据 AlphaMoat 统计,截至 2026-09,Python Venv 累计下载 1,728 次、获 0 个星标,在全部 5,078 个 AI 技能中排名第 4,628 位,在「开发编程」分类(577 个)中排名第 547 位。
| 平台 | 累计安装 | 累计下载 | 星标 | 评论 |
|---|---|---|---|---|
| ClawHub ↗ | 37 | 1,330 | - | - |
| SkillHub ↗ | 150 | 1,728 | - | — |
各平台的计数口径不同,统计时间不一致。
该技能根据 lock 文件、项目配置和现有环境推荐 uv、pip、conda、venv 等方案,并主张优先复用现有环境。创建环境、安装依赖或删除既有 .venv 都会改变工作区,应先确认具体范围;远程安装脚本需独立核实来源与内容。生成的建议是环境管理指引,执行前应检查项目依赖和团队规范。 选择管理工具前应核对已安装工具和项目规范。
资料发布于 2026-10-29
以下是根据技能文档生成的示例,不代表实际运行结果。
2026-09 起统计方法调整:同名技能按作者分别统计,并覆盖全部技能。图中虚线为调整前的月份,与之后的数据不直接比较,也不计算跨越调整的增长。
| 月份 | 累计下载 | 环比 | 星标 |
|---|---|---|---|
| 2026-09 | 1,728 | — | - |
| 2026-08 | 1,405 | +14.8% | - |
| 2026-07 | 1,224 | +20.4% | - |
| 2026-06 | 1,017 | +18.5% | - |
| 2026-05 | 858 | — | - |
| 2026-03 | 321 | — | - |
以下是作者发布的原始文件,按纯文本显示,本站未做修改或审核;其中的链接不可点击,命令请核实后再运行。抓取于 2026-10-23。
--- name: python-venv description: "Python environment management skill. Automatically detect project type and existing environments, recommend based on popularity. Minimize interruptions, only ask when necessary." --- # Python Environment Management Skill ## Core Principles 1. **Reuse Existing Environments** - Don't recreate, reuse existing virtual environments
2. **Use Project-Type Decision** - Auto-select based on lock files
3. **Recommend by Popularity** - uv > pip > conda > venv
4. **Minimize Interruption** - Only ask when necessary
---
## Tool Popularity Ranking
| Priority | Tool | Best For |
|----------|------|----------|
| 🥇 | uv | New projects, fast installs |
| 🥈 | pip | Compatibility first |
| 🥉 | conda | Data science, specific versions |
| 4 | venv | Built-in, no extra install |
| 5 | poetry | Existing poetry.lock |
| 6 | pipenv | Existing Pipfile (declining) |
---
## Decision Flow
```
┌─────────────────────────────────────┐
│ Detect project dependency files │
└─────────────────────────────────────┘
↓
┌─────────┴─────────┐
↓ ↓
Clear decision Unclear
↓ ↓
Use directly Detect existing env
↓
┌─────┴─────┐
↓ ↓
Has env No env
↓ ↓
Reuse Assess complexity
↓
┌─────────┴─────────┐
↓ ↓
Simple task Needs deps
↓ ↓
System Python Recommend uv/conda
```
---
## 1. Clear Decisions (Execute Directly, No Ask)
When these files are detected, use the corresponding tool directly:
| Detected File | Execute |
|--------------|---------|
| `uv.lock` exists | `uv sync` or `uv pip install -r requirements.txt` |
| `poetry.lock` exists | `poetry install` |
| `environment.yml` exists | `conda env create -f environment.yml` |
| `Pipfile.lock` exists | `pipenv install` |
---
## 2. Detect Existing Environments (Reuse First)
```bash
# Priority: uv venv > conda > venv
# 2.1 Detect uv virtual environment
ls -la .venv/ 2>/dev/null && uv pip list 2>/dev/null | head -3
# 2.2 Detect conda environment
conda info --envs 2>/dev/null | grep "*" || echo $CONDA_PREFIX
# 2.3 Detect standard venv
ls -la venv/ .venv/ env/ 2>/dev/null
# 2.4 If exists → Reuse (activate and run commands)
```
**Reuse Example:**
```
Detected existing .venv/ directory
→ Activate: source .venv/bin/activate
→ Run: uv pip install <package>
```
---
## 3. When Unclear (Assess Complexity)
| Scenario | Action |
|----------|--------|
| Stdlib only, no 3rd party | System Python (python3) |
| Simple pip install test | System Python (temp) |
| Has requirements.txt | Recommend uv > pip > venv |
| Has pyproject.toml | Recommend uv > pip |
| Multi-file project, needs isolation | Recommend uv |
---
## 4. When to Ask User (Only These Cases)
✅ **Ask:**
1. Empty project + first dependency install → Ask which tool
2. Both requirements.txt + pyproject.toml → Ask which to use
3. User explicitly wants different tool → e.g., "I want conda"
❌ **Don't Ask:**
- Has uv.lock but user didn't specify
- Has .venv/ directory
- Regular pip install task
---
## 5. Recommended Tool (No Clear Directive)
```
First: uv
├── uv venv (create)
├── uv pip install (install)
└── uv sync (sync)
Backup: pip
├── python3 -m venv .venv
└── pip install
Special: conda
├── conda create -n envname python=x.x
└── conda env create
```
---
## Detection Commands
```bash
# Check available tools
which uv
which conda
which pip
which python3
# Check project files
ls -la *.lock pyproject.toml requirements.txt environment.yml Pipfile 2>/dev/null
# Check existing environments
ls -la .venv/ venv/ env/ 2>/dev/null
conda info --envs 2>/dev/null
# Check current environment
echo $VIRTUAL_ENV
echo $CONDA_PREFIX
```
---
## Interaction Examples (Only When Needed)
```
🔍 Detection result:
- Project file: pyproject.toml
- Existing env: None
- Recommended: uv (fastest)
Running: uv pip install <package>
```
```
🔍 Detection result:
- Project file: requirements.txt
- Existing env: None
- Recommended: uv
Available options:
1) uv (recommended) - faster
2) pip - better compatibility
3) venv - uses stdlib
4) conda - if specific version needed
Enter option or press Enter to use recommended:
```
---
## Quick Command Reference
| Action | uv | pip | conda | venv |
|--------|-----|-----|-------|------|
| Create env | `uv venv` | - | `conda create` | `python3 -m venv` |
| Install pkg | `uv pip install` | `pip install` | `conda install` | `pip install` |
| Install deps | `uv sync` | `pip install -r` | `conda env create` | `pip install -r` |
| Activate | (auto) | (auto) | `conda activate` | `source venv/bin/activate` |
---
## Core Principle
**"Do more, ask less"** - Execute directly when you can determine, only ask when truly unclear.
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数据月份:2026-09 · 下载/星标/安装数聚合自公开技能注册库(ClawHub、SkillHub),按月更新。口径说明见数据方法。