy virtual environment from builder
ENV VIRTUAL_ENV=/app/.venv \
    PATH="/app/.venv/bin:$PATH"
COPY --from=builder /app/.venv ${VIRTUAL_ENV}

# Copy application
COPY . .

# Run as non-root
RUN useradd -m -u 1001 appuser && \
    chown -R appuser:appuser /app
USER appuser

CMD ["python", "app.py"]

Best Practices Summary

Virtual Environment

  • Always use virtual environments (never install globally)
  • One virtual environment per project
  • Keep venv/ out of version control (.gitignore)
  • Document Python version requirements (.python-version)
  • Use pyenv for managing multiple Python versions

Dependency Management

  • Pin exact versions in production (no ~, ^)
  • Use pip-tools or Poetry for dependency resolution
  • Separate dev and production dependencies
  • Use lock files (poetry.lock, requirements.txt with hashes)
  • Regularly update dependencies for security
  • Document why specific versions are pinned

Project Structure

  • Use src/ layout for packages
  • Keep tests separate from source
  • Include comprehensive.gitignore
  • Add README.md with setup instructions
  • Use pyproject.toml for modern projects

Security

  • Never commit.env files
  • Use python-dotenv for environment variables
  • Scan dependencies with pip-audit or safety
  • Use hashes in requirements.txt
  • Keep dependencies minimal
  • Update regularly for security patches

Development Workflow

  • Use pre-commit hooks for code quality
  • Configure formatters (black, isort)
  • Use type hints and mypy
  • Write tests with pytest
  • Document setup steps in README

Quick Reference Commands

# venv basics
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
pip freeze > requirements.txt

# Poetry basics
poetry new project
poetry init
poetry add package
poetry install
poetry shell
poetry run python script.py

# pyenv basics
pyenv install 3.11.5
pyenv local 3.11.5
pyenv virtualenv 3.11.5 myenv

# pip-tools basics
pip-compile requirements.in
pip-sync requirements.txt
pip-compile --upgrade

# Common tasks
pip list --outdated
pip check
poetry show --outdated
poetry update

Notes

  • Prefer Poetry or pip-tools over manual requirements.txt management
  • Use pyenv to manage multiple Python versions
  • Always activate virtual environment before installing packages
  • Keep dependencies documented and up-to-date
  • Use lock files for reproducible builds
  • Test dependency updates in isolated environment first
  • Configure proper.gitignore to exclude virtual environments
  • Use type hints and static analysis tools (mypy)
  • Set up CI/CD to verify dependency installation
  • Regular security audits of dependencies

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Gemini CLI

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7.68%
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Cursor

3.39%
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安全审计

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未通过

Socket

通过

Snyk

可疑

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/curiouslearner/devkit --skill python-venv-manager;npx skills add curiouslearner/devkit --skill "python-venv-manager" 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

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